@article {pmid40238826,
year = {2025},
author = {Lee, J and Kim, B},
title = {Zero inflated high dimensional compositional data with DeepInsight.},
journal = {PloS one},
volume = {20},
number = {4},
pages = {e0320832},
doi = {10.1371/journal.pone.0320832},
pmid = {40238826},
issn = {1932-6203},
mesh = {Humans ; High-Throughput Nucleotide Sequencing/methods ; *Microbiota/genetics ; Neural Networks, Computer ; Inflammatory Bowel Diseases/microbiology ; Child ; },
abstract = {Through the Human Microbiome Project, research on human-associated microbiomes has been conducted in various fields. New sequencing techniques such as Next Generation Sequencing (NGS) and High-Throughput Sequencing (HTS) have enabled the inclusion of a wide range of features of the microbiome. These advancements have also contributed to the development of numerical proxies like Operational Taxonomic Units (OTUs) and Amplicon Sequence Variants (ASVs). Studies involving such microbiome data often encounter zero-inflated and high-dimensional problems. Based on the need to address these two issues and the recent emphasis on compositional interpretation of microbiome data, we conducted our research. To solve the zero-inflated problem in compositional microbiome data, we transformed the data onto the surface of the hypersphere using a square root transformation. Then, to solve the high-dimensional problem, we modified DeepInsight, an image-generating method using Convolutional Neural Networks (CNNs), to fit the hypersphere space. Furthermore, to resolve the common issue of distinguishing between true zero values and fake zero values in zero-inflated images, we added a small value to the true zero values. We validated our approach using pediatric inflammatory bowel disease (IBD) fecal sample data and achieved an area under the curve (AUC) value of 0.847, which is higher than the previous study's result of 0.83.},
}

Humans
High-Throughput Nucleotide Sequencing/methods
*Microbiota/genetics
Neural Networks, Computer
Inflammatory Bowel Diseases/microbiology
Child

@article {pmid40144639,
year = {2025},
author = {Sabu, P and Pathak, HB and Nissen, E and Chalise, P and Koestler, DC and Godwin, AK and Umar, S and Spoozak, L and Jewell, A and Mahoney, DE},
title = {Translational Implications of The Gut Microbiome in Women with A Benign or Malignant Pelvic Mass.},
journal = {Annals of obstetrics and gynecology},
volume = {8},
number = {1},
pages = {},
pmid = {40144639},
issn = {2641-6522},
abstract = {OBJECTIVE: The role of the gut microbiome in non-gastrointestinal cancers has generated growing interest in the field of gynecologic oncology. Our objective was to characterize the gut microbiome in women with a pelvic mass suspicious for ovarian cancer. We hypothesized that (1) women with a pelvic mass would have reduced gut microbiota bacterial diversity compared to healthy controls and (2) gut microbial diversity would differ between benign disease compared to ovarian cancer.

METHODS: In this case-control observational study, patients who presented with a suspicious pelvic mass were recruited from university affiliated gynecologic oncology clinics for fecal biospecimen donation. Fecal samples that were obtained from patients underwent 16S rRNA gene sequencing for microbial evaluation and statistical analysis. We used the Human Microbiome Project (HMP) Data Portal to compare gut microbiota profiles for our study to that of healthy female controls.

RESULTS: Fifteen patients with a pelvic mass were included ages 24-75 years. When comparing the gut microbiomes of these patients to 82 healthy females from the HMP Dataset, those with a pelvic mass had a significantly lower microbiota gut bacterial diversity. On the final pathology, 8 of the 15 patients with a suspicious pelvic mass had ovarian cancer and 7 had benign disease. Although not statistically significant, the alpha diversity was marginally reduced in patients with ovarian cancer compared to those with benign disease.

CONCLUSION: These findings underscore the necessity for validation in larger patient cohorts for clinical translation as a potential tool for disease diagnostics and disease prediction in diverse populations.},
}

@article {pmid40105993,
year = {2025},
author = {Ge, Y and Yang, H and Fu, Y and Zhou, J and Cheng, Z and Fan, X and Yu, Y},
title = {A Mendelian randomization study to reveal gut-disc axis: causal associations between gut microbiota with intervertebral disc diseases.},
journal = {European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society},
volume = {},
number = {},
pages = {},
pmid = {40105993},
issn = {1432-0932},
support = {No.cstc2021jcyj-msxmX0853//Natural Science Foundation of Chongqing, China/ ; No.2024ZYZD006//Chongqing Traditional Chinese Medicine scientific research project (Joint project of Chongqing Health Commission and Science and Technology Bureau)/ ; Grant No.KJQN202215120//The Science and Technology Research Program of Chongqing Municipal Education Commission/ ; },
abstract = {PURPOSE: Emerging evidence suggests a link between gut microbiota and intervertebral disc diseases (IDDs); however, the causal relationships remain unclear. This study aimed to evaluate the causal effects of gut microbiota on the risk of cervical disc disorders (CDD), other intervertebral disc disorders (OIDD), pyogenic intervertebral disc infections, and discitis, shedding light on the potential "gut-disc axis".

METHODS: Genetic variation data for 202 gut microbiota taxa were obtained from the Dutch Microbiome Project, and disease outcome data were sourced from the FinnGen consortium. A Mendelian Randomization (MR) approach was employed to assess causal relationships, using genetic variants as instrumental variables. Sensitivity analyses, including tests for pleiotropy, heterogeneity, and reverse causation, ensured robust findings.

RESULTS: The study identified 20 gut microbial taxa with significant associations to IDDs. Notably, taxa within the Erysipelotrichaceae family showed consistent protective effects against OIDD after Bonferroni correction (P < 0.05). Associations between several species and specific diseases, such as Alistipes senegalensis with CDD and Ruminococcus lactaris with discitis, were also observed. Sensitivity analyses confirmed no evidence of confounding or reverse causation.

CONCLUSION: This study provides evidence of causal relationships between specific gut microbiota and IDDs, supporting the existence of a "gut-disc axis." The findings suggest that microbial dysbiosis may influence spinal health through systemic inflammation and immune regulation. These insights open new possibilities for microbiota-targeted interventions, such as probiotics or dietary modifications, to prevent or manage IDDs. However, further research is required to validate these therapeutic strategies.},
}

@article {pmid40081329,
year = {2025},
author = {Zeng, S and Wang, H and Mu, D and Wang, S},
title = {The African gut microbiome: A window into the hidden human microbial diversity.},
journal = {Cell host & microbe},
volume = {33},
number = {3},
pages = {320-322},
doi = {10.1016/j.chom.2025.02.015},
pmid = {40081329},
issn = {1934-6069},
mesh = {Humans ; *Gastrointestinal Microbiome ; *HIV Infections/microbiology/virology ; Africa ; Bacteria/classification/genetics/isolation & purification ; Biodiversity ; },
abstract = {Studies on industrialized populations have uncovered gut microbiome diversity and its disease associations. However, non-industrialized populations remain underrepresented. In a recent paper, Maghini et al. present findings from the AWI-Gen 2 Microbiome Project, substantially expanding our knowledge of the African gut bacterial and viral diversity and its linkage with HIV infection.},
}

Humans
*Gastrointestinal Microbiome
*HIV Infections/microbiology/virology
Africa
Bacteria/classification/genetics/isolation & purification
Biodiversity

@article {pmid40027484,
year = {2025},
author = {Liu, L and Zhou, Q and Xu, T and Deng, Q and Sun, Y and Fu, J and Chen, M and Chen, X and Ma, Z and Dong, Q and Ma, B and Jiao, Y and Zhou, Y and Wu, T and Zou, H and Shi, J and Wang, Y and Sheng, Y and Tang, L and Zheng, C and Wu, W and Ma, W and Sun, W and Hu, S and Zhou, H and He, Y and Kong, X and Chen, L},
title = {Non-differential gut microbes contribute to hypertension and its severity through co-abundances: A multi-regional prospective cohort study.},
journal = {iMeta},
volume = {4},
number = {1},
pages = {e268},
pmid = {40027484},
issn = {2770-596X},
abstract = {Microbial dysbiosis, characterized by an imbalanced microbial community structure and function, has been linked to hypertension. While prior research has primarily focused on differential abundances, our study highlights the role of non-differential microbes in hypertension. We propose that non-differential microbes contribute to hypertension through their ecological interactions, as defined by co-abundances (pairs of microbes exhibiting correlated abundance patterns). Using gut microbiome data from the Guangdong Gut Microbiome Project, which includes 2355 hypertensive and 4644 non-hypertensive participants across 14 regions, we identified replicable hypertension-related microbial interactions. Notably, most co-abundances involved non-differential microbes, which were found to correlate with both hypertension severity and hypertension-related microbial metabolic pathways. These findings emphasize the importance of microbial interactions in hypertension pathogenesis and propose a novel perspective for microbiome-based therapeutic strategies.},
}

@article {pmid39984469,
year = {2025},
author = {Davison, S and Mascellani Bergo, A and Ward, Z and Sackett, A and Strykova, A and Jaimes, JD and Travis, D and Clayton, JB and Murphy, HW and Danforth, MD and Smith, BK and Blekhman, R and Fuh, T and Niatou Singa, FS and Havlik, J and Petrzelkova, K and Gomez, A},
title = {Cardiometabolic disease risk in gorillas is associated with altered gut microbial metabolism.},
journal = {NPJ biofilms and microbiomes},
volume = {11},
number = {1},
pages = {33},
pmid = {39984469},
issn = {2055-5008},
support = {LM2023064//Ministerstvo Školství, Mládeže a Tělovýchovy (Ministry of Education, Youth and Sports)/ ; LTAUSA18209//Ministerstvo Školství, Mládeže a Tělovýchovy (Ministry of Education, Youth and Sports)/ ; },
mesh = {Animals ; *Gastrointestinal Microbiome ; *Gorilla gorilla/microbiology ; *Feces/microbiology ; *Animals, Zoo/microbiology ; *Cardiovascular Diseases/microbiology/etiology ; Bacteria/classification/metabolism/isolation & purification/genetics ; Africa, Central ; United States/epidemiology ; Ape Diseases/microbiology/etiology ; Male ; Female ; Diet ; },
abstract = {Cardiometabolic disease is the leading cause of death in zoo apes; yet its etiology remains unknown. Here, we investigated compositional and functional microbial markers in fecal samples from 57 gorillas across U.S. zoos, 20 of which are diagnosed with cardiovascular disease, in contrast with 17 individuals from European zoos and 19 wild gorillas from Central Africa. Results show that zoo-housed gorillas in the U.S. exhibit the most diverse gut microbiomes and markers of increased protein and carbohydrate fermentation, at the expense of microbial metabolic traits associated with plant cell-wall degradation. Machine learning models identified unique microbial traits in U.S. gorillas with cardiometabolic distress; including reduced metabolism of sulfur-containing amino acids and hexoses, increased abundance of potential enteric pathogens, and low fecal butyrate and propionate production. These findings show that cardiometabolic disease in gorillas is potentially associated with altered gut microbial function, influenced by zoo-specific diets and environments.},
}

Animals
*Gastrointestinal Microbiome
*Gorilla gorilla/microbiology
*Feces/microbiology
*Animals, Zoo/microbiology
*Cardiovascular Diseases/microbiology/etiology
Bacteria/classification/metabolism/isolation & purification/genetics
Africa, Central
United States/epidemiology
Ape Diseases/microbiology/etiology
Male
Female
Diet

@article {pmid39969325,
year = {2024},
author = {Li, W and Li, A},
title = {Exploring the causal relationship between gut microbiota and atopic dermatitis: A Mendelian randomization study.},
journal = {Medicine},
volume = {103},
number = {52},
pages = {e40193},
doi = {10.1097/MD.0000000000040193},
pmid = {39969325},
issn = {1536-5964},
mesh = {*Dermatitis, Atopic/microbiology/genetics ; *Mendelian Randomization Analysis ; *Gastrointestinal Microbiome/genetics ; Humans ; *Genome-Wide Association Study ; },
abstract = {Accumulating evidence indicates a correlation between gut microbiota (GM) and atopic dermatitis (AD). Nevertheless, the causal relationship between specific pathogenic bacterial taxa and AD remains uncertain. This investigation utilized a two-sample Mendelian randomization (MR) analysis to assess the causal association between GM and AD, identifying the most influential GM taxa. An MR study was conducted utilizing summary statistics derived from genome-wide association studies encompassing 207 GM taxa and their association with AD risk. The genome-wide association studies summary statistics for 207 GM taxa (from phylum to species level) were generated by the Dutch Microbiome Project. The genetic variants (P < 1 × 10-5) correlated with GM (n = 7738) were identified from this investigation. Additionally, 4 supplementary MR approaches, simple mode, MR-Egger, weighted mode, and weighted median, supported the inverse-variance weighted approach. Furthermore, sensitivity analyses were executed using leave-one-out analysis, Cochran Q test, MR-Egger intercept test, MR pleiotropy residual sum and outlier global test, and MR Steiger test. The MR analysis identified 17 distinct bacterial taxa involving 2 orders, 4 families, 5 genera, and 6 species. The inverse-variance weighted method demonstrated that 6 bacterial taxa were positively associated with AD. These taxa included the order Pasteurellales, family Burkholderiales noname, family Pasteurellaceae, genus Burkholderiales noname, species Burkholderiales bacterium_1_1_47, and species Desulfovibrio piger. Eleven bacterial taxa were negatively associated with AD, comprising the order Actinomycetales, family Micrococcaceae, family Oscillospiraceae, genus Rothia, genus Collinsella, genus Oscillibacter, genus Pseudoflavonifractor, species Oscillibacter_unclassified, species Roseburia hominis, species R mucilaginosa, and species Parabacteroides merdae. Moreover, the MR-Egger intercept test and MR pleiotropy residual sum and outlier global test validated that the MR analysis remained unaffected by horizontal pleiotropy (P > .05). Furthermore, the leave-one-out analysis contributed to validating the robustness of the outcomes. Finally, an MR Steiger directionality test confirmed the assessment of potential causal direction (P < .001). This investigation identified specific intestinal flora causally associated with AD risk, offering novel insights for future investigations and innovative avenues for AD diagnosis, therapeutic intervention, and prognostic assessment.},
}

*Dermatitis, Atopic/microbiology/genetics
*Mendelian Randomization Analysis
*Gastrointestinal Microbiome/genetics
Humans
*Genome-Wide Association Study

@article {pmid39950509,
year = {2025},
author = {Li, M and Wang, L and Peng, Z and Jiang, L and Yan, Y and Xia, Y and Wang, Y and Guo, L and Miao, J and Bian, Y},
title = {Causal Associations of Gut Microbiota Species With Lymphoma: A Two-Sample Mendelian Randomization Study.},
journal = {Hematological oncology},
volume = {43},
number = {2},
pages = {e70046},
doi = {10.1002/hon.70046},
pmid = {39950509},
issn = {1099-1069},
support = {82104671//National Natural Science Foundation of China/ ; },
mesh = {Humans ; *Mendelian Randomization Analysis ; *Gastrointestinal Microbiome ; Genome-Wide Association Study ; Lymphoma/epidemiology ; },
abstract = {This study aims to focus on GM at species level, exploring the causal associations with different kinds of lymphoma to provide some information on potential intervention directions in lymphoma. Data of GM taxa were extracted from the genome-wide association study conducted by the MiBioGen and Dutch Microbiome Project (DMP), and those of lymphomas were obtained from the FinnGen consortium. Inverse variance weighted (IVW) method and Bonferroni multiple correction were utilized to assess the causal associations of GM species with different kinds of lymphoma. The effect size was expressed by odds ratios (ORs) with 95% confidence intervals (CIs). Reverse causal association analysis has also been performed. Additionally, scatter plots and leave-one-out test were conducted for sensitivity analysis. After correction, the IVW estimates suggested that elevated relative abundance of species Faecalibacterium_prausnitzii had a negatively causal association with increased odds of Hodgkin's lymphoma (HL) (OR = 0.584, 95% CI: 0.516-0.662). Relative abundance of species Gordonibacter_pamelaeae, Holdemania_filiformis, Sutterella_wadsworthensis and Coprococcus_sp_ART55_1 was negatively associated with follicular lymphoma (FL) odds, whereas that of species Bifidobacterium_catenulatum and Coprococcus_comes were positively associated with FL odds (all p < 0.05). Relative abundance of species Akkermansia_muciniphila and Coprococcus_sp_ART55_1 had a negatively causal association with non-follicular lymphoma (NFL) odds, respectively, while that of Bacteroides_uniformis had a positive one (all p < 0.05). Relative abundance of species Flavonifractor_plautii was negatively linked to diffuse large B-cell lymphoma (DLBCL) risk (OR = 0.471, 95% CI: 0.344-0.645). Relative abundance of species Eggerthella_unclassified was positively associated with T/NK cell lymphoma (TNK) risk while that of Ruminococcus_lactaris was negatively associated with TNK risk (all p < 0.05). Elevated relative abundance of Parabacteroides_unclassified was associated with higher risk of non-Hodgkin's lymphoma (NHL) (OR = 1.955, 95% CI: 1.654-2.312). The relative abundance of species Holdemania_filiformis was negatively associated with mantle cell lymphoma (MCL) risk (OR = 0.637, 95% CI: 0.544-0.746). The relative abundance of species Rothia_mucilaginosa and Lachnospiraceae_bacterium_3_1_46FAA had positively causal association with marginal zone lymphoma (MZL) risk, while that of species Alistipes_senegalensis had a negative one (all p < 0.05). This study identified 16 GM species that have potential causal associations with different kinds of lymphoma, which provided some new idea for further exploration on prevention and treatment targets in lymphoma.},
}

Humans
*Mendelian Randomization Analysis
*Gastrointestinal Microbiome
Genome-Wide Association Study
Lymphoma/epidemiology

@article {pmid39948579,
year = {2025},
author = {Guo, J and Wang, C and Li, H and Ding, C},
title = {Exploring the causal associations of the gut microbiota and plasma metabolites with ovarian cancer: an approach of mendelian randomization analysis combined with network pharmacology and molecular docking.},
journal = {Journal of ovarian research},
volume = {18},
number = {1},
pages = {27},
pmid = {39948579},
issn = {1757-2215},
support = {82174135//National Natural Science Foundation of China/ ; YC-2023-0610//Specialized Discipline of Chinese Medicine and Liver Disease in Summit Plateau, Pudong New Area/ ; },
abstract = {BACKGROUND: While increasing evidence suggests that alterations in the gut microbiota and metabolites are associated with ovarian cancer (OC) risk, whether these associations imply causation remains to be identified.

METHODS: We conducted a two-sample Mendelian randomization (MR) study utilizing a large-scale genome-wide association study (GWAS) to explore the causal effects of the gut microbiota of 196/220 individuals and 1,400 plasma metabolites on OC and epithelial ovarian cancer (EOC) subtypes. Data on the gut microbiota were obtained from the MiBioGen consortium of 18,340 subjects and the Dutch Microbiome Project of 7,738 volunteers. Data on plasma metabolites were derived from a GWAS of plasma metabolites in 8,299 participants. Ovarian cancer (n = 25,509) and EOC subtypes were obtained from the Ovarian Cancer Association Consortium (OCAC). Metabolites and associated targets were analyzed via network pharmacology and molecular docking.

RESULTS: At the genus and species levels, we identified seven risk factors for the gut microbiota: the genus Dialister (P = 0.024), genus Ruminiclostridium5 (P = 0.0004), genus Phascolarctobacterium (P = 0.0217), species Bacteroides massiliensis (P = 0.011), species Phascolarctobacterium succinatutens (P = 0.0212), species Paraprevotella clara (P = 0.0247) and species Bacteroides dorei (P = 0.0054). In addition, five gut microbes at the genus and species levels were found to be protective: genus Family XIII AD3011 group (P = 0.006), genus Butyrivibrio (P = 0.0095), genus Oscillibacter (P = 0.0206), species Roseburia hominis (P = 0.0241), and species Bifidobacterium bifidum (P = 0.0224). For plasma metabolites, we revealed five positive and four negative correlations with OC. Among these, caffeic acid and caffeine metabolites and sphingomyelin and ceramide metabolites were identified as risk factors, whereas phenylalanine metabolites, butyric acid metabolites, and some lipid metabolites were recognized as protective factors. A series of sensitivity analyses revealed no abnormalities, including pleiotropy and heterogeneity analyses.

CONCLUSION: Our MR analysis demonstrated that the gut microbiota and metabolites are causally associated with OC, which has significant potential for the early detection and diagnosis of OC and EOC subtypes, providing valuable insights into this area of research.},
}

@article {pmid39940948,
year = {2025},
author = {Rastegari, F and Driscoll, M and Riordan, JD and Nadeau, JH and Johnson, JS and Weinstock, GM},
title = {Comparison of Lysis and Amplification Methodologies for Optimal 16S rRNA Gene Profiling for Human and Mouse Microbiome Studies.},
journal = {International journal of molecular sciences},
volume = {26},
number = {3},
pages = {},
doi = {10.3390/ijms26031180},
pmid = {39940948},
issn = {1422-0067},
support = {HG01244/GF/NIH HHS/United States ; },
mesh = {*RNA, Ribosomal, 16S/genetics ; Humans ; Animals ; Mice ; *Microbiota/genetics ; *Feces/microbiology ; Bacteria/genetics/classification ; Polymerase Chain Reaction/methods ; DNA, Bacterial/genetics ; Sequence Analysis, DNA/methods ; },
abstract = {When conducting sequence-based analysis of microbiome samples, it is important to accurately represent the bacterial communities present. The aim of this study was to compare two commercially available DNA isolation and PCR amplification approaches to determine their impact on the taxonomic composition of microbiome samples following 16S rRNA gene sequencing. A well-established 16S rRNA gene profiling approach, which was widely used in the Human Microbiome Project (HMP), was compared with a novel alkaline degenerative technique that utilizes alkaline cell lysis in combination with a degenerate pool of primers for nucleic acid extraction and PCR amplification. When comparing these different approaches for the microbiome profiling of human and mouse fecal samples, we found that the alkaline-based method was able to detect greater taxonomic diversity. An in silico analysis of predicted primer binding against a curated 16S rRNA gene reference database further suggested that this novel approach had the potential to reduce population bias found with traditional methods, thereby offering opportunities for improved microbial community profiling.},
}

*RNA, Ribosomal, 16S/genetics
Humans
Animals
Mice
*Microbiota/genetics
*Feces/microbiology
Bacteria/genetics/classification
Polymerase Chain Reaction/methods
DNA, Bacterial/genetics
Sequence Analysis, DNA/methods

@article {pmid39913178,
year = {2025},
author = {Yao, Y and Chen, J and Cao, H and Lu, Z and Shen, H and Ji, J and Jiao, Q},
title = {Causal Effect Between Gut Microbiota, Gut Bacterial Pathway, and Chronic Spontaneous Urticaria: A Large-Scale Bidirectional Mendelian Randomization Analysis.},
journal = {Journal of investigational allergology & clinical immunology},
volume = {},
number = {},
pages = {0},
doi = {10.18176/jiaci.1054},
pmid = {39913178},
issn = {1018-9068},
abstract = {BACKGROUND: To analyze causality between gut microbiota and chronic spontaneous urticaria (CSU) and to investigate the mediating effect of metabolic pathways.

METHODS: We extracted genome-wide association study summary statistics for 211 microbiota taxa from the MiBioGen consortium (N=18 340), 205 microbiota metabolic pathways from the Dutch Microbiome Project (N=7738), and CSU from the FinnGen genomics initiative (N=450). Bidirectional Mendelian randomization (MR) was performed to detect genetic causality between gut microbiota, gut bacterial pathways, and CSU. Sensitivity analyses were performed to validate the robustness of the results. Mediation MR investigated mediators in the association between gut microbiota and CSU.

RESULTS: MR analysis suggested that the family Peptococcaceae and its child taxon, the genus Peptococcus, were risk factors for CSU. In addition, the genera Collinsella, Lachnospiraceae UCG004, Ruminococcaceae UCG004, and Sellimonas were also risk factors for CSU, whereas Family XIII UCG001, Lachnospiraceae UCG010, and Methanobrevibacter had protective effects on CSU. As for metabolic pathways, NONMEVIPP-PWY, PWY-5022, and PWY-7221 were positively associated with CSU, although others, such as KDO-NAGLIPASYN-PWY, PWY- 6353, and PWY-7400 presented a suggestive association with CSU. Moreover, PWY-7400 was a mediator in causality between the family Peptococcaceae and CSU. These results were based on nominal significance (P<.05). None of the Bonferroni corrected P values were <.05.

CONCLUSIONS: Our study confirmed a causal association between gut microbiota and CSU, with the metabolic pathway being a potential mediator. Our findings provide new insights for further mechanistic and clinical studies in CSU.},
}

@article {pmid39905038,
year = {2025},
author = {Qu, Q and Dou, Q and Xiang, Z and Yu, B and Chen, L and Fan, Z and Zhao, X and Yang, S and Zeng, P},
title = {Population-level gut microbiome and its associations with environmental factors and metabolic disorders in Southwest China.},
journal = {NPJ biofilms and microbiomes},
volume = {11},
number = {1},
pages = {24},
pmid = {39905038},
issn = {2055-5008},
mesh = {*Gastrointestinal Microbiome ; Humans ; China ; *Metabolic Diseases/microbiology/etiology ; *Feces/microbiology ; *Metagenomics/methods ; Female ; Male ; Middle Aged ; Diet ; Adult ; Bacteria/classification/genetics/isolation & purification ; Life Style ; Socioeconomic Factors ; },
abstract = {Gut microbiota affects host health and disease. Large-scale cohorts have explored the interactions between the microbiota, host, and environment to reveal the disease-associated microbiota variation. A population-level gut metagenomic cohort is still rare in China. Here, we performed metagenomic sequencing on fecal samples from the CMEC Microbiome Project in Southwest China. In this study, we identified host socioeconomics, diet, lifestyle, and medical measurements that were significantly associated with microbiome function and composition. We revealed extensive novel associations between the host microbiome and common metabolic disorders. Our results provide new insight into associations of gut microbiota with metabolic disorders so as to support the translation of gut microbiome findings into potential clinical practice.},
}

*Gastrointestinal Microbiome
Humans
China
*Metabolic Diseases/microbiology/etiology
*Feces/microbiology
*Metagenomics/methods
Female
Male
Middle Aged
Diet
Adult
Bacteria/classification/genetics/isolation & purification
Life Style
Socioeconomic Factors

@article {pmid39880958,
year = {2025},
author = {Maghini, DG and Oduaran, OH and Olubayo, LAI and Cook, JA and Smyth, N and Mathema, T and Belger, CW and Agongo, G and Boua, PR and Choma, SSR and Gómez-Olivé, FX and Kisiangani, I and Mashaba, GR and Micklesfield, L and Mohamed, SF and Nonterah, EA and Norris, S and Sorgho, H and Tollman, S and Wafawanaka, F and Tluway, F and Ramsay, M and Wirbel, J and , and Bhatt, AS and Hazelhurst, S},
title = {Expanding the human gut microbiome atlas of Africa.},
journal = {Nature},
volume = {},
number = {},
pages = {},
pmid = {39880958},
issn = {1476-4687},
abstract = {Population studies provide insights into the interplay between the gut microbiome and geographical, lifestyle, genetic and environmental factors. However, low- and middle-income countries, in which approximately 84% of the world's population lives[1], are not equitably represented in large-scale gut microbiome research[2-4]. Here we present the AWI-Gen 2 Microbiome Project, a cross-sectional gut microbiome study sampling 1,801 women from Burkina Faso, Ghana, Kenya and South Africa. By engaging with communities that range from rural and horticultural to post-industrial and urban informal settlements, we capture a far greater breadth of the world's population diversity. Using shotgun metagenomic sequencing, we identify taxa with geographic and lifestyle associations, including Treponema and Cryptobacteroides species loss and Bifidobacterium species gain in urban populations. We uncover 1,005 bacterial metagenome-assembled genomes, and we identify antibiotic susceptibility as a factor that might drive Treponema succinifaciens absence in urban populations. Finally, we find an HIV infection signature defined by several taxa not previously associated with HIV, including Dysosmobacter welbionis and Enterocloster sp. This study represents the largest population-representative survey of gut metagenomes of African individuals so far, and paired with extensive clinical biomarkers and demographic data, provides extensive opportunity for microbiome-related discovery.},
}

@article {pmid39849986,
year = {2025},
author = {Liu, Y and Geng, Y and Jiang, Y and Li, P and Li, YZ and Zhang, Z},
title = {Global microbial community biodiversity increases with antimicrobial toxin abundance of rare taxa.},
journal = {The ISME journal},
volume = {},
number = {},
pages = {},
doi = {10.1093/ismejo/wraf012},
pmid = {39849986},
issn = {1751-7370},
abstract = {One of the central questions in microbial ecology is how to explain the high biodiversity of communities. A large number of rare taxa in the community have not been excluded by abundant taxa with competitive advantages, a contradiction known as the biodiversity paradox. Recently, increasing evidence has revealed the central importance of antimicrobial toxins as crucial weapons of antagonism in microbial survival. The powerful effects of antimicrobial toxins result in simple combinations of microorganisms failing to coexist under laboratory conditions, but it is unclear whether they also have a negative impact on the biodiversity of natural communities. Here, we revealed that microbial communities worldwide universally possess functional potential for antimicrobial toxin production. Counterintuitively, the biodiversity of global microbial communities increases, rather than decreases, as the abundance of antimicrobial toxins in rare taxa rises. Rare taxa may encode more antimicrobial toxins than abundant taxa, which is associated with the maintenance of the high biodiversity of microbial communities amid complex interactions. Our findings suggest that the antagonistic interaction caused by antimicrobial toxins may play a positive role in microbial community biodiversity at the global scale.},
}

@article {pmid39798621,
year = {2025},
author = {Heckmann, ND and Culler, M and Mont, MA and Lieberman, JR and Parvizi, J},
title = {Emerging Concepts in Periprosthetic Joint Infection Research: The Human Microbiome.},
journal = {The Journal of arthroplasty},
volume = {},
number = {},
pages = {},
doi = {10.1016/j.arth.2025.01.001},
pmid = {39798621},
issn = {1532-8406},
abstract = {Microorganisms, including bacteria, fungi, and viruses, that reside on and within the human body are collectively known as the human microbiome. Dysbiosis, or disruption in the microbiome, has been implicated in several disease processes, including asthma, obesity, autoimmune diseases, and numerous other conditions. While the Human Microbiome Project (HMP) and the generation of descriptive studies it inspired established correlations between characteristic patterns in the composition of the microbiome and specific disease phenotypes, current research has begun to focus on elucidating the causal role of the microbiome in disease pathogenesis. Within the field of orthopaedic surgery, researchers have proposed the concept of a "gut-joint axis" by which the intestinal microbiome influences joint health and the development of diseases such as osteoarthritis and periprosthetic joint infection (PJI). It is theorized that intestinal dysbiosis increases gut permeability, leading to the translocation of bacteria and their metabolic products into the systemic circulation and the stimulation of proinflammatory response cascades throughout the body, including within the joints. While correlative studies have identified patterns of dysbiotic derangement associated with osteoarthritis and PJI, translational research is needed to clarify the precise mechanisms by which these changes influence disease processes. Additionally, an emerging body of literature has challenged the previously held belief that certain body sites are sterile and do not possess a microbiome, with studies identifying distinct microbial genomic signatures and a core microbiome that varies between anatomic sites. A more thorough characterization of the joint microbiome may have profound implications for our understanding of PJI pathogenesis and our ability to stratify patients based on risk. The purpose of this review was to outline our current understanding of the human microbiome, to describe the gut-joint axis and its role in specific pathologies, including PJI, and to highlight the potential of microbiome-based therapeutic interventions in the field of orthopaedics.},
}

@article {pmid39794490,
year = {2025},
author = {Dilmore, AH and Kuplicki, R and McDonald, D and Kumar, M and Estaki, M and Youngblut, N and Tyakht, A and Ackermann, G and Blach, C and MahmoudianDehkordi, S and Dunlop, BW and Bhattacharyya, S and Guinjoan, S and Mandaviya, P and Ley, RE and Kaddaruh-Dauok, R and Paulus, MP and Knight, R and , },
title = {Medication use is associated with distinct microbial features in anxiety and depression.},
journal = {Molecular psychiatry},
volume = {},
number = {},
pages = {},
pmid = {39794490},
issn = {1476-5578},
support = {U19AG063744//U.S. Department of Health & Human Services | NIH | National Institute on Aging (U.S. National Institute on Aging)/ ; 5U19AG063744//U.S. Department of Health & Human Services | NIH | National Institute on Aging (U.S. National Institute on Aging)/ ; 5U19AG063744//U.S. Department of Health & Human Services | NIH | National Institute on Aging (U.S. National Institute on Aging)/ ; 5U19AG063744//U.S. Department of Health & Human Services | NIH | National Institute on Aging (U.S. National Institute on Aging)/ ; 5U19AG063744//U.S. Department of Health & Human Services | NIH | National Institute on Aging (U.S. National Institute on Aging)/ ; 5U19AG063744//U.S. Department of Health & Human Services | NIH | National Institute on Aging (U.S. National Institute on Aging)/ ; },
abstract = {This study investigated the relationship between gut microbiota and neuropsychiatric disorders (NPDs), specifically anxiety disorder (ANXD) and/or major depressive disorder (MDD), as defined by Diagnostic and Statistical Manual of Mental Disorders (DSM)-IV or V criteria. The study also examined the influence of medication use, particularly antidepressants and/or anxiolytics, classified through the Anatomical Therapeutic Chemical (ATC) Classification System, on the gut microbiota. Both 16S rRNA gene amplicon sequencing (16S) and shallow shotgun sequencing (WGS) were performed on DNA extracted from 666 fecal samples from the Tulsa-1000 and Neurocomputational Mechanisms of Affiliation and Personality Study Center for Biomedical Research Excellence (NeuroMAP CoBRE) cohorts. The results highlight the significant influence of medication use; antidepressant use is associated with significant differences in gut microbiota beta diversity and has a larger effect size than NPD diagnosis. Next, specific microbes were associated with ANXD and MDD, highlighting their potential for non-pharmacological intervention. Finally, the study demonstrated the capability of Random Forest classifiers to predict diagnoses of NPD and medication use from microbial profiles, suggesting a promising direction for the use of gut microbiota as biomarkers for NPD. Though the effect sizes were larger in females than males, similar trends emerged for both sexes. These findings encourage future research on the gut microbiota's role in NPD and its interactions with pharmacological treatments.},
}

@article {pmid39754287,
year = {2025},
author = {Epstein, HE and Brown, T and Akinrinade, AO and McMinds, R and Pollock, FJ and Sonett, D and Smith, S and Bourne, DG and Carpenter, CS and Knight, R and Willis, BL and Medina, M and Lamb, JB and Thurber, RV and Zaneveld, JR},
title = {Evidence for microbially-mediated tradeoffs between growth and defense throughout coral evolution.},
journal = {Animal microbiome},
volume = {7},
number = {1},
pages = {1},
pmid = {39754287},
issn = {2524-4671},
support = {2006244//National Science Foundation/ ; 1442306//National Science Foundation/ ; 1942647//National Science Foundation/ ; },
abstract = {BACKGROUND: Evolutionary tradeoffs between life-history strategies are important in animal evolution. Because microbes can influence multiple aspects of host physiology, including growth rate and susceptibility to disease or stress, changes in animal-microbial symbioses have the potential to mediate life-history tradeoffs. Scleractinian corals provide a biodiverse, data-rich, and ecologically-relevant host system to explore this idea.

RESULTS: Using a comparative approach, we tested if coral microbiomes correlate with disease susceptibility across 425 million years of coral evolution by conducting a cross-species coral microbiome survey (the "Global Coral Microbiome Project") and combining the results with long-term global disease prevalence and coral trait data. Interpreting these data in their phylogenetic context, we show that microbial dominance predicts disease susceptibility, and traced this dominance-disease association to a single putatively beneficial symbiont genus, Endozoicomonas. Endozoicomonas relative abundance in coral tissue explained 30% of variation in disease susceptibility and 60% of variation in microbiome dominance across 40 coral genera, while also correlating strongly with high growth rates.

CONCLUSIONS: These results demonstrate that the evolution of Endozoicomonas symbiosis in corals correlates with both disease prevalence and growth rate, and suggest a mediating role. Exploration of the mechanistic basis for these findings will be important for our understanding of how microbial symbioses influence animal life-history tradeoffs.},
}

@article {pmid39732755,
year = {2024},
author = {Bao, Z and Yang, Z and Sun, R and Chen, G and Meng, R and Wu, W and Li, MD},
title = {Predicting host health status through an integrated machine learning framework: insights from healthy gut microbiome aging trajectory.},
journal = {Scientific reports},
volume = {14},
number = {1},
pages = {31143},
pmid = {39732755},
issn = {2045-2322},
support = {2016YFC0906300//China Precision Medicine Initiative/ ; 2016YFC0906300//China Precision Medicine Initiative/ ; 2016YFC0906300//China Precision Medicine Initiative/ ; 2016YFC0906300//China Precision Medicine Initiative/ ; 2016YFC0906300//China Precision Medicine Initiative/ ; 2016YFC0906300//China Precision Medicine Initiative/ ; },
mesh = {Humans ; *Gastrointestinal Microbiome ; *Machine Learning ; *Health Status ; *Aging ; Female ; Male ; Middle Aged ; Aged ; Cohort Studies ; Adult ; },
abstract = {The gut microbiome, recognized as a critical component in the development of chronic diseases and aging processes, constitutes a promising approach for predicting host health status. Previous research has underscored the potential of microbiome-based predictions, and the rapid advancements of machine learning techniques have introduced new opportunities for exploiting microbiome data. To predict various host nonhealthy conditions, this study proposed an integrated machine learning-based estimation pipeline of Gut Age Index (GAI) by establishing a health aging baseline with the gut microbiome data from healthy individuals. We assessed the performance of GAI pipeline on two extensive cohorts - the Guangdong Gut Microbiome Project (GGMP) and the American Gut Project (AGP). In the GGMP cohort, for 20 common chronic diseases such as metabolic syndrome, obesity, and cardiovascular diseases, the proposed GAI achieved a balanced accuracy, ranging from 66 to 75%, with the prediction performance for atherosclerosis being the highest. In the AGP cohort, the balanced accuracy of GAI ranged from 58 to 72% for 10 diseases. Based on the results from these two datasets, we conclude that our proposed approach in this study can be used to predict individual health status, which offers the potential for scalable, cost-effective, and personalized health insights.},
}

Humans
*Gastrointestinal Microbiome
*Machine Learning
*Health Status
*Aging
Female
Male
Middle Aged
Aged
Cohort Studies
Adult

@article {pmid39684937,
year = {2024},
author = {Balla, B and Illés, A and Tobiás, B and Pikó, H and Beke, A and Sipos, M and Lakatos, P and Kósa, JP},
title = {The Role of the Vaginal and Endometrial Microbiomes in Infertility and Their Impact on Pregnancy Outcomes in Light of Recent Literature.},
journal = {International journal of molecular sciences},
volume = {25},
number = {23},
pages = {},
pmid = {39684937},
issn = {1422-0067},
support = {2020-4.1.1.-TKP2020-MOLORKIV//Hungarian Ministry of Innovation and Technology/ ; },
mesh = {Humans ; Female ; *Vagina/microbiology ; Pregnancy ; *Microbiota ; *Endometrium/microbiology/metabolism ; *Pregnancy Outcome ; Dysbiosis/microbiology ; Infertility, Female/microbiology ; Infertility/microbiology ; },
abstract = {The Human Microbiome Project (HMP), initiated in 2007, aimed to gather comprehensive knowledge to create a genetic and metabolic map of human-associated microorganisms and their contribution to physiological states and predisposition to certain diseases. Research has revealed that the human microbiome is highly diverse and exhibits significant interpersonal variability; consequently, its exact impact on health remains unclear. With the development of next-generation sequencing (NGS) technologies, the broad spectrum of microbial communities has been better characterized. The lower female genital tract, particularly the vagina, is colonized by various bacterial species, with Lactobacillus spp. predominating. The upper female genital tract, especially the uterus, was long considered sterile. However, recent studies have identified a distinct endometrial microbiome. A Lactobacillus-dominated microbiome of the female genital tract is associated with favorable reproductive outcomes, including higher success rates in natural conception and assisted reproductive technologies (ART). Conversely, microbial imbalances, or dysbiosis, marked by reduced Lactobacilli as well as an increased diversity and abundance of pathogenic species (e.g., Gardnerella vaginalis or Prevotella spp.), are linked to infertility, implantation failure, and pregnancy complications such as miscarriage and preterm birth. Dysbiosis can impair the vaginal or endometrial mucosal barrier and also trigger pro-inflammatory responses, disrupting essential reproductive processes like implantation. Despite growing evidence supporting the associations between the microbiome of the female genital tract and certain gynecological and obstetric conditions, clear microbial biomarkers have yet to be identified, and there is no consensus on the precise composition of a normal or healthy microbiome. The lack of standardized protocols and biomarkers limits the routine use of microbiome screening tests. Therefore, larger patient cohorts are needed to facilitate comparative studies and improve our understanding of the physiological microbiome profiles of the uterus and vagina, as well as how dysbiosis may influence clinical outcomes. Further research is required to refine diagnostic tools and develop personalized therapeutic strategies to improve fertility and pregnancy outcomes.},
}

Humans
Female
*Vagina/microbiology
Pregnancy
*Microbiota
*Endometrium/microbiology/metabolism
*Pregnancy Outcome
Dysbiosis/microbiology
Infertility, Female/microbiology
Infertility/microbiology

@article {pmid39662756,
year = {2024},
author = {Hodgkiss, R and Acharjee, A},
title = {Unravelling metabolite-microbiome interactions in inflammatory bowel disease through AI and interaction-based modelling.},
journal = {Biochimica et biophysica acta. Molecular basis of disease},
volume = {1871},
number = {3},
pages = {167618},
doi = {10.1016/j.bbadis.2024.167618},
pmid = {39662756},
issn = {1879-260X},
abstract = {Inflammatory Bowel Diseases (IBDs) are chronic inflammatory disorders of the gastrointestinal tract and colon affecting approximately 7 million individuals worldwide. The knowledge of specific pathology and aetiological mechanisms leading to IBD is limited, however a reduced immune system, antibiotic use and reserved diet may initiate symptoms. Dysbiosis of the gut microbiome, and consequently a varied composition of the metabolome, has been extensively linked to these risk factors and IBD. Metagenomic sequencing and liquid-chromatography mass spectrometry (LC-MS) of N = 220 fecal samples by Fransoza et al., provided abundance data on microbial genera and metabolites for use in this study. Identification of differentially abundant microbes and metabolites was performed using a Wilcoxon test, followed by feature selection of random forest (RF), gradient-boosting (XGBoost) and least absolute shrinkage operator (LASSO) models. The performance of these features was then validated using RF models on the Human Microbiome Project 2 (HMP2) dataset and a microbial community (MICOM) model was utilised to predict and interpret the interactions between key microbes and metabolites. The Flavronifractor genus and microbes of the families Lachnospiraceae and Oscillospiraceae were found differential by all models. Metabolic pathways commonly influenced by such microbes in IBD were CoA biosynthesis, bile acid metabolism and amino acid production and degradation. This study highlights distinct interactive microbiome and metabolome profiles within IBD and the highly potential pathways causing disease pathology. It therefore paves way for future investigation into new therapeutic targets and non-invasive diagnostic tools for IBD.},
}

@article {pmid39660282,
year = {2024},
author = {Bai, B and Luo, L and Yao, F and Sun, Q and Chen, X and Zheng, W and Jiang, L and Wang, X and Su, G},
title = {The causal relationship between the human gut microbiota and pyogenic arthritis: a Mendelian randomization study.},
journal = {Frontiers in cellular and infection microbiology},
volume = {14},
number = {},
pages = {1452480},
pmid = {39660282},
issn = {2235-2988},
mesh = {Humans ; *Mendelian Randomization Analysis ; *Gastrointestinal Microbiome/genetics ; *Arthritis, Infectious/microbiology/genetics ; *Genome-Wide Association Study ; Bacteria/genetics/classification/isolation & purification ; },
abstract = {BACKGROUND: Recent studies have indicated the role of the gut microbiota in the progression of osteoarticular diseases, however, the causal relationship between the gut microbiota and pyogenic arthritis remains unclear. There is also a lack of theoretical basis for the application of the gut microbiota in the treatment of pyogenic arthritis.

METHODS: In our study, we utilized the largest genome-wide association study (GWAS) data from the MiBioGen Consortium involving 13,400 participants and extracted summary statistical data of the microbiota metabolic pathways of 7,738 participants of European descent from the Dutch Microbiome Project (DMP) The data of pyogenic arthritis were derived from the FinnGen R10 database, including 1,086 patients and 147,221 controls. We employed the two-sample Mendelian randomization approach to investigate the causal association between the gut microbiota and pyogenic arthritis. Our methods comprised inverse variance weighting, Mendelian Randomization Egger regression, weighted median, and weighted modal methods. Subsequently, polygenic and heterogeneity analyses were conducted.

RESULTS: At the class level, β-proteobacteria is positively correlated with the risk of pyogenic arthritis. At the order level, Burkholderia is positively associated with the disease. At the genus level, the unclassified genus of Sutterellaceae is positively correlated with the disease, while the unnamed genus of Lachnospiraceae, Rothia, and the unnamed genus of Erysipelotrichaceae are negatively correlated with the disease. In addition, Faecalibacterium and Finegoldia are also negatively correlated with the disease. Sensitivity analysis did not show any abnormal evidence.

CONCLUSION: This study indicates that β-proteobacteria, Burkholderiales, and the unclassified genus of Sutterellaceae are associated with an increased risk of the disease, while the unnamed genus of Lachnospiraceae, Rothia, the unnamed genus of Erysipelotrichaceae, Faecalibacterium, and Finegoldia are related to a reduced risk. Future studies are needed to elucidate the specific mechanisms by which these specific bacterial groups affect pyogenic arthritis.},
}

Humans
*Mendelian Randomization Analysis
*Gastrointestinal Microbiome/genetics
*Arthritis, Infectious/microbiology/genetics
*Genome-Wide Association Study
Bacteria/genetics/classification/isolation & purification

@article {pmid39639265,
year = {2024},
author = {Ma, ZS},
title = {Revisiting microgenderome: detecting and cataloguing sexually unique and enriched species in human microbiomes.},
journal = {BMC biology},
volume = {22},
number = {1},
pages = {284},
pmid = {39639265},
issn = {1741-7007},
mesh = {Humans ; Female ; Male ; *Microbiota ; *Sex Characteristics ; Species Specificity ; },
abstract = {BACKGROUND: Microgenderome or arguably more accurately microsexome refers to studies on sexual dimorphism of human microbiomes aimed at investigating bidirectional interactions between human microbiomes, sex hormones, and immune systems. It is important because of its implications to disease susceptibility and therapy, in which men and women demonstrate divergence in many diseases especially autoimmune diseases. In a previous report [1], we presented analyses of several key ecological aspects of microgenderome by leveraging the large datasets of the HMP (human microbiome project) but failed to offer species-level composition differences such as sexually unique species (US) and enriched species (ES). Existing approaches, for such tasks, including differential species relative abundance analysis and differential network analysis, possess certain limitations given that virtually all rely on species abundance alone or are univariate, while ignoring species distribution information across samples. Obviously, it is both species abundance and distribution that shape/drive the structure and dynamics of human microbiomes, and both should be equally responsible for the universal heterogeneity of microbiomes including the sexual dimorphism.

RESULTS: Here, we fill the gap by taking advantages of a recently developed computational algorithm, species specificity, and specificity diversity (SSD) framework (refer to the companion article) to reanalyze the HMP and complementary seminovaginal microbiome datasets. The SSD framework can randomly search and catalogue the sexually specific unique/enriched species with statistical rigor, guided by species specificity (a synthetic metric of abundance and distribution) and specificity diversity (SD). The SSD framework reveals that men seem to have more unique species than women in their gut and reproductive system microbiomes, but women seem to have more unique species than men in the airway, oral, and skin microbiomes, which is likely due to sexual dimorphism in the hormone and immune systems. We further investigate co-dependency and heterogeneity of those sexually unique/enriched species across 15 body sites, with core/periphery network analyses.

CONCLUSIONS: This study not only produced sexually unique/enriched species in the human microbiomes and analyzed their codependency and heterogeneity but also further validated the robustness of the SSD framework presented in the companion article, by performing all negative control tests based on the HMP gut microbiome samples.},
}

Humans
Female
Male
*Microbiota
*Sex Characteristics
Species Specificity

@article {pmid39612063,
year = {2024},
author = {Xu, H and Li, O and Kim, D and Bao, Z and Yang, F},
title = {Gut microbiota and epigenetic age acceleration: a bi-directional Mendelian randomization study.},
journal = {Aging clinical and experimental research},
volume = {36},
number = {1},
pages = {227},
pmid = {39612063},
issn = {1720-8319},
support = {82071581//National Natural Science Foundation of China/ ; XXRC2211//Huadong Hospital Program/ ; },
mesh = {Humans ; *Gastrointestinal Microbiome/genetics ; *Mendelian Randomization Analysis ; *Aging/genetics ; *Epigenesis, Genetic ; Genome-Wide Association Study ; },
abstract = {BACKGROUND: The gut microbiota is closely related to aging, but the genetic relationship between gut microbiota and aging has not been well investigated. The aim of the study was to explore the association of microbiota with epigenetic age acceleration (EAA) using the Mendelian randomization.

METHOD: The independent genetic instruments of gut microbiota were obtained from MiBioGen consortium and the Dutch Microbiome Project. EAA data were derived from genome-wide association study. To assess the causal relationship between gut microbiota and EAA, we applied four different methods of Mendelian Randomization (MR) analysis: the inverse variance weighted method (IVW), the MR-Egger regression, the weighted median analysis (WMA), and the weighted mode. Furthermore, sensitivity analyses were conducted to evaluate heterogeneity and horizontal pleiotropy.

RESULTS: We identified potential causal associations between 12 bacterial taxa and EAA (PIVW and PWMA < 0.05). Among them, species Holdemania_unclassified (OR: 1.31, 95% CI: 1.13-1.52, P = 0.0004) retained a strong positive association with GrimAge acceleration. Family Acidaminococcaceae (OR: 0.64, 95% CI: 0.44-0.93, P = 0.019) and family Clostridiaceae1 (OR: 0.69, 95% CI: 0.49-0.97 P = 0.031) were negative association with GrimAge acceleration. Reverse MR analyses indicated that EAA was associated with 6 bacterial taxa in IVW and WMA. Among them, a strong inverse association was found between Phenoage acceleration and genus Turicibacter (OR: 0.928, 95%CI: 0.888-0.971, PIVW and PWMA < 0.001).

CONCLUSION: Our study implicates the potential causal effects of specific microbiota on EAA, potentially providing novel insights into the prevention aging through specific gut microbiota.},
}

Humans
*Gastrointestinal Microbiome/genetics
*Mendelian Randomization Analysis
*Aging/genetics
*Epigenesis, Genetic
Genome-Wide Association Study

@article {pmid39563467,
year = {2024},
author = {Liu, R and Wang, Y and Cheng, D},
title = {Micro-DeMix: a mixture beta-multinomial model for investigating the heterogeneity of the stool microbiome compositions.},
journal = {Bioinformatics (Oxford, England)},
volume = {40},
number = {12},
pages = {},
pmid = {39563467},
issn = {1367-4811},
support = {DMS-2220523//National Institute of Health/ ; 854127//Simons Foundation Collaboration/ ; },
mesh = {Humans ; *Feces/microbiology ; *Gastrointestinal Microbiome ; *Software ; Inflammatory Bowel Diseases/microbiology ; },
abstract = {MOTIVATION: Extensive research has uncovered the critical role of the human gut microbiome in various aspects of health, including metabolism, nutrition, physiology, and immune function. Fecal microbiota is often used as a proxy for understanding the gut microbiome, but it represents an aggregate view, overlooking spatial variations across different gastrointestinal (GI) locations. Emerging studies with spatial microbiome data collected from specific GI regions offer a unique opportunity to better understand the spatial composition of the stool microbiome.

RESULTS: We introduce Micro-DeMix, a mixture beta-multinomial model that deconvolutes the fecal microbiome at the compositional level by integrating stool samples with spatial microbiome data. Micro-DeMix facilitates the comparison of microbial compositions across different GI regions within the stool microbiome through a hypothesis-testing framework. We demonstrate the effectiveness and efficiency of Micro-DeMix using multiple simulated datasets and the inflammatory bowel disease data from the NIH Integrative Human Microbiome Project.

The R package is available at https://github.com/liuruoqian/MicroDemix.},
}

Humans
*Feces/microbiology
*Gastrointestinal Microbiome
*Software
Inflammatory Bowel Diseases/microbiology

@article {pmid39559896,
year = {2024},
author = {Zhao, Q and Baranova, A and Cao, H and Zhang, F},
title = {Evaluating Causal Effects of Gut Microbiome on Alzheimer's Disease.},
journal = {The journal of prevention of Alzheimer's disease},
volume = {11},
number = {6},
pages = {1843-1848},
doi = {10.14283/jpad.2024.113},
pmid = {39559896},
issn = {2426-0266},
mesh = {*Alzheimer Disease/microbiology ; *Gastrointestinal Microbiome ; Humans ; *Genome-Wide Association Study ; Mendelian Randomization Analysis ; },
abstract = {BACKGROUND: The preceding evidence indicates a close correlation between imbalances in the gut microbiome and Alzheimer's disease (AD), yet the direct causal relationship remains unclear. Our objective is to investigate this potential causal connection.

METHODS: We obtained summary results from two significant genome-wide association studies (GWAS) on gut microbiota (the MibioGen consortium and the Dutch Microbiome Project), along with one GWAS summary result for AD. Using a two-sample Mendelian randomization (TSMR) analysis, we examined the potential causal effects of gut microbiota on AD.

RESULTS: Our TSMR analysis revealed that 16 gut bacterial taxa were linked to a reduced risk of AD. These included phylum Tenericutes, classes Bacilli and Clostridia along with its order Clostridiales, family Bacteroidaceae, genus Bacteroides, and species Bifidobacterium bifidum (OR: 0.867~0.971, P ≤ 0.045). Conversely, the presence of 12 taxa correlated with an increased risk of AD. These comprised class Actinobacteria and its family Coriobacteriaceae, as well as class Betaproteobacteria, its order Burkholderiales, and its family Sutterellaceae (OR: 1.042~1.140, P ≤ 0.035).

CONCLUSION: Our research uncovered evidence suggesting certain gut bacterial species might play a causal role in AD risk, providing a fresh angle for AD treatment strategies.},
}

*Alzheimer Disease/microbiology
*Gastrointestinal Microbiome
Humans
*Genome-Wide Association Study
Mendelian Randomization Analysis

@article {pmid39548551,
year = {2024},
author = {Chen, S and Chen, W and Wang, X and Liu, S},
title = {Mendelian randomization analyses support causal relationships between gut microbiome and longevity.},
journal = {Journal of translational medicine},
volume = {22},
number = {1},
pages = {1032},
pmid = {39548551},
issn = {1479-5876},
support = {32100039//National Natural Science Foundation of China/ ; },
mesh = {*Longevity ; Humans ; *Mendelian Randomization Analysis ; *Gastrointestinal Microbiome/genetics ; *Genome-Wide Association Study ; Causality ; },
abstract = {BACKGROUND: Gut microbiome plays a significant role in longevity, and dysbiosis is indeed one of the hallmarks of aging. However, the causal relationship between gut microbiota and human longevity or aging remains elusive.

METHODS: Our study assessed the causal relationships between gut microbiome and longevity using Mendelian Randomization (MR). Summary statistics for the gut microbiome were obtained from four genome-wide association study (GWAS) meta-analysis of the MiBioGen consortium (N = 18,340), Dutch Microbiome Project (N = 7738), German individuals (N = 8956), and Finland individuals (N = 5959). Summary statistics for Longevity were obtained from Five GWAS meta-analysis, including Human healthspan (N = 300,447), Longevity (N = 36,745), Lifespans (N = 1,012,240), Parental longevity (N = 389,166), and Frailty (one of the primary aging-linked physiological hallmarks, N = 175,226).

RESULTS: Our findings reveal several noteworthy associations, including a negative correlation between Bacteroides massiliensis and longevity, whereas the genus Subdoligranulum and Alistipes, as well as species Alistipes senegalensis and Alistipes shahii, exhibited positive associations with specific longevity traits. Moreover, the microbial pathway of coenzyme A biosynthesis I, pyruvate fermentation to acetate and lactate II, and pentose phosphate pathway exhibited positive associations with two or more traits linked to longevity. Conversely, the TCA cycle VIII (helicobacter) pathway consistently demonstrated a negative correlation with lifespan and parental longevity.

CONCLUSIONS: Our findings of this MR study indicated many significant associations between gut microbiome and longevity. These microbial taxa and pathways may potentially play a protective role in promoting longevity or have a suppressive effect on lifespan.},
}

*Longevity
Humans
*Mendelian Randomization Analysis
*Gastrointestinal Microbiome/genetics
*Genome-Wide Association Study
Causality

@article {pmid39468693,
year = {2024},
author = {Tian, Y and Gu, M and Chen, D and Dong, Q and Wang, Y and Sun, W and Kong, X},
title = {Causal Associations Between the Gut Microbiota and Hypertension-Related Traits Through Mendelian Randomization: A Cross-Sectional Cohort Study.},
journal = {Journal of clinical hypertension (Greenwich, Conn.)},
volume = {},
number = {},
pages = {},
doi = {10.1111/jch.14925},
pmid = {39468693},
issn = {1751-7176},
support = {//Jiangsu Province Hospital High-level Talent Cultivation Program (Phase I)/ ; },
abstract = {Previous studies have suggested a link between the gut microbiome and hypertension-related traits like blood pressure. However, these reports are often limited by weak causal evidence. This study investigates the potential causal association between gut microbiota and hypertension-related traits using Mendelian randomization with summary data from genome-wide association studies. The inverse-variance weighted method revealed that the Clostridium innocuum group (Odds ratio [OR]: 1.0047, 95% confidence interval [CI]: 1.0004-1.0090, p = 0.0336), Eubacterium fissicatena group (OR: 1.0047, 95% CI: 1.0005-1.0088, p = 0.0266), Lachnospiraceae FCS020 group (OR: 1.0063, 95% CI: 1.0004-1.0122, p = 0.0361), and Olsenella (OR: 1.0044, 95% CI: 1.0001-1.0088, p = 0.0430) were associated with an increased risk of hypertension. Conversely, Flavonifractor (OR: 0.9901, 95% CI: 0.9821-0.9982, p = 0.0166), Parabacteroides (OR: 0.9874, 95% CI: 0.9776-0.9972, p = 0.0121), and Senegalimassilia (OR: 0.9907, 95% CI: 0.9842-0.9974, p = 0.0063) were associated with a decreased risk of hypertension. External validation with the Guangdong Gut Microbiome Project confirmed a negative correlation between Parabacteroides and hypertension, potentially through metabolic pathways. These findings provide further evidence supporting the hypothesis that microbes and their metabolites play a role in blood pressure regulation.},
}

@article {pmid39394961,
year = {2024},
author = {Branck, T and Hu, Z and Nickols, WA and Walsh, AM and Bhosle, A and Short, MI and Nearing, JT and Asnicar, F and McIver, LJ and Maharjan, S and Rahnavard, A and Louyakis, AS and Badri, DV and Brockel, C and Thompson, KN and Huttenhower, C},
title = {Comprehensive profile of the companion animal gut microbiome integrating reference-based and reference-free methods.},
journal = {The ISME journal},
volume = {18},
number = {1},
pages = {},
pmid = {39394961},
issn = {1751-7370},
mesh = {Animals ; *Gastrointestinal Microbiome/genetics ; Dogs/microbiology ; Cats ; *Pets/microbiology ; *Feces/microbiology ; *Phylogeny ; *Metagenome ; Humans ; *Metagenomics ; Bacteria/genetics/classification/isolation & purification ; },
abstract = {The gut microbiome of companion animals is relatively underexplored, despite its relevance to animal health, pet owner health, and basic microbial community biology. Here, we provide the most comprehensive analysis of the canine and feline gut microbiomes to date, incorporating 2639 stool shotgun metagenomes (2272 dog and 367 cat) spanning 14 publicly available datasets (n = 730) and 8 new study populations (n = 1909). These are compared with 238 and 112 baseline human gut metagenomes from the Human Microbiome Project 1-II and a traditionally living Malagasy cohort, respectively, processed in a manner identical to the animal metagenomes. All microbiomes were characterized using reference-based taxonomic and functional profiling, as well as de novo assembly yielding metagenomic assembled genomes clustered into species-level genome bins. Companion animals shared 184 species-level genome bins not found in humans, whereas 198 were found in all three hosts. We applied novel methodology to distinguish strains of these shared organisms either transferred or unique to host species, with phylogenetic patterns suggesting host-specific adaptation of microbial lineages. This corresponded with functional divergence of these lineages by host (e.g. differences in metabolic and antibiotic resistance genes) likely important to companion animal health. This study provides the largest resource to date of companion animal gut metagenomes and greatly contributes to our understanding of the "One Health" concept of a shared microbial environment among humans and companion animals, affecting infectious diseases, immune response, and specific genetic elements.},
}

Animals
*Gastrointestinal Microbiome/genetics
Dogs/microbiology
Cats
*Pets/microbiology
*Feces/microbiology
*Phylogeny
*Metagenome
Humans
*Metagenomics
Bacteria/genetics/classification/isolation & purification

@article {pmid39377919,
year = {2024},
author = {Tiwari, P and Ansari, WA and Kumar, SC and Tiwari, PK and Kumar, M and Chakdar, H and Srivastava, AK and Saxena, AK and Shantikumar, L},
title = {Genetic Diversity and Functional Potential of Streptomyces spp. Isolated from Pachmarhi Biosphere Reserve, India.},
journal = {Current microbiology},
volume = {81},
number = {11},
pages = {397},
pmid = {39377919},
issn = {1432-0991},
support = {Indian Soil Microbiome Project//National Bureau of Agriculturally Important Microorganisms/ ; },
mesh = {*Streptomyces/genetics/isolation & purification/classification ; India ; *Phylogeny ; *RNA, Ribosomal, 16S/genetics ; *Genetic Variation ; Soil Microbiology ; DNA, Bacterial/genetics ; },
abstract = {Streptomyces is a diverse genus, well known for producing a wide array of metabolites that have significant industrial utilization. The present study investigates the genetic and functional diversity of Streptomyces spp. isolated from the Pachmarhi Biosphere Reserve (PBR), India, an unexplored site. The 16S rRNA gene sequencing and analysis revealed 96 isolates belonging to 40 different species indicating a substantial phylogenetic diversity. The strains were clustered into two groups: a major cluster with 94 strains and a small cluster with two strains. BOX- PCR analyses revealed an incredible genetic diversity existing among the strains of Streptomyces spp. in PBR. The analyses revealed the intra-species diversity and inter-species closeness within the genus Streptomyces in the study area. Qualitative screening for enzyme production has shown that 53, 42, 41, 11, and 54 strains tested positive for CMCase, xylanase, amylase, pectinase, and β-glucosidase, respectively. Additionally, 54 strains tested positive for PHB production. The strains were assayed quantitatively for the production of CMCase, xylanase, amylase, and pectinase. Streptomyces sp. MP9-2, Streptomyces sp. MP10-11, Streptomyces sp. MP10-18, and Streptomyces sp. MP10-6 recorded maximum CMCase (0.604 U/mL), xylanase (0.553 U/mL), amylase (1.714 U/mL), and pectinase (13.15 U/mL) activities, respectively. Furthermore, several strains demonstrated plant growth-promoting traits, viz. zinc and phosphate solubilization and production of ammonia, HCN (hydrogen cyanide), and IAA (Indole acetic acid), and nitrogen fixation. Fifty strains showed antifungal activity against Fusarium oxysporum f. sp. lycopersici with inhibitions ranging from 7.5 to 47.5%. Current findings underscore the ecological and biotechnological significance of Streptomyces spp. in the unexplored habitat of PBR.},
}

*Streptomyces/genetics/isolation & purification/classification
India
*Phylogeny
*RNA, Ribosomal, 16S/genetics
*Genetic Variation
Soil Microbiology
DNA, Bacterial/genetics

@article {pmid39349378,
year = {2024},
author = {Palmer, D and Henze, L and Murua Escobar, H and Walter, U and Kowald, A and Fuellen, G},
title = {Multicohort study testing the generalisability of the SASKit-ML stroke and PDAC prognostic model pipeline to other chronic diseases.},
journal = {BMJ open},
volume = {14},
number = {9},
pages = {e088181},
pmid = {39349378},
issn = {2044-6055},
mesh = {Humans ; *Diabetes Mellitus, Type 2/complications ; Prognosis ; Female ; Male ; *Pancreatic Neoplasms ; *Stroke ; Middle Aged ; Arthritis, Rheumatoid ; Machine Learning ; Inflammatory Bowel Diseases ; Aged ; Longitudinal Studies ; Chronic Disease ; Prospective Studies ; Biomarkers/blood ; Cohort Studies ; },
abstract = {OBJECTIVES: To validate and test the generalisability of the SASKit-ML pipeline, a prepublished feature selection and machine learning pipeline for the prediction of health deterioration after a stroke or pancreatic adenocarcinoma event, by using it to identify biomarkers of health deterioration in chronic disease.

DESIGN: This is a validation study using a predefined protocol applied to multiple publicly available datasets, including longitudinal data from cohorts with type 2 diabetes (T2D), inflammatory bowel disease (IBD), rheumatoid arthritis (RA) and various cancers. The datasets were chosen to mimic as closely as possible the SASKit cohort, a prospective, longitudinal cohort study.

DATA SOURCES: Public data were used from the T2D (77 patients with potential pre-diabetes and 18 controls) and IBD (49 patients with IBD and 12 controls) branches of the Human Microbiome Project (HMP), RA Map (RA-MAP, 92 patients with RA, 22 controls) and The Cancer Genome Atlas (TCGA, 16 cancers).

METHODS: Data integration steps were performed in accordance with the prepublished study protocol, generating features to predict disease outcomes using 10-fold cross-validated random survival forests.

OUTCOME MEASURES: Health deterioration was assessed using disease-specific clinical markers and endpoints across different cohorts. In the HMP-T2D cohort, the worsening of glycated haemoglobin (HbA1c) levels (5.7% or more HbA1c in the blood), fasting plasma glucose (at least 100 mg/dL) and oral glucose tolerance test (at least 140) results were considered. For the HMP-IBD cohort, a worsening by at least 3 points of a disease-specific severity measure, the "Simple Clinical Colitis Activity Index" or "Harvey-Bradshaw Index" indicated an event. For the RA-MAP cohort, the outcome was defined as the worsening of the "Disease Activity Score 28" or "Simple Disease Activity Index" by at least five points, or the worsening of the "Health Assessment Questionnaire" score or an increase in the number of swollen/tender joints were evaluated. Finally, the outcome for all TCGA datasets was the progression-free interval.

RESULTS: Models for the prediction of health deterioration in T2D, IBD, RA and 16 cancers were produced. The T2D (C-index of 0.633 and Integrated Brier Score (IBS) of 0.107) and the RA (C-index of 0.654 and IBS of 0.150) models were modestly predictive. The IBD model was uninformative. TCGA models tended towards modest predictive power.

CONCLUSIONS: The SASKit-ML pipeline produces informative and useful features with the power to predict health deterioration in a variety of diseases and cancers; however, this performance is disease-dependent.},
}

Humans
*Diabetes Mellitus, Type 2/complications
Prognosis
Female
Male
*Pancreatic Neoplasms
*Stroke
Middle Aged
Arthritis, Rheumatoid
Machine Learning
Inflammatory Bowel Diseases
Aged
Longitudinal Studies
Chronic Disease
Prospective Studies
Biomarkers/blood
Cohort Studies

@article {pmid39309525,
year = {2024},
author = {Liu, L and He, G and Yu, R and Lin, B and Lin, L and Wei, R and Zhu, Z and Xu, Y},
title = {Causal relationships between gut microbiome and obstructive sleep apnea: a bi-directional Mendelian randomization.},
journal = {Frontiers in microbiology},
volume = {15},
number = {},
pages = {1410624},
pmid = {39309525},
issn = {1664-302X},
abstract = {BACKGROUND: Previous studies have identified a clinical association between gut microbiota and Obstructive sleep apnea (OSA), but the potential causal relationship between the two has not been determined. Therefore, we aim to utilize Mendelian randomization (MR) to investigate the potential causal effects of gut microbiota on OSA and the impact of OSA on altering the composition of gut microbiota.

METHODS: Bi-directional MR and replicated validation were utilized. Summary-level genetic data of gut microbiota were derived from the MiBioGen consortium and the Dutch Microbiome Project (DMP). Summary statistics of OSA were drawn from FinnGen Consortium and Million Veteran Program (MVP). Inverse-variance-weighted (IVW), weighted median, MR-Egger, Simple Mode, and Weighted Mode methods were used to evaluate the potential causal link between gut microbiota and OSA.

RESULTS: We identified potential causal associations between 23 gut microbiota and OSA. Among them, genus Eubacterium xylanophilum group (OR = 0.86; p = 0.00013), Bifidobacterium longum (OR = 0.90; p = 0.0090), Parabacteroides merdae (OR = 0.85; p = 0.00016) retained a strong negative association with OSA after the Bonferroni correction. Reverse MR analyses indicated that OSA was associated with 20 gut microbiota, among them, a strong inverse association between OSA and genus Anaerostipes (beta = -0.35; p = 0.00032) was identified after Bonferroni correction.

CONCLUSION: Our study implicates the potential bi-directional causal effects of the gut microbiota on OSA, potentially providing new insights into the prevention and treatment of OSA through specific gut microbiota.},
}

@article {pmid39286351,
year = {2024},
author = {Jin, W and Li, B and Wang, L and Zhu, L and Chai, S and Hou, R},
title = {The causal association between gut microbiota and postpartum depression: a two-sample Mendelian randomization study.},
journal = {Frontiers in microbiology},
volume = {15},
number = {},
pages = {1415237},
pmid = {39286351},
issn = {1664-302X},
abstract = {BACKGROUND: An escalating body of clinical trials and observational studies hints at a plausible link between gut flora and postpartum depression (PPD). The definitive causal dynamics between these two entities remain shrouded in ambiguity. Therefore, in this study, we employed the two-sample Mendelian randomization approach to ascertain the causal link between gut microbiota and PPD.

METHODS: Summary-level GWAS data related to the human gut microbiota were obtained from the international consortium MiBioGen and the Dutch Microbiome Project (species). For PPD, GWAS data were derived from the FinnGen biobank, consisting 57,604 cases and 596,601 controls. The inverse variance weighted method (IVW) as the cornerstone of our analytical approach. Subsequent to this, a comprehensive suite of tests for pleiotropy and heterogeneity were conducted to ensure the reliability and robustness of our findings.

RESULTS: We identified 12 bacterial taxa associated with the risk of PPD. Veillonellaceae, Ruminococcaceae UCG 011, Bifidobacterium adolescentis, Paraprevotella clara, Clostridium leptum, Eubacterium siraeum, Coprococcus catus exhibited an inversely associated with the risk of PPD. Alphaproteobacteria, Roseburia, FamilyXIIIAD3011group, Alistipes onderdonkii, Bilophila wadsworthia showed a positive correlation with the risk of PPD.

LIMITATIONS: The GWAS data derived from the MiBioGen consortium, DMP, and FinnGen consortium, may introduce selection bias. Moreover, the data primarily originates from European populations, hence extrapolating these results to diverse populations should be approached with caution. The etiological factors behind PPD remain enigmatic, alluding to the existence of potential undisclosed confounders.

CONCLUSION: Based on this MR analysis, we found a causal relationship between certain gut microbial communities and PPD. Future clinical studies can further explore the treatment of PPD through the combined use of microorganisms. This not only offers insights into the pathogenesis of PPD but also lays the foundation for utilizing gut microbiota as biotherapeutics in treating neurological disorders.},
}

@article {pmid39281749,
year = {2024},
author = {Kang, JW and Khatib, LA and Heston, MB and Dilmore, AH and Labus, JS and Deming, Y and Schimmel, L and Blach, C and McDonald, D and Gonzalez, A and Bryant, M and Sanders, K and Schwartz, A and Ulland, TK and Johnson, SC and Asthana, S and Carlsson, CM and Chin, NA and Blennow, K and Zetterberg, H and Rey, FE and , and Kaddurah-Daouk, R and Knight, R and Bendlin, BB},
title = {Gut Microbiome Compositional and Functional Features Associate with Alzheimer's Disease Pathology.},
journal = {medRxiv : the preprint server for health sciences},
volume = {},
number = {},
pages = {},
pmid = {39281749},
support = {R21 AG089348/AG/NIA NIH HHS/United States ; R01 AG092220/AG/NIA NIH HHS/United States ; U19 AG063744/AG/NIA NIH HHS/United States ; S10 OD026929/OD/NIH HHS/United States ; U01 AG061359/AG/NIA NIH HHS/United States ; P30 AG062715/AG/NIA NIH HHS/United States ; R01 AG083883/AG/NIA NIH HHS/United States ; R01 AG070973/AG/NIA NIH HHS/United States ; },
abstract = {BACKGROUND: The gut microbiome is a potentially modifiable factor in Alzheimer's disease (AD); however, understanding of its composition and function regarding AD pathology is limited.

METHODS: Shallow-shotgun metagenomic data was used to analyze fecal microbiome from participants enrolled in the Wisconsin Microbiome in Alzheimer's Risk Study, leveraging clinical data and cerebrospinal fluid (CSF) biomarkers. Differential abundance and ordinary least squares regression analyses were performed to find differentially abundant gut microbiome features and their associations with CSF biomarkers of AD and related pathologies.

RESULTS: Gut microbiome composition and function differed between people with AD and cognitively unimpaired individuals. The compositional difference was replicated in an independent cohort. Differentially abundant gut microbiome features were associated with CSF biomarkers of AD and related pathologies.

DISCUSSION: These findings enhance our understanding of alterations in gut microbial composition and function in AD, and suggest that gut microbes and their pathways are linked to AD pathology.},
}

@article {pmid39252313,
year = {2024},
author = {Fan, T and Li, L and Chen, Y},
title = {Causal relationships between gut microbiota and depression/anxiety disorders: A 2-sample Mendelian randomization study.},
journal = {Medicine},
volume = {103},
number = {36},
pages = {e39543},
doi = {10.1097/MD.0000000000039543},
pmid = {39252313},
issn = {1536-5964},
mesh = {*Mendelian Randomization Analysis ; Humans ; *Gastrointestinal Microbiome/genetics ; *Anxiety Disorders/microbiology/genetics ; *Genome-Wide Association Study ; Depressive Disorder/microbiology/genetics ; Depression/microbiology ; },
abstract = {Evidence shows that the composition of the gut microbiota (GM) is associated with depression and anxiety disorders. However, the causal relationship between them remains controversial. To investigate the potential causal relationship between the GM and depression/anxiety disorders and to identify specific bacterial taxa, we conducted a 2-sample Mendelian randomization (MR) analysis on the gut microbiome implicated in depression and anxiety disorders. We incorporated summary data from genome-wide association studies (GWAS) of the microbiome derived from 7738 individuals in the Dutch Microbiome Project and 18,340 individuals in the MiBioGen consortium as our exposure variable. Concurrently, the GWAS of depression and anxiety disorders was employed as our outcome variable. The principal estimates were procured using the inverse-variance weighted test complemented by 4 robust methods: MR Egger, weighted median, simple mode, and weighted mode. In addition, we performed comprehensive sensitivity and directionality analyses. The results showed that 5 bacterial taxa were positively correlated with depression, 6 were negatively correlated; 5 were positively correlated with anxiety disorders, and 11 were negatively correlated. This study provides new insights into the connection between the GM and the pathogenesis of depression and anxiety disorders and offers new perspectives for the diagnosis and treatment of these disorders.},
}

*Mendelian Randomization Analysis
Humans
*Gastrointestinal Microbiome/genetics
*Anxiety Disorders/microbiology/genetics
*Genome-Wide Association Study
Depressive Disorder/microbiology/genetics
Depression/microbiology

@article {pmid39243281,
year = {2024},
author = {Jiang, X and Wang, M and Liu, B and Yang, H and Ren, J and Chen, S and Ye, D and Yang, S and Mao, Y},
title = {Gut microbiota and risk of ankylosing spondylitis.},
journal = {Clinical rheumatology},
volume = {43},
number = {11},
pages = {3351-3360},
pmid = {39243281},
issn = {1434-9949},
support = {81973663//National Natural Science Foundation of China/ ; 82174208//National Natural Science Foundation of China/ ; LY22H260005//Natural Science Foundation of Zhejiang Province/ ; 2023ZL286//Zhejiang Province Traditional Chinese Medical Science and Technology Plan/ ; },
mesh = {*Spondylitis, Ankylosing/microbiology ; Humans ; *Gastrointestinal Microbiome ; *Mendelian Randomization Analysis ; Risk Factors ; Bacteroides/genetics/isolation & purification ; },
abstract = {OBJECTIVE: Observational studies have established a connection between gut microbiota and ankylosing spondylitis (AS) risk; however, whether the observed associations are causal remains unclear. Therefore, we conducted a two-sample Mendelian randomization (MR) analysis to assess the potential causal associations of gut microbiota with AS risk.

METHODS: Instrumental variants of gut microbiota were obtained from the MiBioGen consortium (n = 18,340) and the Dutch Microbiome Project (n = 7738). The FinnGen consortium provided genetic association summary statistics for AS, encompassing 2860 cases and 270,964 controls. We used the inverse-variance weighted (IVW) method as the primary analysis, supplemented with the weighted median method, maximum likelihood-based method, MR pleiotropy residual sum and outlier test, and MR-Egger regression. In addition, we conducted a reverse MR analysis to assess the likelihood of reverse causality.

RESULTS: After the Bonferroni correction, species Bacteroides vulgatus remained statistically significantly associated with AS risk (odds ratio (OR) 1.55, 95% confidence interval (CI) 1.22-1.95, P = 2.55 × 10[-4]). Suggestive evidence of associations of eleven bacterial traits with AS risk was also observed (P < 0.05 by IVW). Among them, eight were associated with an elevated AS risk (OR 1.37, 95% CI 1.07-1.74, P = 0.011 for phylum Verrucomicrobia; OR 1.31, 95% CI 1.03-1.65, P = 0.026 for class Verrucomicrobiae; OR 1.17, 95% CI 1.01-1.36, P = 0.035 for order Bacillales; OR 1.31, 95% CI 1.03-1.65, P = 0.026 for order Verrucomicrobiales; OR 1.43, 95% CI 1.13-1.82, P = 0.003 for family Alcaligenaceae; OR 1.31, 95% CI 1.03-1.65, P = 0.026 for family Verrucomicrobiaceae; OR 1.31, 95% CI 1.03-1.65, P = 0.026 for genus Akkermansia; OR 1.55, 95% CI 1.19-2.02, P = 0.001 for species Sutterella wadsworthensis). Three traits exhibited a negative association with AS risk (OR 0.68, 95% CI 0.53-0.88, P = 0.003 for genus Dialister; OR 0.84, 95% CI 0.72-0.97, P = 0.020 for genus Howardella; OR 0.75, 95% CI 0.59-0.97, P = 0.026 for genus Oscillospira). Consistent associations were observed when employing alternate MR methods. In the reverse MR, no statistically significant correlations were detected between AS and these bacterial traits.

CONCLUSION: Our results revealed the associations of several gut bacterial traits with AS risk, suggesting a potential causal role of gut microbiota in AS development. Nevertheless, additional research is required to clarify the mechanisms by which these bacteria influence AS risk. Key Points • The association of gut microbiota with AS risk in observational studies is unclear. • This MR analysis revealed associations of 12 gut bacterial traits with AS risk.},
}

*Spondylitis, Ankylosing/microbiology
Humans
*Gastrointestinal Microbiome
*Mendelian Randomization Analysis
Risk Factors
Bacteroides/genetics/isolation & purification

@article {pmid39230701,
year = {2024},
author = {Hera, MR and Liu, S and Wei, W and Rodriguez, JS and Ma, C and Koslicki, D},
title = {Metagenomic functional profiling: to sketch or not to sketch?.},
journal = {Bioinformatics (Oxford, England)},
volume = {40},
number = {Suppl 2},
pages = {ii165-ii173},
pmid = {39230701},
issn = {1367-4811},
support = {R01 GM146462/GM/NIGMS NIH HHS/United States ; R01GM146462/GF/NIH HHS/United States ; },
mesh = {*Metagenomics/methods ; *Software ; *Algorithms ; *Metagenome/genetics ; Humans ; Microbiota/genetics ; Databases, Genetic ; },
abstract = {MOTIVATION: Functional profiling of metagenomic samples is essential to decipher the functional capabilities of microbial communities. Traditional and more widely used functional profilers in the context of metagenomics rely on aligning reads against a known reference database. However, aligning sequencing reads against a large and fast-growing database is computationally expensive. In general, k-mer-based sketching techniques have been successfully used in metagenomics to address this bottleneck, notably in taxonomic profiling. In this work, we describe leveraging FracMinHash (implemented in sourmash, a publicly available software), a k-mer-sketching algorithm, to obtain functional profiles of metagenome samples.

RESULTS: We show how pieces of the sourmash software (and the resulting FracMinHash sketches) can be put together in a pipeline to functionally profile a metagenomic sample. We named our pipeline fmh-funprofiler. We report that the functional profiles obtained using this pipeline demonstrate comparable completeness and better purity compared to the profiles obtained using other alignment-based methods when applied to simulated metagenomic data. We also report that fmh-funprofiler is 39-99× faster in wall-clock time, and consumes up to 40-55× less memory. Coupled with the KEGG database, this method not only replicates fundamental biological insights but also highlights novel signals from the Human Microbiome Project datasets.

This fast and lightweight metagenomic functional profiler is freely available and can be accessed here: https://github.com/KoslickiLab/fmh-funprofiler. All scripts of the analyses we present in this manuscript can be found on GitHub.},
}

*Metagenomics/methods
*Software
*Algorithms
*Metagenome/genetics
Humans
Microbiota/genetics
Databases, Genetic

@article {pmid39230322,
year = {2024},
author = {Flamholz, AI and Goldford, JE and Richter, PA and Larsson, EM and Jinich, A and Fischer, WW and Newman, DK},
title = {Annotation-free prediction of microbial dioxygen utilization.},
journal = {mSystems},
volume = {9},
number = {10},
pages = {e0076324},
pmid = {39230322},
issn = {2379-5077},
support = {61-1772//Jane Coffin Childs Memorial Fund for Medical Research (JCC)/ ; GBMF4513//Gordon and Betty Moore Foundation (GBMF)/ ; 2127442//National Science Foundation (NSF)/ ; W911NF-22-2-0210//DOD | USA | AFC | CCDC | Army Research Office (ARO)/ ; GT16787//Howard Hughes Medical Institute (HHMI)/ ; },
mesh = {*Oxygen/metabolism/analysis ; Genome, Bacterial/genetics ; Phylogeny ; Molecular Sequence Annotation ; },
abstract = {Aerobes require dioxygen (O2) to grow; anaerobes do not. However, nearly all microbes-aerobes, anaerobes, and facultative organisms alike-express enzymes whose substrates include O2, if only for detoxification. This presents a challenge when trying to assess which organisms are aerobic from genomic data alone. This challenge can be overcome by noting that O2 utilization has wide-ranging effects on microbes: aerobes typically have larger genomes encoding distinctive O2-utilizing enzymes, for example. These effects permit high-quality prediction of O2 utilization from annotated genome sequences, with several models displaying ≈80% accuracy on a ternary classification task for which blind guessing is only 33% accurate. Since genome annotation is compute-intensive and relies on many assumptions, we asked if annotation-free methods also perform well. We discovered that simple and efficient models based entirely on genomic sequence content-e.g., triplets of amino acids-perform as well as intensive annotation-based classifiers, enabling rapid processing of genomes. We further show that amino acid trimers are useful because they encode information about protein composition and phylogeny. To showcase the utility of rapid prediction, we estimated the prevalence of aerobes and anaerobes in diverse natural environments cataloged in the Earth Microbiome Project. Focusing on a well-studied O2 gradient in the Black Sea, we found quantitative correspondence between local chemistry (O2:sulfide concentration ratio) and the composition of microbial communities. We, therefore, suggest that statistical methods like ours might be used to estimate, or "sense," pivotal features of the chemical environment using DNA sequencing data.IMPORTANCEWe now have access to sequence data from a wide variety of natural environments. These data document a bewildering diversity of microbes, many known only from their genomes. Physiology-an organism's capacity to engage metabolically with its environment-may provide a more useful lens than taxonomy for understanding microbial communities. As an example of this broader principle, we developed algorithms that accurately predict microbial dioxygen utilization directly from genome sequences without annotating genes, e.g., by considering only the amino acids in protein sequences. Annotation-free algorithms enable rapid characterization of natural samples, highlighting quantitative correspondence between sequences and local O2 levels in a data set from the Black Sea. This example suggests that DNA sequencing might be repurposed as a multi-pronged chemical sensor, estimating concentrations of O2 and other key facets of complex natural settings.},
}

*Oxygen/metabolism/analysis
Genome, Bacterial/genetics
Phylogeny
Molecular Sequence Annotation

@article {pmid39226947,
year = {2024},
author = {Di, J and Xi, Y and Wu, Y and Di, Y and Xing, X and Zhang, Z and Xiang, C},
title = {Gut microbiota metabolic pathways: Key players in knee osteoarthritis development.},
journal = {Experimental gerontology},
volume = {196},
number = {},
pages = {112566},
doi = {10.1016/j.exger.2024.112566},
pmid = {39226947},
issn = {1873-6815},
mesh = {*Gastrointestinal Microbiome/physiology ; Humans ; *Osteoarthritis, Knee/metabolism/microbiology ; *Mendelian Randomization Analysis ; Polymorphism, Single Nucleotide ; Metabolic Networks and Pathways ; Risk Factors ; },
abstract = {OBJECTIVE: To confirm the causality of gut microbiota pathway abundance and knee osteoarthritis (KOA).

METHODS: Microbial metabolic pathways were taken as exposures, with data from the Dutch Microbiome Project (DMP). Data on KOA from the UK Biobank were utilized as endpoints. In addition, we extracted significant and independent single nucleotide polymorphisms as instrumental variables. Two-sample Mendelian randomization (MR) analysis was applied to explore the causal relationship between gut microbiota pathway abundance and KOA, and MR-Egger and weighted median were used as additional validation of the MR results. Meanwhile, Cochran Q, MR-Egger intercept, MR-PRESSO, and leave-one-out were used to perform sensitivity analyses on the MR results.

RESULTS: MR results showed that enterobactin biosynthesis, diacylglycerol biosynthesis I, Clostridium acetobutylicum acidogenic fermentation, glyoxylate bypass and tricarboxylic acid cycle were the risk factors for KOA. (OR = 1.13,95%CI = 1.04-1.23;OR = 1.12,95%CI = 1.04-1.20;OR = 1.14,95%CI = 1.04-1.26; OR = 1.06,95%CI = 1.00-1.12) However, adenosylcobalamin salvage from cobinamide I, hexitol fermentation to lactate formate ethanol and acetate, purine nucleotides degradation II aerobic, L tryptophan biosynthesis and inosine 5 phosphate biosynthesis III pathway showed significant protection against KOA. (OR = 0.93,95%CI = 0.86-1.00;OR = 0.94,95%CI = 0.88-1.00;OR = 0.91,95%CI = 0.86-0.97;OR = 0.95,95%CI = 0.92-0.99; OR = 0.91, 95%CI = 0.85-0.98) Further multiplicity and sensitivity analyses demonstrated the robustness of the results.

CONCLUSION: Our study identified specific metabolic pathways in gut microbiota that promote or inhibit KOA, which provides the most substantial evidence-based medical evidence for the pathogenesis and prevention of KOA.},
}

*Gastrointestinal Microbiome/physiology
Humans
*Osteoarthritis, Knee/metabolism/microbiology
*Mendelian Randomization Analysis
Polymorphism, Single Nucleotide
Metabolic Networks and Pathways
Risk Factors

@article {pmid39209213,
year = {2024},
author = {Koellsch, C and Poulin, R and Salloum, PM},
title = {What shapes a microbiome? Differences in bacterial communities associated with helminth-amphipod interactions.},
journal = {International journal for parasitology},
volume = {54},
number = {14},
pages = {733-742},
doi = {10.1016/j.ijpara.2024.08.005},
pmid = {39209213},
issn = {1879-0135},
mesh = {Animals ; *Host-Parasite Interactions ; *Acanthocephala/physiology/genetics ; *Amphipoda/parasitology/microbiology ; *Microbiota ; *Cestoda/genetics/physiology/classification ; *RNA, Ribosomal, 16S/genetics ; Bacteria/classification/genetics/isolation & purification ; Hemolymph/microbiology/parasitology ; Female ; Helminths/genetics/classification/physiology/isolation & purification ; Male ; },
abstract = {The fast technological advances of molecular tools have enabled us to uncover a new dimension hidden within parasites and their hosts: their microbiomes. Increasingly, parasitologists characterise host microbiome changes in the face of parasitic infections, revealing the potential of these microscopic fast-evolving entities to influence host-parasite interactions. However, most of the changes in host microbiomes seem to depend on the host and parasite species in question. Furthermore, we should understand the relative role of parasitic infections as microbiome modulators when compared with other microbiome-impacting factors (e.g., host size, age, sex). Here, we characterised the microbiome of a single intermediate host species infected by two parasites belonging to different phyla: the acanthocephalan Plagiorhynchus allisonae and a dilepidid cestode, both infecting Transorchestia serrulata amphipods collected simultaneously from the same locality. We used the v4 hypervariable region of the 16S rRNA prokaryotic gene to identify the hemolymph bacterial community of uninfected, acanthocephalan-infected, and cestode-infected amphipods, as well as the bacteria in the amphipods' immediate environment and in the parasites infecting them. Our results show that parasitic infections were more strongly associated with differences in host bacterial community richness than amphipod size, presence of amphipod eggs in female amphipods, and even parasite load. Amphipods infected by acanthocephalans had the most divergent bacterial community, with a marked decrease in alpha diversity compared with cestode-infected and uninfected hosts. In accordance with the species-specific nature of microbiome changes in parasitic infections, we found unique microbial taxa associating with hosts infected by each parasite species, as well as taxa only shared between a parasite species and their infected hosts. However, there were some bacterial taxa detected in all parasitised amphipods (regardless of the parasite species), but not in uninfected amphipods or the environment. We propose that shared bacteria associated with all hosts parasitised by distantly related helminths may be important either in helping host defences or parasites' success, and could thus interact with host-parasite evolution.},
}

Animals
*Host-Parasite Interactions
*Acanthocephala/physiology/genetics
*Amphipoda/parasitology/microbiology
*Microbiota
*Cestoda/genetics/physiology/classification
*RNA, Ribosomal, 16S/genetics
Bacteria/classification/genetics/isolation & purification
Hemolymph/microbiology/parasitology
Female
Helminths/genetics/classification/physiology/isolation & purification
Male

@article {pmid39207108,
year = {2024},
author = {Crouch, AL and Monsey, L and Rambeau, M and Ramos, C and Yracheta, JM and Anderson, MZ},
title = {Metagenomic discovery of microbial eukaryotes in stool microbiomes.},
journal = {mBio},
volume = {15},
number = {10},
pages = {e0206324},
pmid = {39207108},
issn = {2150-7511},
support = {//Ohio State University (OSU)/ ; 2046863//National Science Foundation (NSF)/ ; //Chan Zuckerberg Initiative (CZI)/ ; },
mesh = {Humans ; *Metagenomics/methods ; *Feces/microbiology ; *Eukaryota/genetics/classification/isolation & purification ; Gastrointestinal Microbiome/genetics ; Metagenome ; Fungi/genetics/classification/isolation & purification ; Sequence Analysis, DNA/methods ; Microbiota/genetics ; },
abstract = {Host-associated microbiota form complex microbial communities that are increasingly associated with host behavior and disease. While these microbes include bacterial, archaeal, viral, and eukaryotic constituents, most studies have focused on bacteria due to their dominance in the human host and available tools for investigation. Accumulating evidence suggests microbial eukaryotes in the microbiome play pivotal roles in host health, but our understandings of these interactions are limited to a few readily identifiable taxa because of technical limitations in unbiased eukaryote exploration. Here, we combined cell sorting, optimized eukaryotic cell lysis, and shotgun sequencing to accelerate metagenomic discovery and analysis of host-associated microbial eukaryotes. Using synthetic communities with a 1% microbial eukaryote representation, the eukaryote-optimized cell lysis and DNA recovery method alone yielded a 38-fold increase in eukaryotic DNA. Automated sorting of eukaryotic cells from stool samples of healthy adults increased the number of microbial eukaryote reads in metagenomic pools by up to 28-fold compared to commercial kits. Read frequencies for identified fungi increased by 10,000× on average compared to the Human Microbiome Project and allowed for the identification of novel taxa, de novo assembly of contigs from previously unknown microbial eukaryotes, and gene prediction from recovered genomic segments. These advances pave the way for the unbiased inclusion of microbial eukaryotes in deciphering determinants of health and disease in the host-associated microbiome.IMPORTANCEMicrobial eukaryotes are common constituents of the human gut where they can contribute to local ecology and host health, but they are often overlooked in microbiome studies. The lack of attention is due to current technical limitations that are heavily biased or poorly recovered DNA from microbial eukaryotes. We developed a method to increase the representation of these eukaryotes in metagenomic sequencing of microbiome samples that allows to improve their detection compared to prior methods and allows for the identification of new species. Application of the technique to gut microbiome samples improved detection of fungi, protists, and helminths. New eukaryotic taxa and their encoded genes could be identified by sequencing a small number of samples. This approach can improve the inclusion of eukaryotes into microbiome research.},
}

Humans
*Metagenomics/methods
*Feces/microbiology
*Eukaryota/genetics/classification/isolation & purification
Gastrointestinal Microbiome/genetics
Metagenome
Fungi/genetics/classification/isolation & purification
Sequence Analysis, DNA/methods
Microbiota/genetics

@article {pmid39139765,
year = {2024},
author = {Sun, Y and Dong, H and Sun, C and Du, D and Gao, R and Voevoda, M and Knyazev, R and Wu, N},
title = {Investigating the association between gut microbiome and aortic aneurysm diseases: a bidirectional two-sample Mendelian randomization analysis.},
journal = {Frontiers in cellular and infection microbiology},
volume = {14},
number = {},
pages = {1406845},
pmid = {39139765},
issn = {2235-2988},
mesh = {*Mendelian Randomization Analysis ; Humans ; *Gastrointestinal Microbiome/genetics ; *Genome-Wide Association Study ; Aortic Aneurysm, Abdominal/microbiology/genetics ; Aortic Aneurysm/microbiology/genetics ; Bacteria/classification/genetics/isolation & purification ; Aortic Aneurysm, Thoracic/microbiology/genetics ; Aortic Dissection/microbiology ; },
abstract = {OBJECTIVE: This study aims to investigate the associations between specific bacterial taxa of the gut microbiome and the development of aortic aneurysm diseases, utilizing Mendelian Randomization (MR) to explore these associations and overcome the confounding factors commonly present in observational studies.

METHODS: Employing the largest available gut microbiome and aortic aneurysm Genome-Wide Association Study databases, including MiBioGen, Dutch Microbiome Project, FinnGen, UK Biobank, and Michigan Genomics Initiative, this study performs two-sample bidirectional MR analyses. Instrumental variables, linked to microbiome taxa at significant levels, were selected for identifying relationships with abdominal aortic aneurysms (AAA), thoracic aortic aneurysms (TAA), and aortic dissection (AD). Methods like inverse variance weighted, MR-PRESSO, MR-Egger, weighted median, simple mode, and mode-based estimate were used for MR analysis. Heterogeneity was assessed with the Cochran Q test. MR-Egger regression and MR-PRESSO addressed potential unbalanced horizontal pleiotropy.

RESULTS: The analysis did not find any evidence of statistically significant associations between the gut microbiome and aortic aneurysm diseases after adjusting for the false discovery rate (FDR). Specifically, while initial results suggested correlations between 19 taxa and AAA, 25 taxa and TAA, and 13 taxa with AD, these suggested associations did not hold statistical significance post-FDR correction. Therefore, the role of individual gut microbial taxa as independent factors in the development and progression of aortic aneurysm diseases remains inconclusive. This finding underscores the necessity for larger sample sizes and more comprehensive studies to further investigate these potential links.

CONCLUSION: The study emphasizes the complex relationship between the gut microbiome and aortic aneurysm diseases. Although no statistically significant associations were found after FDR correction, the findings provide valuable insights and highlight the importance of considering gut microbiota in aortic aneurysm diseases research. Understanding these interactions may eventually contribute to identifying new therapeutic and preventive strategies for aortic aneurysm diseases.},
}

*Mendelian Randomization Analysis
Humans
*Gastrointestinal Microbiome/genetics
*Genome-Wide Association Study
Aortic Aneurysm, Abdominal/microbiology/genetics
Aortic Aneurysm/microbiology/genetics
Bacteria/classification/genetics/isolation & purification
Aortic Aneurysm, Thoracic/microbiology/genetics
Aortic Dissection/microbiology

@article {pmid39053136,
year = {2024},
author = {Gholamzad, A and Khakpour, N and Hashemi, SMA and Goudarzi, Y and Ahmadi, P and Gholamzad, M and Mohammadi, M and Hashemi, M},
title = {Exploring the virome: An integral part of human health and disease.},
journal = {Pathology, research and practice},
volume = {260},
number = {},
pages = {155466},
doi = {10.1016/j.prp.2024.155466},
pmid = {39053136},
issn = {1618-0631},
mesh = {Humans ; *Virome ; *Gastrointestinal Microbiome ; Inflammatory Bowel Diseases/virology ; },
abstract = {The human microbiome is a complex network of microorganisms that includes viruses, bacteria, and fungi. The gut virome is an essential component of the immune system, which is responsible for regulating the growth and responses of the host's immune system. The virome maintains a crucial role in the development of numerous diseases, including inflammatory bowel disease (IBD), Crohn's disease, and neurodegenerative disorders. The human virome has emerged as a promising biomarker and therapeutic target. This comprehensive review summarizes the present understanding of the virome and its implications in matters of health and disease, with a focus on the Human Microbiome Project.},
}

Humans
*Virome
*Gastrointestinal Microbiome
Inflammatory Bowel Diseases/virology

@article {pmid39040076,
year = {2024},
author = {Onwuka, S and Bravo-Merodio, L and Gkoutos, GV and Acharjee, A},
title = {Explainable AI-prioritized plasma and fecal metabolites in inflammatory bowel disease and their dietary associations.},
journal = {iScience},
volume = {27},
number = {7},
pages = {110298},
pmid = {39040076},
issn = {2589-0042},
abstract = {Fecal metabolites effectively discriminate inflammatory bowel disease (IBD) and show differential associations with diet. Metabolomics and AI-based models, including explainable AI (XAI), play crucial roles in understanding IBD. Using datasets from the UK Biobank and the Human Microbiome Project Phase II IBD Multi'omics Database (HMP2 IBDMDB), this study uses multiple machine learning (ML) classifiers and Shapley additive explanations (SHAP)-based XAI to prioritize plasma and fecal metabolites and analyze their diet correlations. Key findings include the identification of discriminative metabolites like glycoprotein acetyl and albumin in plasma, as well as nicotinic acid metabolites andurobilin in feces. Fecal metabolites provided a more robust disease predictor model (AUC [95%]: 0.93 [0.87-0.99]) compared to plasma metabolites (AUC [95%]: 0.74 [0.69-0.79]), with stronger and more group-differential diet-metabolite associations in feces. The study validates known metabolite associations and highlights the impact of IBD on the interplay between gut microbial metabolites and diet.},
}

@article {pmid39027091,
year = {2024},
author = {Li, J and Li, J and Liu, Y and Zeng, J and Liu, Y and Wu, Y},
title = {Large-scale bidirectional Mendelian randomization study identifies new gut microbiome significantly associated with immune thrombocytopenic purpura.},
journal = {Frontiers in microbiology},
volume = {15},
number = {},
pages = {1423951},
pmid = {39027091},
issn = {1664-302X},
abstract = {INTRODUCTION: A variety of studies have shown a link between the gut microbiota and autoimmune diseases, but the causal relationship with Henoch-Schönlein purpura (HSP) and immune thrombocytopenic purpura (ITP) is unknown.

METHODS: This study investigated the bidirectional causality between gut microbiota and HSP and ITP using Mendelian randomization (MR). Large-scale genetic data of gut microbiota at phylum to species level from the MiBioGen consortium and the Dutch Microbiome Project were utilized. Genome-wide association studies (GWAS) summary statistics for HSP and ITP came from FinnGen R10. Various MR methods were applied to infer causal relationships, including inverse variance weighted (IVW), maximum likelihood (ML), cML-MA, MR-Egger, weighted median, weighted model, and MR-PRESSO. Multiple sensitivity analyses and Bonferroni correction were conducted to enhance robustness and reliability.

RESULTS: Based on the IVW estimates, 23 bacterial taxa were identified to have suggestive associations with HSP and ITP. Remarkably, after Bonferroni correction, family Alcaligenaceae (OR = 2.86, 95% CI = 1.52-5.37; IVW, p = 1.10 × 10[-3], ML, p = 1.40 × 10[-3]) was significantly associated with ITP as a risk factor, while family Bacteroidales S24 7group (OR = 0.46, 95% CI = 0.29-0.74; IVW, p = 1.40 × 10[-3]) was significantly associated with ITP as a protective factor. No significant associations between HSP and ITP and gut microbiota were found in reverse analyses.

CONCLUSION: Our study provides evidence of causal effects of gut microbiota on HSP and ITP, highlighting the importance of further research to clarify the underlying mechanisms and develop targeted therapeutic interventions for these autoimmune diseases.},
}

@article {pmid38989853,
year = {2024},
author = {Koellsch, C and Poulin, R and Salloum, PM},
title = {Microbial artists: the role of parasite microbiomes in explaining colour polymorphism among amphipods and potential link to host manipulation.},
journal = {Journal of evolutionary biology},
volume = {37},
number = {9},
pages = {1009-1022},
doi = {10.1093/jeb/voae085},
pmid = {38989853},
issn = {1420-9101},
mesh = {Animals ; *Amphipoda/microbiology/parasitology ; *Host-Parasite Interactions ; *Microbiota ; Acanthocephala/genetics/physiology ; Pigmentation/genetics ; Color ; },
abstract = {Parasite infections are increasingly reported to change the microbiome of the parasitized hosts, while parasites bring their own microbes to what can be a multi-dimensional interaction. For instance, a recent hypothesis suggests that the microbial communities harboured by parasites may play a role in the well-documented ability of many parasites to manipulate host phenotype, and explain why the degree to which host phenotype is altered varies among conspecific parasites. Here, we explored whether the microbiomes of both hosts and parasites are associated with variation in host manipulation by parasites. Using colour quantification methods applied to digital images, we investigated colour variation among uninfected Transorchestia serrulata amphipods, as well as amphipods infected with Plagiorhynchus allisonae acanthocephalans and with a dilepidid cestode. We then characterized the bacteriota of amphipod hosts and of their parasites, looking for correlations between host phenotype and the bacterial taxa associated with hosts and parasites. We found large variation in amphipod colours, and weak support for a direct impact of parasites on the colour of their hosts. Conversely, and most interestingly, the parasite's bacteriota was more strongly correlated with colour variation among their amphipod hosts, with potential impact of amphipod-associated bacteria as well. Some bacterial taxa found associated with amphipods and parasites may have the ability to synthesize pigments, and we propose they may interact with colour determination in the amphipods. This study provides correlational support for an association between the parasite's microbiome and the evolution of host manipulation by parasites and host-parasite interactions more generally.},
}

Animals
*Amphipoda/microbiology/parasitology
*Host-Parasite Interactions
*Microbiota
Acanthocephala/genetics/physiology
Pigmentation/genetics
Color

@article {pmid38977973,
year = {2024},
author = {Zhao, Q and Baranova, A and Cao, H and Zhang, F},
title = {Gut microbiome and major depressive disorder: insights from two-sample Mendelian randomization.},
journal = {BMC psychiatry},
volume = {24},
number = {1},
pages = {493},
pmid = {38977973},
issn = {1471-244X},
mesh = {Humans ; *Gastrointestinal Microbiome/genetics ; *Depressive Disorder, Major/microbiology/genetics ; *Mendelian Randomization Analysis ; *Genome-Wide Association Study ; },
abstract = {BACKGROUND: Existing evidence suggests that alterations in the gut microbiome are closely associated with major depressive disorder (MDD). We aimed to reveal the causal relationships between MDD and various microbial taxa in the gut.

METHODS: We used the two-sample Mendelian randomization (TSMR) to explore the bidirectional causal effects between gut microbiota and MDD. The genome-wide association studies summary results of gut microbiota were obtained from two large consortia, the MibioGen consortium and the Dutch Microbiome Project, which we analyzed separately.

RESULTS: Our TSMR analysis identified 10 gut bacterial taxa that were protective against MDD, including phylum Actinobacteria, order Clostridiales, and family Bifidobacteriaceae (OR: 0.96 ∼ 0.98). Ten taxa were associated with an increased risk of MDD, including phyla Firmicutes and Proteobacteria, class Actinobacteria, and genus Alistipes (OR: 1.01 ∼ 1.09). On the other hand, MDD may decrease the abundance of 12 taxa, including phyla Actinobacteria and Firmicutes, families Bifidobacteriaceae and Defluviitaleaceae (OR: 0.63 ∼ 0.88). MDD may increase the abundance of 8 taxa, including phylum Bacteroidetes, genera Parabacteroides, and Bacteroides (OR: 1.12 ∼ 1.43).

CONCLUSIONS: Our study supports that there are mutual causal relationships between certain gut microbiota and the development of MDD suggesting that gut microbiota may be targeted in the treatment of MDD.},
}

Humans
*Gastrointestinal Microbiome/genetics
*Depressive Disorder, Major/microbiology/genetics
*Mendelian Randomization Analysis
*Genome-Wide Association Study

@article {pmid38962750,
year = {2024},
author = {Schweickart, A and Batra, R and Neth, BJ and Martino, C and Shenhav, L and Zhang, AR and Shi, P and Karu, N and Huynh, K and Meikle, PJ and Schimmel, L and Dilmore, AH and Blennow, K and Zetterberg, H and Blach, C and Dorrestein, PC and Knight, R and , and Craft, S and Kaddurah-Daouk, R and Krumsiek, J},
title = {Serum and CSF metabolomics analysis shows Mediterranean Ketogenic Diet mitigates risk factors of Alzheimer's disease.},
journal = {npj metabolic health and disease},
volume = {2},
number = {1},
pages = {15},
pmid = {38962750},
issn = {2948-2828},
support = {R01 AG046171/AG/NIA NIH HHS/United States ; R01 AG069901/AG/NIA NIH HHS/United States ; U19 AG063744/AG/NIA NIH HHS/United States ; P30 AG049638/AG/NIA NIH HHS/United States ; UL1 TR001420/TR/NCATS NIH HHS/United States ; RF1 AG059093/AG/NIA NIH HHS/United States ; U01 AG061359/AG/NIA NIH HHS/United States ; RF1 AG057452/AG/NIA NIH HHS/United States ; RF1 AG058942/AG/NIA NIH HHS/United States ; RF1 AG051550/AG/NIA NIH HHS/United States ; },
abstract = {Alzheimer's disease (AD) is influenced by a variety of modifiable risk factors, including a person's dietary habits. While the ketogenic diet (KD) holds promise in reducing metabolic risks and potentially affecting AD progression, only a few studies have explored KD's metabolic impact, especially on blood and cerebrospinal fluid (CSF). Our study involved participants at risk for AD, either cognitively normal or with mild cognitive impairment. The participants consumed both a modified Mediterranean Ketogenic Diet (MMKD) and the American Heart Association diet (AHAD) for 6 weeks each, separated by a 6-week washout period. We employed nuclear magnetic resonance (NMR)-based metabolomics to profile serum and CSF and metagenomics profiling on fecal samples. While the AHAD induced no notable metabolic changes, MMKD led to significant alterations in both serum and CSF. These changes included improved modifiable risk factors, like increased HDL-C and reduced BMI, reversed serum metabolic disturbances linked to AD such as a microbiome-mediated increase in valine levels, and a reduction in systemic inflammation. Additionally, the MMKD was linked to increased amino acid levels in the CSF, a breakdown of branched-chain amino acids (BCAAs), and decreased valine levels. Importantly, we observed a strong correlation between metabolic changes in the CSF and serum, suggesting a systemic regulation of metabolism. Our findings highlight that MMKD can improve AD-related risk factors, reverse some metabolic disturbances associated with AD, and align metabolic changes across the blood-CSF barrier.},
}

@article {pmid38927665,
year = {2024},
author = {Li, X and Xu, B and Yang, H and Zhu, Z},
title = {Gut Microbiota, Human Blood Metabolites, and Esophageal Cancer: A Mendelian Randomization Study.},
journal = {Genes},
volume = {15},
number = {6},
pages = {},
pmid = {38927665},
issn = {2073-4425},
mesh = {Humans ; *Mendelian Randomization Analysis ; *Esophageal Neoplasms/genetics/microbiology/blood ; *Gastrointestinal Microbiome/genetics ; *Genome-Wide Association Study ; Metabolome ; },
abstract = {BACKGROUND: Unbalances in the gut microbiota have been proposed as a possible cause of esophageal cancer (ESCA), yet the exact causal relationship remains unclear.

PURPOSE: To investigate the potential causal relationship between the gut microbiota and ESCA with Mendelian randomization (MR) analysis.

METHODS: Genome-wide association studies (GWASs) of 207 gut microbial taxa (5 phyla, 10 classes, 13 orders, 26 families, 48 genera, and 105 species) and 205 gut microbiota metabolic pathways conducted by the Dutch Microbiome Project (DMP) and a FinnGen cohort GWAS of esophageal cancer specified the summary statistics. To investigate the possibility of a mediation effect between the gut microbiota and ESCA, mediation MR analyses were performed for 1091 blood metabolites and 309 metabolite ratios.

RESULTS: MR analysis indicated that the relative abundance of 10 gut microbial taxa was associated with ESCA but all the 12 gut microbiota metabolic pathways with ESCA indicated no statistically significant association existing. Two blood metabolites and a metabolite ratio were discovered to be mediating factors in the pathway from gut microbiota to ESCA.

CONCLUSION: This research indicated the potential mediating effects of blood metabolites and offered genetic evidence in favor of a causal correlation between gut microbiota and ESCA.},
}

Humans
*Mendelian Randomization Analysis
*Esophageal Neoplasms/genetics/microbiology/blood
*Gastrointestinal Microbiome/genetics
*Genome-Wide Association Study
Metabolome

@article {pmid38909071,
year = {2024},
author = {Pechlivanis, N and Karakatsoulis, G and Kyritsis, K and Tsagiopoulou, M and Sgardelis, S and Kappas, I and Psomopoulos, F},
title = {Microbial co-occurrence network demonstrates spatial and climatic trends for global soil diversity.},
journal = {Scientific data},
volume = {11},
number = {1},
pages = {672},
pmid = {38909071},
issn = {2052-4463},
mesh = {*Soil Microbiology ; *Microbiota ; *Climate ; Bacteria ; Biodiversity ; },
abstract = {Despite recent research efforts to explore the co-occurrence patterns of diverse microbes within soil microbial communities, a substantial knowledge-gap persists regarding global climate influences on soil microbiota behaviour. Comprehending co-occurrence patterns within distinct geoclimatic groups is pivotal for unravelling the ecological structure of microbial communities, that are crucial for preserving ecosystem functions and services. Our study addresses this gap by examining global climatic patterns of microbial diversity. Using data from the Earth Microbiome Project, we analyse a meta-community co-occurrence network for bacterial communities. This method unveils substantial shifts in topological features, highlighting regional and climatic trends. Arid, Polar, and Tropical zones show lower diversity but maintain denser networks, whereas Temperate and Cold zones display higher diversity alongside more modular networks. Furthermore, it identifies significant co-occurrence patterns across diverse climatic regions. Central taxa associated with different climates are pinpointed, highlighting climate's pivotal role in community structure. In conclusion, our study identifies significant correlations between microbial interactions in diverse climatic regions, contributing valuable insights into the intricate dynamics of soil microbiota.},
}

*Soil Microbiology
*Microbiota
*Climate
Bacteria
Biodiversity

@article {pmid38878076,
year = {2024},
author = {Jawanda, IK and Soni, T and Kumari, S and Prabha, V},
title = {The evolving facets of vaginal microbiota transplantation: reinvigorating the unexplored frontier amid complex challenges.},
journal = {Archives of microbiology},
volume = {206},
number = {7},
pages = {306},
pmid = {38878076},
issn = {1432-072X},
mesh = {Animals ; Female ; Humans ; Anti-Bacterial Agents/therapeutic use ; *Dysbiosis/microbiology/therapy ; Lactobacillus ; *Microbiota ; *Probiotics/administration & dosage ; *Vagina/microbiology ; },
abstract = {In an age of cutting-edge sequencing methods and worldwide endeavors such as The Human Microbiome Project and MetaHIT, the human microbiome stands as a complex and diverse community of microorganisms. A central theme in current scientific inquiry revolves around reinstating a balanced microbial composition, referred to as "eubiosis," as a targeted approach for treating vast array of diseases. Vaginal Microbiota Transplantation (VMT), inspired by the success of fecal microbiota transplantation, emerges as an innovative therapy addressing vaginal dysbacteriosis by transferring the complete microbiota from a healthy donor. Antibiotics, while effective, pose challenges with adverse effects, high recurrence rates, and potential harm to beneficial Lactobacillus strains. Continued antibiotic usage also sparks worries regarding the development of resistant strains. Probiotics, though showing promise, exhibit inconsistency in treating multifactorial diseases, and concerns linger about their suitability for diverse genetic backgrounds. Given the recurrent challenges associated with antibiotic and probiotic treatments, VMT emerges as an imperative alternative, offering a unique and promising avenue for efficiently and reliably managing vaginal dysbiosis among a majority of women. This review critically evaluates findings from both animal and human studies, offering nuanced insights into the efficacy and challenges of VMT. An extensive analysis of clinical trials, provides a current overview of ongoing and completed trials, shedding light on the evolving clinical landscape and therapeutic potential of VMT. Delving into the origins, mechanisms, and optimized protocols of VMT, the review underscores the imperative for sustained research efforts to advance this groundbreaking gynecological therapy.},
}

Animals
Female
Humans
Anti-Bacterial Agents/therapeutic use
*Dysbiosis/microbiology/therapy
Lactobacillus
*Microbiota
*Probiotics/administration & dosage
*Vagina/microbiology

@article {pmid38855762,
year = {2024},
author = {Huang, Y and Kang, Z and He, Y and Qiu, Y and Song, Y and Liu, W},
title = {Association between gut microbiota and common overlapping gastrointestinal disorders: a bidirectional two-sample Mendelian randomization study.},
journal = {Frontiers in microbiology},
volume = {15},
number = {},
pages = {1343564},
pmid = {38855762},
issn = {1664-302X},
abstract = {BACKGROUND: The main functional gastrointestinal disorders (FGIDs) include functional dyspepsia (FD) and irritable bowel syndrome (IBS), which often present overlapping symptoms with gastroesophageal reflux disease (GERD), posing a challenge for clinical diagnosis and treatment. The gut microbiota is closely associated with FGIDs and GERD, although the causal relationship has not been fully elucidated. Therefore, we aimed to investigate the potential causal relationship using bidirectional two-sample Mendelian randomization (MR) analysis.

MATERIALS AND METHODS: The genetic data of the 211 gut microbiota were obtained from the MiBioGen consortium (N = 14,306, from phylum to genus level) and species level of gut microbiota were acquired from the Dutch Microbiome Project (N = 7,738). For FD and IBS, we utilized the FinnGen consortium, whereas, for GERD data analysis, we obtained the IEU OpenGWAS project. The inverse-variance weighted (IVW) method was used as the primary method to calculate causal effect values. Sensitivity analyses were also performed to confirm the robustness of the primary findings of the MR analyses. Moreover, a reverse MR analysis was conducted to assess the likelihood of reverse causality.

RESULTS: Combining the results of the preliminary and sensitivity analyses, we identified that 8 gut microbial taxa were associated with FD. Genus Lachnospiraceae NK4A136 group (p = 3.63 × 10[-3]) and genus Terrisporobacter (p = 1.13 × 10[-3]) were strongly associated with FD. At the same time, we found that 8 gut microbial taxa were associated with IBS. Family Prevotellaceae (p = 2.44 × 10[-3]) and species Clostridium leptum (p = 7.68 × 10[-3]) display a robust correlation with IBS. In addition, 5 gut microbial taxa were associated with GERD using the IVW approach. In the reverse MR analysis, 2 gut microbial taxa were found to be associated with FD, 5 gut microbial taxa were found to be associated with IBS, and 21 gut microbial taxa were found to be associated with GERD.

CONCLUSION: The study reveals the potential causal effects of specific microbial taxa on FD, IBS, and GERD and may offer novel insights into the diagnosis and treatment of these conditions.},
}

@article {pmid38849944,
year = {2024},
author = {Ornish, D and Madison, C and Kivipelto, M and Kemp, C and McCulloch, CE and Galasko, D and Artz, J and Rentz, D and Lin, J and Norman, K and Ornish, A and Tranter, S and DeLamarter, N and Wingers, N and Richling, C and Kaddurah-Daouk, R and Knight, R and McDonald, D and Patel, L and Verdin, E and E Tanzi, R and Arnold, SE},
title = {Effects of intensive lifestyle changes on the progression of mild cognitive impairment or early dementia due to Alzheimer's disease: a randomized, controlled clinical trial.},
journal = {Alzheimer's research & therapy},
volume = {16},
number = {1},
pages = {122},
pmid = {38849944},
issn = {1758-9193},
support = {P30 AG062429/AG/NIA NIH HHS/United States ; GC-202102-2021459//The Alzheimer's Drug Discovery Foundation/ ; funded by NIA U19AG063744 & U01AG061359 & R01AG081322//Alzheimer Gut Microbiome Project/ ; },
mesh = {Humans ; Male ; Female ; Aged ; *Cognitive Dysfunction ; *Alzheimer Disease/psychology ; *Disease Progression ; Aged, 80 and over ; *Life Style ; Middle Aged ; Dementia/psychology ; Amyloid beta-Peptides/blood ; Neuropsychological Tests ; Treatment Outcome ; },
abstract = {BACKGROUND: Evidence links lifestyle factors with Alzheimer's disease (AD). We report the first randomized, controlled clinical trial to determine if intensive lifestyle changes may beneficially affect the progression of mild cognitive impairment (MCI) or early dementia due to AD.

METHODS: A 1:1 multicenter randomized controlled phase 2 trial, ages 45-90 with MCI or early dementia due to AD and a Montreal Cognitive Assessment (MoCA) score of 18 or higher. The primary outcome measures were changes in cognition and function tests: Clinical Global Impression of Change (CGIC), Alzheimer's Disease Assessment Scale (ADAS-Cog), Clinical Dementia Rating-Sum of Boxes (CDR-SB), and Clinical Dementia Rating Global (CDR-G) after 20 weeks of an intensive multidomain lifestyle intervention compared to a wait-list usual care control group. ADAS-Cog, CDR-SB, and CDR-Global scales were compared using a Mann-Whitney-Wilcoxon rank-sum test, and CGIC was compared using Fisher's exact test. Secondary outcomes included plasma Aβ42/40 ratio, other biomarkers, and correlating lifestyle with the degree of change in these measures.

RESULTS: Fifty-one AD patients enrolled, mean age 73.5. No significant differences in any measures at baseline. Only two patients withdrew. All patients had plasma Aβ42/40 ratios <0.0672 at baseline, strongly supporting AD diagnosis. After 20 weeks, significant between-group differences in the CGIC (p= 0.001), CDR-SB (p= 0.032), and CDR Global (p= 0.037) tests and borderline significance in the ADAS-Cog test (p= 0.053). CGIC, CDR Global, and ADAS-Cog showed improvement in cognition and function and CDR-SB showed significantly less progression, compared to the control group which worsened in all four measures. Aβ42/40 ratio increased in the intervention group and decreased in the control group (p = 0.003). There was a significant correlation between lifestyle and both cognitive function and the plasma Aβ42/40 ratio. The microbiome improved only in the intervention group (p <0.0001).

CONCLUSIONS: Comprehensive lifestyle changes may significantly improve cognition and function after 20 weeks in many patients with MCI or early dementia due to AD.

TRIAL REGISTRATION: Approved by Western Institutional Review Board on 12/31/2017 (#20172897) and by Institutional Review Boards of all sites. This study was registered retrospectively with clinicaltrials.gov on October 8, 2020 (NCT04606420, ID: 20172897).},
}

Humans
Male
Female
Aged
*Cognitive Dysfunction
*Alzheimer Disease/psychology
*Disease Progression
Aged, 80 and over
*Life Style
Middle Aged
Dementia/psychology
Amyloid beta-Peptides/blood
Neuropsychological Tests
Treatment Outcome

@article {pmid38849517,
year = {2024},
author = {Jansen, R and Milaneschi, Y and Schranner, D and Kastenmuller, G and Arnold, M and Han, X and Dunlop, BW and , and Rush, AJ and Kaddurah-Daouk, R and Penninx, BWJH},
title = {The metabolome-wide signature of major depressive disorder.},
journal = {Molecular psychiatry},
volume = {29},
number = {12},
pages = {3722-3733},
pmid = {38849517},
issn = {1476-5578},
support = {636310017//ZonMw (Netherlands Organisation for Health Research and Development)/ ; },
mesh = {Humans ; *Depressive Disorder, Major/metabolism/genetics ; Female ; Male ; *Metabolome ; Adult ; Middle Aged ; Metabolomics/methods ; Netherlands ; Lipid Metabolism/physiology/genetics ; Cohort Studies ; },
abstract = {Major Depressive Disorder (MDD) is a common, frequently chronic condition characterized by substantial molecular alterations and pathway dysregulations. Single metabolite and targeted metabolomics platforms have revealed several metabolic alterations in depression, including energy metabolism, neurotransmission, and lipid metabolism. More comprehensive coverage of the metabolome is needed to further specify metabolic dysregulations in depression and reveal previously untargeted mechanisms. Here, we measured 820 metabolites using the metabolome-wide Metabolon platform in 2770 subjects from a large Dutch clinical cohort with extensive clinical phenotyping (1101 current MDD, 868 remitted MDD, 801 healthy controls) at baseline, which were repeated in 1805 subjects at 6-year follow up (327 current MDD, 1045 remitted MDD, 433 healthy controls). MDD diagnosis was based on DSM-IV psychiatric interviews. Depression severity was measured with the Inventory of Depressive Symptomatology Self-report. Associations between metabolites and MDD status and depression severity were assessed at baseline and at 6-year follow-up. At baseline, 139 and 126 metabolites were associated with current MDD status and depression severity, respectively, with 79 overlapping metabolites. Adding body mass index and lipid-lowering medication to the models changed results only marginally. Among the overlapping metabolites, 34 were confirmed in internal replication analyses using 6-year follow-up data. Downregulated metabolites were enriched with long-chain monounsaturated (P = 6.7e-07) and saturated (P = 3.2e-05) fatty acids; upregulated metabolites were enriched with lysophospholipids (P = 3.4e-4). Mendelian randomization analyses using genetic instruments for metabolites (N = 14,000) and MDD (N = 800,000) showed that genetically predicted higher levels of the lysophospholipid 1-linoleoyl-GPE (18:2) were associated with greater risk of depression. The identified metabolome-wide profile of depression indicated altered lipid metabolism with downregulation of long-chain fatty acids and upregulation of lysophospholipids, for which causal involvement was suggested using genetic tools. This metabolomics signature offers a window on depression pathophysiology and a potential access point for the development of novel therapeutic approaches.},
}

Humans
*Depressive Disorder, Major/metabolism/genetics
Female
Male
*Metabolome
Adult
Middle Aged
Metabolomics/methods
Netherlands
Lipid Metabolism/physiology/genetics
Cohort Studies

@article {pmid38792577,
year = {2024},
author = {Koo, H and Morrow, CD},
title = {Bacteroidales-Specific Antimicrobial Genes Can Influence the Selection of the Dominant Fecal Strain of Bacteroides vulgatus and Bacteroides uniformis from the Gastrointestinal Tract Microbial Community.},
journal = {Life (Basel, Switzerland)},
volume = {14},
number = {5},
pages = {},
pmid = {38792577},
issn = {2075-1729},
abstract = {Bacteroides vulgatus and Bacteroides uniformis are known to be abundant in the human fecal microbial community. Although these strains typically remain stable over time in humans, disruption of this microbial community following antibiotics resulted in the transient change to new strains suggesting that a complex, dynamic strain community exists in humans. To further study the selection of dominant fecal microbial strains from the gastrointestinal tract (GIT) community, we analyzed three longitudinal metagenomic sequencing data sets using BLAST+ to identify genes encoding Bacteroidales-specific antimicrobial proteins (BSAP) that have known functions to restrict species-specific replication of B. uniformis (BSAP-2) or B. vulgatus (BSAP-3) and have been postulated to provide a competitive advantage in microbial communities. In the HMP (Human Microbiome Project) data set, we found fecal samples from individuals had B. vulgatus or B. uniformis with either complete or deleted BSAP genes that did not change over time. We also examined fecal samples from two separate longitudinal data sets of individuals who had been given either single or multiple antibiotics. The BSAP gene pattern from most individuals given either single or multiple antibiotics recovered to be the same as the pre-antibiotic strain. However, in a few individuals, we found incomplete BSAP-3 genes at early times during the recovery that were replaced by B. vulgatus with the complete BSAP-3 gene, consistent with the function of the BSAP to specifically restrict Bacteroides spp. The results of these studies provide insights into the fluxes that occur in the Bacteroides spp. GIT community following perturbation and the dynamics of the selection of a dominant fecal strain of Bacteroides spp.},
}

@article {pmid38765682,
year = {2024},
author = {Chen, Z and Wang, Z and Ma, H and Bao, H and Jiang, T and Yang, T and Ma, S},
title = {Immune cells mediated the causal relationship between the gut microbiota and lung cancer: a Mendelian randomization study.},
journal = {Frontiers in microbiology},
volume = {15},
number = {},
pages = {1390722},
pmid = {38765682},
issn = {1664-302X},
abstract = {INTRODUCTION: The gut microbiota (GM) influences the occurrence and progression of lung cancer (LC), with potential involvement of immune cells (IC). We aimed to investigate the causal impact of GM on LC and identify potential immune cell mediators.

METHODS: The utilized data for the Genome-Wide Association Studies (GWAS) were summarized as follows: gut microbiota data from the Dutch Microbiome Project (DMP) (N = 7,738), lung cancer data from the Transdisciplinary Research in Cancer of the Lung (TRICL) and International Lung Cancer Consortium (ILCCO) (Ncase = 29,266, Ncontrol = 56,450) included four types of cancer: NSCLC, LUAD, LUSC, and SCLC, and immune cell data from European populations (N = 3,757). We employed bi-directional two-sample univariable Mendelian randomization (UVMR), multivariable Mendelian randomization (MVMR), and mediation analysis to assess the causal relationship between GM and LC and potential immune cell mediators.

RESULTS: Bi-directional UVMR analysis revealed that 24 gut microbiota species can affect LC, while LC can affect the abundance of 17 gut microbiota species. Mediation analysis demonstrated that six immune cells mediated the causal relationships of seven gut microbiota species on LC: "CCR7 on naive CD8+ T cell" mediated the causal relationship between s_Alistipes_putredinis and LUAD, with a mediation proportion of 9.5% and P = 0.018; "IgD- CD27- B cell %lymphocyte" mediated the causal relationships between g_Gordonibacter and s_Gordonibacter_pamelaeae with LUSC, with mediation proportions of 11.8% and 11.9%, respectively and P = 0.029; "CD20- CD38- B cell %lymphocyte" mediated the causal relationship between s_Bacteroides_clarus and SCLC, with a mediation proportion of 13.8% and P = 0.005; "CD20 on IgD+ CD38- unswitched memory B cell" mediated the causal relationship between s_Streptococcus_thermophilus and SCLC, with a mediation proportion of 14.1% and P = 0.023; "HLA DR on CD14- CD16+ monocyte" mediated the causal relationship between s_Bifidobacterium_bifidum and SCLC, with a mediation proportion of 8.7% and P = 0.012; "CD45 on Granulocytic Myeloid-Derived Suppressor Cells" mediated the causal relationship between f_Lactobacillaceae and SCLC, with a mediation proportion of 4.0% and P = 0.021.

CONCLUSION: This Mendelian randomization study identified several specific gut microbiotas that exhibit causal relationships with lung cancer and potentially mediate immune cells.},
}

@article {pmid38745153,
year = {2024},
author = {Liu, Y and Yu, J and Yang, Y and Han, B and Wang, Q and Du, S},
title = {Investigating the causal relationship of gut microbiota with GERD and BE: a bidirectional mendelian randomization.},
journal = {BMC genomics},
volume = {25},
number = {1},
pages = {471},
pmid = {38745153},
issn = {1471-2164},
support = {7204303//Beijing Natural Science Foundation/ ; 7204303//Beijing Natural Science Foundation/ ; 7204303//Beijing Natural Science Foundation/ ; 7204303//Beijing Natural Science Foundation/ ; 7204303//Beijing Natural Science Foundation/ ; 7204303//Beijing Natural Science Foundation/ ; },
mesh = {*Mendelian Randomization Analysis ; *Gastrointestinal Microbiome/genetics ; *Gastroesophageal Reflux/microbiology ; Humans ; *Barrett Esophagus/microbiology/genetics ; Risk Factors ; Polymorphism, Single Nucleotide ; },
abstract = {BACKGROUND: Gut microbiota(GM) have been proven associated with lots of gastrointestinal diseases, but its causal relationship with Gastroesophageal reflux disease(GERD) and Barrett's esophagus(BE) hasn't been explored. We aimed to uncover the causal relation between GM and GERD/BE and potential mediators by utilizing Mendelian Randomization(MR) analysis.

METHODS: Summary statistics of GM(comprising 301 bacteria taxa and 205 metabolism pathways) were extracted from MiBioGen Consortium(N = 18,340) and Dutch Microbiome Project(N = 7,738), GERD and BE from a multitrait meta-analysis(NGERD=602,604, NBE=56,429). Bidirectional two-sample MR analysis and linkage disequilibrium score regression(LDSC) were used to explore the genetic correlation between GM and GERD/BE. Mediation MR analysis was performed for the risk factors of GERD/BE, including Body mass index(BMI), weight, type 2 diabetes, major depressive disorder(MDD), smoking initiation, alcohol consumption, and dietary intake(including carbohydrate, sugar, fat, protein intake), to detect the potential mediators between GM and GERD/BE.

RESULTS: 11 bacterial taxa and 13 metabolism pathways were found associated with GERD, and 18 taxa and 5 pathways exhibited causal relationship with BE. Mediation MR analysis suggested weight and BMI played a crucial role in these relationships. LDSC identified 1 taxon and 4 metabolism pathways related to GERD, and 1 taxon related to BE. Specie Faecalibacterium prausnitzii had a suggestive impact on both GERD(OR = 1.087, 95%CI = 1.01-1.17) and BE(OR = 1.388, 95%CI = 1.03-1.86) and LDSC had determined their correlation. Reverse MR indicated that BE impacted 10 taxa and 4 pathways.

CONCLUSIONS: This study established a causal link between gut microbiota and GERD/BE, and identified the probable mediators. It offers new insights into the role of gut microbiota in the development and progression of GERD and BE in the host.},
}

*Mendelian Randomization Analysis
*Gastrointestinal Microbiome/genetics
*Gastroesophageal Reflux/microbiology
Humans
*Barrett Esophagus/microbiology/genetics
Risk Factors
Polymorphism, Single Nucleotide

@article {pmid38740275,
year = {2024},
author = {Long, AR and Mortara, EL and Mendoza, BN and Fink, EC and Sacco, FX and Ciesla, MJ and Stack, TMM},
title = {Sequence similarity network analysis of drug- and dye-modifying azoreductase enzymes found in the human gut microbiome.},
journal = {Archives of biochemistry and biophysics},
volume = {757},
number = {},
pages = {110025},
pmid = {38740275},
issn = {1096-0384},
support = {P20 GM103430/GM/NIGMS NIH HHS/United States ; },
mesh = {Humans ; *Nitroreductases/metabolism/genetics ; *Gastrointestinal Microbiome ; *NADH, NADPH Oxidoreductases/metabolism/genetics/chemistry ; Coloring Agents/metabolism ; Molecular Docking Simulation ; Substrate Specificity ; Sulfasalazine ; Bacterial Proteins/metabolism/genetics/chemistry ; Kinetics ; Clostridiales/enzymology/genetics ; Azo Compounds/metabolism/chemistry ; },
abstract = {Drug metabolism by human gut microbes is often exemplified by azo bond reduction in the anticolitic prodrug sulfasalazine. Azoreductase activity is often found in incubations with cell cultures or ex vivo gut microbiome samples and contributes to the xenobiotic metabolism of drugs and food additives. Applying metagenomic studies to personalized medicine requires knowledge of the genes responsible for sulfasalazine and other drug metabolism, and candidate genes and proteins for drug modifications are understudied. A representative gut-abundant azoreductase from Anaerotignum lactatifermentan DSM 14214 efficiently reduces sulfasalazine and another drug, phenazopyridine, but could not reduce all azo-bonded drugs in this class. We used enzyme kinetics to characterize this enzyme for its NADH-dependent reduction of these drugs and food additives and performed computational docking to provide the groundwork for understanding substrate specificity in this family. We performed an analysis of the Flavodoxin-like fold InterPro family (IPR003680) by computing a sequence similarity network to classify distinct subgroups of the family and then performed chemically-guided functional profiling to identify proteins that are abundant in the NIH Human Microbiome Project dataset. This strategy aims to reduce the number of unique azoreductases needed to characterize one protein family in the diverse set of potential drug- and dye-modifying activities found in the human gut microbiome.},
}

Humans
*Nitroreductases/metabolism/genetics
*Gastrointestinal Microbiome
*NADH, NADPH Oxidoreductases/metabolism/genetics/chemistry
Coloring Agents/metabolism
Molecular Docking Simulation
Substrate Specificity
Sulfasalazine
Bacterial Proteins/metabolism/genetics/chemistry
Kinetics
Clostridiales/enzymology/genetics
Azo Compounds/metabolism/chemistry

@article {pmid38736244,
year = {2024},
author = {Chen, J and Wang, X and Yang, J and Huang, J and Xie, M and Su, Z and Jiang, F},
title = {Association between gut microbiota and central retinal artery occlusion: A two-sample Mendelian randomization study.},
journal = {Indian journal of ophthalmology},
volume = {72},
number = {Suppl 5},
pages = {S801-S808},
pmid = {38736244},
issn = {1998-3689},
mesh = {Humans ; *Gastrointestinal Microbiome ; *Mendelian Randomization Analysis ; *Retinal Artery Occlusion/diagnosis/microbiology/epidemiology ; *Genome-Wide Association Study ; Risk Factors ; Polymorphism, Single Nucleotide ; },
abstract = {PURPOSE: The gut microbiota might be closely related to central retinal artery occlusion (CRAO), but the causality has not been well defined. Two-sample Mendelian randomization (MR) study was used to reveal the potential causal effect between the gut microbiota and CRAO.

METHODS: Data for gut microbiota were obtained from the genome-wide association studies of the Dutch Microbiome Project (DMP) (n = 7738) and the MiBioGen consortium (n = 18,340), and data on CRAO were obtained from samples of FinnGen project (546 cases and 344,569 controls). Causalities of exposures and outcomes were explored mainly using the inverse variance weighted method. In addition, multiple sensitivity analyses including MR-Egger, weighted median (WM), simple mode, weighted mode, and MR Pleiotropy RESidual Sum and Outlier were simultaneously applied to validate the final results.

RESULTS: We identified three microbial pathways (two risk factors/one protective factor) and seven microbial taxa (two risk factors/five protective factors) associated with CRAO in the DMP study. Based on the data from the MiBioGen consortium, we identified seven microbial taxa (two risk factors/five protective factors) associated with CRAO, including the Eubacterium genus, which was consistently identified as a risk factor in both the DMP and the MiBioGen consortium MR analyses.

CONCLUSION: Our study implicates the potential causal effects of specific microbial taxa and pathways on CRAO, potentially providing new insights into the prevention and treatment of CRAO through specific gut microbial taxa and pathway. Since our conclusion is a hypothesis derived from secondary genome-wide association studies (GWAS) data analysis, further research is needed for confirmation.},
}

Humans
*Gastrointestinal Microbiome
*Mendelian Randomization Analysis
*Retinal Artery Occlusion/diagnosis/microbiology/epidemiology
*Genome-Wide Association Study
Risk Factors
Polymorphism, Single Nucleotide

@article {pmid38720308,
year = {2024},
author = {Zhou, J and Zhu, D and Xu, Y and Chen, C and Wang, K},
title = {Genetically predicted gut microbiota mediate the association between plasma lipidomics and primary sclerosing cholangitis.},
journal = {BMC gastroenterology},
volume = {24},
number = {1},
pages = {158},
pmid = {38720308},
issn = {1471-230X},
support = {No. JDY2023018//the Jiangsu University Medical Education Collaborative Innovation Fund Project/ ; No. Z2021010//the Medical Research Project of Jiangsu Health Commission/ ; },
mesh = {Humans ; *Cholangitis, Sclerosing/blood/microbiology/genetics ; *Gastrointestinal Microbiome/genetics ; *Lipidomics ; *Mendelian Randomization Analysis ; Male ; Genome-Wide Association Study ; Female ; Phosphatidylcholines/blood ; Dysbiosis/blood ; Middle Aged ; Adult ; },
abstract = {BACKGROUND: Primary sclerosing cholangitis (PSC) is a complex disease with pathogenic mechanisms that remain to be elucidated. Previous observational studies with small sample sizes have reported associations between PSC, dyslipidemia, and gut microbiota dysbiosis. However, the causality of these associations is uncertain, and there has been no systematic analysis to date.

METHODS: The datasets comprise data on PSC, 179 lipid species, and 412 gut microbiota species. PSC data (n = 14,890) were sourced from the International PSC Study Group, while the dataset pertaining to plasma lipidomics originated from a study involving 7174 Finnish individuals. Data on gut microbiota species were derived from the Dutch Microbiome Project study, which conducted a genome-wide association study involving 7738 participants. Furthermore, we employed a two-step Mendelian randomization (MR) analysis to quantify the proportion of the effect of gut microbiota-mediated lipidomics on PSC.

RESULTS: Following a rigorous screening process, our MR analysis revealed a causal relationship between higher levels of gene-predicted Phosphatidylcholine (O-16:1_18:1) (PC O-16:1_18:1) and an increased risk of developing PSC (inverse variance-weighted method, odds ratio (OR) 1.30, 95% confidence interval (CI) 1.03-1.63). There is insufficient evidence to suggest that gene-predicted PSC impacts the levels of PC O-16:1_18:1 (OR 1.01, 95% CI 0.98-1.05). When incorporating gut microbiota data into the analysis, we found that Eubacterium rectale-mediated genetic prediction explains 17.59% of the variance in PC O-16:1_18:1 levels.

CONCLUSION: Our study revealed a causal association between PC O-16:1_18:1 levels and PSC, with a minor portion of the effect mediated by Eubacterium rectale. This study aims to further explore the pathogenesis of PSC and identify promising therapeutic targets. For patients with PSC who lack effective treatment options, the results are encouraging.},
}

Humans
*Cholangitis, Sclerosing/blood/microbiology/genetics
*Gastrointestinal Microbiome/genetics
*Lipidomics
*Mendelian Randomization Analysis
Male
Genome-Wide Association Study
Female
Phosphatidylcholines/blood
Dysbiosis/blood
Middle Aged
Adult

@article {pmid38694799,
year = {2024},
author = {Zhang, Y and Xue, G and Wang, F and Zhang, J and Xu, L and Yu, C},
title = {The impact of antibiotic exposure on antibiotic resistance gene dynamics in the gut microbiota of inflammatory bowel disease patients.},
journal = {Frontiers in microbiology},
volume = {15},
number = {},
pages = {1382332},
pmid = {38694799},
issn = {1664-302X},
abstract = {BACKGROUND: While antibiotics are commonly used to treat inflammatory bowel disease (IBD), their widespread application can disturb the gut microbiota and foster the emergence and spread of antibiotic resistance. However, the dynamic changes to the human gut microbiota and direction of resistance gene transmission under antibiotic effects have not been clearly elucidated.

METHODS: Based on the Human Microbiome Project, a total of 90 fecal samples were collected from 30 IBD patients before, during and after antibiotic treatment. Through the analysis workflow of metagenomics, we described the dynamic process of changes in bacterial communities and resistance genes pre-treatment, during and post-treatment. We explored potential consistent relationships between gut microbiota and resistance genes, and established gene transmission networks among species before and after antibiotic use.

RESULTS: Exposure to antibiotics can induce alterations in the composition of the gut microbiota in IBD patients, particularly a reduction in probiotics, which gradually recovers to a new steady state after cessation of antibiotics. Network analyses revealed intra-phylum transfers of resistance genes, predominantly between taxonomically close organisms. Specific resistance genes showed increased prevalence and inter-species mobility after antibiotic cessation.

CONCLUSION: This study demonstrates that antibiotics shape the gut resistome through selective enrichment and promotion of horizontal gene transfer. The findings provide insights into ecological processes governing resistance gene dynamics and dissemination upon antibiotic perturbation of the microbiota. Optimizing antibiotic usage may help limit unintended consequences like increased resistance in gut bacteria during IBD management.},
}

@article {pmid38674735,
year = {2024},
author = {Isokpehi, RD and Kim, Y and Krejci, SE and Trivedi, VD},
title = {Ecological Trait-Based Digital Categorization of Microbial Genomes for Denitrification Potential.},
journal = {Microorganisms},
volume = {12},
number = {4},
pages = {},
pmid = {38674735},
issn = {2076-2607},
support = {U41 HG006941/HG/NHGRI NIH HHS/United States ; U41HG006941/NH/NIH HHS/United States ; },
abstract = {Microorganisms encode proteins that function in the transformations of useful and harmful nitrogenous compounds in the global nitrogen cycle. The major transformations in the nitrogen cycle are nitrogen fixation, nitrification, denitrification, anaerobic ammonium oxidation, and ammonification. The focus of this report is the complex biogeochemical process of denitrification, which, in the complete form, consists of a series of four enzyme-catalyzed reduction reactions that transforms nitrate to nitrogen gas. Denitrification is a microbial strain-level ecological trait (characteristic), and denitrification potential (functional performance) can be inferred from trait rules that rely on the presence or absence of genes for denitrifying enzymes in microbial genomes. Despite the global significance of denitrification and associated large-scale genomic and scholarly data sources, there is lack of datasets and interactive computational tools for investigating microbial genomes according to denitrification trait rules. Therefore, our goal is to categorize archaeal and bacterial genomes by denitrification potential based on denitrification traits defined by rules of enzyme involvement in the denitrification reduction steps. We report the integration of datasets on genome, taxonomic lineage, ecosystem, and denitrifying enzymes to provide data investigations context for the denitrification potential of microbial strains. We constructed an ecosystem and taxonomic annotated denitrification potential dataset of 62,624 microbial genomes (866 archaea and 61,758 bacteria) that encode at least one of the twelve denitrifying enzymes in the four-step canonical denitrification pathway. Our four-digit binary-coding scheme categorized the microbial genomes to one of sixteen denitrification traits including complete denitrification traits assigned to 3280 genomes from 260 bacteria genera. The bacterial strains with complete denitrification potential pattern included Arcobacteraceae strains isolated or detected in diverse ecosystems including aquatic, human, plant, and Mollusca (shellfish). The dataset on microbial denitrification potential and associated interactive data investigations tools can serve as research resources for understanding the biochemical, molecular, and physiological aspects of microbial denitrification, among others. The microbial denitrification data resources produced in our research can also be useful for identifying microbial strains for synthetic denitrifying communities.},
}

@article {pmid38596649,
year = {2024},
author = {Zhang, H and Ma, L and Peng, W and Wang, B and Sun, Y},
title = {Association between gut microbiota and onset of type 2 diabetes mellitus: a two-sample Mendelian randomization study.},
journal = {Frontiers in cellular and infection microbiology},
volume = {14},
number = {},
pages = {1327032},
pmid = {38596649},
issn = {2235-2988},
mesh = {Humans ; *Diabetes Mellitus, Type 2/genetics ; *Gastrointestinal Microbiome/genetics ; Genome-Wide Association Study ; Mendelian Randomization Analysis ; *Microbiota ; *Sulfalene ; Meta-Analysis as Topic ; },
abstract = {AIM: Mendelian randomization (MR) analysis has been used in the exploration of the role of gut microbiota (GM) in type 2 diabetes mellitus (T2DM); however, it was limited to the genus level. This study herein aims to investigate the relationship of GM, especially at the species level, with T2DM in order to provide some evidence for further exploration of more specific GM taxa and pathway abundance in T2DM.

METHODS: This two-sample MR study was based on the summary statistics of GM from the available genome-wide association study (GWAS) meta-analysis conducted by the MiBioGen consortium as well as the Dutch Microbiome Project (DMP), whereas the summary statistics of T2DM were obtained from the FinnGen consortium released data. Inverse variance weighted (IVW), MR-Egger, strength test (F), and weighted median methods were used to examine the causal association between GM and the onset of T2DM. Cochran's Q statistics was employed to quantify the heterogeneity of instrumental variables. Bonferroni's correction was conducted to correct the bias of multiple testing. We also performed reverse causality analysis.

RESULTS: The corrected IVW estimates suggested the increased relative abundance of family Oxalobacteraceae (OR = 1.0704) and genus Oxalobacter (OR = 1.0874), respectively, were associated with higher odds of T2DM, while that of species faecis (OR = 0.9460) had a negative relationship with T2DM. The relationships of class Betaproteobacteria, family Lactobacillaceae, species finegoldii, and species longum with T2DM were also significant according to the IVW results (all P < 0.05).

CONCLUSIONS: GM had a potential causal association with T2DM, especially species faecis, finegoldii, and longum. Further studies are still needed to clarify certain results that are contradictory with previous findings.},
}

Humans
*Diabetes Mellitus, Type 2/genetics
*Gastrointestinal Microbiome/genetics
Genome-Wide Association Study
Mendelian Randomization Analysis
*Microbiota
*Sulfalene
Meta-Analysis as Topic

@article {pmid38586050,
year = {2024},
author = {Ho, PY and Huang, KC},
title = {Challenges in quantifying functional redundancy and selection in microbial communities.},
journal = {bioRxiv : the preprint server for biology},
volume = {},
number = {},
pages = {},
doi = {10.1101/2024.03.26.586891},
pmid = {38586050},
issn = {2692-8205},
abstract = {Microbiomes can exhibit large variations in species abundances but high reproducibility in abundances of functional units, an observation often considered evidence for functional redundancy. Based on such reduction in functional variability, selection is hypothesized to act on functional units in these ecosystems. However, the link between functional redundancy and selection remains unclear. Here, we show that reduction in functional variability does not always imply selection on functional profiles. We propose empirical null models to account for the confounding effects of statistical averaging and bias toward environment-independent beneficial functions. We apply our models to existing data sets, and find that the abundances of metabolic groups within microbial communities from bromeliad foliage do not exhibit any evidence of the previously hypothesized functional selection. By contrast, communities of soil bacteria or human gut commensals grown in vitro are selected for metabolic capabilities. By separating the effects of averaging and functional bias on functional variability, we find that the appearance of functional selection in gut microbiome samples from the Human Microbiome Project is artifactual, and that there is no evidence of selection for any molecular function represented by KEGG orthology. These concepts articulate a basic framework for quantifying functional redundancy and selection, advancing our understanding of the mapping between microbiome taxonomy and function.},
}

@article {pmid38577200,
year = {2024},
author = {Salvadori, M and Rosso, G},
title = {Update on the gut microbiome in health and diseases.},
journal = {World journal of methodology},
volume = {14},
number = {1},
pages = {89196},
pmid = {38577200},
issn = {2222-0682},
abstract = {The Human Microbiome Project, Earth Microbiome Project, and next-generation sequencing have advanced novel genome association, host genetic linkages, and pathogen identification. The microbiome is the sum of the microbes, their genetic information, and their ecological niche. This study will describe how millions of bacteria in the gut affect the human body in health and disease. The gut microbiome changes in relation with age, with an increase in Bacteroidetes and Firmicutes. Host and environmental factors affecting the gut microbiome are diet, drugs, age, smoking, exercise, and host genetics. In addition, changes in the gut microbiome may affect the local gut immune system and systemic immune system. In this study, we discuss how the microbiome may affect the metabolism of healthy subjects or may affect the pathogenesis of metabolism-generating metabolic diseases. Due to the high number of publications on the argument, from a methodologically point of view, we decided to select the best papers published in referred journals in the last 3 years. Then we selected the previously published papers. The major goals of our study were to elucidate which microbiome and by which pathways are related to healthy and disease conditions.},
}

@article {pmid38563656,
year = {2024},
author = {Zhu, J and Yin, J and Chen, J and Hu, M and Lu, W and Wang, H and Zhang, H and Chen, W},
title = {Integrative analysis with microbial modelling and machine learning uncovers potential alleviators for ulcerative colitis.},
journal = {Gut microbes},
volume = {16},
number = {1},
pages = {2336877},
pmid = {38563656},
issn = {1949-0984},
mesh = {Animals ; Mice ; Humans ; *Colitis, Ulcerative ; *Gastrointestinal Microbiome ; *Inflammatory Bowel Diseases ; *Colitis ; Machine Learning ; },
abstract = {Ulcerative colitis (UC) is a challenging form of inflammatory bowel disease, and its etiology is intricately linked to disturbances in the gut microbiome. To identify the potential alleviators of UC, we employed an integrative analysis combining microbial community modeling with advanced machine learning techniques. Using metagenomics data sourced from the Integrated Human Microbiome Project, we constructed individualized microbiome community models for each participant. Our analysis highlighted a significant decline in both α and β-diversity of strain-level microbial populations in UC subjects compared to controls. Distinct differences were also observed in the predicted fecal metabolite profiles and strain-to-metabolite contributions between the two groups. Using tree-based machine learning models, we successfully identified specific microbial strains and their associated metabolites as potential alleviators of UC. Notably, our experimental validation using a dextran sulfate sodium-induced UC mouse model demonstrated that the administration of Parabacteroides merdae ATCC 43,184 and N-acetyl-D-mannosamine provided notable relief from colitis symptoms. In summary, our study underscores the potential of an integrative approach to identify novel therapeutic avenues for UC, paving the way for future targeted interventions.},
}

Animals
Mice
Humans
*Colitis, Ulcerative
*Gastrointestinal Microbiome
*Inflammatory Bowel Diseases
*Colitis
Machine Learning

@article {pmid38562901,
year = {2024},
author = {Dilmore, AH and Kuplicki, R and McDonald, D and Kumar, M and Estaki, M and Youngblut, N and Tyakht, A and Ackermann, G and Blach, C and MahmoudianDehkordi, S and Dunlop, BW and Bhattacharyya, S and Guinjoan, S and Mandaviya, P and Ley, RE and Kaddaruh-Dauok, R and Paulus, MP and Knight, R and , },
title = {Medication Use is Associated with Distinct Microbial Features in Anxiety and Depression.},
journal = {bioRxiv : the preprint server for biology},
volume = {},
number = {},
pages = {},
pmid = {38562901},
issn = {2692-8205},
support = {R01 AG046171/AG/NIA NIH HHS/United States ; U19 AG063744/AG/NIA NIH HHS/United States ; RF1 AG059093/AG/NIA NIH HHS/United States ; U01 AG061359/AG/NIA NIH HHS/United States ; RF1 AG057452/AG/NIA NIH HHS/United States ; RF1 AG058942/AG/NIA NIH HHS/United States ; RF1 AG051550/AG/NIA NIH HHS/United States ; },
abstract = {This study investigated the relationship between gut microbiota and neuropsychiatric disorders (NPDs), specifically anxiety disorder (ANXD) and/or major depressive disorder (MDD), as defined by DSM-IV or V criteria. The study also examined the influence of medication use, particularly antidepressants and/or anxiolytics, classified through the Anatomical Therapeutic Chemical (ATC) Classification System, on the gut microbiota. Both 16S rRNA gene amplicon sequencing and shallow shotgun sequencing were performed on DNA extracted from 666 fecal samples from the Tulsa-1000 and NeuroMAP CoBRE cohorts. The results highlight the significant influence of medication use; antidepressant use is associated with significant differences in gut microbiota beta diversity and has a larger effect size than NPD diagnosis. Next, specific microbes were associated with ANXD and MDD, highlighting their potential for non-pharmacological intervention. Finally, the study demonstrated the capability of Random Forest classifiers to predict diagnoses of NPD and medication use from microbial profiles, suggesting a promising direction for the use of gut microbiota as biomarkers for NPD. The findings suggest that future research on the gut microbiota's role in NPD and its interactions with pharmacological treatments are needed.},
}

@article {pmid38559015,
year = {2024},
author = {Maghini, DG and Oduaran, OH and Wirbel, J and Olubayo, LAI and Smyth, N and Mathema, T and Belger, CW and Agongo, G and Boua, PR and Choma, SS and Gómez-Olivé, FX and Kisiangani, I and Mashaba, GR and Micklesfield, L and Mohamed, SF and Nonterah, EA and Norris, S and Sorgho, H and Tollman, S and Wafawanaka, F and Tluway, F and Ramsay, M and Bhatt, AS and Hazelhurst, S},
title = {Expanding the human gut microbiome atlas of Africa.},
journal = {bioRxiv : the preprint server for biology},
volume = {},
number = {},
pages = {},
pmid = {38559015},
issn = {2692-8205},
support = {R01 AI148623/AI/NIAID NIH HHS/United States ; D43 TW010540/TW/FIC NIH HHS/United States ; R01 AI143757/AI/NIAID NIH HHS/United States ; U54 HG006938/HG/NHGRI NIH HHS/United States ; S10 OD023452/OD/NIH HHS/United States ; },
abstract = {Population studies are crucial in understanding the complex interplay between the gut microbiome and geographical, lifestyle, genetic, and environmental factors. However, populations from low- and middle-income countries, which represent ~84% of the world population, have been excluded from large-scale gut microbiome research. Here, we present the AWI-Gen 2 Microbiome Project, a cross-sectional gut microbiome study sampling 1,803 women from Burkina Faso, Ghana, Kenya, and South Africa. By intensively engaging with communities that range from rural and horticultural to urban informal settlements and post-industrial, we capture population diversity that represents a far greater breadth of the world's population. Using shotgun metagenomic sequencing, we find that study site explains substantially more microbial variation than disease status. We identify taxa with strong geographic and lifestyle associations, including loss of Treponema and Cryptobacteroides species and gain of Bifidobacterium species in urban populations. We uncover a wealth of prokaryotic and viral novelty, including 1,005 new bacterial metagenome-assembled genomes, and identify phylogeography signatures in Treponema succinifaciens. Finally, we find a microbiome signature of HIV infection that is defined by several taxa not previously associated with HIV, including Dysosmobacter welbionis and Enterocloster sp. This study represents the largest population-representative survey of gut metagenomes of African individuals to date, and paired with extensive clinical biomarkers, demographic data, and lifestyle information, provides extensive opportunity for microbiome-related discovery and research.},
}

@article {pmid38553666,
year = {2024},
author = {Ma, ZS},
title = {Towards a unified medical microbiome ecology of the OMU for metagenomes and the OTU for microbes.},
journal = {BMC bioinformatics},
volume = {25},
number = {1},
pages = {137},
pmid = {38553666},
issn = {1471-2105},
mesh = {Animals ; Humans ; Metagenome ; *Microbiota/genetics ; *Gastrointestinal Microbiome ; Biodiversity ; Sequence Analysis, DNA ; Metagenomics/methods ; },
abstract = {BACKGROUND: Metagenomic sequencing technologies offered unprecedented opportunities and also challenges to microbiology and microbial ecology particularly. The technology has revolutionized the studies of microbes and enabled the high-profile human microbiome and earth microbiome projects. The terminology-change from microbes to microbiomes signals that our capability to count and classify microbes (microbiomes) has achieved the same or similar level as we can for the biomes (macrobiomes) of plants and animals (macrobes). While the traditional investigations of macrobiomes have usually been conducted through naturalists' (Linnaeus & Darwin) naked eyes, and aerial and satellite images (remote-sensing), the large-scale investigations of microbiomes have been made possible by DNA-sequencing-based metagenomic technologies. Two major types of metagenomic sequencing technologies-amplicon sequencing and whole-genome (shotgun sequencing)-respectively generate two contrastingly different categories of metagenomic reads (data)-OTU (operational taxonomic unit) tables representing microorganisms and OMU (operational metagenomic unit), a new term coined in this article to represent various cluster units of metagenomic genes.

RESULTS: The ecological science of microbiomes based on the OTU representing microbes has been unified with the classic ecology of macrobes (macrobiomes), but the unification based on OMU representing metagenomes has been rather limited. In a previous series of studies, we have demonstrated the applications of several classic ecological theories (diversity, composition, heterogeneity, and biogeography) to the studies of metagenomes. Here I push the envelope for the unification of OTU and OMU again by demonstrating the applications of metacommunity assembly and ecological networks to the metagenomes of human gut microbiomes. Specifically, the neutral theory of biodiversity (Sloan's near neutral model), Ning et al.stochasticity framework, core-periphery network, high-salience skeleton network, special trio-motif, and positive-to-negative ratio are applied to analyze the OMU tables from whole-genome sequencing technologies, and demonstrated with seven human gut metagenome datasets from the human microbiome project.

CONCLUSIONS: All of the ecological theories demonstrated previously and in this article, including diversity, composition, heterogeneity, stochasticity, and complex network analyses, are equally applicable to OMU metagenomic analyses, just as to OTU analyses. Consequently, I strongly advocate the unification of OTU/OMU (microbiomes) with classic ecology of plants and animals (macrobiomes) in the context of medical ecology.},
}

Animals
Humans
Metagenome
*Microbiota/genetics
*Gastrointestinal Microbiome
Biodiversity
Sequence Analysis, DNA
Metagenomics/methods

@article {pmid38549112,
year = {2024},
author = {Edwin, NR and Fitzpatrick, AH and Brennan, F and Abram, F and O'Sullivan, O},
title = {An in-depth evaluation of metagenomic classifiers for soil microbiomes.},
journal = {Environmental microbiome},
volume = {19},
number = {1},
pages = {19},
pmid = {38549112},
issn = {2524-6372},
support = {SFI/16/RC/3835//VistaMilk/ ; Ref: 2020019//Teagasc Walsh Scholarship Programme/ ; },
abstract = {BACKGROUND: Recent endeavours in metagenomics, exemplified by projects such as the human microbiome project and TARA Oceans, have illuminated the complexities of microbial biomes. A robust bioinformatic pipeline and meticulous evaluation of their methodology have contributed to the success of these projects. The soil environment, however, with its unique challenges, requires a specialized methodological exploration to maximize microbial insights. A notable limitation in soil microbiome studies is the dearth of soil-specific reference databases available to classifiers that emulate the complexity of soil communities. There is also a lack of in-vitro mock communities derived from soil strains that can be assessed for taxonomic classification accuracy.

RESULTS: In this study, we generated a custom in-silico mock community containing microbial genomes commonly observed in the soil microbiome. Using this mock community, we simulated shotgun sequencing data to evaluate the performance of three leading metagenomic classifiers: Kraken2 (supplemented with Bracken, using a custom database derived from GTDB-TK genomes along with its own default database), Kaiju, and MetaPhlAn, utilizing their respective default databases for a robust analysis. Our results highlight the importance of optimizing taxonomic classification parameters, database selection, as well as analysing trimmed reads and contigs. Our study showed that classifiers tailored to the specific taxa present in our samples led to fewer errors compared to broader databases including microbial eukaryotes, protozoa, or human genomes, highlighting the effectiveness of targeted taxonomic classification. Notably, an optimal classifier performance was achieved when applying a relative abundance threshold of 0.001% or 0.005%. The Kraken2 supplemented with bracken, with a custom database demonstrated superior precision, sensitivity, F1 score, and overall sequence classification. Using a custom database, this classifier classified 99% of in-silico reads and 58% of real-world soil shotgun reads, with the latter identifying previously overlooked phyla using a custom database.

CONCLUSION: This study underscores the potential advantages of in-silico methodological optimization in metagenomic analyses, especially when deciphering the complexities of soil microbiomes. We demonstrate that the choice of classifier and database significantly impacts microbial taxonomic profiling. Our findings suggest that employing Kraken2 with Bracken, coupled with a custom database of GTDB-TK genomes and fungal genomes at a relative abundance threshold of 0.001% provides optimal accuracy in soil shotgun metagenome analysis.},
}

@article {pmid38506069,
year = {2024},
author = {Li, J and Zheng, G and Jiang, D and Deng, C and Zhang, Y and Ma, Y and Su, J},
title = {Mendelian randomization analysis reveals a causal effect of Streptococcus salivarius on diabetic retinopathy through regulating host fasting glucose.},
journal = {Journal of cellular and molecular medicine},
volume = {28},
number = {7},
pages = {e18200},
pmid = {38506069},
issn = {1582-4934},
support = {KYQD20201001//Scientific Research Foundation for Talents of Wenzhou Medical University/ ; LR19C060001//Natural Science Foundation of Zhejiang Province/ ; 2023M732679//China Postdoctoral Science Foundation/ ; 32200535//National Natural Science Foundation of China/ ; 61871294//National Natural Science Foundation of China/ ; 82172882//National Natural Science Foundation of China/ ; },
mesh = {Adult ; Humans ; Mendelian Randomization Analysis ; *Streptococcus salivarius ; *Diabetic Retinopathy ; Genome-Wide Association Study ; Fasting ; Glucose ; *Diabetes Mellitus ; },
abstract = {Diabetic retinopathy (DR) is one of leading causes of vision loss in adults with increasing prevalence worldwide. Increasing evidence has emphasized the importance of gut microbiome in the aetiology and development of DR. However, the causal relationship between gut microbes and DR remains largely unknown. To investigate the causal associations of DR with gut microbes and DR risk factors, we employed two-sample Mendelian Randomization (MR) analyses to estimate the causal effects of 207 gut microbes on DR outcomes. Inputs for MR included Genome-wide Association Study (GWAS) summary statistics of 207 taxa of gut microbes (the Dutch Microbiome Project) and 21 risk factors for DR. The GWAS summary statistics data of DR was from the FinnGen Research Project. Data analysis was performed in May 2023. We identified eight bacterial taxa that exhibited significant causal associations with DR (FDR < 0.05). Among them, genus Collinsella and species Collinsella aerofaciens were associated with increased risk of DR, while the species Bacteroides faecis, Burkholderiales bacterium_1_1_47, Ruminococcus torques, Streptococcus salivarius, genus Burkholderiales_noname and family Burkholderiales_noname showed protective effects against DR. Notably, we found that the causal effect of species Streptococcus salivarius on DR was mediated through the level of host fasting glucose, a well-established risk factor for DR. Our results reveal that specific gut microbes may be causally linked to DR via mediating host metabolic risk factors, highlighting potential novel therapeutic or preventive targets for DR.},
}

Adult
Humans
Mendelian Randomization Analysis
*Streptococcus salivarius
*Diabetic Retinopathy
Genome-Wide Association Study
Fasting
Glucose
*Diabetes Mellitus

@article {pmid38497260,
year = {2024},
author = {Singh, A and Luallen, RJ},
title = {Understanding the factors regulating host-microbiome interactions using Caenorhabditis elegans.},
journal = {Philosophical transactions of the Royal Society of London. Series B, Biological sciences},
volume = {379},
number = {1901},
pages = {20230059},
pmid = {38497260},
issn = {1471-2970},
support = {R35 GM146836/GM/NIGMS NIH HHS/United States ; },
mesh = {Animals ; Humans ; Caenorhabditis elegans/genetics ; *Microbiota ; *Gastrointestinal Microbiome ; },
abstract = {The Human Microbiome Project was a research programme that successfully identified associations between microbial species and healthy or diseased individuals. However, a major challenge identified was the absence of model systems for studying host-microbiome interactions, which would increase our capacity to uncover molecular interactions, understand organ-specificity and discover new microbiome-altering health interventions. Caenorhabditis elegans has been a pioneering model organism for over 70 years but was largely studied in the absence of a microbiome. Recently, ecological sampling of wild nematodes has uncovered a large amount of natural genetic diversity as well as a slew of associated microbiota. The field has now explored the interactions of C. elegans with its associated gut microbiome, a defined and non-random microbial community, highlighting its suitability for dissecting host-microbiome interactions. This core microbiome is being used to study the impact of host genetics, age and stressors on microbiome composition. Furthermore, single microbiome species are being used to dissect molecular interactions between microbes and the animal gut. Being amenable to health altering genetic and non-genetic interventions, C. elegans has emerged as a promising system to generate and test new hypotheses regarding host-microbiome interactions, with the potential to uncover novel paradigms relevant to other systems. This article is part of the theme issue 'Sculpting the microbiome: how host factors determine and respond to microbial colonization'.},
}

Animals
Humans
Caenorhabditis elegans/genetics
*Microbiota
*Gastrointestinal Microbiome

@article {pmid38491556,
year = {2024},
author = {Elradi, M and Ahmed, AI and Saleh, AM and Abdel-Raouf, KMA and Berika, L and Daoud, Y and Amleh, A},
title = {Derivation of a novel antimicrobial peptide from the Red Sea Brine Pools modified to enhance its anticancer activity against U2OS cells.},
journal = {BMC biotechnology},
volume = {24},
number = {1},
pages = {14},
pmid = {38491556},
issn = {1472-6750},
mesh = {Animals ; Mice ; Humans ; Caspase 3/genetics/metabolism/pharmacology ; Survivin/genetics/metabolism/pharmacology ; Escherichia coli/metabolism ; Antimicrobial Peptides ; Cell Line, Tumor ; Indian Ocean ; Ki-67 Antigen/metabolism ; Staphylococcus aureus ; Apoptosis ; Peptides/pharmacology/metabolism ; *Antineoplastic Agents/pharmacology/chemistry ; *Anti-Infective Agents/pharmacology ; Annexins/pharmacology ; *Salts ; },
abstract = {Cancer associated drug resistance is a major cause for cancer aggravation, particularly as conventional therapies have presented limited efficiency, low specificity, resulting in long term deleterious side effects. Peptide based drugs have emerged as potential alternative cancer treatment tools due to their selectivity, ease of design and synthesis, safety profile, and low cost of manufacturing. In this study, we utilized the Red Sea metagenomics database, generated during AUC/KAUST Red Sea microbiome project, to derive a viable anticancer peptide (ACP). We generated a set of peptide hits from our library that shared similar composition to ACPs. A peptide with a homeodomain was selected, modified to improve its anticancer properties, verified to maintain high anticancer properties, and processed for further in-silico prediction of structure and function. The peptide's anticancer properties were then assessed in vitro on osteosarcoma U2OS cells, through cytotoxicity assay (MTT assay), scratch-wound healing assay, apoptosis/necrosis detection assay (Annexin/PI assay), RNA expression analysis of Caspase 3, KI67 and Survivin, and protein expression of PARP1. L929 mouse fibroblasts were also assessed for cytotoxicity treatment. In addition, the antimicrobial activity of the peptide was also examined on E coli and S. aureus, as sample representative species of the human bacterial microbiome, by examining viability, disk diffusion, morphological assessment, and hemolytic analysis. We observed a dose dependent cytotoxic response from peptide treatment of U2OS, with a higher tolerance in L929s. Wound closure was debilitated in cells exposed to the peptide, while annexin fluorescent imaging suggested peptide treatment caused apoptosis as a major mode of cell death. Caspase 3 gene expression was not altered, while KI67 and Survivin were both downregulated in peptide treated cells. Additionally, PARP-1 protein analysis showed a decrease in expression with peptide exposure. The peptide exhibited minimal antimicrobial activity on critical human microbiome species E. coli and S. aureus, with a low inhibition rate, maintenance of structural morphology and minimal hemolytic impact. These findings suggest our novel peptide displayed preliminary ACP properties against U2OS cells, through limited specificity, while triggering apoptosis as a primary mode of cell death and while having minimal impact on the microbiological species E. coli and S. aureus.},
}

Animals
Mice
Humans
Caspase 3/genetics/metabolism/pharmacology
Survivin/genetics/metabolism/pharmacology
Escherichia coli/metabolism
Antimicrobial Peptides
Cell Line, Tumor
Indian Ocean
Ki-67 Antigen/metabolism
Staphylococcus aureus
Apoptosis
Peptides/pharmacology/metabolism
*Antineoplastic Agents/pharmacology/chemistry
*Anti-Infective Agents/pharmacology
Annexins/pharmacology
*Salts

@article {pmid38486697,
year = {2024},
author = {Xiao, QA and Qin, L and Yu, J and Hu, YT and Ai, LF and Wang, DC and Xia, X and Zhang, XL},
title = {The causality between gut microbiome and chronic regional pain: a Mendelian randomization analysis.},
journal = {Frontiers in microbiology},
volume = {15},
number = {},
pages = {1329521},
pmid = {38486697},
issn = {1664-302X},
abstract = {BACKGROUND: Numerous investigations have underscored the causal effect between chronic pain (CP) and gut microbiota, jointly contributing to the onset and development of widespread CP. Nonetheless, there was still uncertainty about the causal effect between gut microbiota and chronic regional pain (CRP).

METHODS: Genome-wide association study (GWAS) summary data of gut microbial taxa (MiBioGen Consortium: 211 microbiotas and the Dutch Microbiome Project: 207 microbiotas) and eight types of CRP were used to reveal the causal effect between persistent pain in a specific region of the body and gut microbiota. A two-sample bidirectional Mendelian randomization (MR) design was used. In order to ensure the accuracy of the results, multiple sensitivity analyses were employed.

RESULTS: This study uncovered significant causal associations between six gut microbial taxa and three types of CRP (forward: Genus Parabacteroides for general pain; Class Bacteroidia, Order Bacteroidales, and Phylum Bacteroidetes for back pain. Reverse: knee pain for Genus Howardella and Order Coriobacteriales) by forward and reverse MR analysis. These findings had been verified by a rigorous Bonferroni correction. Furthermore, this research identified 19 microbial taxa that exhibited potential correlations with four types of CRP. There are no significant or potential gut microbiotas that were associated with other types of CRP, including fascial pain, stomach or abdominal pain, and hip pain.

CONCLUSION: This two-sample bidirectional MR analysis unveiled the causality between gut microbial taxa and eight CRP conditions. The findings reveal the interplay between CRP and 6 gut microbiotas while also delineating 19 potential specific microbial taxa corresponding to diverse locations of persistent pain.},
}

@article {pmid38481313,
year = {2024},
author = {Wang, J and Teng, M and Feng, R and Su, X and Xu, K and Wang, J and Wang, G and Zhang, Y and Xu, P},
title = {Large-scale causal analysis of gut microbiota and six common complications of diabetes: a mendelian randomization study.},
journal = {Diabetology & metabolic syndrome},
volume = {16},
number = {1},
pages = {66},
pmid = {38481313},
issn = {1758-5996},
abstract = {BACKGROUND: This study aimed to reveal the association between the gut microbiota (GM) and six diabetic complications: diabetic hypoglycemia; ketoacidosis; nephropathy; neuropathy; retinopathy; and Charcot's foot.

METHODS: GM data were obtained from the MiBioGen consortium and Dutch Microbiome Project while data on the six diabetic complications were obtained from the FinnGen consortium. Two-sample Mendelian randomization (TSMR) was performed to explore the association between GM and the common diabetic complications. Inverse MR analysis was conducted to examine the effect of diabetic complications on the identified GM. Sensitivity tests were conducted to validate the stability of the results. Finally, multivariate MR (MVMR) was performed to determine whether GM had a direct influence on the diabetic complications.

RESULTS: After multiple corrections, the inverse variance weighted (IVW) results predicted 61 suggestive markers between GM and six diabetic complications. In particular, the IVW results revealed that the Bacteroidia class and Bacteroidales order were positively associated with diabetic hypoglycemia while the Verrucomicrobiae class and Verrucomicrobiales order were positively associated with diabetic nephropathy. Based on the replication analysis, these results were identified to be stable. MVMR showed that the results remained stable after accounting for traditional risk factors.

CONCLUSION: Extensive causal associations were found between GM and diabetic complications, which may provide new insights into the mechanisms of microbiome-mediated complications of diabetes.},
}

@article {pmid38474213,
year = {2024},
author = {Hong, BY and Driscoll, M and Gratalo, D and Jarvie, T and Weinstock, GM},
title = {Improved DNA Extraction and Amplification Strategy for 16S rRNA Gene Amplicon-Based Microbiome Studies.},
journal = {International journal of molecular sciences},
volume = {25},
number = {5},
pages = {},
pmid = {38474213},
issn = {1422-0067},
mesh = {Humans ; RNA, Ribosomal, 16S/genetics ; Sequence Analysis, DNA/methods ; Genes, rRNA ; Reproducibility of Results ; DNA, Bacterial/genetics ; *Microbiota/genetics ; Bacteria/genetics ; High-Throughput Nucleotide Sequencing/methods ; },
abstract = {Next-generation sequencing technology has driven the rapid advancement of human microbiome studies by enabling community-level sequence profiling of microbiomes. Although all microbiome sequencing methods depend on recovering the DNA from a sample as a first critical step, lysis methods can be a major determinant of microbiome profile bias. Gentle enzyme-based DNA preparation methods preserve DNA quality but can bias the results by failing to open difficult-to-lyse bacteria. Mechanical methods like bead beating can also bias DNA recovery because the mechanical energy required to break tougher cell walls may shear the DNA of the more easily lysed microbes, and shearing can vary depending on the time and intensity of beating, influencing reproducibility. We introduce a non-mechanical, non-enzymatic, novel rapid microbial DNA extraction procedure suitable for 16S rRNA gene-based microbiome profiling applications that eliminates bead beating. The simultaneous application of alkaline, heat, and detergent ('Rapid' protocol) to milligram quantity samples provided consistent representation across the population of difficult and easily lysed bacteria equal to or better than existing protocols, producing sufficient high-quality DNA for full-length 16S rRNA gene PCR. The novel 'Rapid' method was evaluated using mock bacterial communities containing both difficult and easily lysed bacteria. Human fecal sample testing compared the novel Rapid method with a standard Human Microbiome Project (HMP) protocol for samples from lung cancer patients and controls. DNA recovered from both methods was analyzed using 16S rRNA gene sequencing of the V1V3 and V4 regions on the Illumina platform and the V1V9 region on the PacBio platform. Our findings indicate that the 'Rapid' protocol consistently yielded higher levels of Firmicutes species, which reflected the profile of the bacterial community structure more accurately, which was confirmed by mock community evaluation. The novel 'Rapid' DNA lysis protocol reduces population bias common to bead beating and enzymatic lysis methods, presenting opportunities for improved microbial community profiling, combined with the reduction in sample input to 10 milligrams or less, and it enables rapid transfer and simultaneous lysis of 96 samples in a standard plate format. This results in a 20-fold reduction in sample handling time and an overall 2-fold time advantage when compared to widely used commercial methods. We conclude that the novel 'Rapid' DNA extraction protocol offers a reliable alternative for preparing fecal specimens for 16S rRNA gene amplicon sequencing.},
}

Humans
RNA, Ribosomal, 16S/genetics
Sequence Analysis, DNA/methods
Genes, rRNA
Reproducibility of Results
DNA, Bacterial/genetics
*Microbiota/genetics
Bacteria/genetics
High-Throughput Nucleotide Sequencing/methods

@article {pmid38467837,
year = {2024},
author = {Bhosle, A and Bae, S and Zhang, Y and Chun, E and Avila-Pacheco, J and Geistlinger, L and Pishchany, G and Glickman, JN and Michaud, M and Waldron, L and Clish, CB and Xavier, RJ and Vlamakis, H and Franzosa, EA and Garrett, WS and Huttenhower, C},
title = {Integrated annotation prioritizes metabolites with bioactivity in inflammatory bowel disease.},
journal = {Molecular systems biology},
volume = {20},
number = {4},
pages = {338-361},
pmid = {38467837},
issn = {1744-4292},
support = {P30 DK040561/DK/NIDDK NIH HHS/United States ; P30 DK043351/DK/NIDDK NIH HHS/United States ; R01 CA230551/CA/NCI NIH HHS/United States ; R24 DK110499/DK/NIDDK NIH HHS/United States ; },
mesh = {Humans ; Animals ; Mice ; *Inflammatory Bowel Diseases/drug therapy/metabolism ; *Colitis ; Metabolome ; Bile Acids and Salts ; },
abstract = {Microbial biochemistry is central to the pathophysiology of inflammatory bowel diseases (IBD). Improved knowledge of microbial metabolites and their immunomodulatory roles is thus necessary for diagnosis and management. Here, we systematically analyzed the chemical, ecological, and epidemiological properties of ~82k metabolic features in 546 Integrative Human Microbiome Project (iHMP/HMP2) metabolomes, using a newly developed methodology for bioactive compound prioritization from microbial communities. This suggested >1000 metabolic features as potentially bioactive in IBD and associated ~43% of prevalent, unannotated features with at least one well-characterized metabolite, thereby providing initial information for further characterization of a significant portion of the fecal metabolome. Prioritized features included known IBD-linked chemical families such as bile acids and short-chain fatty acids, and less-explored bilirubin, polyamine, and vitamin derivatives, and other microbial products. One of these, nicotinamide riboside, reduced colitis scores in DSS-treated mice. The method, MACARRoN, is generalizable with the potential to improve microbial community characterization and provide therapeutic candidates.},
}

Humans
Animals
Mice
*Inflammatory Bowel Diseases/drug therapy/metabolism
*Colitis
Metabolome
Bile Acids and Salts

@article {pmid38340164,
year = {2024},
author = {Osborne, C and Gilbert-Parkes, S and Spiers, G and Lamit, LJ and Lilleskov, EA and Basiliko, N and Watmough, S and , },
title = {Global Patterns of Metal and Other Element Enrichment in Bog and Fen Peatlands.},
journal = {Archives of environmental contamination and toxicology},
volume = {86},
number = {2},
pages = {125-139},
pmid = {38340164},
issn = {1432-0703},
mesh = {Wetlands ; Metals ; *Mercury/analysis ; Soil ; *Environmental Pollutants ; },
abstract = {Peatlands are found on all continents, covering 3% of the global land area. However, the spatial extent and causes of metal enrichment in peatlands is understudied and no attempt has been made to evaluate global patterns of metal enrichment in bog and fen peatlands, despite that certain metals and rare earth elements (REE) arise from anthropogenic sources. We analyzed 368 peat cores sampled in 16 countries across five continents and measured metal and other element concentrations at three depths down to 70 cm as well as estimated cumulative atmospheric S deposition (1850-2009) for each site. Sites were assigned to one of three distinct broadly recognized peatland categories (bog, poor fen, and intermediate-to-moderately rich fen) that varied primarily along a pH gradient. Metal concentrations differed among peatland types, with intermediate-to-moderately rich fens demonstrating the highest concentrations of most metals. Median enrichment factors (EFs; a metric comparing natural and anthropogenic metal deposition) for individual metals were similar among bogs and fens (all groups), with metals likely to be influenced by anthropogenic sources (As, Cd, Co, Cu, Hg, Pb, and Sb) demonstrating median enrichment factors (EFs) > 1.5. Additionally, mean EFs were substantially higher than median values, and the positive correlation (< 0.40) with estimated cumulative atmospheric S deposition, confirmed some level of anthropogenic influence of all pollutant metals except for Hg that was unrelated to S deposition. Contrary to expectations, high EFs were not restricted to pollutant metals, with Mn, K and Rb all exhibiting elevated median EFs that were in the same range as pollutant metals likely due to peatland biogeochemical processes leading to enrichment of these nutrients in surface soil horizons. The global patterns of metal enrichment in bogs and fens identified in this study underscore the importance of these peatlands as environmental archives of metal deposition, but also illustrates that biogeochemical processes can enrich metals in surface peat and EFs alone do not necessarily indicate atmospheric contamination.},
}

Wetlands
Metals
*Mercury/analysis
Soil
*Environmental Pollutants

@article {pmid38285276,
year = {2024},
author = {Fang, M and Liu, W and Wang, Z and Li, J and Hu, S and Li, Z and Chen, W and Zhang, N},
title = {Causal associations between gut microbiota with intervertebral disk degeneration, low back pain, and sciatica: a Mendelian randomization study.},
journal = {European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society},
volume = {33},
number = {4},
pages = {1424-1439},
pmid = {38285276},
issn = {1432-0932},
support = {81972514//National Natural Science Foundation of China/ ; },
mesh = {Humans ; *Sciatica/epidemiology/genetics ; *Intervertebral Disc Degeneration/epidemiology/genetics ; *Low Back Pain/epidemiology/genetics ; *Gastrointestinal Microbiome/genetics ; Mendelian Randomization Analysis ; Genome-Wide Association Study ; *Intervertebral Disc Displacement ; },
abstract = {PURPOSE: Although studies have suggested that gut microbiota may be associated with intervertebral disk disease, their causal relationship is unclear. This study aimed to investigate the causal relationship between the gut microbiota and its metabolic pathways with the risk of intervertebral disk degeneration (IVDD), low back pain (LBP), and sciatica.

METHODS: Genetic variation data for 211 gut microbiota taxa at the phylum to genus level were obtained from the MiBioGen consortium. Genetic variation data for 105 taxa at the species level and 205 metabolic pathways were obtained from the Dutch Microbiome Project. Genetic variation data for disease outcomes were obtained from the FinnGen consortium. The causal relationships between the gut microbiota and its metabolic pathways and the risk of IVDD, LBP, and sciatica were evaluated via Mendelian randomization (MR). The robustness of the results was assessed through sensitivity analysis.

RESULTS: Inverse variance weighting identified 46 taxa and 33 metabolic pathways that were causally related to IVDD, LBP, and sciatica. After correction by weighted median and MR-PRESSO, 15 taxa and nine pathways remained stable. After FDR correction, only the effect of the genus_Eubacterium coprostanoligenes group on IVDD remained stable. Sensitivity analyses showed no evidence of horizontal pleiotropy, heterogeneity, or reverse causation.

CONCLUSION: Some microbial taxa and their metabolic pathways are causally related to IVDD, LBP, and sciatica and may serve as potential intervention targets. This study provides new insights into the mechanisms of gut microbiota-mediated development of intervertebral disk disease.},
}

Humans
*Sciatica/epidemiology/genetics
*Intervertebral Disc Degeneration/epidemiology/genetics
*Low Back Pain/epidemiology/genetics
*Gastrointestinal Microbiome/genetics
Mendelian Randomization Analysis
Genome-Wide Association Study
*Intervertebral Disc Displacement

@article {pmid38284649,
year = {2024},
author = {Hayer, SS and Conrin, M and French, JA and Benson, AK and Alvarez, S and Cooper, K and Fischer, A and Alsafwani, ZW and Gasper, W and Suhr Van Haute, MJ and Hassenstab, HR and Azadmanesh, S and Briardy, M and Gerbers, S and Jabenis, A and Thompson, JL and Clayton, JB},
title = {Antibiotic-induced gut dysbiosis elicits gut-brain axis relevant multi-omic signatures and behavioral and neuroendocrine changes in a nonhuman primate model.},
journal = {Gut microbes},
volume = {16},
number = {1},
pages = {2305476},
pmid = {38284649},
issn = {1949-0984},
support = {K01 OD030514/OD/NIH HHS/United States ; P20 GM103427/GM/NIGMS NIH HHS/United States ; P30 CA036727/CA/NCI NIH HHS/United States ; R25 GM141506/GM/NIGMS NIH HHS/United States ; },
mesh = {Animals ; Humans ; *Anti-Bacterial Agents/toxicity ; Callithrix ; Brain-Gut Axis ; *Gastrointestinal Microbiome ; Dysbiosis/microbiology ; Multiomics ; },
abstract = {Emerging evidence indicates that antibiotic-induced dysbiosis can play an etiological role in the pathogenesis of neuropsychiatric disorders. However, most of this evidence comes from rodent models. The objective of this study was to evaluate if antibiotic-induced gut dysbiosis can elicit changes in gut metabolites and behavior indicative of gut-brain axis disruption in common marmosets (Callithrix jacchus) - a nonhuman primate model often used to study sociability and stress. We were able to successfully induce dysbiosis in marmosets using a custom antibiotic cocktail (vancomycin, enrofloxacin and neomycin) administered orally for 28 days. This gut dysbiosis altered gut metabolite profiles, behavior, and stress reactivity. Increase in gut Fusobacterium spp. post-antibiotic administration was a novel dysbiotic response and has not been observed in any rodent or human studies to date. There were significant changes in concentrations of several gut metabolites which are either neurotransmitters (e.g., GABA and serotonin) or have been found to be moderators of gut-brain axis communication in rodent models (e.g., short-chain fatty acids and bile acids). There was an increase in affiliative behavior and sociability in antibiotic-administered marmosets, which might be a coping mechanism in response to gut dysbiosis-induced stress. Increase in urinary cortisol levels after multiple stressors provides more definitive proof that this model of dysbiosis may cause disrupted communication between gut and brain in common marmosets. This study is a first attempt to establish common marmosets as a novel model to study the impact of severe gut dysbiosis on gut-brain axis cross-talk and behavior.},
}

Animals
Humans
*Anti-Bacterial Agents/toxicity
Callithrix
Brain-Gut Axis
*Gastrointestinal Microbiome
Dysbiosis/microbiology
Multiomics

@article {pmid38233502,
year = {2024},
author = {Chopra, A and Franco-Duarte, R and Rajagopal, A and Choowong, P and Soares, P and Rito, T and Eberhard, J and Jayasinghe, TN},
title = {Exploring the presence of oral bacteria in non-oral sites of patients with cardiovascular diseases using whole metagenomic data.},
journal = {Scientific reports},
volume = {14},
number = {1},
pages = {1476},
pmid = {38233502},
issn = {2045-2322},
support = {2022.00340.CEECIND//Fundação para a Ciência e a Tecnologia/ ; "Contrato-Programa" UIDB/04050/2020//Fundação para a Ciência e a Tecnologia/ ; },
mesh = {Humans ; *Cardiovascular Diseases ; *Microbiota/genetics ; Bacteria/genetics ; Metagenome ; *Plaque, Atherosclerotic ; },
abstract = {Cardiovascular diseases (CVDs) encompass various conditions affecting the heart and its blood vessels and are often linked with oral microbes. Our data analysis aimed to identify oral bacteria from other non-oral sites (i.e., gut, arterial plaque and cultured blood) that could be linked with CVDs. Taxonomic profiling identified bacteria to the species level and compared with the Human Oral Microbiome Database (HOMD). The oral bacteria in the gut, cultured blood and arterial plaque samples were catalogued, with their average frequency calculated for each sample. Additionally, data were filtered by comparison with the Human Microbiome Project (HMP) database. We identified 17,243 microbial species, of which 410 were present in the HOMD database and further denominated as "oral", and were found in at least one gut sample, but only 221 and 169 species were identified in the cultured blood and plaque samples, respectively. Of the 410 species, 153 were present solely in oral-associated environments after comparison with the HMP database, irrespective of their presence in other body sites. Our results suggest a potential connection between the presence of specific species of oral bacterial and occurrence of CVDs. Detecting these oral bacterial species in non-oral sites of patients with CVDs could help uncover the link between oral health and general health, including cardiovascular conditions via bacterial translocation.},
}

Humans
*Cardiovascular Diseases
*Microbiota/genetics
Bacteria/genetics
Metagenome
*Plaque, Atherosclerotic

@article {pmid38168274,
year = {2023},
author = {Liu, R and Wang, Y and Cheng, D},
title = {Micro-DeMix: A mixture beta-multinomial model for investigating the fecal microbiome compositions.},
journal = {bioRxiv : the preprint server for biology},
volume = {},
number = {},
pages = {},
pmid = {38168274},
issn = {2692-8205},
support = {R01 GM145772/GM/NIGMS NIH HHS/United States ; },
abstract = {Extensive research has uncovered the involvement of the human gut microbiome in various facets of human health, including metabolism, nutrition, physiology, and immune function. Researchers often study fecal microbiota as a proxy for understanding the gut microbiome. However, it has been demonstrated that this approach may not suffice to yield a comprehensive understanding of the entire gut microbial community. Emerging research is revealing the heterogeneity of the gut microbiome across different gastrointestinal (GI) locations in both composition and functions. While spatial metagenomics approach has been developed to address these variations in mice, limitations arise when applying it to human-subject research, primarily due to its invasive nature. With these restrictions, we introduce Micro-DeMix, a mixture beta-multinomial model that decomposes the fecal microbiome at compositional level to understand the heterogeneity of the gut microbiome across various GI locations and extract meaningful insights about the biodiversity of the gut microbiome. Moreover, Micro-DeMix facilitates the discovery of differentially abundant microbes between GI regions through a hypothesis testing framework. We utilize the Inflammatory Bowel Disease (IBD) data from the NIH Integrative Human Microbiome Project to demonstrate the effectiveness and efficiency of the proposed Micro-DeMix.},
}

@article {pmid38132705,
year = {2024},
author = {Hoisington, AJ and Stearns-Yoder, KA and Stamper, CE and Holliday, R and Brostow, DP and Penzenik, ME and Forster, JE and Postolache, TT and Lowry, CA and Brenner, LA},
title = {Association of homelessness and diet on the gut microbiome: a United States-Veteran Microbiome Project (US-VMP) study.},
journal = {mSystems},
volume = {9},
number = {1},
pages = {e0102123},
pmid = {38132705},
issn = {2379-5077},
mesh = {Humans ; United States/epidemiology ; *Veterans/psychology ; *Gastrointestinal Microbiome ; *Ill-Housed Persons ; *Microbiota ; Diet ; },
abstract = {Military veterans account for 8% of homeless individuals living in the United States. To highlight associations between history of homelessness and the gut microbiome, we compared the gut microbiome of veterans who reported having a previous experience of homelessness to those from individuals who reported never having experienced a period of homelessness. Moreover, we examined the impact of the cumulative exposure of prior and current homelessness to understand possible associations between these experiences and the gut microbiome. Microbiome samples underwent genomic sequencing and were analyzed based on alpha diversity, beta diversity, and taxonomic differences. Additionally, demographic information, dietary data, and mental health history were collected. A lifetime history of homelessness was found to be associated with alcohol use disorder, substance use disorder, and healthy eating index compared to those without such a history. In terms of differences in gut microbiota, beta diversity was significantly different between veterans who had experienced homelessness and veterans who had never been homeless (P = 0.047, weighted UniFrac), while alpha diversity was similar. The microbial community differences were, in part, driven by a lower relative abundance of Akkermansia in veterans who had experienced homelessness (mean; range [in percentages], 1.07; 0-33.9) compared to veterans who had never been homeless (2.02; 0-36.8) (P = 0.014, ancom-bc2). Additional research is required to facilitate understanding regarding the complex associations between homelessness, the gut microbiome, and mental and physical health conditions, with a focus on increasing understanding regarding the longitudinal impact of housing instability throughout the lifespan.IMPORTANCEAlthough there are known stressors related to homelessness as well as chronic health conditions experienced by those without stable housing, there has been limited work evaluating the associations between microbial community composition and homelessness. We analyzed, for the first time, bacterial gut microbiome associations among those with experiences of homelessness on alpha diversity, beta diversity, and taxonomic differences. Additionally, we characterized the influences of diet, demographic characteristics, military service history, and mental health conditions on the microbiome of veterans with and without any lifetime history of homelessness. Future longitudinal research to evaluate the complex relationships between homelessness, the gut microbiome, and mental health outcomes is recommended. Ultimately, differences in the gut microbiome of individuals experiencing and not experiencing homelessness could assist in identification of treatment targets to improve health outcomes.},
}

Humans
United States/epidemiology
*Veterans/psychology
*Gastrointestinal Microbiome
*Ill-Housed Persons
*Microbiota
Diet

@article {pmid38127919,
year = {2023},
author = {L'Heureux, JE and van der Giezen, M and Winyard, PG and Jones, AM and Vanhatalo, A},
title = {Localisation of nitrate-reducing and highly abundant microbial communities in the oral cavity.},
journal = {PloS one},
volume = {18},
number = {12},
pages = {e0295058},
pmid = {38127919},
issn = {1932-6203},
mesh = {Humans ; *Nitrates/metabolism ; Nitrogen Dioxide ; Mouth/microbiology ; Bacteria ; Saliva/metabolism ; *Microbiota ; Streptococcus ; },
abstract = {The nitrate (NO3-) reducing bacteria resident in the oral cavity have been implicated as key mediators of nitric oxide (NO) homeostasis and human health. NO3--reducing oral bacteria reduce inorganic dietary NO3- to nitrite (NO2-) via the NO3--NO2--NO pathway. Studies of oral NO3--reducing bacteria have typically sampled from either the tongue surface or saliva. The aim of this study was to assess whether other areas in the mouth could contain a physiologically relevant abundance of NO3- reducing bacteria, which may be important for sampling in clinical studies. The bacterial composition of seven oral sample types from 300 individuals were compared using a meta-analysis of the Human Microbiome Project data. This analysis revealed significant differences in the proportions of 20 well-established oral bacteria and highly abundant NO3--reducing bacteria across each oral site. The genera included Actinomyces, Brevibacillus, Campylobacter, Capnocytophaga, Corynebacterium, Eikenella, Fusobacterium, Granulicatella, Haemophilus, Leptotrichia, Microbacterium, Neisseria, Porphyromonas, Prevotella, Propionibacterium, Rothia, Selenomonas, Staphylococcus, Streptococcus and Veillonella. The highest proportion of NO3--reducing bacteria was observed in saliva, where eight of the bacterial genera were found in higher proportion than on the tongue dorsum, whilst the lowest proportions were found in the hard oral surfaces. Saliva also demonstrated higher intra-individual variability and bacterial diversity. This study provides new information on where samples should be taken in the oral cavity to assess the abundance of NO3--reducing bacteria. Taking saliva samples may benefit physiological studies, as saliva contained the highest abundance of NO3- reducing bacteria and is less invasive than other sampling methods. These results inform future studies coupling oral NO3--reducing bacteria research with physiological outcomes affecting human health.},
}

Humans
*Nitrates/metabolism
Nitrogen Dioxide
Mouth/microbiology
Bacteria
Saliva/metabolism
*Microbiota
Streptococcus

@article {pmid38095449,
year = {2024},
author = {Arehart, CH and Sterrett, JD and Garris, RL and Quispe-Pilco, RE and Gignoux, CR and Evans, LM and Stanislawski, MA},
title = {Poly-omic risk scores predict inflammatory bowel disease diagnosis.},
journal = {mSystems},
volume = {9},
number = {1},
pages = {e0067723},
pmid = {38095449},
issn = {2379-5077},
support = {K01 HL157658/HL/NHLBI NIH HHS/United States ; P30 DK048520/DK/NIDDK NIH HHS/United States ; T32 MH016880/MH/NIMH NIH HHS/United States ; },
mesh = {Humans ; *Inflammatory Bowel Diseases/diagnosis ; Metagenomics/methods ; Phenotype ; *Microbiota ; Risk Factors ; },
abstract = {Inflammatory bowel disease (IBD) is characterized by complex etiology and a disrupted colonic ecosystem. We provide a framework for the analysis of multi-omic data, which we apply to study the gut ecosystem in IBD. Specifically, we train and validate models using data on the metagenome, metatranscriptome, virome, and metabolome from the Human Microbiome Project 2 IBD multi-omic database, with 1,785 repeated samples from 130 individuals (103 cases and 27 controls). After splitting the participants into training and testing groups, we used mixed-effects least absolute shrinkage and selection operator regression to select features for each omic. These features, with demographic covariates, were used to generate separate single-omic prediction scores. All four single-omic scores were then combined into a final regression to assess the relative importance of the individual omics and the predictive benefits when considered together. We identified several species, pathways, and metabolites known to be associated with IBD risk, and we explored the connections between data sets. Individually, metabolomic and viromic scores were more predictive than metagenomics or metatranscriptomics, and when all four scores were combined, we predicted disease diagnosis with a Nagelkerke's R[2] of 0.46 and an area under the curve of 0.80 (95% confidence interval: 0.63, 0.98). Our work supports that some single-omic models for complex traits are more predictive than others, that incorporating multiple omic data sets may improve prediction, and that each omic data type provides a combination of unique and redundant information. This modeling framework can be extended to other complex traits and multi-omic data sets.IMPORTANCEComplex traits are characterized by many biological and environmental factors, such that multi-omic data sets are well-positioned to help us understand their underlying etiologies. We applied a prediction framework across multiple omics (metagenomics, metatranscriptomics, metabolomics, and viromics) from the gut ecosystem to predict inflammatory bowel disease (IBD) diagnosis. The predicted scores from our models highlighted key features and allowed us to compare the relative utility of each omic data set in single-omic versus multi-omic models. Our results emphasized the importance of metabolomics and viromics over metagenomics and metatranscriptomics for predicting IBD status. The greater predictive capability of metabolomics and viromics is likely because these omics serve as markers of lifestyle factors such as diet. This study provides a modeling framework for multi-omic data, and our results show the utility of combining multiple omic data types to disentangle complex disease etiologies and biological signatures.},
}

Humans
*Inflammatory Bowel Diseases/diagnosis
Metagenomics/methods
Phenotype
*Microbiota
Risk Factors

@article {pmid38094582,
year = {2023},
author = {Luo, Y and Zhou, Y and Huang, P and Zhang, Q and Luan, F and Peng, Y and Wei, J and Li, N and Wang, C and Wang, X and Zhang, J and Yu, K and Zhao, M and Wang, C},
title = {Causal relationship between gut Prevotellaceae and risk of sepsis: a two-sample Mendelian randomization and clinical retrospective study in the framework of predictive, preventive, and personalized medicine.},
journal = {The EPMA journal},
volume = {14},
number = {4},
pages = {697-711},
pmid = {38094582},
issn = {1878-5077},
abstract = {OBJECTIVE: Gut microbiota is closely related to sepsis. Recent studies have suggested that Prevotellaceae could be associated with intestinal inflammation; however, the causal relationship between Prevotellaceae and sepsis remains uncertain. From the perspective of predictive, preventive, and personalized medicine (PPPM), exploring the causal relationship between gut Prevotellaceae and sepsis could provide opportunity for targeted prevention and personalized treatment.

METHODS: The genome-wide association study (GWAS) summary-level data of Prevotellaceae (N = 7738) and sepsis were obtained from the Dutch Microbiome Project and the UK Biobank (sepsis, 1380 cases; 429,985 controls). MR analysis was conducted to estimate the associations between Prevotellaceae and sepsis risk. The 16S rRNA sequencing analysis was conducted to calculate the relative abundance of Prevotellaceae in sepsis patients to explore the relationship between Prevotellaceae relative abundance and the 28-day mortality.

RESULTS: Genetic liability to f__Prevotellaceae (OR, 1.91; CI, 1.35-2.71; p = 0.0003) was associated with a high risk of sepsis with inverse-variance weighted (IVW). The median Prevotellaceae relative abundance in non-survivors was significantly higher than in survivors (2.34% vs 0.17%, p < 0.001). Multivariate analysis confirmed that Prevotellaceae relative abundance (OR, 1.10; CI, 1.03-1.22; p = 0.027) was an independent factor of 28-day mortality in sepsis patients. ROC curve analysis indicated that Prevotellaceae relative abundance (AUC: 0.787, 95% CI: 0.671-0.902, p = 0.0003) could predict the prognosis of sepsis patients.

CONCLUSION: Our results revealed that Prevotellaceae was causally associated with sepsis and affected the prognosis of sepsis patients. These findings may provide insights to clinicians on developing improved sepsis PPPM strategies.

SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s13167-023-00340-6.},
}

@article {pmid38076824,
year = {2023},
author = {Schweickart, A and Batra, R and Neth, BJ and Martino, C and Shenhav, L and Zhang, AR and Shi, P and Karu, N and Huynh, K and Meikle, PJ and Schimmel, L and Dilmore, AH and Blennow, K and Zetterberg, H and Blach, C and Dorrestein, PC and Knight, R and , and Craft, S and Kaddurah-Daouk, R and Krumsiek, J},
title = {A Modified Mediterranean Ketogenic Diet mitigates modifiable risk factors of Alzheimer's Disease: a serum and CSF-based metabolic analysis.},
journal = {medRxiv : the preprint server for health sciences},
volume = {},
number = {},
pages = {},
pmid = {38076824},
support = {R01 AG046171/AG/NIA NIH HHS/United States ; U24 AG021886/AG/NIA NIH HHS/United States ; R01 AG069901/AG/NIA NIH HHS/United States ; U19 AG063744/AG/NIA NIH HHS/United States ; P30 AG049638/AG/NIA NIH HHS/United States ; UL1 TR001420/TR/NCATS NIH HHS/United States ; RF1 AG059093/AG/NIA NIH HHS/United States ; U01 AG061359/AG/NIA NIH HHS/United States ; RF1 AG057452/AG/NIA NIH HHS/United States ; P30 AG072947/AG/NIA NIH HHS/United States ; RF1 AG058942/AG/NIA NIH HHS/United States ; RF1 AG051550/AG/NIA NIH HHS/United States ; },
abstract = {Alzheimer's disease (AD) is influenced by a variety of modifiable risk factors, including a person's dietary habits. While the ketogenic diet (KD) holds promise in reducing metabolic risks and potentially affecting AD progression, only a few studies have explored KD's metabolic impact, especially on blood and cerebrospinal fluid (CSF). Our study involved participants at risk for AD, either cognitively normal or with mild cognitive impairment. The participants consumed both a modified Mediterranean-ketogenic diet (MMKD) and the American Heart Association diet (AHAD) for 6 weeks each, separated by a 6-week washout period. We employed nuclear magnetic resonance (NMR)-based metabolomics to profile serum and CSF and metagenomics profiling on fecal samples. While the AHAD induced no notable metabolic changes, MMKD led to significant alterations in both serum and CSF. These changes included improved modifiable risk factors, like increased HDL-C and reduced BMI, reversed serum metabolic disturbances linked to AD such as a microbiome-mediated increase in valine levels, and a reduction in systemic inflammation. Additionally, the MMKD was linked to increased amino acid levels in the CSF, a breakdown of branched-chain amino acids (BCAAs), and decreased valine levels. Importantly, we observed a strong correlation between metabolic changes in the CSF and serum, suggesting a systemic regulation of metabolism. Our findings highlight that MMKD can improve AD-related risk factors, reverse some metabolic disturbances associated with AD, and align metabolic changes across the blood-CSF barrier.},
}

@article {pmid38051644,
year = {2023},
author = {Hou, T and Wang, Q and Dai, H and Hou, Y and Zheng, J and Wang, T and Lin, H and Wang, S and Li, M and Zhao, Z and Chen, Y and Xu, Y and Lu, J and Liu, R and Ning, G and Wang, W and Xu, M and Bi, Y},
title = {Interactive Association Between Gut Microbiota and Thyroid Cancer.},
journal = {Endocrinology},
volume = {165},
number = {1},
pages = {},
doi = {10.1210/endocr/bqad184},
pmid = {38051644},
issn = {1945-7170},
support = {81930021//National Natural Science Foundation of China/ ; SHDC2020CR1001A//Clinical Research Plan of SHDC/ ; 20152508//Shanghai Municipal Education Commission-Gaofeng Clinical Medicine Grant Support/ ; },
mesh = {Humans ; *Gastrointestinal Microbiome ; Genome-Wide Association Study ; *Microbiota ; *Thyroid Neoplasms/genetics ; },
abstract = {CONTEXT: The association between the gut microbiota and thyroid cancer remains controversial.

OBJECTIVE: We aimed to systematically investigate the interactive causal relationships between the abundance and metabolism pathways of gut microbiota and thyroid cancer.

METHODS: We leveraged genome-wide association studies for the abundance of 211 microbiota taxa from the MiBioGen study (N = 18 340), 205 microbiota metabolism pathways from the Dutch Microbiome Project (N = 7738), and thyroid cancer from the Global Biobank Meta-analysis Initiative (N cases = 6699 and N participants = 1 620 354). We performed a bidirectional Mendelian randomization (MR) to investigate the causality from microbiota taxa and metabolism pathways to thyroid cancer and vice versa. We performed a systematic review of previous observational studies and compared MR results with observational findings.

RESULTS: Eight taxa and 12 metabolism pathways had causal effects on thyroid cancer, where RuminococcaceaeUCG004 genus (P = .001), Streptococcaceae family (P = .016), Olsenella genus (P = .029), ketogluconate metabolism pathway (P = .003), pentose phosphate pathway (P = .016), and L-arginine degradation II in the AST pathway (P = .0007) were supported by sensitivity analyses. Conversely, thyroid cancer had causal effects on 3 taxa and 2 metabolism pathways, where the Holdemanella genus (P = .015) was supported by sensitivity analyses. The Proteobacteria phylum, Streptococcaceae family, Ruminococcus2 genus, and Holdemanella genus were significantly associated with thyroid cancer in both the systematic review and MR, whereas the other 121 significant taxa in observational results were not supported by MR.

DISCUSSIONS: These findings implicated the potential role of host-microbiota crosstalk in thyroid cancer, while the discrepancy among observational studies calls for further investigations.},
}

Humans
*Gastrointestinal Microbiome
Genome-Wide Association Study
*Microbiota
*Thyroid Neoplasms/genetics

@article {pmid38048079,
year = {2023},
author = {Fu, P and Wu, Y and Zhang, Z and Qiu, Y and Wang, Y and Peng, Y},
title = {VIGA: a one-stop tool for eukaryotic virus identification and genome assembly from next-generation-sequencing data.},
journal = {Briefings in bioinformatics},
volume = {25},
number = {1},
pages = {},
pmid = {38048079},
issn = {1477-4054},
support = {32370700//National Natural Science Foundation of China/ ; 2022YFC2303802//National Key Plan for Scientific Research and Development of China/ ; },
mesh = {Humans ; High-Throughput Nucleotide Sequencing ; *Colitis, Ulcerative ; *Crohn Disease ; Genome, Viral ; Metagenome ; },
abstract = {Identification of viruses and further assembly of viral genomes from the next-generation-sequencing data are essential steps in virome studies. This study presented a one-stop tool named VIGA (available at https://github.com/viralInformatics/VIGA) for eukaryotic virus identification and genome assembly from NGS data. It was composed of four modules, namely, identification, taxonomic annotation, assembly and novel virus discovery, which integrated several third-party tools such as BLAST, Trinity, MetaCompass and RagTag. Evaluation on multiple simulated and real virome datasets showed that VIGA assembled more complete virus genomes than its competitors on both the metatranscriptomic and metagenomic data and performed well in assembling virus genomes at the strain level. Finally, VIGA was used to investigate the virome in metatranscriptomic data from the Human Microbiome Project and revealed different composition and positive rate of viromes in diseases of prediabetes, Crohn's disease and ulcerative colitis. Overall, VIGA would help much in identification and characterization of viromes, especially the known viruses, in future studies.},
}

Humans
High-Throughput Nucleotide Sequencing
*Colitis, Ulcerative
*Crohn Disease
Genome, Viral
Metagenome

@article {pmid38047279,
year = {2023},
author = {Candeliere, F and Musmeci, E and Amaretti, A and Sola, L and Raimondi, S and Rossi, M},
title = {Profiling of the intestinal community of Clostridia: taxonomy and evolutionary analysis.},
journal = {Microbiome research reports},
volume = {2},
number = {2},
pages = {13},
pmid = {38047279},
issn = {2771-5965},
abstract = {Aim: Clostridia are relevant commensals of the human gut due to their major presence and correlations to the host. In this study, we investigated intestinal Clostridia of 51 healthy subjects and reconstructed their taxonomy and phylogeny. The relatively small number of intestinal Clostridia allowed a systematic whole genome approach based on average amino acid identity (AAI) and core genome with the aim of revising the current classification into genera and determining evolutionary relationships. Methods: 51 healthy subjects' metagenomes were retrieved from public databases. After the dataset's validation through comparison with Human Microbiome Project (HMP) samples, the metagenomes were profiled using MetaPhlAn3 to identify the population ascribed to the class Clostridia. Intestinal Clostridia genomes were retrieved and subjected to AAI analysis and core genome identification. Phylogeny investigation was conducted with RAxML and Unweighted Pair Group Method with Arithmetic Mean (UPGMA) algorithms, and SplitsTree for split decomposition. Results: 225 out of 406 bacterial taxonomic units were ascribed to Bacillota [Firmicutes], among which 124 were assigned to the class Clostridia. 77 out of the 124 taxonomic units were referred to a species, altogether covering 87.7% of Clostridia abundance. According to the lowest AAI genus boundary set at 55%, 15 putative genera encompassing more than one species (G1 to G15) were identified, while 19 species did not cluster with any other one and each appeared to belong to a diverse genus. Phylogenetic investigations highlighted that most of the species clustered into three main evolutive clades. Conclusion: This study shed light on the species of Clostridia colonizing the gut of healthy adults and pinpointed several gaps in knowledge regarding the taxonomy and the phylogeny of Clostridia.},
}

@article {pmid38045612,
year = {2023},
author = {Brüssow, H},
title = {The human microbiome project at ten years - some critical comments and reflections on "our third genome", the human virome.},
journal = {Microbiome research reports},
volume = {2},
number = {1},
pages = {7},
pmid = {38045612},
issn = {2771-5965},
abstract = {The Human Microbiome Project (HMP) has raised great expectations claiming the far-reaching influence of the microbiome on human health and disease ranging from obesity and malnutrition to effects going well beyond the gut. So far, with the notable exception of fecal microbiota transplantation in Clostridioides difficile infection, practical application of microbiome intervention has only achieved modest clinical effects. It is argued here that we need criteria for the link between microbiome and disease modelled on the links between pathogens and infectious disease in Koch's postulates. The most important question is whether the microbiome change is a cause of the given disease or a consequence of a pathology leading to disease where the microbiome change is only a parallel event without a causal connection to the disease - in philosophical parlance, an epiphenomenon. Also discussed here is whether human virome research is a necessary complement to the microbiome project with a high potential for practical applications.},
}

@article {pmid38029073,
year = {2023},
author = {Xie, Q and Hu, B},
title = {Effects of gut microbiota on prostatic cancer: a two-sample Mendelian randomization study.},
journal = {Frontiers in microbiology},
volume = {14},
number = {},
pages = {1250369},
pmid = {38029073},
issn = {1664-302X},
abstract = {AIM: Recent observational and small-sample case-control studies have shown a relationship between gut microbiota composition and prostatic cancer (PCa). Nevertheless, the causal association between gut microbiota and PCa is still unclear. Herein, we used the Mendelian randomization (MR) method to explore the potential causal relationship between gut microbiota and PCa.

METHODS: In this two-sample MR study, data were extracted from the summary statistics of gut microbiota from the largest available genome-wide association study meta-analysis conducted by the MiBioGen consortium (n = 14,306) and the Dutch Microbiome Project (n = 8,208). Summary statistics for PCa were obtained from the FinnGen consortium release data (n = 95,213). Inverse variance weighted (IVW), MR-Egger, strength test (F), and MR-PRESSO were used to examine the potential causal association between gut microbiota and PCa. Cochran's Q statistics were used to quantify the heterogeneity of instrumental variables.

RESULTS: IVW estimates suggested that the relative abundance of Akkermansia muciniphila (odds ratio [OR] = 0.7926, 95% confidence interval [CI]: 0.6655-0.9440) and Bacteroides salyersiae (OR = 0.9023, 95% CI: 0.8262-0.9853) were negatively associated with the odds of PCa, while that of Eubacterium biforme (OR = 1.1629, 95% CI: 1.0110-1.3376) was positively associated with the odds of PCa. In addition, we explored these relationships among patients without other cancers and similarly found that the relative abundance of Akkermansia muciniphila, Bacteroides salyersiae, and Eubacterium biforme were linked to PCa (all P < 0.05).

CONCLUSION: Gut microbiota potentially influenced the occurrence of PCa. Our findings may provide some new ideas for researching the methods of PCa prevention. In addition, further studies are needed to explore the causal association and specific underlying mechanisms between gut microbiota and PCa.},
}

@article {pmid37973865,
year = {2023},
author = {King, AM and Zhang, Z and Glassey, E and Siuti, P and Clardy, J and Voigt, CA},
title = {Systematic mining of the human microbiome identifies antimicrobial peptides with diverse activity spectra.},
journal = {Nature microbiology},
volume = {8},
number = {12},
pages = {2420-2434},
pmid = {37973865},
issn = {2058-5276},
support = {HR0011-15-C-0084//United States Department of Defense | Defense Advanced Research Projects Agency (DARPA)/ ; },
mesh = {Humans ; Antimicrobial Peptides ; *Methicillin-Resistant Staphylococcus aureus ; Escherichia coli ; Peptides/genetics/pharmacology/chemistry ; Bacteria/genetics ; *Microbiota/genetics ; Anti-Bacterial Agents/pharmacology ; },
abstract = {Human-associated bacteria secrete modified peptides to control host physiology and remodel the microbiota species composition. Here we scanned 2,229 Human Microbiome Project genomes of species colonizing skin, gastrointestinal tract, urogenital tract, mouth and trachea for gene clusters encoding RiPPs (ribosomally synthesized and post-translationally modified peptides). We found 218 lanthipeptides and 25 lasso peptides, 70 of which were synthesized and expressed in E. coli and 23 could be purified and functionally characterized. They were tested for activity against bacteria associated with healthy human flora and pathogens. New antibiotics were identified against strains implicated in skin, nasal and vaginal dysbiosis as well as from oral strains selectively targeting those in the gut. Extended- and narrow-spectrum antibiotics were found against methicillin-resistant Staphylococcus aureus and vancomycin-resistant Enterococci. Mining natural products produced by human-associated microbes will enable the elucidation of ecological relationships and may be a rich resource for antimicrobial discovery.},
}

Humans
Antimicrobial Peptides
*Methicillin-Resistant Staphylococcus aureus
Escherichia coli
Peptides/genetics/pharmacology/chemistry
Bacteria/genetics
*Microbiota/genetics
Anti-Bacterial Agents/pharmacology

@article {pmid37940997,
year = {2023},
author = {Dai, H and Hou, T and Wang, Q and Hou, Y and Zhu, Z and Zhu, Y and Zhao, Z and Li, M and Lin, H and Wang, S and Zheng, R and Xu, Y and Lu, J and Wang, T and Ning, G and Wang, W and Zheng, J and Bi, Y and Xu, M},
title = {Roles of gut microbiota in atrial fibrillation: insights from Mendelian randomization analysis and genetic data from over 430,000 cohort study participants.},
journal = {Cardiovascular diabetology},
volume = {22},
number = {1},
pages = {306},
pmid = {37940997},
issn = {1475-2840},
mesh = {*Atrial Fibrillation/diagnosis/epidemiology/genetics ; Cohort Studies ; *Diabetes Mellitus, Type 2 ; *Gastrointestinal Microbiome ; Eubacterium ; Humans ; Genome-Wide Association Study ; Mendelian Randomization Analysis ; *Coronary Artery Disease ; },
abstract = {BACKGROUND: Gut microbiota imbalances have been suggested as a contributing factor to atrial fibrillation (AF), but the causal relationship is not fully understood.

OBJECTIVES: To explore the causal relationships between the gut microbiota and AF using Mendelian randomization (MR) analysis.

METHODS: Summary statistics were from genome-wide association studies (GWAS) of 207 gut microbial taxa (5 phyla, 10 classes, 13 orders, 26 families, 48 genera, and 105 species) (the Dutch Microbiome Project) and two large meta-GWASs of AF. The significant results were validated in FinnGen cohort and over 430,000 UK Biobank participants. Mediation MR analyses were conducted for AF risk factors, including type 2 diabetes, coronary artery disease (CAD), body mass index (BMI), blood lipids, blood pressure, and obstructive sleep apnea, to explore the potential mediation effect of these risk factors in between the gut microbiota and AF.

RESULTS: Two microbial taxa causally associated with AF: species Eubacterium ramulus (odds ratio [OR] 1.08, 95% confidence interval [CI] 1.04-1.12, P = 0.0001, false discovery rate (FDR) adjusted p-value = 0.023) and genus Holdemania (OR 1.15, 95% CI 1.07-1.25, P = 0.0004, FDR adjusted p-value = 0.042). Genus Holdemania was associated with incident AF risk in the UK Biobank. The proportion of mediation effect of species Eubacterium ramulus via CAD was 8.05% (95% CI 1.73% - 14.95%, P = 0.008), while the proportion of genus Holdemania on AF via BMI was 12.01% (95% CI 5.17% - 19.39%, P = 0.0005).

CONCLUSIONS: This study provided genetic evidence to support a potential causal mechanism between gut microbiota and AF and suggested the mediation role of AF risk factors.},
}

*Atrial Fibrillation/diagnosis/epidemiology/genetics
Cohort Studies
*Diabetes Mellitus, Type 2
*Gastrointestinal Microbiome
Eubacterium
Humans
Genome-Wide Association Study
Mendelian Randomization Analysis
*Coronary Artery Disease

@article {pmid37875417,
year = {2024},
author = {Li, J and Yang, Z and Yuan, W and Bao, Z and Li, MD},
title = {Heme Metabolism Mediates the Effects of Smoking on Gut Microbiome.},
journal = {Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco},
volume = {26},
number = {6},
pages = {742-751},
doi = {10.1093/ntr/ntad209},
pmid = {37875417},
issn = {1469-994X},
support = {2016YFC0906300//China Precision Medicine Initiative/ ; 2021539200340045//Joint Research Institute of Tobacco and Health of China/ ; //Research Center for Air Pollution and Health of Zhejiang University/ ; },
mesh = {Humans ; *Gastrointestinal Microbiome ; *Heme/metabolism ; Transcriptome ; Male ; Female ; Metagenome ; Adult ; Smoking/adverse effects ; Bacteroides/genetics ; },
abstract = {INTRODUCTION: The number of smokers worldwide increased greatly during the past decades and reached 1.14 billion in 2019, becoming a leading risk factor for human health. Tobacco smoking has wide effects on human genetics, epigenetics, transcriptome, and gut microbiome. Although many studies have revealed effects of smoking on host transcriptome, research on the relationship between smoking, host gene expression, and the gut microbiome is limited.

AIMS AND METHODS: We first explored transcriptome and metagenome profile differences between smokers and nonsmokers. To evaluate the relationship between host gene expression and gut microbiome, we then applied bidirectional mediation analysis to infer causal relationships between smoking, gene expression, and gut microbes.

RESULTS: Metagenome and transcriptome analyses revealed 71 differential species and 324 differential expressed genes between smokers and nonsmokers. With smoking as an exposure variable, we identified 272 significant causal relationships between gene expression and gut microbes, among which there were 247 genes that mediate the effect of smoking on gut microbes. Pathway-based enrichment analysis showed that these genes were significantly enriched in heme metabolic pathway, which mainly mediated the changes of Bacteroides finegoldii and Lachnospiraceae bacterium 9_1_43BFAA. Additionally, by performing metabolome data analysis in the Integrated Human Microbiome Project (iHMP) database, we verified the correlation between the intermediate products of the heme metabolism pathway (porphobilinogen, bilirubin, and biliverdin) and gut microbiome.

CONCLUSIONS: By investigating the bidirectional interaction between smoking-related host gene expression and gut microbes, this study provided evidence for the mediation of smoking on gut microbes through co-involvement or interaction of heme metabolism.

IMPLICATIONS: By comparing the metagenome and transcriptome sequencing profiles between 34 smokers and 33 age- and gender-matched nonsmokers, we are the first to reveal causal relationships among tobacco smoking, host gene expression, and gut microbes. These findings offer insight into how smoking affects gut microbes through host gene expression and metabolism, which highlights the importance of heme metabolism in modulating the effects of smoking on gut microbiome.},
}

Humans
*Gastrointestinal Microbiome
*Heme/metabolism
Transcriptome
Male
Female
Metagenome
Adult
Smoking/adverse effects
Bacteroides/genetics

@article {pmid37874170,
year = {2023},
author = {Brostow, DP and Donovan, M and Penzenik, M and Stamper, CE and Spark, T and Lowry, CA and Ishaq, SL and Hoisington, AJ and Brenner, LA},
title = {Food desert residence has limited impact on veteran fecal microbiome composition: a U.S. Veteran Microbiome Project study.},
journal = {mSystems},
volume = {8},
number = {6},
pages = {e0071723},
pmid = {37874170},
issn = {2379-5077},
support = {//U.S. Department of Veterans Affairs (VA)/ ; },
mesh = {Humans ; Food Deserts ; *Veterans/psychology ; *Microbiota ; Feces ; *Gastrointestinal Microbiome ; },
abstract = {Social and economic inequities can have a profound impact on human health. The inequities could result in alterations to the gut microbiome, an important factor that may have profound abilities to alter health outcomes. Moreover, the strong correlations between social and economic inequities have been long understood. However, to date, limited research regarding the microbiome and mental health within the context of socioeconomic inequities exists. One particular inequity that may influence both mental health and the gut microbiome is living in a food desert. Persons living in food deserts may lack access to sufficient and/or nutritious food and often experience other inequities, such as increased exposure to air pollution and poor access to healthcare. Together, these factors may confer a unique risk for microbial perturbation. Indeed, external factors beyond a food desert might compound over time to have a lasting effect on an individual's gut microbiome. Therefore, adoption of a life-course approach is expected to increase the ecological validity of research related to social inequities, the gut microbiome, and physical and mental health.},
}

Humans
Food Deserts
*Veterans/psychology
*Microbiota
Feces
*Gastrointestinal Microbiome

@article {pmid37810788,
year = {2023},
author = {Ochoa-Sánchez, M and Acuña Gomez, EP and Ramírez-Fenández, L and Eguiarte, LE and Souza, V},
title = {Current knowledge of the Southern Hemisphere marine microbiome in eukaryotic hosts and the Strait of Magellan surface microbiome project.},
journal = {PeerJ},
volume = {11},
number = {},
pages = {e15978},
pmid = {37810788},
issn = {2167-8359},
mesh = {Animals ; *Eukaryota/genetics ; RNA, Ribosomal, 16S/genetics ; *Microbiota/genetics ; Metagenome ; Fishes/genetics ; Aquatic Organisms/genetics ; Mammals/genetics ; },
abstract = {Host-microbe interactions are ubiquitous and play important roles in host biology, ecology, and evolution. Yet, host-microbe research has focused on inland species, whereas marine hosts and their associated microbes remain largely unexplored, especially in developing countries in the Southern Hemisphere. Here, we review the current knowledge of marine host microbiomes in the Southern Hemisphere. Our results revealed important biases in marine host species sampling for studies conducted in the Southern Hemisphere, where sponges and marine mammals have received the greatest attention. Sponge-associated microbes vary greatly across geographic regions and species. Nevertheless, besides taxonomic heterogeneity, sponge microbiomes have functional consistency, whereas geography and aging are important drivers of marine mammal microbiomes. Seabird and macroalgal microbiomes in the Southern Hemisphere were also common. Most seabird microbiome has focused on feces, whereas macroalgal microbiome has focused on the epibiotic community. Important drivers of seabird fecal microbiome are aging, sex, and species-specific factors. In contrast, host-derived deterministic factors drive the macroalgal epibiotic microbiome, in a process known as "microbial gardening". In turn, marine invertebrates (especially crustaceans) and fish microbiomes have received less attention in the Southern Hemisphere. In general, the predominant approach to study host marine microbiomes has been the sequencing of the 16S rRNA gene. Interestingly, there are some marine holobiont studies (i.e., studies that simultaneously analyze host (e.g., genomics, transcriptomics) and microbiome (e.g., 16S rRNA gene, metagenome) traits), but only in some marine invertebrates and macroalgae from Africa and Australia. Finally, we introduce an ongoing project on the surface microbiome of key species in the Strait of Magellan. This is an international project that will provide novel microbiome information of several species in the Strait of Magellan. In the short-term, the project will improve our knowledge about microbial diversity in the region, while long-term potential benefits include the use of these data to assess host-microbial responses to the Anthropocene derived climate change.},
}

Animals
*Eukaryota/genetics
RNA, Ribosomal, 16S/genetics
*Microbiota/genetics
Metagenome
Fishes/genetics
Aquatic Organisms/genetics
Mammals/genetics

@article {pmid37790319,
year = {2023},
author = {Jansen, R and Milaneschi, Y and Schranner, D and Kastenmuller, G and Arnold, M and Han, X and Dunlop, BW and , and Rush, AJ and Kaddurah-Daouk, R and Penninx, BW},
title = {The Metabolome-Wide Signature of Major Depressive Disorder.},
journal = {Research square},
volume = {},
number = {},
pages = {},
pmid = {37790319},
issn = {2693-5015},
support = {R01 AG046171/AG/NIA NIH HHS/United States ; R01 MH108348/MH/NIMH NIH HHS/United States ; R01 AG069901/AG/NIA NIH HHS/United States ; U19 AG063744/AG/NIA NIH HHS/United States ; RF1 AG059093/AG/NIA NIH HHS/United States ; U01 AG061359/AG/NIA NIH HHS/United States ; RF1 AG057452/AG/NIA NIH HHS/United States ; RF1 AG058942/AG/NIA NIH HHS/United States ; RF1 AG051550/AG/NIA NIH HHS/United States ; },
abstract = {Major Depressive Disorder (MDD) is an often-chronic condition with substantial molecular alterations and pathway dysregulations involved. Single metabolite, pathway and targeted metabolomics platforms have indeed revealed several metabolic alterations in depression including energy metabolism, neurotransmission and lipid metabolism. More comprehensive coverage of the metabolome is needed to further specify metabolic dysregulation in depression and reveal previously untargeted mechanisms. Here we measured 820 metabolites using the metabolome-wide Metabolon platform in 2770 subjects from a large Dutch clinical cohort with extensive depression clinical phenotyping (1101 current MDD, 868 remitted MDD, 801 healthy controls) at baseline and 1805 subjects at 6-year follow up (327 current MDD, 1045 remitted MDD, 433 healthy controls). MDD diagnosis was based on DSM-IV psychiatric interviews. Depression severity was measured with the Inventory of Depressive Symptomatology self-report. Associations between metabolites and MDD status and depression severity were assessed at baseline and at the 6-year follow-up. Metabolites consistently associated with MDD status or depression severity on both occasions were examined in Mendelian randomization (MR) analysis using metabolite (N=14,000) and MDD (N=800,000) GWAS results. At baseline, 139 and 126 metabolites were associated with current MDD status and depression severity, respectively, with 79 overlapping metabolites. Six years later, 34 out of the 79 metabolite associations were subsequently replicated. Downregulated metabolites were enriched with long-chain monounsaturated (P=6.7e-07) and saturated (P=3.2e-05) fatty acids and upregulated metabolites with lysophospholipids (P=3.4e-4). Adding BMI to the models changed results only marginally. MR analyses showed that genetically-predicted higher levels of the lysophospholipid 1-linoleoyl-GPE (18:2) were associated with greater risk of depression. The identified metabolome-wide profile of depression (severity) indicated altered lipid metabolism with downregulation of long-chain fatty acids and upregulation of lysophospholipids, for which causal involvement was suggested using genetic tools. This metabolomics signature offers a window on depression pathophysiology and a potential access point for the development of novel therapeutic approaches.},
}

@article {pmid37747198,
year = {2023},
author = {Duan, Z and Fu, J and Zhang, F and Cai, Y and Wu, G and Ma, W and Zhou, H and He, Y},
title = {The association between BMI and serum uric acid is partially mediated by gut microbiota.},
journal = {Microbiology spectrum},
volume = {11},
number = {5},
pages = {e0114023},
pmid = {37747198},
issn = {2165-0497},
abstract = {Obesity is a risk factor for the development of hyperuricemia, both of which were related to gut microbiota. However, whether alterations in the gut microbiota lie in the pathways mediating obesity's effects on hyperuricemia is less clear. Body mass index (BMI) and serum uric acid (SUA) were separately important indicators of obesity and hyperuricemia. Our study aims to investigate whether BMI-related gut microbiota characteristics would mediate the association between BMI and SUA levels. A total of 6,280 participants from Guangdong Gut Microbiome Project were included in this study. Stool samples were collected for 16S rRNA gene sequencing. The results revealed that BMI was significantly and positively associated with SUA. Meanwhile, BMI was significantly associated with the abundance of 102 gut microbial genera, 16 of which were also significantly associated with SUA. The mediation analysis revealed that the association between BMI and SUA was partially mediated by the abundance of Proteobacteria (proportion mediated: 0.94%, P < 0.05). At the genus level, 25 bacterial genera, including Ralstonia, Oscillospira, Faecalibacterium, etc., could also partially mediate the association of BMI with SUA (the highest proportion is mediated by Ralstonia, proportion mediated: 2.76%, P < 0.05). This study provided evidence for the associations among BMI, gut microbiota, and SUA, and the mediation analysis suggested that the association of BMI with SUA was partially mediated by the gut microbiota. IMPORTANCE Using 16S rRNA sequencing analysis, local interpretable machine learning technique analysis and mediation analysis were used to explore the association between BMI with SUA, and the mediating effects of gut microbial dysbiosis in the association were investigated.},
}

@article {pmid37719161,
year = {2023},
author = {Hayer, SS and Hwang, S and Clayton, JB},
title = {Antibiotic-induced gut dysbiosis and cognitive, emotional, and behavioral changes in rodents: a systematic review and meta-analysis.},
journal = {Frontiers in neuroscience},
volume = {17},
number = {},
pages = {1237177},
pmid = {37719161},
issn = {1662-4548},
support = {K01 OD030514/OD/NIH HHS/United States ; },
abstract = {There are previous epidemiological studies reporting associations between antibiotic use and psychiatric symptoms. Antibiotic-induced gut dysbiosis and alteration of microbiota-gut-brain axis communication has been proposed to play a role in this association. In this systematic review and meta-analysis, we reviewed published articles that have presented results on changes in cognition, emotion, and behavior in rodents (rats and mice) after antibiotic-induced gut dysbiosis. We searched three databases-PubMed, Web of Science, and SCOPUS to identify such articles using dedicated search strings and extracted data from 48 articles. Increase in anxiety and depression-like behavior was reported in 32.7 and 40.7 percent of the study-populations, respectively. Decrease in sociability, social novelty preference, recognition memory and spatial cognition was found in 18.1, 35.3, 26.1, and 62.5 percent of the study-populations, respectively. Only one bacterial taxon (increase in gut Proteobacteria) showed statistically significant association with behavioral changes (increase in anxiety). There were no consistent findings with statistical significance for the potential biomarkers [Brain-derived neurotrophic factor (BDNF) expression in the hippocampus, serum corticosterone and circulating IL-6 and IL-1β levels]. Results of the meta-analysis revealed a significant association between symptoms of negative valence system (including anxiety and depression) and cognitive system (decreased spatial cognition) with antibiotic intake (p < 0.05). However, between-study heterogeneity and publication bias were statistically significant (p < 0.05). Risk of bias was evaluated to be high in the majority of the studies. We identified and discussed several reasons that could contribute to the heterogeneity between the results of the studies examined. The results of the meta-analysis provide promising evidence that there is indeed an association between antibiotic-induced gut dysbiosis and psychopathologies. However, inconsistencies in the implemented methodologies make generalizing these results difficult. Gut microbiota depletion using antibiotics may be a useful strategy to evaluate if and how gut microbes influence cognition, emotion, and behavior, but the heterogeneity in methodologies used precludes any definitive interpretations for a translational impact on clinical practice.},
}

@article {pmid37655719,
year = {2023},
author = {Corewyn, LC and Kelaita, MA and Nollman, J and Hagnauer, I and Blanco-Peña, K and Lessnau, RG and Clayton, JB and Shields-Cutler, R and Stoos, KB},
title = {Hematology and blood biochemistry in a declining population of mantled howler monkeys (Alouatta palliata palliata) at La Pacifica, Costa Rica.},
journal = {Journal of medical primatology},
volume = {52},
number = {6},
pages = {353-360},
pmid = {37655719},
issn = {1600-0684},
support = {K01 OD030514/OD/NIH HHS/United States ; },
mesh = {Female ; Male ; Animals ; Costa Rica ; *Alouatta ; *Alouatta caraya ; *Hematology ; },
abstract = {BACKGROUND: Alouatta palliata palliata are an ecologically flexible howler monkey subspecies that has recently been relisted as Endangered. Populations are declining through much of the subspecies' range, including at our study site at La Pacifica, Costa Rica. Our objectives were to screen blood hematology and biochemistry samples collected from this wild population to elucidate their baseline health.

METHODS: We collected blood samples from 38 adult individuals from across the study site and analyzed 13 hematology and 14 biochemistry parameters.

RESULTS: Most hematology and blood biochemistry parameter values were similar between males and females. However, mean hemoglobin was significantly lower, and mean white blood cell count was significantly higher in females; and mean calcium and mean creatinine were significantly lower in females compared to males.

CONCLUSIONS: Overall, the La Pacifica population appeared healthy based on the blood parameters analyzed from sampled individuals. Our results were also largely consistent with published data available from other populations of A. p. palliata, and with reference values for captive Alouatta caraya.},
}

Female
Male
Animals
Costa Rica
*Alouatta
*Alouatta caraya
*Hematology