A meta-analysis of the gut microbiome in inflammatory bowel disease patients identifies disease-associated small molecules.

Changes in the gut microbiome have been associated with several human diseases, but the molecular and functional details underlying these associations remain largely unknown. Here, we performed a multi-cohort analysis of small molecule biosynthetic gene clusters (BGCs) in 5,306 metagenomic samples of the gut microbiome from 2,033 Inflammatory Bowel Disease (IBD) patients and 833 matched healthy subjects and identified a group of Clostridia-derived BGCs that are significantly associated with IBD. Using synthetic biology, we discovered and solved the structures of six fatty acid amides as the products of the IBD-enriched BGCs. Using two mouse models of colitis, we show that the discovered small molecules disrupt gut permeability and exacerbate inflammation in chemically and genetically susceptible mice. These findings suggest that microbiome-derived small molecules may play a role in the etiology of IBD and represent a generalizable approach for discovering molecular mediators of microbiome-host interactions in the context of microbiome-associated diseases.

An accurate aging clock developed from large-scale gut microbiome and human gene expression data.

Accurate measurement of the biological markers of the aging process could provide an "aging clock" measuring predicted longevity and enable the quantification of the effects of specific lifestyle choices on healthy aging. Using machine learning techniques, we demonstrate that chronological age can be predicted accurately from (1) the expression level of human genes in capillary blood and (2) the expression level of microbial genes in stool samples. The latter uses a very large metatranscriptomic dataset, stool samples from 90,303 individuals, which arguably results in a higher quality microbiome-aging model than prior work. Our analysis suggests associations between biological age and lifestyle/health factors, e.g., people on a paleo diet or with IBS tend to have higher model-predicted ages and people on a vegetarian diet tend to have lower model-predicted ages. We delineate the key pathways of systems-level biological decline based on the age-specific features of our model.

Pathogen detection and characterization from throat swabs using unbiased metatranscriptomic analyses.

OBJECTIVES: Infectious diseases are common but are not easily or readily diagnosed with current methodologies. This problem is further exacerbated by the constant presence of mutated, emerging, and novel pathogens. One of the most common sites of infection by many pathogens is the human throat. However, there is no universal diagnostic test that can distinguish these pathogens. Metatranscriptomic (MT) analysis of the throat represents an important and novel development in infectious disease detection and characterization, because it is able to identify all pathogens using a fully unbiased approach. METHODS: To test the utility of an MT approach to pathogen detection, throat samples were collected from participants before, during, and after an acute sickness. RESULTS: Clear sickness-associated shifts in pathogenic microorganisms were detected in the patients. Important insights into microbial functions and antimicrobial resistance genes were obtained. CONCLUSION: MT analysis of the throat represents an effective method for the unbiased identification and characterization of pathogens. Because MT data include all microorganisms in the sample, this approach should not only allow the identification of pathogens, but provide an understanding of the effects of the resident throat microbiome in the context of human health and disease.

A clinically validated human capillary blood transcriptome test for global systems biology studies.

To prevent and treat chronic diseases, including cancer, a global application of systems biology is needed. We report here a whole blood transcriptome test that needs only 50 µl of capillary (fingerprick) blood. This test is suitable for global applications because the samples are preserved at ambient temperature for up to 4 weeks and the RNA preservative inactivates all pathogens, enabling safe transportation. Both the laboratory and bioinformatic steps are automated and performed in a clinical lab, which minimizes batch effects and creates unbiased datasets. Given its clinical testing performance and accessibility to traditionally underrepresented and diverse populations, this test offers a unique ability to reveal molecular mechanisms of disease and enable longitudinal, population-scale studies.

A metagenomic strategy for harnessing the chemical repertoire of the human microbiome.

Extensive progress has been made in determining the effects of the microbiome on human physiology and disease, but the underlying molecules and mechanisms governing these effects remain largely unexplored. Here, we combine a new computational algorithm with synthetic biology to access biologically active small molecules encoded directly in human microbiome-derived metagenomic sequencing data. We discover that members of a clinically used class of molecules are widely encoded in the human microbiome and that they exert potent antibacterial activities against neighboring microbes, implying a possible role in niche competition and host defense. Our approach paves the way toward a systematic unveiling of the chemical repertoire encoded by the human microbiome and provides a generalizable platform for discovering molecular mediators of microbiome-host and microbiome-microbiome interactions.