Showing papers by "George M. Weinstock published in 2020"

Deciphering Functional Redundancy in the Human Microbiome

Abstract: Although the taxonomic composition of the human microbiome varies tremendously across individuals, its gene composition or functional capacity is highly conserved — implying an ecological property known as functional redundancy. Such functional redundancy has been hypothesized to underlie the stability and resilience of the human microbiome, but this hypothesis has never been quantitatively tested. The origin of functional redundancy is still elusive. Here, we investigate the basis for functional redundancy in the human microbiome by analyzing its genomic content network — a bipartite graph that links microbes to the genes in their genomes. We find that this network exhibits several topological features that favor high functional redundancy. Furthermore, we develop a simple genome evolution model to generate genomic content network, finding that moderate selection pressure and high horizontal gene transfer rate are necessary to generate genomic content networks with key topological features that favor high functional redundancy. Finally, we analyze data from two published studies of fecal microbiota transplantation (FMT), finding that high functional redundancy of the recipient’s pre-FMT microbiota raises barriers to donor microbiota engraftment. This work elucidates the potential ecological and evolutionary processes that create and maintain functional redundancy in the human microbiome and contribute to its resilience. Here, the authors develop a genome evolution model to investigate the origin of functional redundancy in the human microbiome by analyzing its genomic content network and illustrate potential ecological and evolutionary processes that may contribute to its resilience.

A Microbe Associated with Sleep Revealed by a Novel Systems Genetic Analysis of the Microbiome in Collaborative Cross Mice.

Abstract: The microbiome influences health and disease through complex networks of host genetics, genomics, microbes, and environment. Identifying the mechanisms of these interactions has remained challenging. Systems genetics in laboratory mice (Mus musculus) enables data-driven discovery of biological network components and mechanisms of host-microbial interactions underlying disease phenotypes. To examine the interplay among the whole host genome, transcriptome, and microbiome, we mapped QTL and correlated the abundance of cecal messenger RNA, luminal microflora, physiology, and behavior in a highly diverse Collaborative Cross breeding population. One such relationship, regulated by a variant on chromosome 7, was the association of Odoribacter (Bacteroidales) abundance and sleep phenotypes. In a test of this association in the BKS.Cg-Dock7m +/+ Leprdb/J mouse model of obesity and diabetes, known to have abnormal sleep and colonization by Odoribacter, treatment with antibiotics altered sleep in a genotype-dependent fashion. The many other relationships extracted from this study can be used to interrogate other diseases, microbes, and mechanisms.

Genetic Basis of Aerobically Supported Voluntary Exercise: Results from a Selection Experiment with House Mice.

Abstract: House mice from 4 replicate lines selectively bred for 61 generations for voluntary wheel-running behavior were compared with 4 non-selected control lines using multiple genome-wide analytical techniques on both haplotype and single nucleotide polymorphism data......

Differences in Gut Microbiome in Hospitalized Immunocompetent vs. Immunocompromised Children, Including Those With Sickle Cell Disease.

Abstract: Background: Gut microbial diversity and composition play important roles in health. This cross-sectional study was designed to test the hypothesis that hospitalized children who may be relatively immunocompromised (IC), defined as those with cancer, sickle cell disease (SCD), transplantation, or receiving immunosuppressive therapy) would have decreased microbial diversity, increased Clostridioides difficile colonization and different species composition compared to non-immunocompromised (Non-IC) children admitted to the same pediatric unit. Methods: A stool sample was obtained within 72 h of admission to a single unit at The Children's Hospital at Montefiore, Bronx, NY from March 2016 to February 2017 and the microbiome assessed by 16S rRNA sequencing. C. difficile colonization was assessed by glutamate dehydrogenase antigen and toxin polymerase chain reaction assays. Results: Stool samples were obtained from 69 IC (32 SCD, 19 cancer, 9 transplantation and 9 other) and 37 Non-IC patients. There were no significant differences in microbial alpha diversity and C. difficile colonization comparing IC vs. non-IC patients. Lower alpha diversity, however, was independently associated with the use of proton pump inhibitors or antibiotics, including prophylactic penicillin in patients with SCD. Differences in specific species abundances were observed when comparing IC vs. non-IC patients, particularly children with SCD. Non-IC patients had increased abundance of commensals associated with health including Alistipes putredinis, Alistipes ihumii, Roseburia inulinivorans, Roseburia intestinalis, and Ruminococcus albus (p < 0.005). Conclusions: Antibiotics and proton pump inhibitors, which were more commonly used in IC children, were identified as risk factors for lower microbial diversity. Non-IC patients had higher abundance of several bacterial species associated with health. Longitudinal studies are needed to determine the clinical significance of these differences in gut microbiome.

Longitudinal Analysis of Serum Cytokine Levels and Gut Microbial Abundance Links IL-17/IL-22 With Clostridia and Insulin Sensitivity in Humans

Abstract: Recent studies using mouse models suggest that interaction between the gut microbiome and IL-17/IL-22-producing cells plays a role in the development of metabolic diseases. We investigated this relationship in humans using data from the prediabetes study of the Integrated Human Microbiome Project (iHMP). Specifically, we addressed the hypothesis that early in the onset of metabolic diseases there is a decline in serum levels of IL-17/IL-22, with concomitant changes in the gut microbiome. Clustering iHMP study participants on the basis of longitudinal IL-17/IL-22 profiles identified discrete groups. Individuals distinguished by low levels of IL-17/IL-22 were linked to established markers of metabolic disease, including insulin sensitivity. These individuals also displayed gut microbiome dysbiosis, characterized by decreased diversity, and IL-17/IL-22-related declines in the phylum Firmicutes, class Clostridia, and order Clostridiales This ancillary analysis of the iHMP data therefore supports a link between the gut microbiome, IL-17/IL-22, and the onset of metabolic diseases. This raises the possibility for novel, microbiome-related therapeutic targets that may effectively alleviate metabolic diseases in humans as they do in animal models.

Approaches for integrating heterogeneous RNA-seq data reveal cross-talk between microbes and genes in asthmatic patients

Abstract: Sputum induction is a non-invasive method to evaluate the airway environment, particularly for asthma. RNA sequencing (RNA-seq) of sputum samples can be challenging to interpret due to the complex and heterogeneous mixtures of human cells and exogenous (microbial) material. In this study, we develop a pipeline that integrates dimensionality reduction and statistical modeling to grapple with the heterogeneity. LDA(Latent Dirichlet allocation)-link connects microbes to genes using reduced-dimensionality LDA topics. We validate our method with single-cell RNA-seq and microscopy and then apply it to the sputum of asthmatic patients to find known and novel relationships between microbes and genes.

Colon Cancer Prevention with Walnuts: A Longitudinal Study in Mice from the Perspective of a Gut Enterotype–like Cluster

Abstract: There is limited understanding of how walnut consumption inhibits the development of colorectal cancer. A possible mechanism may involve alterations to the gut microbiota. In this study, the effects of walnut on gut microbiota were tested in a mouse tumor bioassay using the colonotropic carcinogen, azoxymethane (AOM) added to the total Western diet (TWD). 16S rRNA pyrosequencing identified three enterotype-like clusters (E1, E2, and E3) in this murine model. E1, E2, and E3 are associated with AOM exposure, walnut consumption, and TWD diet, respectively. E2 and E3 showed distinct taxonomic and functional characteristics, while E1 represented an intermediate state. At the family level, E1 and E3 were both enriched with Bacteroidaceae, but driven by two different operational taxonomic units (OTU; OTU-2 for E1, OTU-4 for E3). E2 was overrepresented with Porphyromonadaceae and Lachnospiraceae, with OTU-3 (family Porphyromonadaceae) as the "driver" OTU for this cluster. Functionally, E3 is overrepresented with genes of glycan biosynthesis and metabolism, xenobiotic metabolism, and lipid metabolism. E2 is enriched with genes associated with cell motility, replication and repair, and amino acid metabolism. Longitudinally, E2 represents the gut microbial status of early life in these mice. In comparison with E1 and E3, E2 is associated with a moderate lower tumor burden (P = 0.12). Our results suggest that walnuts may reduce the risk of colorectal cancer within a Western diet by altering the gut microbiota. Our findings provide further evidence that colorectal cancer risk is potentially modifiable by diet via alterations to the microbiota.

Improving Characterization of Understudied Human Microbiomes Using Targeted Phylogenetics.

Abstract: Whole-genome bacterial sequences are required to better understand microbial functions, niche-specific bacterial metabolism, and disease states. Although genomic sequences are available for many of the human-associated bacteria from commonly tested body habitats (e.g., feces), as few as 13% of bacterium-derived reads from other sites such as the skin map to known bacterial genomes. To facilitate a better characterization of metagenomic shotgun reads from underrepresented body sites, we collected over 10,000 bacterial isolates originating from 14 human body habitats, identified novel taxonomic groups based on full-length 16S rRNA gene sequences, clustered the sequences to ensure that no individual taxonomic group was overselected for sequencing, prioritized bacteria from underrepresented body sites (such as skin and respiratory and urinary tracts), and sequenced and assembled genomes for 665 new bacterial strains. Here, we show that addition of these genomes improved read mapping rates of Human Microbiome Project (HMP) metagenomic samples by nearly 30% for the previously underrepresented phylum Fusobacteria, and 27.5% of the novel genomes generated here had high representation in at least one of the tested HMP samples, compared to 12.5% of the sequences in the public databases, indicating an enrichment of useful novel genomic sequences resulting from the prioritization procedure. As our understanding of the human microbiome continues to improve and to enter the realm of therapy developments, targeted approaches such as this to improve genomic databases will increase in importance from both an academic and a clinical perspective.IMPORTANCE The human microbiome plays a critically important role in health and disease, but current understanding of the mechanisms underlying the interactions between the varying microbiome and the different host environments is lacking. Having access to a database of fully sequenced bacterial genomes provides invaluable insights into microbial functions, but currently sequenced genomes for the human microbiome have largely come from a limited number of body sites (primarily feces), while other sites such as the skin, respiratory tract, and urinary tract are underrepresented, resulting in as little as 13% of bacterium-derived reads mapping to known bacterial genomes. Here, we sequenced and assembled 665 new bacterial genomes, prioritized from a larger database to select underrepresented body sites and bacterial taxa in the existing databases. As a result, we substantially improve mapping rates for samples from the Human Microbiome Project and provide an important contribution to human bacterial genomic databases for future studies.