Bacterial SNPs in the human gut microbiome associate with host BMI.

Genome-wide association studies (GWASs) have provided numerous associations between human single-nucleotide polymorphisms (SNPs) and health traits. Likewise, metagenome-wide association studies (MWASs) between bacterial SNPs and human traits can suggest mechanistic links, but very few such studies have been done thus far. In this study, we devised an MWAS framework to detect SNPs and associate them with host phenotypes systematically. We recruited and obtained gut metagenomic samples from a cohort of 7,190 healthy individuals and discovered 1,358 statistically significant associations between a bacterial SNP and host body mass index (BMI), from which we distilled 40 independent associations. Most of these associations were unexplained by diet, medications or physical exercise, and 17 replicated in a geographically independent cohort. We uncovered BMI-associated SNPs in 27 bacterial species, and 12 of them showed no association by standard relative abundance analysis. We revealed a BMI association of an SNP in a potentially inflammatory pathway of Bilophila wadsworthia as well as of a group of SNPs in a region coding for energy metabolism functions in a Faecalibacterium prausnitzii genome. Our results demonstrate the importance of considering nucleotide-level diversity in microbiome studies and pave the way toward improved understanding of interpersonal microbiome differences and their potential health implications.

Phage display sequencing reveals that genetic, environmental, and intrinsic factors influence variation of human antibody epitope repertoire.

Phage-displayed immunoprecipitation sequencing (PhIP-seq) has enabled high-throughput profiling of human antibody repertoires. However, a comprehensive overview of environmental and genetic determinants shaping human adaptive immunity is lacking. In this study, we investigated the effects of genetic, environmental, and intrinsic factors on the variation in human antibody repertoires. We characterized serological antibody repertoires against 344,000 peptides using PhIP-seq libraries from a wide range of microbial and environmental antigens in 1,443 participants from a population cohort. We detected individual-specificity, temporal consistency, and co-housing similarities in antibody repertoires. Genetic analyses showed the involvement of the HLA, IGHV, and FUT2 gene regions in antibody-bound peptide reactivity. Furthermore, we uncovered associations between phenotypic factors (including age, cell counts, sex, smoking behavior, and allergies, among others) and particular antibody-bound peptides. Our results indicate that human antibody epitope repertoires are shaped by both genetics and environmental exposures and highlight specific signatures of distinct phenotypes and genotypes.

Phage-display immunoprecipitation sequencing of the antibody epitope repertoire in inflammatory bowel disease reveals distinct antibody signatures.

Inflammatory bowel diseases (IBDs), e.g., Crohn's disease (CD) and ulcerative colitis (UC), are chronic immune-mediated inflammatory diseases. A comprehensive overview of an IBD-specific antibody epitope repertoire is, however, lacking. Using high-throughput phage-display immunoprecipitation sequencing (PhIP-Seq), we identified antibodies against 344,000 antimicrobial, immune, and food antigens in 497 individuals with IBD compared with 1,326 controls. IBD was characterized by 373 differentially abundant antibody responses (202 overrepresented and 171 underrepresented), with 17% shared by both IBDs, 55% unique to CD, and 28% unique to UC. Antibody reactivities against bacterial flagellins dominated in CD and were associated with ileal involvement, fibrostenotic disease, and anti-Saccharomyces cerevisiae antibody positivity, but not with fecal microbiome composition. Antibody epitope repertoires accurately discriminated CD from controls (area under the curve [AUC] = 0.89), and similar discrimination was achieved when using only ten antibodies (AUC = 0.87). Individuals with IBD thus show a distinct antibody repertoire against selected peptides, allowing clinical stratification and discovery of immunological targets.

Allergenic food protein consumption is associated with systemic IgG antibody responses in non-allergic individuals.

Although food-directed immunoglobulin E (IgE) has been studied in the context of allergies, the prevalence and magnitude of IgG responses against dietary antigens are incompletely characterized in the general population. Here, we measured IgG binding against food and environmental antigens obtained from allergen databases and the immune epitope database (IEDB), represented in a phage displayed library of 58,233 peptides. By profiling blood samples of a large cohort representing the average adult Israeli population (n = 1,003), we showed that many food antigens elicited systemic IgG in up to 50% of individuals. Dietary intake of specific food protein correlated with antibody binding, suggesting that diet can shape the IgG epitope repertoire. Our work documents abundant systemic IgG responses against food antigens and provides a reference map of the exact immunogenic epitopes on a population scale, laying the foundation to unravel the role of food- and environmental antigen-directed antibody binding in disease contexts.

BIPS-A code base for designing and coding of a Phage ImmunoPrecipitation Oligo Library.

BIPS (Build Phage ImmunoPrecipitation Sequencing library) is a software that converts a list of proteins into a custom DNA oligonucleotide library for the PhIP-Seq system. The tool creates constant-length oligonucleotides with internal barcodes, while maintaining the original length of the peptide. This allows using large libraries, of hundreds of thousands of oligonucleotides, while saving on the costs of sequencing and maintaining the accuracy of oligonucleotide reads identification. BIPS is available under GNU public license from: https://github.com/kalkairis/BuildPhIPSeqLibrary.

Systemic antibody responses against human microbiota flagellins are overrepresented in chronic fatigue syndrome patients.

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a debilitating disease with an unclear etiology and pathogenesis. Both an involvement of the immune system and gut microbiota dysbiosis have been implicated in its pathophysiology. However, potential interactions between adaptive immune responses and the microbiota in ME/CFS have been incompletely characterized. Here, we profiled antibody responses of patients with severe ME/CFS and healthy controls against microbiota and viral antigens represented as a phage-displayed 244,000 variant library. Patients with severe ME/CFS exhibited distinct serum antibody epitope repertoires against flagellins of Lachnospiraceae bacteria. Training machine learning algorithms on this antibody-binding data demonstrated that immune responses against gut microbiota represent a unique layer of information beyond standard blood tests, providing improved molecular diagnostics for ME/CFS. Together, our results point toward an involvement of the microbiota-immune axis in ME/CFS and lay the foundation for comparative studies with inflammatory bowel diseases and illnesses characterized by long-term fatigue symptoms, including post-COVID-19 syndrome.

An expanded reference map of the human gut microbiome reveals hundreds of previously unknown species.

The gut is the richest ecosystem of microbes in the human body and has great influence on our health. Despite many efforts, the set of microbes inhabiting this environment is not fully known, limiting our ability to identify microbial content and to research it. In this work, we combine new microbial metagenomic assembled genomes from 51,052 samples, with previously published genomes to produce a curated set of 241,118 genomes. Based on this set, we procure a new and improved human gut microbiome reference set of 3594 high quality species genomes, which successfully matches 83.65% validation samples' reads. This improved reference set contains 310 novel species, including one that exists in 19% of validation samples. Overall, this study provides a gut microbial genome reference set that can serve as a valuable resource for further research.

An atlas of robust microbiome associations with phenotypic traits based on large-scale cohorts from two continents.

Numerous human conditions are associated with the microbiome, yet studies are inconsistent as to the magnitude of the associations and the bacteria involved, likely reflecting insufficiently employed sample sizes. Here, we collected diverse phenotypes and gut microbiota from 34,057 individuals from Israel and the U.S.. Analyzing these data using a much-expanded microbial genomes set, we derive an atlas of robust and numerous unreported associations between bacteria and physiological human traits, which we show to replicate in cohorts from both continents. Using machine learning models trained on microbiome data, we show prediction accuracy of human traits across two continents. Subsampling our cohort to smaller cohort sizes yielded highly variable models and thus sensitivity to the selected cohort, underscoring the utility of large cohorts and possibly explaining the source of discrepancies across studies. Finally, many of our prediction models saturate at these numbers of individuals, suggesting that similar analyses on larger cohorts may not further improve these predictions.

Cross-reactive antibodies against human coronaviruses and the animal coronavirome suggest diagnostics for future zoonotic spillovers.

The spillover of animal coronaviruses (aCoVs) to humans has caused SARS, MERS, and COVID-19. While antibody responses displaying cross-reactivity between SARS-CoV-2 and seasonal/common cold human coronaviruses (hCoVs) have been reported, potential cross-reactivity with aCoVs and the diagnostic implications are incompletely understood. Here, we probed for antibody binding against all seven hCoVs and 49 aCoVs represented as 12,924 peptides within a phage-displayed antigen library. Antibody repertoires of 269 recovered COVID-19 patients showed distinct changes compared to 260 unexposed pre-pandemic controls, not limited to binding of SARS-CoV-2 antigens but including binding to antigens from hCoVs and aCoVs with shared motifs to SARS-CoV-2. We isolated broadly reactive monoclonal antibodies from recovered COVID-19 patients that bind a shared motif of SARS-CoV-2, hCoV-OC43, hCoV-HKU1, and several aCoVs, demonstrating that interspecies cross-reactivity can be mediated by a single immunoglobulin. Employing antibody binding data against the entire CoV antigen library allowed accurate discrimination of recovered COVID-19 patients from unexposed individuals by machine learning. Leaving out SARS-CoV-2 antigens and relying solely on antibody binding to other hCoVs and aCoVs achieved equally accurate detection of SARS-CoV-2 infection. The ability to detect SARS-CoV-2 infection without knowledge of its unique antigens solely from cross-reactive antibody responses against other hCoVs and aCoVs suggests a potential diagnostic strategy for the early stage of future pandemics. Creating regularly updated antigen libraries representing the animal coronavirome can provide the basis for a serological assay already poised to identify infected individuals following a future zoonotic transmission event.

Population-wide diversity and stability of serum antibody epitope repertoires against human microbiota.

Serum antibodies can recognize both pathogens and commensal gut microbiota. However, our current understanding of antibody repertoires is largely based on DNA sequencing of the corresponding B-cell receptor genes, and actual bacterial antigen targets remain incompletely characterized. Here we have profiled the serum antibody responses of 997 healthy individuals against 244,000 rationally selected peptide antigens derived from gut microbiota and pathogenic and probiotic bacteria. Leveraging phage immunoprecipitation sequencing (PhIP-Seq) based on phage-displayed synthetic oligo libraries, we detect a wide breadth of individual-specific as well as shared antibody responses against microbiota that associate with age and gender. We also demonstrate that these antibody epitope repertoires are more longitudinally stable than gut microbiome species abundances. Serum samples of more than 200 individuals collected five years apart could be accurately matched and could serve as an immunologic fingerprint. Overall, our results suggest that systemic antibody responses provide a non-redundant layer of information about microbiota beyond gut microbial species composition.

Potential role of indolelactate and butyrate in multiple sclerosis revealed by integrated microbiome-metabolome analysis.

Multiple sclerosis (MS) is an immune-mediated disease whose precise etiology is unknown. Several studies found alterations in the microbiome of individuals with MS, but the mechanism by which it may affect MS is poorly understood. Here we analyze the microbiome of 129 individuals with MS and find that they harbor distinct microbial patterns compared with controls. To study the functional consequences of these differences, we measure levels of 1,251 serum metabolites in a subgroup of subjects and unravel a distinct metabolite signature that separates affected individuals from controls nearly perfectly (AUC = 0.97). Individuals with MS are found to be depleted in butyrate-producing bacteria and in bacteria that produce indolelactate, an intermediate in generation of the potent neuroprotective antioxidant indolepropionate, which we found to be lower in their serum. We identify microbial and metabolite candidates that may contribute to MS and should be explored further for their causal role and therapeutic potential.

Diversity and functional landscapes in the microbiota of animals in the wild.

Animals in the wild are able to subsist on pathogen-infected and poisonous food and show immunity to various diseases. These may be due to their microbiota, yet we have a poor understanding of animal microbial diversity and function. We used metagenomics to analyze the gut microbiota of more than 180 species in the wild, covering diverse classes, feeding behaviors, geographies, and traits. Using de novo metagenome assembly, we constructed and functionally annotated a database of more than 5000 genomes, comprising 1209 bacterial species of which 75% are unknown. The microbial composition, diversity, and functional content exhibit associations with animal taxonomy, diet, activity, social structure, and life span. We identify the gut microbiota of wild animals as a largely untapped resource for the discovery of therapeutics and biotechnology applications.

SARS-CoV-2 antibody testing for estimating COVID-19 prevalence in the population.

Reliable antibody testing against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has the potential to uncover the population-wide spread of coronavirus disease 2019 (COVID-19), which is critical for making informed healthcare and economic decisions. Here we review different types of antibody tests available for SARS-CoV-2 and their application for population-scale testing. Biases because of varying test accuracy, results of ongoing large-scale serological studies, and use of antibody testing for monitoring development of herd immunity are summarized. Although current SARS-CoV-2 antibody testing efforts have generated valuable insights, the accuracy of serological tests and the selection criteria for the tested cohorts need to be evaluated carefully.

A reference map of potential determinants for the human serum metabolome.

The serum metabolome contains a plethora of biomarkers and causative agents of various diseases, some of which are endogenously produced and some that have been taken up from the environment1. The origins of specific compounds are known, including metabolites that are highly heritable2,3, or those that are influenced by the gut microbiome4, by lifestyle choices such as smoking5, or by diet6. However, the key determinants of most metabolites are still poorly understood. Here we measured the levels of 1,251 metabolites in serum samples from a unique and deeply phenotyped healthy human cohort of 491 individuals. We applied machine-learning algorithms to predict metabolite levels in held-out individuals on the basis of host genetics, gut microbiome, clinical parameters, diet, lifestyle and anthropometric measurements, and obtained statistically significant predictions for more than 76% of the profiled metabolites. Diet and microbiome had the strongest predictive power, and each explained hundreds of metabolites-in some cases, explaining more than 50% of the observed variance. We further validated microbiome-related predictions by showing a high replication rate in two geographically independent cohorts7,8 that were not available to us when we trained the algorithms. We used feature attribution analysis9 to reveal specific dietary and bacterial interactions. We further demonstrate that some of these interactions might be causal, as some metabolites that we predicted to be positively associated with bread were found to increase after a randomized clinical trial of bread intervention. Overall, our results reveal potential determinants of more than 800 metabolites, paving the way towards a mechanistic understanding of alterations in metabolites under different conditions and to designing interventions for manipulating the levels of circulating metabolites.

A Significant Expansion of Our Understanding of the Composition of the Human Microbiome.

Shotgun sequencing of samples taken from the human microbiome often reveals only partial mapping of the sequenced metagenomic reads to existing reference genomes. Such partial mappability indicates that many genomes are missing in our reference genome set. This is particularly true for non-Western populations and for samples that do not originate from the gut. Pasolli et al. (E. Pasolli, F. Asnicar, S. Manara, M. Zolfo, et al., Cell, 2019, https://doi.org/10.1016/j.cell.2019.01.001) perform a grand effort to expand the reference set, and to better classify its members, revealing a wider pangenome of existing species as well as identifying new species of previously unknown taxonomic branches.