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Zahavi L, Lavon A, Reicher L, Shoer S, Godneva A, Leviatan S, Rein M, Weissbrod O, Weinberger A, Segal E. Bacterial SNPs in the human gut microbiome associate with host BMI. Nat Med 2023; 29:2785-2792. [PMID: 37919437 PMCID: PMC10999242 DOI: 10.1038/s41591-023-02599-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2022] [Accepted: 09/19/2023] [Indexed: 11/04/2023]
Abstract
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.
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Affiliation(s)
- Liron Zahavi
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel
| | - Amit Lavon
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel
| | - Lee Reicher
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel
- Lis Maternity and Women's Hospital, Tel Aviv Sourasky Medical Center, Tel Aviv University (affiliated with Sackler Faculty of Medicine), Tel Aviv, Israel
| | - Saar Shoer
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel
| | - Anastasia Godneva
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel
| | - Sigal Leviatan
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel
| | - Michal Rein
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel
| | | | - Adina Weinberger
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel
| | - Eran Segal
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel.
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel.
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2
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Andreu-Sánchez S, Bourgonje AR, Vogl T, Kurilshikov A, Leviatan S, Ruiz-Moreno AJ, Hu S, Sinha T, Vich Vila A, Klompus S, Kalka IN, de Leeuw K, Arends S, Jonkers I, Withoff S, Brouwer E, Weinberger A, Wijmenga C, Segal E, Weersma RK, Fu J, Zhernakova A. Phage display sequencing reveals that genetic, environmental, and intrinsic factors influence variation of human antibody epitope repertoire. Immunity 2023; 56:1376-1392.e8. [PMID: 37164013 DOI: 10.1016/j.immuni.2023.04.003] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Revised: 12/13/2022] [Accepted: 04/06/2023] [Indexed: 05/12/2023]
Abstract
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.
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Affiliation(s)
- Sergio Andreu-Sánchez
- Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands; Department of Pediatrics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Arno R Bourgonje
- Department of Gastroenterology and Hepatology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Thomas Vogl
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel; Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel; Diagnostic and Research Institute of Hygiene, Microbiology and Environmental Medicine, Medical University Graz, Graz, Austria; Center for Cancer Research, Medical University of Vienna, Wien, Austria.
| | - Alexander Kurilshikov
- Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Sigal Leviatan
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel; Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel
| | - Angel J Ruiz-Moreno
- Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Shixian Hu
- Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands; Department of Gastroenterology and Hepatology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Trishla Sinha
- Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Arnau Vich Vila
- Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands; Department of Gastroenterology and Hepatology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Shelley Klompus
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel; Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel
| | - Iris N Kalka
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel
| | - Karina de Leeuw
- Department of Rheumatology and Clinical Immunology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Suzanne Arends
- Department of Rheumatology and Clinical Immunology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Iris Jonkers
- Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Sebo Withoff
- Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Elisabeth Brouwer
- Department of Rheumatology and Clinical Immunology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Adina Weinberger
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel; Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel
| | - Cisca Wijmenga
- Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Eran Segal
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel; Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel
| | - Rinse K Weersma
- Department of Gastroenterology and Hepatology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Jingyuan Fu
- Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands; Department of Pediatrics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Alexandra Zhernakova
- Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.
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3
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Bourgonje AR, Andreu-Sánchez S, Vogl T, Hu S, Vich Vila A, Gacesa R, Leviatan S, Kurilshikov A, Klompus S, Kalka IN, van Dullemen HM, Weinberger A, Visschedijk MC, Festen EAM, Faber KN, Wijmenga C, Dijkstra G, Segal E, Fu J, Zhernakova A, Weersma RK. Phage-display immunoprecipitation sequencing of the antibody epitope repertoire in inflammatory bowel disease reveals distinct antibody signatures. Immunity 2023; 56:1393-1409.e6. [PMID: 37164015 DOI: 10.1016/j.immuni.2023.04.017] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Revised: 12/13/2022] [Accepted: 04/14/2023] [Indexed: 05/12/2023]
Abstract
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.
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Affiliation(s)
- Arno R Bourgonje
- Department of Gastroenterology and Hepatology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Sergio Andreu-Sánchez
- Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands; Department of Pediatrics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Thomas Vogl
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel; Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel; Diagnostic and Research Institute of Hygiene, Microbiology and Environmental Medicine, Medical University Graz, Graz, Austria; Center for Cancer Research, Medical University of Vienna, Wien, Austria
| | - Shixian Hu
- Department of Gastroenterology and Hepatology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands; Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Arnau Vich Vila
- Department of Gastroenterology and Hepatology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands; Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Ranko Gacesa
- Department of Gastroenterology and Hepatology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands; Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Sigal Leviatan
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel; Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel
| | - Alexander Kurilshikov
- Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Shelley Klompus
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel; Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel
| | - Iris N Kalka
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel; Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel
| | - Hendrik M van Dullemen
- Department of Gastroenterology and Hepatology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Adina Weinberger
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel; Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel
| | - Marijn C Visschedijk
- Department of Gastroenterology and Hepatology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Eleonora A M Festen
- Department of Gastroenterology and Hepatology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Klaas Nico Faber
- Department of Gastroenterology and Hepatology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Cisca Wijmenga
- Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Gerard Dijkstra
- Department of Gastroenterology and Hepatology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Eran Segal
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel; Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel
| | - Jingyuan Fu
- Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands; Department of Pediatrics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Alexandra Zhernakova
- Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Rinse K Weersma
- Department of Gastroenterology and Hepatology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.
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4
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Vogl T, Kalka IN, Klompus S, Leviatan S, Weinberger A, Segal E. Systemic antibody responses against human microbiota flagellins are overrepresented in chronic fatigue syndrome patients. Sci Adv 2022; 8:eabq2422. [PMID: 36149952 DOI: 10.1126/sciadv.abq2422] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
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.
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Affiliation(s)
- Thomas Vogl
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel
- Diagnostic and Research Institute of Hygiene, Microbiology and Environmental Medicine, Medical University Graz, Graz, Austria
| | - Iris N Kalka
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel
| | - Shelley Klompus
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel
| | - Sigal Leviatan
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel
| | - Adina Weinberger
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel
| | - Eran Segal
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel
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5
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Rothschild D, Leviatan S, Hanemann A, Cohen Y, Weissbrod O, Segal E. An atlas of robust microbiome associations with phenotypic traits based on large-scale cohorts from two continents. PLoS One 2022; 17:e0265756. [PMID: 35324954 PMCID: PMC8947124 DOI: 10.1371/journal.pone.0265756] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2021] [Accepted: 03/07/2022] [Indexed: 12/12/2022] Open
Abstract
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.
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Affiliation(s)
- Daphna Rothschild
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel
| | - Sigal Leviatan
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel
| | | | | | - Omer Weissbrod
- Epidemiology Department, Harvard T.H. Chan School of Public Health, Boston, MA, United States of America
| | - Eran Segal
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel
- * E-mail:
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6
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Klompus S, Leviatan S, Vogl T, Mazor RD, Kalka IN, Stoler-Barak L, Nathan N, Peres A, Moss L, Godneva A, Kagan Ben Tikva S, Shinar E, Dvashi HC, Gabizon R, London N, Diskin R, Yaari G, Weinberger A, Shulman Z, Segal E. Cross-reactive antibodies against human coronaviruses and the animal coronavirome suggest diagnostics for future zoonotic spillovers. Sci Immunol 2021; 6:6/61/eabe9950. [PMID: 34326184 PMCID: PMC9267281 DOI: 10.1126/sciimmunol.abe9950] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2020] [Accepted: 07/27/2021] [Indexed: 12/12/2022]
Abstract
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.
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Affiliation(s)
- Shelley Klompus
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot 76100, Israel.,Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot 76100, Israel
| | - Sigal Leviatan
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot 76100, Israel.,Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot 76100, Israel
| | - Thomas Vogl
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot 76100, Israel .,Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot 76100, Israel.,Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot 76100, Israel
| | - Roei D Mazor
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot 76100, Israel.,Department of Immunology, Weizmann Institute of Science, Rehovot 76100, Israel
| | - Iris N Kalka
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot 76100, Israel.,Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot 76100, Israel.,Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot 76100, Israel
| | - Liat Stoler-Barak
- Department of Immunology, Weizmann Institute of Science, Rehovot 76100, Israel.,Department of Immunology, Weizmann Institute of Science, Rehovot 76100, Israel
| | - Nachum Nathan
- Department of Immunology, Weizmann Institute of Science, Rehovot 76100, Israel
| | - Ayelet Peres
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot 76100, Israel.,Faculty of Engineering, Bar Ilan University, Ramat Gan 52900, Israel
| | - Lihee Moss
- Department of Immunology, Weizmann Institute of Science, Rehovot 76100, Israel
| | - Anastasia Godneva
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot 76100, Israel.,Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot 76100, Israel
| | - Sharon Kagan Ben Tikva
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot 76100, Israel.,Department of Immunology, Weizmann Institute of Science, Rehovot 76100, Israel
| | | | - Hadas Cohen Dvashi
- Department of Chemical and Structural Biology, Weizmann Institute of Science, Rehovot 7610001, Israel
| | - Ronen Gabizon
- Department of Chemical and Structural Biology, Weizmann Institute of Science, Rehovot 7610001, Israel
| | - Nir London
- Department of Chemical and Structural Biology, Weizmann Institute of Science, Rehovot 7610001, Israel
| | - Ron Diskin
- Department of Chemical and Structural Biology, Weizmann Institute of Science, Rehovot 7610001, Israel
| | - Gur Yaari
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot 76100, Israel.,Faculty of Engineering, Bar Ilan University, Ramat Gan 52900, Israel
| | - Adina Weinberger
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot 76100, Israel.,Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot 76100, Israel.,Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot 76100, Israel
| | - Ziv Shulman
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot 76100, Israel .,Department of Immunology, Weizmann Institute of Science, Rehovot 76100, Israel
| | - Eran Segal
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot 76100, Israel .,Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot 76100, Israel.,Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot 76100, Israel
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7
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Levi I, Gurevich M, Perlman G, Magalashvili D, Menascu S, Bar N, Godneva A, Zahavi L, Chermon D, Kosower N, Wolf BC, Malka G, Lotan-Pompan M, Weinberger A, Yirmiya E, Rothschild D, Leviatan S, Tsur A, Didkin M, Dreyer S, Eizikovitz H, Titngi Y, Mayost S, Sonis P, Dolev M, Stern Y, Achiron A, Segal E. Potential role of indolelactate and butyrate in multiple sclerosis revealed by integrated microbiome-metabolome analysis. Cell Rep Med 2021; 2:100246. [PMID: 33948576 PMCID: PMC8080254 DOI: 10.1016/j.xcrm.2021.100246] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2019] [Revised: 01/18/2021] [Accepted: 03/18/2021] [Indexed: 12/12/2022]
Abstract
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.
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Affiliation(s)
- Izhak Levi
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot 7610001, Israel
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot 7610001, Israel
| | - Michael Gurevich
- Multiple Sclerosis Center, Sheba Medical Center, Tel Hashomer, Ramat-Gan 526200, Israel
| | - Gal Perlman
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot 7610001, Israel
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot 7610001, Israel
| | - David Magalashvili
- Multiple Sclerosis Center, Sheba Medical Center, Tel Hashomer, Ramat-Gan 526200, Israel
| | - Shay Menascu
- Multiple Sclerosis Center, Sheba Medical Center, Tel Hashomer, Ramat-Gan 526200, Israel
- Sackler School of Medicine, Tel-Aviv University, Tel Aviv 69978, Israel
| | - Noam Bar
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot 7610001, Israel
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot 7610001, Israel
| | - Anastasia Godneva
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot 7610001, Israel
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot 7610001, Israel
| | - Liron Zahavi
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot 7610001, Israel
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot 7610001, Israel
| | - Danyel Chermon
- Multiple Sclerosis Center, Sheba Medical Center, Tel Hashomer, Ramat-Gan 526200, Israel
| | - Noa Kosower
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot 7610001, Israel
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot 7610001, Israel
| | - Bat Chen Wolf
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot 7610001, Israel
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot 7610001, Israel
| | - Gal Malka
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot 7610001, Israel
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot 7610001, Israel
| | - Maya Lotan-Pompan
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot 7610001, Israel
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot 7610001, Israel
| | - Adina Weinberger
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot 7610001, Israel
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot 7610001, Israel
| | - Erez Yirmiya
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot 7610001, Israel
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot 7610001, Israel
| | - Daphna Rothschild
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot 7610001, Israel
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot 7610001, Israel
| | - Sigal Leviatan
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot 7610001, Israel
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot 7610001, Israel
| | - Avishag Tsur
- Multiple Sclerosis Center, Sheba Medical Center, Tel Hashomer, Ramat-Gan 526200, Israel
| | - Maria Didkin
- Multiple Sclerosis Center, Sheba Medical Center, Tel Hashomer, Ramat-Gan 526200, Israel
| | - Sapir Dreyer
- Multiple Sclerosis Center, Sheba Medical Center, Tel Hashomer, Ramat-Gan 526200, Israel
| | - Hen Eizikovitz
- Multiple Sclerosis Center, Sheba Medical Center, Tel Hashomer, Ramat-Gan 526200, Israel
| | - Yamit Titngi
- Multiple Sclerosis Center, Sheba Medical Center, Tel Hashomer, Ramat-Gan 526200, Israel
| | - Sue Mayost
- Multiple Sclerosis Center, Sheba Medical Center, Tel Hashomer, Ramat-Gan 526200, Israel
| | - Polina Sonis
- Multiple Sclerosis Center, Sheba Medical Center, Tel Hashomer, Ramat-Gan 526200, Israel
| | - Mark Dolev
- Multiple Sclerosis Center, Sheba Medical Center, Tel Hashomer, Ramat-Gan 526200, Israel
| | - Yael Stern
- Multiple Sclerosis Center, Sheba Medical Center, Tel Hashomer, Ramat-Gan 526200, Israel
| | - Anat Achiron
- Multiple Sclerosis Center, Sheba Medical Center, Tel Hashomer, Ramat-Gan 526200, Israel
- Sackler School of Medicine, Tel-Aviv University, Tel Aviv 69978, Israel
| | - Eran Segal
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot 7610001, Israel
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot 7610001, Israel
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8
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Levin D, Raab N, Pinto Y, Rothschild D, Zanir G, Godneva A, Mellul N, Futorian D, Gal D, Leviatan S, Zeevi D, Bachelet I, Segal E. Diversity and functional landscapes in the microbiota of animals in the wild. Science 2021; 372:science.abb5352. [PMID: 33766942 DOI: 10.1126/science.abb5352] [Citation(s) in RCA: 68] [Impact Index Per Article: 22.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2020] [Revised: 07/17/2020] [Accepted: 03/09/2021] [Indexed: 12/11/2022]
Abstract
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.
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Affiliation(s)
| | | | | | - Daphna Rothschild
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, 7610001 Israel.,Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot 7610001, Israel.,Department of Developmental Biology, Stanford University, Stanford, CA 94305, USA.,Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | | | - Anastasia Godneva
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, 7610001 Israel.,Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot 7610001, Israel
| | | | | | | | - Sigal Leviatan
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, 7610001 Israel.,Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot 7610001, Israel
| | - David Zeevi
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, 7610001 Israel.,Center for Studies in Physics and Biology, Rockefeller University, New York, NY 10065, USA
| | - Ido Bachelet
- Wild Biotech, Rehovot, Israel.,Augmanity, Rehovot, Israel
| | - Eran Segal
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, 7610001 Israel. .,Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot 7610001, Israel
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9
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Abstract
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.
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Affiliation(s)
- Thomas Vogl
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel
| | - Sigal Leviatan
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel
| | - Eran Segal
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel
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11
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Bar N, Korem T, Weissbrod O, Zeevi D, Rothschild D, Leviatan S, Kosower N, Lotan-Pompan M, Weinberger A, Le Roy CI, Menni C, Visconti A, Falchi M, Spector TD, Adamski J, Franks PW, Pedersen O, Segal E. A reference map of potential determinants for the human serum metabolome. Nature 2020; 588:135-140. [DOI: 10.1038/s41586-020-2896-2] [Citation(s) in RCA: 121] [Impact Index Per Article: 30.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2019] [Accepted: 09/29/2020] [Indexed: 12/13/2022]
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