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Dokoshi T, Chen Y, Cavagnero KJ, Rahman G, Hakim D, Brinton S, Schwarz H, Brown EA, O'Neill A, Nakamura Y, Li F, Salzman NH, Knight R, Gallo RL. Dermal injury drives a skin to gut axis that disrupts the intestinal microbiome and intestinal immune homeostasis in mice. Nat Commun 2024; 15:3009. [PMID: 38589392 PMCID: PMC11001995 DOI: 10.1038/s41467-024-47072-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Accepted: 03/20/2024] [Indexed: 04/10/2024] Open
Abstract
The composition of the microbial community in the intestine may influence the functions of distant organs such as the brain, lung, and skin. These microbes can promote disease or have beneficial functions, leading to the hypothesis that microbes in the gut explain the co-occurrence of intestinal and skin diseases. Here, we show that the reverse can occur, and that skin directly alters the gut microbiome. Disruption of the dermis by skin wounding or the digestion of dermal hyaluronan results in increased expression in the colon of the host defense genes Reg3 and Muc2, and skin wounding changes the composition and behavior of intestinal bacteria. Enhanced expression Reg3 and Muc2 is induced in vitro by exposure to hyaluronan released by these skin interventions. The change in the colon microbiome after skin wounding is functionally important as these bacteria penetrate the intestinal epithelium and enhance colitis from dextran sodium sulfate (DSS) as seen by the ability to rescue skin associated DSS colitis with oral antibiotics, in germ-free mice, and fecal microbiome transplantation to unwounded mice from mice with skin wounds. These observations provide direct evidence of a skin-gut axis by demonstrating that damage to the skin disrupts homeostasis in intestinal host defense and alters the gut microbiome.
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Affiliation(s)
- Tatsuya Dokoshi
- Department of Dermatology, University of California, San Diego, La Jolla, CA, USA
| | - Yang Chen
- Department of Dermatology, University of California, San Diego, La Jolla, CA, USA
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA
| | - Kellen J Cavagnero
- Department of Dermatology, University of California, San Diego, La Jolla, CA, USA
| | - Gibraan Rahman
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA
| | - Daniel Hakim
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA
| | - Samantha Brinton
- Department of Dermatology, University of California, San Diego, La Jolla, CA, USA
| | - Hana Schwarz
- Department of Dermatology, University of California, San Diego, La Jolla, CA, USA
| | - Elizabeth A Brown
- Department of Dermatology, University of California, San Diego, La Jolla, CA, USA
| | - Alan O'Neill
- Department of Dermatology, University of California, San Diego, La Jolla, CA, USA
| | - Yoshiyuki Nakamura
- Department of Dermatology, University of California, San Diego, La Jolla, CA, USA
| | - Fengwu Li
- Department of Dermatology, University of California, San Diego, La Jolla, CA, USA
| | - Nita H Salzman
- Department of Pediatrics, Division of Gastroenterology and Center for Microbiome Research, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Rob Knight
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA
- Department of Computer Science & Engineering, University of California, San Diego, La Jolla, CA, USA
- Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA
- Center for Microbiome Innovation, University of California, San Diego, La Jolla, CA, USA
| | - Richard L Gallo
- Department of Dermatology, University of California, San Diego, La Jolla, CA, USA.
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2
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Liu Y, Ritchie SC, Teo SM, Ruuskanen MO, Kambur O, Zhu Q, Sanders J, Vázquez-Baeza Y, Verspoor K, Jousilahti P, Lahti L, Niiranen T, Salomaa V, Havulinna AS, Knight R, Méric G, Inouye M. Integration of polygenic and gut metagenomic risk prediction for common diseases. NATURE AGING 2024; 4:584-594. [PMID: 38528230 PMCID: PMC11031402 DOI: 10.1038/s43587-024-00590-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Accepted: 02/13/2024] [Indexed: 03/27/2024]
Abstract
Multiomics has shown promise in noninvasive risk profiling and early detection of various common diseases. In the present study, in a prospective population-based cohort with ~18 years of e-health record follow-up, we investigated the incremental and combined value of genomic and gut metagenomic risk assessment compared with conventional risk factors for predicting incident coronary artery disease (CAD), type 2 diabetes (T2D), Alzheimer disease and prostate cancer. We found that polygenic risk scores (PRSs) improved prediction over conventional risk factors for all diseases. Gut microbiome scores improved predictive capacity over baseline age for CAD, T2D and prostate cancer. Integrated risk models of PRSs, gut microbiome scores and conventional risk factors achieved the highest predictive performance for all diseases studied compared with models based on conventional risk factors alone. The present study demonstrates that integrated PRSs and gut metagenomic risk models improve the predictive value over conventional risk factors for common chronic diseases.
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Affiliation(s)
- Yang Liu
- Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia.
- Department of Clinical Pathology, Melbourne Medical School, University of Melbourne, Melbourne, Victoria, Australia.
- Victor Phillip Dahdaleh Heart and Lung Research Institute, University of Cambridge, Cambridge, UK.
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
| | - Scott C Ritchie
- Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
- Victor Phillip Dahdaleh Heart and Lung Research Institute, University of Cambridge, Cambridge, UK
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- British Heart Foundation Cambridge Centre of Research Excellence, School of Clinical Medicine, University of Cambridge, Cambridge, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK
| | - Shu Mei Teo
- Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
- Centre for Youth Mental Health, University of Melbourne, Melbourne, Victoria, Australia
| | - Matti O Ruuskanen
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland
- Department of Computing, University of Turku, Turku, Finland
| | - Oleg Kambur
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Qiyun Zhu
- School of Life Sciences, Arizona State University, Tempe, AZ, USA
- Biodesign Center for Fundamental and Applied Microbiomics, Arizona State University, Tempe, AZ, USA
| | - Jon Sanders
- Department of Ecology and Evolutionary Biology, Cornell University, Ithaca, NY, USA
| | - Yoshiki Vázquez-Baeza
- Center for Microbiome Innovation, Jacobs School of Engineering, University of California San Diego, La Jolla, CA, USA
| | - Karin Verspoor
- School of Computing Technologies, RMIT University, Melbourne, Victoria, Australia
- School of Computing and Information Systems, University of Melbourne, Melbourne, Victoria, Australia
| | - Pekka Jousilahti
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Leo Lahti
- Department of Computing, University of Turku, Turku, Finland
| | - Teemu Niiranen
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland
- Division of Medicine, Turku University Hospital and University of Turku, Turku, Finland
| | - Veikko Salomaa
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Aki S Havulinna
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland
- Institute for Molecular Medicine Finland, FIMM-HiLIFE, University of Helsinki, Helsinki, Finland
| | - Rob Knight
- Center for Microbiome Innovation, Jacobs School of Engineering, University of California San Diego, La Jolla, CA, USA
- Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA, USA
- Department of Pediatrics, School of Medicine, University of California San Diego, La Jolla, CA, USA
| | - Guillaume Méric
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
- Central Clinical School, Monash University, Melbourne, Victoria, Australia
- Department of Cardiometabolic Health, University of Melbourne, Melbourne, Victoria, Australia
- Department of Cardiovascular Research, Translation and Implementation, La Trobe University, Melbourne, Victoria, Australia
- Department of Medical Sciences, Molecular Epidemiology, Uppsala University, Uppsala, Sweden
| | - Michael Inouye
- Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia.
- Department of Clinical Pathology, Melbourne Medical School, University of Melbourne, Melbourne, Victoria, Australia.
- Victor Phillip Dahdaleh Heart and Lung Research Institute, University of Cambridge, Cambridge, UK.
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
- British Heart Foundation Cambridge Centre of Research Excellence, School of Clinical Medicine, University of Cambridge, Cambridge, UK.
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK.
- The Alan Turing Institute, London, UK.
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3
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Burcham ZM, Belk AD, McGivern BB, Bouslimani A, Ghadermazi P, Martino C, Shenhav L, Zhang AR, Shi P, Emmons A, Deel HL, Xu ZZ, Nieciecki V, Zhu Q, Shaffer M, Panitchpakdi M, Weldon KC, Cantrell K, Ben-Hur A, Reed SC, Humphry GC, Ackermann G, McDonald D, Chan SHJ, Connor M, Boyd D, Smith J, Watson JMS, Vidoli G, Steadman D, Lynne AM, Bucheli S, Dorrestein PC, Wrighton KC, Carter DO, Knight R, Metcalf JL. A conserved interdomain microbial network underpins cadaver decomposition despite environmental variables. Nat Microbiol 2024; 9:595-613. [PMID: 38347104 PMCID: PMC10914610 DOI: 10.1038/s41564-023-01580-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Accepted: 12/08/2023] [Indexed: 03/07/2024]
Abstract
Microbial breakdown of organic matter is one of the most important processes on Earth, yet the controls of decomposition are poorly understood. Here we track 36 terrestrial human cadavers in three locations and show that a phylogenetically distinct, interdomain microbial network assembles during decomposition despite selection effects of location, climate and season. We generated a metagenome-assembled genome library from cadaver-associated soils and integrated it with metabolomics data to identify links between taxonomy and function. This universal network of microbial decomposers is characterized by cross-feeding to metabolize labile decomposition products. The key bacterial and fungal decomposers are rare across non-decomposition environments and appear unique to the breakdown of terrestrial decaying flesh, including humans, swine, mice and cattle, with insects as likely important vectors for dispersal. The observed lockstep of microbial interactions further underlies a robust microbial forensic tool with the potential to aid predictions of the time since death.
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Affiliation(s)
- Zachary M Burcham
- Department of Animal Sciences, Colorado State University, Fort Collins, CO, USA
- Department of Microbiology, University of Tennessee, Knoxville, TN, USA
| | - Aeriel D Belk
- Department of Animal Sciences, Colorado State University, Fort Collins, CO, USA
- Department of Animal Sciences, Auburn University, Auburn, AL, USA
| | - Bridget B McGivern
- Department of Soil and Crop Sciences, Colorado State University, Fort Collins, CO, USA
| | - Amina Bouslimani
- Collaborative Mass Spectrometry Innovation Center, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, San Diego, CA, USA
| | - Parsa Ghadermazi
- Department of Chemical and Biological Engineering, Colorado State University, Fort Collins, CO, USA
| | - Cameron Martino
- Department of Pediatrics, University of California San Diego, La Jolla, California, USA
| | - Liat Shenhav
- Center for Studies in Physics and Biology, Rockefeller University, New York, NY, USA
- Institute for Systems Genetics, New York Grossman School of Medicine, New York University, New York, NY, USA
- Department of Computer Science, New York University, New York, NY, USA
| | - Anru R Zhang
- Department of Biostatistics and Bioinformatics, Duke University, Durham, NC, USA
- Department of Computer Science, Duke University, Durham, NC, USA
| | - Pixu Shi
- Department of Biostatistics and Bioinformatics, Duke University, Durham, NC, USA
| | - Alexandra Emmons
- Department of Animal Sciences, Colorado State University, Fort Collins, CO, USA
| | - Heather L Deel
- Graduate Program in Cell and Molecular Biology, Colorado State University, Fort Collins, CO, USA
| | - Zhenjiang Zech Xu
- School of Food Science and Technology, Nanchang University, Nanchang, Jiangxi, China
| | - Victoria Nieciecki
- Department of Animal Sciences, Colorado State University, Fort Collins, CO, USA
- Graduate Program in Cell and Molecular Biology, Colorado State University, Fort Collins, CO, USA
| | - Qiyun Zhu
- Department of Pediatrics, University of California San Diego, La Jolla, California, USA
- School of Life Sciences, Arizona State University, Tempe, AZ, USA
- Center for Fundamental and Applied Microbiomics, Arizona State University, Tempe, AZ, USA
| | - Michael Shaffer
- Department of Soil and Crop Sciences, Colorado State University, Fort Collins, CO, USA
| | - Morgan Panitchpakdi
- Collaborative Mass Spectrometry Innovation Center, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, San Diego, CA, USA
| | - Kelly C Weldon
- Collaborative Mass Spectrometry Innovation Center, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, San Diego, CA, USA
| | - Kalen Cantrell
- Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA, USA
| | - Asa Ben-Hur
- Department of Computer Science, Colorado State University, Fort Collins, CO, USA
| | - Sasha C Reed
- U.S. Geological Survey, Southwest Biological Science Center, Moab, UT, USA
| | - Greg C Humphry
- Department of Pediatrics, University of California San Diego, La Jolla, California, USA
| | - Gail Ackermann
- Department of Pediatrics, University of California San Diego, La Jolla, California, USA
| | - Daniel McDonald
- Department of Pediatrics, University of California San Diego, La Jolla, California, USA
| | - Siu Hung Joshua Chan
- Department of Chemical and Biological Engineering, Colorado State University, Fort Collins, CO, USA
| | - Melissa Connor
- Forensic Investigation Research Station, Colorado Mesa University, Grand Junction, CO, USA
| | - Derek Boyd
- Forensic Anthropology Center, Department of Anthropology, University of Tennessee, Knoxville, TN, USA
- Department of Social, Cultural, and Justice Studies, University of Tennessee at Chattanooga, Chattanooga, TN, USA
| | - Jake Smith
- Forensic Anthropology Center, Department of Anthropology, University of Tennessee, Knoxville, TN, USA
- Mid-America College of Funeral Service, Jeffersonville, IN, USA
| | - Jenna M S Watson
- Forensic Anthropology Center, Department of Anthropology, University of Tennessee, Knoxville, TN, USA
| | - Giovanna Vidoli
- Forensic Anthropology Center, Department of Anthropology, University of Tennessee, Knoxville, TN, USA
| | - Dawnie Steadman
- Forensic Anthropology Center, Department of Anthropology, University of Tennessee, Knoxville, TN, USA
| | - Aaron M Lynne
- Department of Biological Sciences, Sam Houston State University, Huntsville, TX, USA
| | - Sibyl Bucheli
- Department of Biological Sciences, Sam Houston State University, Huntsville, TX, USA
| | - Pieter C Dorrestein
- Collaborative Mass Spectrometry Innovation Center, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, San Diego, CA, USA
| | - Kelly C Wrighton
- Department of Soil and Crop Sciences, Colorado State University, Fort Collins, CO, USA
| | - David O Carter
- Laboratory of Forensic Taphonomy, Forensic Sciences Unit, School of Natural Sciences and Mathematics, Chaminade University of Honolulu, Honolulu, HI, USA
| | - Rob Knight
- Department of Pediatrics, University of California San Diego, La Jolla, California, USA
- Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA, USA
- Center for Microbiome Innovation, University of California San Diego, La Jolla, CA, USA
- Department of Bioengineering, University of California San Diego, La Jolla, CA, USA
| | - Jessica L Metcalf
- Department of Animal Sciences, Colorado State University, Fort Collins, CO, USA.
- Graduate Program in Cell and Molecular Biology, Colorado State University, Fort Collins, CO, USA.
- Humans and the Microbiome Program, Canadian Institute for Advanced Research, Toronto, Ontario, Canada.
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4
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Dalton KR, Lee M, Wang Z, Zhao S, Parks CG, Beane-Freeman LE, Motsinger-Reif AA, London SJ. Occupational farm work activities influence workers' indoor home microbiome. ENVIRONMENTAL RESEARCH 2024; 243:117819. [PMID: 38052359 PMCID: PMC10872285 DOI: 10.1016/j.envres.2023.117819] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/05/2023] [Revised: 11/10/2023] [Accepted: 11/27/2023] [Indexed: 12/07/2023]
Abstract
BACKGROUND Farm work entails a heterogeneous mixture of exposures that vary considerably across farms and farmers. Farm work is associated with various health outcomes, both adverse and beneficial. One mechanism by which farming exposures can impact health is through the microbiome, including the indoor home environment microbiome. It is unknown how individual occupational exposures shape the microbial composition in workers' homes. OBJECTIVES We investigated associations between farm work activities, including specific tasks and pesticide use, and the indoor microbiome in the homes of 468 male farmers. METHODS Participants were licensed pesticide applicators, mostly farmers, enrolled in the Agricultural Lung Health Study from 2008 to 2011. Vacuumed dust from participants' bedrooms underwent whole-genome shotgun sequencing for indoor microbiome assessment. Using questionnaire data, we evaluated 6 farm work tasks (processing of either hay, silage, animal feed, fertilizer, or soy/grains, and cleaning grain bins) and 19 pesticide ingredients currently used in the past year, plus 7 banned persistent pesticide ingredients ever used. RESULTS All 6 work tasks were associated with increased microbial diversity levels, with a positive dose-response for the total number of tasks performed (P = 0.001). All tasks were associated with altered microbial compositions (weighted UniFrac P = 0.001) and with higher abundance of specific microbes, including soil-based commensal microbes such as Haloterrigena. Among the 19 pesticides, current use of glyphosate and past use of lindane were associated with increased microbial diversity (P = 0.02-0.04). Ten currently used pesticides and all 7 banned pesticides were associated with altered microbial composition (P = 0.001-0.04). Six pesticides were associated with differential abundance of certain microbes. DISCUSSION Different farm activities and exposures can uniquely impact the dust microbiome inside homes. Our work suggests that changes to the home microbiome could serve as one pathway for how occupational exposures impact the health of workers and their cohabitating family members, offering possible future intervention targets.
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Affiliation(s)
- Kathryn R Dalton
- Genomics and the Environment in Respiratory and Allergic Health Group, Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Durham, NC, USA
| | - Mikyeong Lee
- Genomics and the Environment in Respiratory and Allergic Health Group, Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Durham, NC, USA
| | - Ziyue Wang
- Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Durham, NC, USA
| | - Shanshan Zhao
- Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Durham, NC, USA
| | - Christine G Parks
- Genomics and the Environment in Respiratory and Allergic Health Group, Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Durham, NC, USA
| | - Laura E Beane-Freeman
- Occupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Alison A Motsinger-Reif
- Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Durham, NC, USA
| | - Stephanie J London
- Genomics and the Environment in Respiratory and Allergic Health Group, Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Durham, NC, USA.
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5
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Oles RE, Terrazas MC, Loomis LR, Hsu CY, Tribelhorn C, Ferre PB, Ea A, Bryant M, Young J, Carrow HC, Sandborn WJ, Dulai P, Sivagnanam M, Pride D, Knight R, Chu H. Pangenome comparison of Bacteroides fragilis genomospecies unveil genetic diversity and ecological insights. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.20.572674. [PMID: 38187556 PMCID: PMC10769428 DOI: 10.1101/2023.12.20.572674] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/09/2024]
Abstract
Bacteroides fragilis is a Gram-negative commensal bacterium commonly found in the human colon that differentiates into two genomospecies termed division I and II. We leverage a comprehensive collection of 694 B. fragilis whole genome sequences and report differential gene abundance to further support the recent proposal that divisions I and II represent separate species. In division I strains, we identify an increased abundance of genes related to complex carbohydrate degradation, colonization, and host niche occupancy, confirming the role of division I strains as gut commensals. In contrast, division II strains display an increased prevalence of plant cell wall degradation genes and exhibit a distinct geographic distribution, primarily originating from Asian countries, suggesting dietary influences. Notably, division II strains have an increased abundance of genes linked to virulence, survival in toxic conditions, and antimicrobial resistance, consistent with a higher incidence of these strains in bloodstream infections. This study provides new evidence supporting a recent proposal for classifying divisions I and II B. fragilis strains as distinct species, and our comparative genomic analysis reveals their niche-specific roles.
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Affiliation(s)
- Renee E Oles
- Department of Pathology, University of California, San Diego, La Jolla, CA
- Department of Pediatrics, School of Medicine, University of California, La Jolla, CA
| | | | - Luke R Loomis
- Department of Pathology, University of California, San Diego, La Jolla, CA
| | - Chia-Yun Hsu
- Department of Pathology, University of California, San Diego, La Jolla, CA
| | - Caitlin Tribelhorn
- Department of Pediatrics, School of Medicine, University of California, La Jolla, CA
| | - Pedro Belda Ferre
- Department of Pediatrics, School of Medicine, University of California, La Jolla, CA
| | - Allison Ea
- Department of Pathology, University of California, San Diego, La Jolla, CA
| | - MacKenzie Bryant
- Department of Pediatrics, School of Medicine, University of California, La Jolla, CA
| | - Jocelyn Young
- Department of Pediatrics, School of Medicine, University of California, La Jolla, CA
- Rady Children's Hospital, San Diego, CA, United States
| | - Hannah C Carrow
- Department of Pathology, University of California, San Diego, La Jolla, CA
| | - William J Sandborn
- Division of Gastroenterology, University of California, San Diego, La Jolla, CA
- Center for Microbiome Innovation, University of California, San Diego, La Jolla, CA
| | - Parambir Dulai
- Division of Gastroenterology, University of California, San Diego, La Jolla, CA
- Division of Gastroenterology, Northwestern University, Chicago, Illinois
| | - Mamata Sivagnanam
- Department of Pediatrics, School of Medicine, University of California, La Jolla, CA
- Rady Children's Hospital, San Diego, CA, United States
| | - David Pride
- Department of Pathology, University of California, San Diego, La Jolla, CA
- Center for Microbiome Innovation, University of California, San Diego, La Jolla, CA
- Center for Innovative Phage Applications and Therapeutics (IPATH), University of California, San Diego, La Jolla, CA
- Center of Advanced Laboratory Medicine (CALM), University of California, San Diego, La Jolla, CA
| | - Rob Knight
- Department of Pediatrics, School of Medicine, University of California, La Jolla, CA
- Center for Microbiome Innovation, University of California, San Diego, La Jolla, CA
- Shu Chien-Gene Lay Department of Bioengineering, University of California San Diego, La Jolla, CA
- Department of Computer Science & Engineering, University of California, San Diego, La Jolla, CA
- Halıcıoğlu Data Science Institute, University of California, San Diego, La Jolla, CA
| | - Hiutung Chu
- Department of Pathology, University of California, San Diego, La Jolla, CA
- Center for Microbiome Innovation, University of California, San Diego, La Jolla, CA
- Chiba University-UC San Diego Center for Mucosal Immunology, Allergy and Vaccines (cMAV), University of California, San Diego, La Jolla, CA
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6
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Yan K, Zhang J, Cai Y, Cao G, Meng L, Soaud SA, Heakel RMY, Ihtisham M, Zhao X, Wei Q, Dai T, Abbas M, El-Sappah AH. Comparative analysis of endophytic fungal communities in bamboo species Phyllostachys edulis, Bambusa rigida, and Pleioblastus amarus. Sci Rep 2023; 13:20910. [PMID: 38017106 PMCID: PMC10684524 DOI: 10.1038/s41598-023-48187-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2023] [Accepted: 11/23/2023] [Indexed: 11/30/2023] Open
Abstract
Fungal endophytes in plant leaf mesophyll form mutually beneficial associations through carbon assimilation, synthesis of biologically active chemicals, and enhancement of aesthetic and nutritional value. Here, we compared community structure, diversity, and richness of endophytic fungi in the leaves of three bamboo species, including Phyllostachys edulis (MZ), Bambusa rigida (KZ), and Pleioblastus amarus (YT) via high-throughput Illumina sequencing. In total, 1070 operational taxonomic units (OTUs) were retrieved and classified into 7 phylum, 27 classes, 82 orders, 185 families, 310 genus, and 448 species. Dominant genera were Cladosporium, Trichomerium, Hannaella, Ascomycota, Sporobolomyces, Camptophora and Strelitziana. The highest fungal diversity was observed in Pleioblastus amarus, followed by Bambusa rigida, and Phyllostachys edulis. Comparatively, monopodial species Ph. edulis and sympodial B. rigida, mixed P. amarus revealed the highest richness of endophytic fungi. We retrieved a few biocontrol agents, Sarocladium and Paraconiothyrium, and unique Sporobolomyces, Camptophora, and Strelitziana genera. FUNGuild analysis revealed the surrounding environment (The annual average temperature is between 15 and 25 °C, and the relative humidity of the air is above 83% all year round) as a source of fungal accumulation in bamboo leaves and their pathogenic nature. Our results provide precise knowledge for better managing bamboo forests and pave the way for isolating secondary metabolites and potential bioactive compounds.
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Affiliation(s)
- Kuan Yan
- Faculty of Agriculture, Forestry and Food Engineering, Yibin University, Yibin, China
- Sichuan Oil Cinnamon Engineering Technology Research Center, Yibin University, Yibin, China
| | - Jian Zhang
- Faculty of Agriculture, Forestry and Food Engineering, Yibin University, Yibin, China
- Sichuan Oil Cinnamon Engineering Technology Research Center, Yibin University, Yibin, China
| | - Yu Cai
- Faculty of Agriculture, Forestry and Food Engineering, Yibin University, Yibin, China
- Sichuan Oil Cinnamon Engineering Technology Research Center, Yibin University, Yibin, China
| | - Guiling Cao
- Faculty of Agriculture, Forestry and Food Engineering, Yibin University, Yibin, China
- Sichuan Oil Cinnamon Engineering Technology Research Center, Yibin University, Yibin, China
| | - Lina Meng
- Faculty of Agriculture, Forestry and Food Engineering, Yibin University, Yibin, China
- Sichuan Oil Cinnamon Engineering Technology Research Center, Yibin University, Yibin, China
| | - Salma A Soaud
- Genetics Department, Faculty of Agriculture, Zagazig University, Zagazig, 44511, Egypt
| | - Rania M Y Heakel
- Genetics Department, Faculty of Agriculture, Zagazig University, Zagazig, 44511, Egypt
| | - Muhammad Ihtisham
- Faculty of Agriculture, Forestry and Food Engineering, Yibin University, Yibin, China
| | - Xianming Zhao
- Faculty of Agriculture, Forestry and Food Engineering, Yibin University, Yibin, China
- Sichuan Oil Cinnamon Engineering Technology Research Center, Yibin University, Yibin, China
| | - Qin Wei
- Faculty of Agriculture, Forestry and Food Engineering, Yibin University, Yibin, China
- Sichuan Oil Cinnamon Engineering Technology Research Center, Yibin University, Yibin, China
| | - Tainfei Dai
- Sichuan Green Food Development Center, Chengdu, 610041, China.
| | - Manzar Abbas
- Faculty of Agriculture, Forestry and Food Engineering, Yibin University, Yibin, China.
| | - Ahmed H El-Sappah
- Faculty of Agriculture, Forestry and Food Engineering, Yibin University, Yibin, China.
- Sichuan Oil Cinnamon Engineering Technology Research Center, Yibin University, Yibin, China.
- Genetics Department, Faculty of Agriculture, Zagazig University, Zagazig, 44511, Egypt.
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7
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Brennan C, Salido RA, Belda-Ferre P, Bryant M, Cowart C, Tiu MD, González A, McDonald D, Tribelhorn C, Zarrinpar A, Knight R. Maximizing the potential of high-throughput next-generation sequencing through precise normalization based on read count distribution. mSystems 2023; 8:e0000623. [PMID: 37350611 PMCID: PMC10469589 DOI: 10.1128/msystems.00006-23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Accepted: 04/24/2023] [Indexed: 06/24/2023] Open
Abstract
Next-generation sequencing technologies have enabled many advances across diverse areas of biology, with many benefiting from increased sample size. Although the cost of running next-generation sequencing instruments has dropped substantially over time, the cost of sample preparation methods has lagged behind. To counter this, researchers have adapted library miniaturization protocols and large sample pools to maximize the number of samples that can be prepared by a certain amount of reagents and sequenced in a single run. However, due to high variability of sample quality, over and underrepresentation of samples in a sequencing run has become a major issue in high-throughput sequencing. This leads to misinterpretation of results due to increased noise, and additional time and cost rerunning underrepresented samples. To overcome this problem, we present a normalization method that uses shallow iSeq sequencing to accurately inform pooling volumes based on read distribution. This method is superior to the widely used fluorometry methods, which cannot specifically target adapter-ligated molecules that contribute to sequencing output. Our normalization method not only quantifies adapter-ligated molecules but also allows normalization of feature space; for example, we can normalize to reads of interest such as non-ribosomal reads. As a result, this normalization method improves the efficiency of high-throughput next-generation sequencing by reducing noise and producing higher average reads per sample with more even sequencing depth. IMPORTANCE High-throughput next generation sequencing (NGS) has significantly contributed to the field of genomics; however, further improvements can maximize the potential of this important tool. Uneven sequencing of samples in a multiplexed run is a common issue that leads to unexpected extra costs or low-quality data. To mitigate this problem, we introduce a normalization method based on read counts rather than library concentration. This method allows for an even distribution of features of interest across samples, improving the statistical power of data sets and preventing the financial loss associated with resequencing libraries. This method optimizes NGS, which already has huge importance across many areas of biology.
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Affiliation(s)
- Caitriona Brennan
- Department of Pediatrics, University of California San Diego, La Jolla, California, USA
| | - Rodolfo A. Salido
- Department of Bioengineering, University of California San Diego, La Jolla, California, USA
| | - Pedro Belda-Ferre
- Department of Pediatrics, University of California San Diego, La Jolla, California, USA
| | - MacKenzie Bryant
- Department of Pediatrics, University of California San Diego, La Jolla, California, USA
| | - Charles Cowart
- Department of Pediatrics, University of California San Diego, La Jolla, California, USA
| | - Maria D. Tiu
- Division of Gastroenterology, University of California San Diego, La Jolla, California, USA
| | - Antonio González
- Department of Pediatrics, University of California San Diego, La Jolla, California, USA
| | - Daniel McDonald
- Department of Pediatrics, University of California San Diego, La Jolla, California, USA
| | - Caitlin Tribelhorn
- Department of Pediatrics, University of California San Diego, La Jolla, California, USA
| | - Amir Zarrinpar
- Division of Gastroenterology, University of California San Diego, La Jolla, California, USA
- Center for Microbiome Innovation, University of California San Diego, La Jolla, California, USA
- VA San Diego Health Sciences, La Jolla, California, USA
| | - Rob Knight
- Department of Pediatrics, University of California San Diego, La Jolla, California, USA
- Department of Bioengineering, University of California San Diego, La Jolla, California, USA
- Center for Microbiome Innovation, University of California San Diego, La Jolla, California, USA
- Department of Computer Science and Engineering, University of California San Diego, La Jolla, California, USA
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8
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Dalton KR, Lee M, Wang Z, Zhao S, Parks CG, Beane-Freeman LE, Motsinger-Reif AA, London SJ. Occupational Farm Work Activities Influence Workers' Indoor Home Microbiome. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.08.17.23293194. [PMID: 37662364 PMCID: PMC10473816 DOI: 10.1101/2023.08.17.23293194] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/05/2023]
Abstract
Background Farm work entails a heterogeneous mixture of exposures that vary considerably across farms and farmers. Farm work is associated with various health outcomes, both adverse and beneficial. One mechanism by which farming exposures can impact health is through the microbiome, including the indoor built environment microbiome. It is unknown how individual occupational exposures shape the microbial composition in workers' homes. Objectives We investigated associations between farm work activities, including specific tasks and pesticide use, and the indoor microbiome in the homes of 468 male farmers. Methods Participants were licensed pesticide applicators, mostly farmers, enrolled in the Agricultural Lung Health Study from 2008-2011. Vacuumed dust from participants' bedrooms underwent whole-genome shotgun sequencing for indoor microbiome assessment. Using questionnaire data, we evaluated 6 farm work tasks (processing of either hay, silage, animal feed, fertilizer, or soy/grains, and cleaning grain bins) and 19 pesticide ingredients currently used in the past year, plus 7 persistent banned pesticide ingredients ever used. Results All 6 work tasks were associated with increased within-sample microbial diversity, with a positive dose-response for the sum of tasks (p=0.001). All tasks were associated with altered overall microbial compositions (weighted UniFrac p=0.001) and with higher abundance of specific microbes, including soil-based microbes such as Haloterrigena. Among the 19 pesticides, only current use of glyphosate and past use of lindane were associated with increased within-sample diversity (p=0.02-0.04). Ten currently used pesticides and all 7 banned pesticides were associated with altered microbial composition (p=0.001-0.04). Six pesticides were associated with differential abundance of certain microbes. Discussion Specific farm activities and exposures can impact the dust microbiome inside homes. Our work suggests that occupational farm exposures could impact the health of workers and their families through modifying the indoor environment, specifically the microbial composition of house dust, offering possible future intervention targets.
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Affiliation(s)
- Kathryn R. Dalton
- Genomics and the Environment in Respiratory and Allergic Health Group, Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Durham, NC, USA
| | - Mikyeong Lee
- Genomics and the Environment in Respiratory and Allergic Health Group, Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Durham, NC, USA
| | - Ziyue Wang
- Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Durham, NC, USA
| | - Shanshan Zhao
- Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Durham, NC, USA
| | - Christine G. Parks
- Genomics and the Environment in Respiratory and Allergic Health Group, Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Durham, NC, USA
| | - Laura E. Beane-Freeman
- Occupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Alison A. Motsinger-Reif
- Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Durham, NC, USA
| | - Stephanie J. London
- Genomics and the Environment in Respiratory and Allergic Health Group, Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Durham, NC, USA
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9
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Wang Z, Dalton KR, Lee M, Parks CG, Beane Freeman LE, Zhu Q, González A, Knight R, Zhao S, Motsinger-Reif AA, London SJ. Metagenomics reveals novel microbial signatures of farm exposures in house dust. Front Microbiol 2023; 14:1202194. [PMID: 37415812 PMCID: PMC10321240 DOI: 10.3389/fmicb.2023.1202194] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2023] [Accepted: 05/26/2023] [Indexed: 07/08/2023] Open
Abstract
Indoor home dust microbial communities, important contributors to human health, are shaped by environmental factors, including farm-related exposures. Advanced metagenomic whole genome shotgun sequencing (WGS) improves detection and characterization of microbiota in the indoor built-environment dust microbiome, compared to conventional 16S rRNA amplicon sequencing (16S). We hypothesized that the improved characterization of indoor dust microbial communities by WGS will enhance detection of exposure-outcome associations. The objective of this study was to identify novel associations of environmental exposures with the dust microbiome from the homes of 781 farmers and farm spouses enrolled in the Agricultural Lung Health Study. We examined various farm-related exposures, including living on a farm, crop versus animal production, and type of animal production, as well as non-farm exposures, including home cleanliness and indoor pets. We assessed the association of the exposures on within-sample alpha diversity and between-sample beta diversity, and the differential abundance of specific microbes by exposure. Results were compared to previous findings using 16S. We found most farm exposures were significantly positively associated with both alpha and beta diversity. Many microbes exhibited differential abundance related to farm exposures, mainly in the phyla Actinobacteria, Bacteroidetes, Firmicutes, and Proteobacteria. The identification of novel differential taxa associated with farming at the genera level, including Rhodococcus, Bifidobacterium, Corynebacterium, and Pseudomonas, was a benefit of WGS compared to 16S. Our findings indicate that characterization of dust microbiota, an important component of the indoor environment relevant to human health, is heavily influenced by sequencing techniques. WGS is a powerful tool to survey the microbial community that provides novel insights on the impact of environmental exposures on indoor dust microbiota. These findings can inform the design of future studies in environmental health.
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Affiliation(s)
- Ziyue Wang
- Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Durham, NC, United States
| | - Kathryn R. Dalton
- Genomics and the Environment in Respiratory and Allergic Health Group, Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Durham, NC, United States
| | - Mikyeong Lee
- Genomics and the Environment in Respiratory and Allergic Health Group, Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Durham, NC, United States
| | - Christine G. Parks
- Genomics and the Environment in Respiratory and Allergic Health Group, Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Durham, NC, United States
| | - Laura E. Beane Freeman
- Occupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, United States
| | - Qiyun Zhu
- School of Life Sciences, Biodesign Center for Fundamental and Applied Microbiomics, Arizona State University, Tempe, AZ, United States
| | - Antonio González
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, United States
| | - Rob Knight
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, United States
- Center for Microbiome Innovation, University of California, San Diego, La Jolla, CA, United States
- Department of Bioengineering, University of California, San Diego, La Jolla, CA, United States
- Department of Computer Science and Engineering, University of California, San Diego, La Jolla, CA, United States
| | - Shanshan Zhao
- Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Durham, NC, United States
| | - Alison A. Motsinger-Reif
- Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Durham, NC, United States
| | - Stephanie J. London
- Genomics and the Environment in Respiratory and Allergic Health Group, Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Durham, NC, United States
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10
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Wang Z, Peters BA, Bryant M, Hanna DB, Schwartz T, Wang T, Sollecito CC, Usyk M, Grassi E, Wiek F, Peter LS, Post WS, Landay AL, Hodis HN, Weber KM, French A, Golub ET, Lazar J, Gustafson D, Sharma A, Anastos K, Clish CB, Burk RD, Kaplan RC, Knight R, Qi Q. Gut microbiota, circulating inflammatory markers and metabolites, and carotid artery atherosclerosis in HIV infection. MICROBIOME 2023; 11:119. [PMID: 37237391 PMCID: PMC10224225 DOI: 10.1186/s40168-023-01566-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Accepted: 05/05/2023] [Indexed: 05/28/2023]
Abstract
BACKGROUND Alterations in gut microbiota have been implicated in HIV infection and cardiovascular disease. However, how gut microbial alterations relate to host inflammation and metabolite profiles, and their relationships with atherosclerosis, have not been well-studied, especially in the context of HIV infection. Here, we examined associations of gut microbial species and functional components measured by shotgun metagenomics with carotid artery plaque assessed by B-mode carotid artery ultrasound in 320 women with or at high risk of HIV (65% HIV +) from the Women's Interagency HIV Study. We further integrated plaque-associated microbial features with serum proteomics (74 inflammatory markers measured by the proximity extension assay) and plasma metabolomics (378 metabolites measured by liquid chromatography tandem mass spectrometry) in relation to carotid artery plaque in up to 433 women. RESULTS Fusobacterium nucleatum, a potentially pathogenic bacteria, was positively associated with carotid artery plaque, while five microbial species (Roseburia hominis, Roseburia inulinivorans, Johnsonella ignava, Odoribacter splanchnicus, Clostridium saccharolyticum) were inversely associated with plaque. Results were consistent between women with and without HIV. Fusobacterium nucleatum was positively associated with several serum proteomic inflammatory markers (e.g., CXCL9), and the other plaque-related species were inversely associated with proteomic inflammatory markers (e.g., CX3CL1). These microbial-associated proteomic inflammatory markers were also positively associated with plaque. Associations between bacterial species (especially Fusobacterium nucleatum) and plaque were attenuated after further adjustment for proteomic inflammatory markers. Plaque-associated species were correlated with several plasma metabolites, including the microbial metabolite imidazole-propionate (ImP), which was positively associated with plaque and several pro-inflammatory markers. Further analysis identified additional bacterial species and bacterial hutH gene (encoding enzyme histidine ammonia-lyase in ImP production) associated with plasma ImP levels. A gut microbiota score based on these ImP-associated species was positively associated with plaque and several pro-inflammatory markers. CONCLUSION Among women living with or at risk of HIV, we identified several gut bacterial species and a microbial metabolite ImP associated with carotid artery atherosclerosis, which might be related to host immune activation and inflammation. Video Abstract.
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Affiliation(s)
- Zheng Wang
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Brandilyn A Peters
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
| | - MacKenzie Bryant
- Department of Pediatrics, University of California, La Jolla, San Diego, CA, USA
| | - David B Hanna
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Tara Schwartz
- Department of Pediatrics, University of California, La Jolla, San Diego, CA, USA
| | - Tao Wang
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
| | | | - Mykhaylo Usyk
- Department of Pediatrics, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Evan Grassi
- Department of Pediatrics, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Fanua Wiek
- Department of Pediatrics, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Lauren St Peter
- Department of Pediatrics, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Wendy S Post
- Department of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Alan L Landay
- Department of Internal Medicine, Rush University Medical Center, Chicago, IL, USA
| | - Howard N Hodis
- Atherosclerosis Research Unit, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | | | - Audrey French
- Department of Internal Medicine, Stroger Hospital of Cook County, Chicago, IL, USA
| | - Elizabeth T Golub
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Jason Lazar
- Department of Medicine, State University of New York Downstate Health Sciences University, Brooklyn, NY, USA
| | - Deborah Gustafson
- Department of Neurology, State University of New York Downstate Health Sciences University, Brooklyn, NY, USA
| | - Anjali Sharma
- Department of Medicine, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Kathryn Anastos
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
- Department of Medicine, Albert Einstein College of Medicine, Bronx, NY, USA
- Department of Obstetrics & Gynecology and Women's Health, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Clary B Clish
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Robert D Burk
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
- Department of Pediatrics, Albert Einstein College of Medicine, Bronx, NY, USA
- Department of Obstetrics & Gynecology and Women's Health, Albert Einstein College of Medicine, Bronx, NY, USA
- Department of Microbiology & Immunology, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Robert C Kaplan
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Rob Knight
- Department of Pediatrics, University of California, La Jolla, San Diego, CA, USA
- Department of Bioengineering, University of California, La Jolla, San Diego, CA, USA
- Department of Computer Science and Engineering, University of California, La Jolla, San Diego, CA, USA
- Center for Microbiome Innovation, University of California, La Jolla, San Diego, CA, USA
| | - Qibin Qi
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA.
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
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11
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Taylor BC, Sheikh Andalibi M, Wandro S, Weldon KC, Sepich-Poore GD, Carpenter CS, Fraraccio S, Franklin D, Iudicello JE, Letendre S, Gianella S, Grant I, Ellis RJ, Heaton RK, Knight R, Swafford AD. Signatures of HIV and Major Depressive Disorder in the Plasma Microbiome. Microorganisms 2023; 11:1022. [PMID: 37110445 PMCID: PMC10146336 DOI: 10.3390/microorganisms11041022] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2023] [Revised: 04/08/2023] [Accepted: 04/10/2023] [Indexed: 04/29/2023] Open
Abstract
Inter-individual differences in the gut microbiome are linked to alterations in inflammation and blood-brain barrier permeability, which may increase the risk of depression in people with HIV (PWH). The microbiome profile of blood, which is considered by many to be typically sterile, remains largely unexplored. We aimed to characterize the blood plasma microbiome composition and assess its association with major depressive disorder (MDD) in PWH and people without HIV (PWoH). In this cross-sectional, observational cohort, we used shallow-shotgun metagenomic sequencing to characterize the plasma microbiome of 151 participants (84 PWH and 67 PWoH), all of whom underwent a comprehensive neuropsychiatric assessment. The microbial composition did not differ between PWH and PWoH or between participants with MDD and those without it. Using the songbird model, we computed the log ratio of the highest and lowest 30% of the ranked classes associated with HIV and MDD. We found that HIV infection and lifetime MDD were enriched in a set of differentially abundant inflammatory classes, such as Flavobacteria and Nitrospira. Our results suggest that the circulating plasma microbiome may increase the risk of MDD related to dysbiosis-induced inflammation in PWH. If confirmed, these findings may indicate new biological mechanisms that could be targeted to improve treatment of MDD in PWH.
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Affiliation(s)
- Bryn C. Taylor
- Biomedical Sciences Graduate Program, University of California San Diego, San Diego, CA 92093, USA
| | - Mohammadsobhan Sheikh Andalibi
- Departments of Neurosciences and Psychiatry, HIV Neurobehavioral Research Center, University of California, San Diego, CA 92093, USA; (M.S.A.)
| | - Stephen Wandro
- Center for Microbiome Innovation, University of California San Diego, San Diego, CA 92093, USA
| | - Kelly C. Weldon
- Center for Microbiome Innovation, University of California San Diego, San Diego, CA 92093, USA
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, San Diego, CA 92093, USA
| | | | - Carolina S. Carpenter
- Center for Microbiome Innovation, University of California San Diego, San Diego, CA 92093, USA
| | - Serena Fraraccio
- Center for Microbiome Innovation, University of California San Diego, San Diego, CA 92093, USA
| | - Donald Franklin
- Department of Psychiatry, School of Medicine, University of California, San Diego, CA 92093, USA
| | - Jennifer E. Iudicello
- Department of Psychiatry, School of Medicine, University of California, San Diego, CA 92093, USA
| | - Scott Letendre
- Departments of Medicine and Psychiatry, University of California San Diego, San Diego, CA 92093, USA
| | - Sara Gianella
- Division of Infectious Diseases and Global Public Health, University of California San Diego, San Diego, CA 92093, USA
| | - Igor Grant
- Department of Psychiatry, School of Medicine, University of California, San Diego, CA 92093, USA
| | - Ronald J. Ellis
- Departments of Neurosciences and Psychiatry, HIV Neurobehavioral Research Center, University of California, San Diego, CA 92093, USA; (M.S.A.)
| | - Robert K. Heaton
- Department of Psychiatry, School of Medicine, University of California, San Diego, CA 92093, USA
| | - Rob Knight
- Center for Microbiome Innovation, University of California San Diego, San Diego, CA 92093, USA
- Department of Bioengineering, University of California San Diego, San Diego, CA 92093, USA
- Department of Pediatrics, School of Medicine, University of California San Diego, San Diego, CA 92093, USA
- Department of Computer Science and Engineering, University of California San Diego, San Diego, CA 92093, USA
| | - Austin D. Swafford
- Center for Microbiome Innovation, University of California San Diego, San Diego, CA 92093, USA
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12
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Thompson LR, Thielen P. Decoding dissolved information: environmental DNA sequencing at global scale to monitor a changing ocean. Curr Opin Biotechnol 2023; 81:102936. [PMID: 37060640 DOI: 10.1016/j.copbio.2023.102936] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2023] [Revised: 03/03/2023] [Accepted: 03/13/2023] [Indexed: 04/17/2023]
Abstract
The use of environmental DNA (eDNA) technology for environmental monitoring is rapidly expanding, with applications for fisheries, coral reefs, harmful algal blooms, invasive and endangered species, and biodiversity monitoring. By enabling detection of species over space and time, eDNA fulfills a fundamental need of environmental surveys. Traditional surveys are expensive, require significant capital expenditure, and can be destructive; eDNA offers promise for cheaper, less invasive, and higher-resolution (i.e. genetic) assessments of environments and stocks. However, challenges in quantification, detection limits, biobanking capacity, reference databases, and data management and integration remain significant hurdles to efficient eDNA monitoring at global and decadal scale. Here, we consider the current state of eDNA technology and its suitability for the problems for which it is being used. We explore the current best practices, the logistical and social challenges that prevent eDNA from widespread adoption and benefit, and the emerging technologies that may address those challenges.
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Affiliation(s)
- Luke R Thompson
- Northern Gulf Institute, Mississippi State University, 2 Research Blvd, Starkville, MS 39759, USA; Ocean Chemistry and Ecosystems Division, Atlantic Oceanographic and Meteorological Laboratory, National Oceanic and Atmospheric Administration, 4301 Rickenbacker Cswy, Miami, FL 33149, USA.
| | - Peter Thielen
- Johns Hopkins University Applied Physics Laboratory, 11100 Johns Hopkins Road, Laurel, MD 20723-6099, USA
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13
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Wang Z, Dalton KR, Lee M, Parks CG, Beane Freeman LE, Zhu Q, Gonz Lez A, Knight R, Zhao S, Motsinger-Reif AA, London SJ. Metagenomics reveals novel microbial signatures of farm exposures in house dust. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.04.07.23288301. [PMID: 37090637 PMCID: PMC10120797 DOI: 10.1101/2023.04.07.23288301] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/25/2023]
Abstract
Indoor home dust microbial communities, important contributors to human health outcomes, are shaped by environmental factors, including farm-related exposures. Detection and characterization of microbiota are influenced by sequencing methodology; however, it is unknown if advanced metagenomic whole genome shotgun sequencing (WGS) can detect novel associations between environmental exposures and the indoor built-environment dust microbiome, compared to conventional 16S rRNA amplicon sequencing (16S). This study aimed to better depict indoor dust microbial communities using WGS to investigate novel associations with environmental risk factors from the homes of 781 farmers and farm spouses enrolled in the Agricultural Lung Health Study. We examined various farm-related exposures, including living on a farm, crop versus animal production, and type of animal production, as well as non-farm exposures, including home cleanliness and indoor pets. We assessed the association of the exposures on within-sample alpha diversity and between-sample beta diversity, and the differential abundance of specific microbes by exposure. Results were compared to previous findings using 16S. We found most farm exposures were significantly positively associated with both alpha and beta diversity. Many microbes exhibited differential abundance related to farm exposures, mainly in the phyla Actinobacteria, Bacteroidetes, Firmicutes , and Proteobacteria . The identification of novel differential taxa associated with farming at the genera level, including Rhodococcus, Bifidobacterium, Corynebacterium , and Pseudomonas , was a benefit of WGS compared to 16S. Our findings indicate that characterization of dust microbiota, an important component of the indoor environment relevant to human health, is heavily influenced by sequencing techniques. WGS is a powerful tool to survey the microbial community that provides novel insights on the impact of environmental exposures on indoor dust microbiota, and should be an important consideration in designing future studies in environmental health.
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14
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Liu Y, Teo SM, Méric G, Tang HHF, Zhu Q, Sanders JG, Vázquez-Baeza Y, Verspoor K, Vartiainen VA, Jousilahti P, Lahti L, Niiranen T, Havulinna AS, Knight R, Salomaa V, Inouye M. The gut microbiome is a significant risk factor for future chronic lung disease. J Allergy Clin Immunol 2022; 151:943-952. [PMID: 36587850 PMCID: PMC10109092 DOI: 10.1016/j.jaci.2022.12.810] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Revised: 11/21/2022] [Accepted: 12/05/2022] [Indexed: 12/30/2022]
Abstract
BACKGROUND The gut-lung axis is generally recognized, but there are few large studies of the gut microbiome and incident respiratory disease in adults. OBJECTIVE We sought to investigate the association and predictive capacity of the gut microbiome for incident asthma and chronic obstructive pulmonary disease (COPD). METHODS Shallow metagenomic sequencing was performed for stool samples from a prospective, population-based cohort (FINRISK02; N = 7115 adults) with linked national administrative health register-derived classifications for incident asthma and COPD up to 15 years after baseline. Generalized linear models and Cox regressions were used to assess associations of microbial taxa and diversity with disease occurrence. Predictive models were constructed using machine learning with extreme gradient boosting. Models considered taxa abundances individually and in combination with other risk factors, including sex, age, body mass index, and smoking status. RESULTS A total of 695 and 392 statistically significant associations were found between baseline taxonomic groups and incident asthma and COPD, respectively. Gradient boosting decision trees of baseline gut microbiome abundance predicted incident asthma and COPD in the validation data sets with mean area under the curves of 0.608 and 0.780, respectively. Cox analysis showed that the baseline gut microbiome achieved higher predictive performance than individual conventional risk factors, with C-indices of 0.623 for asthma and 0.817 for COPD. The integration of the gut microbiome and conventional risk factors further improved prediction capacities. CONCLUSIONS The gut microbiome is a significant risk factor for incident asthma and incident COPD and is largely independent of conventional risk factors.
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Affiliation(s)
- Yang Liu
- Department of Clinical Pathology, Melbourne Medical School, The University of Melbourne, Melbourne, Australia; Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Australia.
| | - Shu Mei Teo
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Australia; Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom; Centre for Youth Mental Health, University of Melbourne, Melbourne, Australia
| | - Guillaume Méric
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Australia
| | - Howard H F Tang
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Australia; Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Qiyun Zhu
- School of Life Sciences, Arizona State University, Tempe, Ariz; Biodesign Center for Fundamental and Applied Microbiomics, Arizona State University, Tempe, Ariz
| | - Jon G Sanders
- Department of Ecology and Evolutionary Biology, Cornell University, Ithaca, NY
| | - Yoshiki Vázquez-Baeza
- Center for Microbiome Innovation, Jacobs School of Engineering, University of California San Diego, La Jolla, Calif
| | - Karin Verspoor
- School of Computing Technologies, RMIT University, Melbourne, Australia; School of Computing and Information Systems, The University of Melbourne, Melbourne, Australia
| | - Ville A Vartiainen
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland; Individualized Drug Therapy Research Program, Faculty of Medicine, University of Helsinki, Helsinki, Finland; Department of Pulmonary Medicine, Heart and Lung Center, Helsinki University Hospital, Helsinki, Finland
| | - Pekka Jousilahti
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Leo Lahti
- Department of Computing, University of Turku, Turku, Finland
| | - Teemu Niiranen
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland; Division of Medicine, Turku University Hospital and University of Turku, Turku, Finland
| | - Aki S Havulinna
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland; Institute for Molecular Medicine Finland, FIMM-HiLIFE, University of Helsinki, Helsinki, Finland
| | - Rob Knight
- Center for Microbiome Innovation, Jacobs School of Engineering, University of California San Diego, La Jolla, Calif; Department of Computer Science and Engineering, University of California San Diego, La Jolla, Calif; Department of Pediatrics, School of Medicine, University of California San Diego, La Jolla, Calif
| | - Veikko Salomaa
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Michael Inouye
- Department of Clinical Pathology, Melbourne Medical School, The University of Melbourne, Melbourne, Australia; Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Australia; Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom; British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom; British Heart Foundation Cambridge Centre of Research Excellence, School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom; Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, United Kingdom; The Alan Turing Institute, London, United Kingdom; Heart and Lung Research Institute, University of Cambridge, Cambridge, United Kingdom.
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15
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Sanders JG, Yan W, Mjungu D, Lonsdorf EV, Hart JA, Sanz CM, Morgan DB, Peeters M, Hahn BH, Moeller AH. A low-cost genomics workflow enables isolate screening and strain-level analyses within microbiomes. Genome Biol 2022; 23:212. [PMID: 36224660 PMCID: PMC9558970 DOI: 10.1186/s13059-022-02777-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Accepted: 09/30/2022] [Indexed: 11/10/2022] Open
Abstract
Earth's environments harbor complex consortia of microbes that affect processes ranging from host health to biogeochemical cycles. Understanding their evolution and function is limited by an inability to isolate genomes in a high-throughput manner. Here, we present a workflow for bacterial whole-genome sequencing using open-source labware and the OpenTrons robotics platform, reducing costs to approximately $10 per genome. We assess genomic diversity within 45 gut bacterial species from wild-living chimpanzees and bonobos. We quantify intraspecific genomic diversity and reveal divergence of homologous plasmids between hosts. This enables population genetic analyses of bacterial strains not currently possible with metagenomic data alone.
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Affiliation(s)
- Jon G Sanders
- Department of Ecology and Evolutionary Biology, Cornell University, Ithaca, NY, USA.
| | - Weiwei Yan
- Department of Ecology and Evolutionary Biology, Cornell University, Ithaca, NY, USA
| | - Deus Mjungu
- Gombe Stream Research Center, Kigoma, Tanzania
| | - Elizabeth V Lonsdorf
- Department of Psychology and Biological Foundations of Behavior Program, Franklin and Marshall College, Lancaster, PA, USA.,Department of Anthropology, Emory University, Atlanta, GA, 30322, USA
| | - John A Hart
- Lukuru Wildlife Research Foundation, Tshuapa-Lomami-Lualaba Project, BP 2012, Kinshasa, Democratic Republic of the Congo
| | - Crickette M Sanz
- Department of Anthropology, Washington University in St. Louis, 1 Brookings Drive, Saint Louis, MO, USA.,Wildlife Conservation Society, Congo Program, Brazzaville, B.P. 14537, Republic of Congo
| | - David B Morgan
- Lester E. Fisher Center for the Study and Conservation of Apes, Lincoln Park Zoo, Chicago, IL, USA
| | - Martine Peeters
- Recherche Translationnelle Appliquée Au VIH Et Aux Maladies Infectieuses, Institut de Recherche Pour Le Développement, University of Montpellier, INSERM, 34090, Montpellier, France
| | - Beatrice H Hahn
- Departments of Medicine and Microbiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Andrew H Moeller
- Department of Ecology and Evolutionary Biology, Cornell University, Ithaca, NY, USA.
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16
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Ruuskanen MO, Vats D, Potbhare R, RaviKumar A, Munukka E, Ashma R, Lahti L. Towards standardized and reproducible research in skin microbiomes. Environ Microbiol 2022; 24:3840-3860. [PMID: 35229437 PMCID: PMC9790573 DOI: 10.1111/1462-2920.15945] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Revised: 02/15/2022] [Accepted: 02/16/2022] [Indexed: 12/30/2022]
Abstract
Skin is a complex organ serving a critical role as a barrier and mediator of interactions between the human body and its environment. Recent studies have uncovered how resident microbial communities play a significant role in maintaining the normal healthy function of the skin and the immune system. In turn, numerous host-associated and environmental factors influence these communities' composition and diversity across the cutaneous surface. In addition, specific compositional changes in skin microbiota have also been connected to the development of several chronic diseases. The current era of microbiome research is characterized by its reliance on large data sets of nucleotide sequences produced with high-throughput sequencing of sample-extracted DNA. These approaches have yielded new insights into many previously uncharacterized microbial communities. Application of standardized practices in the study of skin microbial communities could help us understand their complex structures, functional capacities, and health associations and increase the reproducibility of the research. Here, we overview the current research in human skin microbiomes and outline challenges specific to their study. Furthermore, we provide perspectives on recent advances in methods, analytical tools and applications of skin microbiomes in medicine and forensics.
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Affiliation(s)
- Matti O. Ruuskanen
- Department of Computing, Faculty of TechnologyUniversity of TurkuTurkuFinland
| | - Deepti Vats
- Department of Zoology, Centre of Advanced StudySavitribai Phule Pune UniversityPuneIndia
| | - Renuka Potbhare
- Department of Zoology, Centre of Advanced StudySavitribai Phule Pune UniversityPuneIndia
| | - Ameeta RaviKumar
- Institute of Bioinformatics and BiotechnologySavitribai Phule Pune UniversityPuneIndia
| | - Eveliina Munukka
- Microbiome Biobank, Institute of BiomedicineUniversity of TurkuTurkuFinland
| | - Richa Ashma
- Department of Zoology, Centre of Advanced StudySavitribai Phule Pune UniversityPuneIndia
| | - Leo Lahti
- Department of Computing, Faculty of TechnologyUniversity of TurkuTurkuFinland
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17
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Camerlenghi F, Favaro S, Masoero L, Broderick T. Scaled process priors for Bayesian nonparametric estimation of the unseen genetic variation. J Am Stat Assoc 2022. [DOI: 10.1080/01621459.2022.2115918] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/15/2022]
Affiliation(s)
- Federico Camerlenghi
- Department of Economics, Management and Statistics, University of Milano - Bicocca, Milan, Italy
| | - Stefano Favaro
- Department of Economics and Statistics, University of Torino and Collegio Carlo Alberto, Torino, Italy
| | - Lorenzo Masoero
- Department of Electrical Engineering and Computer Science, CSAIL, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Tamara Broderick
- Department of Electrical Engineering and Computer Science, CSAIL, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
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18
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Shaffer JP, Carpenter CS, Martino C, Salido RA, Minich JJ, Bryant M, Sanders K, Schwartz T, Humphrey G, Swafford AD, Knight R. A comparison of six DNA extraction protocols for 16S, ITS and shotgun metagenomic sequencing of microbial communities. Biotechniques 2022; 73:34-46. [PMID: 35713407 PMCID: PMC9361692 DOI: 10.2144/btn-2022-0032] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
Abstract
Microbial communities contain a broad phylogenetic diversity of organisms; however, the majority of methods center on describing bacteria and archaea. Fungi are important symbionts in many ecosystems and are potentially important members of the human microbiome, beyond those that can cause disease. To expand our analysis of microbial communities to include data from the fungal internal transcribed spacer (ITS) region, five candidate DNA extraction kits were compared against our standardized protocol for describing bacteria and archaea using 16S rRNA gene amplicon- and shotgun metagenomics sequencing. The results are presented considering a diverse panel of host-associated and environmental sample types and comparing the cost, processing time, well-to-well contamination, DNA yield, limit of detection and microbial community composition among protocols. Across all criteria, the MagMAX Microbiome kit was found to perform best. The PowerSoil Pro kit performed comparably but with increased cost per sample and overall processing time. The Zymo MagBead, NucleoMag Food and Norgen Stool kits were included.
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Affiliation(s)
- Justin P Shaffer
- Department of Pediatrics, University of California, San Diego, La Jolla, CA 92093, USA
| | - Carolina S Carpenter
- Scripps Institution of Oceanography, University of California, San Diego, La Jolla, CA 92093, USA
- Center for Microbiome Innovation, University of California, San Diego, La Jolla, CA 92093, USA
| | - Cameron Martino
- Department of Pediatrics, University of California, San Diego, La Jolla, CA 92093, USA
- Center for Microbiome Innovation, University of California, San Diego, La Jolla, CA 92093, USA
- Bioinformatics & Systems Biology Program, University of California San Diego, La Jolla, CA 92093, USA
| | - Rodolfo A Salido
- Department of Pediatrics, University of California, San Diego, La Jolla, CA 92093, USA
- Department of Bioengineering, University of California San Diego, La Jolla, CA 92093, USA
| | - Jeremiah J Minich
- Marine Biology Research Division, University of California, San Diego, La Jolla, CA 92093, USA
| | - MacKenzie Bryant
- Department of Pediatrics, University of California, San Diego, La Jolla, CA 92093, USA
| | - Karenina Sanders
- Department of Pediatrics, University of California, San Diego, La Jolla, CA 92093, USA
| | - Tara Schwartz
- Department of Pediatrics, University of California, San Diego, La Jolla, CA 92093, USA
| | - Gregory Humphrey
- Department of Pediatrics, University of California, San Diego, La Jolla, CA 92093, USA
| | - Austin D Swafford
- Center for Microbiome Innovation, University of California, San Diego, La Jolla, CA 92093, USA
- InterOme, Inc. Carlsbad, CA 92008, USA
| | - Rob Knight
- Department of Pediatrics, University of California, San Diego, La Jolla, CA 92093, USA
- Center for Microbiome Innovation, University of California, San Diego, La Jolla, CA 92093, USA
- Micronoma Inc. San Diego, CA 92121, USA
- Department of Computer Science & Engineering, University of California, San Diego, La Jolla, CA 92093, USA
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19
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Zhu Q, Huang S, Gonzalez A, McGrath I, McDonald D, Haiminen N, Armstrong G, Vázquez-Baeza Y, Yu J, Kuczynski J, Sepich-Poore GD, Swafford AD, Das P, Shaffer JP, Lejzerowicz F, Belda-Ferre P, Havulinna AS, Méric G, Niiranen T, Lahti L, Salomaa V, Kim HC, Jain M, Inouye M, Gilbert JA, Knight R. Phylogeny-Aware Analysis of Metagenome Community Ecology Based on Matched Reference Genomes while Bypassing Taxonomy. mSystems 2022; 7:e0016722. [PMID: 35369727 PMCID: PMC9040630 DOI: 10.1128/msystems.00167-22] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2022] [Accepted: 02/25/2022] [Indexed: 02/06/2023] Open
Abstract
We introduce the operational genomic unit (OGU) method, a metagenome analysis strategy that directly exploits sequence alignment hits to individual reference genomes as the minimum unit for assessing the diversity of microbial communities and their relevance to environmental factors. This approach is independent of taxonomic classification, granting the possibility of maximal resolution of community composition, and organizes features into an accurate hierarchy using a phylogenomic tree. The outputs are suitable for contemporary analytical protocols for community ecology, differential abundance, and supervised learning while supporting phylogenetic methods, such as UniFrac and phylofactorization, that are seldom applied to shotgun metagenomics despite being prevalent in 16S rRNA gene amplicon studies. As demonstrated in two real-world case studies, the OGU method produces biologically meaningful patterns from microbiome data sets. Such patterns further remain detectable at very low metagenomic sequencing depths. Compared with taxonomic unit-based analyses implemented in currently adopted metagenomics tools, and the analysis of 16S rRNA gene amplicon sequence variants, this method shows superiority in informing biologically relevant insights, including stronger correlation with body environment and host sex on the Human Microbiome Project data set and more accurate prediction of human age by the gut microbiomes of Finnish individuals included in the FINRISK 2002 cohort. We provide Woltka, a bioinformatics tool to implement this method, with full integration with the QIIME 2 package and the Qiita web platform, to facilitate adoption of the OGU method in future metagenomics studies. IMPORTANCE Shotgun metagenomics is a powerful, yet computationally challenging, technique compared to 16S rRNA gene amplicon sequencing for decoding the composition and structure of microbial communities. Current analyses of metagenomic data are primarily based on taxonomic classification, which is limited in feature resolution. To solve these challenges, we introduce operational genomic units (OGUs), which are the individual reference genomes derived from sequence alignment results, without further assigning them taxonomy. The OGU method advances current read-based metagenomics in two dimensions: (i) providing maximal resolution of community composition and (ii) permitting use of phylogeny-aware tools. Our analysis of real-world data sets shows that it is advantageous over currently adopted metagenomic analysis methods and the finest-grained 16S rRNA analysis methods in predicting biological traits. We thus propose the adoption of OGUs as an effective practice in metagenomic studies.
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Affiliation(s)
- Qiyun Zhu
- School of Life Sciences, Arizona State University, Tempe, Arizona, USA
- Center for Fundamental and Applied Microbiomics, Arizona State University, Tempe, Arizona, USA
- Department of Pediatrics, School of Medicine, University of California San Diego, La Jolla, California, USA
| | - Shi Huang
- Department of Pediatrics, School of Medicine, University of California San Diego, La Jolla, California, USA
- Center for Microbiome Innovation, Jacobs School of Engineering, University of California San Diego, La Jolla, California, USA
- Faculty of Dentistry, The University of Hong Kong, Hong Kong SAR, China
| | - Antonio Gonzalez
- Department of Pediatrics, School of Medicine, University of California San Diego, La Jolla, California, USA
| | - Imran McGrath
- Center for Microbiome Innovation, Jacobs School of Engineering, University of California San Diego, La Jolla, California, USA
- Division of Biological Sciences, University of California San Diego, La Jolla, California, USA
| | - Daniel McDonald
- Department of Pediatrics, School of Medicine, University of California San Diego, La Jolla, California, USA
| | - Niina Haiminen
- IBM T. J. Watson Research Center, Yorktown Heights, New York, USA
| | - George Armstrong
- Department of Pediatrics, School of Medicine, University of California San Diego, La Jolla, California, USA
- Center for Microbiome Innovation, Jacobs School of Engineering, University of California San Diego, La Jolla, California, USA
- Bioinformatics and Systems Biology Program, University of California San Diego, La Jolla, California, USA
| | - Yoshiki Vázquez-Baeza
- Center for Microbiome Innovation, Jacobs School of Engineering, University of California San Diego, La Jolla, California, USA
| | - Julian Yu
- School of Life Sciences, Arizona State University, Tempe, Arizona, USA
- Center for Fundamental and Applied Microbiomics, Arizona State University, Tempe, Arizona, USA
| | | | | | - Austin D. Swafford
- Center for Microbiome Innovation, Jacobs School of Engineering, University of California San Diego, La Jolla, California, USA
| | - Promi Das
- Department of Pediatrics, School of Medicine, University of California San Diego, La Jolla, California, USA
- Scripps Institution of Oceanography, University of California San Diego, La Jolla, California, USA
| | - Justin P. Shaffer
- Department of Pediatrics, School of Medicine, University of California San Diego, La Jolla, California, USA
| | - Franck Lejzerowicz
- Department of Pediatrics, School of Medicine, University of California San Diego, La Jolla, California, USA
- Center for Microbiome Innovation, Jacobs School of Engineering, University of California San Diego, La Jolla, California, USA
| | - Pedro Belda-Ferre
- Department of Pediatrics, School of Medicine, University of California San Diego, La Jolla, California, USA
- Center for Microbiome Innovation, Jacobs School of Engineering, University of California San Diego, La Jolla, California, USA
| | - Aki S. Havulinna
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland
- Institute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Helsinki, Finland
| | - Guillaume Méric
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
- Department of Infectious Diseases, Central Clinical School, Monash University, Melbourne, Victoria, Australia
| | - Teemu Niiranen
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland
- Department of Internal Medicine, University of Turku, Turku, Finland
- Division of Medicine, Turku University Hospital, Finland
| | - Leo Lahti
- Department of Computing, University of Turku, Turku, Finland
| | - Veikko Salomaa
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Ho-Cheol Kim
- IBM Almaden Research Center, San Jose, California, USA
| | - Mohit Jain
- Department of Medicine, University of California San Diego, La Jolla, California, USA
- Department of Pharmacology, University of California San Diego, La Jolla, California, USA
| | - Michael Inouye
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
- Department of Public Health and Primary Care, Cambridge University, Cambridge, United Kingdom
| | - Jack A. Gilbert
- Department of Pediatrics, School of Medicine, University of California San Diego, La Jolla, California, USA
- Center for Microbiome Innovation, Jacobs School of Engineering, University of California San Diego, La Jolla, California, USA
- Scripps Institution of Oceanography, University of California San Diego, La Jolla, California, USA
| | - Rob Knight
- Department of Pediatrics, School of Medicine, University of California San Diego, La Jolla, California, USA
- Department of Bioengineering, University of California San Diego, La Jolla, California, USA
- Department of Computer Science and Engineering, University of California San Diego, La Jolla, California, USA
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20
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The impact of maternal asthma on the preterm infants' gut metabolome and microbiome (MAP study). Sci Rep 2022; 12:6437. [PMID: 35440708 PMCID: PMC9018729 DOI: 10.1038/s41598-022-10276-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2021] [Accepted: 03/30/2022] [Indexed: 11/20/2022] Open
Abstract
Preterm infants are at a greater risk for the development of asthma and atopic disease, which can lead to lifelong negative health consequences. This may be due, in part, to alterations that occur in the gut microbiome and metabolome during their stay in the Neonatal Intensive Care Unit (NICU). To explore the differential roles of family history (i.e., predisposition due to maternal asthma diagnosis) and hospital-related environmental and clinical factors that alter microbial exposures early in life, we considered a unique cohort of preterm infants born ≤ 34 weeks gestational age from two local level III NICUs, as part of the MAP (Microbiome, Atopic disease, and Prematurity) Study. From MAP participants, we chose a sub-cohort of infants whose mothers had a history of asthma and matched gestational age and sex to infants of mothers without a history of asthma diagnosis (control). We performed a prospective, paired metagenomic and metabolomic analysis of stool and milk feed samples collected at birth, 2 weeks, and 6 weeks postnatal age. Although there were clinical factors associated with shifts in the diversity and composition of stool-associated bacterial communities, maternal asthma diagnosis did not play an observable role in shaping the infant gut microbiome during the study period. There were significant differences, however, in the metabolite profile between the maternal asthma and control groups at 6 weeks postnatal age. The most notable changes occurred in the linoleic acid spectral network, which plays a role in inflammatory and immune pathways, suggesting early metabolomic changes in the gut of preterm infants born to mothers with a history of asthma. Our pilot study suggests that a history of maternal asthma alters a preterm infants’ metabolomic pathways in the gut, as early as the first 6 weeks of life.
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21
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Ruuskanen MO, Erawijantari PP, Havulinna AS, Liu Y, Méric G, Tuomilehto J, Inouye M, Jousilahti P, Salomaa V, Jain M, Knight R, Lahti L, Niiranen TJ. Gut Microbiome Composition Is Predictive of Incident Type 2 Diabetes in a Population Cohort of 5,572 Finnish Adults. Diabetes Care 2022; 45:811-818. [PMID: 35100347 PMCID: PMC9016732 DOI: 10.2337/dc21-2358] [Citation(s) in RCA: 37] [Impact Index Per Article: 18.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/12/2021] [Accepted: 01/05/2022] [Indexed: 02/03/2023]
Abstract
OBJECTIVE To examine the previously unknown long-term association between gut microbiome composition and incident type 2 diabetes in a representative population cohort. RESEARCH DESIGN AND METHODS We collected fecal samples from 5,572 Finns (mean age 48.7 years; 54.1% women) in 2002 who were followed up for incident type 2 diabetes until 31 December 2017. The samples were sequenced using shotgun metagenomics. We examined associations between gut microbiome composition and incident diabetes using multivariable-adjusted Cox regression models. We first used the eastern Finland subpopulation to obtain initial findings and validated these in the western Finland subpopulation. RESULTS Altogether, 432 cases of incident diabetes occurred over the median follow-up of 15.8 years. We detected four species and two clusters consistently associated with incident diabetes in the validation models. These four species were Clostridium citroniae (hazard ratio [HR] 1.21; 95% CI 1.04-1.42), C. bolteae (HR 1.20; 95% CI 1.04-1.39), Tyzzerella nexilis (HR 1.17; 95% CI 1.01-1.36), and Ruminococcus gnavus (HR 1.17; 95% CI 1.01-1.36). The positively associated clusters, cluster 1 (HR 1.18; 95% CI 1.02-1.38) and cluster 5 (HR 1.18; 95% CI 1.02-1.36), mostly consisted of these same species. CONCLUSIONS We observed robust species-level taxonomic features predictive of incident type 2 diabetes over long-term follow-up. These findings build on and extend previous mainly cross-sectional evidence and further support links between dietary habits, metabolic diseases, and type 2 diabetes that are modulated by the gut microbiome. The gut microbiome can potentially be used to improve disease prediction and uncover novel therapeutic targets for diabetes.
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Affiliation(s)
- Matti O. Ruuskanen
- Department of Computing, University of Turku, Turku, Finland
- Corresponding author: Matti O. Ruuskanen,
| | | | - Aki S. Havulinna
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Science, Helsinki, Finland
| | - Yang Liu
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
- Department of Clinical Pathology, Melbourne Medical School, University of Melbourne, Melbourne, Victoria, Australia
| | - Guillaume Méric
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
- Department of Infectious Diseases, Central Clinical School, Monash University, Melbourne, Victoria, Australia
| | - Jaakko Tuomilehto
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland
- Department of Public Health, University of Helsinki, Helsinki, Finland
- Saudi Diabetes Research Group, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Michael Inouye
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
- Department of Public Health and Primary Care, Cambridge University, Cambridge, U.K
| | - Pekka Jousilahti
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Veikko Salomaa
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Mohit Jain
- Department of Medicine, University of California San Diego, La Jolla, CA
- Department of Pharmacology, University of California San Diego, La Jolla, CA
| | - Rob Knight
- Jacobs School of Engineering, University of California San Diego, La Jolla, CA
- Center for Microbiome Innovation, University of California San Diego, La Jolla, CA
- Department of Pediatrics, School of Medicine, University of California San Diego, La Jolla, CA
- Department of Computer Science & Engineering, University of California San Diego, La Jolla, CA
| | - Leo Lahti
- Department of Computing, University of Turku, Turku, Finland
| | - Teemu J. Niiranen
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland
- Division of Medicine, Turku University Hospital, Turku, Finland
- Department of Internal Medicine, University of Turku, Turku, Finland
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22
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Adler A, Poirier S, Pagni M, Maillard J, Holliger C. Disentangle genus microdiversity within a complex microbial community by using a multi-distance long-read binning method: example of Candidatus Accumulibacter. Environ Microbiol 2022; 24:2136-2156. [PMID: 35315560 PMCID: PMC9311429 DOI: 10.1111/1462-2920.15947] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2021] [Accepted: 02/19/2022] [Indexed: 11/26/2022]
Abstract
Complete genomes can be recovered from metagenomes by assembling and binning DNA sequences into metagenome assembled genomes (MAGs). Yet, the presence of microdiversity can hamper the assembly and binning processes, possibly yielding chimeric, highly fragmented and incomplete genomes. Here, the metagenomes of four samples of aerobic granular sludge bioreactors containing Candidatus (Ca.) Accumulibacter, a phosphate-accumulating organism of interest for wastewater treatment, were sequenced with both PacBio and Illumina. Different strategies of genome assembly and binning were investigated, including published protocols and a binning procedure adapted to the binning of long contigs (MuLoBiSC). Multiple criteria were considered to select the best strategy for Ca. Accumulibacter, whose multiple strains in every sample represent a challenging microdiversity. In this case, the best strategy relies on long-read only assembly and a custom binning procedure including MuLoBiSC in metaWRAP. Several high-quality Ca. Accumulibacter MAGs, including a novel species, were obtained independently from different samples. Comparative genomic analysis showed that MAGs retrieved in different samples harbour genomic rearrangements in addition to accumulation of point mutations. The microdiversity of Ca. Accumulibacter, likely driven by mobile genetic elements, causes major difficulties in recovering MAGs, but it is also a hallmark of the panmictic lifestyle of these bacteria.
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Affiliation(s)
- Aline Adler
- Laboratory for Environmental Biotechnology, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Simon Poirier
- Laboratory for Environmental Biotechnology, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Marco Pagni
- Laboratory for Environmental Biotechnology, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.,Vital-IT Group, SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Julien Maillard
- Laboratory for Environmental Biotechnology, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.,IFP Energie nouvelles, 1 et 4 avenue de Bois-Préau, 92852, Rueil-Malmaison Cedex, France
| | - Christof Holliger
- Laboratory for Environmental Biotechnology, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
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23
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Bacher R, Chu LF, Argus C, Bolin JM, Knight P, Thomson J, Stewart R, Kendziorski C. Enhancing biological signals and detection rates in single-cell RNA-seq experiments with cDNA library equalization. Nucleic Acids Res 2022; 50:e12. [PMID: 34850101 PMCID: PMC8789062 DOI: 10.1093/nar/gkab1071] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2020] [Revised: 10/14/2021] [Accepted: 10/20/2021] [Indexed: 11/14/2022] Open
Abstract
Considerable effort has been devoted to refining experimental protocols to reduce levels of technical variability and artifacts in single-cell RNA-sequencing data (scRNA-seq). We here present evidence that equalizing the concentration of cDNA libraries prior to pooling, a step not consistently performed in single-cell experiments, improves gene detection rates, enhances biological signals, and reduces technical artifacts in scRNA-seq data. To evaluate the effect of equalization on various protocols, we developed Scaffold, a simulation framework that models each step of an scRNA-seq experiment. Numerical experiments demonstrate that equalization reduces variation in sequencing depth and gene-specific expression variability. We then performed a set of experiments in vitro with and without the equalization step and found that equalization increases the number of genes that are detected in every cell by 17-31%, improves discovery of biologically relevant genes, and reduces nuisance signals associated with cell cycle. Further support is provided in an analysis of publicly available data.
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Affiliation(s)
- Rhonda Bacher
- Department of Biostatistics, University of Florida, FL, USA
| | - Li-Fang Chu
- Department of Comparative Biology and Experimental Medicine, University of Calgary, Calgary, AB, Canada
- Morgridge Institute for Research, Madison, WI, USA
| | - Cara Argus
- Morgridge Institute for Research, Madison, WI, USA
| | | | - Parker Knight
- Department of Mathematics, University of Florida, FL, USA
| | | | - Ron Stewart
- Morgridge Institute for Research, Madison, WI, USA
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24
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Standardized multi-omics of Earth's microbiomes reveals microbial and metabolite diversity. Nat Microbiol 2022; 7:2128-2150. [PMID: 36443458 PMCID: PMC9712116 DOI: 10.1038/s41564-022-01266-x] [Citation(s) in RCA: 29] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2021] [Accepted: 10/10/2022] [Indexed: 11/30/2022]
Abstract
Despite advances in sequencing, lack of standardization makes comparisons across studies challenging and hampers insights into the structure and function of microbial communities across multiple habitats on a planetary scale. Here we present a multi-omics analysis of a diverse set of 880 microbial community samples collected for the Earth Microbiome Project. We include amplicon (16S, 18S, ITS) and shotgun metagenomic sequence data, and untargeted metabolomics data (liquid chromatography-tandem mass spectrometry and gas chromatography mass spectrometry). We used standardized protocols and analytical methods to characterize microbial communities, focusing on relationships and co-occurrences of microbially related metabolites and microbial taxa across environments, thus allowing us to explore diversity at extraordinary scale. In addition to a reference database for metagenomic and metabolomic data, we provide a framework for incorporating additional studies, enabling the expansion of existing knowledge in the form of an evolving community resource. We demonstrate the utility of this database by testing the hypothesis that every microbe and metabolite is everywhere but the environment selects. Our results show that metabolite diversity exhibits turnover and nestedness related to both microbial communities and the environment, whereas the relative abundances of microbially related metabolites vary and co-occur with specific microbial consortia in a habitat-specific manner. We additionally show the power of certain chemistry, in particular terpenoids, in distinguishing Earth's environments (for example, terrestrial plant surfaces and soils, freshwater and marine animal stool), as well as that of certain microbes including Conexibacter woesei (terrestrial soils), Haloquadratum walsbyi (marine deposits) and Pantoea dispersa (terrestrial plant detritus). This Resource provides insight into the taxa and metabolites within microbial communities from diverse habitats across Earth, informing both microbial and chemical ecology, and provides a foundation and methods for multi-omics microbiome studies of hosts and the environment.
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25
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Gaio D, DeMaere MZ, Anantanawat K, Chapman TA, Djordjevic SP, Darling AE. Post-weaning shifts in microbiome composition and metabolism revealed by over 25 000 pig gut metagenome-assembled genomes. Microb Genom 2021; 7. [PMID: 34370660 PMCID: PMC8549361 DOI: 10.1099/mgen.0.000501] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
Using a previously described metagenomics dataset of 27 billion reads, we reconstructed over 50 000 metagenome-assembled genomes (MAGs) of organisms resident in the porcine gut, 46.5 % of which were classified as >70 % complete with a <10 % contamination rate, and 24.4 % were nearly complete genomes. Here, we describe the generation and analysis of those MAGs using time-series samples. The gut microbial communities of piglets appear to follow a highly structured developmental programme in the weeks following weaning, and this development is robust to treatments including an intramuscular antibiotic treatment and two probiotic treatments. The high resolution we obtained allowed us to identify specific taxonomic ‘signatures’ that characterize the gut microbial development immediately after weaning. Additionally, we characterized the carbohydrate repertoire of the organisms resident in the porcine gut. We tracked the abundance shifts of 294 carbohydrate active enzymes, and identified the species and higher-level taxonomic groups carrying each of these enzymes in their MAGs. This knowledge can contribute to the design of probiotics and prebiotic interventions as a means to modify the piglet gut microbiome.
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Affiliation(s)
- Daniela Gaio
- iThree Institute, University of Technology Sydney, Sydney, New South Wales, Australia
| | - Matthew Z DeMaere
- iThree Institute, University of Technology Sydney, Sydney, New South Wales, Australia
| | - Kay Anantanawat
- iThree Institute, University of Technology Sydney, Sydney, New South Wales, Australia
| | - Toni A Chapman
- NSW Department of Primary Industries, Elizabeth Macarthur Agricultural Institute, Menangle, New South Wales, Australia
| | - Steven P Djordjevic
- iThree Institute, University of Technology Sydney, Sydney, New South Wales, Australia
| | - Aaron E Darling
- iThree Institute, University of Technology Sydney, Sydney, New South Wales, Australia
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26
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d'Humières C, Salmona M, Dellière S, Leo S, Rodriguez C, Angebault C, Alanio A, Fourati S, Lazarevic V, Woerther PL, Schrenzel J, Ruppé E. The Potential Role of Clinical Metagenomics in Infectious Diseases: Therapeutic Perspectives. Drugs 2021; 81:1453-1466. [PMID: 34328626 PMCID: PMC8323086 DOI: 10.1007/s40265-021-01572-4] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/07/2021] [Indexed: 12/24/2022]
Abstract
Clinical metagenomics (CMg) is the process of sequencing nucleic acid of clinical samples to obtain clinically relevant information such as the identification of microorganisms and their susceptibility to antimicrobials. Over the last decades, sequencing and bioinformatic solutions supporting CMg have much evolved and an increasing number of case reports and series covering various infectious diseases have been published. Metagenomics is a new approach to infectious disease diagnosis that is currently being developed and is certainly one of the most promising for the coming years. However, most CMg studies are retrospective, and few address the potential impact CMg could have on patient management, including initiation, adaptation, or cessation of antimicrobials. In this narrative review, we have discussed the potential role of CMg in bacteriology, virology, mycology, and parasitology. Several reports and case-series confirm that CMg is an innovative tool with which one can (i) identify more microorganisms than with conventional methods in a single test, (ii) obtain results within hours, and (iii) tailor the antimicrobial regimen of patients. However, the cost-efficiency of CMg and its real impact on patient management are still to be determined.
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Affiliation(s)
- Camille d'Humières
- Université de Paris, IAME, INSERM, 75018, Paris, France.,AP-HP, Hôpital Bichat, Laboratoire de Bactériologie, Hôpital Bichat-Claude Bernard, 46 rue Henri Huchard, 75018, Paris, France
| | - Maud Salmona
- Unité de Paris, INSERM U976, Insight Team, 75010, Paris, France.,AP-HP, Hôpital Saint-Louis, Laboratoire de Virologie, 75010, Paris, France
| | - Sarah Dellière
- AP-HP, Hôpital Saint-Louis, Laboratoire de Parasitologie-Mycologie, 75010, Paris, France.,Molecular Mycology Unit, Institut Pasteur, CNRS UMR2000, 75015, Paris, France
| | - Stefano Leo
- Faculty of Medicine, CMU, University of Geneva, Geneva, Switzerland.,Service of Infectious Diseases, Genomic Research Laboratory, Geneva University Hospitals, Geneva, Switzerland
| | - Christophe Rodriguez
- Département de Microbiologie, AP-HP, Hôpital Henri Mondor, 94000, Créteil, France.,INSERM U955, Université Paris-Est, 94000, Créteil, France
| | - Cécile Angebault
- Département de Microbiologie, AP-HP, Hôpital Henri Mondor, 94000, Créteil, France.,Université Paris Est Créteil, Ecole Nationale Vétérinaire d'Alfort, USC ANSES, EA7380 Dynamic, 94000, Créteil, France
| | - Alexandre Alanio
- AP-HP, Hôpital Saint-Louis, Laboratoire de Parasitologie-Mycologie, 75010, Paris, France.,Molecular Mycology Unit, Institut Pasteur, CNRS UMR2000, 75015, Paris, France
| | - Slim Fourati
- Département de Microbiologie, AP-HP, Hôpital Henri Mondor, 94000, Créteil, France.,INSERM U955, Université Paris-Est, 94000, Créteil, France
| | - Vladimir Lazarevic
- Faculty of Medicine, CMU, University of Geneva, Geneva, Switzerland.,Service of Infectious Diseases, Genomic Research Laboratory, Geneva University Hospitals, Geneva, Switzerland
| | - Paul-Louis Woerther
- Département de Microbiologie, AP-HP, Hôpital Henri Mondor, 94000, Créteil, France.,Université Paris Est Créteil, Ecole Nationale Vétérinaire d'Alfort, USC ANSES, EA7380 Dynamic, 94000, Créteil, France
| | - Jacques Schrenzel
- Faculty of Medicine, CMU, University of Geneva, Geneva, Switzerland.,Service of Infectious Diseases, Genomic Research Laboratory, Geneva University Hospitals, Geneva, Switzerland
| | - Etienne Ruppé
- Université de Paris, IAME, INSERM, 75018, Paris, France. .,AP-HP, Hôpital Bichat, Laboratoire de Bactériologie, Hôpital Bichat-Claude Bernard, 46 rue Henri Huchard, 75018, Paris, France.
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27
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Salosensaari A, Laitinen V, Havulinna AS, Meric G, Cheng S, Perola M, Valsta L, Alfthan G, Inouye M, Watrous JD, Long T, Salido RA, Sanders K, Brennan C, Humphrey GC, Sanders JG, Jain M, Jousilahti P, Salomaa V, Knight R, Lahti L, Niiranen T. Taxonomic signatures of cause-specific mortality risk in human gut microbiome. Nat Commun 2021; 12:2671. [PMID: 33976176 PMCID: PMC8113604 DOI: 10.1038/s41467-021-22962-y] [Citation(s) in RCA: 48] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2020] [Accepted: 04/06/2021] [Indexed: 12/26/2022] Open
Abstract
The collection of fecal material and developments in sequencing technologies have enabled standardised and non-invasive gut microbiome profiling. Microbiome composition from several large cohorts have been cross-sectionally linked to various lifestyle factors and diseases. In spite of these advances, prospective associations between microbiome composition and health have remained uncharacterised due to the lack of sufficiently large and representative population cohorts with comprehensive follow-up data. Here, we analyse the long-term association between gut microbiome variation and mortality in a well-phenotyped and representative population cohort from Finland (n = 7211). We report robust taxonomic and functional microbiome signatures related to the Enterobacteriaceae family that are associated with mortality risk during a 15-year follow-up. Our results extend previous cross-sectional studies, and help to establish the basis for examining long-term associations between human gut microbiome composition, incident outcomes, and general health status.
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Affiliation(s)
- Aaro Salosensaari
- Division of Medicine, Turku University Hospital and University of Turku, Turku, Finland
- Department of Computing, University of Turku, Turku, Finland
- Department of Mathematics and Statistics, University of Turku, Turku, Finland
| | - Ville Laitinen
- Department of Computing, University of Turku, Turku, Finland
| | - Aki S Havulinna
- Finnish Institute for Health and Welfare, Helsinki, Finland
- Institute for Molecular Medicine Finland, FIMM-HiLIFE, Helsinki, Finland
| | - Guillaume Meric
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, VIC, Australia
- Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Susan Cheng
- Division of Cardiology, Brigham and Women's Hospital, Boston, MA, USA
- Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Markus Perola
- Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Liisa Valsta
- Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Georg Alfthan
- Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Michael Inouye
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, VIC, Australia
- Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Jeramie D Watrous
- Departments of Medicine and Pharmacology, University of California San Diego, San Diego, CA, USA
| | - Tao Long
- Departments of Medicine and Pharmacology, University of California San Diego, San Diego, CA, USA
| | - Rodolfo A Salido
- Department of Pediatrics, University of California San Diego, San Diego, CA, USA
| | - Karenina Sanders
- Department of Pediatrics, University of California San Diego, San Diego, CA, USA
| | - Caitriona Brennan
- Department of Pediatrics, University of California San Diego, San Diego, CA, USA
| | - Gregory C Humphrey
- Department of Pediatrics, University of California San Diego, San Diego, CA, USA
| | - Jon G Sanders
- Department of Pediatrics, University of California San Diego, San Diego, CA, USA
| | - Mohit Jain
- Departments of Medicine and Pharmacology, University of California San Diego, San Diego, CA, USA
| | | | - Veikko Salomaa
- Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Rob Knight
- Department of Pediatrics, University of California San Diego, San Diego, CA, USA
| | - Leo Lahti
- Department of Computing, University of Turku, Turku, Finland.
| | - Teemu Niiranen
- Division of Medicine, Turku University Hospital and University of Turku, Turku, Finland.
- Finnish Institute for Health and Welfare, Helsinki, Finland.
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28
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Du J, Zayed AA, Kigerl KA, Zane K, Sullivan MB, Popovich PG. Spinal Cord Injury Changes the Structure and Functional Potential of Gut Bacterial and Viral Communities. mSystems 2021; 6:e01356-20. [PMID: 33975974 PMCID: PMC8125080 DOI: 10.1128/msystems.01356-20] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2020] [Accepted: 03/25/2021] [Indexed: 01/11/2023] Open
Abstract
Emerging data indicate that gut dysbiosis contributes to many human diseases, including several comorbidities that develop after traumatic spinal cord injury (SCI). To date, all analyses of SCI-induced gut dysbiosis have used 16S rRNA amplicon sequencing. This technique has several limitations, including being susceptible to taxonomic "blind spots," primer bias, and an inability to profile microbiota functions or identify viruses. Here, SCI-induced gut dysbiosis was assessed by applying genome- and gene-resolved metagenomic analysis of murine stool samples collected 21 days after an experimental SCI at the 4th thoracic spine (T4) or 10th thoracic spine (T10) spinal level. These distinct injuries partially (T10) or completely (T4) abolish sympathetic tone in the gut. Among bacteria, 105 medium- to high-quality metagenome-assembled genomes (MAGs) were recovered, with most (n = 96) representing new bacterial species. Read mapping revealed that after SCI, the relative abundance of beneficial commensals (Lactobacillus johnsonii and CAG-1031 spp.) decreased, while potentially pathogenic bacteria (Weissella cibaria, Lactococcus lactis _A, Bacteroides thetaiotaomicron) increased. Functionally, microbial genes encoding proteins for tryptophan, vitamin B6, and folate biosynthesis, essential pathways for central nervous system function, were reduced after SCI. Among viruses, 1,028 mostly novel viral populations were recovered, expanding known murine gut viral species sequence space ∼3-fold compared to that of public databases. Phages of beneficial commensal hosts (CAG-1031, Lactobacillus, and Turicibacter) decreased, while phages of pathogenic hosts (Weissella, Lactococcus, and class Clostridia) increased after SCI. Although the microbiomes and viromes were changed in all SCI mice, some of these changes varied as a function of spinal injury level, implicating loss of sympathetic tone as a mechanism underlying gut dysbiosis.IMPORTANCE To our knowledge, this is the first article to apply metagenomics to characterize changes in gut microbial population dynamics caused by a clinically relevant model of central nervous system (CNS) trauma. It also utilizes the most current approaches in genome-resolved metagenomics and viromics to maximize the biological inferences that can be made from these data. Overall, this article highlights the importance of autonomic nervous system regulation of a distal organ (gut) and its microbiome inhabitants after traumatic spinal cord injury (SCI). By providing information on taxonomy, function, and viruses, metagenomic data may better predict how SCI-induced gut dysbiosis influences systemic and neurological outcomes after SCI.
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Affiliation(s)
- Jingjie Du
- Department of Microbiology, The Ohio State University, Columbus, Ohio, USA
| | - Ahmed A Zayed
- Department of Microbiology, The Ohio State University, Columbus, Ohio, USA
- Center of Microbiome Science, The Ohio State University, Columbus, Ohio, USA
| | - Kristina A Kigerl
- Department of Neuroscience, The Ohio State University College of Medicine, Columbus, Ohio, USA
- The Belford Center for Spinal Cord Injury, The Ohio State University College of Medicine, Columbus, Ohio, USA
- The Center for Brain and Spinal Cord Repair, The Ohio State University College of Medicine, Columbus, Ohio, USA
- Center of Microbiome Science, The Ohio State University, Columbus, Ohio, USA
| | - Kylie Zane
- Medical Scientist Training Program, The Ohio State University College of Medicine, Columbus, Ohio, USA
| | - Matthew B Sullivan
- Department of Microbiology, The Ohio State University, Columbus, Ohio, USA
- Department of Civil, Environmental and Geodetic Engineering, The Ohio State University, Columbus, Ohio, USA
- Infectious Disease Institute, The Ohio State University, Columbus, Ohio, USA
- Center of Microbiome Science, The Ohio State University, Columbus, Ohio, USA
| | - Phillip G Popovich
- Department of Neuroscience, The Ohio State University College of Medicine, Columbus, Ohio, USA
- The Belford Center for Spinal Cord Injury, The Ohio State University College of Medicine, Columbus, Ohio, USA
- The Center for Brain and Spinal Cord Repair, The Ohio State University College of Medicine, Columbus, Ohio, USA
- Center of Microbiome Science, The Ohio State University, Columbus, Ohio, USA
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29
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Abstract
Expanding our knowledge of microbial communities across diverse environments includes collecting samples in places far from the laboratory. Identifying cost-effective preservatives that will enable room temperature storage of microbial communities for sequencing analysis is crucial to enabling microbiome analyses across diverse populations. As the number of human microbiome studies expand, it is increasingly important to identify cost-effective, practical preservatives that allow for room temperature sample storage. Here, we reanalyzed 16S rRNA gene amplicon sequencing data from a large sample storage study published in 2016 and performed shotgun metagenomic sequencing on remnant DNA from this experiment. Both results support the initial findings that 95% ethanol, a nontoxic, cost-effective preservative, is effective at preserving samples at room temperature for weeks. We expanded on this analysis by collecting a new set of fecal, saliva, and skin samples to determine the optimal ratio of 95% ethanol to sample. We identified optimal collection protocols for fecal samples (storing a fecal swab in 95% ethanol) and saliva samples (storing unstimulated saliva in 95% ethanol at a ratio of 1:2). Storing skin swabs in 95% ethanol reduced microbial biomass and disrupted community composition, highlighting the difficulties of low biomass sample preservation. The results from this study identify practical solutions for large-scale analyses of fecal and oral microbial communities. IMPORTANCE Expanding our knowledge of microbial communities across diverse environments includes collecting samples in places far from the laboratory. Identifying cost-effective preservatives that will enable room temperature storage of microbial communities for sequencing analysis is crucial to enabling microbiome analyses across diverse populations. Here, we validate findings that 95% ethanol efficiently preserves microbial composition at room temperature for weeks. We also identified the optimal ratio of 95% ethanol to sample for stool and saliva to preserve both microbial load and composition. These results provide rationale for an accessible, nontoxic, cost-effective solution that will enable crowdsourcing microbiome studies, such as The Microsetta Initiative, and lower the barrier for collecting diverse samples.
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30
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Arumugam K, Bessarab I, Haryono MAS, Liu X, Zuniga-Montanez RE, Roy S, Qiu G, Drautz-Moses DI, Law YY, Wuertz S, Lauro FM, Huson DH, Williams RBH. Recovery of complete genomes and non-chromosomal replicons from activated sludge enrichment microbial communities with long read metagenome sequencing. NPJ Biofilms Microbiomes 2021; 7:23. [PMID: 33727564 PMCID: PMC7966762 DOI: 10.1038/s41522-021-00196-6] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2020] [Accepted: 02/12/2021] [Indexed: 01/31/2023] Open
Abstract
New long read sequencing technologies offer huge potential for effective recovery of complete, closed genomes from complex microbial communities. Using long read data (ONT MinION) obtained from an ensemble of activated sludge enrichment bioreactors we recover 22 closed or complete genomes of community members, including several species known to play key functional roles in wastewater bioprocesses, specifically microbes known to exhibit the polyphosphate- and glycogen-accumulating organism phenotypes (namely Candidatus Accumulibacter and Dechloromonas, and Micropruina, Defluviicoccus and Candidatus Contendobacter, respectively), and filamentous bacteria (Thiothrix) associated with the formation and stability of activated sludge flocs. Additionally we demonstrate the recovery of close to 100 circularised plasmids, phages and small microbial genomes from these microbial communities using long read assembled sequence. We describe methods for validating long read assembled genomes using their counterpart short read metagenome-assembled genomes, and assess the influence of different correction procedures on genome quality and predicted gene quality. Our findings establish the feasibility of performing long read metagenome-assembled genome recovery for both chromosomal and non-chromosomal replicons, and demonstrate the value of parallel sampling of moderately complex enrichment communities to obtaining high quality reference genomes of key functional species relevant for wastewater bioprocesses.
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Affiliation(s)
- Krithika Arumugam
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore, Singapore
| | - Irina Bessarab
- Singapore Centre for Environmental Life Sciences Engineering, National University of Singapore, Singapore, Singapore
| | - Mindia A S Haryono
- Singapore Centre for Environmental Life Sciences Engineering, National University of Singapore, Singapore, Singapore
| | - Xianghui Liu
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore, Singapore
| | - Rogelio E Zuniga-Montanez
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore, Singapore
- Department of Civil and Environmental Engineering, One Shields Avenue, University of California, Davis, CA, USA
| | - Samarpita Roy
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore, Singapore
| | - Guanglei Qiu
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore, Singapore
- School of Environment and Energy, South China University of Technology, Guangzhou, China
| | - Daniela I Drautz-Moses
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore, Singapore
| | - Ying Yu Law
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore, Singapore
| | - Stefan Wuertz
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore, Singapore
- School of Civil and Environmental Engineering, Nanyang Technological University, Singapore, Singapore
| | - Federico M Lauro
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore, Singapore
- Asian School of the Environment, Nanyang Technological University, Singapore, Singapore
| | - Daniel H Huson
- Institute for Bioinformatics and Medical Informatics, University of Tübingen, Tübingen, Germany
- Life Sciences Institute, National University of Singapore, Singapore, Singapore
| | - Rohan B H Williams
- Singapore Centre for Environmental Life Sciences Engineering, National University of Singapore, Singapore, Singapore.
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31
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Shaffer JP, Marotz C, Belda-Ferre P, Martino C, Wandro S, Estaki M, Salido RA, Carpenter CS, Zaramela LS, Minich JJ, Bryant M, Sanders K, Fraraccio S, Ackermann G, Humphrey G, Swafford AD, Miller-Montgomery S, Knight R. A comparison of DNA/RNA extraction protocols for high-throughput sequencing of microbial communities. Biotechniques 2021; 70:149-159. [PMID: 33512248 PMCID: PMC7931620 DOI: 10.2144/btn-2020-0153] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2020] [Accepted: 01/04/2021] [Indexed: 11/23/2022] Open
Abstract
One goal of microbial ecology researchers is to capture the maximum amount of information from all organisms in a sample. The recent COVID-19 pandemic, caused by the RNA virus SARS-CoV-2, has highlighted a gap in traditional DNA-based protocols, including the high-throughput methods the authors previously established as field standards. To enable simultaneous SARS-CoV-2 and microbial community profiling, the authors compared the relative performance of two total nucleic acid extraction protocols with the authors' previously benchmarked protocol. The authors included a diverse panel of environmental and host-associated sample types, including body sites commonly swabbed for COVID-19 testing. Here the authors present results comparing the cost, processing time, DNA and RNA yield, microbial community composition, limit of detection and well-to-well contamination between these protocols.
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Affiliation(s)
- Justin P Shaffer
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA
| | - Clarisse Marotz
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA
| | - Pedro Belda-Ferre
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA
| | - Cameron Martino
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA
- Center for Microbiome Innovation, University of California, San Diego, La Jolla, CA, USA
- Bioinformatics & Systems Biology Program, University of California San Diego, La Jolla, CA, USA
| | - Stephen Wandro
- Center for Microbiome Innovation, University of California, San Diego, La Jolla, CA, USA
- Micronoma Inc., San Diego, CA, USA
| | - Mehrbod Estaki
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA
| | - Rodolfo A Salido
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA
| | - Carolina S Carpenter
- Center for Microbiome Innovation, University of California, San Diego, La Jolla, CA, USA
| | - Livia S Zaramela
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA
| | - Jeremiah J Minich
- Marine Biology Research Division, University of California, San Diego, La Jolla, CA, USA
| | - MacKenzie Bryant
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA
| | - Karenina Sanders
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA
| | - Serena Fraraccio
- Center for Microbiome Innovation, University of California, San Diego, La Jolla, CA, USA
- Micronoma Inc., San Diego, CA, USA
| | - Gail Ackermann
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA
| | - Gregory Humphrey
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA
| | - Austin D Swafford
- Center for Microbiome Innovation, University of California, San Diego, La Jolla, CA, USA
| | - Sandrine Miller-Montgomery
- Center for Microbiome Innovation, University of California, San Diego, La Jolla, CA, USA
- Micronoma Inc., San Diego, CA, USA
| | - Rob Knight
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA
- Center for Microbiome Innovation, University of California, San Diego, La Jolla, CA, USA
- Department of Computer Science & Engineering, University of California, San Diego, La Jolla, CA, USA
- Micronoma Inc., San Diego, CA, USA
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32
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Masoero L, Camerlenghi F, Favaro S, Broderick T. More for less: predicting and maximizing genomic variant discovery via Bayesian nonparametrics. Biometrika 2021. [DOI: 10.1093/biomet/asab012] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022] Open
Abstract
Summary
While the cost of sequencing genomes has decreased dramatically in recent years, this expense often remains nontrivial. Under a fixed budget, scientists face a natural trade-off between quantity and quality: spending resources to sequence a greater number of genomes or spending resources to sequence genomes with increased accuracy. Our goal is to find the optimal allocation of resources between quantity and quality. Optimizing resource allocation promises to reveal as many new variations in the genome as possible. We introduce a Bayesian nonparametric methodology to predict the number of new variants in a follow-up study based on a pilot study. When experimental conditions are kept constant between the pilot and follow-up, we find that our prediction is competitive with the best existing methods. Unlike current methods, though, our new method allows practitioners to change experimental conditions between the pilot and the follow-up. We demonstrate how this distinction allows our method to be used for more realistic predictions and for optimal allocation of a fixed budget between quality and quantity. We validate our method on cancer and human genomics data.
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33
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Ruuskanen MO, Åberg F, Männistö V, Havulinna AS, Méric G, Liu Y, Loomba R, Vázquez-Baeza Y, Tripathi A, Valsta LM, Inouye M, Jousilahti P, Salomaa V, Jain M, Knight R, Lahti L, Niiranen TJ. Links between gut microbiome composition and fatty liver disease in a large population sample. Gut Microbes 2021; 13:1-22. [PMID: 33651661 PMCID: PMC7928040 DOI: 10.1080/19490976.2021.1888673] [Citation(s) in RCA: 38] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/17/2020] [Revised: 01/14/2021] [Accepted: 01/28/2021] [Indexed: 02/08/2023] Open
Abstract
Fatty liver disease is the most common liver disease in the world. Its connection with the gut microbiome has been known for at least 80 y, but this association remains mostly unstudied in the general population because of underdiagnosis and small sample sizes. To address this knowledge gap, we studied the link between the Fatty Liver Index (FLI), a well-established proxy for fatty liver disease, and gut microbiome composition in a representative, ethnically homogeneous population sample of 6,269 Finnish participants. We based our models on biometric covariates and gut microbiome compositions from shallow metagenome sequencing. Our classification models could discriminate between individuals with a high FLI (≥60, indicates likely liver steatosis) and low FLI (<60) in internal cross-region validation, consisting of 30% of the data not used in model training, with an average AUC of 0.75 and AUPRC of 0.56 (baseline at 0.30). In addition to age and sex, our models included differences in 11 microbial groups from class Clostridia, mostly belonging to orders Lachnospirales and Oscillospirales. Our models were also predictive of the high FLI group in a different Finnish cohort, consisting of 258 participants, with an average AUC of 0.77 and AUPRC of 0.51 (baseline at 0.21). Pathway analysis of representative genomes of the positively FLI-associated taxa in (NCBI) Clostridium subclusters IV and XIVa indicated the presence of, e.g., ethanol fermentation pathways. These results support several findings from smaller case-control studies, such as the role of endogenous ethanol producers in the development of the fatty liver.
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Affiliation(s)
- Matti O. Ruuskanen
- Department of Internal Medicine, University of Turku, Turku, Finland
- Department of Public Health Solutions, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Fredrik Åberg
- Transplantation and Liver Surgery Clinic, Helsinki University Hospital, University of Helsinki, Helsinki, Finland
- Transplant Institute, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Ville Männistö
- Department of Medicine, Kuopio University Hospital, University of Eastern Finland, Kuopio, Finland
- Department of Experimental Vascular Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Aki S. Havulinna
- Department of Public Health Solutions, Finnish Institute for Health and Welfare, Helsinki, Finland
- Institute for Molecular Medicine Finland, FIMM - HiLIFE, Helsinki, Finland
| | - Guillaume Méric
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
- Department of Infectious Diseases, Central Clinical School, Monash University, Melbourne, Victoria, Australia
| | - Yang Liu
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
- Department of Clinical Pathology, The University of Melbourne, Melbourne, Victoria, Australia
| | - Rohit Loomba
- Department of Medicine, NAFLD Research Center, La Jolla, CA, USA
- Department of Medicine, University of California San Diego, La Jolla, CA, USA
| | - Yoshiki Vázquez-Baeza
- Center for Microbiome Innovation, Jacobs School of Engineering, University of California San Diego, La Jolla, CA, USA
| | - Anupriya Tripathi
- Collaborative Mass Spectrometry Innovation Center, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA
- Division of Biological Sciences, University of California San Diego, La Jolla, CA, USA
| | - Liisa M. Valsta
- Department of Public Health Solutions, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Michael Inouye
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
- Department of Public Health and Primary Care, Cambridge University, Cambridge, UK
| | - Pekka Jousilahti
- Department of Public Health Solutions, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Veikko Salomaa
- Department of Public Health Solutions, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Mohit Jain
- Department of Medicine, University of California San Diego, La Jolla, CA, USA
- Department of Pharmacology, University of California San Diego, La Jolla, California, USA
| | - Rob Knight
- Center for Microbiome Innovation, Jacobs School of Engineering, University of California San Diego, La Jolla, CA, USA
- Department of Pediatrics, School of Medicine, University of California San Diego, La Jolla, California, USA
- Department of Computer Science & Engineering, University of California San Diego, La Jolla, California, USA
| | - Leo Lahti
- Deparment of Computing, University of Turku, Turku, Finland
| | - Teemu J. Niiranen
- Department of Internal Medicine, University of Turku, Turku, Finland
- Department of Public Health Solutions, Finnish Institute for Health and Welfare, Helsinki, Finland
- Division of Medicine, Turku University Hospital, Turku, Finland
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34
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Ha CWY, Martin A, Sepich-Poore GD, Shi B, Wang Y, Gouin K, Humphrey G, Sanders K, Ratnayake Y, Chan KSL, Hendrick G, Caldera JR, Arias C, Moskowitz JE, Ho Sui SJ, Yang S, Underhill D, Brady MJ, Knott S, Kaihara K, Steinbaugh MJ, Li H, McGovern DPB, Knight R, Fleshner P, Devkota S. Translocation of Viable Gut Microbiota to Mesenteric Adipose Drives Formation of Creeping Fat in Humans. Cell 2020; 183:666-683.e17. [PMID: 32991841 PMCID: PMC7521382 DOI: 10.1016/j.cell.2020.09.009] [Citation(s) in RCA: 178] [Impact Index Per Article: 44.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2019] [Revised: 07/19/2020] [Accepted: 09/01/2020] [Indexed: 02/08/2023]
Abstract
A mysterious feature of Crohn's disease (CD) is the extra-intestinal manifestation of "creeping fat" (CrF), defined as expansion of mesenteric adipose tissue around the inflamed and fibrotic intestine. In the current study, we explore whether microbial translocation in CD serves as a central cue for CrF development. We discovered a subset of mucosal-associated gut bacteria that consistently translocated and remained viable in CrF in CD ileal surgical resections, and identified Clostridium innocuum as a signature of this consortium with strain variation between mucosal and adipose isolates, suggesting preference for lipid-rich environments. Single-cell RNA sequencing characterized CrF as both pro-fibrotic and pro-adipogenic with a rich milieu of activated immune cells responding to microbial stimuli, which we confirm in gnotobiotic mice colonized with C. innocuum. Ex vivo validation of expression patterns suggests C. innocuum stimulates tissue remodeling via M2 macrophages, leading to an adipose tissue barrier that serves to prevent systemic dissemination of bacteria.
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Affiliation(s)
- Connie W Y Ha
- F. Widjaja Foundation Inflammatory Bowel and Immunobiology Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Anthony Martin
- F. Widjaja Foundation Inflammatory Bowel and Immunobiology Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Gregory D Sepich-Poore
- Department of Bioengineering, University of California San Diego, La Jolla, California 92093, USA
| | - Baochen Shi
- Department of Molecular and Medical Pharmacology, Crump Institute for Molecular Imaging, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90095, USA
| | - Yizhou Wang
- Applied Genomics, Computation and Translational Core, Cedars-Sinai Cancer, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Kenneth Gouin
- Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA; Applied Genomics, Computation and Translational Core, Cedars-Sinai Cancer, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Gregory Humphrey
- Department of Pediatrics, University of California San Diego, La Jolla, CA 92093, USA
| | - Karenina Sanders
- Department of Pediatrics, University of California San Diego, La Jolla, CA 92093, USA
| | | | | | - Gustaf Hendrick
- F. Widjaja Foundation Inflammatory Bowel and Immunobiology Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - J R Caldera
- Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Christian Arias
- F. Widjaja Foundation Inflammatory Bowel and Immunobiology Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Jacob E Moskowitz
- F. Widjaja Foundation Inflammatory Bowel and Immunobiology Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Shannan J Ho Sui
- Harvard Chan Bioinformatics Core, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Shaohong Yang
- F. Widjaja Foundation Inflammatory Bowel and Immunobiology Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - David Underhill
- F. Widjaja Foundation Inflammatory Bowel and Immunobiology Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA; Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Matthew J Brady
- Department of Medicine, Section of Endocrinology and Metabolism, The University of Chicago, Chicago, IL 60637, USA
| | - Simon Knott
- Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA; Applied Genomics, Computation and Translational Core, Cedars-Sinai Cancer, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | | | - Michael J Steinbaugh
- Harvard Chan Bioinformatics Core, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Huiying Li
- Department of Molecular and Medical Pharmacology, Crump Institute for Molecular Imaging, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90095, USA
| | - Dermot P B McGovern
- F. Widjaja Foundation Inflammatory Bowel and Immunobiology Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Rob Knight
- Department of Pediatrics, University of California San Diego, La Jolla, CA 92093, USA; Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA 92093, USA
| | - Phillip Fleshner
- F. Widjaja Foundation Inflammatory Bowel and Immunobiology Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA; Division of Colorectal Surgery, Department of Surgery, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Suzanne Devkota
- F. Widjaja Foundation Inflammatory Bowel and Immunobiology Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA; Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA.
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Martino C, Kellman BP, Sandoval DR, Clausen TM, Marotz CA, Song SJ, Wandro S, Zaramela LS, Salido Benítez RA, Zhu Q, Armingol E, Vázquez-Baeza Y, McDonald D, Sorrentino JT, Taylor B, Belda-Ferre P, Liang C, Zhang Y, Schifanella L, Klatt NR, Havulinna AS, Jousilahti P, Huang S, Haiminen N, Parida L, Kim HC, Swafford AD, Zengler K, Cheng S, Inouye M, Niiranen T, Jain M, Salomaa V, Esko JD, Lewis NE, Knight R. Bacterial modification of the host glycosaminoglycan heparan sulfate modulates SARS-CoV-2 infectivity. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2020. [PMID: 32839779 PMCID: PMC7444296 DOI: 10.1101/2020.08.17.238444] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
The human microbiota has a close relationship with human disease and it remodels components of the glycocalyx including heparan sulfate (HS). Studies of the severe acute respiratory syndrome coronavirus (SARS-CoV-2) spike protein receptor binding domain suggest that infection requires binding to HS and angiotensin converting enzyme 2 (ACE2) in a codependent manner. Here, we show that commensal host bacterial communities can modify HS and thereby modulate SARS-CoV-2 spike protein binding and that these communities change with host age and sex. Common human-associated commensal bacteria whose genomes encode HS-modifying enzymes were identified. The prevalence of these bacteria and the expression of key microbial glycosidases in bronchoalveolar lavage fluid (BALF) was lower in adult COVID-19 patients than in healthy controls. The presence of HS-modifying bacteria decreased with age in two large survey datasets, FINRISK 2002 and American Gut, revealing one possible mechanism for the observed increase in COVID-19 susceptibility with age. In vitro , bacterial glycosidases from unpurified culture media supernatants fully blocked SARS-CoV-2 spike binding to human H1299 protein lung adenocarcinoma cells. HS-modifying bacteria in human microbial communities may regulate viral adhesion, and loss of these commensals could predispose individuals to infection. Understanding the impact of shifts in microbial community composition and bacterial lyases on SARS-CoV-2 infection may lead to new therapeutics and diagnosis of susceptibility.
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36
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Krishnaswamy VG, Aishwarya S, Kathawala TM. Extrication of the Microbial Interactions of Activated Sludge Used in the Textile Effluent Treatment of Anaerobic Reactor Through Metagenomic Profiling. Curr Microbiol 2020; 77:2496-2509. [DOI: 10.1007/s00284-020-02020-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2019] [Accepted: 05/07/2020] [Indexed: 11/29/2022]
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37
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Poore GD, Kopylova E, Zhu Q, Carpenter C, Fraraccio S, Wandro S, Kosciolek T, Janssen S, Metcalf J, Song SJ, Kanbar J, Miller-Montgomery S, Heaton R, Mckay R, Patel SP, Swafford AD, Knight R. Microbiome analyses of blood and tissues suggest cancer diagnostic approach. Nature 2020; 579:567-574. [PMID: 32214244 PMCID: PMC7500457 DOI: 10.1038/s41586-020-2095-1] [Citation(s) in RCA: 581] [Impact Index Per Article: 145.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2019] [Accepted: 02/06/2020] [Indexed: 01/05/2023]
Abstract
Systematic characterization of the cancer microbiome provides the opportunity to develop techniques that exploit non-human, microorganism-derived molecules in the diagnosis of a major human disease. Following recent demonstrations that some types of cancer show substantial microbial contributions1-10, we re-examined whole-genome and whole-transcriptome sequencing studies in The Cancer Genome Atlas11 (TCGA) of 33 types of cancer from treatment-naive patients (a total of 18,116 samples) for microbial reads, and found unique microbial signatures in tissue and blood within and between most major types of cancer. These TCGA blood signatures remained predictive when applied to patients with stage Ia-IIc cancer and cancers lacking any genomic alterations currently measured on two commercial-grade cell-free tumour DNA platforms, despite the use of very stringent decontamination analyses that discarded up to 92.3% of total sequence data. In addition, we could discriminate among samples from healthy, cancer-free individuals (n = 69) and those from patients with multiple types of cancer (prostate, lung, and melanoma; 100 samples in total) solely using plasma-derived, cell-free microbial nucleic acids. This potential microbiome-based oncology diagnostic tool warrants further exploration.
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Affiliation(s)
- Gregory D Poore
- Department of Bioengineering, University of California San Diego, La Jolla, CA, USA
| | - Evguenia Kopylova
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
- Clarity Genomics, Beerse, Belgium
| | - Qiyun Zhu
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Carolina Carpenter
- Center for Microbiome Innovation, University of California San Diego, La Jolla, CA, USA
| | - Serena Fraraccio
- Center for Microbiome Innovation, University of California San Diego, La Jolla, CA, USA
| | - Stephen Wandro
- Center for Microbiome Innovation, University of California San Diego, La Jolla, CA, USA
| | - Tomasz Kosciolek
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
- Malopolska Centre of Biotechnology, Jagiellonian University in Krakow, Krakow, Poland
| | - Stefan Janssen
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
- Algorithmic Bioinformatics, Department of Biology and Chemistry, Justus Liebig University Gießen, Gießen, Germany
| | - Jessica Metcalf
- Department of Animal Sciences, Colorado State University, Fort Collins, CO, USA
| | - Se Jin Song
- Center for Microbiome Innovation, University of California San Diego, La Jolla, CA, USA
| | - Jad Kanbar
- Department of Medicine, University of California San Diego, La Jolla, CA, USA
| | - Sandrine Miller-Montgomery
- Department of Bioengineering, University of California San Diego, La Jolla, CA, USA
- Center for Microbiome Innovation, University of California San Diego, La Jolla, CA, USA
| | - Robert Heaton
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Rana Mckay
- Moores Cancer Center, University of California San Diego Health, La Jolla, CA, USA
| | - Sandip Pravin Patel
- Center for Microbiome Innovation, University of California San Diego, La Jolla, CA, USA
- Moores Cancer Center, University of California San Diego Health, La Jolla, CA, USA
| | - Austin D Swafford
- Center for Microbiome Innovation, University of California San Diego, La Jolla, CA, USA
| | - Rob Knight
- Department of Bioengineering, University of California San Diego, La Jolla, CA, USA.
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA.
- Center for Microbiome Innovation, University of California San Diego, La Jolla, CA, USA.
- Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA, USA.
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