51
|
Contreras AV, Cocom-Chan B, Hernandez-Montes G, Portillo-Bobadilla T, Resendis-Antonio O. Host-Microbiome Interaction and Cancer: Potential Application in Precision Medicine. Front Physiol 2016; 7:606. [PMID: 28018236 PMCID: PMC5145879 DOI: 10.3389/fphys.2016.00606] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2016] [Accepted: 11/21/2016] [Indexed: 12/19/2022] Open
Abstract
It has been experimentally shown that host-microbial interaction plays a major role in shaping the wellness or disease of the human body. Microorganisms coexisting in human tissues provide a variety of benefits that contribute to proper functional activity in the host through the modulation of fundamental processes such as signal transduction, immunity and metabolism. The unbalance of this microbial profile, or dysbiosis, has been correlated with the genesis and evolution of complex diseases such as cancer. Although this latter disease has been thoroughly studied using different high-throughput (HT) technologies, its heterogeneous nature makes its understanding and proper treatment in patients a remaining challenge in clinical settings. Notably, given the outstanding role of host-microbiome interactions, the ecological interactions with microorganisms have become a new significant aspect in the systems that can contribute to the diagnosis and potential treatment of solid cancers. As a part of expanding precision medicine in the area of cancer research, efforts aimed at effective treatments for various kinds of cancer based on the knowledge of genetics, biology of the disease and host-microbiome interactions might improve the prediction of disease risk and implement potential microbiota-directed therapeutics. In this review, we present the state of the art of sequencing and metabolome technologies, computational methods and schemes in systems biology that have addressed recent breakthroughs of uncovering relationships or associations between microorganisms and cancer. Together, microbiome studies extend the horizon of new personalized treatments against cancer from the perspective of precision medicine through a synergistic strategy integrating clinical knowledge, HT data, bioinformatics, and systems biology.
Collapse
Affiliation(s)
| | - Benjamin Cocom-Chan
- Instituto Nacional de Medicina GenómicaMexico City, Mexico; Human Systems Biology Laboratory, Instituto Nacional de Medicina GenómicaMexico City, Mexico
| | - Georgina Hernandez-Montes
- Coordinación de la Investigación Científica, Red de Apoyo a la Investigación-National Autonomous University of Mexico (UNAM) Mexico City, Mexico
| | - Tobias Portillo-Bobadilla
- Coordinación de la Investigación Científica, Red de Apoyo a la Investigación-National Autonomous University of Mexico (UNAM) Mexico City, Mexico
| | - Osbaldo Resendis-Antonio
- Instituto Nacional de Medicina GenómicaMexico City, Mexico; Human Systems Biology Laboratory, Instituto Nacional de Medicina GenómicaMexico City, Mexico; Coordinación de la Investigación Científica, Red de Apoyo a la Investigación-National Autonomous University of Mexico (UNAM)Mexico City, Mexico
| |
Collapse
|
52
|
Snijders AM, Langley SA, Kim YM, Brislawn CJ, Noecker C, Zink EM, Fansler SJ, Casey CP, Miller DR, Huang Y, Karpen GH, Celniker SE, Brown JB, Borenstein E, Jansson JK, Metz TO, Mao JH. Influence of early life exposure, host genetics and diet on the mouse gut microbiome and metabolome. Nat Microbiol 2016; 2:16221. [PMID: 27892936 DOI: 10.1038/nmicrobiol.2016.221] [Citation(s) in RCA: 67] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2016] [Accepted: 10/07/2016] [Indexed: 12/22/2022]
Abstract
Although the gut microbiome plays important roles in host physiology, health and disease1, we lack understanding of the complex interplay between host genetics and early life environment on the microbial and metabolic composition of the gut. We used the genetically diverse Collaborative Cross mouse system2 to discover that early life history impacts the microbiome composition, whereas dietary changes have only a moderate effect. By contrast, the gut metabolome was shaped mostly by diet, with specific non-dietary metabolites explained by microbial metabolism. Quantitative trait analysis identified mouse genetic trait loci (QTL) that impact the abundances of specific microbes. Human orthologues of genes in the mouse QTL are implicated in gastrointestinal cancer. Additionally, genes located in mouse QTL for Lactobacillales abundance are implicated in arthritis, rheumatic disease and diabetes. Furthermore, Lactobacillales abundance was predictive of higher host T-helper cell counts, suggesting an important link between Lactobacillales and host adaptive immunity.
Collapse
Affiliation(s)
- Antoine M Snijders
- Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA
| | - Sasha A Langley
- Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA
| | - Young-Mo Kim
- Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, Washington 99352, USA
| | - Colin J Brislawn
- Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, Washington 99352, USA
| | - Cecilia Noecker
- Department of Genome Sciences, University of Washington, Seattle, Washington 98105, USA
| | - Erika M Zink
- Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, Washington 99352, USA
| | - Sarah J Fansler
- Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, Washington 99352, USA
| | - Cameron P Casey
- Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, Washington 99352, USA
| | - Darla R Miller
- Systems Genetics Core Facility, Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
| | - Yurong Huang
- Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA
| | - Gary H Karpen
- Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA.,Department of Molecular and Cell Biology, University of California, Berkeley, California 94720, USA
| | - Susan E Celniker
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA
| | - James B Brown
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA
| | - Elhanan Borenstein
- Department of Genome Sciences, University of Washington, Seattle, Washington 98105, USA.,Department of Computer Science and Engineering, University of Washington, Seattle, Washington 98195, USA.,Santa Fe Institute, Santa Fe, New Mexico 87501, USA
| | - Janet K Jansson
- Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, Washington 99352, USA
| | - Thomas O Metz
- Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, Washington 99352, USA
| | - Jian-Hua Mao
- Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA
| |
Collapse
|
53
|
Pal C, Bengtsson-Palme J, Kristiansson E, Larsson DGJ. The structure and diversity of human, animal and environmental resistomes. MICROBIOME 2016; 4:54. [PMID: 27717408 PMCID: PMC5055678 DOI: 10.1186/s40168-016-0199-5] [Citation(s) in RCA: 267] [Impact Index Per Article: 33.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/15/2016] [Accepted: 09/28/2016] [Indexed: 05/19/2023]
Abstract
BACKGROUND Antibiotic resistance genes (ARGs) are widespread but cause problems only when present in pathogens. Environments where selection and transmission of antibiotic resistance frequently take place are likely to be characterized by high abundance and diversity of horizontally transferable ARGs. Large-scale quantitative data on ARGs is, however, lacking for most types of environments, including humans and animals, as is data on resistance genes to potential co-selective agents, such as biocides and metals. This paucity prevents efficient identification of risk environments. RESULTS We provide a comprehensive characterization of resistance genes, mobile genetic elements (MGEs) and bacterial taxonomic compositions for 864 metagenomes from humans (n = 350), animals (n = 145) and external environments (n = 369), all deeply sequenced using Illumina technology. Environment types showed clear differences in both resistance profiles and bacterial community compositions. Human and animal microbial communities were characterized by limited taxonomic diversity and low abundance and diversity of biocide/metal resistance genes and MGEs but a relatively high abundance of ARGs. In contrast, external environments showed consistently high taxonomic diversity which in turn was linked to high diversity of both biocide/metal resistance genes and MGEs. Water, sediment and soil generally carried low relative abundance and few varieties of known ARGs, whereas wastewater/sludge was on par with the human gut. The environments with the largest relative abundance and/or diversity of ARGs, including genes encoding resistance to last resort antibiotics, were those subjected to industrial antibiotic pollution and a limited set of deeply sequenced air samples from a Beijing smog event. CONCLUSIONS Our study identifies air and antibiotic-polluted environments as under-investigated transmission routes and reservoirs for antibiotic resistance. The high taxonomic and genetic diversity of external environments supports the hypothesis that these also form vast sources of unknown resistance genes, with potential to be transferred to pathogens in the future.
Collapse
Affiliation(s)
- Chandan Pal
- Department of Infectious Diseases, Institute of Biomedicine, Sahlgrenska Academy, University of Gothenburg, SE-413 46, Gothenburg, Sweden
- Centre for Antibiotic Resistance Research (CARe), University of Gothenburg, Gothenburg, Sweden
| | - Johan Bengtsson-Palme
- Department of Infectious Diseases, Institute of Biomedicine, Sahlgrenska Academy, University of Gothenburg, SE-413 46, Gothenburg, Sweden
- Centre for Antibiotic Resistance Research (CARe), University of Gothenburg, Gothenburg, Sweden
| | - Erik Kristiansson
- Centre for Antibiotic Resistance Research (CARe), University of Gothenburg, Gothenburg, Sweden
- Department of Mathematical Sciences, Chalmers University of Technology, SE-412 96, Gothenburg, Sweden
| | - D G Joakim Larsson
- Department of Infectious Diseases, Institute of Biomedicine, Sahlgrenska Academy, University of Gothenburg, SE-413 46, Gothenburg, Sweden.
- Centre for Antibiotic Resistance Research (CARe), University of Gothenburg, Gothenburg, Sweden.
| |
Collapse
|
54
|
Vincent AT, Derome N, Boyle B, Culley AI, Charette SJ. Next-generation sequencing (NGS) in the microbiological world: How to make the most of your money. J Microbiol Methods 2016; 138:60-71. [PMID: 26995332 DOI: 10.1016/j.mimet.2016.02.016] [Citation(s) in RCA: 71] [Impact Index Per Article: 8.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2015] [Revised: 01/26/2016] [Accepted: 02/24/2016] [Indexed: 12/16/2022]
Abstract
The Sanger sequencing method produces relatively long DNA sequences of unmatched quality and has been considered for long time as the gold standard for sequencing DNA. Many improvements of the Sanger method that culminated with fluorescent dyes coupled with automated capillary electrophoresis enabled the sequencing of the first genomes. Nevertheless, using this technology to sequence whole genomes was costly, laborious and time consuming even for genomes that are relatively small in size. A major technological advance was the introduction of next-generation sequencing (NGS) pioneered by 454 Life Sciences in the early part of the 21th century. NGS allowed scientists to sequence thousands to millions of DNA molecules in a single machine run. Since then, new NGS technologies have emerged and existing NGS platforms have been improved, enabling the production of genome sequences at an unprecedented rate as well as broadening the spectrum of NGS applications. The current affordability of generating genomic information, especially with microbial samples, has resulted in a false sense of simplicity that belies the fact that many researchers still consider these technologies a black box. In this review, our objective is to identify and discuss four steps that we consider crucial to the success of any NGS-related project. These steps are: (1) the definition of the research objectives beyond sequencing and appropriate experimental planning, (2) library preparation, (3) sequencing and (4) data analysis. The goal of this review is to give an overview of the process, from sample to analysis, and discuss how to optimize your resources to achieve the most from your NGS-based research. Regardless of the evolution and improvement of the sequencing technologies, these four steps will remain relevant.
Collapse
Affiliation(s)
- Antony T Vincent
- Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Quebec City, QC G1V 0A6, Canada; Département de biochimie, de microbiologie et de bio-informatique, Faculté des sciences et de génie, Université Laval, Quebec City, QC G1V 0A6, Canada; Centre de recherche de l'Institut universitaire de cardiologie et de pneumologie de Québec, Quebec City, QC G1V 4G5, Canada
| | - Nicolas Derome
- Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Quebec City, QC G1V 0A6, Canada; Département de biologie, Faculté des sciences et de génie, Université Laval, Quebec City G1V 0A6, Canada
| | - Brian Boyle
- Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Quebec City, QC G1V 0A6, Canada
| | - Alexander I Culley
- Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Quebec City, QC G1V 0A6, Canada; Département de biochimie, de microbiologie et de bio-informatique, Faculté des sciences et de génie, Université Laval, Quebec City, QC G1V 0A6, Canada; Groupe de Recherche en Écologie Buccale (GREB), Faculté de médecine dentaire, Université Laval, Quebec City, QC G1V 0A6, Canada
| | - Steve J Charette
- Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Quebec City, QC G1V 0A6, Canada; Département de biochimie, de microbiologie et de bio-informatique, Faculté des sciences et de génie, Université Laval, Quebec City, QC G1V 0A6, Canada; Centre de recherche de l'Institut universitaire de cardiologie et de pneumologie de Québec, Quebec City, QC G1V 4G5, Canada.
| |
Collapse
|
55
|
Metagenomic evidence for taxonomic dysbiosis and functional imbalance in the gastrointestinal tracts of children with cystic fibrosis. Sci Rep 2016; 6:22493. [PMID: 26940651 PMCID: PMC4778032 DOI: 10.1038/srep22493] [Citation(s) in RCA: 80] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2015] [Accepted: 02/12/2016] [Indexed: 01/07/2023] Open
Abstract
Cystic fibrosis (CF) results in inflammation, malabsorption of fats and other nutrients, and obstruction in the gastrointestinal (GI) tract, yet the mechanisms linking these disease manifestations to microbiome composition remain largely unexplored. Here we used metagenomic analysis to systematically characterize fecal microbiomes of children with and without CF, demonstrating marked CF-associated taxonomic dysbiosis and functional imbalance. We further showed that these taxonomic and functional shifts were especially pronounced in young children with CF and diminished with age. Importantly, the resulting dysbiotic microbiomes had significantly altered capacities for lipid metabolism, including decreased capacity for overall fatty acid biosynthesis and increased capacity for degrading anti-inflammatory short-chain fatty acids. Notably, these functional differences correlated with fecal measures of fat malabsorption and inflammation. Combined, these results suggest that enteric fat abundance selects for pro-inflammatory GI microbiota in young children with CF, offering novel strategies for improving the health of children with CF-associated fat malabsorption.
Collapse
|
56
|
Noecker C, Eng A, Srinivasan S, Theriot CM, Young VB, Jansson JK, Fredricks DN, Borenstein E. Metabolic Model-Based Integration of Microbiome Taxonomic and Metabolomic Profiles Elucidates Mechanistic Links between Ecological and Metabolic Variation. mSystems 2016; 1:e00013-15. [PMID: 27239563 PMCID: PMC4883586 DOI: 10.1128/msystems.00013-15] [Citation(s) in RCA: 138] [Impact Index Per Article: 17.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2015] [Accepted: 12/01/2015] [Indexed: 02/07/2023] Open
Abstract
Multiple molecular assays now enable high-throughput profiling of the ecology, metabolic capacity, and activity of the human microbiome. However, to date, analyses of such multi-omic data typically focus on statistical associations, often ignoring extensive prior knowledge of the mechanisms linking these various facets of the microbiome. Here, we introduce a comprehensive framework to systematically link variation in metabolomic data with community composition by utilizing taxonomic, genomic, and metabolic information. Specifically, we integrate available and inferred genomic data, metabolic network modeling, and a method for predicting community-wide metabolite turnover to estimate the biosynthetic and degradation potential of a given community. Our framework then compares variation in predicted metabolic potential with variation in measured metabolites' abundances to evaluate whether community composition can explain observed shifts in the community metabolome, and to identify key taxa and genes contributing to the shifts. Focusing on two independent vaginal microbiome data sets, each pairing 16S community profiling with large-scale metabolomics, we demonstrate that our framework successfully recapitulates observed variation in 37% of metabolites. Well-predicted metabolite variation tends to result from disease-associated metabolism. We further identify several disease-enriched species that contribute significantly to these predictions. Interestingly, our analysis also detects metabolites for which the predicted variation negatively correlates with the measured variation, suggesting environmental control points of community metabolism. Applying this framework to gut microbiome data sets reveals similar trends, including prediction of bile acid metabolite shifts. This framework is an important first step toward a system-level multi-omic integration and an improved mechanistic understanding of the microbiome activity and dynamics in health and disease. IMPORTANCE Studies characterizing both the taxonomic composition and metabolic profile of various microbial communities are becoming increasingly common, yet new computational methods are needed to integrate and interpret these data in terms of known biological mechanisms. Here, we introduce an analytical framework to link species composition and metabolite measurements, using a simple model to predict the effects of community ecology on metabolite concentrations and evaluating whether these predictions agree with measured metabolomic profiles. We find that a surprisingly large proportion of metabolite variation in the vaginal microbiome can be predicted based on species composition (including dramatic shifts associated with disease), identify putative mechanisms underlying these predictions, and evaluate the roles of individual bacterial species and genes. Analysis of gut microbiome data using this framework recovers similar community metabolic trends. This framework lays the foundation for model-based multi-omic integrative studies, ultimately improving our understanding of microbial community metabolism.
Collapse
Affiliation(s)
- Cecilia Noecker
- Department of Genome Sciences, University of Washington, Seattle, Washington, USA
| | - Alexander Eng
- Department of Genome Sciences, University of Washington, Seattle, Washington, USA
| | - Sujatha Srinivasan
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
| | - Casey M. Theriot
- Department of Population Health and Pathobiology, North Carolina State University, Raleigh, North Carolina, USA
| | - Vincent B. Young
- Department of Internal Medicine, Division of Infectious Diseases, University of Michigan, Ann Arbor, Michigan, USA
- Department of Microbiology and Immunology, University of Michigan, Ann Arbor, Michigan, USA
| | - Janet K. Jansson
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington, USA
| | - David N. Fredricks
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
- Division of Allergy and Infectious Diseases, University of Washington, Seattle, Washington, USA
- Department of Microbiology, University of Washington, Seattle, Washington, USA
| | - Elhanan Borenstein
- Department of Genome Sciences, University of Washington, Seattle, Washington, USA
- Department of Computer Science and Engineering, University of Washington, Seattle, Washington, USA
- Santa Fe Institute, Santa Fe, New Mexico, USA
| |
Collapse
|
57
|
Van Rossum T, Peabody MA, Uyaguari-Diaz MI, Cronin KI, Chan M, Slobodan JR, Nesbitt MJ, Suttle CA, Hsiao WWL, Tang PKC, Prystajecky NA, Brinkman FSL. Year-Long Metagenomic Study of River Microbiomes Across Land Use and Water Quality. Front Microbiol 2015; 6:1405. [PMID: 26733955 PMCID: PMC4681185 DOI: 10.3389/fmicb.2015.01405] [Citation(s) in RCA: 39] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2015] [Accepted: 11/25/2015] [Indexed: 01/04/2023] Open
Abstract
Select bacteria, such as Escherichia coli or coliforms, have been widely used as sentinels of low water quality; however, there are concerns regarding their predictive accuracy for the protection of human and environmental health. To develop improved monitoring systems, a greater understanding of bacterial community structure, function, and variability across time is required in the context of different pollution types, such as agricultural and urban contamination. Here, we present a year-long survey of free-living bacterial DNA collected from seven sites along rivers in three watersheds with varying land use in Southwestern Canada. This is the first study to examine the bacterial metagenome in flowing freshwater (lotic) environments over such a time span, providing an opportunity to describe bacterial community variability as a function of land use and environmental conditions. Characteristics of the metagenomic data, such as sequence composition and average genome size (AGS), vary with sampling site, environmental conditions, and water chemistry. For example, AGS was correlated with hours of daylight in the agricultural watershed and, across the agriculturally and urban-affected sites, k-mer composition clustering corresponded to nutrient concentrations. In addition to indicating a community shift, this change in AGS has implications in terms of the normalization strategies required, and considerations surrounding such strategies in general are discussed. When comparing abundances of gene functional groups between high- and low-quality water samples collected from an agricultural area, the latter had a higher abundance of nutrient metabolism and bacteriophage groups, possibly reflecting an increase in agricultural runoff. This work presents a valuable dataset representing a year of monthly sampling across watersheds and an analysis targeted at establishing a foundational understanding of how bacterial lotic communities vary across time and land use. The results provide important context for future studies, including further analyses of watershed ecosystem health, and the identification and development of biomarkers for improved water quality monitoring systems.
Collapse
Affiliation(s)
- Thea Van Rossum
- Department of Molecular Biology and Biochemistry, Simon Fraser University Burnaby, BC, Canada
| | - Michael A Peabody
- Department of Molecular Biology and Biochemistry, Simon Fraser University Burnaby, BC, Canada
| | - Miguel I Uyaguari-Diaz
- Department of Pathology and Laboratory Medicine, University of British Columbia Vancouver, BC, Canada
| | - Kirby I Cronin
- Department of Pathology and Laboratory Medicine, University of British Columbia Vancouver, BC, Canada
| | - Michael Chan
- British Columbia Public Health Microbiology and Reference Laboratory, British Columbia Centre for Disease Control Vancouver, BC, Canada
| | | | | | - Curtis A Suttle
- Department of Microbiology and Immunology, University of British ColumbiaVancouver, BC, Canada; Department of Earth, Ocean and Atmospheric Sciences, University of British ColumbiaVancouver, BC, Canada; Department of Botany, University of British ColumbiaVancouver, BC, Canada; Canadian Institute for Advanced ResearchToronto, ON, Canada
| | - William W L Hsiao
- Department of Pathology and Laboratory Medicine, University of British ColumbiaVancouver, BC, Canada; British Columbia Public Health Microbiology and Reference Laboratory, British Columbia Centre for Disease ControlVancouver, BC, Canada
| | - Patrick K C Tang
- Department of Pathology and Laboratory Medicine, University of British ColumbiaVancouver, BC, Canada; British Columbia Public Health Microbiology and Reference Laboratory, British Columbia Centre for Disease ControlVancouver, BC, Canada
| | - Natalie A Prystajecky
- Department of Pathology and Laboratory Medicine, University of British ColumbiaVancouver, BC, Canada; British Columbia Public Health Microbiology and Reference Laboratory, British Columbia Centre for Disease ControlVancouver, BC, Canada
| | - Fiona S L Brinkman
- Department of Molecular Biology and Biochemistry, Simon Fraser University Burnaby, BC, Canada
| |
Collapse
|
58
|
Library preparation methodology can influence genomic and functional predictions in human microbiome research. Proc Natl Acad Sci U S A 2015; 112:14024-9. [PMID: 26512100 DOI: 10.1073/pnas.1519288112] [Citation(s) in RCA: 130] [Impact Index Per Article: 14.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
Observations from human microbiome studies are often conflicting or inconclusive. Many factors likely contribute to these issues including small cohort sizes, sample collection, and handling and processing differences. The field of microbiome research is moving from 16S rDNA gene sequencing to a more comprehensive genomic and functional representation through whole-genome sequencing (WGS) of complete communities. Here we performed quantitative and qualitative analyses comparing WGS metagenomic data from human stool specimens using the Illumina Nextera XT and Illumina TruSeq DNA PCR-free kits, and the KAPA Biosystems Hyper Prep PCR and PCR-free systems. Significant differences in taxonomy are observed among the four different next-generation sequencing library preparations using a DNA mock community and a cell control of known concentration. We also revealed biases in error profiles, duplication rates, and loss of reads representing organisms that have a high %G+C content that can significantly impact results. As with all methods, the use of benchmarking controls has revealed critical differences among methods that impact sequencing results and later would impact study interpretation. We recommend that the community adopt PCR-free-based approaches to reduce PCR bias that affects calculations of abundance and to improve assemblies for accurate taxonomic assignment. Furthermore, the inclusion of a known-input cell spike-in control provides accurate quantitation of organisms in clinical samples.
Collapse
|
59
|
Belizário JE, Napolitano M. Human microbiomes and their roles in dysbiosis, common diseases, and novel therapeutic approaches. Front Microbiol 2015; 6:1050. [PMID: 26500616 PMCID: PMC4594012 DOI: 10.3389/fmicb.2015.01050] [Citation(s) in RCA: 198] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2015] [Accepted: 09/14/2015] [Indexed: 12/13/2022] Open
Abstract
The human body is the residence of a large number of commensal (non-pathogenic) and pathogenic microbial species that have co-evolved with the human genome, adaptive immune system, and diet. With recent advances in DNA-based technologies, we initiated the exploration of bacterial gene functions and their role in human health. The main goal of the human microbiome project is to characterize the abundance, diversity and functionality of the genes present in all microorganisms that permanently live in different sites of the human body. The gut microbiota expresses over 3.3 million bacterial genes, while the human genome expresses only 20 thousand genes. Microbe gene-products exert pivotal functions via the regulation of food digestion and immune system development. Studies are confirming that manipulation of non-pathogenic bacterial strains in the host can stimulate the recovery of the immune response to pathogenic bacteria causing diseases. Different approaches, including the use of nutraceutics (prebiotics and probiotics) as well as phages engineered with CRISPR/Cas systems and quorum sensing systems have been developed as new therapies for controlling dysbiosis (alterations in microbial community) and common diseases (e.g., diabetes and obesity). The designing and production of pharmaceuticals based on our own body’s microbiome is an emerging field and is rapidly growing to be fully explored in the near future. This review provides an outlook on recent findings on the human microbiomes, their impact on health and diseases, and on the development of targeted therapies.
Collapse
Affiliation(s)
- José E Belizário
- Department of Pharmacology, Institute of Biomedical Sciences, University of São Paulo, São Paulo Brazil
| | - Mauro Napolitano
- Department of Pharmacology, Institute of Biomedical Sciences, University of São Paulo, São Paulo Brazil
| |
Collapse
|
60
|
Nayfach S, Fischbach MA, Pollard KS. MetaQuery: a web server for rapid annotation and quantitative analysis of specific genes in the human gut microbiome. Bioinformatics 2015; 31:3368-70. [PMID: 26104745 PMCID: PMC4595903 DOI: 10.1093/bioinformatics/btv382] [Citation(s) in RCA: 46] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2015] [Accepted: 06/16/2015] [Indexed: 11/24/2022] Open
Abstract
Summary: Microbiome researchers frequently want to know how abundant a particular microbial gene or pathway is across different human hosts, including its association with disease and its co-occurrence with other genes or microbial taxa. With thousands of publicly available metagenomes, these questions should be easy to answer. However, computational barriers prevent most researchers from conducting such analyses. We address this problem with MetaQuery, a web application for rapid and quantitative analysis of specific genes in the human gut microbiome. The user inputs one or more query genes, and our software returns the estimated abundance of these genes across 1267 publicly available fecal metagenomes from American, European and Chinese individuals. In addition, our application performs downstream statistical analyses to identify features that are associated with gene variation, including other query genes (i.e. gene co-variation), taxa, clinical variables (e.g. inflammatory bowel disease and diabetes) and average genome size. The speed and accessibility of MetaQuery are a step toward democratizing metagenomics research, which should allow many researchers to query the abundance and variation of specific genes in the human gut microbiome. Availability and implementation:http://metaquery.docpollard.org. Contact:snayfach@gmail.com Supplementary information:Supplementary data are available at Bioinformatics online.
Collapse
Affiliation(s)
- Stephen Nayfach
- Integrative Program in Quantitative Biology, Gladstone Institutes, and Division of Biostatistics, University of California San Francisco and
| | - Michael A Fischbach
- Department of Bioengineering and Therapeutic Sciences and California Institute for Quantitative Biosciences, University of California San Francisco, San Francisco, CA, USA
| | - Katherine S Pollard
- Integrative Program in Quantitative Biology, Gladstone Institutes, and Division of Biostatistics, University of California San Francisco and
| |
Collapse
|