101
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Li Q, Lin F, Yang C, Wang J, Lin Y, Shen M, Park MS, Li T, Zhao J. A Large-Scale Comparative Metagenomic Study Reveals the Functional Interactions in Six Bloom-Forming Microcystis-Epibiont Communities. Front Microbiol 2018; 9:746. [PMID: 29731741 PMCID: PMC5919953 DOI: 10.3389/fmicb.2018.00746] [Citation(s) in RCA: 31] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2017] [Accepted: 04/03/2018] [Indexed: 11/13/2022] Open
Abstract
Cyanobacterial blooms are worldwide issues of societal concern and scientific interest. Lake Taihu and Lake Dianchi, two of the largest lakes in China, have been suffering from annual Microcystis-based blooms over the past two decades. These two eutrophic lakes differ in both nutrient load and environmental parameters, where Microcystis microbiota consisting of different Microcystis morphospecies and associated bacteria (epibionts) have dominated. We conducted a comprehensive metagenomic study that analyzed species diversity, community structure, functional components, metabolic pathways and networks to investigate functional interactions among the members of six Microcystis-epibiont communities in these two lakes. Our integrated metagenomic pipeline consisted of efficient assembly, binning, annotation, and quality assurance methods that ensured high-quality genome reconstruction. This study provides a total of 68 reconstructed genomes including six complete Microcystis genomes and 28 high quality bacterial genomes of epibionts belonging to 14 distinct taxa. This metagenomic dataset constitutes the largest reference genome catalog available for genome-centric studies of the Microcystis microbiome. Epibiont community composition appears to be dynamic rather than fixed, and the functional profiles of communities were related to the environment of origin. This study demonstrates mutualistic interactions between Microcystis and epibionts at genetic and metabolic levels. Metabolic pathway reconstruction provided evidence for functional complementation in nitrogen and sulfur cycles, fatty acid catabolism, vitamin synthesis, and aromatic compound degradation among community members. Thus, bacterial social interactions within Microcystis-epibiont communities not only shape species composition, but also stabilize the communities functional profiles. These interactions appear to play an important role in environmental adaptation of Microcystis colonies.
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Affiliation(s)
- Qi Li
- State Key Laboratory of Freshwater Ecology and Biotechnology, Institute of Hydrobiology, Chinese Academy of Science, Wuhan, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Feibi Lin
- State Key Laboratory of Freshwater Ecology and Biotechnology, Institute of Hydrobiology, Chinese Academy of Science, Wuhan, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Chen Yang
- Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Wuhan, China
| | - Juanping Wang
- State Key Laboratory of Freshwater Ecology and Biotechnology, Institute of Hydrobiology, Chinese Academy of Science, Wuhan, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Yan Lin
- State Key Laboratory of Freshwater Ecology and Biotechnology, Institute of Hydrobiology, Chinese Academy of Science, Wuhan, China
| | - Mengyuan Shen
- State Key Laboratory of Freshwater Ecology and Biotechnology, Institute of Hydrobiology, Chinese Academy of Science, Wuhan, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Min S. Park
- Center for Microalgal Biotechnology and Biofuels, Institute of Hydrobiology, Chinese Academy of Science, Wuhan, China
| | - Tao Li
- State Key Laboratory of Freshwater Ecology and Biotechnology, Institute of Hydrobiology, Chinese Academy of Science, Wuhan, China
| | - Jindong Zhao
- State Key Laboratory of Freshwater Ecology and Biotechnology, Institute of Hydrobiology, Chinese Academy of Science, Wuhan, China
- State Key Laboratory of Protein and Plant Genetic Engineering, College of Life Sciences, Peking University, Beijing, China
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102
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Coelho LP, Kultima JR, Costea PI, Fournier C, Pan Y, Czarnecki-Maulden G, Hayward MR, Forslund SK, Schmidt TSB, Descombes P, Jackson JR, Li Q, Bork P. Similarity of the dog and human gut microbiomes in gene content and response to diet. MICROBIOME 2018; 6:72. [PMID: 29669589 PMCID: PMC5907387 DOI: 10.1186/s40168-018-0450-3] [Citation(s) in RCA: 176] [Impact Index Per Article: 29.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/11/2017] [Accepted: 03/19/2018] [Indexed: 05/19/2023]
Abstract
BACKGROUND Gut microbes influence their hosts in many ways, in particular by modulating the impact of diet. These effects have been studied most extensively in humans and mice. In this work, we used whole genome metagenomics to investigate the relationship between the gut metagenomes of dogs, humans, mice, and pigs. RESULTS We present a dog gut microbiome gene catalog containing 1,247,405 genes (based on 129 metagenomes and a total of 1.9 terabasepairs of sequencing data). Based on this catalog and taxonomic abundance profiling, we show that the dog microbiome is closer to the human microbiome than the microbiome of either pigs or mice. To investigate this similarity in terms of response to dietary changes, we report on a randomized intervention with two diets (high-protein/low-carbohydrate vs. lower protein/higher carbohydrate). We show that diet has a large and reproducible effect on the dog microbiome, independent of breed or sex. Moreover, the responses were in agreement with those observed in previous human studies. CONCLUSIONS We conclude that findings in dogs may be predictive of human microbiome results. In particular, a novel finding is that overweight or obese dogs experience larger compositional shifts than lean dogs in response to a high-protein diet.
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Affiliation(s)
- Luis Pedro Coelho
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Jens Roat Kultima
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Paul Igor Costea
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | | | | | | | - Matthew Robert Hayward
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Sofia K. Forslund
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | | | | | | | | | - Peer Bork
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
- Max Delbrück Centre for Molecular Medicine, 13125 Berlin, Germany
- Department of Bioinformatics, Biocenter, University of Würzburg, 97074 Würzburg, Germany
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103
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Maier L, Pruteanu M, Kuhn M, Zeller G, Telzerow A, Anderson EE, Brochado AR, Fernandez KC, Dose H, Mori H, Patil KR, Bork P, Typas A. Extensive impact of non-antibiotic drugs on human gut bacteria. Nature 2018; 555:623-628. [PMID: 29555994 PMCID: PMC6108420 DOI: 10.1038/nature25979] [Citation(s) in RCA: 1143] [Impact Index Per Article: 190.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2017] [Accepted: 02/08/2018] [Indexed: 12/13/2022]
Abstract
A few commonly used non-antibiotic drugs have recently been associated with changes in gut microbiome composition, but the extent of this phenomenon is unknown. Here, we screened more than 1,000 marketed drugs against 40 representative gut bacterial strains, and found that 24% of the drugs with human targets, including members of all therapeutic classes, inhibited the growth of at least one strain in vitro. Particular classes, such as the chemically diverse antipsychotics, were overrepresented in this group. The effects of human-targeted drugs on gut bacteria are reflected on their antibiotic-like side effects in humans and are concordant with existing human cohort studies. Susceptibility to antibiotics and human-targeted drugs correlates across bacterial species, suggesting common resistance mechanisms, which we verified for some drugs. The potential risk of non-antibiotics promoting antibiotic resistance warrants further exploration. Our results provide a resource for future research on drug-microbiome interactions, opening new paths for side effect control and drug repurposing, and broadening our view of antibiotic resistance.
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Affiliation(s)
- Lisa Maier
- European Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany
| | - Mihaela Pruteanu
- European Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany
| | - Michael Kuhn
- European Molecular Biology Laboratory, Structural and Computational Biology Unit, Heidelberg, Germany
| | - Georg Zeller
- European Molecular Biology Laboratory, Structural and Computational Biology Unit, Heidelberg, Germany
| | - Anja Telzerow
- European Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany
| | - Exene Erin Anderson
- European Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany
| | - Ana Rita Brochado
- European Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany
| | | | - Hitomi Dose
- Graduate School of Biological Sciences, Nara Institute of Science and Technology, Ikoma, Japan
| | - Hirotada Mori
- Graduate School of Biological Sciences, Nara Institute of Science and Technology, Ikoma, Japan
| | - Kiran Raosaheb Patil
- European Molecular Biology Laboratory, Structural and Computational Biology Unit, Heidelberg, Germany
| | - Peer Bork
- European Molecular Biology Laboratory, Structural and Computational Biology Unit, Heidelberg, Germany
- Max-Delbrück-Centre for Molecular Medicine, Berlin, Germany
- Molecular Medicine Partnership Unit, Heidelberg, Germany
- Department of Bioinformatics, Biocenter, University of Würzburg, Germany
| | - Athanasios Typas
- European Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany
- European Molecular Biology Laboratory, Structural and Computational Biology Unit, Heidelberg, Germany
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104
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Huerta-Cepas J, Forslund K, Coelho LP, Szklarczyk D, Jensen LJ, von Mering C, Bork P. Fast Genome-Wide Functional Annotation through Orthology Assignment by eggNOG-Mapper. Mol Biol Evol 2018; 34:2115-2122. [PMID: 28460117 PMCID: PMC5850834 DOI: 10.1093/molbev/msx148] [Citation(s) in RCA: 1578] [Impact Index Per Article: 263.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
Orthology assignment is ideally suited for functional inference. However, because predicting orthology is computationally intensive at large scale, and most pipelines are relatively inaccessible (e.g., new assignments only available through database updates), less precise homology-based functional transfer is still the default for (meta-)genome annotation. We, therefore, developed eggNOG-mapper, a tool for functional annotation of large sets of sequences based on fast orthology assignments using precomputed clusters and phylogenies from the eggNOG database. To validate our method, we benchmarked Gene Ontology (GO) predictions against two widely used homology-based approaches: BLAST and InterProScan. Orthology filters applied to BLAST results reduced the rate of false positive assignments by 11%, and increased the ratio of experimentally validated terms recovered over all terms assigned per protein by 15%. Compared with InterProScan, eggNOG-mapper achieved similar proteome coverage and precision while predicting, on average, 41 more terms per protein and increasing the rate of experimentally validated terms recovered over total term assignments per protein by 35%. EggNOG-mapper predictions scored within the top-5 methods in the three GO categories using the CAFA2 NK-partial benchmark. Finally, we evaluated eggNOG-mapper for functional annotation of metagenomics data, yielding better performance than interProScan. eggNOG-mapper runs ∼15× faster than BLAST and at least 2.5× faster than InterProScan. The tool is available standalone and as an online service at http://eggnog-mapper.embl.de.
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Affiliation(s)
- Jaime Huerta-Cepas
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Kristoffer Forslund
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Luis Pedro Coelho
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Damian Szklarczyk
- Institute of Molecular Life Sciences, University of Zurich, Zurich, Switzerland.,Bioinformatics/Systems Biology Group, Swiss Institute of Bioinformatics (SIB), Zurich, Switzerland
| | - Lars Juhl Jensen
- The Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Christian von Mering
- Institute of Molecular Life Sciences, University of Zurich, Zurich, Switzerland.,Bioinformatics/Systems Biology Group, Swiss Institute of Bioinformatics (SIB), Zurich, Switzerland
| | - Peer Bork
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany.,Germany Molecular Medicine Partnership Unit (MMPU), University Hospital Heidelberg and European Molecular Biology Laboratory, Heidelberg, Germany.,Max Delbrück Centre for Molecular Medicine, Berlin, Germany.,Department of Bioinformatics, Biocenter University of Würzburg, Würzburg, Germany
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105
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Chiara M, Placido A, Picardi E, Ceci LR, Horner DS, Pesole G. A-GAME: improving the assembly of pooled functional metagenomics sequence data. BMC Genomics 2018; 19:44. [PMID: 29329522 PMCID: PMC5767027 DOI: 10.1186/s12864-017-4369-z] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2017] [Accepted: 12/08/2017] [Indexed: 02/06/2023] Open
Abstract
Background Expression screening of environmental DNA (eDNA) libraries is a popular approach for the identification and characterization of novel microbial enzymes with promising biotechnological properties. In such “functional metagenomics” experiments, inserts, selected on the basis of activity assays, are sequenced with high throughput sequencing technologies. Assembly is followed by gene prediction, annotation and identification of candidate genes that are subsequently evaluated for biotechnological applications. Results Here we present A-GAME (A GAlaxy suite for functional MEtagenomics), a web service incorporating state of the art tools and workflows for the analysis of eDNA sequence data. We illustrate the potential of A-GAME workflows using real functional metagenomics data, showing that they outperform alternative metagenomics assemblers. Dedicated tools available in A-GAME allow efficient analysis of pooled libraries and rapid identification of candidate genes, reducing sequencing costs and saving the need for laborious manual annotation. Conclusion In conclusion, we believe A-GAME will constitute a valuable resource for the functional metagenomics community. A-GAME is publicly available at http://beaconlab.it/agame Electronic supplementary material The online version of this article (10.1186/s12864-017-4369-z) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Matteo Chiara
- Department of Biosciences, University of Milan, via Celoria 26, 20133, Milan, Italy
| | - Antonio Placido
- Institute of Biomembranes, Bioenergetics and Molecular Biotechnology, Consiglio Nazionale delle Ricerche, via Amendola 165A, 70126, Bari, Italy
| | - Ernesto Picardi
- Institute of Biomembranes, Bioenergetics and Molecular Biotechnology, Consiglio Nazionale delle Ricerche, via Amendola 165A, 70126, Bari, Italy.,Department of Biosciences, Biotechnology and Biopharmaceutics, University of Bari "A. Moro", via Orabona, 4, 70126, Bari, Italy
| | - Luigi Ruggiero Ceci
- Institute of Biomembranes, Bioenergetics and Molecular Biotechnology, Consiglio Nazionale delle Ricerche, via Amendola 165A, 70126, Bari, Italy
| | - David Stephen Horner
- Department of Biosciences, University of Milan, via Celoria 26, 20133, Milan, Italy. .,Institute of Biomembranes, Bioenergetics and Molecular Biotechnology, Consiglio Nazionale delle Ricerche, via Amendola 165A, 70126, Bari, Italy.
| | - Graziano Pesole
- Institute of Biomembranes, Bioenergetics and Molecular Biotechnology, Consiglio Nazionale delle Ricerche, via Amendola 165A, 70126, Bari, Italy.,Department of Biosciences, Biotechnology and Biopharmaceutics, University of Bari "A. Moro", via Orabona, 4, 70126, Bari, Italy
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106
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Costea PI, Coelho LP, Sunagawa S, Munch R, Huerta-Cepas J, Forslund K, Hildebrand F, Kushugulova A, Zeller G, Bork P. Subspecies in the global human gut microbiome. Mol Syst Biol 2017; 13:960. [PMID: 29242367 PMCID: PMC5740502 DOI: 10.15252/msb.20177589] [Citation(s) in RCA: 80] [Impact Index Per Article: 11.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2017] [Revised: 11/24/2017] [Accepted: 11/29/2017] [Indexed: 02/06/2023] Open
Abstract
Population genomics of prokaryotes has been studied in depth in only a small number of primarily pathogenic bacteria, as genome sequences of isolates of diverse origin are lacking for most species. Here, we conducted a large-scale survey of population structure in prevalent human gut microbial species, sampled from their natural environment, with a culture-independent metagenomic approach. We examined the variation landscape of 71 species in 2,144 human fecal metagenomes and found that in 44 of these, accounting for 72% of the total assigned microbial abundance, single-nucleotide variation clearly indicates the existence of sub-populations (here termed subspecies). A single subspecies (per species) usually dominates within each host, as expected from ecological theory. At the global scale, geographic distributions of subspecies differ between phyla, with Firmicutes subspecies being significantly more geographically restricted. To investigate the functional significance of the delineated subspecies, we identified genes that consistently distinguish them in a manner that is independent of reference genomes. We further associated these subspecies-specific genes with properties of the microbial community and the host. For example, two of the three Eubacterium rectale subspecies consistently harbor an accessory pro-inflammatory flagellum operon that is associated with lower gut community diversity, higher host BMI, and higher blood fasting insulin levels. Using an additional 676 human oral samples, we further demonstrate the existence of niche specialized subspecies in the different parts of the oral cavity. Taken together, we provide evidence for subspecies in the majority of abundant gut prokaryotes, leading to a better functional and ecological understanding of the human gut microbiome in conjunction with its host.
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Affiliation(s)
- Paul I Costea
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Luis Pedro Coelho
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Shinichi Sunagawa
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
- Department of Biology, Institute of Microbiology, ETH Zurich, Zurich, Switzerland
| | - Robin Munch
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Jaime Huerta-Cepas
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Kristoffer Forslund
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Falk Hildebrand
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | | | - Georg Zeller
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Peer Bork
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
- Max-Delbrück-Centre for Molecular Medicine, Berlin, Germany
- Molecular Medicine Partnership Unit, Heidelberg, Germany
- Department of Bioinformatics, Biocenter, University of Würzburg, Würzburg, Germany
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107
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Wilck N, Matus MG, Kearney SM, Olesen SW, Forslund K, Bartolomaeus H, Haase S, Mähler A, Balogh A, Markó L, Vvedenskaya O, Kleiner FH, Tsvetkov D, Klug L, Costea PI, Sunagawa S, Maier L, Rakova N, Schatz V, Neubert P, Frätzer C, Krannich A, Gollasch M, Grohme DA, Côrte-Real BF, Gerlach RG, Basic M, Typas A, Wu C, Titze JM, Jantsch J, Boschmann M, Dechend R, Kleinewietfeld M, Kempa S, Bork P, Linker RA, Alm EJ, Müller DN. Salt-responsive gut commensal modulates T H17 axis and disease. Nature 2017; 551:585-589. [PMID: 29143823 PMCID: PMC6070150 DOI: 10.1038/nature24628] [Citation(s) in RCA: 806] [Impact Index Per Article: 115.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2016] [Accepted: 10/10/2017] [Indexed: 12/12/2022]
Abstract
A Western lifestyle with high salt consumption can lead to hypertension and cardiovascular disease. High salt may additionally drive autoimmunity by inducing T helper 17 (TH17) cells, which can also contribute to hypertension. Induction of TH17 cells depends on gut microbiota; however, the effect of salt on the gut microbiome is unknown. Here we show that high salt intake affects the gut microbiome in mice, particularly by depleting Lactobacillus murinus. Consequently, treatment of mice with L. murinus prevented salt-induced aggravation of actively induced experimental autoimmune encephalomyelitis and salt-sensitive hypertension by modulating TH17 cells. In line with these findings, a moderate high-salt challenge in a pilot study in humans reduced intestinal survival of Lactobacillus spp., increased TH17 cells and increased blood pressure. Our results connect high salt intake to the gut-immune axis and highlight the gut microbiome as a potential therapeutic target to counteract salt-sensitive conditions.
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Affiliation(s)
- Nicola Wilck
- Experimental and Clinical Research Center, a joint cooperation of Max-Delbrück Center for Molecular Medicine and Charité-Universitätsmedizin Berlin, 13125 Berlin, Germany
- Charité-Universitätsmedizin Berlin, 10117 Berlin, Germany
- Max-Delbrück Center for Molecular Medicine in the Helmholtz Association, 13125 Berlin, Germany
- DZHK (German Centre for Cardiovascular Research), partner site Berlin, Germany
- Berlin Institute of Health (BIH), Berlin, Germany
| | - Mariana G Matus
- Center for Microbiome Informatics and Therapeutics, and Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
- Computational and Systems Biology Program, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
| | - Sean M Kearney
- Center for Microbiome Informatics and Therapeutics, and Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
| | - Scott W Olesen
- Center for Microbiome Informatics and Therapeutics, and Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
| | - Kristoffer Forslund
- European Molecular Biology Laboratory, Structural and Computational Biology Unit, 69117 Heidelberg, Germany
| | - Hendrik Bartolomaeus
- Experimental and Clinical Research Center, a joint cooperation of Max-Delbrück Center for Molecular Medicine and Charité-Universitätsmedizin Berlin, 13125 Berlin, Germany
- Charité-Universitätsmedizin Berlin, 10117 Berlin, Germany
- Max-Delbrück Center for Molecular Medicine in the Helmholtz Association, 13125 Berlin, Germany
- DZHK (German Centre for Cardiovascular Research), partner site Berlin, Germany
| | - Stefanie Haase
- Department of Neurology, Friedrich-Alexander-University Erlangen-Nuremberg, 91054 Erlangen, Germany
| | - Anja Mähler
- Experimental and Clinical Research Center, a joint cooperation of Max-Delbrück Center for Molecular Medicine and Charité-Universitätsmedizin Berlin, 13125 Berlin, Germany
- Berlin Institute of Health (BIH), Berlin, Germany
| | - András Balogh
- Experimental and Clinical Research Center, a joint cooperation of Max-Delbrück Center for Molecular Medicine and Charité-Universitätsmedizin Berlin, 13125 Berlin, Germany
- Charité-Universitätsmedizin Berlin, 10117 Berlin, Germany
- Max-Delbrück Center for Molecular Medicine in the Helmholtz Association, 13125 Berlin, Germany
- DZHK (German Centre for Cardiovascular Research), partner site Berlin, Germany
- Berlin Institute of Health (BIH), Berlin, Germany
| | - Lajos Markó
- Experimental and Clinical Research Center, a joint cooperation of Max-Delbrück Center for Molecular Medicine and Charité-Universitätsmedizin Berlin, 13125 Berlin, Germany
- Charité-Universitätsmedizin Berlin, 10117 Berlin, Germany
- Max-Delbrück Center for Molecular Medicine in the Helmholtz Association, 13125 Berlin, Germany
- DZHK (German Centre for Cardiovascular Research), partner site Berlin, Germany
- Berlin Institute of Health (BIH), Berlin, Germany
| | - Olga Vvedenskaya
- Max-Delbrück Center for Molecular Medicine in the Helmholtz Association, 13125 Berlin, Germany
- Integrative Proteomics and Metabolomics Platform, Berlin Institute for Medical Systems Biology BIMSB, 13125 Berlin, Germany
- Berlin School of Integrative Oncology, Charité University Medicine Berlin, Berlin, Germany
| | - Friedrich H Kleiner
- Experimental and Clinical Research Center, a joint cooperation of Max-Delbrück Center for Molecular Medicine and Charité-Universitätsmedizin Berlin, 13125 Berlin, Germany
| | - Dmitry Tsvetkov
- Experimental and Clinical Research Center, a joint cooperation of Max-Delbrück Center for Molecular Medicine and Charité-Universitätsmedizin Berlin, 13125 Berlin, Germany
- Charité-Universitätsmedizin Berlin, 10117 Berlin, Germany
| | - Lars Klug
- Experimental and Clinical Research Center, a joint cooperation of Max-Delbrück Center for Molecular Medicine and Charité-Universitätsmedizin Berlin, 13125 Berlin, Germany
- Berlin Institute of Health (BIH), Berlin, Germany
| | - Paul I Costea
- European Molecular Biology Laboratory, Structural and Computational Biology Unit, 69117 Heidelberg, Germany
| | - Shinichi Sunagawa
- European Molecular Biology Laboratory, Structural and Computational Biology Unit, 69117 Heidelberg, Germany
- Institute of Microbiology, ETH Zurich, 8092 Zurich, Switzerland
| | - Lisa Maier
- European Molecular Biology Laboratory, Genome Biology Unit, 69117 Heidelberg, Germany
| | - Natalia Rakova
- Experimental and Clinical Research Center, a joint cooperation of Max-Delbrück Center for Molecular Medicine and Charité-Universitätsmedizin Berlin, 13125 Berlin, Germany
- Department of Neurology, Friedrich-Alexander-University Erlangen-Nuremberg, 91054 Erlangen, Germany
| | - Valentin Schatz
- Institute of Clinical Microbiology and Hygiene, University Hospital of Regensburg, University of Regensburg, 93053 Regensburg, Germany
| | - Patrick Neubert
- Institute of Clinical Microbiology and Hygiene, University Hospital of Regensburg, University of Regensburg, 93053 Regensburg, Germany
| | | | | | - Maik Gollasch
- Experimental and Clinical Research Center, a joint cooperation of Max-Delbrück Center for Molecular Medicine and Charité-Universitätsmedizin Berlin, 13125 Berlin, Germany
- Charité-Universitätsmedizin Berlin, 10117 Berlin, Germany
- Max-Delbrück Center for Molecular Medicine in the Helmholtz Association, 13125 Berlin, Germany
| | - Diana A Grohme
- Translational Immunology, Department of Clinical Pathobiochemistry, Medical Faculty Carl Gustav Carus, Technical University of Dresden, 01307 Dresden, Germany
| | - Beatriz F Côrte-Real
- VIB Laboratory of Translational Immunomodulation, VIB Center for Inflammation Research (IRC), Hasselt University, Campus Diepenbeek, 3590 Diepenbeek, Belgium
| | - Roman G Gerlach
- Project Group 5, Robert Koch Institute, 38855 Wernigerode, Germany
| | - Marijana Basic
- Hannover Medical School, Institute for Laboratory Animal Science and Central Animal Facility, 30625 Hannover, Germany
| | - Athanasios Typas
- European Molecular Biology Laboratory, Genome Biology Unit, 69117 Heidelberg, Germany
| | - Chuan Wu
- Experimental Immunology Branch, National Cancer Institute, US National Institutes of Health, Bethesda, Maryland, USA
| | - Jens M Titze
- Division of Clinical Pharmacology, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
| | - Jonathan Jantsch
- Institute of Clinical Microbiology and Hygiene, University Hospital of Regensburg, University of Regensburg, 93053 Regensburg, Germany
| | - Michael Boschmann
- Experimental and Clinical Research Center, a joint cooperation of Max-Delbrück Center for Molecular Medicine and Charité-Universitätsmedizin Berlin, 13125 Berlin, Germany
- Berlin Institute of Health (BIH), Berlin, Germany
| | - Ralf Dechend
- Experimental and Clinical Research Center, a joint cooperation of Max-Delbrück Center for Molecular Medicine and Charité-Universitätsmedizin Berlin, 13125 Berlin, Germany
- Charité-Universitätsmedizin Berlin, 10117 Berlin, Germany
- Berlin Institute of Health (BIH), Berlin, Germany
| | - Markus Kleinewietfeld
- Translational Immunology, Department of Clinical Pathobiochemistry, Medical Faculty Carl Gustav Carus, Technical University of Dresden, 01307 Dresden, Germany
- VIB Laboratory of Translational Immunomodulation, VIB Center for Inflammation Research (IRC), Hasselt University, Campus Diepenbeek, 3590 Diepenbeek, Belgium
- Center for Regenerative Therapies Dresden (CRTD), 01307 Dresden, Germany
| | - Stefan Kempa
- Max-Delbrück Center for Molecular Medicine in the Helmholtz Association, 13125 Berlin, Germany
- Berlin Institute of Health (BIH), Berlin, Germany
- Integrative Proteomics and Metabolomics Platform, Berlin Institute for Medical Systems Biology BIMSB, 13125 Berlin, Germany
| | - Peer Bork
- Max-Delbrück Center for Molecular Medicine in the Helmholtz Association, 13125 Berlin, Germany
- European Molecular Biology Laboratory, Structural and Computational Biology Unit, 69117 Heidelberg, Germany
- Molecular Medicine Partnership Unit, University of Heidelberg and European Molecular Biology Laboratory, 69120 Heidelberg, Germany
- Department of Bioinformatics, Biocenter, University of Würzburg, 97074 Würzburg, Germany
| | - Ralf A Linker
- Department of Neurology, Friedrich-Alexander-University Erlangen-Nuremberg, 91054 Erlangen, Germany
| | - Eric J Alm
- Center for Microbiome Informatics and Therapeutics, and Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
| | - Dominik N Müller
- Experimental and Clinical Research Center, a joint cooperation of Max-Delbrück Center for Molecular Medicine and Charité-Universitätsmedizin Berlin, 13125 Berlin, Germany
- Charité-Universitätsmedizin Berlin, 10117 Berlin, Germany
- Max-Delbrück Center for Molecular Medicine in the Helmholtz Association, 13125 Berlin, Germany
- DZHK (German Centre for Cardiovascular Research), partner site Berlin, Germany
- Berlin Institute of Health (BIH), Berlin, Germany
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108
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Huerta-Cepas J, Forslund K, Coelho LP, Szklarczyk D, Jensen LJ, von Mering C, Bork P. Fast Genome-Wide Functional Annotation through Orthology Assignment by eggNOG-Mapper. Mol Biol Evol 2017. [PMID: 28460117 DOI: 10.1093/molbev/msx148.] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Orthology assignment is ideally suited for functional inference. However, because predicting orthology is computationally intensive at large scale, and most pipelines are relatively inaccessible (e.g., new assignments only available through database updates), less precise homology-based functional transfer is still the default for (meta-)genome annotation. We, therefore, developed eggNOG-mapper, a tool for functional annotation of large sets of sequences based on fast orthology assignments using precomputed clusters and phylogenies from the eggNOG database. To validate our method, we benchmarked Gene Ontology (GO) predictions against two widely used homology-based approaches: BLAST and InterProScan. Orthology filters applied to BLAST results reduced the rate of false positive assignments by 11%, and increased the ratio of experimentally validated terms recovered over all terms assigned per protein by 15%. Compared with InterProScan, eggNOG-mapper achieved similar proteome coverage and precision while predicting, on average, 41 more terms per protein and increasing the rate of experimentally validated terms recovered over total term assignments per protein by 35%. EggNOG-mapper predictions scored within the top-5 methods in the three GO categories using the CAFA2 NK-partial benchmark. Finally, we evaluated eggNOG-mapper for functional annotation of metagenomics data, yielding better performance than interProScan. eggNOG-mapper runs ∼15× faster than BLAST and at least 2.5× faster than InterProScan. The tool is available standalone and as an online service at http://eggnog-mapper.embl.de.
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Affiliation(s)
- Jaime Huerta-Cepas
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Kristoffer Forslund
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Luis Pedro Coelho
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Damian Szklarczyk
- Institute of Molecular Life Sciences, University of Zurich, Zurich, Switzerland.,Bioinformatics/Systems Biology Group, Swiss Institute of Bioinformatics (SIB), Zurich, Switzerland
| | - Lars Juhl Jensen
- The Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Christian von Mering
- Institute of Molecular Life Sciences, University of Zurich, Zurich, Switzerland.,Bioinformatics/Systems Biology Group, Swiss Institute of Bioinformatics (SIB), Zurich, Switzerland
| | - Peer Bork
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany.,Germany Molecular Medicine Partnership Unit (MMPU), University Hospital Heidelberg and European Molecular Biology Laboratory, Heidelberg, Germany.,Max Delbrück Centre for Molecular Medicine, Berlin, Germany.,Department of Bioinformatics, Biocenter University of Würzburg, Würzburg, Germany
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109
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Bedarf JR, Hildebrand F, Coelho LP, Sunagawa S, Bahram M, Goeser F, Bork P, Wüllner U. Functional implications of microbial and viral gut metagenome changes in early stage L-DOPA-naïve Parkinson's disease patients. Genome Med 2017; 9:39. [PMID: 28449715 PMCID: PMC5408370 DOI: 10.1186/s13073-017-0428-y] [Citation(s) in RCA: 358] [Impact Index Per Article: 51.1] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2016] [Accepted: 04/08/2017] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND Parkinson's disease (PD) presently is conceptualized as a protein aggregation disease in which pathology involves both the enteric and the central nervous system, possibly spreading from one to another via the vagus nerves. As gastrointestinal dysfunction often precedes or parallels motor symptoms, the enteric system with its vast diversity of microorganisms may be involved in PD pathogenesis. Alterations in the enteric microbial taxonomic level of L-DOPA-naïve PD patients might also serve as a biomarker. METHODS We performed metagenomic shotgun analyses and compared the fecal microbiomes of 31 early stage, L-DOPA-naïve PD patients to 28 age-matched controls. RESULTS We found increased Verrucomicrobiaceae (Akkermansia muciniphila) and unclassified Firmicutes, whereas Prevotellaceae (Prevotella copri) and Erysipelotrichaceae (Eubacterium biforme) were markedly lowered in PD samples. The observed differences could reliably separate PD from control with a ROC-AUC of 0.84. Functional analyses of the metagenomes revealed differences in microbiota metabolism in PD involving the ẞ-glucuronate and tryptophan metabolism. While the abundances of prophages and plasmids did not differ between PD and controls, total virus abundance was decreased in PD participants. Based on our analyses, the intake of either a MAO inhibitor, amantadine, or a dopamine agonist (which in summary relates to 90% of PD patients) had no overall influence on taxa abundance or microbial functions. CONCLUSIONS Our data revealed differences of colonic microbiota and of microbiota metabolism between PD patients and controls at an unprecedented detail not achievable through 16S sequencing. The findings point to a yet unappreciated aspect of PD, possibly involving the intestinal barrier function and immune function in PD patients. The influence of the parkinsonian medication should be further investigated in the future in larger cohorts.
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Affiliation(s)
- J R Bedarf
- Department of Neurology, University of Bonn, Bonn, Germany.,German Centre for neurodegenerative disease research (DZNE), Bonn, Germany
| | - F Hildebrand
- European Molecular Biology Laboratory, EMBL, Heidelberg, Germany
| | - L P Coelho
- European Molecular Biology Laboratory, EMBL, Heidelberg, Germany
| | - S Sunagawa
- European Molecular Biology Laboratory, EMBL, Heidelberg, Germany.,ETH Zurich, Institute of Microbiology, Vladimir-Prelog-1-5/10, 8093, Zurich, Switzerland
| | - M Bahram
- Evolutionary Biology Centre, Uppsala University, Norbyva ̈gen 18D, 75236, Uppsala, Sweden.,Institute of Ecology and Earth Sciences, University of Tartu, 40 Lai St., 51005, Tartu, Estonia
| | - F Goeser
- Department of Internal Medicine I, University of Bonn, Bonn, Germany.,German Center for Infection Research (DZIF), Bonn-Cologne, Germany
| | - P Bork
- European Molecular Biology Laboratory, EMBL, Heidelberg, Germany. .,Molecular Medicine Partnership Unit (MMPU), University of Heidelberg and European Molecular Biology Laboratory, Heidelberg, Germany. .,Max Delbrück Centre for Molecular Medicine, 13125, Berlin, Germany. .,Department of Bioinformatics, University of Würzburg, 97074, Würzburg, Germany. .,, Meyerhofstraße 1, 69117, Heidelberg, Germany.
| | - U Wüllner
- Department of Neurology, University of Bonn, Bonn, Germany. .,German Centre for neurodegenerative disease research (DZNE), Bonn, Germany. .,, Sigmund-Freud-Str. 25, 53127, Bonn, Germany.
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110
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Österlund T, Jonsson V, Kristiansson E. HirBin: high-resolution identification of differentially abundant functions in metagenomes. BMC Genomics 2017; 18:316. [PMID: 28431529 PMCID: PMC5399828 DOI: 10.1186/s12864-017-3686-6] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2016] [Accepted: 04/06/2017] [Indexed: 12/16/2022] Open
Abstract
Background Gene-centric analysis of metagenomics data provides information about the biochemical functions present in a microbiome under a certain condition. The ability to identify significant differences in functions between metagenomes is dependent on accurate classification and quantification of the sequence reads (binning). However, biological effects acting on specific functions may be overlooked if the classes are too general. Methods Here we introduce High-Resolution Binning (HirBin), a new method for gene-centric analysis of metagenomes. HirBin combines supervised annotation with unsupervised clustering to bin sequence reads at a higher resolution. The supervised annotation is performed by matching sequence fragments to genes using well-established protein domains, such as TIGRFAM, PFAM or COGs, followed by unsupervised clustering where each functional domain is further divided into sub-bins based on sequence similarity. Finally, differential abundance of the sub-bins is statistically assessed. Results We show that HirBin is able to identify biological effects that are only present at more specific functional levels. Furthermore we show that changes affecting more specific functional levels are often diluted at the more general level and therefore overlooked when analyzed using standard binning approaches. Conclusions HirBin improves the resolution of the gene-centric analysis of metagenomes and facilitates the biological interpretation of the results. HirBin is implemented as a Python package and is freely available for download at http://bioinformatics.math.chalmers.se/hirbin. Electronic supplementary material The online version of this article (doi:10.1186/s12864-017-3686-6) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Tobias Österlund
- Department of Mathematical Sciences, Chalmers University of Technology and University of Gothenburg, SE-41296, Gothenburg, Sweden.
| | - Viktor Jonsson
- Department of Mathematical Sciences, Chalmers University of Technology and University of Gothenburg, SE-41296, Gothenburg, Sweden
| | - Erik Kristiansson
- Department of Mathematical Sciences, Chalmers University of Technology and University of Gothenburg, SE-41296, Gothenburg, Sweden
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111
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Greenwald WW, Klitgord N, Seguritan V, Yooseph S, Venter JC, Garner C, Nelson KE, Li W. Utilization of defined microbial communities enables effective evaluation of meta-genomic assemblies. BMC Genomics 2017; 18:296. [PMID: 28407798 PMCID: PMC5390407 DOI: 10.1186/s12864-017-3679-5] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2016] [Accepted: 04/04/2017] [Indexed: 12/25/2022] Open
Abstract
BACKGROUND Metagenomics is the study of the microbial genomes isolated from communities found on our bodies or in our environment. By correctly determining the relation between human health and the human associated microbial communities, novel mechanisms of health and disease can be found, thus enabling the development of novel diagnostics and therapeutics. Due to the diversity of the microbial communities, strategies developed for aligning human genomes cannot be utilized, and genomes of the microbial species in the community must be assembled de novo. However, in order to obtain the best metagenomic assemblies, it is important to choose the proper assembler. Due to the rapidly evolving nature of metagenomics, new assemblers are constantly created, and the field has not yet agreed on a standardized process. Furthermore, the truth sets used to compare these methods are either too simple (computationally derived diverse communities) or complex (microbial communities of unknown composition), yielding results that are hard to interpret. In this analysis, we interrogate the strengths and weaknesses of five popular assemblers through the use of defined biological samples of known genomic composition and abundance. We assessed the performance of each assembler on their ability to reassemble genomes, call taxonomic abundances, and recreate open reading frames (ORFs). RESULTS We tested five metagenomic assemblers: Omega, metaSPAdes, IDBA-UD, metaVelvet and MEGAHIT on known and synthetic metagenomic data sets. MetaSPAdes excelled in diverse sets, IDBA-UD performed well all around, metaVelvet had high accuracy in high abundance organisms, and MEGAHIT was able to accurately differentiate similar organisms within a community. At the ORF level, metaSPAdes and MEGAHIT had the least number of missing ORFs within diverse and similar communities respectively. CONCLUSIONS Depending on the metagenomics question asked, the correct assembler for the task at hand will differ. It is important to choose the appropriate assembler, and thus clearly define the biological problem of an experiment, as different assemblers will give different answers to the same question.
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Affiliation(s)
- William W. Greenwald
- Bioinformatics and Systems Biology, University of California San Diego, La Jolla, CA USA
| | | | | | - Shibu Yooseph
- Department of Computer Science, University of Central Florida, Orlando, FL USA
| | - J. Craig Venter
- Human Longevity Inc, San Diego, CA USA
- J. Craig Venter Institute, La Jolla, CA USA
| | | | - Karen E. Nelson
- Human Longevity Inc, San Diego, CA USA
- J. Craig Venter Institute, La Jolla, CA USA
| | - Weizhong Li
- Human Longevity Inc, San Diego, CA USA
- J. Craig Venter Institute, La Jolla, CA USA
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112
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Knoll RL, Forslund K, Kultima JR, Meyer CU, Kullmer U, Sunagawa S, Bork P, Gehring S. Gut microbiota differs between children with Inflammatory Bowel Disease and healthy siblings in taxonomic and functional composition: a metagenomic analysis. Am J Physiol Gastrointest Liver Physiol 2017; 312:G327-G339. [PMID: 28039159 DOI: 10.1152/ajpgi.00293.2016] [Citation(s) in RCA: 55] [Impact Index Per Article: 7.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/12/2016] [Revised: 12/15/2016] [Accepted: 12/23/2016] [Indexed: 02/07/2023]
Abstract
Current treatment for pediatric inflammatory bowel disease (IBD) patients is often ineffective, with serious side effects. Manipulating the gut microbiota via fecal microbiota transplantation (FMT) is an emerging treatment approach but remains controversial. We aimed to assess the composition of the fecal microbiome through a comparison of pediatric IBD patients to their healthy siblings, evaluating risks and prospects for FMT in this setting. A case-control (sibling) study was conducted analyzing fecal samples of six children with Crohn's disease (CD), six children with ulcerative colitis (UC) and 12 healthy siblings by metagenomic sequencing. In addition, lifetime antibiotic intake was retrospectively determined. Species richness and diversity were significantly reduced in UC patients compared with control [Mann-Whitney U-test false discovery rate (MWU FDR) = 0.011]. In UC, bacteria positively influencing gut homeostasis, e.g., Eubacterium rectale and Faecalibacterium prausnitzii, were significantly reduced in abundance (MWU FDR = 0.05). Known pathobionts like Escherichia coli were enriched in UC patients (MWU FDR = 0.084). Moreover, E. coli abundance correlated positively with that of several virulence genes (SCC > 0.65, FDR < 0.1). A shift toward antibiotic-resistant taxa in both IBD groups distinguished them from controls [MWU Benjamini-Hochberg-Yekutieli procedure (BY) FDR = 0.062 in UC, MWU BY FDR = 0.019 in CD). The collected results confirm a microbial dysbiosis in pediatric UC, and to a lesser extent in CD patients, replicating associations found previously using different methods. Taken together, these observations suggest microbiotal remodeling therapy from family donors, at least for children with UC, as a viable option.NEW & NOTEWORTHY In this sibling study, prior reports of microbial dysbiosis in IBD patients from 16S rRNA sequencing was verified using deep shotgun sequencing and augmented with insights into the abundance of bacterial virulence genes and bacterial antibiotic resistance determinants, seen against the background of data on the specific antibiotic intake of each of the study participants. The observed dysbiosis, which distinguishes patients from siblings, highlights such siblings as potential donors for microbiotal remodeling therapy in IBD.
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Affiliation(s)
- Rebecca L Knoll
- Children's Hospital, University Medical Center, Johannes Gutenberg University, Mainz, Germany
| | - Kristoffer Forslund
- European Molecular Biology Laboratory, Structural and Computational Biology Unit, Heidelberg, Germany
| | - Jens Roat Kultima
- European Molecular Biology Laboratory, Structural and Computational Biology Unit, Heidelberg, Germany
| | - Claudius U Meyer
- Children's Hospital, University Medical Center, Johannes Gutenberg University, Mainz, Germany
| | - Ulrike Kullmer
- Children's Hospital, University Medical Center, Johannes Gutenberg University, Mainz, Germany
| | - Shinichi Sunagawa
- European Molecular Biology Laboratory, Structural and Computational Biology Unit, Heidelberg, Germany.,Institute of Microbiology, ETH Zurich, Zurich, Switzerland
| | - Peer Bork
- European Molecular Biology Laboratory, Structural and Computational Biology Unit, Heidelberg, Germany.,Molecular Medicine Partnership Unit, University of Heidelberg and European Molecular Biology Laboratory, Heidelberg, Germany.,Max Delbrück Centre for Molecular Medicine, Berlin, Germany; and.,Department of Bioinformatics, Biocenter, Würzburg, Germany
| | - Stephan Gehring
- Children's Hospital, University Medical Center, Johannes Gutenberg University, Mainz, Germany;
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114
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Noecker C, McNally CP, Eng A, Borenstein E. High-resolution characterization of the human microbiome. Transl Res 2017; 179:7-23. [PMID: 27513210 PMCID: PMC5164958 DOI: 10.1016/j.trsl.2016.07.012] [Citation(s) in RCA: 45] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/29/2016] [Revised: 07/12/2016] [Accepted: 07/15/2016] [Indexed: 12/29/2022]
Abstract
The human microbiome plays an important and increasingly recognized role in human health. Studies of the microbiome typically use targeted sequencing of the 16S rRNA gene, whole metagenome shotgun sequencing, or other meta-omic technologies to characterize the microbiome's composition, activity, and dynamics. Processing, analyzing, and interpreting these data involve numerous computational tools that aim to filter, cluster, annotate, and quantify the obtained data and ultimately provide an accurate and interpretable profile of the microbiome's taxonomy, functional capacity, and behavior. These tools, however, are often limited in resolution and accuracy and may fail to capture many biologically and clinically relevant microbiome features, such as strain-level variation or nuanced functional response to perturbation. Over the past few years, extensive efforts have been invested toward addressing these challenges and developing novel computational methods for accurate and high-resolution characterization of microbiome data. These methods aim to quantify strain-level composition and variation, detect and characterize rare microbiome species, link specific genes to individual taxa, and more accurately characterize the functional capacity and dynamics of the microbiome. These methods and the ability to produce detailed and precise microbiome information are clearly essential for informing microbiome-based personalized therapies. In this review, we survey these methods, highlighting the challenges each method sets out to address and briefly describing methodological approaches.
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Affiliation(s)
- Cecilia Noecker
- Department of Genome Sciences, University of Washington, Seattle, WA
| | - Colin P McNally
- Department of Genome Sciences, University of Washington, Seattle, WA
| | - Alexander Eng
- Department of Genome Sciences, University of Washington, Seattle, WA
| | - Elhanan Borenstein
- Department of Genome Sciences, University of Washington, Seattle, WA
- Department of Computer Science and Engineering, University of Washington, Seattle, WA
- Santa Fe Institute, Santa Fe, NM
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115
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Abstract
Modern life is associated with changes in gut microbial communities, believed to be involved in the emergence of non-communicable chronic diseases. While there is an increasing effort of the scientific community towards designing microbiota-targeting therapies aiming to restore the microbiota of diseased patients, there is a lack of approaches designed to prevent the disruption of the symbiosis between human and its microbial symbionts. We discuss in this review how new technologies, tools and models will contribute to identify diet-derived health-relevant microbial metabolites, possible targets for dietary recommendations tailored to individuals' physiology, diet, genetics, lifestyle and gut microbiota.
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Affiliation(s)
- Patrick Veiga
- Danone Nutricia Research, Avenue de la Vauve, 91120 Palaiseau, France
| | - Julien Tap
- Danone Nutricia Research, Avenue de la Vauve, 91120 Palaiseau, France
| | - Muriel Derrien
- Danone Nutricia Research, Avenue de la Vauve, 91120 Palaiseau, France
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116
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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.
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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
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Raguideau S, Plancade S, Pons N, Leclerc M, Laroche B. Inferring Aggregated Functional Traits from Metagenomic Data Using Constrained Non-negative Matrix Factorization: Application to Fiber Degradation in the Human Gut Microbiota. PLoS Comput Biol 2016; 12:e1005252. [PMID: 27984592 PMCID: PMC5161307 DOI: 10.1371/journal.pcbi.1005252] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2016] [Accepted: 11/17/2016] [Indexed: 12/16/2022] Open
Abstract
Whole Genome Shotgun (WGS) metagenomics is increasingly used to study the structure and functions of complex microbial ecosystems, both from the taxonomic and functional point of view. Gene inventories of otherwise uncultured microbial communities make the direct functional profiling of microbial communities possible. The concept of community aggregated trait has been adapted from environmental and plant functional ecology to the framework of microbial ecology. Community aggregated traits are quantified from WGS data by computing the abundance of relevant marker genes. They can be used to study key processes at the ecosystem level and correlate environmental factors and ecosystem functions. In this paper we propose a novel model based approach to infer combinations of aggregated traits characterizing specific ecosystemic metabolic processes. We formulate a model of these Combined Aggregated Functional Traits (CAFTs) accounting for a hierarchical structure of genes, which are associated on microbial genomes, further linked at the ecosystem level by complex co-occurrences or interactions. The model is completed with constraints specifically designed to exploit available genomic information, in order to favor biologically relevant CAFTs. The CAFTs structure, as well as their intensity in the ecosystem, is obtained by solving a constrained Non-negative Matrix Factorization (NMF) problem. We developed a multicriteria selection procedure for the number of CAFTs. We illustrated our method on the modelling of ecosystemic functional traits of fiber degradation by the human gut microbiota. We used 1408 samples of gene abundances from several high-throughput sequencing projects and found that four CAFTs only were needed to represent the fiber degradation potential. This data reduction highlighted biologically consistent functional patterns while providing a high quality preservation of the original data. Our method is generic and can be applied to other metabolic processes in the gut or in other ecosystems.
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Affiliation(s)
- Sébastien Raguideau
- Institut Micalis, INRA, AgroParisTech, Université Paris-Saclay, Jouy-en-Josas, France
- MaIAGE, INRA, Université Paris-Saclay, Jouy-en-Josas, France
| | - Sandra Plancade
- MaIAGE, INRA, Université Paris-Saclay, Jouy-en-Josas, France
| | - Nicolas Pons
- MGP, INRA, Université Paris-Saclay, Jouy-en-Josas, France
| | - Marion Leclerc
- Institut Micalis, INRA, AgroParisTech, Université Paris-Saclay, Jouy-en-Josas, France
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Nichols RG, Hume NE, Smith PB, Peters JM, Patterson AD. Omics Approaches To Probe Microbiota and Drug Metabolism Interactions. Chem Res Toxicol 2016; 29:1987-1997. [PMID: 27782392 DOI: 10.1021/acs.chemrestox.6b00236] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
The drug metabolism field has long recognized the beneficial and sometimes deleterious influence of microbiota in the absorption, distribution, metabolism, and excretion of drugs. Early pioneering work with the sulfanilamide precursor prontosil pointed toward the necessity not only to better understand the metabolic capabilities of the microbiota but also, importantly, to identify the specific microbiota involved in the generation and metabolism of drugs. However, technological limitations important for cataloging the microbiota community as well as for understanding and/or predicting their metabolic capabilities hindered progress. Current advances including mass spectrometry-based metabolite profiling as well as culture-independent sequence-based identification and functional analysis of microbiota have begun to shed light on microbial metabolism. In this review, case studies will be presented to highlight key aspects (e.g., microbiota identification, metabolic function and prediction, metabolite identification, and profiling) that have helped to clarify how the microbiota might impact or be impacted by drug metabolism. Lastly, a perspective of the future of this field is presented that takes into account what important knowledge is lacking and how to tackle these problems.
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Affiliation(s)
- Robert G Nichols
- Center for Molecular Toxicology and Carcinogenesis, Department of Veterinary and Biomedical Sciences, The Pennsylvania State University , University Park, Pennsylvania 16802, United States
| | - Nicole E Hume
- Center for Molecular Toxicology and Carcinogenesis, Department of Veterinary and Biomedical Sciences, The Pennsylvania State University , University Park, Pennsylvania 16802, United States
| | - Philip B Smith
- Center for Molecular Toxicology and Carcinogenesis, Department of Veterinary and Biomedical Sciences, The Pennsylvania State University , University Park, Pennsylvania 16802, United States
| | - Jeffrey M Peters
- Center for Molecular Toxicology and Carcinogenesis, Department of Veterinary and Biomedical Sciences, The Pennsylvania State University , University Park, Pennsylvania 16802, United States
| | - Andrew D Patterson
- Center for Molecular Toxicology and Carcinogenesis, Department of Veterinary and Biomedical Sciences, The Pennsylvania State University , University Park, Pennsylvania 16802, United States
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119
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DeCastro ME, Rodríguez-Belmonte E, González-Siso MI. Metagenomics of Thermophiles with a Focus on Discovery of Novel Thermozymes. Front Microbiol 2016; 7:1521. [PMID: 27729905 PMCID: PMC5037290 DOI: 10.3389/fmicb.2016.01521] [Citation(s) in RCA: 72] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2016] [Accepted: 09/12/2016] [Indexed: 11/24/2022] Open
Abstract
Microbial populations living in environments with temperatures above 50°C (thermophiles) have been widely studied, increasing our knowledge in the composition and function of these ecological communities. Since these populations express a broad number of heat-resistant enzymes (thermozymes), they also represent an important source for novel biocatalysts that can be potentially used in industrial processes. The integrated study of the whole-community DNA from an environment, known as metagenomics, coupled with the development of next generation sequencing (NGS) technologies, has allowed the generation of large amounts of data from thermophiles. In this review, we summarize the main approaches commonly utilized for assessing the taxonomic and functional diversity of thermophiles through metagenomics, including several bioinformatics tools and some metagenome-derived methods to isolate their thermozymes.
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Affiliation(s)
- María-Eugenia DeCastro
- Grupo EXPRELA, Centro de Investigacións Científicas Avanzadas (CICA), Departamento de Bioloxía Celular e Molecular, Facultade de Ciencias, Universidade da Coruña A Coruña, Spain
| | - Esther Rodríguez-Belmonte
- Grupo EXPRELA, Centro de Investigacións Científicas Avanzadas (CICA), Departamento de Bioloxía Celular e Molecular, Facultade de Ciencias, Universidade da Coruña A Coruña, Spain
| | - María-Isabel González-Siso
- Grupo EXPRELA, Centro de Investigacións Científicas Avanzadas (CICA), Departamento de Bioloxía Celular e Molecular, Facultade de Ciencias, Universidade da Coruña A Coruña, Spain
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