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Wang L, Lin D, Xiao KQ, Ma LJ, Fu YM, Huo YX, Liu Y, Ye M, Sun MM, Zhu D, Rillig MC, Zhu YG. Soil viral-host interactions regulate microplastic-dependent carbon storage. Proc Natl Acad Sci U S A 2024; 121:e2413245121. [PMID: 39467127 PMCID: PMC11551317 DOI: 10.1073/pnas.2413245121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2024] [Accepted: 09/13/2024] [Indexed: 10/30/2024] Open
Abstract
Microplastic is globally regarded as an important factor impacting biogeochemical cycles, yet our understanding of such influences is limited by the uncertainties of intricate microbial processes. By multiomics analysis, coupled with soil chemodiversity characterization and microbial carbon use efficiency (CUE), we investigated how microbial responses to microplastics impacted soil carbon cycling in a long-term field experiment. We showed that biodegradable microplastics promoted soil organic carbon accrual by an average of 2.47%, while nondegradable microplastics inhibited it by 17.4%, as a consequence of the virus-bacteria coadaptations to the microplastics disturbance. In the relevant functional pathways, nondegradable microplastics significantly (P < 0.05) enhanced the abundance and transcriptional activity related to complex carbohydrate metabolism, whereas biodegradable microplastics significantly (P < 0.05) promoted functions involved in amino acid metabolism and glycolysis. Accordingly, viral lysis enhanced in nondegradable microplastics treatments to introduce more complex organic compounds to soil dissolved organic matters, thus benefiting the oligotrophs with high carbon metabolic capabilities in exploitation competition. In contrast, biodegradable microplastics enriched viral auxiliary metabolic genes of carbon metabolism through "piggyback-the-winner" strategy, conferring to dominant copiotrophs, enhanced substrate utilization capabilities. These virus-host interactions were also demonstrated in the corresponding soil plastisphere, which would alter microbial resource allocation and metabolism via CUE, affecting carbon storage consequently. Overall, our results underscore the importance of viral-host interactions in understanding the microplastics-dependent carbon storage in the soil ecosystem.
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Affiliation(s)
- Lu Wang
- Key Laboratory of Urban Environment and Health, Ningbo Urban Environment Observation and Research Station, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen361021, China
- Zhejiang Key Laboratory of Urban Environmental Processes and Pollution Control, Chinese Academy of Sciences Haixi Industrial Technology Innovation Center in Beilun, Ningbo315830, China
| | - Da Lin
- Key Laboratory of Urban Environment and Health, Ningbo Urban Environment Observation and Research Station, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen361021, China
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing100049, China
| | - Ke-Qing Xiao
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing100049, China
- State Key Laboratory of Urban and Regional Ecology, Research Centre for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing100085, China
| | - Li-Juan Ma
- Key Laboratory of Urban Environment and Health, Ningbo Urban Environment Observation and Research Station, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen361021, China
- School of Life Sciences, Hebei University, Baoding071002, China
| | - Yan-Mei Fu
- Key Laboratory of Wetland Ecology and Environment, State Key Laboratory of Black Soils Conservation and Utilization, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun130102, China
| | - Yu-Xin Huo
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing100049, China
- State Key Laboratory of Urban and Regional Ecology, Research Centre for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing100085, China
| | - Yanjie Liu
- Key Laboratory of Wetland Ecology and Environment, State Key Laboratory of Black Soils Conservation and Utilization, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun130102, China
| | - Mao Ye
- National Engineering Research Center for Soil Nutrient Management and Pollution Remediation, Institute of Soil Science, Chinese Academy of Sciences, Nanjing210008, China
| | - Ming-Ming Sun
- Soil Ecology Lab, Nanjing Agricultural University, Nanjing210095, China
| | - Dong Zhu
- Key Laboratory of Urban Environment and Health, Ningbo Urban Environment Observation and Research Station, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen361021, China
- Zhejiang Key Laboratory of Urban Environmental Processes and Pollution Control, Chinese Academy of Sciences Haixi Industrial Technology Innovation Center in Beilun, Ningbo315830, China
| | - Matthias C. Rillig
- Institute of Biology, Freie Universität Berlin, Berlin14195, Germany
- Berlin-Brandenburg Institute of Advanced Biodiversity Research, Berlin14195, Germany
| | - Yong-Guan Zhu
- Key Laboratory of Urban Environment and Health, Ningbo Urban Environment Observation and Research Station, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen361021, China
- Zhejiang Key Laboratory of Urban Environmental Processes and Pollution Control, Chinese Academy of Sciences Haixi Industrial Technology Innovation Center in Beilun, Ningbo315830, China
- State Key Laboratory of Urban and Regional Ecology, Research Centre for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing100085, China
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Kosmopoulos JC, Klier KM, Langwig MV, Tran PQ, Anantharaman K. Viromes vs. mixed community metagenomes: choice of method dictates interpretation of viral community ecology. MICROBIOME 2024; 12:195. [PMID: 39375774 PMCID: PMC11460016 DOI: 10.1186/s40168-024-01905-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/13/2023] [Accepted: 08/12/2024] [Indexed: 10/09/2024]
Abstract
BACKGROUND Viruses, the majority of which are uncultivated, are among the most abundant biological entities on Earth. From altering microbial physiology to driving community dynamics, viruses are fundamental members of microbiomes. While the number of studies leveraging viral metagenomics (viromics) for studying uncultivated viruses is growing, standards for viromics research are lacking. Viromics can utilize computational discovery of viruses from total metagenomes of all community members (hereafter metagenomes) or use physical separation of virus-specific fractions (hereafter viromes). However, differences in the recovery and interpretation of viruses from metagenomes and viromes obtained from the same samples remain understudied. RESULTS Here, we compare viral communities from paired viromes and metagenomes obtained from 60 diverse samples across human gut, soil, freshwater, and marine ecosystems. Overall, viral communities obtained from viromes had greater species richness and total viral genome abundances than those obtained from metagenomes, although there were some exceptions. Despite this, metagenomes still contained many viral genomes not detected in viromes. We also found notable differences in the predicted lytic state of viruses detected in viromes vs metagenomes at the time of sequencing. Other forms of variation observed include genome presence/absence, genome quality, and encoded protein content between viromes and metagenomes, but the magnitude of these differences varied by environment. CONCLUSIONS Overall, our results show that the choice of method can lead to differing interpretations of viral community ecology. We suggest that the choice of whether to target a metagenome or virome to study viral communities should be dependent on the environmental context and ecological questions being asked. However, our overall recommendation to researchers investigating viral ecology and evolution is to pair both approaches to maximize their respective benefits. Video Abstract.
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Affiliation(s)
- James C Kosmopoulos
- Department of Bacteriology, University of Wisconsin-Madison, Madison, WI, USA
- Microbiology Doctoral Training Program, University of Wisconsin-Madison, Madison, WI, USA
| | - Katherine M Klier
- Department of Bacteriology, University of Wisconsin-Madison, Madison, WI, USA
- Freshwater and Marine Sciences Program, University of Wisconsin-Madison, Madison, WI, USA
| | - Marguerite V Langwig
- Department of Bacteriology, University of Wisconsin-Madison, Madison, WI, USA
- Freshwater and Marine Sciences Program, University of Wisconsin-Madison, Madison, WI, USA
| | - Patricia Q Tran
- Department of Bacteriology, University of Wisconsin-Madison, Madison, WI, USA
| | - Karthik Anantharaman
- Department of Bacteriology, University of Wisconsin-Madison, Madison, WI, USA.
- Department of Integrative Biology, University of Wisconsin-Madison, Madison, WI, USA.
- Department of Data Science and AI, Wadhwani School of Data Science and AI, Indian Institute of Technology Madras, Chennai, India.
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3
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Zuppi M, Vatanen T, Wilson BC, Golovina E, Portlock T, Cutfield WS, Vickers MH, O'Sullivan JM. Fecal microbiota transplantation alters gut phage communities in a clinical trial for obesity. MICROBIOME 2024; 12:122. [PMID: 38970126 PMCID: PMC11227244 DOI: 10.1186/s40168-024-01833-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/21/2024] [Accepted: 05/08/2024] [Indexed: 07/07/2024]
Abstract
BACKGROUND Fecal microbiota transplantation (FMT) is a therapeutic intervention used to treat diseases associated with the gut microbiome. In the human gut microbiome, phages have been implicated in influencing human health, with successful engraftment of donor phages correlated with FMT treatment efficacy. The impact that gastrointestinal phages exert on human health has primarily been connected to their ability to modulate the bacterial communities in the gut. Nonetheless, how FMT affects recipients' phage populations, and in turn, how this influences the gut environment, is not yet fully understood. In this study, we investigated the effects of FMT on the phageome composition of participants within the Gut Bugs Trial (GBT), a double-blind, randomized, placebo-controlled trial that investigated the efficacy of FMT in treating obesity and comorbidities in adolescents. Stool samples collected from donors at the time of treatment and recipients at four time points (i.e., baseline and 6 weeks, 12 weeks, and 26 weeks post-intervention), underwent shotgun metagenomic sequencing. Phage sequences were identified and characterized in silico to examine evidence of phage engraftment and to assess the extent of FMT-induced alterations in the recipients' phageome composition. RESULTS Donor phages engrafted stably in recipients following FMT, composing a significant proportion of their phageome for the entire course of the study (33.8 ± 1.2% in females and 33.9 ± 3.7% in males). Phage engraftment varied between donors and donor engraftment efficacy was positively correlated with their phageome alpha diversity. FMT caused a shift in recipients' phageome toward the donors' composition and increased phageome alpha diversity and variability over time. CONCLUSIONS FMT significantly altered recipients' phage and, overall, microbial populations. The increase in microbial diversity and variability is consistent with a shift in microbial population dynamics. This proposes that phages play a critical role in modulating the gut environment and suggests novel approaches to understanding the efficacy of FMT in altering the recipient's microbiome. TRIAL REGISTRATION The Gut Bugs Trial was registered with the Australian New Zealand Clinical Trials Registry (ACTR N12615001351505). Trial protocol: the trial protocol is available at https://bmjopen.bmj.com/content/9/4/e026174 . Video Abstract.
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Affiliation(s)
- Michele Zuppi
- Liggins Institute, The University of Auckland, Auckland, New Zealand
| | - Tommi Vatanen
- Liggins Institute, The University of Auckland, Auckland, New Zealand.
- Institute of Biotechnology, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland.
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland.
- Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| | - Brooke C Wilson
- Liggins Institute, The University of Auckland, Auckland, New Zealand
| | - Evgeniia Golovina
- Liggins Institute, The University of Auckland, Auckland, New Zealand
| | - Theo Portlock
- Liggins Institute, The University of Auckland, Auckland, New Zealand
| | - Wayne S Cutfield
- Liggins Institute, The University of Auckland, Auckland, New Zealand
- A Better Start - National Science Challenge, University of Auckland, Auckland, New Zealand
| | - Mark H Vickers
- Liggins Institute, The University of Auckland, Auckland, New Zealand
- A Better Start - National Science Challenge, University of Auckland, Auckland, New Zealand
- The Maurice Wilkins Centre, The University of Auckland, Auckland, New Zealand
| | - Justin M O'Sullivan
- Liggins Institute, The University of Auckland, Auckland, New Zealand.
- The Maurice Wilkins Centre, The University of Auckland, Auckland, New Zealand.
- MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton, UK.
- Australian Parkinson's Mission, Garvan Institute of Medical Research, Sydney, NSW, Australia.
- A*STAR Singapore Institute for Clinical Sciences, Singapore, Singapore.
- Garvan Institute of Medical Research, Sydney, NSW, Australia.
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4
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Yang Y, Dufault-Thompson K, Yan W, Cai T, Xie L, Jiang X. Large-scale genomic survey with deep learning-based method reveals strain-level phage specificity determinants. Gigascience 2024; 13:giae017. [PMID: 38649301 PMCID: PMC11034027 DOI: 10.1093/gigascience/giae017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2023] [Revised: 01/23/2024] [Accepted: 03/24/2024] [Indexed: 04/25/2024] Open
Abstract
BACKGROUND Phage therapy, reemerging as a promising approach to counter antimicrobial-resistant infections, relies on a comprehensive understanding of the specificity of individual phages. Yet the significant diversity within phage populations presents a considerable challenge. Currently, there is a notable lack of tools designed for large-scale characterization of phage receptor-binding proteins, which are crucial in determining the phage host range. RESULTS In this study, we present SpikeHunter, a deep learning method based on the ESM-2 protein language model. With SpikeHunter, we identified 231,965 diverse phage-encoded tailspike proteins, a crucial determinant of phage specificity that targets bacterial polysaccharide receptors, across 787,566 bacterial genomes from 5 virulent, antibiotic-resistant pathogens. Notably, 86.60% (143,200) of these proteins exhibited strong associations with specific bacterial polysaccharides. We discovered that phages with identical tailspike proteins can infect different bacterial species with similar polysaccharide receptors, underscoring the pivotal role of tailspike proteins in determining host range. The specificity is mainly attributed to the protein's C-terminal domain, which strictly correlates with host specificity during domain swapping in tailspike proteins. Importantly, our dataset-driven predictions of phage-host specificity closely match the phage-host pairs observed in real-world phage therapy cases we studied. CONCLUSIONS Our research provides a rich resource, including both the method and a database derived from a large-scale genomics survey. This substantially enhances understanding of phage specificity determinants at the strain level and offers a valuable framework for guiding phage selection in therapeutic applications.
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Affiliation(s)
- Yiyan Yang
- National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA
| | | | - Wei Yan
- National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA
| | - Tian Cai
- Ph.D. Program in Computer Science, The Graduate Center, The City University of New York, New York, NY 10016, USA
| | - Lei Xie
- Ph.D. Program in Computer Science, The Graduate Center, The City University of New York, New York, NY 10016, USA
- Department of Computer Science, Hunter College, The City University of New York, New York, NY 10065, USA
| | - Xiaofang Jiang
- National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA
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5
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Kosmopoulos JC, Klier KM, Langwig MV, Tran PQ, Anantharaman K. Viromes vs. mixed community metagenomes: choice of method dictates interpretation of viral community ecology. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.15.562385. [PMID: 37904928 PMCID: PMC10614762 DOI: 10.1101/2023.10.15.562385] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/01/2023]
Abstract
Background Viruses, the majority of which are uncultivated, are among the most abundant biological entities on Earth. From altering microbial physiology to driving community dynamics, viruses are fundamental members of microbiomes. While the number of studies leveraging viral metagenomics (viromics) for studying uncultivated viruses is growing, standards for viromics research are lacking. Viromics can utilize computational discovery of viruses from total metagenomes of all community members (hereafter metagenomes) or use physical separation of virus-specific fractions (hereafter viromes). However, differences in the recovery and interpretation of viruses from metagenomes and viromes obtained from the same samples remain understudied. Results Here, we compare viral communities from paired viromes and metagenomes obtained from 60 diverse samples across human gut, soil, freshwater, and marine ecosystems. Overall, viral communities obtained from viromes were more abundant and species rich than those obtained from metagenomes, although there were some exceptions. Despite this, metagenomes still contained many viral genomes not detected in viromes. We also found notable differences in the predicted lytic state of viruses detected in viromes vs metagenomes at the time of sequencing. Other forms of variation observed include genome presence/absence, genome quality, and encoded protein content between viromes and metagenomes, but the magnitude of these differences varied by environment. Conclusions Overall, our results show that the choice of method can lead to differing interpretations of viral community ecology. We suggest that the choice of whether to target a metagenome or virome to study viral communities should be dependent on the environmental context and ecological questions being asked. However, our overall recommendation to researchers investigating viral ecology and evolution is to pair both approaches to maximize their respective benefits.
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Affiliation(s)
- James C. Kosmopoulos
- Department of Bacteriology, University of Wisconsin-Madison, Madison, Wisconsin, USA
- Microbiology Doctoral Training Program, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Katherine M. Klier
- Department of Bacteriology, University of Wisconsin-Madison, Madison, Wisconsin, USA
- Freshwater and Marine Sciences Program, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Marguerite V. Langwig
- Department of Bacteriology, University of Wisconsin-Madison, Madison, Wisconsin, USA
- Freshwater and Marine Sciences Program, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Patricia Q. Tran
- Department of Bacteriology, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Karthik Anantharaman
- Department of Bacteriology, University of Wisconsin-Madison, Madison, Wisconsin, USA
- Department of Integrative Biology, University of Wisconsin-Madison, Madison, Wisconsin, USA
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6
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Rangel-Pineros G, Almeida A, Beracochea M, Sakharova E, Marz M, Reyes Muñoz A, Hölzer M, Finn RD. VIRify: An integrated detection, annotation and taxonomic classification pipeline using virus-specific protein profile hidden Markov models. PLoS Comput Biol 2023; 19:e1011422. [PMID: 37639475 PMCID: PMC10491390 DOI: 10.1371/journal.pcbi.1011422] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Revised: 09/08/2023] [Accepted: 08/09/2023] [Indexed: 08/31/2023] Open
Abstract
The study of viral communities has revealed the enormous diversity and impact these biological entities have on various ecosystems. These observations have sparked widespread interest in developing computational strategies that support the comprehensive characterisation of viral communities based on sequencing data. Here we introduce VIRify, a new computational pipeline designed to provide a user-friendly and accurate functional and taxonomic characterisation of viral communities. VIRify identifies viral contigs and prophages from metagenomic assemblies and annotates them using a collection of viral profile hidden Markov models (HMMs). These include our manually-curated profile HMMs, which serve as specific taxonomic markers for a wide range of prokaryotic and eukaryotic viral taxa and are thus used to reliably classify viral contigs. We tested VIRify on assemblies from two microbial mock communities, a large metagenomics study, and a collection of publicly available viral genomic sequences from the human gut. The results showed that VIRify could identify sequences from both prokaryotic and eukaryotic viruses, and provided taxonomic classifications from the genus to the family rank with an average accuracy of 86.6%. In addition, VIRify allowed the detection and taxonomic classification of a range of prokaryotic and eukaryotic viruses present in 243 marine metagenomic assemblies. Finally, the use of VIRify led to a large expansion in the number of taxonomically classified human gut viral sequences and the improvement of outdated and shallow taxonomic classifications. Overall, we demonstrate that VIRify is a novel and powerful resource that offers an enhanced capability to detect a broad range of viral contigs and taxonomically classify them.
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Affiliation(s)
- Guillermo Rangel-Pineros
- The Globe Institute, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Max Planck Tandem Group in Computational Biology, Department of Biological Sciences, Universidad de los Andes, Bogota, Colombia
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, United Kingdom
| | - Alexandre Almeida
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, United Kingdom
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, United Kingdom
- Department of Veterinary Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Martin Beracochea
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, United Kingdom
| | - Ekaterina Sakharova
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, United Kingdom
| | - Manja Marz
- RNA Bioinformatics, Friedrich Schiller University, Jena, Germany
- European Virus Bioinformatics Center, Friedrich Schiller University, Jena, Germany
| | - Alejandro Reyes Muñoz
- Max Planck Tandem Group in Computational Biology, Department of Biological Sciences, Universidad de los Andes, Bogota, Colombia
| | - Martin Hölzer
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, United Kingdom
- European Virus Bioinformatics Center, Friedrich Schiller University, Jena, Germany
- Methodology and Research Infrastructure, Genome Competence Center (MF1), Robert Koch Institute, Berlin, Germany
| | - Robert D. Finn
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, United Kingdom
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Venturini C, Petrovic Fabijan A, Fajardo Lubian A, Barbirz S, Iredell J. Biological foundations of successful bacteriophage therapy. EMBO Mol Med 2022; 14:e12435. [PMID: 35620963 PMCID: PMC9260219 DOI: 10.15252/emmm.202012435] [Citation(s) in RCA: 26] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2022] [Revised: 04/13/2022] [Accepted: 04/19/2022] [Indexed: 12/20/2022] Open
Abstract
Bacteriophages (phages) are selective viral predators of bacteria. Abundant and ubiquitous in nature, phages can be used to treat bacterial infections (phage therapy), including refractory infections and those resistant to antibiotics. However, despite an abundance of anecdotal evidence of efficacy, significant hurdles remain before routine implementation of phage therapy into medical practice, including a dearth of robust clinical trial data. Phage-bacterium interactions are complex and diverse, characterized by co-evolution trajectories that are significantly influenced by the environments in which they occur (mammalian body sites, water, soil, etc.). An understanding of the molecular mechanisms underpinning these dynamics is essential for successful clinical translation. This review aims to cover key aspects of bacterium-phage interactions that affect bacterial killing by describing the most relevant published literature and detailing the current knowledge gaps most likely to influence therapeutic success.
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Affiliation(s)
- Carola Venturini
- Centre for Infectious Diseases and MicrobiologyWestmead Institute for Medical ResearchWestmeadNSWAustralia
- Faculty of ScienceSydney School of Veterinary ScienceThe University of SydneySydneyNSWAustralia
| | - Aleksandra Petrovic Fabijan
- Centre for Infectious Diseases and MicrobiologyWestmead Institute for Medical ResearchWestmeadNSWAustralia
- Faculty of Health and MedicineSchool of MedicineSydney Medical SchoolThe University of SydneySydneyNSWAustralia
| | - Alicia Fajardo Lubian
- Centre for Infectious Diseases and MicrobiologyWestmead Institute for Medical ResearchWestmeadNSWAustralia
- Faculty of Health and MedicineSchool of MedicineSydney Medical SchoolThe University of SydneySydneyNSWAustralia
| | - Stefanie Barbirz
- Department of MedicineScience FacultyMSB Medical School BerlinBerlinGermany
| | - Jonathan Iredell
- Centre for Infectious Diseases and MicrobiologyWestmead Institute for Medical ResearchWestmeadNSWAustralia
- Faculty of Health and MedicineSchool of MedicineSydney Medical SchoolThe University of SydneySydneyNSWAustralia
- Westmead HospitalWestern Sydney Local Health DistrictWestmeadNSWAustralia
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8
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Andrade-Martínez JS, Camelo Valera LC, Chica Cárdenas LA, Forero-Junco L, López-Leal G, Moreno-Gallego JL, Rangel-Pineros G, Reyes A. Computational Tools for the Analysis of Uncultivated Phage Genomes. Microbiol Mol Biol Rev 2022; 86:e0000421. [PMID: 35311574 PMCID: PMC9199400 DOI: 10.1128/mmbr.00004-21] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
Over a century of bacteriophage research has uncovered a plethora of fundamental aspects of their biology, ecology, and evolution. Furthermore, the introduction of community-level studies through metagenomics has revealed unprecedented insights on the impact that phages have on a range of ecological and physiological processes. It was not until the introduction of viral metagenomics that we began to grasp the astonishing breadth of genetic diversity encompassed by phage genomes. Novel phage genomes have been reported from a diverse range of biomes at an increasing rate, which has prompted the development of computational tools that support the multilevel characterization of these novel phages based solely on their genome sequences. The impact of these technologies has been so large that, together with MAGs (Metagenomic Assembled Genomes), we now have UViGs (Uncultivated Viral Genomes), which are now officially recognized by the International Committee for the Taxonomy of Viruses (ICTV), and new taxonomic groups can now be created based exclusively on genomic sequence information. Even though the available tools have immensely contributed to our knowledge of phage diversity and ecology, the ongoing surge in software programs makes it challenging to keep up with them and the purpose each one is designed for. Therefore, in this review, we describe a comprehensive set of currently available computational tools designed for the characterization of phage genome sequences, focusing on five specific analyses: (i) assembly and identification of phage and prophage sequences, (ii) phage genome annotation, (iii) phage taxonomic classification, (iv) phage-host interaction analysis, and (v) phage microdiversity.
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Affiliation(s)
- Juan Sebastián Andrade-Martínez
- Max Planck Tandem Group in Computational Biology, Department of Biological Sciences, Universidad de los Andes, Bogotá, Colombia
| | - Laura Carolina Camelo Valera
- Max Planck Tandem Group in Computational Biology, Department of Biological Sciences, Universidad de los Andes, Bogotá, Colombia
| | - Luis Alberto Chica Cárdenas
- Max Planck Tandem Group in Computational Biology, Department of Biological Sciences, Universidad de los Andes, Bogotá, Colombia
| | - Laura Forero-Junco
- Max Planck Tandem Group in Computational Biology, Department of Biological Sciences, Universidad de los Andes, Bogotá, Colombia
- Department of Plant and Environmental Science, University of Copenhagen, Frederiksberg, Denmark
| | - Gamaliel López-Leal
- Max Planck Tandem Group in Computational Biology, Department of Biological Sciences, Universidad de los Andes, Bogotá, Colombia
| | - J. Leonardo Moreno-Gallego
- Max Planck Tandem Group in Computational Biology, Department of Biological Sciences, Universidad de los Andes, Bogotá, Colombia
- Department of Microbiome Science, Max Planck Institute for Developmental Biology, Tübingen, Germany
| | - Guillermo Rangel-Pineros
- Max Planck Tandem Group in Computational Biology, Department of Biological Sciences, Universidad de los Andes, Bogotá, Colombia
- The GLOBE Institute, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Alejandro Reyes
- Max Planck Tandem Group in Computational Biology, Department of Biological Sciences, Universidad de los Andes, Bogotá, Colombia
- The Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, Missouri, USA
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9
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Dutilh BE, Varsani A, Tong Y, Simmonds P, Sabanadzovic S, Rubino L, Roux S, Muñoz AR, Lood C, Lefkowitz EJ, Kuhn JH, Krupovic M, Edwards RA, Brister JR, Adriaenssens EM, Sullivan MB. Perspective on taxonomic classification of uncultivated viruses. Curr Opin Virol 2021; 51:207-215. [PMID: 34781105 DOI: 10.1016/j.coviro.2021.10.011] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2021] [Revised: 10/26/2021] [Accepted: 10/27/2021] [Indexed: 12/19/2022]
Abstract
Historically, virus taxonomy has been limited to describing viruses that were readily cultivated in the laboratory or emerging in natural biomes. Metagenomic analyses, single-particle sequencing, and database mining efforts have yielded new sequence data on an astounding number of previously unknown viruses. As metagenomes are relatively free of biases, these data provide an unprecedented insight into the vastness of the virosphere, but to properly value the extent of this diversity it is critical that the viruses are taxonomically classified. Inclusion of uncultivated viruses has already improved the process as well as the understanding of the taxa, viruses, and their evolutionary relationships. The continuous development and testing of computational tools will be required to maintain a dynamic virus taxonomy that can accommodate the new discoveries.
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Affiliation(s)
- Bas E Dutilh
- Theoretical Biology and Bioinformatics, Science for Life, Utrecht University, Padualaan 8, 3584 CH, Utrecht, The Netherlands; Institute of Bioloversity, Faculty of Biological Sciences, Cluster of Excellence Balance of the Microverse, Friedrich-Schiller-University Jena, 07743, Jena, Germany.
| | - Arvind Varsani
- The Biodesign Center of Fundamental and Applied Microbiomics, School of Life Sciences, Center for Evolution and Medicine, Arizona State University, Tempe, AZ 85287, USA; Structural Biology Research Unit, Department of Integrative Biomedical Sciences, University of Cape Town, 7925, Cape Town, South Africa
| | - Yigang Tong
- Beijing Advanced Innovation Centre for Soft Matter Science and Engineering, College of Life Science and Technology, Beijing University of Chemical Technology, Beijing, 100029, China
| | - Peter Simmonds
- Nuffield Department of Medicine, University of Oxford, Peter Medawar Building, South Parks Road, Oxford, OX1 3SY, UK
| | - Sead Sabanadzovic
- Department of Biochemistry, Molecular Biology, Entomology and Plant Pathology, Mississippi State University, MS 39762, USA
| | - Luisa Rubino
- Istituto per la Protezione Sostenibile delle Piante, Consiglio Nazionale delle Ricerche, Bari, Italy
| | - Simon Roux
- DOE Joint Genome Institute, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Alejandro Reyes Muñoz
- Max Planck Tandem Group in Computational Biology, Department of Biological Sciences, Universidad de los Andes, Bogotá, Colombia
| | - Cédric Lood
- Department of Microbial and Molecular Systems, KU Leuven, Kasteelpark Arenberg 23, 3001, Leuven, Belgium; Department of Biosystems, KU Leuven, Willem de Croylaan 42, 3001, Leuven, Belgium
| | - Elliot J Lefkowitz
- Department of Microbiology, University of Alabama at Birmingham, Birmingham, AL 35294, USA
| | - Jens H Kuhn
- Integrated Research Facility at Fort Detrick, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Fort Detrick, Frederick, MD 21702, USA
| | - Mart Krupovic
- Institut Pasteur, Université de Paris, Archaeal Virology Unit, F-75015, Paris, France
| | - Robert A Edwards
- College of Science and Engineering, Flinders University, Bedford Park, SA 5042, Australia
| | - J Rodney Brister
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda MD 20894, USA
| | | | - Matthew B Sullivan
- Departments of Microbiology and Civil, Environmental, and Geodetic Engineering, Ohio State University, Columbus, OH, USA
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