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Ma K, Thairu MW, Sankaran K. MolPad: An R-Shiny Package for Cluster Co-Expression Analysis in Longitudinal Microbiomics. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.29.569321. [PMID: 38077024 PMCID: PMC10705384 DOI: 10.1101/2023.11.29.569321] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/19/2024]
Abstract
The R-Shiny package MolPad provides an interactive dashboard for understanding the dynamics of longitudinal molecular co-expression in microbiomics. The main idea for addressing the issue is first to use a network to overview major patterns among their predictive relationships and then zoom into specific clusters of interest. It is designed with a focus-plus-context analysis strategy and automatically generates links to online curated annotations. The dashboard consists of a cluster-level network, a bar plot of taxonomic composition, a line plot of data modalities, and a table for each pathway. Further, the package includes functions that handle the data processing for creating the dashboard. This makes it beginner-friendly for users with less R programming experience. We illustrate these methods with a case study on a longitudinal metagenomics analysis of the cheese microbiome.
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2
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Zhu G, Chao H, Sun M, Jiang Y, Ye M. Toxicity sharing model of earthworm intestinal microbiome reveals shared functional genes are more powerful than species in resisting pesticide stress. JOURNAL OF HAZARDOUS MATERIALS 2023; 446:130646. [PMID: 36587599 DOI: 10.1016/j.jhazmat.2022.130646] [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: 10/07/2022] [Revised: 12/06/2022] [Accepted: 12/19/2022] [Indexed: 06/17/2023]
Abstract
Earthworm intestinal bacteria and indigenous soil bacteria work closely during various biochemical processes and play a crucial role in maintaining the internal stability of the soil environment. However, the response mechanism of these bacterial communities to external pesticide disturbance is unknown. In this study, soil and earthworm gut contents were metagenomically sequenced after exposure to various concentrations of nitrochlorobenzene (0-1026.7 mg kg-1). A high degree of similarity was found between the microbial community composition and abundance in the worm gut and soil, both of which decreased significantly (P < 0.05) under elevated pesticide stress. The toxicity sharing model (TSM) showed that the toxicity sharing capacity was 97.4-125.7 % and 100.4-130.2 % for Egenes (genes in the worm gut) and Emet(degradation genes in the worm gut) in the earthworm intestinal microbiome, respectively. This indicated that the earthworm intestinal microbiome assisted in relieving the pesticide toxicity of the indigenous soil microbiome. This study showed that the TSM could quantitatively describe the toxic effect of pesticides on the earthworm intestinal microbiome. It provides a new analytical model for investigating the ecological alliance between earthworm intestinal microbiome and indigenous soil microbiome under pesticide stress while contributing a more profound understanding of the potential to use earthworms to mitigate pesticide pollution in soils and develop earthworm-based soil remediation techniques.
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Affiliation(s)
- Guofan Zhu
- National Engineering Laboratort of Soil Nutrients Management, Pollution Control and Remediation Technoligies, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China
| | - Huizhen Chao
- Soil Ecology Lab, College of Resources and Environmental Sciences, Nanjing Agricultural University, Nanjing 210095, China
| | - Mingming Sun
- Soil Ecology Lab, College of Resources and Environmental Sciences, Nanjing Agricultural University, Nanjing 210095, China
| | - Yuji Jiang
- State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, 210008 Nanjing, China
| | - Mao Ye
- National Engineering Laboratort of Soil Nutrients Management, Pollution Control and Remediation Technoligies, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China.
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3
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Pilosof S. Conceptualizing microbe-plasmid communities as complex adaptive systems. Trends Microbiol 2023:S0966-842X(23)00025-2. [PMID: 36822952 DOI: 10.1016/j.tim.2023.01.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Revised: 12/29/2022] [Accepted: 01/23/2023] [Indexed: 02/24/2023]
Abstract
Plasmids shape microbial communities' diversity, structure, and function. Nevertheless, we lack a mechanistic understanding of how community structure and dynamics emerge from local microbe-plasmid interactions and coevolution. Addressing this gap is challenging because multiple processes operate simultaneously at multiple levels of organization. For example, immunity operates between a plasmid and a cell, but incompatibility mechanisms regulate coexistence between plasmids. Conceptualizing microbe-plasmid communities as complex adaptive systems is a promising approach to overcoming these challenges. I illustrate how agent-based evolutionary modeling, extended by network analysis, can be used to quantify the relative importance of local processes governing community dynamics. These theoretical developments can advance our understanding of plasmid ecology and evolution, especially when combined with empirical data.
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Affiliation(s)
- Shai Pilosof
- Department of Life Sciences, Ben-Gurion University of the Negev, Be'er-Sheva, Israel.
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4
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Borges DGF, Carvalho DS, Bomfim GC, Ramos PIP, Brzozowski J, Góes-Neto A, F. S. Andrade R, El-Hani C. On the origin of mitochondria: a multilayer network approach. PeerJ 2023; 11:e14571. [PMID: 36632145 PMCID: PMC9828282 DOI: 10.7717/peerj.14571] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Accepted: 11/28/2022] [Indexed: 01/08/2023] Open
Abstract
Backgound The endosymbiotic theory is widely accepted to explain the origin of mitochondria from a bacterial ancestor. While ample evidence supports the intimate connection of Alphaproteobacteria to the mitochondrial ancestor, pinpointing its closest relative within sampled Alphaproteobacteria is still an open evolutionary debate. Many different phylogenetic methods and approaches have been used to answer this challenging question, further compounded by the heterogeneity of sampled taxa, varying evolutionary rates of mitochondrial proteins, and the inherent biases in each method, all factors that can produce phylogenetic artifacts. By harnessing the simplicity and interpretability of protein similarity networks, herein we re-evaluated the origin of mitochondria within an enhanced multilayer framework, which is an extension and improvement of a previously developed method. Methods We used a dataset of eight proteins found in mitochondria (N = 6 organisms) and bacteria (N = 80 organisms). The sequences were aligned and resulting identity matrices were combined to generate an eight-layer multiplex network. Each layer corresponded to a protein network, where nodes represented organisms and edges were placed following mutual sequence identity. The Multi-Newman-Girvan algorithm was applied to evaluate community structure, and bifurcation events linked to network partition allowed to trace patterns of divergence between studied taxa. Results In our network-based analysis, we first examined the topology of the 8-layer multiplex when mitochondrial sequences disconnected from the main alphaproteobacterial cluster. The resulting topology lent firm support toward an Alphaproteobacteria-sister placement for mitochondria, reinforcing the hypothesis that mitochondria diverged from the common ancestor of all Alphaproteobacteria. Additionally, we observed that the divergence of Rickettsiales was an early event in the evolutionary history of alphaproteobacterial clades. Conclusion By leveraging complex networks methods to the challenging question of circumscribing mitochondrial origin, we suggest that the entire Alphaproteobacteria clade is the closest relative to mitochondria (Alphaproteobacterial-sister hypothesis), echoing recent findings based on different datasets and methodologies.
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Affiliation(s)
| | - Daniel S. Carvalho
- Institute of Biological Sciences, Federal University of Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | - Gilberto C. Bomfim
- Institute of Biology, Federal University of Bahia, Salvador, Bahia, Brazil
| | | | - Jerzy Brzozowski
- Philosophy Department, Federal University of Santa Catarina, Florianópolis, Santa Catarina, Brazil
| | - Aristóteles Góes-Neto
- Institute of Biological Sciences, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil,Graduate Program in Bioinformatics, Institute of Biological Sciences, Federal University of Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | - Roberto F. S. Andrade
- Institute of Physics, Federal University of Bahia, Salvador, Bahia, Brazil,National Institute of Science and Technology in Interdisciplinary and Transdisciplinary Studies in Ecology and Evolution (INCT IN-TREE), Salvador, Bahia, Brazil
| | - Charbel El-Hani
- Institute of Biology, Federal University of Bahia, Salvador, Bahia, Brazil,National Institute of Science and Technology in Interdisciplinary and Transdisciplinary Studies in Ecology and Evolution (INCT IN-TREE), Salvador, Bahia, Brazil
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5
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Analysis and Dynamic Monitoring of Indoor Air Quality Based on Laser-Induced Breakdown Spectroscopy and Machine Learning. CHEMOSENSORS 2022. [DOI: 10.3390/chemosensors10070259] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Abstract
The air quality of the living area influences human health to a certain extent. Therefore, it is particularly important to detect the quality of indoor air. However, traditional detection methods mainly depend on chemical analysis, which has long been criticized for its high time cost. In this research, a rapid air detection method for the indoor environment using laser-induced breakdown spectroscopy (LIBS) and machine learning was proposed. Four common scenes were simulated, including burning carbon, burning incense, spraying perfume and hot shower which often led to indoor air quality changes. Two steps of spectral measurements and algorithm analysis were used in the experiment. Moreover, the proposed method was found to be effective in distinguishing different kinds of aerosols and presenting sensitivity to the air compositions. In this paper, the signal was isolated by the forest, so the singular values were filtered out. Meanwhile, the spectra of different scenarios were analyzed via the principal component analysis (PCA), and the air environment was classified by K-Nearest Neighbor (KNN) algorithm with an accuracy of 99.2%. Moreover, based on the establishment of a high-precision quantitative detection model, a back propagation (BP) neural network was introduced to improve the robustness and accuracy of indoor environment. The results show that by taking this method, the dynamic prediction of elements concentration can be realized, and its recognition accuracy is 96.5%.
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6
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Favila N, Madrigal-Trejo D, Legorreta D, Sánchez-Pérez J, Espinosa-Asuar L, Eguiarte LE, Souza V. MicNet toolbox: Visualizing and unraveling a microbial network. PLoS One 2022; 17:e0259756. [PMID: 35749381 PMCID: PMC9231805 DOI: 10.1371/journal.pone.0259756] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2021] [Accepted: 04/05/2022] [Indexed: 11/19/2022] Open
Abstract
Applications of network theory to microbial ecology are an emerging and promising approach to understanding both global and local patterns in the structure and interplay of these microbial communities. In this paper, we present an open-source python toolbox which consists of two modules: on one hand, we introduce a visualization module that incorporates the use of UMAP, a dimensionality reduction technique that focuses on local patterns, and HDBSCAN, a clustering technique based on density; on the other hand, we have included a module that runs an enhanced version of the SparCC code, sustaining larger datasets than before, and we couple the resulting networks with network theory analyses to describe the resulting co-occurrence networks, including several novel analyses, such as structural balance metrics and a proposal to discover the underlying topology of a co-occurrence network. We validated the proposed toolbox on 1) a simple and well described biological network of kombucha, consisting of 48 ASVs, and 2) we validate the improvements of our new version of SparCC. Finally, we showcase the use of the MicNet toolbox on a large dataset from Archean Domes, consisting of more than 2,000 ASVs. Our toolbox is freely available as a github repository (https://github.com/Labevo/MicNetToolbox), and it is accompanied by a web dashboard (http://micnetapplb-1212130533.us-east-1.elb.amazonaws.com) that can be used in a simple and straightforward manner with relative abundance data. This easy-to-use implementation is aimed to microbial ecologists with little to no experience in programming, while the most experienced bioinformatics will also be able to manipulate the source code's functions with ease.
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Affiliation(s)
- Natalia Favila
- Laboratorio de Inteligencia Artificial, Ixulabs, Mexico City, Mexico
| | - David Madrigal-Trejo
- Departamento de Ecología Evolutiva, Instituto de Ecología, Universidad Nacional Autónoma de México, Mexico City, Mexico
| | - Daniel Legorreta
- Laboratorio de Inteligencia Artificial, Ixulabs, Mexico City, Mexico
| | - Jazmín Sánchez-Pérez
- Departamento de Ecología Evolutiva, Instituto de Ecología, Universidad Nacional Autónoma de México, Mexico City, Mexico
| | - Laura Espinosa-Asuar
- Departamento de Ecología Evolutiva, Instituto de Ecología, Universidad Nacional Autónoma de México, Mexico City, Mexico
| | - Luis E. Eguiarte
- Departamento de Ecología Evolutiva, Instituto de Ecología, Universidad Nacional Autónoma de México, Mexico City, Mexico
| | - Valeria Souza
- Departamento de Ecología Evolutiva, Instituto de Ecología, Universidad Nacional Autónoma de México, Mexico City, Mexico
- Centro de Estudios del Cuaternario de Fuego-Patagonia y Antártica (CEQUA), Punta Arenas, Chile
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7
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Richard D, Roumagnac P, Pruvost O, Lefeuvre P. A network approach to decipher the dynamics of Lysobacteraceae plasmid gene sharing. Mol Ecol 2022; 32:2660-2673. [PMID: 35593155 DOI: 10.1111/mec.16536] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2021] [Revised: 04/21/2022] [Accepted: 05/05/2022] [Indexed: 11/27/2022]
Abstract
Plasmids provide an efficient vehicle for gene sharing among bacterial populations, playing a key role in bacterial evolution. Network approaches are particularly suitable to represent multipartite relationships and are useful tools to characterize plasmid-mediated gene sharing events. The Lysobacteraceae bacterial family gathers plant commensal, plant pathogenic and opportunistic human pathogens for which plasmid mediated adaptation was reported. We searched for homologues of plasmid gene sequences from this family in all the diversity of available bacterial genome sequences and built a network of plasmid gene sharing from the results. While plasmid genes are openly shared between the bacteria of the Lysobacteraceae family, taxonomy strongly defined the boundaries of these exchanges, that only barely reached other families. Most inferred plasmid gene sharing events involved a few genes only, and evidence of full plasmid transfers were restricted to taxonomically close taxon. We detected multiple plasmid-chromosome gene transfers, among which the otherwise known sharing of a heavy metal resistance transposon. In the network, bacterial lifestyles shaped sub-structures of isolates colonizing specific ecological niches and harboring specific types of resistance genes. Genes associated to pathogenicity or antibiotic and metal resistance were among those that most importantly structured the network, highlighting the imprints of human-mediated selective pressure on pathogenic populations. A massive sequencing effort on environmental Lysobacteraceae is therefore required to refine our understanding on how this reservoir fuels the emergence and the spread of genes amongst this family and its potential impact on plant, animal and human health.
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Affiliation(s)
- D Richard
- Cirad, UMR PVBMT, F-97410 St Pierre, Réunion, France.,ANSES, Plant Health Laboratory, F-97410 St Pierre, Réunion, France.,Université de La Réunion, La Réunion, France
| | - P Roumagnac
- Montpellier, France.,PHIM Plant Health Institute, Univ Montpellier, CIRAD, INRAE, Institut Agro, IRD, Montpellier, France
| | - O Pruvost
- Cirad, UMR PVBMT, F-97410 St Pierre, Réunion, France
| | - P Lefeuvre
- Cirad, UMR PVBMT, F-97410 St Pierre, Réunion, France
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8
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Kong S, Pons JC, Kubatko L, Wicke K. Classes of explicit phylogenetic networks and their biological and mathematical significance. J Math Biol 2022; 84:47. [PMID: 35503141 DOI: 10.1007/s00285-022-01746-y] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2021] [Revised: 01/18/2022] [Accepted: 03/31/2022] [Indexed: 11/24/2022]
Abstract
The evolutionary relationships among organisms have traditionally been represented using rooted phylogenetic trees. However, due to reticulate processes such as hybridization or lateral gene transfer, evolution cannot always be adequately represented by a phylogenetic tree, and rooted phylogenetic networks that describe such complex processes have been introduced as a generalization of rooted phylogenetic trees. In fact, estimating rooted phylogenetic networks from genomic sequence data and analyzing their structural properties is one of the most important tasks in contemporary phylogenetics. Over the last two decades, several subclasses of rooted phylogenetic networks (characterized by certain structural constraints) have been introduced in the literature, either to model specific biological phenomena or to enable tractable mathematical and computational analyses. In the present manuscript, we provide a thorough review of these network classes, as well as provide a biological interpretation of the structural constraints underlying these networks where possible. In addition, we discuss how imposing structural constraints on the network topology can be used to address the scalability and identifiability challenges faced in the estimation of phylogenetic networks from empirical data.
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Affiliation(s)
- Sungsik Kong
- Department of Evolution, Ecology, and Organismal Biology, The Ohio State University, Columbus, OH, USA
| | - Joan Carles Pons
- Department of Mathematics and Computer Science, University of the Balearic Islands, Palma, 07122, Spain
| | - Laura Kubatko
- Department of Evolution, Ecology, and Organismal Biology, The Ohio State University, Columbus, OH, USA.,Department of Statistics, The Ohio State University, Columbus, OH, USA
| | - Kristina Wicke
- Department of Mathematics, The Ohio State University, Columbus, OH, USA.
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9
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Oña L, Kost C. Cooperation increases robustness to ecological disturbance in microbial cross-feeding networks. Ecol Lett 2022; 25:1410-1420. [PMID: 35384221 DOI: 10.1111/ele.14006] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2021] [Revised: 01/26/2022] [Accepted: 02/22/2022] [Indexed: 12/19/2022]
Abstract
Microorganisms mainly exist within complex networks of ecological interactions. Given that the growth and survival of community members frequently depend on an obligate exchange of essential metabolites, it is generally unclear how such communities can persist despite the destabilising force of ecological disturbance. Here we address this issue using a population dynamics model. In contrast to previous work that suggests the potential for obligate interaction networks to emerge is limited, we find the opposite pattern: ecological disturbance favours both specific network topologies and cooperative cross-feeding among community members. These results establish environmental perturbations as a key driver shaping the architecture of microbial interaction networks.
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Affiliation(s)
- Leonardo Oña
- Department of Ecology, School of Biology/Chemistry, Osnabrück University, Osnabrück, Germany
| | - Christian Kost
- Department of Ecology, School of Biology/Chemistry, Osnabrück University, Osnabrück, Germany
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10
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Mall A, Kasarlawar S, Saini S. Limited Pairwise Synergistic and Antagonistic Interactions Impart Stability to Microbial Communities. Front Ecol Evol 2022. [DOI: 10.3389/fevo.2022.648997] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
One of the central goals of ecology is to explain and predict coexistence of species. In this context, microbial communities provide a model system where community structure can be studied in environmental niches and in laboratory conditions. A community of microbial population is stabilized by interactions between participating species. However, the nature of these stabilizing interactions has remained largely unknown. Theory and experiments have suggested that communities are stabilized by antagonistic interactions between member species, and destabilized by synergistic interactions. However, experiments have also revealed that a large fraction of all the interactions between species in a community are synergistic in nature. To understand the relative significance of the two types of interactions (synergistic vs. antagonistic) between species, we perform simulations of microbial communities with a small number of participating species using two frameworks—a replicator equation and a Lotka-Volterra framework. Our results demonstrate that synergistic interactions between species play a critical role in maintaining diversity in cultures. These interactions are critical for the ability of the communities to survive perturbations and maintain diversity. We follow up the simulations with quantification of the extent to which synergistic and antagonistic interactions are present in a bacterial community present in a soil sample. Overall, our results show that community stability is largely achieved with the help of synergistic interactions between participating species. However, we perform experiments to demonstrate that antagonistic interactions, in specific circumstances, can also contribute toward community stability.
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11
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Svahn AJ, Chang SL, Rockett RJ, Cliff OM, Wang Q, Arnott A, Ramsperger M, Sorrell TC, Sintchenko V, Prokopenko M. GENOME-WIDE NETWORKS REVEAL EMERGENCE OF EPIDEMIC STRAINS OF SALMONELLA ENTERITIDIS. Int J Infect Dis 2022; 117:65-73. [DOI: 10.1016/j.ijid.2022.01.056] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Revised: 01/24/2022] [Accepted: 01/26/2022] [Indexed: 10/19/2022] Open
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12
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Baquero F, Martínez JL, F. Lanza V, Rodríguez-Beltrán J, Galán JC, San Millán A, Cantón R, Coque TM. Evolutionary Pathways and Trajectories in Antibiotic Resistance. Clin Microbiol Rev 2021; 34:e0005019. [PMID: 34190572 PMCID: PMC8404696 DOI: 10.1128/cmr.00050-19] [Citation(s) in RCA: 66] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
Evolution is the hallmark of life. Descriptions of the evolution of microorganisms have provided a wealth of information, but knowledge regarding "what happened" has precluded a deeper understanding of "how" evolution has proceeded, as in the case of antimicrobial resistance. The difficulty in answering the "how" question lies in the multihierarchical dimensions of evolutionary processes, nested in complex networks, encompassing all units of selection, from genes to communities and ecosystems. At the simplest ontological level (as resistance genes), evolution proceeds by random (mutation and drift) and directional (natural selection) processes; however, sequential pathways of adaptive variation can occasionally be observed, and under fixed circumstances (particular fitness landscapes), evolution is predictable. At the highest level (such as that of plasmids, clones, species, microbiotas), the systems' degrees of freedom increase dramatically, related to the variable dispersal, fragmentation, relatedness, or coalescence of bacterial populations, depending on heterogeneous and changing niches and selective gradients in complex environments. Evolutionary trajectories of antibiotic resistance find their way in these changing landscapes subjected to random variations, becoming highly entropic and therefore unpredictable. However, experimental, phylogenetic, and ecogenetic analyses reveal preferential frequented paths (highways) where antibiotic resistance flows and propagates, allowing some understanding of evolutionary dynamics, modeling and designing interventions. Studies on antibiotic resistance have an applied aspect in improving individual health, One Health, and Global Health, as well as an academic value for understanding evolution. Most importantly, they have a heuristic significance as a model to reduce the negative influence of anthropogenic effects on the environment.
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Affiliation(s)
- F. Baquero
- Department of Microbiology, Ramón y Cajal University Hospital, Ramón y Cajal Institute for Health Research (IRYCIS), Network Center for Research in Epidemiology and Public Health (CIBERESP), Madrid, Spain
| | - J. L. Martínez
- National Center for Biotechnology (CNB-CSIC), Madrid, Spain
| | - V. F. Lanza
- Department of Microbiology, Ramón y Cajal University Hospital, Ramón y Cajal Institute for Health Research (IRYCIS), Network Center for Research in Epidemiology and Public Health (CIBERESP), Madrid, Spain
- Central Bioinformatics Unit, Ramón y Cajal Institute for Health Research (IRYCIS), Madrid, Spain
| | - J. Rodríguez-Beltrán
- Department of Microbiology, Ramón y Cajal University Hospital, Ramón y Cajal Institute for Health Research (IRYCIS), Network Center for Research in Epidemiology and Public Health (CIBERESP), Madrid, Spain
| | - J. C. Galán
- Department of Microbiology, Ramón y Cajal University Hospital, Ramón y Cajal Institute for Health Research (IRYCIS), Network Center for Research in Epidemiology and Public Health (CIBERESP), Madrid, Spain
| | - A. San Millán
- National Center for Biotechnology (CNB-CSIC), Madrid, Spain
| | - R. Cantón
- Department of Microbiology, Ramón y Cajal University Hospital, Ramón y Cajal Institute for Health Research (IRYCIS), Network Center for Research in Epidemiology and Public Health (CIBERESP), Madrid, Spain
| | - T. M. Coque
- Department of Microbiology, Ramón y Cajal University Hospital, Ramón y Cajal Institute for Health Research (IRYCIS), Network Center for Research in Epidemiology and Public Health (CIBERESP), Madrid, Spain
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13
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Wallin R, van Iersel L, Kelk S, Stougie L. Applicability of several rooted phylogenetic network algorithms for representing the evolutionary history of SARS-CoV-2. BMC Ecol Evol 2021; 21:220. [PMID: 34876022 PMCID: PMC8649988 DOI: 10.1186/s12862-021-01946-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2021] [Accepted: 11/03/2021] [Indexed: 11/13/2022] Open
Abstract
Background Rooted phylogenetic networks are used to display complex evolutionary history involving so-called reticulation events, such as genetic recombination. Various methods have been developed to construct such networks, using for example a multiple sequence alignment or multiple phylogenetic trees as input data. Coronaviruses are known to recombine frequently, but rooted phylogenetic networks have not yet been used extensively to describe their evolutionary history. Here, we created a workflow to compare the evolutionary history of SARS-CoV-2 with other SARS-like viruses using several rooted phylogenetic network inference algorithms. This workflow includes filtering noise from sets of phylogenetic trees by contracting edges based on branch length and bootstrap support, followed by resolution of multifurcations. We explored the running times of the network inference algorithms, the impact of filtering on the properties of the produced networks, and attempted to derive biological insights regarding the evolution of SARS-CoV-2 from them. Results The network inference algorithms are capable of constructing rooted phylogenetic networks for coronavirus data, although running-time limitations require restricting such datasets to a relatively small number of taxa. Filtering generally reduces the number of reticulations in the produced networks and increases their temporal consistency. Taxon bat-SL-CoVZC45 emerges as a major and structural source of discordance in the dataset. The tested algorithms often indicate that SARS-CoV-2/RaTG13 is a tree-like clade, with possibly some reticulate activity further back in their history. A smaller number of constructed networks posit SARS-CoV-2 as a possible recombinant, although this might be a methodological artefact arising from the interaction of bat-SL-CoVZC45 discordance and the optimization criteria used. Conclusion Our results demonstrate that as part of a wider workflow and with careful attention paid to running time, rooted phylogenetic network algorithms are capable of producing plausible networks from coronavirus data. These networks partly corroborate existing theories about SARS-CoV-2, and partly produce new avenues for exploration regarding the location and significance of reticulate activity within the wider group of SARS-like viruses. Our workflow may serve as a model for pipelines in which phylogenetic network algorithms can be used to analyse different datasets and test different hypotheses.
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Affiliation(s)
- Rosanne Wallin
- Centrum Wiskunde & Informatica (CWI), Science Park 123, 1098 XG, Amsterdam, The Netherlands
| | - Leo van Iersel
- Delft Institute of Applied Mathematics, Delft University of Technology, Van Mourik Broekmanweg 6, 2628 XE, Delft, The Netherlands
| | - Steven Kelk
- Department of Data Science and Knowledge Engineering (DKE), Maastricht University, Maastricht, The Netherlands
| | - Leen Stougie
- Centrum Wiskunde & Informatica (CWI), Science Park 123, 1098 XG, Amsterdam, The Netherlands. .,School of Business and Economics, Vrije Universiteit, Amsterdam, The Netherlands.
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14
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Rangel-Pineros G, Millard A, Michniewski S, Scanlan D, Sirén K, Reyes A, Petersen B, Clokie MR, Sicheritz-Pontén T. From Trees to Clouds: PhageClouds for Fast Comparison of ∼640,000 Phage Genomic Sequences and Host-Centric Visualization Using Genomic Network Graphs. PHAGE (NEW ROCHELLE, N.Y.) 2021; 2:194-203. [PMID: 36147515 PMCID: PMC9041511 DOI: 10.1089/phage.2021.0008] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/14/2023]
Abstract
Background: Fast and computationally efficient strategies are required to explore genomic relationships within an increasingly large and diverse phage sequence space. Here, we present PhageClouds, a novel approach using a graph database of phage genomic sequences and their intergenomic distances to explore the phage genomic sequence space. Methods: A total of 640,000 phage genomic sequences were retrieved from a variety of databases and public virome assemblies. Intergenomic distances were calculated with dashing, an alignment-free method suitable for handling massive data sets. These data were used to build a Neo4j® graph database. Results: PhageClouds supported the search of related phages among all complete phage genomes from GenBank for a single query phage in just 10 s. Moreover, PhageClouds expanded the number of closely related phage sequences detected for both finished and draft phage genomes, in comparison with searches exclusively targeting phage entries from GenBank. Conclusions: PhageClouds is a novel resource that will facilitate the analysis of phage genomic sequences and the characterization of assembled phage genomes.
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Affiliation(s)
- Guillermo Rangel-Pineros
- Section for Evolutionary Genomics, 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
| | - Andrew Millard
- Department of Genetics and Genome Biology, University of Leicester, Leicester, United Kingdom
| | - Slawomir Michniewski
- Warwick Medical School of Life Sciences, University of Warwick, Coventry, United Kingdom
| | - David Scanlan
- Warwick Medical School of Life Sciences, University of Warwick, Coventry, United Kingdom
| | - Kimmo Sirén
- Section for Evolutionary Genomics, 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, Bogota, Colombia
| | - Bent Petersen
- Centre of Excellence for Omics-Driven Computational Biodiscovery (COMBio), Faculty of Applied Sciences, AIMST University, Kedah, Malaysia
- Center for Evolutionary Hologenomics, Globe Institute, University of Copenhagen, Copenhagen, Denmark
| | - Martha R.J. Clokie
- Department of Genetics and Genome Biology, University of Leicester, Leicester, United Kingdom
| | - Thomas Sicheritz-Pontén
- Centre of Excellence for Omics-Driven Computational Biodiscovery (COMBio), Faculty of Applied Sciences, AIMST University, Kedah, Malaysia
- Center for Evolutionary Hologenomics, Globe Institute, University of Copenhagen, Copenhagen, Denmark
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15
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Watson AK, Lopez P, Bapteste E. Hundreds of out-of-frame remodelled gene families in the E. coli pangenome. Mol Biol Evol 2021; 39:6430988. [PMID: 34792602 PMCID: PMC8788219 DOI: 10.1093/molbev/msab329] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023] Open
Abstract
All genomes include gene families with very limited taxonomic distributions that potentially represent new genes and innovations in protein-coding sequence, raising questions on the origins of such genes. Some of these genes are hypothesized to have formed de novo, from noncoding sequences, and recent work has begun to elucidate the processes by which de novo gene formation can occur. A special case of de novo gene formation, overprinting, describes the origin of new genes from noncoding alternative reading frames of existing open reading frames (ORFs). We argue that additionally, out-of-frame gene fission/fusion events of alternative reading frames of ORFs and out-of-frame lateral gene transfers could contribute to the origin of new gene families. To demonstrate this, we developed an original pattern-search in sequence similarity networks, enhancing the use of these graphs, commonly used to detect in-frame remodeled genes. We applied this approach to gene families in 524 complete genomes of Escherichia coli. We identified 767 gene families whose evolutionary history likely included at least one out-of-frame remodeling event. These genes with out-of-frame components represent ∼2.5% of all genes in the E. coli pangenome, suggesting that alternative reading frames of existing ORFs can contribute to a significant proportion of de novo genes in bacteria.
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Affiliation(s)
- Andrew K Watson
- Institut de Systématique, Evolution, Biodiversité (ISYEB), Sorbonne Université, CNRS, Museum National d'Histoire Naturelle, EPHE, Université des Antilles, 7, quai Saint Bernard, Paris, 75005, France
| | - Philippe Lopez
- Institut de Systématique, Evolution, Biodiversité (ISYEB), Sorbonne Université, CNRS, Museum National d'Histoire Naturelle, EPHE, Université des Antilles, 7, quai Saint Bernard, Paris, 75005, France
| | - Eric Bapteste
- Institut de Systématique, Evolution, Biodiversité (ISYEB), Sorbonne Université, CNRS, Museum National d'Histoire Naturelle, EPHE, Université des Antilles, 7, quai Saint Bernard, Paris, 75005, France
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16
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Sun TW, Ku C. Unraveling gene content variation across eukaryotic giant viruses based on network analyses and host associations. Virus Evol 2021; 7:veab081. [PMID: 34754514 PMCID: PMC8570155 DOI: 10.1093/ve/veab081] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2021] [Revised: 08/31/2021] [Accepted: 09/15/2021] [Indexed: 12/31/2022] Open
Abstract
The nucleocytoplasmic large DNA viruses (NCLDVs, phylum Nucleocytoviricota) infect vertebrates, invertebrates, algae, amoebae, and other unicellular organisms across supergroups of eukaryotes and in various ecosystems. The expanding collection of their genome sequences has revolutionized our view of virus genome size and coding capacity. Phylogenetic trees based on a few core genes are commonly used as a model to understand their evolution. However, the tree topology can differ between analyses, and the vast majority of encoded genes might not share a common evolutionary history. To explore the whole-genome variation and evolution of NCLDVs, we dissected their gene contents using clustering, network, and comparative analyses. Our updated core-gene tree served as a framework to classify NCLDVs into families and intrafamilial lineages, but networks of individual genomes and family pangenomes showed patterns of gene sharing that contradict with the tree topology, in particular at higher taxonomic levels. Clustering of NCLDV genomes revealed variable granularity and degrees of gene sharing within each family, which cannot be inferred from the tree. At the level of NCLDV families, a correlation exists between gene content variation, but not core-gene sequence divergence, and host supergroup diversity. In addition, there is significantly higher gene sharing between divergent viruses that infect similar host types. The identified shared genes would be a useful resource for further functional analyses of NCLDV–host interactions. Overall this study provides a comprehensive view of gene repertoire variation in NCLDVs at different taxonomic levels, as well as a novel approach to studying the extremely diverse giant virus genomes.
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Affiliation(s)
- Tsu-Wang Sun
- Institute of Plant and Microbial Biology, Academia Sinica, Taipei 11529, Taiwan
| | - Chuan Ku
- Institute of Plant and Microbial Biology, Academia Sinica, Taipei 11529, Taiwan
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17
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Abstract
The advent of comparative genomics in the late 1990s led to the discovery of extensive lateral gene transfer in prokaryotes. The resulting debate over whether life as a whole is best represented as a tree or a network has since given way to a general consensus in which trees and networks co-exist rather than stand in opposition. Embracing this consensus allows us to move beyond the question of which is true or false. The future of the tree of life debate lies in asking what trees and networks can, and should, do for science.
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Affiliation(s)
- Cédric Blais
- Centre for Comparative Genomics and Evolutionary Bioinformatics, Dalhousie University, Halifax, NS, Canada; Department of Biochemistry and Molecular Biology, Dalhousie University, Halifax, NS, Canada.
| | - John M Archibald
- Centre for Comparative Genomics and Evolutionary Bioinformatics, Dalhousie University, Halifax, NS, Canada; Department of Biochemistry and Molecular Biology, Dalhousie University, Halifax, NS, Canada.
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18
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Han X, Guo J, Pang E, Song H, Lin K. Ab Initio Construction and Evolutionary Analysis of Protein-Coding Gene Families with Partially Homologous Relationships: Closely Related Drosophila Genomes as a Case Study. Genome Biol Evol 2021; 12:185-202. [PMID: 32108239 PMCID: PMC7144356 DOI: 10.1093/gbe/evaa041] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/18/2020] [Indexed: 01/05/2023] Open
Abstract
How have genes evolved within a well-known genome phylogeny? Many protein-coding genes should have evolved as a whole at the gene level, and some should have evolved partly through fragments at the subgene level. To comprehensively explore such complex homologous relationships and better understand gene family evolution, here, with de novo-identified modules, the subgene units which could consecutively cover proteins within a set of closely related species, we applied a new phylogeny-based approach that considers evolutionary models with partial homology to classify all protein-coding genes in nine Drosophila genomes. Compared with two other popular methods for gene family construction, our approach improved practical gene family classifications with a more reasonable view of homology and provided a much more complete landscape of gene family evolution at the gene and subgene levels. In the case study, we found that most expanded gene families might have evolved mainly through module rearrangements rather than gene duplications and mainly generated single-module genes through partial gene duplication, suggesting that there might be pervasive subgene rearrangement in the evolution of protein-coding gene families. The use of a phylogeny-based approach with partial homology to classify and analyze protein-coding gene families may provide us with a more comprehensive landscape depicting how genes evolve within a well-known genome phylogeny.
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Affiliation(s)
- Xia Han
- State Key Laboratory of Earth Surface Processes and Resource Ecology, Ministry of Education Key Laboratory for Biodiversity Science and Ecological Engineering, College of Life Sciences, Beijing Normal University, China
| | - Jindan Guo
- State Key Laboratory of Earth Surface Processes and Resource Ecology, Ministry of Education Key Laboratory for Biodiversity Science and Ecological Engineering, College of Life Sciences, Beijing Normal University, China
| | - Erli Pang
- State Key Laboratory of Earth Surface Processes and Resource Ecology, Ministry of Education Key Laboratory for Biodiversity Science and Ecological Engineering, College of Life Sciences, Beijing Normal University, China
| | - Hongtao Song
- State Key Laboratory of Earth Surface Processes and Resource Ecology, Ministry of Education Key Laboratory for Biodiversity Science and Ecological Engineering, College of Life Sciences, Beijing Normal University, China
| | - Kui Lin
- State Key Laboratory of Earth Surface Processes and Resource Ecology, Ministry of Education Key Laboratory for Biodiversity Science and Ecological Engineering, College of Life Sciences, Beijing Normal University, China
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19
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Makarenkov V, Mazoure B, Rabusseau G, Legendre P. Horizontal gene transfer and recombination analysis of SARS-CoV-2 genes helps discover its close relatives and shed light on its origin. BMC Ecol Evol 2021; 21:5. [PMID: 33514319 PMCID: PMC7817968 DOI: 10.1186/s12862-020-01732-2] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2020] [Accepted: 12/08/2020] [Indexed: 12/30/2022] Open
Abstract
BACKGROUND The SARS-CoV-2 pandemic is one of the greatest global medical and social challenges that have emerged in recent history. Human coronavirus strains discovered during previous SARS outbreaks have been hypothesized to pass from bats to humans using intermediate hosts, e.g. civets for SARS-CoV and camels for MERS-CoV. The discovery of an intermediate host of SARS-CoV-2 and the identification of specific mechanism of its emergence in humans are topics of primary evolutionary importance. In this study we investigate the evolutionary patterns of 11 main genes of SARS-CoV-2. Previous studies suggested that the genome of SARS-CoV-2 is highly similar to the horseshoe bat coronavirus RaTG13 for most of the genes and to some Malayan pangolin coronavirus (CoV) strains for the receptor binding (RB) domain of the spike protein. RESULTS We provide a detailed list of statistically significant horizontal gene transfer and recombination events (both intergenic and intragenic) inferred for each of 11 main genes of the SARS-CoV-2 genome. Our analysis reveals that two continuous regions of genes S and N of SARS-CoV-2 may result from intragenic recombination between RaTG13 and Guangdong (GD) Pangolin CoVs. Statistically significant gene transfer-recombination events between RaTG13 and GD Pangolin CoV have been identified in region [1215-1425] of gene S and region [534-727] of gene N. Moreover, some statistically significant recombination events between the ancestors of SARS-CoV-2, RaTG13, GD Pangolin CoV and bat CoV ZC45-ZXC21 coronaviruses have been identified in genes ORF1ab, S, ORF3a, ORF7a, ORF8 and N. Furthermore, topology-based clustering of gene trees inferred for 25 CoV organisms revealed a three-way evolution of coronavirus genes, with gene phylogenies of ORF1ab, S and N forming the first cluster, gene phylogenies of ORF3a, E, M, ORF6, ORF7a, ORF7b and ORF8 forming the second cluster, and phylogeny of gene ORF10 forming the third cluster. CONCLUSIONS The results of our horizontal gene transfer and recombination analysis suggest that SARS-CoV-2 could not only be a chimera virus resulting from recombination of the bat RaTG13 and Guangdong pangolin coronaviruses but also a close relative of the bat CoV ZC45 and ZXC21 strains. They also indicate that a GD pangolin may be an intermediate host of this dangerous virus.
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Affiliation(s)
- Vladimir Makarenkov
- Département d'informatique, Université du Québec à Montréal, Montreal, QC, Canada.
| | - Bogdan Mazoure
- Montreal Institute for Learning Algorithms (Mila), Montreal, QC, Canada
| | - Guillaume Rabusseau
- Montreal Institute for Learning Algorithms (Mila), Montreal, QC, Canada
- Département d'informatique et de Recherche Opérationnelle, Université de Montréal and Canada CIFAR AI Chair, Montreal, QC, Canada
| | - Pierre Legendre
- Département de Sciences Biologiques, Université de Montréal, C. P. 6128, Succursale Centre-Ville, Montreal, QC, H3C 3J7, Canada
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20
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Arredondo-Alonso S, Top J, Corander J, Willems RJL, Schürch AC. Mode and dynamics of vanA-type vancomycin resistance dissemination in Dutch hospitals. Genome Med 2021; 13:9. [PMID: 33472670 PMCID: PMC7816424 DOI: 10.1186/s13073-020-00825-3] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2020] [Accepted: 12/30/2020] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND Enterococcus faecium is a commensal of the gastrointestinal tract of animals and humans but also a causative agent of hospital-acquired infections. Resistance against glycopeptides and to vancomycin has motivated the inclusion of E. faecium in the WHO global priority list. Vancomycin resistance can be conferred by the vanA gene cluster on the transposon Tn1546, which is frequently present in plasmids. The vanA gene cluster can be disseminated clonally but also horizontally either by plasmid dissemination or by Tn1546 transposition between different genomic locations. METHODS We performed a retrospective study of the genomic epidemiology of 309 vancomycin-resistant E. faecium (VRE) isolates across 32 Dutch hospitals (2012-2015). Genomic information regarding clonality and Tn1546 characterization was extracted using hierBAPS sequence clusters (SC) and TETyper, respectively. Plasmids were predicted using gplas in combination with a network approach based on shared k-mer content. Next, we conducted a pairwise comparison between isolates sharing a potential epidemiological link to elucidate whether clonal, plasmid, or Tn1546 spread accounted for vanA-type resistance dissemination. RESULTS On average, we estimated that 59% of VRE cases with a potential epidemiological link were unrelated which was defined as VRE pairs with a distinct Tn1546 variant. Clonal dissemination accounted for 32% cases in which the same SC and Tn1546 variants were identified. Horizontal plasmid dissemination accounted for 7% of VRE cases, in which we observed VRE pairs belonging to a distinct SC but carrying an identical plasmid and Tn1546 variant. In 2% of cases, we observed the same Tn1546 variant in distinct SC and plasmid types which could be explained by mixed and consecutive events of clonal and plasmid dissemination. CONCLUSIONS In related VRE cases, the dissemination of the vanA gene cluster in Dutch hospitals between 2012 and 2015 was dominated by clonal spread. However, we also identified outbreak settings with high frequencies of plasmid dissemination in which the spread of resistance was mainly driven by horizontal gene transfer (HGT). This study demonstrates the feasibility of distinguishing between modes of dissemination with short-read data and provides a novel assessment to estimate the relative contribution of nested genomic elements in the dissemination of vanA-type resistance.
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Affiliation(s)
- Sergio Arredondo-Alonso
- Department of Medical Microbiology, University Medical Center Utrecht, Utrecht, The Netherlands.,Department of Biostatistics, University of Oslo, Oslo, Norway
| | - Janetta Top
- Department of Medical Microbiology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Jukka Corander
- Department of Biostatistics, University of Oslo, Oslo, Norway.,Pathogen Genomics, Wellcome Trust Sanger Institute, Cambridge, CB10 1SA, UK.,Department of Mathematics and Statistics, Helsinki Institute of Information Technology (HIIT), FI-00014 University of Helsinki, Helsinki, Finland
| | - Rob J L Willems
- Department of Medical Microbiology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Anita C Schürch
- Department of Medical Microbiology, University Medical Center Utrecht, Utrecht, The Netherlands.
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21
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Jalasvuori M. Silent rain: does the atmosphere-mediated connectivity between microbiomes influence bacterial evolutionary rates? FEMS Microbiol Ecol 2020; 96:5841522. [PMID: 32436564 DOI: 10.1093/femsec/fiaa096] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2020] [Accepted: 05/20/2020] [Indexed: 01/21/2023] Open
Abstract
Air carries a vast number of bacteria and viruses over great distances all the time. This leads to continuous introduction of foreign genetic material to local, established microbial communities. In this perspective, I ask whether this silent rain may have a slowing effect on the overall evolutionary rates in the microbial biosphere. Arguably, the greater the genetic divergence between gene 'donors' and 'recipients', the greater the chance that the gene product has a deleterious epistatic interaction with other gene products in its genetic environment. This is due to the long-term absence of check for mutual compatibility. As such, if an organism is extensively different from other bacteria, genetic innovations are less probable to fit to the genome. Here, genetic innovation would be anything that elevates the fitness of the gene vehicle (e.g. bacterium) over its contemporaries. Adopted innovations increase the fitness of the compatible genome over incompatible ones, thus possibly tempering the pace at which mutations accumulate in existing genomes over generations. I further discuss the transfer of bacteriophages through atmosphere and potential effects that this may have on local dynamics and perhaps phage survival.
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Affiliation(s)
- Matti Jalasvuori
- Department of Biological and Environmental Science, Nanoscience Center, University of Jyvaskyla, Jyvaskyla, FI-40014, Finland
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22
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Bapteste E, Papale F. Modeling the evolution of interconnected processes: It is the song and the singers: Tracking units of selection with interaction networks. Bioessays 2020; 43:e2000077. [PMID: 33165956 DOI: 10.1002/bies.202000077] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2020] [Revised: 09/18/2020] [Accepted: 09/24/2020] [Indexed: 01/04/2023]
Abstract
Recently, Doolittle and Inkpen formulated a thought provoking theory, asserting that evolution by natural selection was responsible for the sideways evolution of two radically different kinds of selective units (also called Domains). The former entities, termed singers, correspond to the usual objects studied by evolutionary biologists (gene, genomes, individuals, species, etc.), whereas the later, termed songs, correspond to re-produced biological and ecosystemic functions, processes, information, and memes. Singers perform songs through selected patterns of interactions, meaning that a wealth of critical phenomena might receive novel evolutionary explanations. However, this theory did not provide an empirical approach to study evolution in such a broadened context. Here, we show that analyzing songs and singers, using patterns of interaction networks as a common ontology for both, offers a novel, actionable, inclusive and mathematical way to analyze not only the re-production but also the evolution and fitness of biological and ecosystemic interconnected processes.
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Affiliation(s)
- Eric Bapteste
- Institut de Systématique, Evolution, Biodiversité (ISYEB), Sorbonne Université, CNRS, Museum National d'Histoire Naturelle, EPHE, Université des Antilles, 7, quai Saint Bernard, Bâtiment A 4ème étage, pièce 427, Paris, 75005, France
| | - François Papale
- Departement of Philosophy, University of Montreal, 2910 Édouard-Montpetit blvd, Montréal, QC, H3C 3J7, Canada
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23
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Lee AH, Lee J, Noh J, Lee C, Hong S, Kwon BO, Kim JJ, Khim JS. Characteristics of long-term changes in microbial communities from contaminated sediments along the west coast of South Korea: Ecological assessment with eDNA and physicochemical analyses. MARINE POLLUTION BULLETIN 2020; 160:111592. [PMID: 32927183 DOI: 10.1016/j.marpolbul.2020.111592] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/31/2020] [Revised: 08/14/2020] [Accepted: 08/22/2020] [Indexed: 06/11/2023]
Abstract
The environmental DNA (eDNA) metabarcoding was applied to assess benthic ecological health in the west coast of South Korea by investigating a long-term microbial community change (2015-17). The ecological interaction among microorganisms, from phylum to family level, and their associations to environmental variables across the five regions were highlighted. As part of the study, the available chemistry and toxicological data in the regions during the monitoring periods were incorporated into an integrated sediment triad assessment. The bacterial communities were dominated by Proteobacteria (34.2%), Bacteroidetes (13.8%), and Firmicutes (10.8%). Proteobacteria and Bacteroidetes dominated consistently across regions and years, while Firmicutes and Cyanobacteria significantly varied by region and years (p < 0.05). The abundance of this phylum declined over time with the increasing abundance of Cyanobacteria, indicating their independent interactions to certain environmental changes. Planctomycetes and Gemmatimonadetes linked to some contaminants (ΣPAHs and Cu), implying indicator taxa. Overall, eDNA-based microbial community analysis combined with exposures of contaminants and responses of microorganisms is a promising strategy for the assessment of benthic ecological health in contaminated sediments from coastal waters.
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Affiliation(s)
- Aslan Hwanhwi Lee
- School of Earth and Environmental Sciences & Research Institute of Oceanography, Seoul National University, Seoul 08826, Republic of Korea
| | - Junghyun Lee
- School of Earth and Environmental Sciences & Research Institute of Oceanography, Seoul National University, Seoul 08826, Republic of Korea
| | - Junsung Noh
- School of Earth and Environmental Sciences & Research Institute of Oceanography, Seoul National University, Seoul 08826, Republic of Korea
| | - Changkeun Lee
- School of Earth and Environmental Sciences & Research Institute of Oceanography, Seoul National University, Seoul 08826, Republic of Korea
| | - Seongjin Hong
- Department of Ocean Environmental Sciences, Chungnam National University, Daejeon 34134, Republic of Korea
| | - Bong-Oh Kwon
- Department of Marine Biotechnology, Kunsan National University, Kunsan 54150, Republic of Korea
| | - Jae-Jin Kim
- Division of Environmental Science & Ecological Engineering, College of Life Science & Biotechnology, Korea University, Seoul 02841, Republic of Korea
| | - Jong Seong Khim
- School of Earth and Environmental Sciences & Research Institute of Oceanography, Seoul National University, Seoul 08826, Republic of Korea.
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24
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Arroyo AS, Lannes R, Bapteste E, Ruiz-Trillo I. Gene Similarity Networks Unveil a Potential Novel Unicellular Group Closely Related to Animals from the Tara Oceans Expedition. Genome Biol Evol 2020; 12:1664-1678. [PMID: 32533833 PMCID: PMC7533066 DOI: 10.1093/gbe/evaa117] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/08/2020] [Indexed: 12/21/2022] Open
Abstract
The Holozoa clade comprises animals and several unicellular lineages (choanoflagellates, filastereans, and teretosporeans). Understanding their full diversity is essential to address the origins of animals and other evolutionary questions. However, they are poorly known. To provide more insights into the real diversity of holozoans and check for undiscovered diversity, we here analyzed 18S rDNA metabarcoding data from the global Tara Oceans expedition. To overcome the low phylogenetic information contained in the metabarcoding data set (composed of sequences from the short V9 region of the gene), we used similarity networks by combining two data sets: unknown environmental sequences from Tara Oceans and known reference sequences from GenBank. We then calculated network metrics to compare environmental sequences with reference sequences. These metrics reflected the divergence between both types of sequences and provided an effective way to search for evolutionary relevant diversity, further validated by phylogenetic placements. Our results showed that the percentage of unicellular holozoan diversity remains hidden. We found novelties in several lineages, especially in Acanthoecida choanoflagellates. We also identified a potential new holozoan group that could not be assigned to any of the described extant clades. Data on geographical distribution showed that, although ubiquitous, each unicellular holozoan lineage exhibits a different distribution pattern. We also identified a positive association between new animal hosts and the ichthyosporean symbiont Creolimax fragrantissima, as well as for other holozoans previously reported as free-living. Overall, our analyses provide a fresh perspective into the diversity and ecology of unicellular holozoans, highlighting the amount of undescribed diversity.
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Affiliation(s)
- Alicia S Arroyo
- Institut de Biologia Evolutiva (CSIC-Universitat Pompeu Fabra), Barcelona, Spain
| | - Romain Lannes
- Institut de Systématique, Evolution, Biodiversité (ISYEB), Sorbonne Université, CNRS, Museum National d’Histoire Naturelle, EPHE, Université des Antilles, Paris, France
| | - Eric Bapteste
- Institut de Systématique, Evolution, Biodiversité (ISYEB), Sorbonne Université, CNRS, Museum National d’Histoire Naturelle, EPHE, Université des Antilles, Paris, France
| | - Iñaki Ruiz-Trillo
- Institut de Biologia Evolutiva (CSIC-Universitat Pompeu Fabra), Barcelona, Spain
- Departament de Genètica, Microbiologia I Estadística, Institut de Recerca de la Biodiversitat, Universitat de Barcelona, Spain
- ICREA, Barcelona, Spain
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25
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Abstract
Developing a detailed understanding of how all known forms of life are related to one another in the tree of life has been a major preoccupation of biology since the idea of tree-like evolution first took hold. Since most life is microbial, our intuitive use of morphological comparisons to infer relatedness only goes so far, and molecular sequence data, most recently from genomes and transcriptomes, has been the primary means to infer these relationships. For prokaryotes this presented new challenges, since the degree of horizontal gene transfer led some to question the tree-like depiction of evolution altogether. Most eukaryotes are also microbial, but in contrast to prokaryotic life, the application of large-scale molecular data to the tree of eukaryotes has largely been a constructive process, leading to a small number of very diverse lineages, or 'supergroups'. The tree is not completely resolved, and contentious problems remain, but many well-established supergroups now encompass much more diversity than the traditional kingdoms. Some of the most exciting recent developments come from the discovery of branches in the tree that we previously had no inkling even existed, many of which are of great ecological or evolutionary interest. These new branches highlight the need for more exploration, by high-throughput molecular surveys, but also more traditional means of observations and cultivation.
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Affiliation(s)
- Patrick J Keeling
- Department of Botany, University of British Columbia, Vancouver V6T 1Z4, British Columbia, Canada.
| | - Fabien Burki
- Department of Organismal Biology, Program in Systematic Biology, Uppsala University, Uppsala, Sweden; Science for Life Laboratory, Uppsala University, Uppsala, Sweden
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26
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DeSalle R, Riley M. Should Networks Supplant Tree Building? Microorganisms 2020; 8:E1179. [PMID: 32756444 PMCID: PMC7466111 DOI: 10.3390/microorganisms8081179] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2020] [Revised: 07/21/2020] [Accepted: 07/29/2020] [Indexed: 12/15/2022] Open
Abstract
Recent studies suggested that network methods should supplant tree building as the basis of genealogical analysis. This proposition is based upon two arguments. First is the observation that bacterial and archaeal lineages experience processes oppositional to bifurcation and hence the representation of the evolutionary process in a tree like structure is illogical. Second is the argument tree building approaches are circular-you ask for a tree and you get one, which pins a verificationist label on tree building that, if correct, should be the end of phylogenetic analysis as we currently know it. In this review, we examine these questions and suggest that rumors of the death of the bacterial tree of life are exaggerated at best.
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Affiliation(s)
- Rob DeSalle
- Sackler Institute for Comparative Genomics, American Museum of Natural History, Central Park West at 79th Street, New York, NY 10024, USA;
| | - Margaret Riley
- Department of Biology, University of Massachusetts Amherst, 116 North Pleasant Street, Amherst, MA 01003, USA
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27
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Qiao P, Hou Y. Application of discrete fruit fly algorithm in enhancement of wireless sensor node coverage. JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2020. [DOI: 10.3233/jifs-179835] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Affiliation(s)
- Peixin Qiao
- College of Education, Shanghai Normal University, Shanghai, China
- School of Basic Medical Sciences, Guangxi Medical University, Nanning, China
| | - Ying Hou
- Department of Physics and Engineering Technology, Guilin Normal College, Guilin, China
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28
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Khot V, Strous M, Hawley AK. Computational approaches in viral ecology. Comput Struct Biotechnol J 2020; 18:1605-1612. [PMID: 32670501 PMCID: PMC7334295 DOI: 10.1016/j.csbj.2020.06.019] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2020] [Revised: 06/09/2020] [Accepted: 06/10/2020] [Indexed: 01/21/2023] Open
Abstract
Dynamic virus-host interactions play a critical role in regulating microbial community structure and function. Yet for decades prior to the genomics era, viruses were largely overlooked in microbial ecology research, as only low-throughput culture-based methods of discovering viruses were available. With the advent of metagenomics, culture-independent techniques have provided exciting opportunities to discover and study new viruses. Here, we review recently developed computational methods for identifying viral sequences, exploring viral diversity in environmental samples, and predicting hosts from metagenomic sequence data. Methods to analyze viruses in silico utilize unconventional approaches to tackle challenges unique to viruses, such as vast diversity, mosaic viral genomes, and the lack of universal marker genes. As the field of viral ecology expands exponentially, computational advances have become increasingly important to gain insight into the role viruses in diverse habitats.
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Affiliation(s)
- Varada Khot
- Department of Geoscience, University of Calgary, Calgary, AB T2N 1N4, Canada
| | - Marc Strous
- Department of Geoscience, University of Calgary, Calgary, AB T2N 1N4, Canada
| | - Alyse K. Hawley
- Department of Geoscience, University of Calgary, Calgary, AB T2N 1N4, Canada
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29
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Shuffling type of biological evolution based on horizontal gene transfer and the biosphere gene pool hypothesis. Biosystems 2020; 193-194:104131. [DOI: 10.1016/j.biosystems.2020.104131] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2019] [Revised: 03/12/2020] [Accepted: 03/12/2020] [Indexed: 02/08/2023]
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30
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Acman M, van Dorp L, Santini JM, Balloux F. Large-scale network analysis captures biological features of bacterial plasmids. Nat Commun 2020; 11:2452. [PMID: 32415210 PMCID: PMC7229196 DOI: 10.1038/s41467-020-16282-w] [Citation(s) in RCA: 53] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2019] [Accepted: 04/23/2020] [Indexed: 11/30/2022] Open
Abstract
Many bacteria can exchange genetic material through horizontal gene transfer (HGT) mediated by plasmids and plasmid-borne transposable elements. Here, we study the population structure and dynamics of over 10,000 bacterial plasmids, by quantifying their genetic similarities and reconstructing a network based on their shared k-mer content. We use a community detection algorithm to assign plasmids into cliques, which correlate with plasmid gene content, bacterial host range, GC content, and existing classifications based on replicon and mobility (MOB) types. Further analysis of plasmid population structure allows us to uncover candidates for yet undescribed replicon genes, and to identify transposable elements as the main drivers of HGT at broad phylogenetic scales. Our work illustrates the potential of network-based analyses of the bacterial 'mobilome' and opens up the prospect of a natural, exhaustive classification framework for bacterial plasmids.
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Affiliation(s)
- Mislav Acman
- UCL Genetics Institute, University College London, Gower Street, London, WC1E 6BT, UK.
| | - Lucy van Dorp
- UCL Genetics Institute, University College London, Gower Street, London, WC1E 6BT, UK
| | - Joanne M Santini
- Institute of Structural and Molecular Biology, University College London, Gower Street, London, WC1E 6BT, UK
| | - Francois Balloux
- UCL Genetics Institute, University College London, Gower Street, London, WC1E 6BT, UK.
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31
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Watson A, Habib M, Bapteste E. Phylosystemics: Merging Phylogenomics, Systems Biology, and Ecology to Study Evolution. Trends Microbiol 2020; 28:176-190. [DOI: 10.1016/j.tim.2019.10.011] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2019] [Revised: 10/21/2019] [Accepted: 10/22/2019] [Indexed: 11/28/2022]
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32
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Kim Y, Leung MHY, Kwok W, Fournié G, Li J, Lee PKH, Pfeiffer DU. Antibiotic resistance gene sharing networks and the effect of dietary nutritional content on the canine and feline gut resistome. Anim Microbiome 2020; 2:4. [PMID: 33500005 PMCID: PMC7807453 DOI: 10.1186/s42523-020-0022-2] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2019] [Accepted: 01/29/2020] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND As one of the most densely populated microbial communities on Earth, the gut microbiota serves as an important reservoir of antibiotic resistance genes (ARGs), referred to as the gut resistome. Here, we investigated the association of dietary nutritional content with gut ARG diversity and composition, using publicly available shotgun metagenomic sequence data generated from canine and feline fecal samples. Also, based on network theory, we explored ARG-sharing patterns between gut bacterial genera by identifying the linkage structure between metagenomic assemblies and their functional genes obtained from the same data. RESULTS In both canine and feline gut microbiota, an increase in protein and a reduction in carbohydrate in the diet were associated with increased ARG diversity. ARG diversity of the canine gut microbiota also increased, but less strongly, after a reduction in protein and an increase in carbohydrate in the diet. The association between ARG and taxonomic composition suggests that diet-induced changes in the gut microbiota may be responsible for changes in ARG composition, supporting the links between protein metabolism and antibiotic resistance in gut microbes. In the analysis of the ARG-sharing patterns, 22 ARGs were shared among 46 genera in the canine gut microbiota, and 11 ARGs among 28 genera in the feline gut microbiota. Of these ARGs, the tetracycline resistance gene tet(W) was shared among the largest number of genera, predominantly among Firmicutes genera. Bifidobacterium, a genus extensively used in the fermentation of dairy products and as probiotics, shared tet(W) with a wide variety of other genera. Finally, genera from the same phylum were more likely to share ARGs than with those from different phyla. CONCLUSIONS Our findings show that dietary nutritional content, especially protein content, is associated with the gut resistome and suggest future research to explore the impact of dietary intervention on the development of antibiotic resistance in clinically-relevant gut microbes. Our network analysis also reveals that the genetic composition of bacteria acts as an important barrier to the horizontal transfer of ARGs. By capturing the underlying gene-sharing relationships between different bacterial taxa from metagenomes, our network approach improves our understanding of horizontal gene transfer dynamics.
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Affiliation(s)
- Younjung Kim
- Department of Infectious Diseases and Public Health, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Hong Kong, China.
| | - Marcus H Y Leung
- School of Energy and Environment, City University of Hong Kong, Hong Kong, China
| | - Wendy Kwok
- Department of Infectious Diseases and Public Health, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Hong Kong, China
| | - Guillaume Fournié
- Department of Pathobiology and Population Sciences, Royal Veterinary College, London, UK
| | - Jun Li
- Department of Infectious Diseases and Public Health, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Hong Kong, China.,School of Data Science, City University of Hong Kong, Hong Kong, China
| | - Patrick K H Lee
- School of Energy and Environment, City University of Hong Kong, Hong Kong, China
| | - Dirk U Pfeiffer
- Department of Infectious Diseases and Public Health, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Hong Kong, China.,Department of Pathobiology and Population Sciences, Royal Veterinary College, London, UK
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33
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Papale F, Saget J, Bapteste É. Networks Consolidate the Core Concepts of Evolution by Natural Selection. Trends Microbiol 2019; 28:254-265. [PMID: 31866140 DOI: 10.1016/j.tim.2019.11.006] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2019] [Revised: 11/12/2019] [Accepted: 11/18/2019] [Indexed: 02/07/2023]
Abstract
Microbiology has unraveled rich evidence of ongoing reticulate evolutionary processes and complex interactions both within and between cells. These phenomena feature real biological networks, which can logically be analyzed using network-based tools. It is thus not surprising that network sciences, a field independent from evolutionary biology and microbiology, have recently pervasively infused their methods into both fields. Importantly, network tools bring forward observations enhancing the understanding of three core evolutionary concepts: variation, fitness, and heredity. Consequently, our work shows how network sciences can enhance evolutionary theory by explaining the evolution by natural selection of a broad diversity of units of selection, while updating the popular figure of Darwin's tree of life with a comprehensive sketch of the networks of evolution.
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Affiliation(s)
- François Papale
- Departement of Philosophy, University of Montreal, Montréal, QC, H3C 3J7, Canada; Institut de Systématique, Evolution, Biodiversité (ISYEB), Sorbonne Université, CNRS, Museum National d'Histoire Naturelle, EPHE, Université des Antilles, 75005 Paris, France
| | - Jordane Saget
- Institut de Systématique, Evolution, Biodiversité (ISYEB), Sorbonne Université, CNRS, Museum National d'Histoire Naturelle, EPHE, Université des Antilles, 75005 Paris, France
| | - Éric Bapteste
- Institut de Systématique, Evolution, Biodiversité (ISYEB), Sorbonne Université, CNRS, Museum National d'Histoire Naturelle, EPHE, Université des Antilles, 75005 Paris, France.
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34
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Kellogg CTE, McClelland JW, Dunton KH, Crump BC. Strong Seasonality in Arctic Estuarine Microbial Food Webs. Front Microbiol 2019; 10:2628. [PMID: 31849850 PMCID: PMC6896822 DOI: 10.3389/fmicb.2019.02628] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2019] [Accepted: 10/29/2019] [Indexed: 11/17/2022] Open
Abstract
Microbial communities in the coastal Arctic Ocean experience extreme variability in organic matter and inorganic nutrients driven by seasonal shifts in sea ice extent and freshwater inputs. Lagoons border more than half of the Beaufort Sea coast and provide important habitats for migratory fish and seabirds; yet, little is known about the planktonic food webs supporting these higher trophic levels. To investigate seasonal changes in bacterial and protistan planktonic communities, amplicon sequences of 16S and 18S rRNA genes were generated from samples collected during periods of ice-cover (April), ice break-up (June), and open water (August) from shallow lagoons along the eastern Alaska Beaufort Sea coast from 2011 through 2013. Protist communities shifted from heterotrophic to photosynthetic taxa (mainly diatoms) during the winter–spring transition, and then back to a heterotroph-dominated summer community that included dinoflagellates and mixotrophic picophytoplankton such as Micromonas and Bathycoccus. Planktonic parasites belonging to Syndiniales were abundant under ice in winter at a time when allochthonous carbon inputs were low. Bacterial communities shifted from coastal marine taxa (Oceanospirillaceae, Alteromonadales) to estuarine taxa (Polaromonas, Bacteroidetes) during the winter-spring transition, and then to oligotrophic marine taxa (SAR86, SAR92) in summer. Chemolithoautotrophic taxa were abundant under ice, including iron-oxidizing Zetaproteobacteria. These results suggest that wintertime Arctic bacterial communities capitalize on the unique biogeochemical gradients that develop below ice near shore, potentially using chemoautotrophic metabolisms at a time when carbon inputs to the system are low. Co-occurrence networks constructed for each season showed that under-ice networks were dominated by relationships between parasitic protists and other microbial taxa, while spring networks were by far the largest and dominated by bacteria-bacteria co-occurrences. Summer networks were the smallest and least connected, suggesting a more detritus-based food web less reliant on interactions among microbial taxa. Eukaryotic and bacterial community compositions were significantly related to trends in concentrations of stable isotopes of particulate organic carbon and nitrogen, among other physiochemical variables such as dissolved oxygen, salinity, and temperature. This suggests the importance of sea ice cover and terrestrial carbon subsidies in contributing to seasonal trends in microbial communities in the coastal Beaufort Sea.
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Affiliation(s)
| | - James W McClelland
- Marine Science Institute, University of Texas at Austin, Port Aransas, TX, United States
| | - Kenneth H Dunton
- Marine Science Institute, University of Texas at Austin, Port Aransas, TX, United States
| | - Byron C Crump
- College of Earth, Ocean, and Atmospheric Sciences, Oregon State University, Corvallis, OR, United States
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35
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Ou Y, McInerney JO. Eukaryote Genes Are More Likely than Prokaryote Genes to Be Composites. Genes (Basel) 2019; 10:genes10090648. [PMID: 31466252 PMCID: PMC6769587 DOI: 10.3390/genes10090648] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2019] [Revised: 08/18/2019] [Accepted: 08/23/2019] [Indexed: 12/27/2022] Open
Abstract
The formation of new genes by combining parts of existing genes is an important evolutionary process. Remodelled genes, which we call composites, have been investigated in many species, however, their distribution across all of life is still unknown. We set out to examine the extent to which genomes from cells and mobile genetic elements contain composite genes. We identify composite genes as those that show partial homology to at least two unrelated component genes. In order to identify composite and component genes, we constructed sequence similarity networks (SSNs) of more than one million genes from all three domains of life, as well as viruses and plasmids. We identified non-transitive triplets of nodes in this network and explored the homology relationships in these triplets to see if the middle nodes were indeed composite genes. In total, we identified 221,043 (18.57%) composites genes, which were distributed across all genomic and functional categories. In particular, the presence of composite genes is statistically more likely in eukaryotes than prokaryotes.
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Affiliation(s)
- Yaqing Ou
- Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester M13 9PL, UK.
| | - James O McInerney
- Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester M13 9PL, UK.
- School of Life Sciences, University of Nottingham, Nottingham NG7 2UH, UK.
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36
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Matsui M, Iwasaki W. Graph Splitting: A Graph-Based Approach for Superfamily-Scale Phylogenetic Tree Reconstruction. Syst Biol 2019; 69:265-279. [DOI: 10.1093/sysbio/syz049] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2018] [Revised: 07/09/2019] [Accepted: 07/20/2019] [Indexed: 11/12/2022] Open
Abstract
Abstract
A protein superfamily contains distantly related proteins that have acquired diverse biological functions through a long evolutionary history. Phylogenetic analysis of the early evolution of protein superfamilies is a key challenge because existing phylogenetic methods show poor performance when protein sequences are too diverged to construct an informative multiple sequence alignment (MSA). Here, we propose the Graph Splitting (GS) method, which rapidly reconstructs a protein superfamily-scale phylogenetic tree using a graph-based approach. Evolutionary simulation showed that the GS method can accurately reconstruct phylogenetic trees and be robust to major problems in phylogenetic estimation, such as biased taxon sampling, heterogeneous evolutionary rates, and long-branch attraction when sequences are substantially diverge. Its application to an empirical data set of the triosephosphate isomerase (TIM)-barrel superfamily suggests rapid evolution of protein-mediated pyrimidine biosynthesis, likely taking place after the RNA world. Furthermore, the GS method can also substantially improve performance of widely used MSA methods by providing accurate guide trees.
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Affiliation(s)
- Motomu Matsui
- Department of Biological Sciences, Graduate School of Science, The University of Tokyo, 2-11-16 Yayoi, Bunkyo-ku, Tokyo 113-0032, Japan
| | - Wataru Iwasaki
- Department of Biological Sciences, Graduate School of Science, The University of Tokyo, 2-11-16 Yayoi, Bunkyo-ku, Tokyo 113-0032, Japan
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8568, Japan
- Atmosphere and Ocean Research Institute, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8564, Japan
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37
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Forster D, Lentendu G, Filker S, Dubois E, Wilding TA, Stoeck T. Improving eDNA-based protist diversity assessments using networks of amplicon sequence variants. Environ Microbiol 2019; 21:4109-4124. [PMID: 31361938 DOI: 10.1111/1462-2920.14764] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2019] [Revised: 07/25/2019] [Accepted: 07/25/2019] [Indexed: 12/20/2022]
Abstract
Effective and precise grouping of highly similar sequences remains a major bottleneck in the evaluation of high-throughput sequencing datasets. Amplicon sequence variants (ASVs) offer a promising alternative that may supersede the widely used operational taxonomic units (OTUs) in environmental sequencing studies. We compared the performance of a recently developed pipeline based on the algorithm DADA2 for obtaining ASVs against a pipeline based on the algorithm SWARM for obtaining OTUs. Illumina-sequencing of 29 individual ciliate species resulted in up to 11 ASVs per species, while SWARM produced up to 19 OTUs per species. To improve the congruency between species diversity and molecular diversity, we applied sequence similarity networks (SSNs) for second-level sequence grouping into network sequence clusters (NSCs). At 100% sequence similarity in SWARM-SSNs, NSC numbers decreased from 7.9-fold overestimation without abundance filter, to 4.5-fold overestimation when an abundance filter was applied. For the DADA2-SSN approach, NSC numbers decreased from 3.5-fold to 3-fold overestimation. Rand index cluster analyses predicted best binning results between 97% and 94% sequence similarity for both DADA2-SSNs and SWARM-SSNs. Depending on the ecological questions addressed in an environmental sequencing study with protists we recommend ASVs as replacement for OTUs, best in combination with SSNs.
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Affiliation(s)
- Dominik Forster
- Department of Ecology, University of Kaiserslautern, Kaiserslautern, Germany
| | - Guillaume Lentendu
- Department of Ecology, University of Kaiserslautern, Kaiserslautern, Germany
| | - Sabine Filker
- Department of Molecular Ecology, University of Kaiserslautern, Kaiserslautern, Germany
| | - Elyssa Dubois
- Department of Ecology, University of Kaiserslautern, Kaiserslautern, Germany
| | - Thomas A Wilding
- Scottish Association for Marine Science, Scottish Marine Institute, Oban, Scotland, UK
| | - Thorsten Stoeck
- Department of Ecology, University of Kaiserslautern, Kaiserslautern, Germany
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38
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Li X, Wang H, Tong W, Feng L, Wang L, Rahman SU, Wei G, Tao S. Exploring the evolutionary dynamics of Rhizobium plasmids through bipartite network analysis. Environ Microbiol 2019; 22:934-951. [PMID: 31361937 DOI: 10.1111/1462-2920.14762] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2019] [Revised: 06/24/2019] [Accepted: 07/25/2019] [Indexed: 10/26/2022]
Abstract
The genus Rhizobium usually has a multipartite genome architecture with a chromosome and several plasmids, making these bacteria a perfect candidate for plasmid biology studies. As there are no universally shared genes among typical plasmids, network analyses can complement traditional phylogenetics in a broad-scale study of plasmid evolution. Here, we present an exhaustive analysis of 216 plasmids from 49 complete genomes of Rhizobium by constructing a bipartite network that consists of two classes of nodes, the plasmids and homologous protein families that connect them. Dissection of the network using a hierarchical clustering strategy reveals extensive variety, with 34 homologous plasmid clusters. Four large clusters including one cluster of symbiotic plasmids and two clusters of chromids carrying some truly essential genes are widely distributed among Rhizobium. In contrast, the other clusters are quite small and rare. Symbiotic clusters and rare accessory clusters are exogenetic and do not appear to have co-evolved with the common accessory clusters; the latter ones have a large coding potential and functional complementarity for different lifestyles in Rhizobium. The bipartite network also provides preliminary evidence of Rhizobium plasmid variation and formation including genetic exchange, plasmid fusion and fission, exogenetic plasmid transfer, host plant selection, and environmental adaptation.
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Affiliation(s)
- Xiangchen Li
- State Key Laboratory of Crop Stress Biology in Arid Areas, Shaanxi Key Laboratory of Agricultural and Environmental Microbiology, College of Life Sciences, Northwest A&F University, Yangling, Shaanxi, 712100, China.,Bioinformatics Center, Northwest A&F University, Yangling, Shaanxi, 712100, China
| | - Hao Wang
- State Key Laboratory of Crop Stress Biology in Arid Areas, Shaanxi Key Laboratory of Agricultural and Environmental Microbiology, College of Life Sciences, Northwest A&F University, Yangling, Shaanxi, 712100, China.,Bioinformatics Center, Northwest A&F University, Yangling, Shaanxi, 712100, China
| | - Wenjun Tong
- State Key Laboratory of Crop Stress Biology in Arid Areas, Shaanxi Key Laboratory of Agricultural and Environmental Microbiology, College of Life Sciences, Northwest A&F University, Yangling, Shaanxi, 712100, China
| | - Li Feng
- College of Enology, Northwest A&F University, Yangling, Shaanxi, 712100, China
| | - Lina Wang
- State Key Laboratory of Crop Stress Biology in Arid Areas, Shaanxi Key Laboratory of Agricultural and Environmental Microbiology, College of Life Sciences, Northwest A&F University, Yangling, Shaanxi, 712100, China.,Bioinformatics Center, Northwest A&F University, Yangling, Shaanxi, 712100, China
| | - Siddiq Ur Rahman
- State Key Laboratory of Crop Stress Biology in Arid Areas, Shaanxi Key Laboratory of Agricultural and Environmental Microbiology, College of Life Sciences, Northwest A&F University, Yangling, Shaanxi, 712100, China.,Bioinformatics Center, Northwest A&F University, Yangling, Shaanxi, 712100, China.,Department of Computer Science and Bioinformatics, Khushal Khan Khattak University, Karak, Khyber Pakhtunkhwa, 27200, Pakistan
| | - Gehong Wei
- State Key Laboratory of Crop Stress Biology in Arid Areas, Shaanxi Key Laboratory of Agricultural and Environmental Microbiology, College of Life Sciences, Northwest A&F University, Yangling, Shaanxi, 712100, China
| | - Shiheng Tao
- State Key Laboratory of Crop Stress Biology in Arid Areas, Shaanxi Key Laboratory of Agricultural and Environmental Microbiology, College of Life Sciences, Northwest A&F University, Yangling, Shaanxi, 712100, China.,Bioinformatics Center, Northwest A&F University, Yangling, Shaanxi, 712100, China
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39
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Viruses as key reservoirs of antibiotic resistance genes in the environment. ISME JOURNAL 2019; 13:2856-2867. [PMID: 31358910 DOI: 10.1038/s41396-019-0478-9] [Citation(s) in RCA: 49] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/07/2019] [Revised: 06/03/2019] [Accepted: 06/21/2019] [Indexed: 11/08/2022]
Abstract
Antibiotic resistance is a rapidly growing health care problem globally and causes many illnesses and deaths. Bacteria can acquire antibiotic resistance genes (ARGs) by horizontal transfer mediated by mobile genetic elements, where the role of phages in their dissemination in natural environments has not yet been clearly resolved. From metagenomic studies, we showed that the mean proportion of predicted ARGs found in prophages (0-0.0028%) was lower than those present in the free viruses (0.001-0.1%). Beta-lactamase, from viruses in the swine gut, represented 0.10 % of the predicted genes. Overall, in the environment, the ARG distribution associated with viruses was strongly linked to human activity, and the low dN/dS ratio observed advocated for a negative selection of the ARGs harbored by the viruses. Our network approach showed that viruses were linked to putative pathogens (Enterobacterales and vibrionaceae) and were considered key vehicles in ARG transfer, similar to plasmids. Therefore, these ARGs could then be disseminated at larger temporal and spatial scales than those included in the bacterial genomes, allowing for time-delayed genetic exchanges.
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40
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Lannes R, Olsson-Francis K, Lopez P, Bapteste E. Carbon Fixation by Marine Ultrasmall Prokaryotes. Genome Biol Evol 2019; 11:1166-1177. [PMID: 30903144 PMCID: PMC6475129 DOI: 10.1093/gbe/evz050] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/04/2019] [Indexed: 12/12/2022] Open
Abstract
Autotrophic carbon fixation is a crucial process for sustaining life on Earth. To date, six pathways, the Calvin–Benson–Bassham cycle, the reductive tricarboxylic acid cycle, the 3-hydroxypropionate bi-cycle, the Wood–Ljungdahl pathway, the dicarboxylate/4-hydroxybutyrate cycle, and the 4-hydroxybutyrate cycle, have been described. Nano-organisms such as members of the Candidate Phyla Radiation (CPR) bacterial superphylum and the Diapherotrites, Parvarchaeota, Aenigmarchaeota, Nanoarchaeota, Nanohalorchaeota (DPANN) archaeal superphylum could deeply impact carbon cycling and carbon fixation in ways that are still to be determined. CPR and DPANN are ubiquitous in the environment but understudied; their gene contents are not exhaustively described; and their metabolisms are not yet fully understood. Here, the completeness of each of the above pathways was quantified and tested for the presence of all key enzymes in nano-organisms from across the World Ocean. The novel marine ultrasmall prokaryotes were demonstrated to collectively harbor the genes required for carbon fixation, in particular the “energetically efficient” dicarboxylate/4-hydroxybutyrate pathway and the 4-hydroxybutyrate pathway. This contrasted with the known carbon metabolic pathways associated with CPR members in aquifers, where they are described as degraders (Castelle CJ, et al. 2015. Genomic expansion of domain archaea highlights roles for organisms from new phyla in anaerobic carbon cycling. Curr Biol. 25(6):690–701; Castelle CJ, et al. 2018. Biosynthetic capacity, metabolic variety and unusual biology in the CPR and DPANN radiations. Nat Rev Microbiol. 16(10):629–645; Anantharaman K, et al. 2016. Thousands of microbial genomes shed light on interconnected biogeochemical processes in an aquifer system. Nat Commun. 7:13219.). Our findings suggest that nano-organisms have a broader contribution to carbon fixation and cycling than currently assumed. Furthermore, CPR and DPANN superphyla are possibly not the only nanosized prokaryotes; therefore, the discovery of new autotrophic marine nano-organisms by future single cell genomics is anticipated.
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Affiliation(s)
- Romain Lannes
- Sorbonne Université, Institut de Systématique, Evolution, Biodiversité (ISYEB), Sorbonne Université, CNRS, Museum National d'Histoire Naturelle, EPHE, Université des Antilles, Paris, France
| | - Karen Olsson-Francis
- School of Environment, Earth and Ecosystems, The Open University, Milton Keynes, United Kingdom
| | - Philippe Lopez
- Institut de Systématique, Evolution, Biodiversité (ISYEB), Sorbonne Université, CNRS, Museum National d'Histoire Naturelle, EPHE, Université des Antilles, Paris, France
| | - Eric Bapteste
- Institut de Systématique, Evolution, Biodiversité (ISYEB), Sorbonne Université, CNRS, Museum National d'Histoire Naturelle, EPHE, Université des Antilles, Paris, France
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41
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Corel E, Méheust R, Watson AK, McInerney JO, Lopez P, Bapteste E. Bipartite Network Analysis of Gene Sharings in the Microbial World. Mol Biol Evol 2019; 35:899-913. [PMID: 29346651 PMCID: PMC5888944 DOI: 10.1093/molbev/msy001] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022] Open
Abstract
Extensive microbial gene flows affect how we understand virology, microbiology, medical sciences, genetic modification, and evolutionary biology. Phylogenies only provide a narrow view of these gene flows: plasmids and viruses, lacking core genes, cannot be attached to cellular life on phylogenetic trees. Yet viruses and plasmids have a major impact on cellular evolution, affecting both the gene content and the dynamics of microbial communities. Using bipartite graphs that connect up to 149,000 clusters of homologous genes with 8,217 related and unrelated genomes, we can in particular show patterns of gene sharing that do not map neatly with the organismal phylogeny. Homologous genes are recycled by lateral gene transfer, and multiple copies of homologous genes are carried by otherwise completely unrelated (and possibly nested) genomes, that is, viruses, plasmids and prokaryotes. When a homologous gene is present on at least one plasmid or virus and at least one chromosome, a process of "gene externalization," affected by a postprocessed selected functional bias, takes place, especially in Bacteria. Bipartite graphs give us a view of vertical and horizontal gene flow beyond classic taxonomy on a single very large, analytically tractable, graph that goes beyond the cellular Web of Life.
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Affiliation(s)
- Eduardo Corel
- Unité Mixte de Recherche 7138 Evolution Paris-Seine, Centre National de la Recherche Scientifique, Institut de Biologie Paris-Seine, Sorbonne Université, Université Pierre et Marie Curie, Paris, France
| | - Raphaël Méheust
- Unité Mixte de Recherche 7138 Evolution Paris-Seine, Centre National de la Recherche Scientifique, Institut de Biologie Paris-Seine, Sorbonne Université, Université Pierre et Marie Curie, Paris, France
| | - Andrew K Watson
- Unité Mixte de Recherche 7138 Evolution Paris-Seine, Centre National de la Recherche Scientifique, Institut de Biologie Paris-Seine, Sorbonne Université, Université Pierre et Marie Curie, Paris, France
| | - James O McInerney
- Chair in Evolutionary Biology, The University of Manchester, United Kingdom
| | - Philippe Lopez
- Unité Mixte de Recherche 7138 Evolution Paris-Seine, Centre National de la Recherche Scientifique, Institut de Biologie Paris-Seine, Sorbonne Université, Université Pierre et Marie Curie, Paris, France
| | - Eric Bapteste
- Unité Mixte de Recherche 7138 Evolution Paris-Seine, Centre National de la Recherche Scientifique, Institut de Biologie Paris-Seine, Sorbonne Université, Université Pierre et Marie Curie, Paris, France
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Pathmanathan JS, Lopez P, Lapointe FJ, Bapteste E. CompositeSearch: A Generalized Network Approach for Composite Gene Families Detection. Mol Biol Evol 2019; 35:252-255. [PMID: 29092069 PMCID: PMC5850286 DOI: 10.1093/molbev/msx283] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
Genes evolve by point mutations, but also by shuffling, fusion, and fission of genetic fragments. Therefore, similarity between two sequences can be due to common ancestry producing homology, and/or partial sharing of component fragments. Disentangling these processes is especially challenging in large molecular data sets, because of computational time. In this article, we present CompositeSearch, a memory-efficient, fast, and scalable method to detect composite gene families in large data sets (typically in the range of several million sequences). CompositeSearch generalizes the use of similarity networks to detect composite and component gene families with a greater recall, accuracy, and precision than recent programs (FusedTriplets and MosaicFinder). Moreover, CompositeSearch provides user-friendly quality descriptions regarding the distribution and primary sequence conservation of these gene families allowing critical biological analyses of these data.
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Affiliation(s)
| | - Philippe Lopez
- Institut de Biologie Paris-Seine (IBPS), UPMC Université Paris 06, Sorbonne Universités, Paris, France
| | | | - Eric Bapteste
- Institut de Biologie Paris-Seine (IBPS), UPMC Université Paris 06, Sorbonne Universités, Paris, France
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Sanaa M, Pouillot R, Vega FG, Strain E, Van Doren JM. GenomeGraphR: A user-friendly open-source web application for foodborne pathogen whole genome sequencing data integration, analysis, and visualization. PLoS One 2019; 14:e0213039. [PMID: 30818354 PMCID: PMC6394949 DOI: 10.1371/journal.pone.0213039] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2018] [Accepted: 02/13/2019] [Indexed: 11/18/2022] Open
Abstract
Food safety risk assessments and large-scale epidemiological investigations have the potential to provide better and new types of information when whole genome sequence (WGS) data are effectively integrated. Today, the NCBI Pathogen Detection database WGS collections have grown significantly through improvements in technology, coordination, and collaboration, such as the GenomeTrakr and PulseNet networks. However, high-quality genomic data is not often coupled with high-quality epidemiological or food chain metadata. We have created a set of tools for cleaning, curation, integration, analysis and visualization of microbial genome sequencing data. It has been tested using Salmonella enterica and Listeria monocytogenes data sets provided by NCBI Pathogen Detection (160,000 sequenced isolates in 2018). GenomeGraphR presents foodborne pathogen WGS data and associated curated metadata in a user-friendly interface that allows a user to query a variety of research questions such as, transmission sources and dynamics, global reach, and persistence of genotypes associated with contamination in the food supply and foodborne illness across time or space. The application is freely available (https://fda-riskmodels.foodrisk.org/genomegraphr/).
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Affiliation(s)
- Moez Sanaa
- Center for Food Safety and Applied Nutrition, Food and Drug Administration, College Park, Maryland, United States of America
| | - Régis Pouillot
- Center for Food Safety and Applied Nutrition, Food and Drug Administration, College Park, Maryland, United States of America
- * E-mail:
| | - Francisco Garcés Vega
- Center for Food Safety and Applied Nutrition, Food and Drug Administration, College Park, Maryland, United States of America
| | - Errol Strain
- Center for Food Safety and Applied Nutrition, Food and Drug Administration, College Park, Maryland, United States of America
| | - Jane M. Van Doren
- Center for Food Safety and Applied Nutrition, Food and Drug Administration, College Park, Maryland, United States of America
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Ocaña-Pallarès E, Najle SR, Scazzocchio C, Ruiz-Trillo I. Reticulate evolution in eukaryotes: Origin and evolution of the nitrate assimilation pathway. PLoS Genet 2019; 15:e1007986. [PMID: 30789903 PMCID: PMC6400420 DOI: 10.1371/journal.pgen.1007986] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2018] [Revised: 03/05/2019] [Accepted: 01/25/2019] [Indexed: 01/17/2023] Open
Abstract
Genes and genomes can evolve through interchanging genetic material, this leading to reticular evolutionary patterns. However, the importance of reticulate evolution in eukaryotes, and in particular of horizontal gene transfer (HGT), remains controversial. Given that metabolic pathways with taxonomically-patchy distributions can be indicative of HGT events, the eukaryotic nitrate assimilation pathway is an ideal object of investigation, as previous results revealed a patchy distribution and suggested that the nitrate assimilation cluster of dikaryotic fungi (Opisthokonta) could have been originated and transferred from a lineage leading to Oomycota (Stramenopiles). We studied the origin and evolution of this pathway through both multi-scale bioinformatic and experimental approaches. Our taxon-rich genomic screening shows that nitrate assimilation is present in more lineages than previously reported, although being restricted to autotrophs and osmotrophs. The phylogenies indicate a pervasive role of HGT, with three bacterial transfers contributing to the pathway origin, and at least seven well-supported transfers between eukaryotes. In particular, we propose a distinct and more complex HGT path between Opisthokonta and Stramenopiles than the one previously suggested, involving at least two transfers of a nitrate assimilation gene cluster. We also found that gene fusion played an essential role in this evolutionary history, underlying the origin of the canonical eukaryotic nitrate reductase, and of a chimeric nitrate reductase in Ichthyosporea (Opisthokonta). We show that the ichthyosporean pathway, including this novel nitrate reductase, is physiologically active and transcriptionally co-regulated, responding to different nitrogen sources; similarly to distant eukaryotes with independent HGT-acquisitions of the pathway. This indicates that this pattern of transcriptional control evolved convergently in eukaryotes, favoring the proper integration of the pathway in the metabolic landscape. Our results highlight the importance of reticulate evolution in eukaryotes, by showing the crucial contribution of HGT and gene fusion in the evolutionary history of the nitrate assimilation pathway. One of the most relevant findings in evolution was that lineages, either genes or genomes, can evolve through interchanging genetic material. For example, exon shuffling can lead to genes with complete novel functions, and genomes can acquire novel functionalities by means of horizontal gene transfer (HGT). Whereas HGT is known to be an important driver of metabolic remodelling and ecological adaptations in Bacteria, its importance and prevalence in eukaryotes remains controversial. We show that HGT played a major role in the origin and evolution of the eukaryotic nitrate assimilation pathway, with several bacteria-to-eukaryote and eukaryote-to-eukaryote transfers promoting the acquisition of this ecologically-relevant pathway to autotrophs and to distinct groups of osmotrophs. Moreover, we also show that gene fusion was important in this evolutionary history, underlying the origin of the canonical eukaryotic nitrate reductase, but also of a non-canonical nitrate reductase that we describe in Ichthyosporea, a poorly-characterized eukaryotic group that includes many parasitic species. In conclusion, our results highlight the importance of reticulate evolution in eukaryotes, by showing the contribution of HGT and gene fusion in the evolutionary history of the nitrate assimilation pathway.
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Affiliation(s)
- Eduard Ocaña-Pallarès
- Institut de Biologia Evolutiva (CSIC-Universitat Pompeu Fabra), Barcelona, Catalonia, Spain
- * E-mail: (EOP); (IRT)
| | - Sebastián R. Najle
- Institut de Biologia Evolutiva (CSIC-Universitat Pompeu Fabra), Barcelona, Catalonia, Spain
- Instituto de Biología Molecular y Celular de Rosario (IBR-CONICET) and Facultad de Ciencias Bioquímicas y Farmacéuticas, Universidad Nacional de Rosario, Ocampo y Esmeralda s/n, Rosario S2000FHQ, Argentina
| | - Claudio Scazzocchio
- Department of Microbiology, Imperial College, London, United Kingdom
- Institute for Integrative Biology of the Cell (I2BC), Gif-sur-Yvette, France
| | - Iñaki Ruiz-Trillo
- Institut de Biologia Evolutiva (CSIC-Universitat Pompeu Fabra), Barcelona, Catalonia, Spain
- Departament de Genètica, Microbiologia i Estadística, Facultat de Biologia, Institut de Recerca de la Biodiversitat (IRBio), Universitat de Barcelona (UB), Barcelona, Catalonia, Spain
- ICREA, Barcelona, Catalonia, Spain
- * E-mail: (EOP); (IRT)
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Gross F, Kranke N, Meunier R. Pluralization through epistemic competition: scientific change in times of data-intensive biology. HISTORY AND PHILOSOPHY OF THE LIFE SCIENCES 2019; 41:1. [PMID: 30603778 DOI: 10.1007/s40656-018-0239-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/10/2017] [Accepted: 12/17/2018] [Indexed: 06/09/2023]
Abstract
We present two case studies from contemporary biology in which we observe conflicts between established and emerging approaches. The first case study discusses the relation between molecular biology and systems biology regarding the explanation of cellular processes, while the second deals with phylogenetic systematics and the challenge posed by recent network approaches to established ideas of evolutionary processes. We show that the emergence of new fields is in both cases driven by the development of high-throughput data generation technologies and the transfer of modeling techniques from other fields. New and emerging views are characterized by different philosophies of nature, i.e. by different ontological and methodological assumptions and epistemic values and virtues. This results in a kind of conflict we call "epistemic competition" that manifests in two ways: On the one hand, opponents engage in mutual critique and defense of their fundamental assumptions. On the other hand, they compete for the acceptance and integration of the knowledge they provide by a broader scientific community. Despite an initial rhetoric of replacement, the views as well as the respective audiences come to be seen as more clearly distinct during the course of the debate. Hence, we observe-contrary to many other accounts of scientific change-that conflict results in the formation of new niches of research, leading to co-existence and perceived complementarity of approaches. Our model thus contributes to the understanding of the pluralization of the scientific landscape.
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Affiliation(s)
- Fridolin Gross
- Institut für Philosophie, Universität Kassel, Henschelstr. 2, 34127, Kassel, Germany
| | - Nina Kranke
- Philosophisches Seminar, Westfälische Wilhelms-Universität Münster, Domplatz 23, 48143, Münster, Germany.
| | - Robert Meunier
- Institut für Philosophie, Universität Kassel, Henschelstr. 2, 34127, Kassel, Germany
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Watson AK, Lannes R, Pathmanathan JS, Méheust R, Karkar S, Colson P, Corel E, Lopez P, Bapteste E. The Methodology Behind Network Thinking: Graphs to Analyze Microbial Complexity and Evolution. Methods Mol Biol 2019; 1910:271-308. [PMID: 31278668 DOI: 10.1007/978-1-4939-9074-0_9] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
In the post genomic era, large and complex molecular datasets from genome and metagenome sequencing projects expand the limits of what is possible for bioinformatic analyses. Network-based methods are increasingly used to complement phylogenetic analysis in studies in molecular evolution, including comparative genomics, classification, and ecological studies. Using network methods, the vertical and horizontal relationships between all genes or genomes, whether they are from cellular chromosomes or mobile genetic elements, can be explored in a single expandable graph. In recent years, development of new methods for the construction and analysis of networks has helped to broaden the availability of these approaches from programmers to a diversity of users. This chapter introduces the different kinds of networks based on sequence similarity that are already available to tackle a wide range of biological questions, including sequence similarity networks, gene-sharing networks and bipartite graphs, and a guide for their construction and analyses.
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Affiliation(s)
- Andrew K Watson
- Sorbonne Universités, Institut de Biologie Paris-Seine, UPMC Université Paris 6, Paris, France
| | - Romain Lannes
- Sorbonne Universités, Institut de Biologie Paris-Seine, UPMC Université Paris 6, Paris, France
| | - Jananan S Pathmanathan
- Sorbonne Universités, Institut de Biologie Paris-Seine, UPMC Université Paris 6, Paris, France
| | - Raphaël Méheust
- Sorbonne Universités, Institut de Biologie Paris-Seine, UPMC Université Paris 6, Paris, France
| | - Slim Karkar
- Sorbonne Universités, Institut de Biologie Paris-Seine, UPMC Université Paris 6, Paris, France
- Department of Ecology, Evolution, and Natural Resources, School of Environmental and Biological Sciences, Rutgers, The State University of NJ, New Brunswick, NJ, USA
| | - Philippe Colson
- Fondation Institut Hospitalo-Universitaire Méditerranée Infection, Pôle des Maladies Infectieuses et Tropicales Clinique et Biologique, Fédération de Bactériologie-Hygiène-Virologie, Centre Hospitalo-Universitaire Tione, Assistance Publique-Hôpitaux de Marseille, Marseille, France
- Unité de Recherche sur les Maladies Infectieuses et Tropicales Emergentes (URMITE) UM63, CNRS 7278, IRD 198, INSERM U1095, Aix-Marseille University, Marseille, France
| | - Eduardo Corel
- Sorbonne Universités, Institut de Biologie Paris-Seine, UPMC Université Paris 6, Paris, France
| | - Philippe Lopez
- Sorbonne Universités, Institut de Biologie Paris-Seine, UPMC Université Paris 6, Paris, France
| | - Eric Bapteste
- Sorbonne Universités, Institut de Biologie Paris-Seine, UPMC Université Paris 6, Paris, France.
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Abstract
Understanding how an animal organism and its gut microbes form an integrated biological organization, known as a holobiont, is becoming a central issue in biological studies. Such an organization inevitably involves a complex web of transmission processes that occur on different scales in time and space, across microbes and hosts. Network-based models are introduced in this chapter to tackle aspects of this complexity and to better take into account vertical and horizontal dimensions of transmission. Two types of network-based models are presented, sequence similarity networks and bipartite graphs. One interest of these networks is that they can consider a rich diversity of important players in microbial evolution that are usually excluded from evolutionary studies, like plasmids and viruses. These methods bring forward the notion of "gene externalization," which is defined as the presence of redundant copies of prokaryotic genes on mobile genetic elements (MGEs), and therefore emphasizes a related although distinct process from lateral gene transfer between microbial cells. This chapter introduces guidelines to the construction of these networks, reviews their analysis, and illustrates their possible biological interpretations and uses. The application to human gut microbiomes shows that sequences present in a higher diversity of MGEs have both biased functions and a broader microbial and human host range. These results suggest that an "externalized gut metagenome" is partly common to humans and benefits the gut microbial community. We conclude that testing relationships between microbial genes, microbes, and their animal hosts, using network-based methods, could help to unravel additional mechanisms of transmission in holobionts.
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Corel E, Pathmanathan JS, Watson AK, Karkar S, Lopez P, Bapteste E. MultiTwin: A Software Suite to Analyze Evolution at Multiple Levels of Organization Using Multipartite Graphs. Genome Biol Evol 2018; 10:2777-2784. [PMID: 30247672 PMCID: PMC6199892 DOI: 10.1093/gbe/evy209] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/19/2018] [Indexed: 01/08/2023] Open
Abstract
The inclusion of introgressive processes in evolutionary studies induces a less constrained view of evolution. Network-based methods (like large-scale similarity networks) allow to include in comparative genomics all extrachromosomic carriers (like viruses, the most abundant biological entities on the planet) with their cellular hosts. The integration of several levels of biological organization (genes, genomes, communities, environments) enables more comprehensive analyses of gene sharing and improved sequence-based classifications. However, the algorithmic tools for the analysis of such networks are usually restricted to people with high programming skills. We present an integrated suite of software tools named MultiTwin, aimed at the construction, structuring, and analysis of multipartite graphs for evolutionary biology. Typically, this kind of graph is useful for the comparative analysis of the gene content of genomes in microbial communities from the environment and for exploring patterns of gene sharing, for example between distantly related cellular genomes, pangenomes, or between cellular genomes and their mobile genetic elements. We illustrate the use of this tool with an application of the bipartite approach (using gene family-genome graphs) for the analysis of pathogenicity traits in prokaryotes.
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Affiliation(s)
- Eduardo Corel
- Unité Mixte de Recherche, Centre National de la Recherche Scientifique, Institut de Biologie Paris-Seine, Université Pierre et Marie Curie, Sorbonne Université, Paris, France
| | - Jananan S Pathmanathan
- Unité Mixte de Recherche, Centre National de la Recherche Scientifique, Institut de Biologie Paris-Seine, Université Pierre et Marie Curie, Sorbonne Université, Paris, France
| | - Andrew K Watson
- Unité Mixte de Recherche, Centre National de la Recherche Scientifique, Institut de Biologie Paris-Seine, Université Pierre et Marie Curie, Sorbonne Université, Paris, France
| | - Slim Karkar
- Unité Mixte de Recherche, Centre National de la Recherche Scientifique, Institut de Biologie Paris-Seine, Université Pierre et Marie Curie, Sorbonne Université, Paris, France
| | - Philippe Lopez
- Unité Mixte de Recherche, Centre National de la Recherche Scientifique, Institut de Biologie Paris-Seine, Université Pierre et Marie Curie, Sorbonne Université, Paris, France
| | - Eric Bapteste
- Unité Mixte de Recherche, Centre National de la Recherche Scientifique, Institut de Biologie Paris-Seine, Université Pierre et Marie Curie, Sorbonne Université, Paris, France
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Aiewsakun P, Adriaenssens EM, Lavigne R, Kropinski AM, Simmonds P. Evaluation of the genomic diversity of viruses infecting bacteria, archaea and eukaryotes using a common bioinformatic platform: steps towards a unified taxonomy. J Gen Virol 2018; 99:1331-1343. [PMID: 30016225 PMCID: PMC6230767 DOI: 10.1099/jgv.0.001110] [Citation(s) in RCA: 59] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2018] [Accepted: 06/13/2018] [Indexed: 01/01/2023] Open
Abstract
Genome Relationship Applied to Virus Taxonomy (GRAViTy) is a genetics-based tool that computes sequence relatedness between viruses. Composite generalized Jaccard (CGJ) distances combine measures of homology between encoded viral genes and similarities in genome organizational features (gene orders and orientations). This scoring framework effectively recapitulates the current, largely morphology and phenotypic-based, family-level classification of eukaryotic viruses. Eukaryotic virus families typically formed monophyletic groups with consistent CGJ distance cut-off dividing between and within family divergence ranges. In the current study, a parallel analysis of prokaryotic virus families revealed quite different sequence relationships, particularly those of tailed phage families (Siphoviridae, Myoviridae and Podoviridae), where members of the same family were generally far more divergent and often not detectably homologous to each other. Analysis of the 20 currently classified prokaryotic virus families indeed split them into 70 separate clusters of tailed phages genetically equivalent to family-level assignments of eukaryotic viruses. It further divided several bacterial (Sphaerolipoviridae, Tectiviridae) and archaeal (Lipothrixviridae) families. We also found that the subfamily-level groupings of tailed phages were generally more consistent with the family assignments of eukaryotic viruses, and this supports ongoing reclassifications, including Spounavirinae and Vi1virus taxa as new virus families. The current study applied a common benchmark with which to compare taxonomies of eukaryotic and prokaryotic viruses. The findings support the planned shift away from traditional morphology-based classifications of prokaryotic viruses towards a genome-based taxonomy. They demonstrate the feasibility of a unified taxonomy of viruses into which the vast body of metagenomic viral sequences may be consistently assigned.
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Affiliation(s)
- Pakorn Aiewsakun
- Nuffield Department of Medicine, University of Oxford, Peter Medawar Building, South Parks, Oxford, OX1 3SY, UK
- Department of Microbiology, Faculty of Science, Mahidol University, Bangkok, 10400, Thailand
| | - Evelien M. Adriaenssens
- Institute of Integrative Biology, University of Liverpool, Biosciences Building, Crown Street, L69 7ZB Liverpool, UK
| | - Rob Lavigne
- Department of Biosystems, Laboratory of Gene Technology, KU Leuven. Kasteelpark Arenberg 21, Box 2462, 3001 Leuven, Belgium
| | - Andrew M. Kropinski
- Departments of Food Science, and Pathobiology, University of Guelph, 50 Stone Rd E, Guelph, ON, N1G 2W1, Canada
| | - Peter Simmonds
- Nuffield Department of Medicine, University of Oxford, Peter Medawar Building, South Parks, Oxford, OX1 3SY, UK
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Abstract
BACKGROUND Deciphering the history of life on Earth has long been regarded as one of the most central tasks in biology. In past years, widespread discordance between the evolutionary histories of different groups of orthologous genes of prokaryotes have been revealed, primarily due to horizontal gene transfers (HGTs). Nonetheless, evidence that support a strong tree-like signal of evolution have been uncovered, despite the presence of HGT events. Therefore, a challenging task is to distill this tree-like signal from the noise induced by all sources of non-tree-like events. RESULTS In this work we tackle this question, using real and simulated data. We first tighten a recent related theoretical result in this field. In a simulation study, we infer individual quartet topologies, and then use the inferred quartets to reconstruct simulated species trees. We demonstrate that accurate tree reconstruction is feasible despite surprisingly high rates of HGT. In a real data study, we construct phylogenies of two sets of prokaryotes, and show that our tree reconstruction scheme is comparable with (and complementary better than) other commonly used methods. CONCLUSIONS Using a blend of theoretical and empirical investigations, our study proves the feasibility of accurate quartet-based phylogenetic reconstruction, the vast impact of HGT events notwithstanding.
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Affiliation(s)
- Eliran Avni
- Department of Evolutionary Biology, University of Haifa, 199 Aba Khoushy Ave. Mount Carmel, Haifa, 3498838, Israel
| | - Sagi Snir
- Department of Evolutionary Biology, University of Haifa, 199 Aba Khoushy Ave. Mount Carmel, Haifa, 3498838, Israel.
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