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      At the Gate of Mutualism: Identification of Genomic Traits Predisposing to Insect-Bacterial Symbiosis in Pathogenic Strains of the Aphid Symbiont Serratia symbiotica

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          Abstract

          Mutualistic associations between insects and heritable bacterial symbionts are ubiquitous in nature. The aphid symbiont Serratia symbiotica is a valuable candidate for studying the evolution of bacterial symbiosis in insects because it includes a wide diversity of strains that reflect the diverse relationships in which bacteria can be engaged with insects, from pathogenic interactions to obligate intracellular mutualism. The recent discovery of culturable strains, which are hypothesized to resemble the ancestors of intracellular strains, provide an opportunity to study the mechanisms underlying bacterial symbiosis in its early stages. In this study, we analyzed the genomes of three of these culturable strains that are pathogenic to aphid hosts, and performed comparative genomic analyses including mutualistic host-dependent strains. All three genomes are larger than those of the host-restricted S. symbiotica strains described so far, and show significant enrichment in pseudogenes and mobile elements, suggesting that these three pathogenic strains are in the early stages of the adaptation to their host. Compared to their intracellular mutualistic relatives, the three strains harbor a greater diversity of genes coding for virulence factors and metabolic pathways, suggesting that they are likely adapted to infect new hosts and are a potential source of metabolic innovation for insects. The presence in their genomes of secondary metabolism gene clusters associated with the production of antimicrobial compounds and phytotoxins supports the hypothesis that S. symbiotia symbionts evolved from plant-associated strains and that plants may serve as intermediate hosts. Mutualistic associations between insects and bacteria are the result of independent transitions to endosymbiosis initiated by the acquisition of environmental progenitors. In this context, the genomes of free-living S. symbiotica strains provide a rare opportunity to study the inventory of genes held by bacterial associates of insects that are at the gateway to a host-dependent lifestyle.

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          IQ-TREE: A Fast and Effective Stochastic Algorithm for Estimating Maximum-Likelihood Phylogenies

          Large phylogenomics data sets require fast tree inference methods, especially for maximum-likelihood (ML) phylogenies. Fast programs exist, but due to inherent heuristics to find optimal trees, it is not clear whether the best tree is found. Thus, there is need for additional approaches that employ different search strategies to find ML trees and that are at the same time as fast as currently available ML programs. We show that a combination of hill-climbing approaches and a stochastic perturbation method can be time-efficiently implemented. If we allow the same CPU time as RAxML and PhyML, then our software IQ-TREE found higher likelihoods between 62.2% and 87.1% of the studied alignments, thus efficiently exploring the tree-space. If we use the IQ-TREE stopping rule, RAxML and PhyML are faster in 75.7% and 47.1% of the DNA alignments and 42.2% and 100% of the protein alignments, respectively. However, the range of obtaining higher likelihoods with IQ-TREE improves to 73.3-97.1%.
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            ModelFinder: Fast Model Selection for Accurate Phylogenetic Estimates

            Model-based molecular phylogenetics plays an important role in comparisons of genomic data, and model selection is a key step in all such analyses. We present ModelFinder, a fast model-selection method that greatly improves the accuracy of phylogenetic estimates. The improvement is achieved by incorporating a model of rate-heterogeneity across sites not previously considered in this context, and by allowing concurrent searches of model-space and tree-space.
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              Unicycler: Resolving bacterial genome assemblies from short and long sequencing reads

              The Illumina DNA sequencing platform generates accurate but short reads, which can be used to produce accurate but fragmented genome assemblies. Pacific Biosciences and Oxford Nanopore Technologies DNA sequencing platforms generate long reads that can produce complete genome assemblies, but the sequencing is more expensive and error-prone. There is significant interest in combining data from these complementary sequencing technologies to generate more accurate “hybrid” assemblies. However, few tools exist that truly leverage the benefits of both types of data, namely the accuracy of short reads and the structural resolving power of long reads. Here we present Unicycler, a new tool for assembling bacterial genomes from a combination of short and long reads, which produces assemblies that are accurate, complete and cost-effective. Unicycler builds an initial assembly graph from short reads using the de novo assembler SPAdes and then simplifies the graph using information from short and long reads. Unicycler uses a novel semi-global aligner to align long reads to the assembly graph. Tests on both synthetic and real reads show Unicycler can assemble larger contigs with fewer misassemblies than other hybrid assemblers, even when long-read depth and accuracy are low. Unicycler is open source (GPLv3) and available at github.com/rrwick/Unicycler.
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                Author and article information

                Contributors
                Journal
                Front Cell Infect Microbiol
                Front Cell Infect Microbiol
                Front. Cell. Infect. Microbiol.
                Frontiers in Cellular and Infection Microbiology
                Frontiers Media S.A.
                2235-2988
                29 June 2021
                2021
                : 11
                : 660007
                Affiliations
                [1] 1 Biodiversity Research Centre, Earth and Life Institute, Université catholique de Louvain (UCLouvain) , Louvain-la-Neuve, Belgium
                [2] 2 Institut de Recherche sur la Biologie de l’insecte, UMR 7261, CNRS, Université de Tours , Tours, France
                [3] 3 Center for Applied Molecular Technologies, Institute of Experimental and Clinical Research, Université catholique de Louvain (UCLouvain) , Woluwe-Saint-Lambert, Belgium
                [4] 4 Univ Lyon, INSA-Lyon, INRAE, BF2i, UMR203, F-69621 , Villeurbanne, France
                [5] 5 Louvain Institute of Biomolecular Science and Technology (LIBST), Université catholique de Louvain (UCLouvain) , Louvain-la-Neuve, Belgium
                [6] 6 Walloon Center of Industrial Biology, Université de Liège , Liège, Belgium
                [7] 7 Laboratory of Food and Environmental Microbiology, Earth and Life Institute, Université catholique de Louvain (UCLouvain) , Louvain-la-Neuve, Belgium
                [8] 8 Evolutionary Biology and Ecology, Université Libre de Bruxelles , Brussels, Belgium
                Author notes

                Edited by: Ghassan M. Matar, American University of Beirut, Lebanon

                Reviewed by: Alejandro Manzano Marín, University of Vienna, Austria; Mira El Chaar, University of Balamand, Lebanon

                *Correspondence: François Renoz, francois.renoz@ 123456uclouvain.be

                This article was submitted to Molecular Bacterial Pathogenesis, a section of the journal Frontiers in Cellular and Infection Microbiology

                Article
                10.3389/fcimb.2021.660007
                8275996
                34268133
                ec3a4d21-9713-4e8c-b1a0-6e63d40cd77b
                Copyright © 2021 Renoz, Foray, Ambroise, Baa-Puyoulet, Bearzatto, Mendez, Grigorescu, Mahillon, Mardulyn, Gala, Calevro and Hance

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 28 January 2021
                : 14 June 2021
                Page count
                Figures: 6, Tables: 0, Equations: 0, References: 152, Pages: 18, Words: 7985
                Funding
                Funded by: Fonds De La Recherche Scientifique - FNRS 10.13039/501100002661
                Categories
                Cellular and Infection Microbiology
                Original Research

                Infectious disease & Microbiology
                aphid symbiont,bacterial mutualism,genome evolution,metabolic pathways,pathogen,secretion systems,serratia symbiotica,virulence factors

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