17 research outputs found
The Evolutionary Success of the Marine Bacterium SAR11 Analyzed through a Metagenomic Perspective
The SAR11 clade of Alphaproteobacteria is the most abundant group of planktonic cells in the near-surface epipelagic waters of the ocean, but the mechanisms underlying its exceptional success have not been fully elucidated. Here, we applied a metagenomic approach to explore microdiversity patterns by measuring the accumulation of synonymous and nonsynonymous mutations as well as homologous recombination in populations of SAR11 from different aquatic habitats (marine epipelagic, bathypelagic, and surface freshwater). The patterns of mutation accumulation and recombination were compared to those of other groups of representative marine microbes with multiple ecological strategies that share the same marine habitat, namely, Cyanobacteria (Prochlorococcus and Synechococcus), Archaea (“Candidatus Nitrosopelagicus” and Marine Group II Thalassoarchaea), and some heterotrophic marine bacteria (Alteromonas and Erythrobacter). SAR11 populations showed widespread recombination among distantly related members, preventing divergence leading to a genetically stable population. Moreover, their high intrapopulation sequence diversity with an enrichment in synonymous replacements supports the idea of a very ancient divergence and the coexistence of multiple different clones. However, other microbes analyzed seem to follow different evolutionary dynamics where processes of diversification driven by geographic and ecological instability produce a higher number of nonsynonymous replacements and lower intrapopulation sequence diversity. Together, these data shed light on some of the evolutionary and ecological processes that lead to the large genomic diversity in SAR11. Furthermore, this approach can be applied to other similar microbes that are difficult to culture in the laboratory, but abundant in nature, to investigate the underlying dynamics of their genomic evolution.This work was supported by grants VIREVO CGL2016-76273-P (AEI/FEDER, EU) (cofunded with FEDER funds) from the Spanish Ministerio de Economía, Industria, y Competitividad and HIDRAS3 PROMETEU/2019/009 from the Generalitat Valenciana to F.R.-V. and by grants CGL2013-40564-R and SAF2013-49267-EXP from the Spanish Ministerio de Economía, Industria, y Competitividad; grant ACIF/2015/332 from the Generalitat Valenciana; and grant 5334 from the Betty Moore Foundation to M.M.-G. F.R.-V. was also a beneficiary of the 5top100-program of the Ministry for Science and Education of Russia. J.M.H.-M. was supported by a Ph.D. fellowship from the Spanish Ministerio de Economía y Competitividad (BES-2014-067828). F.H.C. was supported by a postdoctoral fellowship from the Generalitat Valenciana (APOSTD/2018/186). M.L.-P. was supported by a postdoctoral fellowship from the Spanish Ministerio de Economía, Industria, y Competitividad (IJCI-2017-34002)
Diversity and Ecology of Aquatic Viruses
Jornada Nous avenços en ecologia microbiana, 4 de febrer de 2022 en BarcelonaPeer reviewe
Machine Learning Applied to Marine Ecology
The need to understand the dynamics of biological communities has never been more pressing. Ecosystems and the biological diversity therein are currently threatened b y anthropogenic impacts. Developing strategies to reduce these impacts is of fundamental importance for the conservation of Earth ́s ecosystems. Doing so depends on the comprehensive and mechanistic understanding of how these ecosystems function, which has been a central goal of ecology. Although undeniable advances have been made, our understanding of the processes driving ecosystem functioning are still limited. This is specially true for the case of mechanistic models that can shed light on these process and also provide reliable predictions for future scenarios. Obtaining such models would allow us to anticipate the extension of anthropogenic impacts at the global scale and also help to develop strategies to mitigate them. [...]Peer reviewe
Metagenomics in polluted aquatic environments
16 p. : il.Metagenomics is defined as the culture-independent genomic analysis of biological
assemblages providing access to the whole set of genes and genomes from a sample. It
encompasses a variety of techniques that are based on (i) total DNA extraction from samples followed by PCR amplification of specific genes, (ii) library construction or amplification and sequencing of the whole genetic material. These methodologies have successfully been applied in studies of composition, dynamics, and functions of microbial communities in a variety of ecosystems including those subjected to anthropogenic modifications (Gilbert & Dupont, 2011).
Culture independent methods allow the analysis of a set of metabolic genes from microbial communities, which can be used to determine how environmental conditions such as pollution can shape community composition and the diversity of genes associated with
biogeochemical cycles such as those of carbon, nitrogen, and phosphorus (Singh et al., 2009).
This approach is also useful for the discovery of novel environmental microorganisms and genes, with important applications for biotechnology, medicine, and bioremediation (Cardoso et al., 2011).
This applicability has resulted in a recent sharp increase in studies focusing in the
metagenomic analysis of polluted sites. Their aim is to characterize microbial communities from a diverse set of environments such as freshwater, marine sediments, open ocean, pelagic ecosystems, soil, and host-associated communities. An example of these initiatives is the Global Ocean Sampling Expedition (GOS), which assessed the genetic diversity of marine microbial communities around the Earth. Since 2003, an enormous amount of data has been generated by GOS helping scientists to reveal the microbial diversity and also allowing them to better understand microbial phylogeny and ecology (Gilbert & Dupont, 2011)
Viruses and Their Interactions With Bacteria and Archaea of Hypersaline Great Salt Lake
18 pages, 5 figures, 2 tables, supplementary material https://www.frontiersin.org/articles/10.3389/fmicb.2021.701414/full#supplementary-material.-- Data Availability Statement: All DNA sequence FASTQ files are deposited in the NCBI Nucleotide Archive under SRR14023866 (CB2 Bacterial and Archaeal), SRR 14023937 (GSL 3510 Bacterial and Archaeal), SRR14023877 (GB14 Bacterial and Archaeal), SRR14023878 (CB2 Viral), SRR14023865 (GSL3510 Viral), and SRR14023938 (GB14 Viral). The Bioproject id is PRJNA714934. The NCBI genome accession numbers for the MAGs and viral assemblies are shown in Supplementary Table S10Viruses play vital biogeochemical and ecological roles by (a) expressing auxiliary metabolic genes during infection, (b) enhancing the lateral transfer of host genes, and (c) inducing host mortality. Even in harsh and extreme environments, viruses are major players in carbon and nutrient recycling from organic matter. However, there is much that we do not yet understand about viruses and the processes mediated by them in the extreme environments such as hypersaline habitats. The Great Salt Lake (GSL) in Utah, United States is a hypersaline ecosystem where the biogeochemical role of viruses is poorly understood. This study elucidates the diversity of viruses and describes virus–host interactions in GSL sediments along a salinity gradient. The GSL sediment virosphere consisted of Haloviruses (32.07 ± 19.33%) and members of families Siphoviridae (39.12 ± 19.8%), Myoviridae (13.7 ± 6.6%), and Podoviridae (5.43 ± 0.64%). Our results demonstrate that salinity alongside the concentration of organic carbon and inorganic nutrients (nitrogen and phosphorus) governs the viral, bacteria, and archaeal diversity in this habitat. Computational host predictions for the GSL viruses revealed a wide host range with a dominance of viruses that infect Proteobacteria, Actinobacteria, and Firmicutes. Identification of auxiliary metabolic genes for photosynthesis (psbA), carbon fixation (rbcL, cbbL), formaldehyde assimilation (SHMT), and nitric oxide reduction (NorQ) shed light on the roles played by GSL viruses in biogeochemical cycles of global relevanceThe funding for this project was provided by the United States National Science Foundation with project number 1510255With the institutional support of the ‘Severo OchoaCentre of Excellence’ accreditation (CEX2019-000928-S)Peer reviewe
La ciència tampoc no es deslliura del racisme
[EN] Racial aggressions have historically existed in the scientific field and eradicating them is the responsibility of each and every one of the people who are part of it[ES] Las agresiones raciales han existido históricamente en el ámbito científico y erradicarlas es responsabilidad de todas y cada una de las personas que forman parte de este[CAT] Les agressions racials han existit històricament en l'àmbit científic i eradicar-les és responsabilitat de totes i cadascuna de les persones que en formen partPeer reviewe
Ecological landscape explains aquifers microbial structure
10 pages, 5 figures, 1 table, supplementary information https://doi.org/10.1016/j.scitotenv.2022.160822.-- Code availability: The bioinformatics pipeline and statistical analysis are available at https://github.com/MeirellesLab/aquifer_metagenomes.-- Data availability: I have shared the link to the data/codes within the manuscript fileAquifers have significant social, economic, and ecological importance. They supply 30 % of the freshwater for human consumption worldwide, including agricultural and industrial use. Despite aquifers' importance, the relationships between aquifer categories and their inhabiting microbial communities are still unknown. Characterizing variations within microbial communities' function and taxonomy structure at different aquifers could give a panoramic view of patterns that may enable the detection and prediction of environmental impact caused by multiple sources. Using publicly available shotgun metagenomic datasets, we examined whether soil properties, land use, and climate variables would have a more significant influence on the taxonomy and functional structure of the microbial communities than the ecological landscapes of the aquifer (i.e., Karst, Porous, Saline, Geyser, and Porous Contaminated). We found that these categories are stronger predictors of microbial communities' structure than geographical localization. In addition, our results show that microbial richness and dominance patterns are the opposite of those found in multicellular life, where extreme habitats harbour richer functional and taxonomic microbial communities. We found that low-abundant and recently described candidate taxa, such as the chemolithoautotrophic genus Candidatus Altiarcheum and the Candidate phylum Parcubacteria, are the main contributors to aquifer microbial communities' dissimilarities. Genes related to gram-negative bacteria proteins, cell wall structures, and phage activity were the primary contributors to aquifer microbial communities' dissimilarities among the aquifers' ecological landscapes. The results reported in the present study highlight the utility of using ecological landscapes for investigating aquifer microbial communities. In addition, we suggest that functions played by recently described and low abundant bacterial groups need further investigation once they might affect water quality, geochemical cycles, and the effects of anthropogenic disturbances such as pollution and climatic events on aquifersThis work was primarily supported by the PROPESQ-UFBA (11268). FASB was supported by Programa Institucional de Bolsas de Iniciação Científica and Fundação de Amparo a Pesquisa da Bahia (4102/2019); CMF was supported by CAPES (88887-468244-2019-00). PMM thanks Serrapilheira Institute (grant number Serra-1709-17818). [...] FHC was supported by a Juan de la Cierva - Incoporación fellowship (Grant IJC2019-039859-I)With the institutional support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S)Peer reviewe
iPHoP: An integrated machine learning framework to maximize host prediction for metagenome-derived viruses of archaea and bacteria
26 pages, 5 figures, supporting information https://doi.org/10.1371/journal.pbio.3002083.-- Data Availability: All data directly relevant are within the paper and its Supporting Information files. Benchmarking analysis were based on the publicly available IMG/VR v3 database (doi 10.1093/nar/gkaa946 - https://genome.jgi.doe.gov/portal/IMG_VR/IMG_VR.home.html)The extraordinary diversity of viruses infecting bacteria and archaea is now primarily studied through metagenomics. While metagenomes enable high-throughput exploration of the viral sequence space, metagenome-derived sequences lack key information compared to isolated viruses, in particular host association. Different computational approaches are available to predict the host(s) of uncultivated viruses based on their genome sequences, but thus far individual approaches are limited either in precision or in recall, i.e., for a number of viruses they yield erroneous predictions or no prediction at all. Here, we describe iPHoP, a two-step framework that integrates multiple methods to reliably predict host taxonomy at the genus rank for a broad range of viruses infecting bacteria and archaea, while retaining a low false discovery rate. Based on a large dataset of metagenome-derived virus genomes from the IMG/VR database, we illustrate how iPHoP can provide extensive host prediction and guide further characterization of uncultivated virusesBED was supported by the European Research Council (ERC) Consolidator grant 865694: DiversiPHI, the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy – EXC 2051 – Project-ID 390713860, the Alexander von Humboldt Foundation in the context of an Alexander von Humboldt Professorship funded by the German Federal Ministry of Education and Research, and the European Union’s Horizon 2020 research and innovation program, under the Marie Skłodowska-Curie Actions Innovative Training Networks grant agreement no. 955974 (VIROINF). FHC was supported by a Juan de la Cierva - Incoporación fellowship (Grant IJC2019-039859-I), and had the institutional support of the “Severo Ochoa Centre of Excellence'' accreditation (CEX2019-000928-S). This work was supported by the U.S. Department of Energy, Office of Science, Biological and Environmental Research, Early Career Research Program (SR) awarded under UC-DOE Prime Contract DE-AC02-05CH11231. The work conducted by the U.S. Department of Energy Joint Genome Institute (https://ror.org/04xm1d337), a DOE Office of Science User Facility, is supported by the Office of Science of the U.S. Department of Energy operated under Contract No. DE-AC02-05CH11231 (SR, APC, SN)Peer reviewe