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The streamlining hypothesis is generally used to explain the genomic reduction events related to the small genome size of free-living bacteria like marine bacteria SAR11. However, our current understanding of the correlation between bacterial genome size and environmental adaptation relies on too few species. It is still unclear whether there are other paths leading to genomic reduction in free-living bacteria. The genome size of marine free-living bacteria of the genus Idiomarina belonging to the order Alteromonadales (Gammaproteobacteria) is much smaller than the size of related genomes from bacteria in the same order. Comparative genomic and physiological analyses showed that the genomic reduction pattern in this genus is different from that of the classical SAR11 lineage. Genomic reduction reconstruction and substrate utilization profile showed that Idiomarina spp. lost a large number of genes related to carbohydrate utilization, and instead they specialized on using proteinaceous resources. Here we propose a new hypothesis to explain genomic reduction in this genus; we propose that trophic specialization increasing the metabolic efficiency for using one kind of substrate but reducing the substrate utilization spectrum could result in bacterial genomic reduction, which would be not uncommon in nature. This hypothesis was further tested in another free-living genus, Kangiella, which also shows dramatic genomic reduction. These findings highlight that trophic specialization is potentially an important path leading to genomic reduction in some marine free-living bacteria, which is distinct from the classical lineages like SAR11.IMPORTANCE The streamlining hypothesis is usually used to explain the genomic reduction events in free-living bacteria like SAR11. However, we find that the genomic reduction phenomenon in the bacterial genus Idiomarina is different from that in SAR11. Therefore, we propose a new hypothesis to explain genomic reduction in this genus based on trophic specialization that could result in genomic reduction, which would be not uncommon in nature. Not only can the trophic specialization hypothesis explain the genomic reduction in the genus Idiomarina, but it also sheds new light on our understanding of the genomic reduction processes in other free-living bacterial lineages.
Pubmed ID: 30647156
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NIH genetic sequence database that provides annotated collection of all publicly available DNA sequences for almost 280 000 formally described species (Jan 2014) .These sequences are obtained primarily through submissions from individual laboratories and batch submissions from large-scale sequencing projects, including whole-genome shotgun (WGS) and environmental sampling projects. Most submissions are made using web-based BankIt or standalone Sequin programs, and GenBank staff assigns accession numbers upon data receipt. It is part of International Nucleotide Sequence Database Collaboration and daily data exchange with European Nucleotide Archive (ENA) and DNA Data Bank of Japan (DDBJ) ensures worldwide coverage. GenBank is accessible through NCBI Entrez retrieval system, which integrates data from major DNA and protein sequence databases along with taxonomy, genome, mapping, protein structure and domain information, and biomedical journal literature via PubMed. BLAST provides sequence similarity searches of GenBank and other sequence databases. Complete bimonthly releases and daily updates of GenBank database are available by FTP.
View all literature mentionsMultiple sequence alignment method with reduced time and space complexity.Multiple sequence alignment with high accuracy and high throughput. Data analysis service for multiple sequence comparison by log- expectation.
View all literature mentionsIntegrated database resource consisting of 16 main databases, broadly categorized into systems information, genomic information, and chemical information. In particular, gene catalogs in completely sequenced genomes are linked to higher-level systemic functions of cell, organism, and ecosystem. Analysis tools are also available. KEGG may be used as reference knowledge base for biological interpretation of large-scale datasets generated by sequencing and other high-throughput experimental technologies.
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