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10.3389/fmicb.2020.596626 http://scihub22266oqcxt.onion/10.3389/fmicb.2020.596626 33281796!7688782!33281796     free     free     free Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Front+Microbiol 2020 ; 11 (ä): 596626 Nephropedia Template TP {{tp|p=33281796|t=2020. High-Quality Genome-Scale Models From Error-Prone, Long-Read Assemblies |pdf=|usr=}}{{33281796}} gab.com Text High-Quality Genome-Scale Models From Error-Prone, Long-Read Assemblies JO: Front Microbiol http://www.kidney.de/pget.php?&tw=1&pmid=33281796 #FOAvip Advances in nanopore-based sequencing techniques have enabled rapid characterization of genomes and transcriptomes. An emerging application of this sequencing technology is point-of-care characterization of pathogenic bacteria. However, genome assessments alone are unable to provide a complete understanding of the pathogenic phenotype. Genome-scale metabolic reconstruction and analysis is a bottom-up Systems Biology technique that has elucidated the phenotypic nuances of antimicrobial resistant (AMR) bacteria and other human pathogens. Combining these genome-scale models (GEMs) with point-of-care nanopore sequencing is a promising strategy for combating the emerging health challenge of AMR pathogens. However, the sequencing errors inherent to the nanopore technique may negatively affect the quality, and therefore the utility, of GEMs reconstructed from nanopore assemblies. Here we describe and validate a workflow for rapid construction of GEMs from nanopore (MinION) derived assemblies. Benchmarking the pipeline against a high-quality reference GEM of Escherichia coli K-12 resulted in nanopore-derived models that were >99% complete even at sequencing depths of less than 10x coverage. Applying the pipeline to clinical isolates of pathogenic bacteria resulted in strain-specific GEMs that identified canonical AMR genome content and enabled simulations of strain-specific microbial growth. Additionally, we show that treating the sequencing run as a mock metagenome did not degrade the quality of models derived from metagenome assemblies. Taken together, this study demonstrates that combining nanopore sequencing with GEM construction pipelines enables rapid, in situ characterization of microbial metabolism. Twit Text FOAVip High-Quality Genome-Scale Models From Error-Prone, Long-Read Assemblies ????Front Microbiol http://www.kidney.de/pget.php?&tw=1&pmid=33281796 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33281796 #FOAvip English Wikipedia <ref>{{Cite pmid|33281796}}</ref> High-Quality Genome-Scale Models From Error-Prone, Long-Read Assemblies #MMPMID33281796 Broddrick JT; Szubin R; Norsigian CJ; Monk JM; Palsson BO; Parenteau MN Front Microbiol 2020[]; 11 (ä): 596626 PMID33281796show ga Advances in nanopore-based sequencing techniques have enabled rapid characterization of genomes and transcriptomes. An emerging application of this sequencing technology is point-of-care characterization of pathogenic bacteria. However, genome assessments alone are unable to provide a complete understanding of the pathogenic phenotype. Genome-scale metabolic reconstruction and analysis is a bottom-up Systems Biology technique that has elucidated the phenotypic nuances of antimicrobial resistant (AMR) bacteria and other human pathogens. Combining these genome-scale models (GEMs) with point-of-care nanopore sequencing is a promising strategy for combating the emerging health challenge of AMR pathogens. However, the sequencing errors inherent to the nanopore technique may negatively affect the quality, and therefore the utility, of GEMs reconstructed from nanopore assemblies. Here we describe and validate a workflow for rapid construction of GEMs from nanopore (MinION) derived assemblies. Benchmarking the pipeline against a high-quality reference GEM of Escherichia coli K-12 resulted in nanopore-derived models that were >99% complete even at sequencing depths of less than 10x coverage. Applying the pipeline to clinical isolates of pathogenic bacteria resulted in strain-specific GEMs that identified canonical AMR genome content and enabled simulations of strain-specific microbial growth. Additionally, we show that treating the sequencing run as a mock metagenome did not degrade the quality of models derived from metagenome assemblies. Taken together, this study demonstrates that combining nanopore sequencing with GEM construction pipelines enables rapid, in situ characterization of microbial metabolism. äHigh-Quality Genome-Scale Models From Error-Prone, Long-Read Assemblie(epmc).pdf DeepDyve Pubget Overpricing