From Genomes to Phenotypes: Traitar, the Microbial Trait Analyzer

ABSTRACT The number of sequenced genomes is growing exponentially, profoundly shifting the bottleneck from data generation to genome interpretation. Traits are often used to characterize and distinguish bacteria and are likely a driving factor in microbial community composition, yet little is known...

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Autores principales:	Aaron Weimann, Kyra Mooren, Jeremy Frank, Phillip B. Pope, Andreas Bremges, Alice C. McHardy
Formato:	article
Lenguaje:	EN
Publicado:	American Society for Microbiology 2016
Materias:	ancestral trait reconstruction genotype-phenotype inference metagenomics microbial traits phenotypes phyletic patterns Microbiology QR1-502
Acceso en línea:	https://doaj.org/article/d9fd0deac5664404a43d4341ffbc6a87
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spelling	oai:doaj.org-article:d9fd0deac5664404a43d4341ffbc6a872021-12-02T18:39:34ZFrom Genomes to Phenotypes: Traitar, the Microbial Trait Analyzer10.1128/mSystems.00101-162379-5077https://doaj.org/article/d9fd0deac5664404a43d4341ffbc6a872016-12-01T00:00:00Zhttps://journals.asm.org/doi/10.1128/mSystems.00101-16https://doaj.org/toc/2379-5077ABSTRACT The number of sequenced genomes is growing exponentially, profoundly shifting the bottleneck from data generation to genome interpretation. Traits are often used to characterize and distinguish bacteria and are likely a driving factor in microbial community composition, yet little is known about the traits of most microbes. We describe Traitar, the microbial trait analyzer, which is a fully automated software package for deriving phenotypes from a genome sequence. Traitar provides phenotype classifiers to predict 67 traits related to the use of various substrates as carbon and energy sources, oxygen requirement, morphology, antibiotic susceptibility, proteolysis, and enzymatic activities. Furthermore, it suggests protein families associated with the presence of particular phenotypes. Our method uses L1-regularized L2-loss support vector machines for phenotype assignments based on phyletic patterns of protein families and their evolutionary histories across a diverse set of microbial species. We demonstrate reliable phenotype assignment for Traitar to bacterial genomes from 572 species of eight phyla, also based on incomplete single-cell genomes and simulated draft genomes. We also showcase its application in metagenomics by verifying and complementing a manual metabolic reconstruction of two novel Clostridiales species based on draft genomes recovered from commercial biogas reactors. Traitar is available at https://github.com/hzi-bifo/traitar . IMPORTANCE Bacteria are ubiquitous in our ecosystem and have a major impact on human health, e.g., by supporting digestion in the human gut. Bacterial communities can also aid in biotechnological processes such as wastewater treatment or decontamination of polluted soils. Diverse bacteria contribute with their unique capabilities to the functioning of such ecosystems, but lab experiments to investigate those capabilities are labor-intensive. Major advances in sequencing techniques open up the opportunity to study bacteria by their genome sequences. For this purpose, we have developed Traitar, software that predicts traits of bacteria on the basis of their genomes. It is applicable to studies with tens or hundreds of bacterial genomes. Traitar may help researchers in microbiology to pinpoint the traits of interest, reducing the amount of wet lab work required.Aaron WeimannKyra MoorenJeremy FrankPhillip B. PopeAndreas BremgesAlice C. McHardyAmerican Society for Microbiologyarticleancestral trait reconstructiongenotype-phenotype inferencemetagenomicsmicrobial traitsphenotypesphyletic patternsMicrobiologyQR1-502ENmSystems, Vol 1, Iss 6 (2016)
institution	DOAJ
collection	DOAJ
language	EN
topic	ancestral trait reconstruction genotype-phenotype inference metagenomics microbial traits phenotypes phyletic patterns Microbiology QR1-502
spellingShingle	ancestral trait reconstruction genotype-phenotype inference metagenomics microbial traits phenotypes phyletic patterns Microbiology QR1-502 Aaron Weimann Kyra Mooren Jeremy Frank Phillip B. Pope Andreas Bremges Alice C. McHardy From Genomes to Phenotypes: Traitar, the Microbial Trait Analyzer
description	ABSTRACT The number of sequenced genomes is growing exponentially, profoundly shifting the bottleneck from data generation to genome interpretation. Traits are often used to characterize and distinguish bacteria and are likely a driving factor in microbial community composition, yet little is known about the traits of most microbes. We describe Traitar, the microbial trait analyzer, which is a fully automated software package for deriving phenotypes from a genome sequence. Traitar provides phenotype classifiers to predict 67 traits related to the use of various substrates as carbon and energy sources, oxygen requirement, morphology, antibiotic susceptibility, proteolysis, and enzymatic activities. Furthermore, it suggests protein families associated with the presence of particular phenotypes. Our method uses L1-regularized L2-loss support vector machines for phenotype assignments based on phyletic patterns of protein families and their evolutionary histories across a diverse set of microbial species. We demonstrate reliable phenotype assignment for Traitar to bacterial genomes from 572 species of eight phyla, also based on incomplete single-cell genomes and simulated draft genomes. We also showcase its application in metagenomics by verifying and complementing a manual metabolic reconstruction of two novel Clostridiales species based on draft genomes recovered from commercial biogas reactors. Traitar is available at https://github.com/hzi-bifo/traitar . IMPORTANCE Bacteria are ubiquitous in our ecosystem and have a major impact on human health, e.g., by supporting digestion in the human gut. Bacterial communities can also aid in biotechnological processes such as wastewater treatment or decontamination of polluted soils. Diverse bacteria contribute with their unique capabilities to the functioning of such ecosystems, but lab experiments to investigate those capabilities are labor-intensive. Major advances in sequencing techniques open up the opportunity to study bacteria by their genome sequences. For this purpose, we have developed Traitar, software that predicts traits of bacteria on the basis of their genomes. It is applicable to studies with tens or hundreds of bacterial genomes. Traitar may help researchers in microbiology to pinpoint the traits of interest, reducing the amount of wet lab work required.
format	article
author	Aaron Weimann Kyra Mooren Jeremy Frank Phillip B. Pope Andreas Bremges Alice C. McHardy
author_facet	Aaron Weimann Kyra Mooren Jeremy Frank Phillip B. Pope Andreas Bremges Alice C. McHardy
author_sort	Aaron Weimann
title	From Genomes to Phenotypes: Traitar, the Microbial Trait Analyzer
title_short	From Genomes to Phenotypes: Traitar, the Microbial Trait Analyzer
title_full	From Genomes to Phenotypes: Traitar, the Microbial Trait Analyzer
title_fullStr	From Genomes to Phenotypes: Traitar, the Microbial Trait Analyzer
title_full_unstemmed	From Genomes to Phenotypes: Traitar, the Microbial Trait Analyzer
title_sort	from genomes to phenotypes: traitar, the microbial trait analyzer
publisher	American Society for Microbiology
publishDate	2016
url	https://doaj.org/article/d9fd0deac5664404a43d4341ffbc6a87
work_keys_str_mv	AT aaronweimann fromgenomestophenotypestraitarthemicrobialtraitanalyzer AT kyramooren fromgenomestophenotypestraitarthemicrobialtraitanalyzer AT jeremyfrank fromgenomestophenotypestraitarthemicrobialtraitanalyzer AT phillipbpope fromgenomestophenotypestraitarthemicrobialtraitanalyzer AT andreasbremges fromgenomestophenotypestraitarthemicrobialtraitanalyzer AT alicecmchardy fromgenomestophenotypestraitarthemicrobialtraitanalyzer
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From Genomes to Phenotypes: Traitar, the Microbial Trait Analyzer

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