Proteome sequence features carry signatures of the environmental niche of prokaryotes

<p>Abstract</p> <p>Background</p> <p>Prokaryotic environmental adaptations occur at different levels within cells to ensure the preservation of genome integrity, proper protein folding and function as well as membrane fluidity. Although specific composition and structur...

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Main Authors: Supek Fran, Nikolic Nela, Smole Zlatko, Šmuc Tomislav, Sbalzarini Ivo F, Krisko Anita
Format: Article
Language:English
Published: BMC 2011-01-01
Series:BMC Evolutionary Biology
Online Access:http://www.biomedcentral.com/1471-2148/11/26
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spelling doaj-eba8a72158894b64969fa38fc9fd520a2021-09-02T16:40:34ZengBMCBMC Evolutionary Biology1471-21482011-01-011112610.1186/1471-2148-11-26Proteome sequence features carry signatures of the environmental niche of prokaryotesSupek FranNikolic NelaSmole ZlatkoŠmuc TomislavSbalzarini Ivo FKrisko Anita<p>Abstract</p> <p>Background</p> <p>Prokaryotic environmental adaptations occur at different levels within cells to ensure the preservation of genome integrity, proper protein folding and function as well as membrane fluidity. Although specific composition and structure of cellular components suitable for the variety of extreme conditions has already been postulated, a systematic study describing such adaptations has not yet been performed. We therefore explored whether the environmental niche of a prokaryote could be deduced from the sequence of its proteome. Finally, we aimed at finding the precise differences between proteome sequences of prokaryotes from different environments.</p> <p>Results</p> <p>We analyzed the proteomes of 192 prokaryotes from different habitats. We collected detailed information about the optimal growth conditions of each microorganism. Furthermore, we selected 42 physico-chemical properties of amino acids and computed their values for each proteome. Further, on the same set of features we applied two fundamentally different machine learning methods, Support Vector Machines and Random Forests, to successfully classify between bacteria and archaea, halophiles and non-halophiles, as well as mesophiles, thermophiles and mesothermophiles. Finally, we performed feature selection by using Random Forests.</p> <p>Conclusions</p> <p>To our knowledge, this is the first time that three different classification cases (domain of life, halophilicity and thermophilicity) of proteome adaptation are successfully performed with the same set of 42 features. The characteristic features of a specific adaptation constitute a signature that may help understanding the mechanisms of adaptation to extreme environments.</p> http://www.biomedcentral.com/1471-2148/11/26
collection DOAJ
language English
format Article
sources DOAJ
author Supek Fran
Nikolic Nela
Smole Zlatko
Šmuc Tomislav
Sbalzarini Ivo F
Krisko Anita
spellingShingle Supek Fran
Nikolic Nela
Smole Zlatko
Šmuc Tomislav
Sbalzarini Ivo F
Krisko Anita
Proteome sequence features carry signatures of the environmental niche of prokaryotes
BMC Evolutionary Biology
author_facet Supek Fran
Nikolic Nela
Smole Zlatko
Šmuc Tomislav
Sbalzarini Ivo F
Krisko Anita
author_sort Supek Fran
title Proteome sequence features carry signatures of the environmental niche of prokaryotes
title_short Proteome sequence features carry signatures of the environmental niche of prokaryotes
title_full Proteome sequence features carry signatures of the environmental niche of prokaryotes
title_fullStr Proteome sequence features carry signatures of the environmental niche of prokaryotes
title_full_unstemmed Proteome sequence features carry signatures of the environmental niche of prokaryotes
title_sort proteome sequence features carry signatures of the environmental niche of prokaryotes
publisher BMC
series BMC Evolutionary Biology
issn 1471-2148
publishDate 2011-01-01
description <p>Abstract</p> <p>Background</p> <p>Prokaryotic environmental adaptations occur at different levels within cells to ensure the preservation of genome integrity, proper protein folding and function as well as membrane fluidity. Although specific composition and structure of cellular components suitable for the variety of extreme conditions has already been postulated, a systematic study describing such adaptations has not yet been performed. We therefore explored whether the environmental niche of a prokaryote could be deduced from the sequence of its proteome. Finally, we aimed at finding the precise differences between proteome sequences of prokaryotes from different environments.</p> <p>Results</p> <p>We analyzed the proteomes of 192 prokaryotes from different habitats. We collected detailed information about the optimal growth conditions of each microorganism. Furthermore, we selected 42 physico-chemical properties of amino acids and computed their values for each proteome. Further, on the same set of features we applied two fundamentally different machine learning methods, Support Vector Machines and Random Forests, to successfully classify between bacteria and archaea, halophiles and non-halophiles, as well as mesophiles, thermophiles and mesothermophiles. Finally, we performed feature selection by using Random Forests.</p> <p>Conclusions</p> <p>To our knowledge, this is the first time that three different classification cases (domain of life, halophilicity and thermophilicity) of proteome adaptation are successfully performed with the same set of 42 features. The characteristic features of a specific adaptation constitute a signature that may help understanding the mechanisms of adaptation to extreme environments.</p>
url http://www.biomedcentral.com/1471-2148/11/26
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