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Proteome sequence features carry signatures of the environmental niche of prokaryotes

Proteome sequence features carry signatures of the environmental niche of prokaryotes
Proteome sequence features carry signatures of the environmental niche of prokaryotes

Background: 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.

Results: 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.

Conclusions: 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.

Adaptation, Biological, Algorithms, Archaea/classification, Artificial Intelligence, Bacteria/classification, Computational Biology/methods, Ecosystem, Proteome/metabolism
1471-2148
Smole, Zlatko
d217141b-e908-4806-a2ea-4495c89b9b37
Nikolic, Nela
88a8f576-d9e2-4eb6-9219-39b7065963d3
Supek, Fran
6449fb01-a557-4bed-855d-406b32189f3e
Šmuc, Tomislav
12f477e9-a0c2-4cf1-8639-cd8012ef096d
Sbalzarini, Ivo F.
224390ef-630d-4417-8b84-76e052218b65
Krisko, Anita
b42ec85e-9cb5-41b2-bb8d-a7b551b8b8c1
Smole, Zlatko
d217141b-e908-4806-a2ea-4495c89b9b37
Nikolic, Nela
88a8f576-d9e2-4eb6-9219-39b7065963d3
Supek, Fran
6449fb01-a557-4bed-855d-406b32189f3e
Šmuc, Tomislav
12f477e9-a0c2-4cf1-8639-cd8012ef096d
Sbalzarini, Ivo F.
224390ef-630d-4417-8b84-76e052218b65
Krisko, Anita
b42ec85e-9cb5-41b2-bb8d-a7b551b8b8c1

Smole, Zlatko, Nikolic, Nela, Supek, Fran, Šmuc, Tomislav, Sbalzarini, Ivo F. and Krisko, Anita (2011) Proteome sequence features carry signatures of the environmental niche of prokaryotes. BMC Evolutionary Biology, 11, [26]. (doi:10.1186/1471-2148-11-26).

Record type: Article

Abstract

Background: 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.

Results: 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.

Conclusions: 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.

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1471-2148-11-26 - Version of Record
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Accepted/In Press date: 26 January 2011
Published date: 26 January 2011
Keywords: Adaptation, Biological, Algorithms, Archaea/classification, Artificial Intelligence, Bacteria/classification, Computational Biology/methods, Ecosystem, Proteome/metabolism

Identifiers

Local EPrints ID: 487907
URI: http://eprints.soton.ac.uk/id/eprint/487907
ISSN: 1471-2148
PURE UUID: 23c50430-f8d9-401b-a509-3fc432683c49
ORCID for Nela Nikolic: ORCID iD orcid.org/0000-0001-9068-6090

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Date deposited: 08 Mar 2024 18:04
Last modified: 15 Jun 2024 02:10

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Contributors

Author: Zlatko Smole
Author: Nela Nikolic ORCID iD
Author: Fran Supek
Author: Tomislav Šmuc
Author: Ivo F. Sbalzarini
Author: Anita Krisko

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