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Adaptations of Escherichia coli strains to oxidative stress are reflected in properties of their structural proteomes.
Mih, Nathan; Monk, Jonathan M; Fang, Xin; Catoiu, Edward; Heckmann, David; Yang, Laurence; Palsson, Bernhard O.
Afiliação
  • Mih N; Department of Bioengineering, University of California San Diego, La Jolla, CA, 92093, USA.
  • Monk JM; Bioinformatics and Systems Biology Program, University of California San Diego, La Jolla, CA, 92093, USA.
  • Fang X; Department of Bioengineering, University of California San Diego, La Jolla, CA, 92093, USA.
  • Catoiu E; Department of Bioengineering, University of California San Diego, La Jolla, CA, 92093, USA.
  • Heckmann D; Department of Bioengineering, University of California San Diego, La Jolla, CA, 92093, USA.
  • Yang L; Department of Bioengineering, University of California San Diego, La Jolla, CA, 92093, USA.
  • Palsson BO; Department of Bioengineering, University of California San Diego, La Jolla, CA, 92093, USA.
BMC Bioinformatics ; 21(1): 162, 2020 Apr 29.
Article em En | MEDLINE | ID: mdl-32349661
ABSTRACT

BACKGROUND:

The reconstruction of metabolic networks and the three-dimensional coverage of protein structures have reached the genome-scale in the widely studied Escherichia coli K-12 MG1655 strain. The combination of the two leads to the formation of a structural systems biology framework, which we have used to analyze differences between the reactive oxygen species (ROS) sensitivity of the proteomes of sequenced strains of E. coli. As proteins are one of the main targets of oxidative damage, understanding how the genetic changes of different strains of a species relates to its oxidative environment can reveal hypotheses as to why these variations arise and suggest directions of future experimental work.

RESULTS:

Creating a reference structural proteome for E. coli allows us to comprehensively map genetic changes in 1764 different strains to their locations on 4118 3D protein structures. We use metabolic modeling to predict basal ROS production levels (ROStype) for 695 of these strains, finding that strains with both higher and lower basal levels tend to enrich their proteomes with antioxidative properties, and speculate as to why that is. We computationally assess a strain's sensitivity to an oxidative environment, based on known chemical mechanisms of oxidative damage to protein groups, defined by their localization and functionality. Two general groups - metalloproteins and periplasmic proteins - show enrichment of their antioxidative properties between the 695 strains with a predicted ROStype as well as 116 strains with an assigned pathotype. Specifically, proteins that a) utilize a molybdenum ion as a cofactor and b) are involved in the biogenesis of fimbriae show intriguing protective properties to resist oxidative damage. Overall, these findings indicate that a strain's sensitivity to oxidative damage can be elucidated from the structural proteome, though future experimental work is needed to validate our model assumptions and findings.

CONCLUSION:

We thus demonstrate that structural systems biology enables a proteome-wide, computational assessment of changes to atomic-level physicochemical properties and of oxidative damage mechanisms for multiple strains in a species. This integrative approach opens new avenues to study adaptation to a particular environment based on physiological properties predicted from sequence alone.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Adaptação Fisiológica / Estresse Oxidativo / Proteoma / Escherichia coli K12 Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Adaptação Fisiológica / Estresse Oxidativo / Proteoma / Escherichia coli K12 Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2020 Tipo de documento: Article