Abstract

Exiguobacterium antarcticum B7 is extremophile Gram-positive bacteria able to survive in cold environments. A key factor to understanding cold adaptation processes is related to the modification of fatty acids composing the cell membranes of psychrotrophic bacteria. In our study we show the in silico reconstruction of the fatty acid biosynthesis pathway of E. antarcticum B7. To build the stoichiometric model, a semiautomatic procedure was applied, which integrates genome information using KEGG and RAST/SEED. Constraint-based methods, namely, Flux Balance Analysis (FBA) and elementary modes (EM), were applied. FBA was implemented in the sense of hexadecenoic acid production maximization. To evaluate the influence of the gene expression in the fluxome analysis, FBA was also calculated using the log2⁡FC values obtained in the transcriptome analysis at 0°C and 37°C. The fatty acid biosynthesis pathway showed a total of 13 elementary flux modes, four of which showed routes for the production of hexadecenoic acid. The reconstructed pathway demonstrated the capacity of E. antarcticum B7 to de novo produce fatty acid molecules. Under the influence of the transcriptome, the fluxome was altered, promoting the production of short-chain fatty acids. The calculated models contribute to better understanding of the bacterial adaptation at cold environments.

Highlights

  • Bacteria are increasingly used in industrial processes to produce chemicals, foods, and drugs, among other products [1]

  • In this work we present the in silico reconstruction of the fatty acid biosynthesis pathway of the Exiguobacterium antarcticum B7, based on linear programming (FBA) and convex cone method

  • The draft of the metabolic network of E. antarcticum B7 was retrieved from the KEGG database [26]

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Summary

Introduction

Bacteria are increasingly used in industrial processes to produce chemicals, foods, and drugs, among other products [1]. The main biochemical pathways of bacteria may be manipulated and optimized to more efficiently produce compounds of industrial interest in various areas; for example, metabolic pathways of Corynebacterium glutamicum are rationally engineered to produce L-amino acids on an industrial scale [2]. To accomplish this task, specific tools are used such as FMM (from metabolite to metabolite) [3] Cytoscape [4], CellDesigner [5], SBW (Systems Biology Workbench) [6], COPASI (COmplex PAthway SImulator) [7], and COBRA (COnstraints Based Reconstruction and Analysis) toolbox [8]. The draf t network generated from the annotated genome still requires significant manual curation for a comprehensive and accurate metabolic representation of the organism [13]

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