Revealing the metabolic alterations during biofilm development of burkholderia cenocepacia based on genome-scale metabolic modeling

Ozlem Altay, Cheng Zhang, Hasan Turkez, Jens Nielsen, Mathias Uhlén, Adil Mardinoglu*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)

Abstract

Burkholderia cenocepacia is among the important pathogens isolated from cystic fibrosis (CF) patients. It has attracted considerable attention because of its capacity to evade host immune defenses during chronic infection. Advances in systems biology methodologies have led to the emergence of methods that integrate experimental transcriptomics data and genome-scale metabolic models (GEMs). Here, we integrated transcriptomics data of bacterial cells grown on exponential and biofilm conditions into a manually curated GEM of B. cenocepacia. We observed substantial differences in pathway response to different growth conditions and alternative pathway susceptibility to extracellular nutrient availability. For instance, we found that blockage of the reactions was vital through the lipid biosynthesis pathways in the exponential phase and the absence of microenvironmental lysine and tryptophan are essential for survival. During biofilm development, bacteria mostly had conserved lipid metabolism but altered pathway activities associated with several amino acids and pentose phosphate pathways. Furthermore, conversion of serine to pyruvate and 2,5-dioxopentanoate synthesis are also identified as potential targets for metabolic remodeling during biofilm development. Altogether, our integrative systems biology analysis revealed the interactions between the bacteria and its microenvironment and enabled the discovery of antimicrobial targets for biofilm-related diseases.

Original languageEnglish
Article number221
JournalMetabolites
Volume11
Issue number4
DOIs
Publication statusPublished - Apr 2021

Keywords

  • Biofilm
  • Burkholderia cenocepacia
  • Genome-scale metabolic models
  • Omics integration
  • Synthetic lethality
  • Transcriptomics

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