Přehled o publikaci
2019
Computational Modelling of Metabolic Burden and Substrate Toxicity in Escherichia coli Carrying a Synthetic Metabolic Pathway
DEMKO, Martin; Lukáš CHRÁST; Pavel DVOŘÁK; Jiří DAMBORSKÝ; David ŠAFRÁNEK et. al.Basic information
Original name
Computational Modelling of Metabolic Burden and Substrate Toxicity in Escherichia coli Carrying a Synthetic Metabolic Pathway
Authors
DEMKO, Martin (703 Slovakia, guarantor, belonging to the institution); Lukáš CHRÁST (203 Czech Republic, belonging to the institution); Pavel DVOŘÁK (203 Czech Republic, belonging to the institution); Jiří DAMBORSKÝ (203 Czech Republic, belonging to the institution) and David ŠAFRÁNEK (203 Czech Republic, belonging to the institution)
Edition
Microorganisms, Basel, MDPI, 2019, 2076-2607
Other information
Language
English
Type of outcome
Article in a journal
Country of publisher
Switzerland
Confidentiality degree
is not subject to a state or trade secret
References:
RIV identification code
RIV/00216224:14310/19:00107775
Organization
Přírodovědecká fakulta – Repository – Repository
UT WoS
000502273600076
EID Scopus
2-s2.0-85074928975
Keywords in English
biodegradation; computational modelling; population growth; metabolic burden; environmental pollutants
Links
GA18-00178S, research and development project. LM2015047, research and development project. LM2015055, research and development project. LM2015085, research and development project. MUNI/A/1018/2018, interní kód Repo.
Changed: 16/2/2023 04:23, RNDr. Daniel Jakubík
Abstract
V originále
In our previous work, we have designed and implemented a synthetic metabolic pathway for 1,2,3-trichloropropane (TCP) biodegradation in Escherichia coli. Significant effects of metabolic burden and toxicity exacerbation were observed on single cell and population levels. Deeper understanding of mechanisms underlying these effects is extremely important for metabolic engineering of efficient microbial cell factories for biotechnological processes. In this paper, we present a novel mathematical model of the pathway. The model addresses for the first time the combined effects of toxicity exacerbation and metabolic burden in the context of bacterial population growth. The model is calibrated with respect to the real data obtained with our original synthetically modified E. coli strain. Using the model, we explore the dynamics of the population growth along with the outcome of the TCP biodegradation pathway considering the toxicity exacerbation and metabolic burden. On the methodological side, we introduce a unique computational workflow utilising algorithmic methods of computer science for the particular modelling problem.
