Literature DB >> 29541890

Population heterogeneity in microbial bioprocesses: origin, analysis, mechanisms, and future perspectives.

Anna-Lena Heins1, Dirk Weuster-Botz2.   

Abstract

Population heterogeneity is omnipresent in all bioprocesses even in homogenous environments. Its origin, however, is only so well understood that potential strategies like bet-hedging, noise in gene expression and division of labour that lead to population heterogeneity can be derived from experimental studies simulating the dynamics in industrial scale bioprocesses. This review aims at summarizing the current state of the different parts of single cell studies in bioprocesses. This includes setups to visualize different phenotypes of single cells, computational approaches connecting single cell physiology with environmental influence and special cultivation setups like scale-down reactors that have been proven to be useful to simulate large-scale conditions. A step in between investigation of populations and single cells is studying subpopulations with distinct properties that differ from the rest of the population with sub-omics methods which are also presented here. Moreover, the current knowledge about population heterogeneity in bioprocesses is summarized for relevant industrial production hosts and mixed cultures, as they provide the unique opportunity to distribute metabolic burden and optimize production processes in a way that is impossible in traditional monocultures. In the end, approaches to explain the underlying mechanism of population heterogeneity and the evidences found to support each hypothesis are presented. For instance, population heterogeneity serving as a bet-hedging strategy that is used as coordinated action against bioprocess-related stresses while at the same time spreading the risk between individual cells as it ensures the survival of least a part of the population in any environment the cells encounter.

Entities:  

Keywords:  Bet-hedging; Mixed culture; Noise in gene expression; Population heterogeneity; Reporter strains; Scale-down reactors; Sub-omics

Mesh:

Year:  2018        PMID: 29541890     DOI: 10.1007/s00449-018-1922-3

Source DB:  PubMed          Journal:  Bioprocess Biosyst Eng        ISSN: 1615-7591            Impact factor:   3.210


  9 in total

Review 1.  The ecology of wine fermentation: a model for the study of complex microbial ecosystems.

Authors:  C G Conacher; N A Luyt; R K Naidoo-Blassoples; D Rossouw; M E Setati; F F Bauer
Journal:  Appl Microbiol Biotechnol       Date:  2021-04-09       Impact factor: 4.813

2.  Biodegradation of waste cooking oil and simultaneous production of rhamnolipid biosurfactant by Pseudomonas aeruginosa P7815 in batch and fed-batch bioreactor.

Authors:  Swati Sharma; Rahul Verma; Sahil Dhull; Soumen K Maiti; Lalit M Pandey
Journal:  Bioprocess Biosyst Eng       Date:  2021-11-12       Impact factor: 3.210

3.  Control of phenotypic diversification based on serial cultivations on different carbon sources leads to improved bacterial xylanase production.

Authors:  Bouchat Romain; Frank Delvigne; Caroline Rémond; Harivony Rakotoarivonina
Journal:  Bioprocess Biosyst Eng       Date:  2022-07-26       Impact factor: 3.434

4.  Control of parallelized bioreactors I: dynamic scheduling software for efficient bioprocess management in high-throughput systems.

Authors:  Lukas Bromig; Nikolas von den Eichen; Dirk Weuster-Botz
Journal:  Bioprocess Biosyst Eng       Date:  2022-10-18       Impact factor: 3.434

5.  Quantitative Flow Cytometry to Understand Population Heterogeneity in Response to Changes in Substrate Availability in Escherichia coli and Saccharomyces cerevisiae Chemostats.

Authors:  Anna-Lena Heins; Ted Johanson; Shanshan Han; Luisa Lundin; Magnus Carlquist; Krist V Gernaey; Søren J Sørensen; Anna Eliasson Lantz
Journal:  Front Bioeng Biotechnol       Date:  2019-08-05

Review 6.  Advances in automated real-time flow cytometry for monitoring of bioreactor processes.

Authors:  Anna-Lena Heins; Manh Dat Hoang; Dirk Weuster-Botz
Journal:  Eng Life Sci       Date:  2021-11-12       Impact factor: 2.678

Review 7.  Optimization and Scale-Up of Fermentation Processes Driven by Models.

Authors:  Yuan-Hang Du; Min-Yu Wang; Lin-Hui Yang; Ling-Ling Tong; Dong-Sheng Guo; Xiao-Jun Ji
Journal:  Bioengineering (Basel)       Date:  2022-09-14

8.  Real-Time Monitoring of the Yeast Intracellular State During Bioprocesses With a Toolbox of Biosensors.

Authors:  Luca Torello Pianale; Peter Rugbjerg; Lisbeth Olsson
Journal:  Front Microbiol       Date:  2022-01-07       Impact factor: 5.640

9.  Monitoring Intracellular Metabolite Dynamics in Saccharomyces cerevisiae during Industrially Relevant Famine Stimuli.

Authors:  Steven Minden; Maria Aniolek; Christopher Sarkizi Shams Hajian; Attila Teleki; Tobias Zerrer; Frank Delvigne; Walter van Gulik; Amit Deshmukh; Henk Noorman; Ralf Takors
Journal:  Metabolites       Date:  2022-03-18
  9 in total

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