Microbial heterogeneity affects bioprocess robustness: Dynamic single‐cell analysis contributes to understanding of microbial populations

Abstract

Heterogeneity or segregation of microbial populations has been the subject of much research, but the real impact of this phenomenon on bioprocesses remains poorly understood. The main reason for this lack of knowledge is the difficulty in monitoring microbial population heterogeneity under dynamic process conditions. The main concepts resulting in microbial population heterogeneity in the context of bioprocesses have been summarized by two distinct hypotheses. The first involves the individual history of microbial cells or the "path" followed during their residence time inside the process equipment. The second hypothesis involves a coordinated response by the microbial population as a bet-hedging strategy, in order to cope with process-related stresses. The respective contribution of each hypothesis to microbial heterogeneity in bioprocesses is still unclear. This illustrates the fact that, although microbial phenotypic heterogeneity has been thoroughly investigated at a fundamental level, the implications of this phenomenon in the context of microbial bioprocesses are still subject to debate. At this time, automated flow cytometry is the best technique for investigating microbial heterogeneity under process conditions. However, dedicated software and relevant biomarkers are needed for the proper integration of flow cytometry as a bioprocess control tool.

Metabolic variability in bioprocessing: implications of microbial phenotypic heterogeneity

“….) [2,71] or the presence of key metabolites [13,72]. These systems are valuable for the determination of the metabolic potential of microbial cell factories, and have notably been exploited for high-throughput selection of a high amino acid producer for Corynebacterium glutamicum [73].…”

“…Impact of microbial phenotypic heterogeneity on microbial bioprocesses Until now, microbial phenotypic heterogeneity has generally only been explored in basic scientific research, and few studies have taken this important phenomenon into account in the context of industrial biotechnological applications [1,2]. The production of bio-based compounds is dependent on stochastic cellular mechanisms, leading to difficulties in controlling bioprocessing.…”

“…Noise in gene expression generally results in a Gaussian distribution of protein content across different individuals of the same population. All these sources of phenotypic heterogeneity are known to affect bioprocess performance [1,2], but the respective contributions of these different components to phenotypic diversification are not known.…”

Simultaneous production of lactobionic and gluconic acid in cheese whey/glucose co-fermentation by Pseudomonas taetrolens

“…The appearance of non-lactobionic acid producing cells, featured by a loss in the membrane integrity as well as lower metabolic activity levels, constitutes a major drawback behind culture robustness. When multimodal phenotypes with subpopulations of reduced fitness are present, fermentation production outputs are strongly affected (Delvigne and Goffin, 2014). In fact, both growth fitness and lactobionic acid production capabilities are greatly jeopardized when physiologically and structurally compromised P. taetrolens cell subpopulations arise due to deleterious bioprocessing conditions (Alonso et al, 2012b(Alonso et al, , 2013c.…”

Editorial: Latest methods and advances in biotechnology

“…Delvigne and Goffin [5] review our current understanding on microbial heterogeneity affecting bioprocess robustness, which is not well understood. The authors review approaches based on flow cytometry and labon-a-chip technologies for monitoring microbial heterogeneity.…”