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See detailMicrobial heterogeneity affects bioprocess robustness: Dynamic single cell analysis contribute to understanding microbial populations
Delvigne, Frank ULg; Goffin, Philippe

in Biotechnology Journal (2014), 9(1), 61-72

Heterogeneity or segregation of microbial populations has been the subject of much research, but the real impact of this phenomenon on bioprocesses remains not well understood. The main reason behind this ... [more ▼]

Heterogeneity or segregation of microbial populations has been the subject of much research, but the real impact of this phenomenon on bioprocesses remains not well understood. The main reason behind this lack of knowledge is the difficulty for monitoring microbial population heterogeneity in dynamic process conditions. The main concepts leading to microbial population heterogeneity in the context of bioprocesses have been summarized by two distinct hypotheses. The first one involves the individual history of microbial cells or “path” followed during their residence time inside process equipment. The second one involves a coordinated response of 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 statement illustrates the fact that, although microbial phenotypic heterogeneity has been thoroughly investigated at the fundamental level, the implications of this phenomenon in the context of microbial bioprocesses are still subjected to debate. At this time, automated flow cytometry is the best technique for the investigation of microbial heterogeneity in process conditions. However, dedicated software and relevant biomarkers are needed for its proper integration as a bioprocess control tool. [less ▲]

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