Heterogeneity in Pure Microbial Systems: Experimental Measurements and Modeling

Abstract

Cellular heterogeneity influences bioprocess performance in ways that until date are not completely elucidated. In order to account for this phenomenon in the design and operation of bioprocesses, reliable analytical and mathematical descriptions are required. We present an overview of the single cell analysis, and the mathematical modeling frameworks that have potential to be used in bioprocess control and optimization, in particular for microbial processes. In order to be suitable for bioprocess monitoring, experimental methods need to be high throughput and to require relatively short processing time. One such method used successfully under dynamic conditions is flow cytometry. Population balance and individual based models are suitable modeling options, the latter one having in particular a good potential to integrate the various data collected through experimentation. This will be highly beneficial for appropriate process design and scale up as a more rigorous approach may prevent a priori unwanted performance losses. It will also help progressing synthetic biology applications to industrial scale.

Coculturing Bacteria Leads to Reduced Phenotypic Heterogeneities

“…We demonstrated that interactions between bacterial populations lead to an adjustment of the individual phenotypic diversities of the interacting populations. Since phenotypic heterogeneity is playing an important role in pathogenicity and virulence (14), antibiotic resistance (12,54), biotechnological applications (20,23,55,56), and ecosystem properties (57), it is crucial to understand its influencing factors. The experimental design presented here provides a framework within which further ecological hypotheses regarding phenotypic heterogeneity and microbial interactions can be tested.…”

“…Two laser-based methods that are suitable for assessing phenotypes are flow cytometry and Raman spectroscopy (21)(22)(23). Two types of light can be detected by the flow cytometer: scattered light and fluorescence.…”

Coculturing bacteria leads to reduced phenotypic heterogeneities

“…We demonstrated that interactions between bacterial populations lead to an adjustment of the individual phenotypic diversities of the interacting populations. As phenotypic heterogeneity is playing an important role in pathogenicity and virulence (14), antibiotics resistance (12, 60), biotechnological applications (20, 23, 61, 62), ecosystem properties (63), it is crucial to understand its influencing factors. The experimental design presented in this study provides a framework within which further ecological hypotheses regarding phenotypic heterogeneity and microbial interactions can be tested.…”

“…Two laser-based methods that are suitable for assessing phenotypes are flow cytometry and Raman spectroscopy (21–23). Two types of light can be detected by the flow cytometer, that is scattered light and fluorescence.…”

Defining Cell Identity with Single‐Cell Omics

“…Since microbial populations are often complex and consist of a community of multiple species, single‐cell analysis may be vital in dissecting molecular heterogeneity between cells . The applications are wide‐ranging from deciphering phylogenetic trees and evolutionary mechanisms, to discovering novel metabolic features within a microbiome, monitoring and optimizing the productivity in industrial bioprocesses, showing the diversity of symbiotic interactions as well as viral integrations, to elucidating “rare biospheres.” Currently, microbiomes are predominantly categorized by sequencing of the small ribosomal 16S subunit using targeted primers. This targeted technique only amplifies a small proportion of the entire genomic content within a microbial cell, often misses less efficiently amplified rare cells within a population and cannot amplify certain members of the Actinobacteria and Crenarchaeota .…”