The effect of acetate on population heterogeneity in different cellular characteristics of Escherichia coli in aerobic batch cultures

Cellular variability as a driver for bioprocess innovation and optimization

Cellular heterogeneity plays a crucial role in biotechnological processes, significantly influencing metabolic activity, product yield, and process consistency. This review explores the different dimensions of cellular heterogeneity, focusing on its manifestation at both single-cell and population levels. The study examines how factors such as asymmetric cell division, age, and environmental conditions contribute to functional diversity within cell populations, with an emphasis on microorganisms like yeast. Age-related cellular heterogeneity, in particular, is highlighted for its impact on metabolic pathways, mitochondrial function, and secondary metabolite production, which directly affect bioprocess outcomes. Furthermore, the review discusses advanced techniques for detecting and managing heterogeneity, including surface marker-based approaches, which utilize proteins, polysaccharides, and lipids, and label-free methods that leverage cellular volume and physical properties for separation. Understanding and controlling cellular heterogeneity is essential for optimizing industrial bioprocesses, improving yield, and ensuring product quality. The review also underscores the potential of emerging biotechnological tools, such as real-time single-cell analysis and microfluidic devices, in enhancing separation techniques and managing cellular diversity for better process efficiency and robustness.

Modeling multiphase fluid flow, mass transfer, and chemical reactions in bioreactors using large-eddy simulation

We present a transient large eddy simulation (LES) modeling approach for simulating the interlinked physics describing free surface hydrodynamics, multiphase mixing, reaction kinetics, and mass transport in bioreactor systems. Presented case-studies include non-reacting and reacting bioreactor systems, modeled through the inclusion of uniform reaction rates and more complex biochemical reactions described using Contois type kinetics. It is shown that the presence of reactions can result in a non-uniform spatially varying species concentration field, the magnitude and extent of which is directly related to the reaction rates and the underlying variations in the local volumetric mass transfer coefficient.

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

Flow cytometry and its technological possibilities have greatly advanced in the past decade as analysis tool for single cell properties and population distributions of different cell types in bioreactors. Along the way, some solutions for automated real-time flow cytometry (ART-FCM) were developed for monitoring of bioreactor processes without operator interference over extended periods with variable sampling frequency. However, there is still great potential for ART-FCM to evolve and possibly become a standard application in bioprocess monitoring and process control. This review first addresses different components of an ART-FCM, including the sampling device, the sample-processing unit, the unit for sample delivery to the flow cytometer and the settings for measurement of pre-processed samples. Also, available algorithms are presented for automated data analysis of multi-parameter fluorescence datasets derived from ART-FCM experiments. Furthermore, challenges are discussed for integration of fluorescence-activated cell sorting into an ART-FCM setup for isolation and separation of interesting subpopulations that can be further characterized by for instance omics-methods. As the application of ART-FCM is especially of interest for bioreactor process monitoring, including investigation of population heterogeneity and automated process control, a summary of already existing setups for these purposes is given. Additionally, the general future potential of ART-FCM is addressed.

Use of qPCR for the analysis of population heterogeneity and dynamics during Lactobacillus delbrueckii spp. bulgaricus batch fculture

Direct molecular methods such as real-time polymerase chain reaction (qPCR) and propidium monoazide (PMA)-qPCR have been successfully used for quantifying viable microorganisms in the food industry. This study attempted to use qPCR and PMA-qPCR for quantifying Lactobacillus delbrueckii spp. bulgaricus sp1.1 physiological states. The qPCR standards of the 16S rRNA gene were employed to calibrate the qPCR assay, which contributed to an amplification efficiency of 98.42%. The number of copies of the 16S rRNA gene was linearly related to cell density, and this linear relationship was used to construct a quantitative curve (R² =0.9981) with a detection limit of 15.1 colony-forming units mL^-1·reaction^-1. qPCR in combination with an optimal PMA concentration (60 μM) helped in discriminating and quantifying the viable cells, without any interference by heat-killed cells. Compared with the conventional methods, the population heterogeneity of viable, culturable, dormant-like and membrane-permeabilized cells were well identified and quantified using qPCR during L. delbrueckii spp. bulgaricus sp1.1 batch culture. Despite the restriction in the enumeration of lysed cells, qPCR-based methods facilitated reliable identification and quantification of bacterial physiological states and provided additional knowledge on the dynamics of L. delbrueckii spp. bulgaricus sp1.1 physiological states.

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

Microbial cells in bioprocesses are usually described with averaged parameters. But in fact, single cells within populations vary greatly in characteristics such as stress resistance, especially in response to carbon source gradients. Our aim was to introduce tools to quantify population heterogeneity in bioprocesses using a combination of reporter strains, flow cytometry, and easily comprehensible parameters. We calculated mean, mode, peak width, and coefficient of variance to describe distribution characteristics and temporal shifts in fluorescence intensity. The skewness and the slope of cumulative distribution function plots illustrated differences in distribution shape. These parameters are person-independent and precise. We demonstrated this by quantifying growth-related population heterogeneity of Saccharomyces cerevisiae and Escherichia coli reporter strains in steady-state of aerobic glucose-limited chemostat cultures at different dilution rates and in response to glucose pulses. Generally, slow-growing cells showed stronger responses to glucose excess than fast-growing cells. Cell robustness, measured as membrane integrity after exposure to freeze-thaw treatment, of fast-growing cells was strongly affected in subpopulations of low membrane robustness. Glucose pulses protected subpopulations of fast-growing but not slower-growing yeast cells against membrane damage. Our parameters could successfully describe population heterogeneity, thereby revealing physiological characteristics that might have been overlooked during traditional averaged analysis.