Real-time on-line flow cytometry for bioprocess monitoring

Advances and opportunities in process analytical technologies for viral vector manufacturing

Viral vectors are an emerging, exciting class of biologics whose application in vaccines, oncology, and gene therapy has grown exponentially in recent years. Following first regulatory approval, this class of therapeutics has been vigorously pursued to treat monogenic disorders including orphan diseases, entering hundreds of new products into pipelines. Viral vector manufacturing supporting clinical efforts has spurred the introduction of a broad swath of analytical techniques dedicated to assessing the diverse and evolving panel of Critical Quality Attributes (CQAs) of these products. Herein, we provide an overview of the current state of analytics enabling measurement of CQAs such as capsid and vector identities, product titer, transduction efficiency, impurity clearance etc. We highlight orthogonal methods and discuss the advantages and limitations of these techniques while evaluating their adaptation as process analytical technologies. Finally, we identify gaps and propose opportunities in enabling existing technologies for real-time monitoring from hardware, software, and data analysis viewpoints for technology development within viral vector biomanufacturing.

Use of a sample injection loop for an accurate measurement of particle number concentration by flow cytometry

Flow cytometry plays a pivotal role in biotechnology by providing quantitative measurements for a wide range of applications. Nonetheless, achieving precise particle quantification, particularly without relying on counting beads, remains a challenge. In this study, we introduce a novel exhaustive counting method featuring a sample loop-based injection system that delivers a defined sample volume to a detection system to enhance quantification in flow cytometry. We systematically assess the performance characteristics of this system with micron-sized polystyrene beads, addressing issues related to sample introduction, adsorption, and volume measurement. Results underscore the excellent analytical performance of the proposed method, characterized by high linearity and repeatability. We compare our approach to counting bead-based measurements, and while an approximate bias value was observed, the measured values were found to be similar between the methods, demonstrating its comparability and reliability. This method holds great promise for improving the accuracy and precision of particle quantification in flow cytometry, with implications for various fields including healthcare and environmental monitoring.

Comparative Approaches for Quantification of Product Yield in a Model Recombinant Green Fluorescent Protein Expressed in E. coli

Process Analytical Technologies (PAT) used to monitor and control manufacturing processes are crucial for efficient and automated bioprocessing, which is in congruence with lights-off-manufacturing and Industry 4.0 initiatives. As biomanufacturing seeks to realize more high-throughput and automated operation, an increasing need for multimodal analysis of process metrics becomes essential. Herein, we detail a series of methods for analyzing product yield from a bioreactor and how to conduct cross-method comparisons. We employ a model system of Escherichia coli (E. coli) expression of green fluorescent protein (GFP), which is a simple, cost effective model for students and educators to replicate at different scales. GFP is an ideal analytical marker as it is easy to visualize due to its fluorescence which indicates cellular protein expression, cell localization and physiological changes of the cell population. In this study, samples from a 300 L bioreactor with GFP-expressing E. coli are analyzed to improve product yield and bioprocessing efficiency. Utilizing a fed-batch process for enhanced cell density and product titer, this bioreactor runs on a 24-hour schedule from inoculation to GFP induction and final harvest. To reliably quantify relative GFP expression and E. coli proliferation, we provide simple protocols and example results for comparing three different analytical methods: (1) in-line bioreactor measurements, (2) plate reader assays, and (3) microscopy. The GFP and cell density results follow similar trends based on the various inline and offline analytical methods and show a peak of GFP expression and cell density between 12.5 and 18 hours post inoculation.

Adaptive modeling optimized by the data fusion strategy: Real-time dying cell percentage prediction using capacitance spectroscopy

The previous research showcased a partial least squares (PLS) regression model accurately predicting cell death percentages using in-line capacitance spectra. The current study advances the model accuracy through adaptive modeling employing a data fusion approach. This strategy enhances prediction performance by incorporating variables from the Cole-Cole model, conductivity and its derivatives over time, and Mahalanobis distance into the predictor matrix (X-matrix). Firstly, the Cole-Cole model, a mechanistic model with parameters linked to early cell death onset, was integrated to enhance prediction performance. Secondly, the inclusion of conductivity and its derivatives over time in the X-matrix mitigated prediction fluctuations resulting from abrupt conductivity changes during process operations. Thirdly, Mahalanobis distance, depicting spectral changes relative to a reference spectrum from a previous time point, improved model adaptability to independent test sets, thereby enhancing performance. The final data fusion model substantially decreased root-mean squared error of prediction (RMSEP) by around 50%, which is a significant boost in prediction accuracy compared to the prior PLS model. Robustness against reference spectrum selection was confirmed by consistent performance across various time points. In conclusion, this study illustrates that the data fusion strategy substantially enhances the model accuracy compared to the previous model relying solely on capacitance spectra.

Application of an Escherichia coli triple reporter strain for at-line monitoring of single-cell physiology during L-phenylalanine production

Biotechnological production processes are sustainable approaches for the production of biobased components such as amino acids for food and feed industry. Scale-up from ideal lab-scale bioreactors to large-scale processes is often accompanied by loss in productivity. This may be related to population heterogeneities of cells originating from isogenic cultures that arise due to dynamic non-ideal conditions in the bioreactor. To better understand this phenomenon, deeper insights into single-cell physiologies in bioprocesses are mandatory before scale-up. Here, a triple reporter strain (3RP) was developed by chromosomally integrating the fluorescent proteins mEmerald, CyOFP1, and mTagBFP2 into the L-phenylalanine producing Escherichia coli strain FUS4 (pF81kan) to allow monitoring of growth, oxygen availability, and general stress response of the single cells. Functionality of the 3RP was confirmed in well-mixed lab-scale fed-batch processes with glycerol as carbon source in comparison to the strain without fluorescent proteins, leading to no difference in process performance. Fluorescence levels could successfully reflect the course of related process state variables, revealed population heterogeneities during the transition between different process phases and potentially subpopulations that exhibit superior process performance. Furthermore, indications were found for noise in gene expression as regulation strategy against environmental perturbation.

Stable production of recombinant SARS-CoV-2 receptor-binding domain in mammalian cells with co-expression of a fluorescent reporter and its validation as antigenic target for COVID-19 serology testing

SARS-CoV-2 receptor binding domain (RBD) recognizes the angiotensin converting enzyme 2 (ACE2) receptor in host cells that enables infection. Due to its antigenic specificity, RBD production is important for development of serological assays. Here we have established a system for stable RBD production in HEK 293T mammalian cells that simultaneously express the recombinant fluorescent protein dTomato, which enables kinetic monitoring of RBD expression by fluorescence microscopy. In addition, we have validated the use of this recombinant RBD in an ELISA assay for the detection of anti-RBD antibodies in serum samples of COVID-19 convalescent patients. Recombinant RBD generated using this approach can be useful for generation of antibody-based therapeutics against SARS-CoV-2, as well serological assays aimed to test antibody responses to this relevant virus.

On-line untargeted metabolomics monitoring of an E. coli succinate fermentation process

The real‐time monitoring of metabolites (RTMet) is instrumental for the industrial production of biobased fermentation products. This study shows the first application of untargeted on‐line metabolomics for the monitoring of undiluted fermentation broth samples taken automatically from a 5 L bioreactor every 5 min via flow injection mass spectrometry. The travel time from the bioreactor to the mass spectrometer was 30 s. Using mass spectrometry allows, on the one hand, the direct monitoring of targeted key process compounds of interest and, on the other hand, provides information on hundreds of additional untargeted compounds without requiring previous calibration data. In this study, this technology was applied in an Escherichia coli succinate fermentation process and 886 different m/z signals were monitored, including key process compounds (glucose, succinate, and pyruvate), potential biomarkers of biomass formation such as (R)‐2,3‐dihydroxy‐isovalerate and (R)‐2,3‐dihydroxy‐3‐methylpentanoate and compounds from the pentose phosphate pathway and nucleotide metabolism, among others. The main advantage of the RTMet technology is that it allows the monitoring of hundreds of signals without the requirement of developing partial least squares regression models, making it a perfect tool for bioprocess monitoring and for testing many different strains and process conditions for bioprocess development.

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.

Flow cytometric analysis reveals culture condition dependent variations in phenotypic heterogeneity of Limosilactobacillus reuteri

Optimisation of cultivation conditions in the industrial production of probiotics is crucial to reach a high-quality product with retained probiotic functionality. Flow cytometry-based descriptors of bacterial morphology may be used as markers to estimate physiological fitness during cultivation, and can be applied for online monitoring to avoid suboptimal growth. In the current study, the effects of temperature, initial pH and oxygen levels on cell growth and cell size distributions of Limosilactobacillus reuteri DSM 17938 were measured using multivariate flow cytometry. A pleomorphic behaviour was evident from the measurements of light scatter and pulse width distributions. A pattern of high growth yielding smaller cells and less heterogeneous populations could be observed. Analysis of pulse width distributions revealed significant morphological heterogeneities within the bacterial cell population under non-optimal growth conditions, and pointed towards low temperature, high initial pH, and high oxygen levels all being triggers for changes in morphology towards cell chain formation. However, cell size did not correlate to survivability after freeze-thaw or freeze-drying stress, indicating that it is not a key determinant for physical stress tolerance. The fact that L. reuteri morphology varies depending on cultivation conditions suggests that it can be used as marker for estimating physiological fitness and responses to its environment.

Characterization of cell cycle and apoptosis in Chinese hamster ovary cell culture using flow cytometry for bioprocess monitoring

Chinese hamster ovary (CHO) cells are by far the most important mammalian cell lines used for producing antibodies and other therapeutic proteins. It is critical to fully understand their physiological conditions during a bioprocess in order to achieve the highest productivity and the desired product quality. Flow cytometry technology possesses unique advantages for measuring multiple cellular attributes for a given cell and examining changes in cell culture heterogeneity over time that can be used as metrics for enhanced process understanding and control strategy. Flow cytometry-based assays were utilized to examine the progression of cell cycle and apoptosis in three case studies using different antibody-producing CHO cell lines in both fed-batch and perfusion bioprocesses. In our case studies, we found that G0/G1 phase distribution and early apoptosis accumulation responded to subtle changes in culture conditions, such as pH shifting or momentary glucose depletion. In a perfusion process, flow cytometry provided an insightful understanding of the cell physiological status under a hypothermic condition. More importantly, these changes in cell cycle and apoptosis were not detected by a routine trypan blue exclusion-based cell counting and viability measurement. In summary, integration of flow cytometry into bioprocesses as a process analytical technology tool can be beneficial for establishing optimum process conditions and process control.

Triangulation of microbial fingerprinting in anaerobic digestion reveals consistent fingerprinting profiles

The anaerobic digestion microbiome has been puzzling us since the dawn of molecular methods for mixed microbial community analysis. Monitoring of the anaerobic digestion microbiome can either take place via a non-targeted holistic evaluation of the microbial community through fingerprinting or by targeted monitoring of selected taxa. Here, we compared four different microbial community fingerprinting methods, i.e., amplicon sequencing, metaproteomics, metabolomics and cytomics, in their ability to characterise the full-scale anaerobic digestion microbiome. Cytometric fingerprinting through cytomics reflects a, for anaerobic digestion, novel, single cell-based approach of direct microbial community fingerprinting by flow cytometry. Three different digester types, i.e., sludge digesters, digesters treating agro-industrial waste and dry anaerobic digesters, each reflected different operational parameters. The α-diversity analysis yielded inconsistent results, especially for richness, across the different methods. In contrast, β-diversity analysis resulted in comparable profiles, even when translated into phyla or functions, with clear separation of the three digester types. In-depth analysis of each method's features i.e., operational taxonomic units, metaproteins, metabolites, and cytometric traits, yielded certain similar features, yet, also some clear differences between the different methods, which was related to the complexity of the anaerobic digestion process. In conclusion, cytometric fingerprinting through flow cytometry is a reliable, fast method for holistic monitoring of the anaerobic digestion microbiome, and the complementary identification of key features through other methods could give rise to a direct interpretation of anaerobic digestion process performance.

Real-Time Mass Spectrometry Measurements of Respiration Rates in Biological Systems

Many organisms process carbon and other nutrients to generate energy through aerobic respiration where organic carbon compounds are broken down and oxygen is consumed, producing carbon dioxide and water. Respiration is indicative of active metabolism, and respiration rates are proportional to the amount of living biomass in an ecosystem. Although there are many methods for measuring respiration rates in the laboratory, current systems, such as infrared gas analyzers, are limited in their ability to independently resolve isotopomer fluxes across a range of relevant gases including both CO₂ and O₂ in real-time. Therefore, monitoring of biological respiration in real time under controlled laboratory conditions would enable better understanding of cellular physiology. To address this challenge, we developed a real time mass spectrometry (RTMS) manifold that simultaneously measures production and consumption of multiple gases and their isotopologues in seconds with the speed and sensitivity necessary to characterize rapidly changing respiration events as they occur. This universal manifold can be fitted to a variety of instruments and affords the same analytical precision and accuracy of the instrument while allowing for the real time measurements. Here, we paired the manifold to a single quad MS with an electron impact (EI) source operated in scan mode to detect extracted target gases by their respective masses (e.g., ¹²CO₂ at mass 44, ¹³CO₂ at 45). We demonstrated applicability of the RTMS instrument to different biological ecosystems (bacterial cultures, plants, and soil), and in all cases, we were able to detect simultaneous and rapid measurements of multiple gases in real time, providing novel insights into complex respiratory metabolism and the influence of biological and environmental factors.

Culture medium density as a simple monitoring tool for cell integrity of Escherichia coli

During the expression of recombinant proteins in the periplasm of Escherichia coli, the integrity of the outer membrane can change, so that product leaks to the medium. Additional stress can induce lysis, the complete disintegration of both inner and outer membrane, leading to release of both product and host cell proteins. Whether leakiness is unwanted or intentional, appropriate monitoring of leakiness and its distinction from lysis is necessary to ensure product quality and process performance. Here, we investigated a novel monitoring tool for leakiness and lysis based on the measurement of the culture supernatant density. The method benefits from short analysis time and low analytical error, simple result output, relatively low cost, low risk of operator errors and the option of easy on-line implementation. Although limitations exist regarding selectivity, we could show that the method is capable of detecting changes in cell integrity. This tool is therefore an interesting addition to the monitoring toolbox for industrial E. coli bioprocesses.

High level extracellular production of recombinant human interferon alpha 2b in glycoengineered Pichia pastoris: culture medium optimization, high cell density cultivation and biological characterization

AIMS

The present study was aimed at design of experiments (DoE)- and artificial intelligence-based culture medium optimization for high level extracellular production of a novel recombinant human interferon alpha 2b (huIFNα2b) in glycoengineered Pichia pastoris and its characterization.

METHODS AND RESULTS

The artificial neural network-genetic algorithm model exhibited improved huIFNα2b production and better predictability compared to response surface methodology. The optimized medium exhibited a fivefold increase in huIFNα2b titre compared to the complex medium. A maximum titre of huIFNα2b (436 mg l^-1 ) was achieved using the optimized medium in the bioreactor. Real-time capacitance data from dielectric spectroscopy were utilized to model the growth kinetics with unstructured models. Biological characterization by antiproliferative assay proved that the purified recombinant huIFNα2b was biologically active, exhibiting growth inhibition on breast cancer cell line.

CONCLUSIONS

Culture medium optimization resulted in enhanced production of huIFNα2b in glycoengineered P. pastoris at both shake flask and bioreactor level. The purified huIFNα2b was found to be N-glycosylated and biologically active.

SIGNIFICANCE AND IMPACT OF THE STUDY

DoE-based medium optimization strategy significantly improved huIFNα2b production. The antiproliferative activity of huIFNα2b substantiates its potential scope for application in cancer therapy.

Flow cytometry applications in water treatment, distribution, and reuse: A review

Ensuring safe and effective water treatment, distribution, and reuse requires robust methods for characterizing and monitoring waterborne microbes. Methods widely used today can be limited by low sensitivity, high labor and time requirements, susceptibility to interference from inhibitory compounds, and difficulties in distinguishing between viable and non-viable cells. Flow cytometry (FCM) has recently gained attention as an alternative approach that can overcome many of these challenges. This article critically and systematically reviews for the first time recent literature on applications of FCM in water treatment, distribution, and reuse. In the review, we identify and examine nearly 300 studies published from 2000 to 2018 that illustrate the benefits and challenges of using FCM for assessing source-water quality and impacts of treatment-plant discharge on receiving waters, wastewater treatment, drinking water treatment, and drinking water distribution. We then discuss options for combining FCM with other indicators of water quality and address several topics that cut across nearly all applications reviewed. Finally, we identify priority areas in which more work is needed to realize the full potential of this approach. These include optimizing protocols for FCM-based analysis of waterborne viruses, optimizing protocols for specifically detecting target pathogens, automating sample handling and preparation to enable real-time FCM, developing computational tools to assist data analysis, and improving standards for instrumentation, methods, and reporting requirements. We conclude that while more work is needed to realize the full potential of FCM in water treatment, distribution, and reuse, substantial progress has been made over the past two decades. There is now a sufficiently large body of research documenting successful applications of FCM that the approach could reasonably and realistically see widespread adoption as a routine method for water quality assessment.

Single-Cell Approach to Monitor the Unfolded Protein Response During Biotechnological Processes With Pichia pastoris

Pichia pastoris (Komagataella sp.) is broadly used for the production of secreted recombinant proteins. Due to the high rate of protein production, incorrectly folded proteins may accumulate in the endoplasmic reticulum (ER). To restore their proper folding, the cell triggers the unfolded protein response (UPR); however, if the proteins cannot be repaired, they are degraded, which impairs process productivity. Moreover, a non-producing/non-secreting subpopulation of cells might occur, which also decreases overall productivity. Therefore, an in depth understanding of intracellular protein fluxes and population heterogeneity is needed to improve productivity. Under industrially relevant cultivation conditions in bioreactors, we cultured P. pastoris strains producing three different recombinant proteins: penicillin G acylase from Escherichia coli (EcPGA), lipase B from Candida antarctica (CaLB) and xylanase A from Thermomyces lanuginosus (TlXynA). Extracellular and intracellular product concentrations were determined, along with flow cytometry-based single-cell measurements of cell viability and the up-regulation of UPR. The cell population was distributed into four clusters, two of which were viable cells with no UPR up-regulation, differing in cell size and complexity. The other two clusters were cells with impaired viability, and cells with up-regulated UPR. Over the time course of cultivation, the distribution of the population into these four clusters changed. After 30 h of production, 60% of the cells producing EcPGA, which accumulated in the cells (50-70% of the product), had up-regulated UPR, but only 13% of the cells had impaired viability. A higher proportion of cells with decreased viability was observed in strains producing CaLB (20%) and TlXynA (27%). The proportion of cells with up-regulated UPR in CaLB-producing (35%) and TlXynA-producing (30%) strains was lower in comparison to the EcPGA-producing strain, and a smaller proportion of CaLB and TlXynA (<10%) accumulated in the cells. These data provide an insight into the development of heterogeneity in a recombinant P. pastoris population during a biotechnological process. A deeper understanding of the relationship between protein production/secretion and the regulation of the UPR might be utilized in bioprocess control and optimization with respect to secretion and population heterogeneity.

In Silico Prediction of Large-Scale Microbial Production Performance: Constraints for Getting Proper Data-Driven Models

Industrial bioreactors range from 10.000 to 700.000 L and characteristically show different zones of substrate availabilities, dissolved gas concentrations and pH values reflecting physical, technical and economic constraints of scale-up. Microbial producers are fluctuating inside the bioreactors thereby experiencing frequently changing micro-environmental conditions. The external stimuli induce responses on microbial metabolism and on transcriptional regulation programs. Both may deteriorate the expected microbial production performance in large scale compared to expectations deduced from ideal, well-mixed lab-scale conditions. Accordingly, predictive tools are needed to quantify large-scale impacts considering bioreactor heterogeneities. The review shows that the time is right to combine simulations of microbial kinetics with calculations of large-scale environmental conditions to predict the bioreactor performance. Accordingly, basic experimental procedures and computational tools are presented to derive proper microbial models and hydrodynamic conditions, and to link both for bioreactor modeling. Particular emphasis is laid on the identification of gene regulatory networks as the implementation of such models will surely gain momentum in future studies.

Analysis of population structures of the microalga Acutodesmus obliquus during lipid production using multi-dimensional single-cell analysis

Microalgae bear a great potential to produce lipids for biodiesel, feed, or even food applications. To understand the still not well-known single-cell dynamics during lipid production in microalgae, a novel single-cell analytical technology was applied to study a well-established model experiment. Multidimensional single-cell dynamics were investigated with a non-supervised image analysis technique that utilizes data from epi-fluorescence microscopy. Reliability of this technique was successfully proven via reference analysis. The technique developed was used to determine cell size, chlorophyll amount, neutral lipid amount, and deriving properties on a single-cellular level in cultures of the biotechnologically promising alga Acutodesmus obliquus. The results illustrated a high correlation between cell size and chlorophyll amount, but a very low and dynamic correlation between cell size, lipid amount, and lipid density. During growth conditions under nitrogen starvation, cells with low chlorophyll content tend to start the lipid production first and the cell suspension differentiated in two subpopulations with significantly different lipid contents. Such quantitative characterization of single-cell dynamics of lipid synthesizing algae was done for the first time and the potential of such simple technology is highly relevant to other biotechnological applications and to deeper investigate the process of microalgal lipid accumulation.

Integrating metabolic modeling and population heterogeneity analysis into optimizing recombinant protein production by Komagataella (Pichia) pastoris

The methylotrophic yeast Komagataella (Pichia) pastoris has become one of the most utilized cell factories for the production of recombinant proteins over the last three decades. This success story is linked to its specific physiological traits, i.e., the ability to grow at high cell density in inexpensive culture medium and to secrete proteins at high yield. Exploiting methanol metabolism is at the core of most P. pastoris-based processes but comes with its own challenges. Co-feeding cultures with glycerol/sorbitol and methanol is a promising approach, which can benefit from improved understanding and prediction of metabolic response. The development of profitable processes relies on the construction and selection of efficient producing strains from less efficient ones but also depends on the ability to master the bioreactor process itself. More specifically, how a bioreactor processes could be monitored and controlled to obtain high yield of production. In this review, new perspectives are detailed regarding a multi-faceted approach to recombinant protein production processes by P. pastoris; including gaining improved understanding of the metabolic pathways involved, accounting for variations in transcriptional and translational efficiency at the single cell level and efficient monitoring and control of methanol levels at the bioreactor level.

Laboratory-Scale Simulation and Real-Time Tracking of a Microbial Contamination Event and Subsequent Shock-Chlorination in Drinking Water

Rapid contamination of drinking water in distribution and storage systems can occur due to pressure drop, backflow, cross-connections, accidents, and bio-terrorism. Small volumes of a concentrated contaminant (e.g., wastewater) can contaminate large volumes of water in a very short time with potentially severe negative health impacts. The technical limitations of conventional, cultivation-based microbial detection methods neither allow for timely detection of such contaminations, nor for the real-time monitoring of subsequent emergency remediation measures (e.g., shock-chlorination). Here we applied a newly developed continuous, ultra high-frequency flow cytometry approach to track a rapid pollution event and subsequent disinfection of drinking water in an 80-min laboratory scale simulation. We quantified total (TCC) and intact (ICC) cell concentrations as well as flow cytometric fingerprints in parallel in real-time with two different staining methods. The ingress of wastewater was detectable almost immediately (i.e., after 0.6% volume change), significantly changing TCC, ICC, and the flow cytometric fingerprint. Shock chlorination was rapid and detected in real time, causing membrane damage in the vast majority of bacteria (i.e., drop of ICC from more than 380 cells μl^-1 to less than 30 cells μl^-1 within 4 min). Both of these effects as well as the final wash-in of fresh tap water followed calculated predictions well. Detailed and highly quantitative tracking of microbial dynamics at very short time scales and for different characteristics (e.g., concentration, membrane integrity) is feasible. This opens up multiple possibilities for targeted investigation of a myriad of bacterial short-term dynamics (e.g., disinfection, growth, detachment, operational changes) both in laboratory-scale research and full-scale system investigations in practice.

Bioprocess scale-up/down as integrative enabling technology: from fluid mechanics to systems biology and beyond

Efficient optimization of microbial processes is a critical issue for achieving a number of sustainable development goals, considering the impact of microbial biotechnology in agrofood, environment, biopharmaceutical and chemical industries. Many of these applications require scale-up after proof of concept. However, the behaviour of microbial systems remains unpredictable (at least partially) when shifting from laboratory-scale to industrial conditions. The need for robust microbial systems is thus highly needed in this context, as well as a better understanding of the interactions between fluid mechanics and cell physiology. For that purpose, a full scale-up/down computational framework is already available. This framework links computational fluid dynamics (CFD), metabolic flux analysis and agent-based modelling (ABM) for a better understanding of the cell lifelines in a heterogeneous environment. Ultimately, this framework can be used for the design of scale-down simulators and/or metabolically engineered cells able to cope with environmental fluctuations typically found in large-scale bioreactors. However, this framework still needs some refinements, such as a better integration of gas-liquid flows in CFD, and taking into account intrinsic biological noise in ABM.

Tailor-made PAT platform for safe syngas fermentations in batch, fed-batch and chemostat mode with Rhodospirillum rubrum

Recently, syngas has gained significant interest as renewable and sustainable feedstock, in particular for the biotechnological production of poly([R]‐3‐hydroxybutyrate) (PHB). PHB is a biodegradable, biocompatible polyester produced by some bacteria growing on the principal component of syngas, CO. However, working with syngas is challenging because of the CO toxicity and the explosion danger of H₂, another main component of syngas. In addition, the bioprocess control needs specific monitoring tools and analytical methods that differ from standard fermentations. Here, we present a syngas fermentation platform with a focus on safety installations and process analytical technology (PAT) that serves as a basis to assess the physiology of the PHB‐producing bacterium Rhodospirillum rubrum. The platform includes (i) off‐gas analysis with an online quadrupole mass spectrometer to measure CO consumption and production rates of H₂ and CO₂, (ii) an at‐line flow cytometer to determine the total cell count and the intracellular PHB content and (iii) different online sensors, notably a redox sensor that is important to confirm that the culture conditions are suitable for the CO metabolization of R. rubrum. Furthermore, we present as first applications of the platform a fed‐batch and a chemostat process with R. rubrum for PHB production from syngas.

Taking control over microbial populations: Current approaches for exploiting biological noise in bioprocesses

Phenotypic plasticity of microbial cells has attracted much attention and several research efforts have been dedicated to the description of methods aiming at characterizing phenotypic heterogeneity and its impact on microbial populations. However, different approaches have also been suggested in order to take benefit from noise in a bioprocess perspective, e.g. by increasing the robustness or productivity of a microbial population. This review is dedicated to outline these controlling methods. A common issue, that has still to be addressed, is the experimental identification and the mathematical expression of noise. Indeed, the effective interfacing of microbial physiology with external parameters that can be used for controlling physiology depends on the acquisition of reliable signals. Latest technologies, like single cell microfluidics and advanced flow cytometric approaches, enable linking physiology, noise, heterogeneity in productive microbes with environmental cues and hence allow correctly mapping and predicting biological behavior via mathematical representations. However, like in the field of electronics, signals are perpetually subjected to noise. If appropriately interpreted, this noise can give an additional insight into the behavior of the individual cells within a microbial population of interest. This review focuses on recent progress made at describing, treating and exploiting biological noise in the context of microbial populations used in various bioprocess applications.

Simple monitoring of cell leakiness and viability in Escherichia coli bioprocesses-A case study

In a recently published study, we developed a simple methodology to monitor Escherichia coli cell integrity and lysis during bioreactor cultivations, where we intentionally triggered leakiness. In this follow-up study, we used this methodology, comprising the measurement of extracellular alkaline phosphatase to monitor leakiness and flow cytometry to follow viability, to investigate the effect of process parameters on a recombinant E. coli strain producing the highly valuable vascular endothelial growth factor A165 (VEGF-A165) in the periplasm. Since the amount of soluble product was very little (<500 μg/g dry cell weight), we directly linked the effect of the three process parameters temperature, specific uptake rate of the inducer arabinose and specific growth rate (μ) to cell integrity and viability. We found that a low temperature and a high μ were beneficial for cell integrity and that an elevated temperature resulted in reduced viability. We concluded that the recombinant E. coli cells producing VEGF-A165 in the periplasm should be cultivated at low temperature and high μ to reduce leakiness and guarantee high viability. Summarizing, in this follow-up study we demonstrate the usefulness of our simple methodology to monitor leakiness and viability of recombinant E. coli cells during bioreactor cultivations.

Automated optogenetic feedback control for precise and robust regulation of gene expression and cell growth

Dynamic control of gene expression can have far-reaching implications for biotechnological applications and biological discovery. Thanks to the advantages of light, optogenetics has emerged as an ideal technology for this task. Current state-of-the-art methods for optical expression control fail to combine precision with repeatability and cannot withstand changing operating culture conditions. Here, we present a novel fully automatic experimental platform for the robust and precise long-term optogenetic regulation of protein production in liquid Escherichia coli cultures. Using a computer-controlled light-responsive two-component system, we accurately track prescribed dynamic green fluorescent protein expression profiles through the application of feedback control, and show that the system adapts to global perturbations such as nutrient and temperature changes. We demonstrate the efficacy and potential utility of our approach by placing a key metabolic enzyme under optogenetic control, thus enabling dynamic regulation of the culture growth rate with potential applications in bacterial physiology studies and biotechnology.

At-line determining spore germination of Penicillium chrysogenum bioprocesses in complex media

Spore inoculum quality in filamentous bioprocesses is a critical parameter associated with viable spore concentration (1) and spore germination (2). It influences pellet morphology and, consequently, process performance. The state-of-the-art method to measure viable spore concentration is tedious, associated with significant inherent bias, and not applicable in real-time. Therefore, it is not usable as process analytical technology (PAT). Spore germination has so far been monitored using image analysis, which is hampered by complex medium background often observed in filamentous bioprocesses. The method presented here is based on the combination of viability staining and large-particle flow cytometry which enables measurements in real-time and hence aims to be applicable as a PAT tool. It is compatible with the complex media background and allows the quantification of metabolically active spores and the monitoring of spore germination. A distinction of germinated spores and not germinated spores was based on logistic regression, using multiparameteric data from flow cytometry. In a first step, a significant correlation between colony-forming unit (CFU) counts and viable spore concentration (1) in an industrially relevant model bioprocess was found. Spore germination (2) was followed over the initial process phase with close temporal resolution. The validation of the method showed an error below 5 %. Differences in spore germination for various spore inocula ages and spore inoculum concentrations were monitored. The real-time applicability of the method suggests the implementation as a PAT tool in filamentous bioprocesses.

Multi-parameter flow cytometry as a process analytical technology (PAT) approach for the assessment of bacterial ghost production

Flow cytometry (FCM) is a tool for the analysis of single-cell properties in a cell suspension. In this contribution, we present an improved FCM method for the assessment of E-lysis in Enterobacteriaceae. The result of the E-lysis process is empty bacterial envelopes-called bacterial ghosts (BGs)-that constitute potential products in the pharmaceutical field. BGs have reduced light scattering properties when compared with intact cells. In combination with viability information obtained from staining samples with the membrane potential-sensitive fluorescent dye bis-(1,3-dibutylarbituric acid) trimethine oxonol (DiBAC4(3)), the presented method allows to differentiate between populations of viable cells, dead cells, and BGs. Using a second fluorescent dye RH414 as a membrane marker, non-cellular background was excluded from the data which greatly improved the quality of the results. Using true volumetric absolute counting, the FCM data correlated well with cell count data obtained from colony-forming units (CFU) for viable populations. Applicability of the method to several Enterobacteriaceae (different Escherichia coli strains, Salmonella typhimurium, Shigella flexneri 2a) could be shown. The method was validated as a resilient process analytical technology (PAT) tool for the assessment of E-lysis and for particle counting during 20-l batch processes for the production of Escherichia coli Nissle 1917 BGs.

Fluorescence-based tools for single-cell approaches in food microbiology

The better understanding of the functioning of microbial communities is a challenging and crucial issue in the field of food microbiology, as it constitutes a prerequisite to the optimization of positive and technological microbial population functioning, as well as for the better control of pathogen contamination of food. Heterogeneity appears now as an intrinsic and multi-origin feature of microbial populations and is a major determinant of their beneficial or detrimental functional properties. The understanding of the molecular and cellular mechanisms behind the behavior of bacteria in microbial communities requires therefore observations at the single-cell level in order to overcome "averaging" effects inherent to traditional global approaches. Recent advances in the development of fluorescence-based approaches dedicated to single-cell analysis provide the opportunity to study microbial communities with an unprecedented level of resolution and to obtain detailed insights on the cell structure, metabolism activity, multicellular behavior and bacterial interactions in complex communities. These methods are now increasingly applied in the field of food microbiology in different areas ranging from research laboratories to industry. In this perspective, we reviewed the main fluorescence-based tools used for single-cell approaches and their concrete applications with specific focus on food microbiology.

Single bacteria movement tracking by online microscopy--a proof of concept study

In this technical report we demonstrate a low-cost online unit allowing movement tracking of flagellated bacteria on a single-cell level during fermentation processes. The system's ability to distinguish different metabolic states (viability) of bacteria by movement velocity was investigated. A flow-through cuvette with automatically adjustable layer thickness was developed. The cuvette can be used with most commercially available laboratory microscopes equipped with 40× amplification and a digital camera. In addition, an automated sample preparation unit and a software module was developed measuring size, moved distance, and speed of bacteria. In a proof of principle study the movement velocities of Bacillus amyloliquefaciens FZB42 during three batch fermentation processes were investigated. In this process the bacteria went through different metabolic states, vegetative growth, diauxic shift, vegetative growth after diauxic shift, and sporulation. It was shown that the movement velocities during the different metabolic states significantly differ from each other. Therefore, the described setup has the potential to be used as a bacteria viability monitoring tool. In contrast to some other techniques, such as electro-optical techniques, this method can even be used in turbid production media.

Monitoring of Microalgal Processes

Process monitoring, which can be defined as the measurement of process variables with the smallest possible delay, is combined with process models to form the basis for successful process control. Minimizing the measurement delay leads inevitably to employing online, in situ sensors where possible, preferably using noninvasive measurement methods with stable, low-cost sensors. Microalgal processes have similarities to traditional bioprocesses but also have unique monitoring requirements. In general, variables to be monitored in microalgal processes can be categorized as physical, chemical, and biological, and they are measured in gaseous, liquid, and solid (biological) phases. Physical and chemical process variables can be usually monitored online using standard industrial sensors. The monitoring of biological process variables, however, relies mostly on sensors developed and validated using laboratory-scale systems or uses offline methods because of difficulties in developing suitable online sensors. Here, we review current technologies for online, in situ monitoring of all types of process parameters of microalgal cultivations, with a focus on monitoring of biological parameters. We discuss newly introduced methods for measuring biological parameters that could be possibly adapted for routine online use, should be preferably noninvasive, and are based on approaches that have been proven in other bioprocesses. New sensor types for measuring physicochemical parameters using optical methods or ion-specific field effect transistor (ISFET) sensors are also discussed. Reviewed methods with online implementation or online potential include measurement of irradiance, biomass concentration by optical density and image analysis, cell count, chlorophyll fluorescence, growth rate, lipid concentration by infrared spectrophotometry, dielectric scattering, and nuclear magnetic resonance. Future perspectives are discussed, especially in the field of image analysis using in situ microscopy, infrared spectrophotometry, and software sensor systems.

The feasibility of automated online flow cytometry for in-situ monitoring of microbial dynamics in aquatic ecosystems

Fluorescent staining coupled with flow cytometry (FCM) is often used for the monitoring, quantification and characterization of bacteria in engineered and environmental aquatic ecosystems including seawater, freshwater, drinking water, wastewater, and industrial bioreactors. However, infrequent grab sampling hampers accurate characterization and subsequent understanding of microbial dynamics in all of these ecosystems. A logic technological progression is high throughput and full automation of the sampling, staining, measurement, and data analysis steps. Here we assess the feasibility and applicability of automated FCM by means of actual data sets produced with prototype instrumentation. As proof-of-concept we demonstrate examples of microbial dynamics in (i) flowing tap water from a municipal drinking water supply network and (ii) river water from a small creek subject to two rainfall events. In both cases, automated measurements were done at 15-min intervals during 12-14 consecutive days, yielding more than 1000 individual data points for each ecosystem. The extensive data sets derived from the automated measurements allowed for the establishment of baseline data for each ecosystem, as well as for the recognition of daily variations and specific events that would most likely be missed (or miss-characterized) by infrequent sampling. In addition, the online FCM data from the river water was combined and correlated with online measurements of abiotic parameters, showing considerable potential for a better understanding of cause-and-effect relationships in aquatic ecosystems. Although several challenges remain, the successful operation of an automated online FCM system and the basic interpretation of the resulting data sets represent a breakthrough toward the eventual establishment of fully automated online microbiological monitoring technologies.

Monitoring of dynamic microbiological processes using real-time flow cytometry

We describe a straightforward approach to continuously monitor a variety of highly dynamic microbiological processes in millisecond resolution with flow cytometry, using standard bench-top instrumentation. Four main experimental examples are provided, namely: (1) green fluorescent protein expression by antibiotic-stressed Escherichia coli, (2) fluorescent labeling of heat-induced membrane damage in an autochthonous freshwater bacterial community, (3) the initial growth response of late stationary E. coli cells inoculated into fresh growth media, and (4) oxidative disinfection of a mixed culture of auto-fluorescent microorganisms. These examples demonstrate the broad applicability of the method to diverse biological experiments, showing that it allows the collection of detailed, time-resolved information on complex processes.

A low-cost, multiplexable, automated flow cytometry procedure for the characterization of microbial stress dynamics in bioreactors

Background

Microbial cell population heterogeneity is now recognized as a major source of issues in the development and optimization of bioprocesses. Even if single cell technologies are available for the study of microbial population heterogeneity, only a few of these methods are available in order to study the dynamics of segregation directly in bioreactors. In this context, specific interfaces have been developed in order to connect a flow cytometer directly to a bioreactor for automated analyses. In this work, we propose a simplified version of such an interface and demonstrate its usefulness for multiplexed experiments.

Results

A low-cost automated flow cytometer has been used in order to monitor the synthesis of a destabilized Green Fluorescent Protein (GFP) under the regulation of the fis promoter and propidium iodide (PI) uptake. The results obtained showed that the dynamics of GFP synthesis are complex and can be attributed to a complex set of biological parameters, i.e. on the one hand the release of protein into the extracellular medium and its uptake modifying the activity of the fis promoter, and on the other hand the stability of the GFP molecule itself, which can be attributed to the protease content and energy status of the cells. In this respect, multiplexed experiments have shown a correlation between heat shock and ATP content and the stability of the reporter molecule.

Conclusion

This work demonstrates that a simplified version of on-line FC can be used at the process level or in a multiplexed version to investigate the dynamics of complex physiological mechanisms. In this respect, the determination of new on-line parameters derived from automated FC is of primary importance in order to fully integrate the power of FC in dedicated feedback control loops.

Real-time monitoring of cell viability and cell density on the basis of a three dimensional optical reflectance method (3D-ORM): investigation of the effect of sub-lethal and lethal injuries

Cell density and cell viability have been followed on-line by using a three-dimensional optical reflectance method (3D-ORM) probe. This method has allowed to highlight the differences between a well-mixed and a scale-down bioreactor configured in order to reproduce mixing deficiencies during a fed-batch culture of Escherichia coli. These differences have been observed both for the obscuration factor (OBF) and the coincidence probability delivered by the probe. These parameters are correlated to flow cytometry measurement based on the PI-uptake test and cell density based on optical density measurement. This first set of results has pointed out the fact that the 3D-ORM probe is sensitive to sub-lethal injuries encountered by microbial cells in process-related conditions. The effect of lethal injuries has been further investigated on the basis of additional experiments involving heat stress and a sharp increase of the OBF has been observed indicating that cells are effectively injured by the increase of temperature. However, further improvement of the probe are needed in order to give access to single-cell measurements.

On-line monitoring of large cultivations of microalgae and cyanobacteria

Large cultivations of microalgae will benefit from on-line monitoring to achieve process control and improved productivity. This monitoring requires reliable sensors for on-line, in situ measurement of both physicochemical and biological process variables. Although standard industrial sensors can be used for many physicochemical variables, monitoring methods for most biological quantities rely on sensors that are currently suitable only for laboratory scale or off-line use. Here, we review these methods and discuss new approaches that could be adapted. We suggest that these new methods should be noninvasive and based on approaches that have already been applied to other bioprocesses; examples discussed here are in situ microscopy, flow cytometry (FC), IR spectroscopy, and software sensors.

An advanced monitoring platform for rational design of recombinant processes

Bioprocess engineering is an application-oriented science in an interdisciplinary environment, and a meaningful combination of different scientific disciplines is the only way to meet the challenges of bioprocess complexity. Setting up a reasoned process monitoring platform is the first step in an iterative procedure aiming at process and systems understanding, being the key to rational and innovative bioprocess design. This chapter describes a comprehensive process monitoring platform and how the resulting knowledge is translated into new strategies in process and/or host cell design.

Internal ribosome entry site mediates protein synthesis in yeast Pichia pastoris

The imitation of translation, as mediated by internal ribosome entry sites, has not yet been reported in Pichia pastoris. An IRES element from Saccharomyces cerevisiae was demonstrated to direct the translation of a dicistronic mRNA in P. pastoris. The 5′-untranslated region of GPR1 mRNA, termed GPR, was cloned into a dual reporter construct containing an upstream Rhizomucor miehei lipase (RML) and a downstream β-galactosidase gene (lacZ) from Escherichia coli BL21. After being transformed into P. pastoris, the RML gene and lacZ were simultaneously expressed. The possibility of DNA rearrangement, spurious splicing, or cryptic promoter in the GPR sequence were eliminated, indicating that expression of a second ORF was IRES-dependent. These findings strongly suggested that the IRES-dependent translation initiation mechanism is conserved in P. pastoris and provides a useful means to express multiple genes simultaneously.

Flow cytometry for the development of biotechnological processes with microalgae

The current interest in microalgae as a sustainable source of next generation biofuels and other valuable substances is driving exploration of their use as unique biotechnological production systems. To design and optimise appropriate production strategies, the behaviour of particular microalgal species should be well characterised under different culture conditions. Thus, flow cytometric (FCM) methods, which are already well established in environmental and toxicological studies of microalgae, are also useful for analysing the physiological state of microalgae, and have the potential to contribute to the rapid development of feasible bioprocesses. These methods are commonly based on the examination of intrinsic features of individual cells within a population (such as autofluorescence or size). Cells possessing the desired physiological or morphological features, which are detectable with or without fluorescent staining, are counted or isolated (sorted) using an FCM device. The options for implementation of FCM in the development of biotechnological processes detailed in this review are (i) analysing the chemical composition of biomass, (ii) monitoring cellular enzyme activity and cell viability, and (iii) sorting cells to isolate those overproducing the target compound or for the preparation of axenic cultures.