Tunable recombinant protein expression with E. coli in a mixed-feed environment

Avoiding the All-or-None Response in Gene Expression During E. coli Continuous Cultivation Based on the On-Line Monitoring of Cell Phenotypic Switching Dynamics

Different expression vectors are available for the effective production of recombinant proteins by bacterial populations. However, the productivity of such systems is limited by the inherent noise of the gene circuits used for the synthesis of recombinant products. An extreme case of cell-to-cell heterogeneity that has been previously reported for the ara- and lac-based expression systems in E. coli is the all-or-none response. According to this mode of response, two subpopulations of cells are generated, i.e., a "low-" subpopulation exhibiting a shallow expression level and a "high-" subpopulation exhibiting a high-expression level. The "low-" subpopulation can be considered as a cluster of non-producing cells contributing to the loss of productivity. Here we describe the setup, design, and operation of a continuous culture where inducer addition is operated based on microbial population dynamics. The determination of population dynamics is done based on an automated flow cytometry (FC) procedure previously denoted as segregostat. We illustrate how this setup can be used to control the activation of an ara-based expression system and avoid phenotypic diversification leading to an all-or-none response. Upon the determination of the natural frequency of the gene circuit used as an expression system, our current protocol can be set up without the requirement of a feedback controller.

Application of cofactors in the regulation of microbial metabolism: A state of the art review

Cofactors are crucial chemicals that maintain cellular redox balance and drive the cell to do synthetic and catabolic reactions. They are involved in practically all enzymatic activities that occur in live cells. It has been a hot research topic in recent years to manage their concentrations and forms in microbial cells by using appropriate techniques to obtain more high-quality target products. In this review, we first summarize the physiological functions of common cofactors, and give a brief overview of common cofactors acetyl coenzyme A, NAD(P)H/NAD(P)⁺, and ATP/ADP; then we provide a detailed introduction of intracellular cofactor regeneration pathways, review the regulation of cofactor forms and concentrations by molecular biological means, and review the existing regulatory strategies of microbial cellular cofactors and their application progress, to maximize and rapidly direct the metabolic flux to target metabolites. Finally, we speculate on the future of cofactor engineering applications in cell factories. Graphical Abstract.

Exploiting Information and Control Theory for Directing Gene Expression in Cell Populations

Microbial populations can adapt to adverse environmental conditions either by appropriately sensing and responding to the changes in their surroundings or by stochastically switching to an alternative phenotypic state. Recent data point out that these two strategies can be exhibited by the same cellular system, depending on the amplitude/frequency of the environmental perturbations and on the architecture of the genetic circuits involved in the adaptation process. Accordingly, several mitigation strategies have been designed for the effective control of microbial populations in different contexts, ranging from biomedicine to bioprocess engineering. Technically, such control strategies have been made possible by the advances made at the level of computational and synthetic biology combined with control theory. However, these control strategies have been applied mostly to synthetic gene circuits, impairing the applicability of the approach to natural circuits. In this review, we argue that it is possible to expand these control strategies to any cellular system and gene circuits based on a metric derived from this information theory, i.e., mutual information (MI). Indeed, based on this metric, it should be possible to characterize the natural frequency of any gene circuits and use it for controlling gene circuits within a population of cells.

Multi-level rebalancing of the naringenin pathway using riboswitch-guided high-throughput screening

Recombinant microbes have emerged as promising alternatives to natural sources of naringenin-a key molecular scaffold for flavonoids. In recombinant strains, expression levels of the pathway genes should be optimized at both transcription and the translation stages to precisely allocate cellular resources and maximize metabolite production. However, the optimization of the expression levels of naringenin generally relies on evaluating a small number of variants from libraries constructed by varying transcription efficiency only. In this study, we introduce a systematic strategy for the multi-level optimization of biosynthetic pathways. We constructed a multi-level combinatorial library covering both transcription and translation stages using synthetic T7 promoter variants and computationally designed 5'-untranslated regions. Furthermore, we identified improved strains through high-throughput screening based on a synthetic naringenin riboswitch. The most-optimized strain obtained using this approach exhibited a 3-fold increase in naringenin production, compared with the parental strain in which only the transcription efficiency was modulated. Furthermore, in a fed-batch bioreactor, the optimized strain produced 260.2 mg/L naringenin, which is the highest concentration reported to date using glycerol and p-coumaric acid as substrates. Collectively, this work provides an efficient strategy for the expression optimization of the biosynthetic pathways.

Reducing phenotypic instabilities of a microbial population during continuous cultivation based on cell switching dynamics

Predicting the fate of individual cells among a microbial population (i.e., growth and gene expression) remains a challenge, especially when this population is exposed to very dynamic environmental conditions, such as those encountered during continuous cultivation. Indeed, the dynamic nature of a continuous cultivation process implies the potential diversification of the microbial population resulting in genotypic and phenotypic heterogeneity. The present work focused on the induction of the arabinose operon in Escherichia coli as a model system to study this diversification process in continuous cultivations. As a preliminary step, the green fluorescent protein (GFP) level triggered by an arabinose-inducible ParaBAD promoter was tracked by flow cytometry in chemostat cultivations with glucose-arabinose co-feeding. For a wide range of glucose-arabinose co-feeding concentrations in the chemostats, the simultaneous occurrence of GFP positive and negative subpopulation was observed. In the second set of experiments, continuous cultivation was performed by adding glucose continuously and arabinose based on the capability of individual cells to switch from low GFP to high GFP expression states, performed with a technology setup called segregostat. In the segregostat cultivation mode, on-line flow cytometry analysis was used for adjusting the arabinose/glucose transitions based on the phenotypic switching profiles of the microbial population. This strategy allowed finding an appropriate arabinose pulsing frequency, leading to prolonged maintenance of the induction level with a limited increase in the phenotypic diversity for more than 60 generations. The results suggest that the steady forcing of individual cells into a given phenotypic trajectory may not be the best strategy for controlling cell populations. Instead, allowing individual cells to switch periodically around a predefined threshold seems to be a more robust strategy leading to oscillations, but within a predictable cell population behavior range.

Tunable expression rate control of a growth-decoupled T7 expression system by L-arabinose only

BACKGROUND

Precise regulation of gene expression is of utmost importance for the production of complex membrane proteins (MP), enzymes or other proteins toxic to the host cell. In this article we show that genes under control of a normally Isopropyl β-D-1-thiogalactopyranoside (IPTG)-inducible P_T7-lacO promoter can be induced solely with L-arabinose in a newly constructed Escherichia coli expression host BL21-AI<gp2>, a strain based on the recently published approach of bacteriophage inspired growth-decoupled recombinant protein production.

RESULTS

Here, we show that BL21-AI<gp2> is able to precisely regulate protein production rates on a cellular level in an L-arabinose concentration-dependent manner and simultaneously allows for reallocation of metabolic resources due to L-arabinose induced growth decoupling by the phage derived inhibitor peptide Gp2. We have successfully characterized the system under relevant fed-batch like conditions in microscale cultivation (800 µL) and generated data proofing a relevant increase in specific yields for 6 different Escherichia coli derived MP-GFP fusion proteins by using online-GFP signals, FACS analysis, SDS-PAGE and western blotting.

CONCLUSIONS

In all cases tested, BL21-AI<gp2> outperformed the parental strain BL21-AI, operated in growth-associated production mode. Specific MP-GFP fusion proteins yields have been improved up to 2.7-fold. Therefore, this approach allows for fine tuning of MP production or expression of multi-enzyme pathways where e.g. particular stoichiometries have to be met to optimize product flux.

Monitoring and control of E. coli cell integrity

Soluble expression of recombinant proteins in E. coli is often done by translocation of the product across the inner membrane (IM) into the periplasm, where it is retained by the outer membrane (OM). While the integrity of the IM is strongly coupled to viability and impurity release, a decrease in OM integrity (corresponding to increased "leakiness") leads to accumulation of product in the extracellular space, strongly impacting the downstream process. Whether leakiness is desired or not, differential monitoring and control of IM and OM integrity are necessary for an efficient E. coli bioprocess in compliance with the guidelines of Quality by Design and Process Analytical Technology. In this review, we give an overview of relevant monitoring tools, summarize the research on factors affecting E. coli membrane integrity and provide a brief discussion on how the available monitoring technology can be implemented in real-time control of E. coli cultivations.

Automatic feed phase identification in multivariate bioprocess profiles by sequential binary classification

In this paper, we propose a new strategy for retrospective identification of feed phases from online sensor-data enriched feed profiles of an Escherichia Coli (E. coli) fed-batch fermentation process. In contrast to conventional (static), data-driven multi-class machine learning (ML), we exploit process knowledge in order to constrain our classification system yielding more parsimonious models compared to static ML approaches. In particular, we enforce unidirectionality on a set of binary, multivariate classifiers trained to discriminate between adjacent feed phases by linking the classifiers through a one-way switch. The switch is activated when the actual classifier output changes. As a consequence, the next binary classifier in the classifier chain is used for the discrimination between the next feed phase pair etc. We allow activation of the switch only after a predefined number of consecutive predictions of a transition event in order to prevent premature activation of the switch and undertake a sensitivity analysis regarding the optimal choice of the (time) lag parameter. From a complexity/parsimony perspective the benefit of our approach is three-fold: i) The multi-class learning task is broken down into binary subproblems which usually have simpler decision surfaces and tend to be less susceptible to the class-imbalance problem. ii) We exploit the fact that the process follows a rigid feed cycle structure (i.e. batch-feed-batch-feed) which allows us to focus on the subproblems involving phase transitions as they occur during the process while discarding off-transition classifiers and iii) only one binary classifier is active at the time which keeps effective model complexity low. We further use a combination of logistic regression and Lasso (i.e. regularized logistic regression, RLR) as a wrapper to extract the most relevant features for individual subproblems from the whole set of high-dimensional sensor data. We train different soft computing classifiers, including decision trees (DT), k-nearest neighbors (k-NN), support vector machines (SVM) and an own developed fuzzy classifier and compare our method with conventional multi-class ML. Our results show a remarkable out-performance of the here proposed method over static ML approaches in terms of accuracy and robustness. We achieved close to error free feed phase classification while reducing the misclassification rates in 17 out of 20 investigated test cases in the range between 39% and 98.2% depending on feature set and classifier architecture. Models trained on features based on selection by RLR significantly outperformed those trained on features suggested by experts and their predictive performance was considerably less affected by the choice of the lag parameter.

A novel method to recover inclusion body protein from recombinant E. coli fed-batch processes based on phage ΦX174-derived lysis protein E

Production of recombinant proteins as inclusion bodies is an important strategy in the production of technical enzymes and biopharmaceutical products. So far, protein from inclusion bodies has been recovered from the cell factory through mechanical or chemical disruption methods, requiring additional cost-intensive unit operations. We describe a novel method that is using a bacteriophage-derived lysis protein to directly recover inclusion body protein from Escherichia coli from high cell density fermentation process: The recombinant inclusion body product is expressed by using a mixed feed fed-batch process which allows expression tuning via adjusting the specific uptake rate of the inducing substrate. Then, bacteriophage ΦX174-derived lysis protein E is expressed to induce cell lysis. Inclusion bodies in empty cell envelopes are harvested via centrifugation of the fermentation broth. A subsequent solubilization step reveals the recombinant protein. The process was investigated by analyzing the impact of fermentation conditions on protein E-mediated cell lysis as well as cell lysis kinetics. Optimal cell lysis efficiencies of 99% were obtained with inclusion body titers of >2.0 g/l at specific growth rates higher 0.12 h^-1 and inducer uptake rates below 0.125 g/(g × h). Protein E-mediated cell disruption showed a first-order kinetics with a kinetic constant of -0.8 ± 0.3 h^-1. This alternative inclusion body protein isolation technique was compared to the one via high-pressure homogenization. SDS gel analysis showed 10% less protein impurities when cells had been disrupted via high-pressure homogenization, than when empty cell envelopes including inclusion bodies were investigated. Within this contribution, an innovative technology, tuning recombinant protein production and substituting cost-intensive mechanical cell disruption, is presented. We anticipate that the presented method will simplify and reduce the production costs of inclusion body processes to produce technical enzymes and biopharmaceutical products.

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.

Tunable recombinant protein expression in E. coli: promoter systems and genetic constraints

Tuning of transcription is a promising strategy to overcome challenges associated with a non-suitable expression rate like outgrowth of segregants, inclusion body formation, metabolic burden and inefficient translocation. By adjusting the expression rate-even on line-to purposeful levels higher product titres and more cost-efficient production processes can be achieved by enabling culture long-term stability and constant product quality. Some tunable systems are registered for patents or already commercially available. Within this contribution, we discuss the induction mechanisms of various Escherichia coli inherent promoter systems with respect to their tunability and review studies using these systems for expression tuning. According to the current level of knowledge, some promoter systems were successfully used for expression tuning, and in some cases, analytical evidence on single-cell level is still pending. However, only a few studies using tunable strains apply a suitable process control strategy. So far, expression tuning has only gathered little attention, but we anticipate that expression tuning harbours great potential for enabling and optimizing the production of a broad spectrum of products in E. coli.

A novel toolbox for E. coli lysis monitoring

The bacterium Escherichia coli is a well-studied recombinant host organism with a plethora of applications in biotechnology. Highly valuable biopharmaceuticals, such as antibody fragments and growth factors, are currently being produced in E. coli. However, the high metabolic burden during recombinant protein production can lead to cell death, consequent lysis, and undesired product loss. Thus, fast and precise analyzers to monitor E. coli bioprocesses and to retrieve key process information, such as the optimal time point of harvest, are needed. However, such reliable monitoring tools are still scarce to date. In this study, we cultivated an E. coli strain producing a recombinant single-chain antibody fragment in the cytoplasm. In bioreactor cultivations, we purposely triggered cell lysis by pH ramps. We developed a novel toolbox using UV chromatograms as fingerprints and chemometric techniques to monitor these lysis events and used flow cytometry (FCM) as reference method to quantify viability offline. Summarizing, we were able to show that a novel toolbox comprising HPLC chromatogram fingerprinting and data science tools allowed the identification of E. coli lysis in a fast and reliable manner. We are convinced that this toolbox will not only facilitate E. coli bioprocess monitoring but will also allow enhanced process control in the future.

Tunable recombinant protein expression in E. coli: enabler for continuous processing?

Tuning of transcription is a powerful process technological tool for efficient recombinant protein production in Escherichia coli. Many challenges such as product toxicity, formation of inclusion bodies, cell death, and metabolic burden are associated with non-suitable (too high or too low) levels of recombinant protein expression. Tunable expression systems allow adjusting the recombinant protein expression using process technological means. This enables to exploit the cell's metabolic capacities to a maximum. Within this article, we review genetic and process technological aspects of tunable expression systems in E. coli, providing a roadmap for the industrial exploitation of the reviewed technologies. We attempt to differentiate the term "expression tuning" from its inflationary use by providing a concise definition and highlight interesting fields of application for this versatile new technology. Dependent on the type of inducer (metabolizable or non-metabolizable), different process strategies are required in order to achieve tuning. To fully profit from the benefits of tunable systems, an independent control of growth rate and expression rate is indispensable. Being able to tackle problems such as long-term culture stability and constant product quality expression tuning is a promising enabler for continuous processing in biopharmaceutical production.