Robotic workflows for automated long-term adaptive laboratory evolution: improving ethanol utilization by Corynebacterium glutamicum.

BACKGROUND: Adaptive laboratory evolution (ALE) is known as a powerful tool for untargeted engineering of microbial strains and genomics research. It is particularly well suited for the adaptation of microorganisms to new environmental conditions, such as alternative substrate sources. Since the probability of generating beneficial mutations increases with the frequency of DNA replication, ALE experiments are ideally free of constraints on the required duration of cell proliferation. RESULTS: Here, we present an extended robotic workflow for performing long-term evolution experiments based on fully automated repetitive batch cultures (rbALE) in a well-controlled microbioreactor environment. Using a microtiter plate recycling approach, the number of batches and thus cell generations is technically unlimited. By applying the validated workflow in three parallel rbALE runs, ethanol utilization by Corynebacterium glutamicum ATCC 13032 (WT) was significantly improved. The evolved mutant strain WT_EtOH-Evo showed a specific ethanol uptake rate of 8.45 ± 0.12 mmolEtOH gCDW-1 h-1 and a growth rate of 0.15 ± 0.01 h-1 in lab-scale bioreactors. Genome sequencing of this strain revealed a striking single nucleotide variation (SNV) upstream of the ald gene (NCgl2698, cg3096) encoding acetaldehyde dehydrogenase (ALDH). The mutated basepair was previously predicted to be part of the binding site for the global transcriptional regulator GlxR, and re-engineering demonstrated that the identified SNV is key for enhanced ethanol assimilation. Decreased binding of GlxR leads to increased synthesis of the rate-limiting enzyme ALDH, which was confirmed by proteomics measurements. CONCLUSIONS: The established rbALE technology is generally applicable to any microbial strain and selection pressure that fits the small-scale cultivation format. In addition, our specific results will enable improved production processes with C. glutamicum from ethanol, which is of particular interest for acetyl-CoA-derived products.

Robotic integration enables autonomous operation of laboratory scale stirred tank bioreactors with model-driven process analysis.

Given its geometric similarity to large-scale production plants and the excellent possibilities for precise process control and monitoring, the classic stirred tank bioreactor (STR) still represents the gold standard for bioprocess development at a laboratory scale. However, compared to microbioreactor technologies, bioreactors often suffer from a low degree of process automation and deriving key performance indicators (KPIs) such as specific rates or yields often requires manual sampling and sample processing. A widely used parallelized STR setup was automated by connecting it to a liquid handling system and controlling it with a custom-made process control system. This allowed for the setup of a flexible modular platform enabling autonomous operation of the bioreactors without any operator present. Multiple unit operations like automated inoculation, sampling, sample processing and analysis, and decision making, for example for automated induction of protein production were implemented to achieve such functionality. The data gained during application studies was used for fitting of bioprocess models to derive relevant KPIs being in good agreement with literature. By combining the capabilities of STRs with the flexibility of liquid handling systems, this platform technology can be applied to a multitude of different bioprocess development pipelines at laboratory scale.

A FRET-based biosensor for the quantification of glucose in culture supernatants of mL scale microbial cultivations.

BACKGROUND: In most microbial cultivations D-glucose is the main carbon and energy source. However, quantification of D-glucose especially in small scale is still challenging. Therefore, we developed a FRET-based glucose biosensor, which can be applied in microbioreactor-based cultivations. This sensor consists of a glucose binding protein sandwiched between two fluorescent proteins, constituting a FRET pair. Upon D-glucose binding the sensor undergoes a conformational change which is translated into a FRET-ratio change. RESULTS: The selected sensor shows an apparent Kd below 1.5 mM D-glucose and a very high sensitivity of up to 70% FRET-ratio change between the unbound and the glucose-saturated state. The soluble sensor was successfully applied online to monitor the glucose concentration in an Escherichia coli culture. Additionally, this sensor was utilized in an at-line process for a Corynebacterium glutamicum culture as an example for a process with cell-specific background (e.g. autofluorescence) and medium-induced quenching. Immobilization of the sensor via HaloTag® enabled purification and covalent immobilization in one step and increased the stability during application, significantly. CONCLUSION: A FRET-based glucose sensor was used to quantify D-glucose consumption in microtiter plate based cultivations. To the best of our knowledge, this is the first method reported for online quantification of D-glucose in microtiter plate based cultivations. In comparison to D-glucose analysis via an enzymatic assay and HPLC, the sensor performed equally well, but enabled much faster measurements, which allowed to speed up microbial strain development significantly.

FeedER: a feedback-regulated enzyme-based slow-release system for fed-batch cultivation in microtiter plates.

With the advent of modern genetic engineering methods, microcultivation systems have become increasingly important tools for accelerated strain phenotyping and bioprocess engineering. While these systems offer sophisticated capabilities to screen batch processes, they lack the ability to realize fed-batch processes, which are used more frequently in industrial bioprocessing. In this study, a novel approach to realize a feedback-regulated enzyme-based slow-release system (FeedER), allowing exponential fed-batch for microscale cultivations, was realized by extending our existing Mini Pilot Plant technology with a customized process control system. By continuously comparing the experimental growth rates with predefined set points, the automated dosage of Amyloglucosidase enzyme for the cleavage of dextrin polymers into D-glucose monomers is triggered. As a prerequisite for stable fed-batch operation, a constant pH is maintained by automated addition of ammonium hydroxide. We show the successful application of FeedER to study fed-batch growth of different industrial model organisms including Corynebacterium glutamicum, Pichia pastoris, and Escherichia coli. Moreover, the comparative analysis of a C. glutamicum GFP producer strain, cultivated under microscale batch and fed-batch conditions, revealed two times higher product yields under slow growing fed-batch operation. In summary, FeedER enables to run 48 parallel fed-batch experiments in an automated and miniaturized manner, and thereby accelerates industrial bioprocess development at the screening stage.

Growth-rate dependency of ribosome abundance and translation elongation rate in Corynebacterium glutamicum differs from that in Escherichia coli.

Bacterial growth rate (µ) depends on the protein synthesis capacity of the cell and thus on the number of active ribosomes and their translation elongation rate. The relationship between these fundamental growth parameters have only been described for few bacterial species, in particular Escherichia coli. Here, we analyse the growth-rate dependency of ribosome abundance and translation elongation rate for Corynebacterium glutamicum, a gram-positive model species differing from E. coli by a lower growth temperature optimum and a lower maximal growth rate. We show that, unlike in E. coli, there is little change in ribosome abundance for µ <0.4 h-1 in C. glutamicum and the fraction of active ribosomes is kept above 70% while the translation elongation rate declines 5-fold. Mathematical modelling indicates that the decrease in the translation elongation rate can be explained by a depletion of translation precursors.

bletl - A Python package for integrating BioLector microcultivation devices in the Design-Build-Test-Learn cycle.

Microbioreactor (MBR) devices have emerged as powerful cultivation tools for tasks of microbial phenotyping and bioprocess characterization and provide a wealth of online process data in a highly parallelized manner. Such datasets are difficult to interpret in short time by manual workflows. In this study, we present the Python package bletl and show how it enables robust data analyses and the application of machine learning techniques without tedious data parsing and preprocessing. bletl reads raw result files from BioLector I, II and Pro devices to make all the contained information available to Python-based data analysis workflows. Together with standard tooling from the Python scientific computing ecosystem, interactive visualizations and spline-based derivative calculations can be performed. Additionally, we present a new method for unbiased quantification of time-variable specific growth rate µ ⃗ t based on unsupervised switchpoint detection with Student-t distributed random walks. With an adequate calibration model, this method enables practitioners to quantify time-variable growth rate with Bayesian uncertainty quantification and automatically detect switch-points that indicate relevant metabolic changes. Finally, we show how time series feature extraction enables the application of machine learning methods to MBR data, resulting in unsupervised phenotype characterization. As an example, Neighbor Embedding (t-SNE) is performed to visualize datasets comprising a variety of growth/DO/pH phenotypes.

pyFOOMB: Python framework for object oriented modeling of bioprocesses.

Quantitative characterization of biotechnological production processes requires the determination of different key performance indicators (KPIs) such as titer, rate and yield. Classically, these KPIs can be derived by combining black-box bioprocess modeling with non-linear regression for model parameter estimation. The presented pyFOOMB package enables a guided and flexible implementation of bioprocess models in the form of ordinary differential equation systems (ODEs). By building on Python as powerful and multi-purpose programing language, ODEs can be formulated in an object-oriented manner, which facilitates their modular design, reusability, and extensibility. Once the model is implemented, seamless integration and analysis of the experimental data is supported by various Python packages that are already available. In particular, for the iterative workflow of experimental data generation and subsequent model parameter estimation we employed the concept of replicate model instances, which are linked by common sets of parameters with global or local properties. For the description of multi-stage processes, discontinuities in the right-hand sides of the differential equations are supported via event handling using the freely available assimulo package. Optimization problems can be solved by making use of a parallelized version of the generalized island approach provided by the pygmo package. Furthermore, pyFOOMB in combination with Jupyter notebooks also supports education in bioprocess engineering and the applied learning of Python as scientific programing language. Finally, the applicability and strengths of pyFOOMB will be demonstrated by a comprehensive collection of notebook examples.

Automated Rational Strain Construction Based on High-Throughput Conjugation.

Molecular cloning is the core of synthetic biology, as it comprises the assembly of DNA and its expression in target hosts. At present, however, cloning is most often a manual, time-consuming, and repetitive process that highly benefits from automation. The automation of a complete rational cloning procedure, i.e., from DNA creation to expression in the target host, involves the integration of different operations and machines. Examples of such workflows are sparse, especially when the design is rational (i.e., the DNA sequence design is fixed and not based on randomized libraries) and the target host is less genetically tractable (e.g., not sensitive to heat-shock transformation). In this study, an automated workflow for the rational construction of plasmids and their subsequent conjugative transfer into the biotechnological platform organism Corynebacterium glutamicum is presented. The whole workflow is accompanied by a custom-made software tool. As an application example, a rationally designed library of transcription factor-biosensors based on the regulator Lrp was constructed and characterized. A sensor with an improved dynamic range was obtained, and insights from the screening provided evidence for a dual regulator function of C. glutamicum Lrp.

Microaerobic growth-decoupled production of α-ketoglutarate and succinate from xylose in a one-pot process using Corynebacterium glutamicum.

BACKGROUND: Lignocellulosic biomass is the most abundant raw material on earth. Its efficient use for novel bio-based materials is essential for an emerging bioeconomy. Possible building blocks for such materials are the key TCA-cycle intermediates α-ketoglutarate and succinate. These organic acids have a wide range of potential applications, particularly in use as monomers for established or novel biopolymers. Recently, Corynebacterium glutamicum was successfully engineered and evolved towards an improved utilization of d-xylose via the Weimberg pathway, yielding the strain WMB2evo . The Weimberg pathway enables a carbon-efficient C5-to-C5 conversion of d-xylose to α-ketoglutarate and a shortcut route to succinate as co-product in a one-pot process. METHODS AND RESULTS: C. glutamicum WMB2evo was grown under dynamic microaerobic conditions on d-xylose, leading to the formation of comparably high amounts of succinate and only small amounts of α-ketoglutarate. Subsequent carbon isotope labeling experiments verified the targeted production route for both products in C. glutamicum WMB2evo . Fed-batch process development was initiated and the effect of oxygen supply and feeding strategy for a growth-decoupled co-production of α-ketoglutarate and succinate were studied in detail. The finally established fed-batch production process resulted in the formation of 78.4 mmol L-1 (11.45 g L-1 ) α-ketoglutarate and 96.2 mmol L-1 (11.36 g L-1 ) succinate. CONCLUSION: The developed one-pot process represents a promising approach for the combined supply of bio-based α-ketoglutarate and succinate. Future work will focus on tailor-made down-stream processing of both organic acids from the fermentation broth to enable their application as building blocks in chemical syntheses. Alternatively, direct conversion of one or both acids via whole-cell or cell-free enzymatic approaches can be envisioned; thus, extending the network of value chains starting from cheap and renewable d-xylose.

(Optochemical) Control of Synthetic Microbial Coculture Interactions on a Microcolony Level.

Synthetic microbial cocultures carry enormous potential for applied biotechnology and are increasingly the subject of fundamental research. So far, most cocultures have been designed and characterized based on bulk cultivations without considering the potentially highly heterogeneous and diverse single-cell behavior. However, an in-depth understanding of cocultures including their interacting single cells is indispensable for the development of novel cultivation approaches and control of cocultures. We present the development, validation, and experimental characterization of an optochemically controllable bacterial coculture on a microcolony level consisting of two Corynebacterium glutamicum strains. Our coculture combines an l-lysine auxotrophic strain together with a l-lysine-producing variant carrying the genetically IPTG-mediated induction of l-lysine production. We implemented two control approaches utilizing IPTG as inducer molecule. First, unmodified IPTG was supplemented to the culture enabling a medium-based control of the production of l-lysine, which serves as the main interacting component. Second, optochemical control was successfully performed by utilizing photocaged IPTG activated by appropriate illumination. Both control strategies were validated studying cellular growth on a microcolony level. The novel microfluidic single-cell cultivation strategies applied in this work can serve as a blueprint to validate cellular control strategies of synthetic mono- and cocultures with single-cell resolution at defined environmental conditions.

Less Sacrifice, More Insight: Repeated Low-Volume Sampling of Microbioreactor Cultivations Enables Accelerated Deep Phenotyping of Microbial Strain Libraries.

With modern genetic engineering tools, high number of potentially improved production strains can be created in a short time. This results in a bottleneck in the succeeding step of bioprocess development, which can be handled by accelerating quantitative microbial phenotyping. Miniaturization and automation are key technologies to achieve this goal. In this study, a novel workflow for repeated low-volume sampling of BioLector-based cultivation setups is presented. Six samples of 20 µL each can be taken automatically from shaken 48-well microtiter plates without disturbing cell population growth. The volume is sufficient for quantification of substrate and product concentrations by spectrophotometric-based enzyme assays. From transient concentration data and replicate cultures, valid performance indicators (titers, rates, yields) are determined through process modeling and random error propagation analysis. Practical relevance of the workflow is demonstrated with a set of five genome-reduced Corynebacterium glutamicum strains that are engineered for Sec-mediated heterologous cutinase secretion. Quantitative phenotyping of this strain library led to the identification of a strain with a 1.6-fold increase in cutinase yield. The prophage-free strain carries combinatorial deletions of three gene clusters (Δ3102-3111, Δ3263-3301, and Δ3324-3345) of which the last two likely contain novel target genes to foster rational engineering of heterologous cutinase secretion in C. glutamicum.

The myo-inositol/proton symporter IolT1 contributes to d-xylose uptake in Corynebacterium glutamicum.

Corynebacterium glutamicum has been engineered to utilize d-xylose as sole carbon and energy source. Recently, a C. glutamicum strain has been optimized for growth on defined medium containing d-xylose by laboratory evolution, but the mutation(s) attributing to the improved-growth phenotype could not be reliably identified. This study shows that loss of the transcriptional repressor IolR is responsible for the increased growth performance on defined d-xylose medium in one of the isolated mutants. Underlying reason is derepression of the gene for the glucose/myo-inositol permease IolT1 in the absence of IolR, which could be shown to also contribute to d-xylose uptake in C. glutamicum. IolR-regulation of iolT1 could be successfully repealed by rational engineering of an IolR-binding site in the iolT1-promoter. This minimally engineered C. glutamicum strain bearing only two nucleotide substitutions mimics the IolR loss-of-function phenotype and allows for a high growth rate on d-xylose-containing media (µmax = 0.24 ±â€¯0.01 h-1).

Production of d-xylonic acid using a non-recombinant Corynebacterium glutamicum strain.

It was found that Corynebacterium glutamicum ΔiolR devoid of the transcriptional regulator IolR accumulates high amounts of d-xylonate when cultivated in the presence of d-xylose. Detailed analyses of constructed deletion mutants revealed that the putative myo-inositol 2-dehydrogenase IolG also acts as d-xylose dehydrogenase and is mainly responsible for d-xylonate oxidation in this organism. Process development for d-xylonate production was initiated by cultivating C. glutamicum ΔiolR on defined d-xylose/d-glucose mixtures under batch and fed-batch conditions. The resulting yield matched the theoretical maximum of 1 mol mol-1 and high volumetric productivities of up to 4 g L-1 h-1 could be achieved. Subsequently, a novel one-pot sequential hydrolysis and fermentation process based on optimized medium containing hydrolyzed sugarcane bagasse was developed. Cost-efficiency and abundance of second-generation substrates, good performance indicators, and enhanced market access using a non-recombinant strain open the perspective for a commercially viable bioprocess for d-xylonate production in the near future.

A microfluidic co-cultivation platform to investigate microbial interactions at defined microenvironments.

Interspecies interactions inside microbial communities bear a tremendous diversity of complex chemical processes that are by far not understood. Even for simplified, often synthetic systems, the interactions between two microbes are barely revealed in detail. Here, we present a microfluidic co-cultivation platform for the analysis of growth and interactions inside microbial consortia with single-cell resolution. Our device allows the spatial separation of two different microbial organisms inside adjacent microchambers facilitating sufficient exchange of metabolites via connecting nanochannels. Inside the cultivation chambers cell growth can be observed with high spatio-temporal resolution by live-cell imaging. In contrast to conventional approaches, in which single-cell activity is typically fully masked by the average bulk behavior, the small dimensions of the microfluidic cultivation chambers enable accurate environmental control and observation of cellular interactions with full spatio-temporal resolution. Our method enables one to study phenomena in microbial interactions, such as gene transfer or metabolic cross-feeding. We chose two different microbial model systems to demonstrate the wide applicability of the technology. First, we investigated commensalistic interactions between an industrially relevant l-lysine-producing Corynebacterium glutamicum strain and an l-lysine auxotrophic variant of the same species. Spatially separated co-cultivation of both strains resulted in growth of the auxotrophic strain due to secreted l-lysine supplied by the producer strain. As a second example we investigated bacterial conjugation between Escherichia coli S17-1 and Pseudomonas putida KT2440 cells. We could show that direct cell contact is essential for the successful gene transfer via conjugation and was hindered when cells were spatially separated. The presented device lays the foundation for further studies on contactless and contact-based interactions of natural and synthetic microbial communities.

Corynebacterium glutamicum Chassis C1*: Building and Testing a Novel Platform Host for Synthetic Biology and Industrial Biotechnology.

Targeted top-down strategies for genome reduction are considered to have a high potential for providing robust basic strains for synthetic biology and industrial biotechnology. Recently, we created a library of 26 genome-reduced strains of Corynebacterium glutamicum carrying broad deletions in single gene clusters and showing wild-type-like biological fitness. Here, we proceeded with combinatorial deletions of these irrelevant gene clusters in two parallel orders, and the resulting library of 28 strains was characterized under various environmental conditions. The final chassis strain C1* carries a genome reduction of 13.4% (412 deleted genes) and shows wild-type-like growth behavior in defined medium with d-glucose as carbon and energy source. Moreover, C1* proves to be robust against several stresses (including oxygen limitation) and shows long-term growth stability under defined and complex medium conditions. In addition to providing a novel prokaryotic chassis strain, our results comprise a large strain library and a revised genome annotation list, which will be valuable sources for future systemic studies of C. glutamicum.

Miniaturized and automated adaptive laboratory evolution: Evolving Corynebacterium glutamicum towards an improved d-xylose utilization.

Adaptive Laboratory Evolution (ALE) is increasingly being used as a technique for untargeted strain optimization. This work aimed at developing an automated and miniaturized ALE approach based on repetitive batch cultivations in microtiter plates. The new method is applied to the recently published strain Corynebacterium glutamicum pEKEx3-xylXABCDCc, which is capable of utilizing d-xylose via the Weimberg (WMB) pathway. As a result, the significantly improved strain WMB2evo was obtained, showing a specific growth rate of 0.26h-1 on d-xylose as sole carbon and energy source. WMB2evo grows stable during lab-scale bioreactor operation, demonstrating the high potential of this strain for future biorefinery applications. Genome sequencing of cell samples from two different ALE processes revealed potential key mutations, e.g. in the gene cg0196 (encoding for the transcriptional regulator IolR of the myo-inositol metabolism). These findings open up new perspectives for the rational engineering of C. glutamicum towards improved d-xylose utilization.

Production of Functional Anti-Ebola Antibodies in Pichia pastoris.

The 2013-2016 Ebola outbreak highlighted the limited treatment options and lack of rapid response strategies for emerging pathogen outbreaks. Here, we propose an efficient development cycle using glycoengineered Pichia pastoris to produce monoclonal antibody cocktails against pathogens. To enable rapid genetic engineering of P. pastoris, we introduced a genomic landing pad for reliable recombinase-mediated DNA integration. We then created strains expressing each of the three monoclonal antibodies that comprise the ZMapp cocktail, and demonstrated that the secreted antibodies bind to the Ebola virus glycoprotein by immunofluorescence assay. We anticipate that this approach could accelerate the production of therapeutics against future pathogen outbreaks.

SNAP-tag based agents for preclinical in vitro imaging in malignant diseases.

Although current cancer treatment strategies are highly aggressive, they are often not effective enough to destroy the collectivity of malignant cells. The residual tumor cells that survived the first-line treatment may continue to proliferate or even metastasize. Therefore, the development of novel more effective strategies to specifically eliminate also single cancer cells is urgently needed. In this respect, the development of antibody-based therapeutics, in particular example immunotoxins, has attracted broad interest. Since the internalization of immunotoxins is essential for their cytotoxic effectivity, it is of crucial importance to study their internalization behavior to assess the potential for their therapeutic use. In this study, we determined the internalization behavior of four different single-chain fragments variable (scFv) when binding to the corresponding target antigen as expressed on solid or non-solid tumor cell lines. The scFvs were recombinantly fused to the SNAP-tag, an engineered variant of the human repair enzyme O(6)-alkylguanine-DNA alkyltransferase that covalently reacts with benzylguanine derivatives. Since a large number of highly sensitive organic fluorescent dyes are already available or can easily be derivatized to react with the self-labeling SNAP-tag, this system provides versatile applications for imaging of intraand extracellular compartments of living cells. The fusion proteins were coupled to SNAP-surface(®) Alexa Fluor(®) 488 or SNAP-surface(®) Alexa Fluor(®) 647 and binding as well as internalization was monitored by flow cytometry and confocal microscopy, respectively. Depending on the respective target antigen, we could distinguish between slow and rapid internalization behavior. Moreover, we detected increased internalization rate for bivalent scFv constructs. Our approach allows for rapid and early stage evaluation of the internalization characteristics of new antibodies designated for further therapeutic development.