"High-throughput screening of catalytically active inclusion bodies using laboratory automation and Bayesian optimization".

BACKGROUND: In recent years, the production of inclusion bodies that retain substantial catalytic activity was demonstrated. These catalytically active inclusion bodies (CatIBs) are formed by genetic fusion of an aggregation-inducing tag to a gene of interest via short linker polypeptides. The resulting CatIBs are known for their easy and cost-efficient production, recyclability as well as their improved stability. Recent studies have outlined the cooperative effects of linker and aggregation-inducing tag on CatIB activities. However, no a priori prediction is possible so far to indicate the best combination thereof. Consequently, extensive screening is required to find the best performing CatIB variant. RESULTS: In this work, a semi-automated cloning workflow was implemented and used for fast generation of 63 CatIB variants with glucose dehydrogenase of Bacillus subtilis (BsGDH). Furthermore, the variant BsGDH-PT-CBDCell was used to develop, optimize and validate an automated CatIB screening workflow, enhancing the analysis of many CatIB candidates in parallel. Compared to previous studies with CatIBs, important optimization steps include the exclusion of plate position effects in the BioLector by changing the cultivation temperature. For the overall workflow including strain construction, the manual workload could be reduced from 59 to 7 h for 48 variants (88%). After demonstration of high reproducibility with 1.9% relative standard deviation across 42 biological replicates, the workflow was performed in combination with a Bayesian process model and Thompson sampling. While the process model is crucial to derive key performance indicators of CatIBs, Thompson sampling serves as a strategy to balance exploitation and exploration in screening procedures. Our methodology allowed analysis of 63 BsGDH-CatIB variants within only three batch experiments. Because of the high likelihood of TDoT-PT-BsGDH being the best CatIB performer, it was selected in 50 biological replicates during the three screening rounds, much more than other, low-performing variants. CONCLUSIONS: At the current state of knowledge, every new enzyme requires screening for different linker/aggregation-inducing tag combinations. For this purpose, the presented CatIB toolbox facilitates fast and simplified construction and screening procedures. The methodology thus assists in finding the best CatIB producer from large libraries in short time, rendering possible automated Design-Build-Test-Learn cycles to generate structure/function learnings.

Automated workflow for characterization of bacteriocin production in natural producers Lactococcus lactis and Latilactobacillus sakei.

BACKGROUND: Lactic acid bacteria are commonly used as protective starter cultures in food products. Among their beneficial effects is the production of ribosomally synthesized peptides termed bacteriocins that kill or inhibit food-spoiling bacteria and pathogens, e.g., members of the Listeria species. As new bacteriocins and producer strains are being discovered rapidly, modern automated methods for strain evaluation and bioprocess development are required to accelerate screening and development processes. RESULTS: In this study, we developed an automated workflow for screening and bioprocess optimization for bacteriocin producing lactic acid bacteria, consisting of microcultivation, sample processing and automated antimicrobial activity assay. We implemented sample processing workflows to minimize bacteriocin adsorption to producer cells via addition of Tween 80 and divalent cations to the cultivation media as well as acidification of culture broth prior to cell separation. Moreover, we demonstrated the applicability of the automated workflow to analyze influence of media components such as MES buffer or yeast extract for bacteriocin producers Lactococcus lactis B1629 and Latilactobacillus sakei A1608. CONCLUSIONS: Our automated workflow provides advanced possibilities to accelerate screening and bioprocess optimization for natural bacteriocin producers. Based on its modular concept, adaptations for other strains, bacteriocin products and applications are easily carried out and a unique tool to support bacteriocin research and bioprocess development is provided.

Optimizing microbioreactor cultivation strategies for Trichoderma reesei: from batch to fed-batch operations.

BACKGROUND: Filamentous fungi have long been recognized for their exceptional enzyme production capabilities. Among these, Trichoderma reesei has emerged as a key producer of various industrially relevant enzymes and is particularly known for the production of cellulases. Despite the availability of advanced gene editing techniques for T. reesei, the cultivation and characterization of resulting strain libraries remain challenging, necessitating well-defined and controlled conditions with higher throughput. Small-scale cultivation devices are popular for screening bacterial strain libraries. However, their current use for filamentous fungi is limited due to their complex morphology. RESULTS: This study addresses this research gap through the development of a batch cultivation protocol using a microbioreactor for cellulase-producing T. reesei strains (wild type, RutC30 and RutC30 TR3158) with offline cellulase activity analysis. Additionally, the feasibility of a microscale fed-batch cultivation workflow is explored, crucial for mimicking industrial cellulase production conditions. A batch cultivation protocol was developed and validated using the BioLector microbioreactor, a Round Well Plate, adapted medium and a shaking frequency of 1000 rpm. A strong correlation between scattered light intensity and cell dry weight underscores the reliability of this method in reflecting fungal biomass formation, even in the context of complex fungal morphology. Building on the batch results, a fed-batch strategy was established for T. reesei RutC30. Starting with a glucose concentration of 2.5 g l - 1 in the batch phase, we introduced a dual-purpose lactose feed to induce cellulase production and prevent carbon catabolite repression. Investigating lactose feeding rates from 0.3 to 0.75 g (l h) - 1 , the lowest rate of 0.3 g (l h) - 1 revealed a threefold increase in cellobiohydrolase and a fivefold increase in ß -glucosidase activity compared to batch processes using the same type and amount of carbon sources. CONCLUSION: We successfully established a robust microbioreactor batch cultivation protocol for T. reesei wild type, RutC30 and RutC30 TR3158, overcoming challenges associated with complex fungal morphologies. The study highlights the effectiveness of microbioreactor workflows in optimizing cellulase production with T. reesei, providing a valuable tool for simultaneous assessment of critical bioprocess parameters and facilitating efficient strain screening. The findings underscore the potential of microscale fed-batch strategies for enhancing enzyme production capabilities, revealing insights for future industrial applications in biotechnology.

Engineered coumarin accumulation reduces mycotoxin-induced oxidative stress and disease susceptibility.

Coumarins can fight pathogens and are thus promising for crop protection. Their biosynthesis, however, has not yet been engineered in crops. We tailored the constitutive accumulation of coumarins in transgenic Nicotiana benthamiana, Glycine max and Arabidopsis thaliana plants, as well as in Nicotiana tabacum BY-2 suspension cells. We did so by overexpressing A. thaliana feruloyl-CoA 6-hydroxylase 1 (AtF6'H1), encoding the key enzyme of scopoletin biosynthesis. Besides scopoletin and its glucoside scopolin, esculin at low level was the only other coumarin detected in transgenic cells. Mechanical damage of scopolin-accumulating tissue led to a swift release of scopoletin, presumably from the scopolin pool. High scopolin levels in A. thaliana roots coincided with reduced susceptibility to the root-parasitic nematode Heterodera schachtii. In addition, transgenic soybean plants were more tolerant to the soil-borne pathogenic fungus Fusarium virguliforme. Because mycotoxin-induced accumulation of reactive oxygen species and cell death were reduced in the AtF6'H1-overexpressors, the weaker sensitivity to F. virguliforme may be caused by attenuated oxidative damage of coumarin-hyperaccumulating cells. Together, engineered coumarin accumulation is promising for enhanced disease resilience of crops.

Explore or exploit? A model-based screening strategy for PETase secretion by Corynebacterium glutamicum.

Extracellular production of target proteins simplifies downstream processing due to obsolete cell disruption. However, optimal combinations of a heterologous protein, suitable signal peptide, and secretion host can currently not be predicted, resulting in large strain libraries that need to be tested. On the experimental side, this challenge can be tackled by miniaturization, parallelization, and automation, which provide high-throughput screening data. These data need to be condensed into a candidate ranking for decision-making to focus bioprocess development on the most promising candidates. We screened for Bacillus subtilis signal peptides mediating Sec secretion of two polyethylene terephthalate degrading enzymes (PETases), leaf-branch compost cutinase (LCC) and polyester hydrolase mutants, by Corynebacterium glutamicum. We developed a fully automated screening process and constructed an accompanying Bayesian statistical modeling framework, which we applied in screenings for highest activity in 4-nitrophenyl palmitate degradation. In contrast to classical evaluation methods, batch effects and biological errors are taken into account and their uncertainty is quantified. Within only two rounds of screening, the most suitable signal peptide was identified for each PETase. Results from LCC secretion in microliter-scale cultivation were shown to be scalable to laboratory-scale bioreactors. This work demonstrates an experiment-modeling loop that can accelerate early-stage screening in a way that experimental capacities are focused to the most promising strain candidates. Combined with high-throughput cloning, this paves the way for using large strain libraries of several hundreds of strains in a Design-Build-Test-Learn approach.

Bayesian calibration, process modeling and uncertainty quantification in biotechnology.

High-throughput experimentation has revolutionized data-driven experimental sciences and opened the door to the application of machine learning techniques. Nevertheless, the quality of any data analysis strongly depends on the quality of the data and specifically the degree to which random effects in the experimental data-generating process are quantified and accounted for. Accordingly calibration, i.e. the quantitative association between observed quantities and measurement responses, is a core element of many workflows in experimental sciences. Particularly in life sciences, univariate calibration, often involving non-linear saturation effects, must be performed to extract quantitative information from measured data. At the same time, the estimation of uncertainty is inseparably connected to quantitative experimentation. Adequate calibration models that describe not only the input/output relationship in a measurement system but also its inherent measurement noise are required. Due to its mathematical nature, statistically robust calibration modeling remains a challenge for many practitioners, at the same time being extremely beneficial for machine learning applications. In this work, we present a bottom-up conceptual and computational approach that solves many problems of understanding and implementing non-linear, empirical calibration modeling for quantification of analytes and process modeling. The methodology is first applied to the optical measurement of biomass concentrations in a high-throughput cultivation system, then to the quantification of glucose by an automated enzymatic assay. We implemented the conceptual framework in two Python packages, calibr8 and murefi, with which we demonstrate how to make uncertainty quantification for various calibration tasks more accessible. Our software packages enable more reproducible and automatable data analysis routines compared to commonly observed workflows in life sciences. Subsequently, we combine the previously established calibration models with a hierarchical Monod-like ordinary differential equation model of microbial growth to describe multiple replicates of Corynebacterium glutamicum batch cultures. Key process model parameters are learned by both maximum likelihood estimation and Bayesian inference, highlighting the flexibility of the statistical and computational framework.

From frozen cell bank to product assay: high-throughput strain characterisation for autonomous Design-Build-Test-Learn cycles.

BACKGROUND: Modern genome editing enables rapid construction of genetic variants, which are further developed in Design-Build-Test-Learn cycles. To operate such cycles in high throughput, fully automated screening, including cultivation and analytics, is crucial in the Test phase. Here, we present the required steps to meet these demands, resulting in an automated microbioreactor platform that facilitates autonomous phenotyping from cryo culture to product assay. RESULTS: First, an automated deep freezer was integrated into the robotic platform to provide working cell banks at all times. A mobile cart allows flexible docking of the freezer to multiple platforms. Next, precultures were integrated within the microtiter plate for cultivation, resulting in highly reproducible main cultures as demonstrated for Corynebacterium glutamicum. To avoid manual exchange of microtiter plates after cultivation, two clean-in-place strategies were established and validated, resulting in restored sterile conditions within two hours. Combined with the previous steps, these changes enable a flexible start of experiments and greatly increase the walk-away time. CONCLUSIONS: Overall, this work demonstrates the capability of our microbioreactor platform to perform autonomous, consecutive cultivation and phenotyping experiments. As highlighted in a case study of cutinase-secreting strains of C. glutamicum, the new procedure allows for flexible experimentation without human interaction while maintaining high reproducibility in early-stage screening processes.

Analysis of protein secretion in Bacillus subtilis by combining a secretion stress biosensor strain with an in vivo split GFP assay.

BACKGROUND: Bacillus subtilis is one of the workhorses in industrial biotechnology and well known for its secretion potential. Efficient secretion of recombinant proteins still requires extensive optimization campaigns and screening with activity-based methods. However, not every protein can be detected by activity-based screening. We therefore developed a combined online monitoring system, consisting of an in vivo split GFP assay for activity-independent target detection and an mCherry-based secretion stress biosensor. The split GFP assay is based on the fusion of a target protein to the eleventh ß-sheet of sfGFP, which can complement a truncated sfGFP that lacks this ß-sheet named GFP1-10. The secretion stress biosensor makes use of the CssRS two component quality control system, which upregulates expression of mCherry in the htrA locus thereby allowing a fluorescence readout of secretion stress. RESULTS: The biosensor strain B. subtilis PAL5 was successfully constructed by exchanging the protease encoding gene htrA with mCherry via CRISPR/Cas9. The Fusarium solani pisi cutinase Cut fused to the GFP11 tag (Cut11) was used as a model enzyme to determine the stress response upon secretion mediated by signal peptides SPPel, SPEpr and SPBsn obtained from naturally secreted proteins of B. subtilis. An in vivo split GFP assay was developed, where purified GFP1-10 is added to the culture broth. By combining both methods, an activity-independent high-throughput method was created, that allowed optimization of Cut11 secretion. Using the split GFP-based detection assay, we demonstrated a good correlation between the amount of secreted cutinase and the enzymatic activity. Additionally, we screened a signal peptide library and identified new signal peptide variants that led to improved secretion while maintaining low stress levels. CONCLUSION: Our results demonstrate that the combination of a split GFP-based detection assay for secreted proteins with a secretion stress biosensor strain enables both, online detection of extracellular target proteins and identification of bottlenecks during protein secretion in B. subtilis. In general, the system described here will also enable to monitor the secretion stress response provoked by using inducible promoters governing the expression of different enzymes.

Microfluidic single-cell scale-down bioreactors: A proof-of-concept for the growth of Corynebacterium glutamicum at oscillating pH values.

In large-scale bioreactors, gradients in cultivation parameters such as oxygen, substrate, and pH result in fluctuating cell environments. pH fluctuations were identified as a critical parameter for bioprocess performance. Traditionally, scale-down systems at the laboratory scale are used to analyze the effects of fluctuating pH values on strains and thus process performance. Here, we demonstrate the application of dynamic microfluidic single-cell cultivation (dMSCC) as a novel scale-down system for the characterization of Corynebacterium glutamicum growth using oscillating pH conditions as a model stress factor. A detailed comparison between two-compartment reactor (two-CR) scale-down experiments and dMSCC was performed for one specific pH oscillation between reference pH 7 (~8 min) and disturbed pH 6 (~2 min). Similar reductions in growth rates were observed in both systems (dMSCC 21% and two-CR 27%) compared to undisturbed cultivation at pH 7. Afterward, systematic experiments at symmetric and asymmetric pH oscillations, between pH ranges of 4-6 and 8-11 and different intervals from 1 to 20 min, were performed to demonstrate the unique application range and throughput of the dMSCC system. Finally, the strength of the dMSCC application was demonstrated by mimicking fluctuating environmental conditions of a putative large-scale bioprocess, which is difficult to conduct using two-CRs.

Construction and characterization of BsGDH-CatIB variants and application as robust and highly active redox cofactor regeneration module for biocatalysis.

BACKGROUND: Catalytically active inclusion bodies (CatIBs) are known for their easy and cost efficient production, recyclability as well as high stability and provide an alternative purely biological technology for enzyme immobilization. Due to their ability to self-aggregate in a carrier-free, biodegradable form, no further laborious immobilization steps or additional reagents are needed. These advantages put CatIBs in a beneficial position in comparison to traditional immobilization techniques. Recent studies outlined the impact of cooperative effects of the linker and aggregation inducing tag on the activity level of CatIBs, requiring to test many combinations to find the best performing CatIB variant. RESULTS: Here, we present the formation of 14 glucose dehydrogenase CatIB variants of Bacillus subtilis, a well-known enzyme in biocatalysis due to its capability for substrate coupled regeneration of reduced cofactors with cheap substrate glucose. Nine variants revealed activity, with highest productivity levels for the more rigid PT-Linker combinations. The best performing CatIB, BsGDH-PT-CBDCell, was characterized in more detail including long-term storage at -20 °C as well as NADH cofactor regeneration performance in repetitive batch experiments with CatIB recycling. After freezing, BsGDH-PT-CBDCell CatIB only lost approx. 10% activity after 8 weeks of storage. Moreover, after 11 CatIB recycling cycles in repetitive batch operation 80% of the activity was still present. CONCLUSIONS: This work presents a method for the effective formation of a highly active and long-term stable BsGDH-CatIB as an immobilized enzyme for robust and convenient NADH regeneration.

Garvicin Q: characterization of biosynthesis and mode of action.

Bacteriocins are ribosomally synthesized antimicrobial peptides, that either kill target bacteria or inhibit their growth. Bacteriocins are used in food preservation and are of increasing interest as potential alternatives to conventional antibiotics. In the present study, we show that Lactococcus petauri B1726, a strain isolated from fermented balsam pear, produces a heat-stable and protease-sensitive compound. Following genome sequencing, a gene cluster for production of a class IId bacteriocin was identified consisting of garQ (encoding for the bacteriocin garvicin Q), garI (for a putative immunity protein), garC, and garD (putative transporter proteins). Growth conditions were optimized for increased bacteriocin activity in supernatants of L. petauri B1726 and purification and mass spectrometry identified the compound as garvicin Q. Further experiments suggest that garvicin Q adsorbs to biomass of various susceptible and insusceptible bacteria and support the hypothesis that garvicin Q requires a mannose-family phosphotransferase system (PTSMan) as receptor to kill target bacteria by disruption of membrane integrity. Heterologous expression of a synthetic garQICD operon was established in Corynebacterium glutamicum demonstrating that genes garQICD are responsible for biosynthesis and secretion of garvicin Q. Moreover, production of garvicin Q by the recombinant C. glutamicum strain was improved by using a defined medium yet product levels were still considerably lower than with the natural L. petauri B1726 producer strain.Collectively, our data identifies the genetic basis for production of the bacteriocin garvicin Q by L. petauri B1726 and provides insights into the receptor and mode of action of garvicin Q. Moreover, we successfully performed first attempts towards biotechnological production of this interesting bacteriocin using natural and heterologous hosts.

Accelerated strain construction and characterization of C. glutamicum protein secretion by laboratory automation.

Secretion of bacterial proteins into the culture medium simplifies downstream processing by avoiding cell disruption for target protein purification. However, a suitable signal peptide for efficient secretion needs to be identified, and currently, there are no tools available to predict optimal combinations of signal peptides and target proteins. The selection of such a combination is influenced by several factors, including protein biosynthesis efficiency and cultivation conditions, which both can have a significant impact on secretion performance. As a result, a large number of combinations must be tested. Therefore, we have developed automated workflows allowing for targeted strain construction and secretion screening using two platforms. Key advantages of this experimental setup include lowered hands-on time and increased throughput. In this study, the automated workflows were established for the heterologous production of Fusarium solani f. sp. pisi cutinase in Corynebacterium glutamicum. The target protein was monitored in culture supernatants via enzymatic activity and split GFP assay. Varying spacer lengths between the Shine-Dalgarno sequence and the start codon of Bacillus subtilis signal peptides were tested. Consistent with previous work on the secretory cutinase production in B. subtilis, a ribosome binding site with extended spacer length to up to 12 nt, which likely slows down translation initiation, does not necessarily lead to poorer cutinase secretion by C. glutamicum. The best performing signal peptides for cutinase secretion with a standard spacer length were identified in a signal peptide screening. Additional insights into the secretion process were gained by monitoring secretion stress using the C. glutamicum K9 biosensor strain. KEY POINTS: • Automated workflows for strain construction and screening of protein secretion • Comparison of spacer, signal peptide, and host combinations for cutinase secretion • Signal peptide screening for secretion by C. glutamicum using the split GFP assay.

Control of parallelized bioreactors II: probabilistic quantification of carboxylic acid reductase activity for bioprocess optimization.

Autonomously operated parallelized mL-scale bioreactors are considered the key to reduce bioprocess development cost and time. However, their application is often limited to products with very simple analytics. In this study, we investigated enhanced protein expression conditions of a carboxyl reductase from Nocardia otitidiscaviarum in E. coli. Cells were produced with exponential feeding in a L-scale bioreactor. After the desired cell density for protein expression was reached, the cells were automatically transferred to 48 mL-scale bioreactors operated by a liquid handling station where protein expression studies were conducted. During protein expression, the feed rate and the inducer concentration was varied. At the end of the protein expression phase, the enzymatic activity was estimated by performing automated whole-cell biotransformations in a deep-well-plate. The results were analyzed with hierarchical Bayesian modelling methods to account for the biomass growth during the biotransformation, biomass interference on the subsequent product assay, and to predict absolute and specific enzyme activities at optimal expression conditions. Lower feed rates seemed to be beneficial for high specific and absolute activities. At the optimal investigated expression conditions an activity of [Formula: see text] was estimated with a [Formula: see text] credible interval of [Formula: see text]. This is about 40-fold higher than the highest published data for the enzyme under investigation. With the proposed setup, 192 protein expression conditions were studied during four experimental runs with minimal manual workload, showing the reliability and potential of automated and digitalized bioreactor systems.

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.

Scaling production of GFP1-10 detector protein in E. coli for secretion screening by split GFP assay.

BACKGROUND: The split GFP assay is a well-known technology for activity-independent screening of target proteins. A superfolder GFP is split into two non-fluorescent parts, GFP11 which is fused to the target protein and GFP1-10. In the presence of both, GFP1-10 and the GFP11-tag are self-assembled and a functional chromophore is formed. However, it relies on the availability and quality of GFP1-10 detector protein to develop fluorescence by assembly with the GFP11-tag connected to the target protein. GFP1-10 detector protein is often produced in small scale shake flask cultivation and purified from inclusion bodies. RESULTS: The production of GFP1-10 in inclusion bodies and purification was comprehensively studied based on Escherichia coli as host. Cultivation in complex and defined medium as well as different feed strategies were tested in laboratory-scale bioreactor cultivation and a standardized process was developed providing high quantity of GFP1-10 detector protein with suitable quality. Split GFP assay was standardized to obtain robust and reliable assay results from cutinase secretion strains of Corynebacterium glutamicum with Bacillus subtilis Sec signal peptides NprE and Pel. Influencing factors from environmental conditions, such as pH and temperature were thoroughly investigated. CONCLUSIONS: GFP1-10 detector protein production could be successfully scaled from shake flask to laboratory scale bioreactor. A single run yielded sufficient material for up to 385 96-well plate screening runs. The application study with cutinase secretory strains showed very high correlation between measured cutinase activity to split GFP fluorescence signal proofing applicability for larger screening studies.

Construction and comprehensive characterization of an EcLDCc-CatIB set-varying linkers and aggregation inducing tags.

BACKGROUND: In recent years, the production of inclusion bodies that retained substantial catalytic activity was demonstrated. These catalytically active inclusion bodies (CatIBs) were formed by genetic fusion of an aggregation inducing tag to a gene of interest via short linker polypeptides and overproduction of the resulting gene fusion in Escherichia coli. The resulting CatIBs are known for their high stability, easy and cost efficient production, and recyclability and thus provide an interesting alternative to conventionally immobilized enzymes. RESULTS: Here, we present the construction and characterization of a CatIB set of the lysine decarboxylase from Escherichia coli (EcLDCc), constructed via Golden Gate Assembly. A total of ten EcLDCc variants consisting of combinations of two linker and five aggregation inducing tag sequences were generated. A flexible Serine/Glycine (SG)- as well as a rigid Proline/Threonine (PT)-Linker were tested in combination with the artificial peptides (18AWT, L6KD and GFIL8) or the coiled-coil domains (TDoT and 3HAMP) as aggregation inducing tags. The linkers were fused to the C-terminus of the EcLDCc to form a linkage between the enzyme and the aggregation inducing tags. Comprehensive morphology and enzymatic activity analyses were performed for the ten EcLDCc-CatIB variants and a wild type EcLDCc control to identify the CatIB variant with the highest activity for the decarboxylation of L-lysine to 1,5-diaminopentane. Interestingly, all of the CatIB variants possessed at least some activity, whilst most of the combinations with the rigid PT-Linker showed the highest conversion rates. EcLDCc-PT-L6KD was identified as the best of all variants allowing a volumetric productivity of 457 g L- 1 d- 1 and a specific volumetric productivity of 256 g L- 1 d- 1 gCatIB-1. Noteworthy, wild type EcLDCc, without specific aggregation inducing tags, also partially formed CatIBs, which, however showed lower activity compared to most of the newly constructed CatIB variants (volumetric productivity: 219 g L- 1 d- 1, specific volumetric activity: 106 g L- 1 d- 1 gCatIB- 1). Furthermore, we demonstrate that microscopic analysis can serve as a tool to find CatIB producing strains and thus allow for prescreening at an early stage to save time and resources. CONCLUSIONS: Our results clearly show that the choice of linker and aggregation inducing tag has a strong influence on the morphology and the enzymatic activity of the CatIBs. Strikingly, the linker had the most pronounced influence on these characteristics.

Need for speed: evaluation of dilute and shoot-mass spectrometry for accelerated metabolic phenotyping in bioprocess development.

With the utilization of small-scale and highly parallelized cultivation platforms embedded in laboratory robotics, microbial phenotyping and bioprocess development have been substantially accelerated, thus generating a bottleneck in bioanalytical bioprocess sample analytics. While microscale cultivation platforms allow the monitoring of typical process parameters, only limited information about product and by-product formation is provided without comprehensive analytics. The use of liquid chromatography mass spectrometry can provide such a comprehensive and quantitative insight, but is often limited by analysis runtime and throughput. In this study, we developed and evaluated six methods for amino acid quantification based on two strong cation exchanger columns and a dilute and shoot approach in hyphenation with either a triple-quadrupole or a quadrupole time-of-flight mass spectrometer. Isotope dilution mass spectrometry with 13C15N labeled amino acids was used to correct for matrix effects. The versatility of the methods for metabolite profiling studies of microbial cultivation supernatants is confirmed by a detailed method validation study. The methods using chromatography columns showed a linear range of approx. 4 orders of magnitude, sufficient response factors, and low quantification limits (7-443 nM) for single analytes. Overall, relative standard deviation was comparable for all analytes, with < 8% and < 11% for unbuffered and buffered media, respectively. The dilute and shoot methods with an analysis time of 1 min provided similar performance but showed a factor of up to 35 times higher throughput. The performance and applicability of the dilute and shoot method are demonstrated using a library of Corynebacterium glutamicum strains producing L-histidine, obtained from random mutagenesis, which were cultivated in a microscale cultivation platform.

Secretome Dynamics in a Gram-Positive Bacterial Model.

Protein secretion is a central biological process in all organisms. Most studies dissecting bacterial secretion mechanisms have focused on Gram-negative cell envelopes such as that of Escherichia coli However, proteomics analyses in Gram negatives is hampered by their outer membrane. Here we studied protein secretion in the Gram-positive bacterium Streptomyces lividans TK24, in which most of the secretome is released in the growth medium. We monitored changes of the secretome as a function of growth phase and medium. We determined distinct protein classes of "house-keeping" secreted proteins that do not change their appearance or abundance in the various media and growth phases. These comprise mainly enzymes involved in cell wall maintenance and basic transport. In addition, we detected significant abundance and content changes to a sub-set of the proteome, as a function of growth in the different media. These did not depend on the media being minimal or rich. Transcriptional regulation but not changes in export machinery components can explain some of these changes. However, additional downstream mechanisms must be important for selective secretome funneling. These observations lay the foundations of using S. lividans as a model organism to study how metabolism is linked to optimal secretion and help develop rational optimization of heterologous protein production.

Catalytically-active inclusion bodies for biotechnology-general concepts, optimization, and application.

Bacterial inclusion bodies (IBs) have long been considered as inactive, unfolded waste material produced by heterologous overexpression of recombinant genes. In industrial applications, they are occasionally used as an alternative in cases where a protein cannot be expressed in soluble form and in high enough amounts. Then, however, refolding approaches are needed to transform inactive IBs into active soluble protein. While anecdotal reports about IBs themselves showing catalytic functionality/activity (CatIB) are found throughout literature, only recently, the use of protein engineering methods has facilitated the on-demand production of CatIBs. CatIB formation is induced usually by fusing short peptide tags or aggregation-inducing protein domains to a target protein. The resulting proteinaceous particles formed by heterologous expression of the respective genes can be regarded as a biologically produced bionanomaterial or, if enzymes are used as target protein, carrier-free enzyme immobilizates. In the present contribution, we review general concepts important for CatIB production, processing, and application. KEY POINTS: • Catalytically active inclusion bodies (CatIBs) are promising bionanomaterials. • Potential applications in biocatalysis, synthetic chemistry, and biotechnology. • CatIB formation represents a generic approach for enzyme immobilization. • CatIB formation efficiency depends on construct design and expression conditions.

Parallelized microscale fed-batch cultivation in online-monitored microtiter plates: implications of media composition and feed strategies for process design and performance.

Limited throughput represents a substantial drawback during bioprocess development. In recent years, several commercial microbioreactor systems have emerged featuring parallelized experimentation with optical monitoring. However, many devices remain limited to batch mode and do not represent the fed-batch strategy typically applied on an industrial scale. A workflow for 32-fold parallelized microscale cultivation of protein secreting Corynebacterium glutamicum in microtiter plates incorporating online monitoring, pH control and feeding was developed and validated. Critical interference of the essential media component protocatechuic acid with pH measurement was revealed, but was effectively resolved by 80% concentration reduction without affecting biological performance. Microfluidic pH control and feeding (pulsed, constant and exponential) were successfully implemented: Whereas pH control improved performance only slightly, feeding revealed a much higher optimization potential. Exponential feeding with µ = 0.1 h-1 resulted in the highest product titers. In contrast, other performance indicators such as biomass-specific or volumetric productivity resulted in different optimal feeding regimes.