Dynamic feedback regulation for efficient membrane protein production using a small RNA-based genetic circuit in Escherichia coli.

BACKGROUND: Membrane proteins (MPs) are an important class of molecules with a wide array of cellular functions and are part of many metabolic pathways. Despite their great potential-as therapeutic drug targets or in microbial cell factory optimization-many challenges remain for efficient and functional expression in a host such as Escherichia coli. RESULTS: A dynamically regulated small RNA-based circuit was developed to counter membrane stress caused by overexpression of different MPs. The best performing small RNAs were able to enhance the maximum specific growth rate with 123%. On culture level, the total MP production was increased two-to three-fold compared to a system without dynamic control. This strategy not only improved cell growth and production of the studied MPs, it also suggested the potential use for countering metabolic burden in general. CONCLUSIONS: A dynamically regulated feedback circuit was developed that can sense metabolic stress caused by, in casu, the overexpression of an MP and responds to it by balancing the metabolic state of the cell and more specifically by downregulating the expression of the MP of interest. This negative feedback mechanism was established by implementing and optimizing simple-to-use genetic control elements based on post-transcriptional regulation: small non-coding RNAs. In addition to membrane-related stress when the MP accumulated in the cytoplasm as aggregates, the sRNA-based feedback control system was still effective for improving cell growth but resulted in a decreased total protein production. This result suggests promiscuity of the MP sensor for more than solely membrane stress.

Biosensor-driven, model-based optimization of the orthogonally expressed naringenin biosynthesis pathway.

BACKGROUND: The rapidly expanding synthetic biology toolbox allows engineers to develop smarter strategies to tackle the optimization of complex biosynthetic pathways. In such a strategy, multi-gene pathways are subdivided in several modules which are each dynamically controlled to fine-tune their expression in response to a changing cellular environment. To fine-tune separate modules without interference between modules or from the host regulatory machinery, a sigma factor (σ) toolbox was developed in previous work for tunable orthogonal gene expression. Here, this toolbox is implemented in E. coli to orthogonally express and fine-tune a pathway for the heterologous biosynthesis of the industrially relevant plant metabolite, naringenin. To optimize the production of this pathway, a practical workflow is still imperative to balance all steps of the pathway. This is tackled here by the biosensor-driven screening, subsequent genotyping of combinatorially engineered libraries and finally the training of three different computer models to predict the optimal pathway configuration. RESULTS: The efficiency and knowledge gained through this workflow is demonstrated here by improving the naringenin production titer by 32% with respect to a random pathway library screen. Our best strain was cultured in a batch bioreactor experiment and was able to produce 286 mg/L naringenin from glycerol in approximately 26 h. This is the highest reported naringenin production titer in E. coli without the supplementation of pathway precursors to the medium or any precursor pathway engineering. In addition, valuable pathway configuration preferences were identified in the statistical learning process, such as specific enzyme variant preferences and significant correlations between promoter strength at specific steps in the pathway and titer. CONCLUSIONS: An efficient strategy, powered by orthogonal expression, was applied to successfully optimize a biosynthetic pathway for microbial production of flavonoids in E. coli up to high, competitive levels. Within this strategy, statistical learning techniques were combined with combinatorial pathway optimization techniques and an in vivo high-throughput screening method to efficiently determine the optimal operon configuration of the pathway. This "pathway architecture designer" workflow can be applied for the fast and efficient development of new microbial cell factories for different types of molecules of interest while also providing additional insights into the underlying pathway characteristics.

A sigma factor toolbox for orthogonal gene expression in Escherichia coli.

Synthetic genetic sensors and circuits enable programmable control over timing and conditions of gene expression and, as a result, are increasingly incorporated into the control of complex and multi-gene pathways. Size and complexity of genetic circuits are growing, but stay limited by a shortage of regulatory parts that can be used without interference. Therefore, orthogonal expression and regulation systems are needed to minimize undesired crosstalk and allow for dynamic control of separate modules. This work presents a set of orthogonal expression systems for use in Escherichia coli based on heterologous sigma factors from Bacillus subtilis that recognize specific promoter sequences. Up to four of the analyzed sigma factors can be combined to function orthogonally between each other and toward the host. Additionally, the toolbox is expanded by creating promoter libraries for three sigma factors without loss of their orthogonal nature. As this set covers a wide range of transcription initiation frequencies, it enables tuning of multiple outputs of the circuit in response to different sensory signals in an orthogonal manner. This sigma factor toolbox constitutes an interesting expansion of the synthetic biology toolbox and may contribute to the assembly of more complex synthetic genetic systems in the future.

Exploring of the feature space of de novo developed post-transcriptional riboregulators.

Metabolic engineering increasingly depends upon RNA technology to customly rewire the metabolism to maximize production. To this end, pure riboregulators allow dynamic gene repression without the need of a potentially burdensome coexpressed protein like typical Hfq binding small RNAs and clustered regularly interspaced short palindromic repeats technology. Despite this clear advantage, no clear general design principles are available to de novo develop repressing riboregulators, limiting the availability and the reliable development of these type of riboregulators. Here, to overcome this lack of knowledge on the functionality of repressing riboregulators, translation inhibiting RNAs are developed from scratch. These de novo developed riboregulators explore features related to thermodynamical and structural factors previously attributed to translation initiation modulation. In total, 12 structural and thermodynamic features were defined of which six features were retained after removing correlations from an in silico generated riboregulator library. From this translation inhibiting RNA library, 18 riboregulators were selected using a experimental design and subsequently constructed and co-expressed with two target untranslated regions to link the translation inhibiting RNA features to functionality. The pure riboregulators in the design of experiments showed repression down to 6% of the original protein expression levels, which could only be partially explained by a ordinary least squares regression model. To allow reliable forward engineering, a partial least squares regression model was constructed and validated to link the properties of translation inhibiting RNA riboregulators to gene repression. In this model both structural and thermodynamic features were important for efficient gene repression by pure riboregulators. This approach enables a more reliable de novo forward engineering of effective pure riboregulators, which further expands the RNA toolbox for gene expression modulation.

Standardization in synthetic biology: an engineering discipline coming of age.

BACKGROUND: Leaping DNA read-and-write technologies, and extensive automation and miniaturization are radically transforming the field of biological experimentation by providing the tools that enable the cost-effective high-throughput required to address the enormous complexity of biological systems. However, standardization of the synthetic biology workflow has not kept abreast with dwindling technical and resource constraints, leading, for example, to the collection of multi-level and multi-omics large data sets that end up disconnected or remain under- or even unexploited. PURPOSE: In this contribution, we critically evaluate the various efforts, and the (limited) success thereof, in order to introduce standards for defining, designing, assembling, characterizing, and sharing synthetic biology parts. The causes for this success or the lack thereof, as well as possible solutions to overcome these, are discussed. CONCLUSION: Akin to other engineering disciplines, extensive standardization will undoubtedly speed-up and reduce the cost of bioprocess development. In this respect, further implementation of synthetic biology standards will be crucial for the field in order to redeem its promise, i.e. to enable predictable forward engineering.

Development of N-acetylneuraminic acid responsive biosensors based on the transcriptional regulator NanR.

Transcriptional biosensors have various applications in metabolic engineering, including dynamic pathway control and high-throughput screening of combinatorial strain libraries. Previously, various biosensors have been created from naturally occurring transcription factors (TFs), largely relying on native sequences without the possibility to modularly optimize their response curve. The lack of design and engineering techniques thus greatly hinders the development of custom biosensors. In view of the intended application this is detrimental. In contrast, a bottom-up approach to design tailor-made biosensors was pursued here. Novel biosensors were created that respond to N-acetylneuraminic acid (Neu5Ac), an important sugar moiety with various biological functions, by employing native and engineered promoters that interact with the TF NanR. This bottom-up approach, whereby various tuned modules, e.g., the ribosome binding site (RBS) controlling NanR translation can be combined, enabled the reliable engineering of various response curve characteristics. The latter was validated by testing these biosensors in combination with various Neu5Ac-producing pathways, which allowed to produce up to 1.4 ± 0.4 g/L extracellular Neu5Ac. In this way, the repertoire of biosensors was expanded with seven novel functional Neu5Ac-responsive biosensors.

Tailor-made transcriptional biosensors for optimizing microbial cell factories.

Monitoring cellular behavior and eventually properly adapting cellular processes is key to handle the enormous complexity of today's metabolic engineering questions. Hence, transcriptional biosensors bear the potential to augment and accelerate current metabolic engineering strategies, catalyzing vital advances in industrial biotechnology. The development of such transcriptional biosensors typically starts with exploring nature's richness. Hence, in a first part, the transcriptional biosensor architecture and the various modi operandi are briefly discussed, as well as experimental and computational methods and relevant ontologies to search for natural transcription factors and their corresponding binding sites. In the second part of this review, various engineering approaches are reviewed to tune the main characteristics of these (natural) transcriptional biosensors, i.e., the response curve and ligand specificity, in view of specific industrial biotechnology applications, which is illustrated using success stories of transcriptional biosensor engineering.

Comparative fluxome and metabolome analysis for overproduction of succinate in Escherichia coli.

An aerobic succinate-producing Escherichia coli mutant was compared to its wild-type by quantitatively analyzing both the metabolome and fluxome, during glucose-limited steady-state and succinate excess dynamic conditions, in order to identify targets for further strain engineering towards more efficient succinate production. The mutant had four functional mutations under the conditions investigated: increased expression of a succinate exporter (DcuC), deletion of a succinate importer (Dct), deletion of succinate dehydrogenase (SUCDH) and expression of a PEP carboxylase (PPC) with increased capacity due to a point mutation. The steady-state and dynamic patterns of the intracellular metabolite levels and fluxes in response to changes were used to locate the quantitative differences in the physiology/metabolism of the mutant strain. Unexpectedly the mutant had a higher energy efficiency, indicated by a much lower rate of oxygen consumption, under glucose-limited conditions, caused by the deletion of the transcription factors IclR and ArcA. Furthermore the mutant had a much lower uptake capacity for succinate (26-fold) and oxygen (17-fold under succinate excess) compared to the wild-type strain. The mutant strain produced 7.9 mmol.CmolX(-1).h(-1) succinate during chemostat cultivation, showing that the choice of the applied genetic modifications was a successful strategy. Furthermore, the applied genetic modifications resulted in multiple large changes in metabolite levels (FBP, pyruvate, 6PG, NAD(+) /NADH ratio, α-ketogluarate) corresponding to large changes in fluxes. Compared to the wild-type a considerable flux shift occurred from the tricarboxylic acid (TCA) cycle to the oxidative part of the pentose phosphate pathway, including an inversion of the pyruvate kinase flux. The mutant responded very differently to excess of succinate, with a remarkable possible reversal of the TCA cycle. The mutant and the wild-type both showed homeostatic behaviour with respect to the energy charge. In contrast, large changes in redox ratios (NAD(+) /NADH) occurred in the wild-type, while the mutant showed even larger changes. This large redox change can be associated to the reversal of flux directions. The observed large flexibility in the central metabolism following genetic (deletions) and environmental (substrate excess) perturbations of the mutant, indicates that introducing a more efficient succinate exporter could result in an even higher succinate production rate.

Development of an in vivo glucosylation platform by coupling production to growth: Production of phenolic glucosides by a glycosyltransferase of Vitis vinifera.

Glycosylation of small molecules can significantly alter their properties such as solubility, stability, and/or bioactivity, making glycosides attractive and highly demanded compounds. Consequently, many biotechnological glycosylation approaches have been developed, with enzymatic synthesis and whole-cell biocatalysis as the most prominent techniques. However, most processes still suffer from low yields, production rates and inefficient UDP-sugar formation. To this end, a novel metabolic engineering strategy is presented for the in vivo glucosylation of small molecules in Escherichia coli W. This strategy focuses on the introduction of an alternative sucrose metabolism using sucrose phosphorylase for the direct and efficient generation of glucose 1-phosphate as precursor for UDP-glucose formation and fructose, which serves as a carbon source for growth. By targeted gene deletions, a split metabolism is created whereby glucose 1-phosphate is rerouted from the glycolysis to product formation (i.e., glucosylation). Further, the production pathway was enhanced by increasing and preserving the intracellular UDP-glucose pool. Expression of a versatile glucosyltransferase from Vitis vinifera (VvGT2) enabled the strain to efficiently produce 14 glucose esters of various hydroxycinnamates and hydroxybenzoates with conversion yields up to 100%. To our knowledge, this fast growing (and simultaneously producing) E. coli mutant is the first versatile host described for the glucosylation of phenolic acids in a fermentative way using only sucrose as a cheap and sustainable carbon source.

Metabolic engineering of Escherichia coli into a versatile glycosylation platform: production of bio-active quercetin glycosides.

BACKGROUND: Flavonoids are bio-active specialized plant metabolites which mainly occur as different glycosides. Due to the increasing market demand, various biotechnological approaches have been developed which use Escherichia coli as a microbial catalyst for the stereospecific glycosylation of flavonoids. Despite these efforts, most processes still display low production rates and titers, which render them unsuitable for large-scale applications. RESULTS: In this contribution, we expanded a previously developed in vivo glucosylation platform in E. coli W, into an efficient system for selective galactosylation and rhamnosylation. The rational of the novel metabolic engineering strategy constitutes of the introduction of an alternative sucrose metabolism in the form of a sucrose phosphorylase, which cleaves sucrose into fructose and glucose 1-phosphate as precursor for UDP-glucose. To preserve these intermediates for glycosylation purposes, metabolization reactions were knocked-out. Due to the pivotal role of UDP-glucose, overexpression of the interconverting enzymes galE and MUM4 ensured the formation of both UDP-galactose and UDP-rhamnose, respectively. By additionally supplying exogenously fed quercetin and overexpressing a flavonol galactosyltransferase (F3GT) or a rhamnosyltransferase (RhaGT), 0.94 g/L hyperoside (quercetin 3-O-galactoside) and 1.12 g/L quercitrin (quercetin 3-O-rhamnoside) could be produced, respectively. In addition, both strains showed activity towards other promising dietary flavonols like kaempferol, fisetin, morin and myricetin. CONCLUSIONS: Two E. coli W mutants were engineered that could effectively produce the bio-active flavonol glycosides hyperoside and quercitrin starting from the cheap substrates sucrose and quercetin. This novel fermentation-based glycosylation strategy will allow the economically viable production of various glycosides.

One step DNA assembly for combinatorial metabolic engineering.

The rapid and efficient assembly of multi-step metabolic pathways for generating microbial strains with desirable phenotypes is a critical procedure for metabolic engineering, and remains a significant challenge in synthetic biology. Although several DNA assembly methods have been developed and applied for metabolic pathway engineering, many of them are limited by their suitability for combinatorial pathway assembly. The introduction of transcriptional (promoters), translational (ribosome binding site (RBS)) and enzyme (mutant genes) variability to modulate pathway expression levels is essential for generating balanced metabolic pathways and maximizing the productivity of a strain. We report a novel, highly reliable and rapid single strand assembly (SSA) method for pathway engineering. The method was successfully optimized and applied to create constructs containing promoter, RBS and/or mutant enzyme libraries. To demonstrate its efficiency and reliability, the method was applied to fine-tune multi-gene pathways. Two promoter libraries were simultaneously introduced in front of two target genes, enabling orthogonal expression as demonstrated by principal component analysis. This shows that SSA will increase our ability to tune multi-gene pathways at all control levels for the biotechnological production of complex metabolites, achievable through the combinatorial modulation of transcription, translation and enzyme activity.

Changes in substrate availability in Escherichia coli lead to rapid metabolite, flux and growth rate responses.

The interactions between the intracellular metabolome, fluxome and growth rate of Escherichia coli after sudden glycolytic/gluconeogenic substrate shifts are studied based on pulses of different substrates to an aerobic glucose-limited steady-state (dilution rate=0.1h(-1)). After each added glycolytic (glucose) and gluconeogenic (pyruvate and succinate) substrate pulse, no by-products were secreted and a pseudo steady state in flux and metabolites was achieved in about 30-40s. In the pulse experiments a large oxygen uptake capacity of the cells was observed. The in vivo dynamic responses showed massive reorganization and flexibility (1/100-14-fold change) of extra/intracellular metabolic fluxes, matching with large changes in the concentrations of intracellular metabolites, including reversal of reaction rate for pseudo/near equilibrium reactions. The coupling of metabolome and fluxome could be described by Q-linear kinetics. Remarkably, the three different substrate pulses resulted in a very similar increase in growth rate (0.13-0.3h(-1)). Data analysis showed that there must exist as yet unknown mechanisms which couple the protein synthesis rate to changes in central metabolites.

Unraveling the Leloir pathway of Bifidobacterium bifidum: significance of the uridylyltransferases.

The GNB/LNB (galacto-N-biose/lacto-N-biose) pathway plays a crucial role in bifidobacteria during growth on human milk or mucin from epithelial cells. It is thought to be the major route for galactose utilization in Bifidobacterium longum as it is an energy-saving variant of the Leloir pathway. Both pathways are present in B. bifidum, and galactose 1-phosphate (gal1P) is considered to play a key role. Due to its toxic nature, gal1P is further converted into its activated UDP-sugar through the action of poorly characterized uridylyltransferases. In this study, three uridylyltransferases (galT1, galT2, and ugpA) from Bifidobacterium bifidum were cloned in an Escherichia coli mutant and screened for activity on the key intermediate gal1P. GalT1 and GalT2 showed UDP-glucose-hexose-1-phosphate uridylyltransferase activity (EC 2.7.7.12), whereas UgpA showed promiscuous UTP-hexose-1-phosphate uridylyltransferase activity (EC 2.7.7.10). The activity of UgpA toward glucose 1-phosphate was about 33-fold higher than that toward gal1P. GalT1, as part of the bifidobacterial Leloir pathway, was about 357-fold more active than GalT2, the functional analog in the GNB/LNB pathway. These results suggest that GalT1 plays a more significant role than previously thought and predominates when B. bifidum grows on lactose and human milk oligosaccharides. GalT2 activity is required only during growth on substrates with a GNB core such as mucin glycans.

Taming CRISPRi: Dynamic range tuning through guide RNA diversion.

CRISPRi is a powerful technique to repress gene expression in a targeted and highly efficient manner. However, this potency is a double-edged sword in inducible systems, as even leaky expression of guide RNA results in a repression phenotype, complicating applications such as dynamic metabolic engineering. We evaluated three methods to enhance the controllability of CRISPRi by modulating the level of free and DNA-bound guide RNA complexes. Overall repression can be attenuated through rationally designed mismatches in the reversibility determining region of the guide RNA sequence; decoy target sites can selectively modulate repression at low levels of induction; and the implementation of feedback control not only enhances the linearity of induction, but broadens the dynamic range of the output as well. Furthermore, feedback control significantly enhances the recovery rate after induction is removed. Used in combination, these techniques enable the fine-tuning of CRISPRi to meet restrictions imposed by the target and match the input signal required for induction.

Effect of iclR and arcA deletions on physiology and metabolic fluxes in Escherichia coli BL21 (DE3).

Deletion of both iclR and arcA in E. coli profoundly alters the central metabolic fluxes and decreases acetate excretion by 70%. In this study we investigate the metabolic consequences of both deletions in E. coli BL21 (DE3). No significant differences in biomass yields, acetate yields, CO(2) yields and metabolic fluxes could be observed between the wild type strain E. coli BL21 (DE3) and the double-knockout strain E. coli BL21 (DE3) ΔarcAΔiclR. This proves that arcA and iclR are poorly active in the BL21 wild type strain. Noteworthy, both strains co-assimilate glucose and acetate at high glucose concentrations (10-15 g l(-1)), while this was never observed in K12 strains. This implies that catabolite repression is less intense in BL21 strains compared to in E. coli K12.

ProD: A Tool for Predictive Design of Tailored Promoters in Escherichia coli.

A major goal in synthetic biology is the engineering of synthetic gene circuits with a predictable, controlled and designed outcome. This creates a need for building blocks that can modulate gene expression without interference with the native cell system. A tool allowing forward engineering of promoters with predictable transcription initiation frequency is still lacking. Promoter libraries specific for σ70 to ensure the orthogonality of gene expression were built in Escherichia coli and labeled using fluorescence-activated cell sorting to obtain high-throughput DNA sequencing data to train a convolutional neural network. We were able to confirm in vivo that the model is able to predict the promoter transcription initiation frequency (TIF) of new promoter sequences. Here, we provide an online tool for promoter design (ProD) in E. coli, which can be used to tailor output sequences of desired promoter TIF or predict the TIF of a custom sequence.

Effect of iclR and arcA knockouts on biomass formation and metabolic fluxes in Escherichia coli K12 and its implications on understanding the metabolism of Escherichia coli BL21 (DE3).

BACKGROUND: Gene expression is regulated through a complex interplay of different transcription factors (TFs) which can enhance or inhibit gene transcription. ArcA is a global regulator that regulates genes involved in different metabolic pathways, while IclR as a local regulator, controls the transcription of the glyoxylate pathway genes of the aceBAK operon. This study investigates the physiological and metabolic consequences of arcA and iclR deletions on E. coli K12 MG1655 under glucose abundant and limiting conditions and compares the results with the metabolic characteristics of E. coli BL21 (DE3). RESULTS: The deletion of arcA and iclR results in an increase in the biomass yield both under glucose abundant and limiting conditions, approaching the maximum theoretical yield of 0.65 c-mole/c-mole glucose under glucose abundant conditions. This can be explained by the lower flux through several CO2 producing pathways in the E. coli K12 ΔarcAΔiclR double knockout strain. Due to iclR gene deletion, the glyoxylate pathway is activated resulting in a redirection of 30% of the isocitrate molecules directly to succinate and malate without CO2 production. Furthermore, a higher flux at the entrance of the TCA was noticed due to arcA gene deletion, resulting in a reduced production of acetate and less carbon loss. Under glucose limiting conditions the flux through the glyoxylate pathway is further increased in the ΔiclR knockout strain, but this effect was not observed in the double knockout strain. Also a striking correlation between the glyoxylate flux data and the isocitrate lyase activity was observed for almost all strains and under both growth conditions, illustrating the transcriptional control of this pathway. Finally, similar central metabolic fluxes were observed in E. coli K12 ΔarcA ΔiclR compared to the industrially relevant E. coli BL21 (DE3), especially with respect to the pentose pathway, the glyoxylate pathway, and the TCA fluxes. In addition, a comparison of the genome sequences of the two strains showed that BL21 possesses two mutations in the promoter region of iclR and rare codons are present in arcA implying a lower tRNA acceptance. Both phenomena presumably result in a reduced ArcA and IclR synthesis in BL21, which contributes to the similar physiology as observed in E. coli K12 ΔarcAΔiclR. CONCLUSIONS: The deletion of arcA results in a decrease of repression on transcription of TCA cycle genes under glucose abundant conditions, without significantly affecting the glyoxylate pathway activity. IclR clearly represses transcription of glyoxylate pathway genes under glucose abundance, a condition in which Crp activation is absent. Under glucose limitation, Crp is responsible for the high glyoxylate flux, but IclR still represses transcription. Finally, in E. coli BL21 (DE3), ArcA and IclR are poorly expressed, explaining the similar fluxes observed compared to the ΔarcAΔiclR strain.

Promoter knock-in: a novel rational method for the fine tuning of genes.

BACKGROUND: Metabolic engineering aims at channeling the metabolic fluxes towards a desired compound. An important strategy to achieve this is the modification of the expression level of specific genes. Several methods for the modification or the replacement of promoters have been proposed, but most of them involve time-consuming screening steps. We describe here a novel optimized method for the insertion of constitutive promoters (referred to as "promoter knock-in") whose strength can be compared with the native promoter by applying a promoter strength predictive (PSP) model. RESULTS: Our method was successfully applied to fine tune the ppc gene of Escherichia coli. While developing the promoter knock-in methodology, we showed the importance of conserving the natural leader region containing the ribosome binding site (RBS) of the gene of interest and of eliminating upstream regulatory elements (transcription factor binding sites). The gene expression was down regulated instead of up regulated when the natural RBS was not conserved and when the upstream regulatory elements were eliminated. Next, three different promoter knock-ins were created for the ppc gene selecting three different artificial promoters. The measured constitutive expression of the ppc gene in these knock-ins reflected the relative strength of the different promoters as predicted by the PSP model. The applicability of our PSP model and promoter knock-in methodology was further demonstrated by showing that the constitutivity and the relative levels of expression were independent of the genetic background (comparing wild-type and mutant E. coli strains). No differences were observed during scaling up from shake flask to bioreactor-scale, confirming that the obtained expression was independent of environmental conditions. CONCLUSION: We are proposing a novel methodology for obtaining appropriate levels of expression of genes of interest, based on the prediction of the relative strength of selected synthetic promoters combined with an optimized promoter knock-in strategy. The obtained expression levels are independent of the genetic background and scale conditions. The method constitutes therefore a valuable addition to the genetic toolbox for the metabolic engineering of E. coli.

Catching prompt metabolite dynamics in Escherichia coli with the BioScope at oxygen rich conditions.

The design and application of a BioScope, a mini plug-flow reactor for carrying out pulse response experiments, specifically designed for Escherichia coli is presented. Main differences with the previous design are an increased volume-specific membrane surface for oxygen transfer and significantly decreased sampling intervals. The characteristics of the new device (pressure drop, residence time distribution, plug-flow behavior and O2 mass transfer) were determined and evaluated. Subsequently, 2.8 mM glucose perturbation experiments on glucose-limited aerobic E. coli chemostat cultures were carried out directly in the chemostat as well as in the BioScope (for two time frames: 8 and 40 s). It was ensured that fully aerobic conditions were maintained during the perturbation experiments. To avoid metabolite leakage during quenching, metabolite quantification (glycolytic and TCA-cycle intermediates and nucleotides) was carried out with a differential method, whereby the amounts measured in the filtrate were subtracted from the amounts measured in total broth. The dynamic metabolite profiles obtained from the BioScope perturbations were very comparable with the profiles obtained from the chemostat perturbation. This agreement demonstrates that the BioScope is a promising device for studying in vivo kinetics in E. coli that shows much faster response (< 10 s) in comparison with eukaryotes.

Dynamic metabolic flux analysis demonstrated on cultures where the limiting substrate is changed from carbon to nitrogen and vice versa.

The main requirement for metabolic flux analysis (MFA) is that the cells are in a pseudo-steady state, that there is no accumulation or depletion of intracellular metabolites. In the past, the applications of MFA were limited to the analysis of continuous cultures. This contribution introduces the concept of dynamic MFA and extends MFA so that it is applicable to transient cultures. Time series of concentration measurements are transformed into flux values. This transformation involves differentiation, which typically increases the noisiness of the data. Therefore, a noise-reducing step is needed. In this work, polynomial smoothing was used. As a test case, dynamic MFA is applied on Escherichia coli cultivations shifting from carbon limitation to nitrogen limitation and vice versa. After switching the limiting substrate from N to C, a lag phase was observed accompanied with an increase in maintenance energy requirement. This lag phase did not occur in the C- to N-limitation case.