MoBioS: Modular Platform Technology for High-Throughput Construction and Characterization of Tunable Transcriptional Biological Sensors.

All living organisms have evolved and fine-tuned specialized mechanisms to precisely monitor a vast array of different types of molecules. These natural mechanisms can be sourced by researchers to build Biological Sensors (BioS) by combining them with an easily measurable output, such as fluorescence. Because they are genetically encoded, BioS are cheap, fast, sustainable, portable, self-generating and highly sensitive and specific. Therefore, BioS hold the potential to become key enabling tools that stimulate innovation and scientific exploration in various disciplines. However, the main bottleneck in unlocking the full potential of BioS is the fact that there is no standardized, efficient and tunable platform available for the high-throughput construction and characterization of biosensors. Therefore, a modular, Golden Gate-based construction platform, called MoBioS, is introduced in this article. It allows for the fast and easy creation of transcription factor-based biosensor plasmids. As a proof of concept, its potential is demonstrated by creating eight different, functional and standardized biosensors that detect eight diverse molecules of industrial interest. In addition, the platform contains novel built-in features to facilitate fast and efficient biosensor engineering and response curve tuning.

Human gut microbiota stratified by (+)-catechin metabolism dynamics reveals colon region-dependent metabolic profile.

Catechins have proven to have several health benefits, yet a huge interindividual variability occurs. The metabolic potency of the colonic microbiota towards catechin is a key determinant of this variability. Microbiota from two donors - previously characterized as a fast and a slow converter- were incubated with (+)-catechin in vitro. The robustness of in vitro metabolic profiles was verified by well-fitted human trials. The colon region-dependent and donor-dependent patterns were reflected in both metabolic features and colonic microbiota composition. Upstream and downstream metabolites were mainly detected in the proximal and distal colons, respectively, and were considered important explanatory variables for microbiota clustering in the corresponding colon regions. Higher abundances of two catechin-metabolizing bacteria, Eggerthella and Flavonifractor were found in the distal colon compared to the proximal colon and in slow converter than fast converter. Additionally, these two bacteria were enriched in treatment samples compared to sham treatment samples.

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.

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.

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.