The differential response of thePbenpromoter ofPseudomonas putida mt-2 to BenR and XylS prevents metabolic conflicts inm-xylene biodegradation

Combinatorial pathway balancing provides biosynthetic access to 2-fluoro-cis,cis-muconate in engineered Pseudomonas putida

The wealth of bio-based building blocks produced by engineered microorganisms seldom include halogen atoms. Muconate is a platform chemical with a number of industrial applications that could be broadened by introducing fluorine atoms to tune its physicochemical properties. The soil bacterium Pseudomonas putida naturally assimilates benzoate via the ortho-cleavage pathway with cis,cis-muconate as intermediate. Here, we harnessed the native enzymatic machinery (encoded within the ben and cat gene clusters) to provide catalytic access to 2-fluoro-cis,cis-muconate (2-FMA) from fluorinated benzoates. The reactions in this pathway are highly imbalanced, leading to accumulation of toxic intermediates and limited substrate conversion. By disentangling regulatory patterns of ben and cat in response to fluorinated effectors, metabolic activities were adjusted to favor 2-FMA biosynthesis. After implementing this combinatorial approach, engineered P. putida converted 3-fluorobenzoate to 2-FMA at the maximum theoretical yield. Hence, this study illustrates how synthetic biology can expand the diversity of nature's biochemical catalysis.

A dual-parameter identification approach for data-based predictive modeling of hybrid gene regulatory network-growth kinetics in Pseudomonas putida mt-2

Data integration to model-based description of biological systems incorporating gene dynamics improves the performance of microbial systems. Bioprocess performance, typically predicted using empirical Monod-type models, is essential for a sustainable bioeconomy. To replace empirical models, we updated a hybrid gene regulatory network-growth kinetic model, predicting aromatic pollutants degradation and biomass growth in Pseudomonas putida mt-2. We modeled a complex biological system including extensive information to understand the role of the regulatory elements in toluene biodegradation and biomass growth. The updated model exhibited extra complications such as the existence of oscillations and discontinuities. As parameter estimation of complex biological models remains a key challenge, we used the updated model to present a dual-parameter identification approach (the 'dual approach') combining two independent methodologies. Approach I handled the complexity by incorporation of demonstrated biological knowledge in the model-development process and combination of global sensitivity analysis and optimisation. Approach II complemented Approach I handling multimodality, ill-conditioning and overfitting through regularisation estimation, global optimisation, and identifiability analysis. To systematically quantify the biological system, we used a vast amount of high-quality time-course data. The dual approach resulted in an accurately calibrated kinetic model (NRMSE: 0.17055) efficiently handling the additional model complexity. We tested model validation using three independent experimental data sets, achieving greater predictive power (NRMSE: 0.18776) than the individual approaches (NRMSE I: 0.25322, II: 0.25227) and increasing model robustness. These results demonstrated data-driven predictive modeling potentially leading to bioprocess' model-based control and optimisation.

A Strategy Employing a TF-Splinting Duplex Nanoswitch to Achieve Single-Step, Enzyme-Free, Signal-On Detection of l-Tryptophan

Transcription factor (TF)-based metabolite detection mainly depends on TF-regulated gene expression in cells. From TF activation to gene transcription and translation, the signal travels a relatively long way before it is received. Here, we propose a TF-splinting duplex DNA nanoswitch to detect metabolites. We show its feasibility using tryptophan repressor (TrpR) to detect l-tryptophan as a model. The assay has been optimized and characterized after obtaining a proof of concept, and the detection of l-tryptophan in complex biological samples is feasible. Unlike an equivalent gene expression approach, the whole process is a single-step, enzyme-free, and signal-on method. It can be completed within 20 min. This proposed TF-splinting duplex has the potential to be applied to the quick and convenient detection of other metabolites or even TFs.

Reverse Engineering of an Aspirin-Responsive Transcriptional Regulator in Escherichia coli

Bacterial transcription factors (TFs) are key devices for the engineering of complex circuits in many biotechnological applications, yet there are few well-characterized inducer-responsive TFs that could be used in the context of an animal or human host. We have deciphered the inducer recognition mechanism of two AraC/XylS regulators from Pseudomonas putida (BenR and XylS) for creating a novel expression system responsive to acetyl salicylate (i.e., aspirin). Using protein homology modeling and molecular docking with the cognate inducer benzoate and a suite of chemical analogues, we identified the conserved binding pocket of BenR and XylS. By means of site-directed mutagenesis, we identified a single amino acid position required for efficient inducer recognition and transcriptional activation. Whereas this modification in BenR abolishes protein activity, in XylS, it increases the response to several inducers, including acetyl salicylic acid, to levels close to those achieved by the canonical inducer. Moreover, by constructing chimeric proteins with swapped N-terminal domains, we created novel regulators with mixed promoter and inducer recognition profiles. As a result, a collection of engineered TFs was generated with an enhanced response to benzoate, 3-methylbenzoate, 2-methylbenzoate, 4-methylbenzoate, salicylic acid, aspirin, and acetylsalicylic acid molecules for eliciting gene expression in E. coli.

Towards the Response Threshold for p-Hydroxyacetophenone in the Denitrifying Bacterium "Aromatoleum aromaticum" EbN1

The denitrifying betaproteobacterium "Aromatoleum aromaticum" EbN1 regulates the capacity to anaerobically degrade p-ethylphenol (via p-hydroxyacetophenone) with high substrate specificity. This process is mediated by the σ⁵⁴-dependent transcriptional regulator EtpR, which apparently recognizes both aromatic compounds, yielding congruent expression profiles. The responsiveness of this regulatory system was studied with p-hydroxyacetophenone, which is more easily administered to cultures and traced analytically. Cultures of A. aromaticum EbN1 were initially cultivated under nitrate-reducing conditions with a growth-limiting supply of benzoate, upon the complete depletion of which p-hydroxyacetophenone was added at various concentrations (from 500 μM down to 0.1 nM). Depletion profiles of this aromatic substrate and presumptive effector were determined by highly sensitive micro-high-performance liquid chromatography (microHPLC). Irrespective of the added concentration of p-hydroxyacetophenone, depletion commenced after less than 5 min and suggested a response threshold of below 10 nM. This approximation was corroborated by time-resolved transcript profiles (quantitative reverse transcription-PCR) of selected degradation and efflux relevant genes (e.g., pchF, encoding a subunit of predicted p-ethylphenol methylenehydroxylase) and narrowed down to a range of 10 to 1 nM. The most pronounced transcriptional response was observed, as expected, for genes located at the beginning of the two operon-like structures, related to catabolism (i.e., acsA) and potential efflux (i.e., ebA335).IMPORTANCE Aromatic compounds are widespread microbial growth substrates with natural as well as anthropogenic sources, albeit with their in situ concentrations and their bioavailabilities varying over several orders of magnitude. Even though degradation pathways and underlying regulatory systems have long been studied with aerobic and, to a lesser extent, with anaerobic bacteria, comparatively little is known about the effector concentration-dependent responsiveness. A. aromaticum EbN1 is a model organism for the anaerobic degradation of aromatic compounds with the architecture of the catabolic network and its substrate-specific regulation having been intensively studied by means of differential proteogenomics. The present study aims at unraveling the minimal concentration of an aromatic growth substrate (p-hydroxyacetophenone here) required to initiate gene expression for its degradation pathway and to learn in principle about the lower limit of catabolic responsiveness of an anaerobic degradation specialist.

Optimal bioprocess design through a gene regulatory network - Growth kinetic hybrid model: Towards replacing Monod kinetics

Currently, design and optimisation of biotechnological bioprocesses is performed either through exhaustive experimentation and/or with the use of empirical, unstructured growth kinetics models. Whereas, elaborate systems biology approaches have been recently explored, mixed-substrate utilisation is predominantly ignored despite its significance in enhancing bioprocess performance. Herein, bioprocess optimisation for an industrially-relevant bioremediation process involving a mixture of highly toxic substrates, m-xylene and toluene, was achieved through application of a novel experimental-modelling gene regulatory network - growth kinetic (GRN-GK) hybrid framework. The GRN model described the TOL and ortho-cleavage pathways in Pseudomonas putida mt-2 and captured the transcriptional kinetics expression patterns of the promoters. The GRN model informed the formulation of the growth kinetics model replacing the empirical and unstructured Monod kinetics. The GRN-GK framework's predictive capability and potential as a systematic optimal bioprocess design tool, was demonstrated by effectively predicting bioprocess performance, which was in agreement with experimental values, when compared to four commonly used models that deviated significantly from the experimental values. Significantly, a fed-batch biodegradation process was designed and optimised through the model-based control of TOL Pr promoter expression resulting in 61% and 60% enhanced pollutant removal and biomass formation, respectively, compared to the batch process. This provides strong evidence of model-based bioprocess optimisation at the gene level, rendering the GRN-GK framework as a novel and applicable approach to optimal bioprocess design. Finally, model analysis using global sensitivity analysis (GSA) suggests an alternative, systematic approach for model-driven strain modification for synthetic biology and metabolic engineering applications.

Deconvolution of Gene Expression Noise into Spatial Dynamics of Transcription Factor-Promoter Interplay

Gene expression noise is not only the mere consequence of stochasticity, but also a signal that reflects the upstream physical dynamics of the cognate molecular machinery. Soil bacteria facing recalcitrant pollutants exploit noise of catabolic promoters to deploy beneficial phenotypes such as metabolic bet-hedging and/or division of biochemical labor. Although the role of upstream promoter-regulator interplay in the origin of this noise is little understood, its specifications are probably ciphered in flow cytometry data patterns. We studied Pm promoter activity of the environmental bacterium Pseudomonas putida and its cognate regulator XylS by following expression of Pm-gfp fusions in single cells. Using mathematical modeling and computational simulations, we determined the kinetic properties of the system and used them as a baseline code to interpret promoter activity in terms of upstream regulator dynamics. Transcriptional noise was predicted to depend on the intracellular physical distance between regulator source (where XylS is produced) and the target promoter. Experiments with engineered bacteria in which this distance is minimized or enlarged confirmed the predicted effects of source/target proximity on noise patterns. This approach allowed deconvolution of cytometry data into mechanistic information on gene expression flow. It also provided a basis for selecting programmable noise levels in synthetic regulatory circuits.

The impact of succinate trace on pWW0 and ortho-cleavage pathway transcription in Pseudomonas putida mt-2 during toluene biodegradation

Toluene is a pollutant catabolised through the interconnected pWW0 (TOL) and ortho-cleavage pathways of Pseudomonas putida mt-2, while upon succinate and toluene mixtures introduction in batch cultures grown on M9 medium, succinate was previously reported as non-repressing. The effect of a 40 times lower succinate concentration, as compared to literature values, was explored through systematic real-time qPCR monitoring of transcriptional kinetics of the key TOL Pu, Pm and ortho-cleavage PbenR, PbenA promoters in mixed-substrate experiments. Even succinate trace inhibited transcription leading to bi-modal promoters expression. Potential carbon catabolite repression mechanisms and novel expression patterns of promoters were unfolded. Lag phase was shortened and biomass growth levels increased compared to sole toluene biodegradation suggesting enhanced pollutant removal efficiency. The study stressed the noticeable effect of a preferred compound's left-over on the main route of a bioprocess, revealing the beneficiary supply of low preferred substrates concentrations to design optimal bioremediation strategies.

High-resolution analysis of the m-xylene/toluene biodegradation subtranscriptome of Pseudomonas putida mt-2

Pseudomonas putida mt-2 metabolizes m-xylene and other aromatic compounds through the enzymes encoded by the xyl operons of the TOL plasmid pWW0 along with other chromosomally encoded activities. Tiling arrays of densely overlapping oligonucleotides were designed to cover every gene involved in this process, allowing dissection of operon structures and exposing the interplay of plasmid and chromosomal functions. All xyl sequences were transcribed in response to aromatic substrates and the 3'-termini of both upper and lower mRNA operons extended beyond their coding regions, i.e. the 3'-end of the lower operon mRNA penetrated into the convergent xylS regulatory gene. Furthermore, xylR mRNA for the master m-xylene responsive regulator of the system was decreased by aromatic substrates, while the cognate upper operon mRNA was evenly stable throughout its full length. RNA sequencing confirmed these data at a single nucleotide level and refined the formerly misannotated xylL sequence. The chromosomal ortho route for degradation of benzoate (the ben, cat clusters and some pca genes) was activated by this aromatic, but not by the TOL substrates, toluene or m-xylene. We advocate this scenario as a testbed of natural retroactivity between a pre-existing metabolic network and a new biochemical pathway implanted through gene transfer.

Functional Characterization of the Mannitol Promoter of Pseudomonas fluorescens DSM 50106 and Its Application for a Mannitol-Inducible Expression System for Pseudomonas putida KT2440

A new pBBR1MCS-2-derived vector containing the Pseudomonas fluorescens DSM10506 mannitol promoter PmtlE and mtlR encoding its AraC/XylS type transcriptional activator was constructed and optimized for low basal expression. Mannitol, arabitol, and glucitol-inducible gene expression was demonstrated with Pseudomonas putida and eGFP as reporter gene. The new vector was applied for functional characterization of PmtlE. Identification of the DNA binding site of MtlR was achieved by in vivo eGFP measurement with PmtlE wild type and mutants thereof. Moreover, purified MtlR was applied for detailed in vitro investigations using electrophoretic mobility shift assays and DNaseI footprinting experiments. The obtained data suggest that MtlR binds to PmtlE as a dimer. The proposed DNA binding site of MtlR is AGTGC-N5-AGTAT-N7-AGTGC-N5-AGGAT. The transcription activation mechanism includes two binding sites with different binding affinities, a strong upstream binding site and a weaker downstream binding site. The presence of the weak downstream binding site was shown to be necessary to sustain mannitol-inducibility of PmtlE. Two possible functions of mannitol are discussed; the effector might stabilize binding of the second monomer to the downstream half site or promote transcription activation by inducing a conformational change of the regulator that influences the contact to the RNA polymerase.

Transcription factor-based biosensors enlightened by the analyte

Whole cell biosensors (WCBs) have multiple applications for environmental monitoring, detecting a wide range of pollutants. WCBs depend critically on the sensitivity and specificity of the transcription factor (TF) used to detect the analyte. We describe the mechanism of regulation and the structural and biochemical properties of TF families that are used, or could be used, for the development of environmental WCBs. Focusing on the chemical nature of the analyte, we review TFs that respond to aromatic compounds (XylS-AraC, XylR-NtrC, and LysR), metal ions (MerR, ArsR, DtxR, Fur, and NikR) or antibiotics (TetR and MarR). Analyzing the structural domains involved in DNA recognition, we highlight the similitudes in the DNA binding domains (DBDs) of these TF families. Opposite to DBDs, the wide range of analytes detected by TFs results in a diversity of structures at the effector binding domain. The modular architecture of TFs opens the possibility of engineering TFs with hybrid DNA and effector specificities. Yet, the lack of a crisp correlation between structural domains and specific functions makes this a challenging task.

Mining Environmental Plasmids for Synthetic Biology Parts and Devices

The scientific and technical ambition of contemporary synthetic biology is the engineering of biological objects with a degree of predictability comparable to those made through electric and industrial manufacturing. To this end, biological parts with given specifications are sequence-edited, standardized, and combined into devices, which are assembled into complete systems. This goal, however, faces the customary context dependency of biological ingredients and their amenability to mutation. Biological orthogonality (i.e., the ability to run a function in a fashion minimally influenced by the host) is thus a desirable trait in any deeply engineered construct. Promiscuous conjugative plasmids found in environmental bacteria have evolved precisely to autonomously deploy their encoded activities in a variety of hosts, and thus they become excellent sources of basic building blocks for genetic and metabolic circuits. In this article we review a number of such reusable functions that originated in environmental plasmids and keep their properties and functional parameters in a variety of hosts. The properties encoded in the corresponding sequences include inter alia origins of replication, DNA transfer machineries, toxin-antitoxin systems, antibiotic selection markers, site-specific recombinases, effector-dependent transcriptional regulators (with their cognate promoters), and metabolic genes and operons. Several of these sequences have been standardized as BioBricks and/or as components of the SEVA (Standard European Vector Architecture) collection. Such formatting facilitates their physical composability, which is aimed at designing and deploying complex genetic constructs with new-to-nature properties.

Chemical reactivity drives spatiotemporal organisation of bacterial metabolism

In this review, we examine how bacterial metabolism is shaped by chemical constraints acting on the material and dynamic layout of enzymatic networks and beyond. These are moulded not only for optimisation of given metabolic objectives (e.g. synthesis of a particular amino acid or nucleotide) but also for curbing the detrimental reactivity of chemical intermediates. Besides substrate channelling, toxicity is avoided by barriers to free diffusion (i.e. compartments) that separate otherwise incompatible reactions, along with ways for distinguishing damaging vs. harmless molecules. On the other hand, enzymes age and their operating lifetime must be tuned to upstream and downstream reactions. This time dependence of metabolic pathways creates time-linked information, learning and memory. These features suggest that the physical structure of existing biosystems, from operon assemblies to multicellular development may ultimately stem from the need to restrain chemical damage and limit the waste inherent to basic metabolic functions. This provides a new twist of our comprehension of fundamental biological processes in live systems as well as practical take-home lessons for the forward DNA-based engineering of novel biological objects.