Switching the Ligand Specificity of the Biosensor XylS from meta to para-Toluic Acid through Directed Evolution Exploiting a Dual Selection System

State-of-the-art in engineering small molecule biosensors and their applications in metabolic engineering

Genetically encoded biosensors are crucial for enhancing our understanding of how molecules regulate biological systems. Small molecule biosensors, in particular, help us understand the interaction between chemicals and biological processes. They also accelerate metabolic engineering by increasing screening throughput and eliminating the need for sample preparation through traditional chemical analysis. Additionally, they offer significantly higher spatial and temporal resolution in cellular analyte measurements. In this review, we discuss recent progress in in vivo biosensors and control systems-biosensor-based controllers-for metabolic engineering. We also specifically explore protein-based biosensors that utilize less commonly exploited signaling mechanisms, such as protein stability and induced degradation, compared to more prevalent transcription factor and allosteric regulation mechanism. We propose that these lesser-used mechanisms will be significant for engineering eukaryotic systems and slower-growing prokaryotic systems where protein turnover may facilitate more rapid and reliable measurement and regulation of the current cellular state. Lastly, we emphasize the utilization of cutting-edge and state-of-the-art techniques in the development of protein-based biosensors, achieved through rational design, directed evolution, and collaborative approaches.

Directed Evolution of 4-Hydroxyphenylpyruvate Biosensors Based on a Dual Selection System

Biosensors based on allosteric transcription factors have been widely used in synthetic biology. In this study, we utilized the Acinetobacter ADP1 transcription factor PobR to develop a biosensor activating the PpobA promoter when bound to its natural ligand, 4-hydroxybenzoic acid (4HB). To screen for PobR mutants responsive to 4-hydroxyphenylpyruvate(HPP), we developed a dual selection system in E. coli. The positive selection of this system was used to enrich PobR mutants that identified the required ligands. The following negative selection eliminated or weakened PobR mutants that still responded to 4HB. Directed evolution of the PobR library resulted in a variant where PobRW177R was 5.1 times more reactive to 4-hydroxyphenylpyruvate than PobRWT. Overall, we developed an efficient dual selection system for directed evolution of biosensors.

Advances in ligand-specific biosensing for structurally similar molecules

The specificity of biological systems makes it possible to develop biosensors targeting specific metabolites, toxins, and pollutants in complex medical or environmental samples without interference from structurally similar compounds. For the last two decades, great efforts have been devoted to creating proteins or nucleic acids with novel properties through synthetic biology strategies. Beyond augmenting biocatalytic activity, expanding target substrate scopes, and enhancing enzymes' enantioselectivity and stability, an increasing research area is the enhancement of molecular specificity for genetically encoded biosensors. Here, we summarize recent advances in the development of highly specific biosensor systems and their essential applications. First, we describe the rational design principles required to create libraries containing potential mutants with less promiscuity or better specificity. Next, we review the emerging high-throughput screening techniques to engineer biosensing specificity for the desired target. Finally, we examine the computer-aided evaluation and prediction methods to facilitate the construction of ligand-specific biosensors.

Tunable T7 Promoter Orthogonality on T7RNAP for cis-Aconitate Decarboxylase Evolution via Base Editor and Screening from Itaconic Acid Biosensor

The deaminase-fused T7 RNA polymerase (T7RNAP) presents a promising toolkit for in vivo target-specific enzyme evolution, offering the unique advantage of simultaneous DNA modification and screening. Previous studies have reported the mutation efficiency of base editors relying on different resources. In contrast, the mechanism underlying the T7RNAP/T7 system is well-understood. Therefore, this study aimed to establish a new platform, termed dT7-Muta, by tuning the binding efficiency between T7RNAP and the T7 promoter for gene mutagenesis. The strategy for proof-of-concept involves alterations in the fluorescence distribution through dT7-Muta and screening of the mutants via flow cytometry. The cis-aconitate decarboxylase from Aspergillus terreus (AtCadA) was evolved and screened via an itaconate-induced biosensor as proof-of-function of enzyme evolution. First, the degenerated codons were designed within the binding and initial region of T7 promoters (dT7s), including upstream (U), central (C), and downstream (D) regions. Three strength variants of dT7 promoter from each design, i.e., strong (S), medium (M), and weak (W), were used for evaluation. Mutation using dT7s of varying strength resulted in a broader fluorescence distribution in sfGFP mutants from the promoters CW and DS. On the other hand, broader fluorescence distribution was observed in the AtCadA mutants from the original promoter T7, UW, and DS, with the highest fluorescence and itaconic acid titer at 860 a.u. and 0.51 g/L, respectively. The present platform introduces a novel aspect of the deaminase-based mutagenesis, emphasizing the potential of altering the binding efficiency between T7RNAP and the T7 promoter for further efforts in enzyme evolution.

Engineering the Substrate Specificity of Toluene Degrading Enzyme XylM Using Biosensor XylS and Machine Learning

Enzyme engineering using machine learning has been developed in recent years. However, to obtain a large amount of data on enzyme activities for training data, it is necessary to develop a high-throughput and accurate method for evaluating enzyme activities. Here, we examined whether a biosensor-based enzyme engineering method can be applied to machine learning. As a model experiment, we aimed to modify the substrate specificity of XylM, a rate-determining enzyme in a multistep oxidation reaction catalyzed by XylMABC in Pseudomonas putida. XylMABC naturally converts toluene and xylene to benzoic acid and toluic acid, respectively. We aimed to engineer XylM to improve its conversion efficiency to a non-native substrate, 2,6-xylenol. Wild-type XylMABC slightly converted 2,6-xylenol to 3-methylsalicylic acid, which is the ligand of the transcriptional regulator XylS in P. putida. By locating a fluorescent protein gene under the control of the Pm promoter to which XylS binds, a XylS-producing Escherichia coli strain showed higher fluorescence intensity in a 3-methylsalicylic acid concentration-dependent manner. We evaluated the 3-methylsalicylic acid productivity of XylM variants using the fluorescence intensity of the sensor strain as an indicator. The obtained data provided the training data for machine learning for the directed evolution of XylM. Two cycles of machine learning-assisted directed evolution resulted in the acquisition of XylM-D140E-V144K-F243L-N244S with 15 times higher productivity than wild-type XylM. These results demonstrate that an indirect enzyme activity evaluation method using biosensors is sufficiently quantitative and high-throughput to be used as training data for machine learning. The findings expand the versatility of machine learning in enzyme engineering.

Directed evolution of linker helix as an efficient strategy for engineering LysR-type transcriptional regulators as whole-cell biosensors

Whole-cell biosensors based on transcriptional regulators are powerful tools for rapid measurement, high-throughput screening, dynamic metabolic regulation, etc. To optimize the biosensing performance of transcriptional regulator, its effector-binding domain is commonly engineered. However, this strategy is encumbered by the limitation of diversifying such a large domain and the risk of affecting effector specificity. Molecular dynamics simulation of effector binding of LysG (an LysR-type transcriptional regulator, LTTR) suggests the crucial role of the short linker helix (LH) connecting effector- and DNA-binding domains in protein conformational change. Directed evolution of LH efficiently produced LysG variants with extended operational range and unaltered effector specificity. The whole-cell biosensor based on the best LysG^E58V variant outperformed the wild-type LysG in enzyme high-throughput screening and dynamic regulation of l-lysine biosynthetic pathway. LH mutations are suggested to affect DNA binding and facilitate transcriptional activation upon effector binding. LH engineering was also successfully applied to optimize another LTTR BenM for biosensing. Since LTTRs represent the largest family of prokaryotic transcriptional regulators with highly conserved structures, LH engineering is an efficient and universal strategy for development and optimization of whole-cell biosensors.

Directed evolution of the PobR allosteric transcription factor to generate a biosensor for 4-hydroxymandelic acid

Hydroxy-mandelic acid (HMA) is widely applied in pharmaceuticals, food and cosmetics. In this study, we aimed to develop an allosteric transcription factors (aTFs) based biosensor for HMA. PobR, an aTF for HMA analog 4-hydroxybenzoic acid, was used to alter its selectivity and create novel aTFs responsive to HMA by directed evolution. We established a PobR mutant library with a capacity of 550,000 mutants using error-prone PCR and Megawhop PCR. Through our screening, two mutants were obtained with responsiveness to HMA. Analysis of each missense mutation indicating residues 122-126 were involved in its PobR ligand specificity. These results showed the effectiveness of directed evolution in switching the ligand specificity of a biosensor and improving HMA production.

Engineering Transcription Factor XylS for Sensing Phthalic Acid and Terephthalic Acid: An Application for Enzyme Evolution

Poly(ethylene terephthalate) (PET) and phthalate esters (PAEs) are used extensively as plastics and plasticizers. Enzymatic degradation of PET and PAEs has drawn great attention in recent years; however, evolution of PET- and PAE-degrading enzymes is still a big challenge, partly because of the lack of an effective screening method to detect phthalic acid (PA) and terephthalic acid (TPA), which are the main hydrolysis products of PAEs and PET. Here, by directed evolution of a promiscuous transcription factor, XylS from Pseudomonas putida, we created two novel variants, XylS-K38R-L224Q and XylS-W88C-L224Q, that are able to bind PA and TPA and activate the downstream expression of a fluorescent reporter protein. Based on these elements, whole-cell biosensors were constructed, which enabled the fluorimetric detection of as little as 10 μM PA or TPA. A PAE hydrolase, GoEst15, was preliminarily engineered using this new biosensor, yielding a mutant GoEst15-V3 whose activity toward dibutyl phthalate (DBP) and p-nitrophenyl butyrate was enhanced 2.0- and 2.5-fold, respectively. It was shown that 96.5% DBP (5 mM) was degraded by GoEst15-V3 in 60 min, while the wild-type enzyme degraded only 55% DBP. This study provides an effective screening tool for directed evolution of PAE-/PET-degrading enzymes.

Engineering of the Ligand Specificity of Transcriptional Regulator XylS by Deep Mutational Scanning

Deep mutational scanning is a method for protein engineering. Here, we applied it to alter the ligand specificity of the transcriptional regulator XylS from Pseudomonas putida to recognize p-toluic acid instead of the native ligand m-toluic acid. For this purpose, we used an antibiotic resistance gene-based dual screening system, which was constructed for the directed evolution of XylS toward the above-mentioned ligand specificity. We constructed a xylS mutant library in which each codon for the amino acid residue of the putative ligand-binding domain (residues 1-213, except 7th residue) was randomized to generate all possible single amino acid-substituted XylS variants and introduced it into Escherichia coli harboring the selection plasmid for the screening system. The cells were cultured in the presence of appropriate antibiotics and m-toluic acid or p-toluic acid, and the frequency of each mutation present in the library was examined using a next-generation sequencer before and after cultivation. Heatmaps showing the enrichment score of each XylS variant were obtained. By searching for a p-toluic-acid-specific heatmap pattern, we focused on G71 and H77. Analysis of the ligand specificities of G71- or H77-substituted XylS variants revealed that several G71-substituted XylS variants responded specifically to p-toluic acid. Thus, the 71st residue was found to be an unprecedented residue that is important for switching ligand specificity. Our study demonstrated the usefulness of deep mutational scanning in engineering the ligand specificity of a transcriptional regulator without structural information. We also discussed the advantages and disadvantages of deep mutational scanning compared with directed evolution.

An update of the unceasingly growing and diverse AraC/XylS family of transcriptional activators

Transcriptional factors play an important role in gene regulation in all organisms, especially in Bacteria. Here special emphasis is placed in the AraC/XylS family of transcriptional regulators. This is one of the most abundant as many predicted members have been identified and more members are added because more bacterial genomes are sequenced. Given the way more experimental evidence has mounded in the past decades, we decided to update the information about this captivating family of proteins. Using bioinformatics tools on all the data available for experimentally characterized members of this family, we found that many members that display a similar functional classification can be clustered together and in some cases they have a similar regulatory scheme. A proposal for grouping these proteins is also discussed. Additionally, an analysis of surveyed proteins in bacterial genomes is presented. Altogether, the current review presents a panoramic view into this family and we hope it helps to stimulate future research in the field.

Macrolide Biosensor Optimization through Cellular Substrate Sequestration

Developing and optimizing small-molecule biosensors is a central goal of synthetic biology. Here we incorporate additional cellular components to improve biosensor sensitivity by preventing target molecules from diffusing out of cells. We demonstrate that trapping erythromycin within Escherichia coli through phosphorylation increases the sensitivity of its biosensor (MphR) by approximately 10-fold. When combined with prior engineering efforts, our optimized biosensor can detect erythromycin concentrations as low as 13 nM. We show that this strategy works with a range of macrolide substrates, enabling the potential usage of our optimized system for drug development and metabolic engineering. This strategy can be extended in future studies to improve the sensitivity of other biosensors. Our findings further suggest that many naturally evolved genes involved in resistance to multiple classes of antibiotics may increase intracellular drug concentrations to modulate their own expression, acting as a form of regulatory feedback.