Tunable protein degradation in bacteria

Metabolic network rewiring and temperature-dependent regulation for enhanced 3-dehydroshikimate production in Escherichia coli

The cyclohexane organic acid 3-dehydroshikimate (DHS) has potent antioxidant activity and is widely utilised in chemical and pharmaceutical industries. However, its production requires a long fermentation with a suboptimal yield and low productivity, and a disproportionate growth-to-production ratio impedes the upscaling of DHS synthesis in microbial cell factories. To overcome these limitations, competing and degradation pathways were knocked-out and key enzymes were balanced in an engineered Escherichia coli production strain, resulting in 12.2 g/L DHS. Furthermore, to achieve equilibrium between cell growth and DHS production, a CRISPRi-based temperature-responsive multi-component repressor system was developed to dynamically control the expression of critical genes (pykF and aroE), resulting in a 30-fold increase in DHS titer. After 33 h fermentation in 5 L bioreactor, the DHS titer, productivity and yield reached 94.2 g/L, 2.8 g/L/h and 55 % glucose conversion, respectively. The results provided valuable insight into the production of DHS and its derivatives.

Relieving metabolic burden to improve robustness and bioproduction by industrial microorganisms

Metabolic burden is defined by the influence of genetic manipulation and environmental perturbations on the distribution of cellular resources. The rewiring of microbial metabolism for bio-based chemical production often leads to a metabolic burden, followed by adverse physiological effects, such as impaired cell growth and low product yields. Alleviating the burden imposed by undesirable metabolic changes has become an increasingly attractive approach for constructing robust microbial cell factories. In this review, we provide a brief overview of metabolic burden engineering, focusing specifically on recent developments and strategies for diminishing the burden while improving robustness and yield. A variety of examples are presented to showcase the promise of metabolic burden engineering in facilitating the design and construction of robust microbial cell factories. Finally, challenges and limitations encountered in metabolic burden engineering are discussed.

Protein overabundance is driven by growth robustness

Protein expression levels optimize cell fitness: Too low an expression level of essential proteins will slow growth by compromising essential processes; whereas overexpression slows growth by increasing the metabolic load. This trade-off naïvely predicts that cells maximize their fitness by sufficiency, expressing just enough of each essential protein for function. We test this prediction in the naturally-competent bacterium Acinetobacter baylyi by characterizing the proliferation dynamics of essential-gene knockouts at a single-cell scale (by imaging) as well as at a genome-wide scale (by TFNseq). In these experiments, cells proliferate for multiple generations as target protein levels are diluted from their endogenous levels. This approach facilitates a proteome-scale analysis of protein overabundance. As predicted by the Robustness-Load Trade-Off (RLTO) model, we find that roughly 70% of essential proteins are overabundant and that overabundance increases as the expression level decreases, the signature prediction of the model. These results reveal that robustness plays a fundamental role in determining the expression levels of essential genes and that overabundance is a key mechanism for ensuring robust growth.

Protein overabundance is driven by growth robustness

Protein expression levels optimize cell fitness: Too low an expression level of essential proteins will slow growth by compromising essential processes; whereas overexpression slows growth by increasing the metabolic load. This trade-off naïvely predicts that cells maximize their fitness by sufficiency, expressing just enough of each essential protein for function. We test this prediction in the naturally-competent bacterium Acinetobacter baylyi by characterizing the proliferation dynamics of essential-gene knockouts at a single-cell scale (by imaging) as well as at a genome-wide scale (by TFNseq). In these experiments, cells proliferate for multiple generations as target protein levels are diluted from their endogenous levels. This approach facilitates a proteome-scale analysis of protein overabundance. As predicted by the Robustness-Load Trade-Off (RLTO) model, we find that roughly 70% of essential proteins are overabundant and that overabundance increases as the expression level decreases, the signature prediction of the model. These results reveal that robustness plays a fundamental role in determining the expression levels of essential genes and that overabundance is a key mechanism for ensuring robust growth.

Logical regulation of endogenous gene expression using programmable, multi-input processing CRISPR guide RNAs

The CRISPR-Cas system provides a versatile RNA-guided approach for a broad range of applications. Thanks to advances in RNA synthetic biology, the engineering of guide RNAs (gRNAs) has enabled the conditional control of the CRISPR-Cas system. However, achieving precise regulation of the CRISPR-Cas system for efficient modulation of internal metabolic processes remains challenging. In this work, we developed a robust dCas9 regulator with engineered conditional gRNAs to enable tight control of endogenous genes. Our conditional gRNAs in Escherichia coli can control gene expression upon specific interaction with trigger RNAs with a dynamic range as high as 130-fold, evaluating up to a three-input logic A OR (B AND C). The conditional gRNA-mediated targeting of endogenous metabolic genes, lacZ, malT and poxB, caused differential regulation of growth in Escherichia coli via metabolic flux control. Further, conditional gRNAs could regulate essential cytoskeleton genes, ftsZ and mreB, to control cell filamentation and division. Finally, three types of two-input logic gates could be applied for the conditional control of ftsZ regulation, resulting in morphological changes. The successful operation and application of conditional gRNAs based on programmable RNA interactions suggests that our system could be compatible with other Cas-effectors and implemented in other host organisms.

Integrating bacterial molecular genetics with chemical biology for renewed antibacterial drug discovery

The application of dyes to understanding the aetiology of infection inspired antimicrobial chemotherapy and the first wave of antibacterial drugs. The second wave of antibacterial drug discovery was driven by rapid discovery of natural products, now making up 69% of current antibacterial drugs. But now with the most prevalent natural products already discovered, ∼107 new soil-dwelling bacterial species must be screened to discover one new class of natural product. Therefore, instead of a third wave of antibacterial drug discovery, there is now a discovery bottleneck. Unlike natural products which are curated by billions of years of microbial antagonism, the vast synthetic chemical space still requires artificial curation through the therapeutics science of antibacterial drugs - a systematic understanding of how small molecules interact with bacterial physiology, effect desired phenotypes, and benefit the host. Bacterial molecular genetics can elucidate pathogen biology relevant to therapeutics development, but it can also be applied directly to understanding mechanisms and liabilities of new chemical agents with new mechanisms of action. Therefore, the next phase of antibacterial drug discovery could be enabled by integrating chemical expertise with systematic dissection of bacterial infection biology. Facing the ambitious endeavour to find new molecules from nature or new-to-nature which cure bacterial infections, the capabilities furnished by modern chemical biology and molecular genetics can be applied to prospecting for chemical modulators of new targets which circumvent prevalent resistance mechanisms.

Accelerating Genetic Sensor Development, Scale-up, and Deployment Using Synthetic Biology

Living cells are exquisitely tuned to sense and respond to changes in their environment. Repurposing these systems to create engineered biosensors has seen growing interest in the field of synthetic biology and provides a foundation for many innovative applications spanning environmental monitoring to improved biobased production. In this review, we present a detailed overview of currently available biosensors and the methods that have supported their development, scale-up, and deployment. We focus on genetic sensors in living cells whose outputs affect gene expression. We find that emerging high-throughput experimental assays and evolutionary approaches combined with advanced bioinformatics and machine learning are establishing pipelines to produce genetic sensors for virtually any small molecule, protein, or nucleic acid. However, more complex sensing tasks based on classifying compositions of many stimuli and the reliable deployment of these systems into real-world settings remain challenges. We suggest that recent advances in our ability to precisely modify nonmodel organisms and the integration of proven control engineering principles (e.g., feedback) into the broader design of genetic sensing systems will be necessary to overcome these hurdles and realize the immense potential of the field.

Proteolytic stability and aggregation in a key metabolic enzyme of bacteria

Proteins that are kinetically stable are thought to be less prone to both aggregation and proteolysis. We demonstrate that the classical lac system of Escherichia coli can be leveraged as a model system to study this relation. β-galactosidase (LacZ) plays a critical role in lactose metabolism and is an extremely stable protein that can persist in growing cells for multiple generations after expression has stopped. By attaching degradation tags to the LacZ protein, we find that LacZ can be transiently degraded during lac operon expression but once expression has stopped functional LacZ is protected from degradation. We reversibly destabilize its tetrameric assembly using α-complementation, and show that unassembled LacZ monomers and dimers can either be degraded or lead to formation of aggregates within cells, while the tetrameric state protects against proteolysis and aggregation. We show that the presence of aggregates is associated with cell death, and that these proteotoxic stress phenotypes can be alleviated by attaching an ssrA tag to LacZ monomers which leads to their degradation. We unify our findings using a biophysical model that enables the interplay of protein assembly, degradation, and aggregation to be studied quantitatively in vivo. This work may yield approaches to reversing and preventing protein-misfolding disease states, while elucidating the functions of proteolytic stability in constant and fluctuating environments.

Self-regulated efficient production of L-threonine via an artificial quorum sensing system in engineered Escherichia coli

Imbalance in carbon flux distribution is one of the most important factors affecting the further increase in the yield of high value-added natural products in microbial metabolic engineering. Meanwhile, the most common inducible expression systems are difficult to achieve industrial-scale production due to the addition of high-cost or toxic inducers during the fermentation process. Quorum sensing system, as a typical model for density-dependent induction of gene expression, has been widely applied in synthetic biology. However, there are currently few reports for efficient production of microbial natural products by using quorum sensing system to self-regulate carbon flux distribution. Here, we designed an artificial quorum sensing system to achieve efficient production of L-threonine in engineered Escherichia coli by altering the carbon flux distribution of the central metabolic pathways at specific periods. Under the combination of switch module and production module, the system was applied to divide the microbial fermentation process into two stages including growth and production, and improve the production of L-threonine by self-inducing the expression of pyruvate carboxylase and threonine extracellular transporter protease after a sufficient amount of cell growth. The final strain TWF106/pST1011, pST1042pr could produce 118.2 g/L L-threonine with a yield of 0.57 g/g glucose and a productivity of 2.46 g/(L· h). The establishment of this system has important guidance and application value for the production of other high value-added chemicals in microorganisms by self-regulation.

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.

Genetic Parts and Enabling Tools for Biocircuit Design

Synthetic biology aims to engineer biological systems for customized tasks through the bottom-up assembly of fundamental building blocks, which requires high-quality libraries of reliable, modular, and standardized genetic parts. To establish sets of parts that work well together, synthetic biologists created standardized part libraries in which every component is analyzed in the same metrics and context. Here we present a state-of-the-art review of the currently available part libraries for designing biocircuits and their gene expression regulation paradigms at transcriptional, translational, and post-translational levels in Escherichia coli. We discuss the necessary facets to integrate these parts into complex devices and systems along with the current efforts to catalogue and standardize measurement data. To better display the range of available parts and to facilitate part selection in synthetic biology workflows, we established biopartsDB, a curated database of well-characterized and useful genetic part and device libraries with detailed quantitative data validated by the published literature.

Recent Advances in Microbial Metabolic Engineering for Production of Natural Phenolic Acids

Phenolic acids are important natural bioactive compounds with varied physiological functions. They are extensively used in food, pharmaceutical, cosmetic, and other chemical industries and have attractive market prospects. Compared to plant extraction and chemical synthesis, microbial fermentation for phenolic acid production from renewable carbon sources has significant advantages. This review focuses on the structural information, physiological functions, current applications, and biosynthesis pathways of phenolic acids, especially advances in the development of metabolically engineered microbes for the production of phenolic acids. This review provides useful insights concerning phenolic acid production through metabolic engineering of microbial cell factories.

A system for inducible mitochondria-specific protein degradation in vivo

Targeted protein degradation systems developed for eukaryotes employ cytoplasmic machineries to perform proteolysis. This has prevented mitochondria-specific analysis of proteins that localize to multiple locations, for example, the mitochondria and the nucleus. Here, we present an inducible mitochondria-specific protein degradation system in Saccharomyces cerevisiae based on the Mesoplasma florum Lon (mf-Lon) protease and its corresponding ssrA tag (called PDT). We show that mitochondrially targeted mf-Lon protease efficiently and selectively degrades a PDT-tagged reporter protein localized to the mitochondrial matrix. The degradation can be induced by depleting adenine from the medium, and tuned by altering the promoter strength of the MF-LON gene. We furthermore demonstrate that mf-Lon specifically degrades endogenous, PDT-tagged mitochondrial proteins. Finally, we show that mf-Lon-dependent PDT degradation can also be achieved in human mitochondria. In summary, this system provides an efficient tool to selectively analyze the mitochondrial function of dually localized proteins.

Degron-Controlled Protein Degradation in Escherichia coli: New Approaches and Parameters

Protein degron tags have proven to be uniquely useful for the characterization of gene function. Degrons can mediate quick depletion, usually within minutes, of a protein of interest, allowing researchers to characterize cellular responses to the loss of function. To develop a general-purpose degron tool in Escherichia coli, we sought to build upon a previously characterized system of SspB-dependent inducible protein degradation. For this, we created a family of expression vectors containing a destabilized allele of SspB, capable of a rapid and nearly perfect "off-to-on" induction response. Using this system, we demonstrated excellent control over several DNA metabolism enzymes. However, other substrates did not respond to degron tagging in such an ideal manner, indicating the apparent limitations of SspB-dependent systems. Several degron-tagged proteins were degraded too slowly to be completely depleted during active growth, whereas others appeared to be completely refractory to degron-promoted degradation. Thus, only a minority of our, admittedly biased, selection of degron substrates proved to be amenable to efficient SspB-catalyzed degradation. We also uncovered an apparent stalling and/or disengagement of ClpXP from a degron-tagged allele of beta-galactosidase (beta-gal). While a degron-containing fusion peptide attached to the carboxy-terminus of beta-gal was degraded quantitatively, no reductions in beta-gal activity or concentration were detected, demonstrating an apparently novel mechanism of protease resistance. We conclude that substrate-dependent effects of the SspB system present a continued challenge to the widespread adoption of this degron system. For substrates that prove to be degradable, we provide a series of titratable SspB-expression vehicles.

Mesoplasma florum: a near-minimal model organism for systems and synthetic biology

Mesoplasma florum is an emerging model organism for systems and synthetic biology due to its small genome (∼800 kb) and fast growth rate. While M. florum was isolated and first described almost 40 years ago, many important aspects of its biology have long remained uncharacterized due to technological limitations, the absence of dedicated molecular tools, and since this bacterial species has not been associated with any disease. However, the publication of the first M. florum genome in 2004 paved the way for a new era of research fueled by the rise of systems and synthetic biology. Some of the most important studies included the characterization and heterologous use of M. florum regulatory elements, the development of the first replicable plasmids, comparative genomics and transposon mutagenesis, whole-genome cloning in yeast, genome transplantation, in-depth characterization of the M. florum cell, as well as the development of a high-quality genome-scale metabolic model. The acquired data, knowledge, and tools will greatly facilitate future genome engineering efforts in M. florum, which could next be exploited to rationally design and create synthetic cells to advance fundamental knowledge or for specific applications.

Combinatorial optimization of gene expression through recombinase-mediated promoter and terminator shuffling in yeast

Microbes are increasingly employed as cell factories to produce biomolecules. This often involves the expression of complex heterologous biosynthesis pathways in host strains. Achieving maximal product yields and avoiding build-up of (toxic) intermediates requires balanced expression of every pathway gene. However, despite progress in metabolic modeling, the optimization of gene expression still heavily relies on trial-and-error. Here, we report an approach for in vivo, multiplexed Gene Expression Modification by LoxPsym-Cre Recombination (GEMbLeR). GEMbLeR exploits orthogonal LoxPsym sites to independently shuffle promoter and terminator modules at distinct genomic loci. This approach facilitates creation of large strain libraries, in which expression of every pathway gene ranges over 120-fold and each strain harbors a unique expression profile. When applied to the biosynthetic pathway of astaxanthin, an industrially relevant antioxidant, a single round of GEMbLeR improved pathway flux and doubled production titers. Together, this shows that GEMbLeR allows rapid and efficient gene expression optimization in heterologous biosynthetic pathways, offering possibilities for enhancing the performance of microbial cell factories.

Light-inducible protein degradation in E. coli with the LOVdeg tag

Molecular tools for optogenetic control allow for spatial and temporal regulation of cell behavior. In particular, light-controlled protein degradation is a valuable mechanism of regulation because it can be highly modular, used in tandem with other control mechanisms, and maintain functionality throughout growth phases. Here, we engineered LOVdeg, a tag that can be appended to a protein of interest for inducible degradation in Escherichia coli using blue light. We demonstrate the modularity of LOVdeg by using it to tag a range of proteins, including the LacI repressor, CRISPRa activator, and the AcrB efflux pump. Additionally, we demonstrate the utility of pairing the LOVdeg tag with existing optogenetic tools to enhance performance by developing a combined EL222 and LOVdeg system. Finally, we use the LOVdeg tag in a metabolic engineering application to demonstrate post-translational control of metabolism. Together, our results highlight the modularity and functionality of the LOVdeg tag system and introduce a powerful new tool for bacterial optogenetics.

A tuneable genetic switch for tight control of tac promoters in Escherichia coli boosts expression of synthetic injectisomes

Biosafety of engineered bacteria as living therapeutics requires a tight regulation to control the specific delivery of protein effectors, maintaining minimum leakiness in the uninduced (OFF) state and efficient expression in the induced (ON) state. Here, we report a three repressors (3R) genetic circuit that tightly regulates the expression of multiple tac promoters (Ptac) integrated in the chromosome of E. coli and drives the expression of a complex type III secretion system injectisome for therapeutic protein delivery. The 3R genetic switch is based on the tetracycline repressor (TetR), the non-inducible lambda repressor cI (ind-) and a mutant lac repressor (LacIW220F ) with higher activity. The 3R switch was optimized with different protein translation and degradation signals that control the levels of LacIW220F . We demonstrate the ability of an optimized switch to fully repress the strong leakiness of the Ptac promoters in the OFF state while triggering their efficient activation in the ON state with anhydrotetracycline (aTc), an inducer suitable for in vivo use. The implementation of the optimized 3R switch in the engineered synthetic injector E. coli (SIEC) strain boosts expression of injectisomes upon aTc induction, while maintaining a silent OFF state that preserves normal growth in the absence of the inducer. Since Ptac is a commonly used promoter, the 3R switch may have multiple applications for tight control of protein expression in E. coli. In addition, the modularity of the 3R switch may enable its tuning for the control of Ptac promoters with different inducers.

Customizing cellular signal processing by synthetic multi-level regulatory circuits

As synthetic biology permeates society, the signal processing circuits in engineered living systems must be customized to meet practical demands. Towards this mission, novel regulatory mechanisms and genetic circuits with unprecedented complexity have been implemented over the past decade. These regulatory mechanisms, such as transcription and translation control, could be integrated into hybrid circuits termed "multi-level circuits". The multi-level circuit design will tremendously benefit the current genetic circuit design paradigm, from modifying basic circuit dynamics to facilitating real-world applications, unleashing our capabilities to customize cellular signal processing and address global challenges through synthetic biology.

Degron-controlled protein degradation in Escherichia coli: New Approaches and Parameters

Protein degron tags have proven uniquely useful for characterization of gene function. Degrons mediate quick depletion, usually within minutes, of a protein of interest - allowing researchers to characterize cellular responses to the loss of function. To develop a general purpose degron tool in E. coli, we sought to build upon a previously characterized system of SspB-dependent inducible protein degradation. For this, we created a family of expression vectors containing a destabilized allele of SspB, capable of a rapid and nearly perfect "off-to-on" induction response. Using this system, we demonstrated control over several enzymes of DNA metabolism, but also found with other substates apparent limitations of a SspB-dependent system. Several degron target proteins were degraded too slowly to affect their complete depletion during active growth, whereas others appeared completely refractory to degron-promoted degradation. We demonstrated that a model substrate, beta-galactosidase, was positively recognized as a degron substrate, but failed to be degraded by the ClpXP protease - demonstrating an apparently unknown mechanism of protease resistance. Thus, only a minority of our, admittedly biased, selection of degron substates proved amenable to rapid SspB-catalyzed degradation. We conclude that substrate-dependence of the SspB system remains a critical factor for the success of this degron system. For substrates that prove degradable, we provide a series of titratable SspB-expression vehicles.

Selective RNA Processing and Stabilization are Multi-Layer and Stoichiometric Regulators of Gene Expression in Escherichia coli

Selective RNA processing and stabilization (SRPS) facilitates the differential expression of multiple genes in polycistronic operons. However, how the coordinated actions of SRPS-related enzymes affect stoichiometric regulation remains unclear. In the present study, the first genome-wide targetome analysis is reported of these enzymes in Escherichia coli, at a single-nucleotide resolution. A strictly linear relationship is observed between the RNA pyrophosphohydrolase processing ratio and scores assigned to the first three nucleotides of the primary transcript. Stem-loops associated with PNPase targetomes exhibit a folding free energy that is negatively correlated with the termination ratio of PNPase at the 3' end. More than one-tenth of the RNase E processing sites in the 5'-untranslated regions（UTR） form different stem-loops that affect ribosome-binding and translation efficiency. The effectiveness of the SRPS elements is validated using a dual-fluorescence reporter system. The findings highlight a multi-layer and quantitative regulatory method for optimizing the stoichiometric expression of genes in bacteria and promoting the application of SRPS in synthetic biology.

Light inducible protein degradation in E. coli with the LOVdeg tag

Molecular tools for optogenetic control allow for spatial and temporal regulation of cell behavior. In particular, light controlled protein degradation is a valuable mechanism of regulation because it can be highly modular, used in tandem with other control mechanisms, and maintain functionality throughout growth phases. Here, we engineered LOVdeg, a tag that can be appended to a protein of interest for inducible degradation in Escherichia coli using blue light. We demonstrate the modularity of LOVdeg by using it to tag a range of proteins, including the LacI repressor, CRISPRa activator, and the AcrB efflux pump. Additionally, we demonstrate the utility of pairing the LOVdeg tag with existing optogenetic tools to enhance performance by developing a combined EL222 and LOVdeg system. Finally, we use the LOVdeg tag in a metabolic engineering application to demonstrate post-translational control of metabolism. Together, our results highlight the modularity and functionality of the LOVdeg tag system, and introduce a powerful new tool for bacterial optogenetics.

Dynamic Metabolic Control: From the Perspective of Regulation Logic

Establishing microbial cell factories has become a sustainable and increasingly promising approach for the synthesis of valuable chemicals. However, introducing heterologous pathways into these cell factories can disrupt the endogenous cellular metabolism, leading to suboptimal production performance. To address this challenge, dynamic pathway regulation has been developed and proven effective in improving microbial biosynthesis. In this review, we summarized typical dynamic regulation strategies based on their control logic. The applicable scenarios for each control logic were highlighted and perspectives for future research direction in this area were discussed.

Unbalanced response to growth variations reshapes the cell fate decision landscape

The global regulation of cell growth rate on gene expression perturbs the performance of gene networks, which would impose complex variations on the cell-fate decision landscape. Here we use a simple synthetic circuit of mutual repression that allows a bistable landscape to examine how such global regulation would affect the stability of phenotypic landscape and the accompanying dynamics of cell-fate determination. We show that the landscape experiences a growth-rate-induced bifurcation between monostability and bistability. Theoretical and experimental analyses reveal that this bifurcating deformation of landscape arises from the unbalanced response of gene expression to growth variations. The path of growth transition across the bifurcation would reshape cell-fate decisions. These results demonstrate the importance of growth regulation on cell-fate determination processes, regardless of specific molecular signaling or regulation.

Bye bye, linearity, bye: quantification of the mean for linear CRNs in a random environment

Molecular reactions within a cell are inherently stochastic, and cells often differ in morphological properties or interact with a heterogeneous environment. Consequently, cell populations exhibit heterogeneity both due to these intrinsic and extrinsic causes. Although state-of-the-art studies that focus on dissecting this heterogeneity use single-cell measurements, the bulk data that shows only the mean expression levels is still in routine use. The fingerprint of the heterogeneity is present also in bulk data, despite being hidden from direct measurement. In particular, this heterogeneity can affect the mean expression levels via bimolecular interactions with low-abundant environment species. We make this statement rigorous for the class of linear reaction systems that are embedded in a discrete state Markov environment. The analytic expression that we provide for the stationary mean depends on the reaction rate constants of the linear subsystem, as well as the generator and stationary distribution of the Markov environment. We demonstrate the effect of the environment on the stationary mean. Namely, we show how the heterogeneous case deviates from the quasi-steady state (Q.SS) case when the embedded system is fast compared to the environment.

Highly Efficient Biosynthesis of Protocatechuic Acid via Recombinant Pseudomonas putida KT2440

Owing to their physiological activities, plant-derived phenolic acids, such as protocatechuic acid (PCA), have extensive applications and market prospects. However, traditional production processes present numerous challenges and cannot meet increasing market demands. Hence, we aimed to biosynthesize PCA by constructing an efficient microbial factory via metabolic engineering of Pseudomonas putida KT2440. Glucose metabolism was engineered by deleting the genes for gluconate 2-dehydrogenase to enhance PCA biosynthesis. To increase the biosynthetic metabolic flux, one extra copy of the genes aroG^opt, aroQ, and aroB was inserted into the genome. The resultant strain, KGVA04, produced 7.2 g/L PCA. By inserting the degradation tags GSD and DAS to decrease the amount of shikimate dehydrogenase, PCA biosynthesis was increased to 13.2 g/L in shake-flask fermentation and 38.8 g/L in fed-batch fermentation. To the best of our knowledge, this was the first use of degradation tags to adjust the amount of a key enzyme at the protein level in P. putida KT2440, evidencing the remarkable potential of this method for naturally producing phenolic acids.

Automated design of gene circuits with optimal mushroom-bifurcation behavior

Recent advances in synthetic biology are enabling exciting technologies, including the next generation of biosensors, the rational design of cell memory, modulated synthetic cell differentiation, and generic multifunctional biocircuits. These novel applications require the design of gene circuits leading to sophisticated behaviors and functionalities. At the same time, designs need to be kept minimal to avoid compromising cell viability. Bifurcation theory addresses such challenges by associating circuit dynamical properties with molecular details of its design. Nevertheless, incorporating bifurcation analysis into automated design processes has not been accomplished yet. This work presents an optimization-based method for the automated design of synthetic gene circuits with specified bifurcation diagrams that employ minimal network topologies. Using this approach, we designed circuits exhibiting the mushroom bifurcation, distilled the most robust topologies, and explored its multifunctional behavior. We then outline potential applications in biosensors, memory devices, and synthetic cell differentiation.

Quantification and mitigation of byproduct formation by low-glycerol-producing Saccharomyces cerevisiae strains containing Calvin-cycle enzymes

BACKGROUND

Anaerobic Saccharomyces cerevisiae cultures require glycerol formation to re-oxidize NADH formed in biosynthetic processes. Introduction of the Calvin-cycle enzymes phosphoribulokinase (PRK) and ribulose-1,5-bisphosphate carboxylase/oxygenase (RuBisCO) has been shown to couple re-oxidation of biosynthetic NADH to ethanol production and improve ethanol yield on sugar in fast-growing batch cultures. Since growth rates in industrial ethanol production processes are not constant, performance of engineered strains was studied in slow-growing cultures.

RESULTS

In slow-growing anaerobic chemostat cultures (D = 0.05 h-1), an engineered PRK/RuBisCO strain produced 80-fold more acetaldehyde and 30-fold more acetate than a reference strain. This observation suggested an imbalance between in vivo activities of PRK/RuBisCO and formation of NADH in biosynthesis. Lowering the copy number of the RuBisCO-encoding cbbm expression cassette from 15 to 2 reduced acetaldehyde and acetate production by 67% and 29%, respectively. Additional C-terminal fusion of a 19-amino-acid tag to PRK reduced its protein level by 13-fold while acetaldehyde and acetate production decreased by 94% and 61%, respectively, relative to the 15 × cbbm strain. These modifications did not affect glycerol production at 0.05 h-1 but caused a 4.6 fold higher glycerol production per amount of biomass in fast-growing (0.29 h-1) anaerobic batch cultures than observed for the 15 × cbbm strain. In another strategy, the promoter of ANB1, whose transcript level positively correlated with growth rate, was used to control PRK synthesis in a 2 × cbbm strain. At 0.05 h-1, this strategy reduced acetaldehyde and acetate production by 79% and 40%, respectively, relative to the 15 × cbbm strain, without affecting glycerol production. The maximum growth rate of the resulting strain equalled that of the reference strain, while its glycerol production was 72% lower.

CONCLUSIONS

Acetaldehyde and acetate formation by slow-growing cultures of engineered S. cerevisiae strains carrying a PRK/RuBisCO bypass of yeast glycolysis was attributed to an in vivo overcapacity of PRK and RuBisCO. Reducing the capacity of PRK and/or RuBisCO was shown to mitigate this undesirable byproduct formation. Use of a growth rate-dependent promoter for PRK expression highlighted the potential of modulating gene expression in engineered strains to respond to growth-rate dynamics in industrial batch processes.

A blueprint for a synthetic genetic feedback optimizer

Biomolecular control enables leveraging cells as biomanufacturing factories. Despite recent advancements, we currently lack genetically encoded modules that can be deployed to dynamically fine-tune and optimize cellular performance. Here, we address this shortcoming by presenting the blueprint of a genetic feedback module to optimize a broadly defined performance metric by adjusting the production and decay rate of a (set of) regulator species. We demonstrate that the optimizer can be implemented by combining available synthetic biology parts and components, and that it can be readily integrated with existing pathways and genetically encoded biosensors to ensure its successful deployment in a variety of settings. We further illustrate that the optimizer successfully locates and tracks the optimum in diverse contexts when relying on mass action kinetics-based dynamics and parameter values typical in Escherichia coli.

Rewiring cell-free metabolic flux in E. coli lysates using a block-push-pull approach

Cell-free systems can expedite the design and implementation of biomanufacturing processes by bypassing troublesome requirements associated with the use of live cells. In particular, the lack of survival objectives and the open nature of cell-free reactions afford engineering approaches that allow purposeful direction of metabolic flux. The use of lysate-based systems to produce desired small molecules can result in competitive titers and productivities when compared to their cell-based counterparts. However, pathway crosstalk within endogenous lysate metabolism can compromise conversion yields by diverting carbon flow away from desired products. Here, the 'block-push-pull' concept of conventional cell-based metabolic engineering was adapted to develop a cell-free approach that efficiently directs carbon flow in lysates from glucose and toward endogenous ethanol synthesis. The approach is readily adaptable, is relatively rapid and allows for the manipulation of central metabolism in cell extracts. In implementing this approach, a block strategy is first optimized, enabling selective enzyme removal from the lysate to the point of eliminating by-product-forming activity while channeling flux through the target pathway. This is complemented with cell-free metabolic engineering methods that manipulate the lysate proteome and reaction environment to push through bottlenecks and pull flux toward ethanol. The approach incorporating these block, push and pull strategies maximized the glucose-to-ethanol conversion in an Escherichia coli lysate that initially had low ethanologenic potential. A 10-fold improvement in the percent yield is demonstrated. To our knowledge, this is the first report of successfully rewiring lysate carbon flux without source strain optimization and completely transforming the consumed input substrate to a desired output product in a lysate-based, cell-free system.

Combinatorial metabolic engineering enables high yield production of α-arbutin from sucrose by biocatalysis

α-Arbutin has been widely used as a skin-whitening ingredient. Previously, we successfully produced α-arbutin via whole-cell biocatalysis and found that the conversion rate of sucrose to α-arbutin was low (~45%). To overcome this issue, herein, we knocked out the genes of enzymes related to the sucrose hydrolysis, including sacB, sacC, levB, and sacA. The sucrose consumption was reduced by 17.4% in 24 h, and the sucrose conversion rate was increased to 51.5%. Furthermore, we developed an inducible protein degradation system with Lon protease isolated from Mesoplasma florum (MfLon) and proteolytic tag to control the PfkA activity, so that more fructose-6-phosphate (F6P) can be converted into glucose-1-phosphate (Glc1P) for α-arbutin synthesis, which can reduce the addition of sucrose and increase the sucrose conversion efficiency. Finally, the pathway of F6P to Glc1P was enhanced by integrating another copy of glucose 6-phosphate isomerase (Pgi) and phosphoglucomutase (PgcA); a high α-arbutin titer (~120 g/L) was obtained. The sucrose conversion rate was increased to 60.4% (mol/mol). In this study, the substrate utilization rate was boosted due to the attenuation of its hydrolysis and the assistance of the intracellular enzymes that converted the side product back into the substrate for α-arbutin synthesis. This strategy provides a new idea for the whole-cell biocatalytic synthesis of other products using sucrose as substrate, especially valuable glycosides.Key points The genes of sucrose metabolic pathway were knocked out to reduce the sucrose consumption. The by-product fructose was reused to synthesize α-arbutin. The optimized whole-cell system improved sucrose conversion by 15.3%.

Development of a Bacterial FhuD-Lysozyme-SsrA Mediated Autolytic (FLSA) System for Effective Release of Intracellular Products

Developing effective bacterial autolytic systems for fast release of intracellular bioproducts could simplify purification procedures and help with the high throughput screening of mutant libraries in protein engineering. Here, we developed a fast and tightly regulated E. coli autolytic system, named the FhuD-lysozyme-SsrA mediated autolytic (FLSA) system, by integrating the secretion signal peptide, T7 lysozyme, and E. coli ClpX/P-SsrA protein degradation machinery. To decrease the cytotoxicity of leaky T7 lysozymes, the SsrA tag was fused to the C-terminus of T7 lysozyme to confer a tight regulation of its production. Using sfGFP as a reporter, we demonstrated that anchoring the Sec-Tat dual pathway signal peptide FhuD to the N-terminus of T7 lysozyme-SsrA could give the highest cell lysing efficiency. The optimization of the FLSA system indicated that weak alkaline conditions (pH 8.0) and 0.5% Triton X-100 could further increase the lysing efficiency by about 24%. The FLSA system was validated by efficient production of sfGFP and human growth hormone 1 (hGH1) in a shake flask, with a cell lytic efficiency of approximately 82% and 80%, respectively. Besides, the FLSA system was applied for large-scale fermentation, in which approximately 90% sGFP was released with a cell density OD₆₀₀ of 110. Moreover, the FLSA system was also tested for α-amylase mutant library screening in microplates, and the results showed that intracellular α-amylase can be efficiently released out of cells for activity quantitation. In all, the FLSA system can facilitate the release of intracellular recombinant proteins into the cell culture medium, which has the potential to serve as an integrated system for large-scale production of recombinant targets and high throughput enzyme engineering in synthetic biology.

De novo engineering of a bacterial lifestyle program

Synthetic biology has shown remarkable potential to program living microorganisms for applications. However, a notable discrepancy exists between the current engineering practice-which focuses predominantly on planktonic cells-and the ubiquitous observation of microbes in nature that constantly alternate their lifestyles on environmental variations. Here we present the de novo construction of a synthetic genetic program that regulates bacterial life cycle and enables phase-specific gene expression. The program is orthogonal, harnessing an engineered protein from 45 candidates as the biofilm matrix building block. It is also highly controllable, allowing directed biofilm assembly and decomposition as well as responsive autonomous planktonic-biofilm phase transition. Coupling to synthesis modules, it is further programmable for various functional realizations that conjugate phase-specific biomolecular production with lifestyle alteration. This work establishes a versatile platform for microbial engineering across physiological regimes, thereby shedding light on a promising path for gene circuit applications in complex contexts.

The PilT retraction ATPase promotes both extension and retraction of the MSHA type IVa pilus in Vibrio cholerae

Diverse bacterial species use type IVa pili (T4aP) to interact with their environments. The dynamic extension and retraction of T4aP is critical for their function, but the mechanisms that regulate this dynamic activity remain poorly understood. T4aP are typically extended via the activity of a dedicated extension motor ATPase and retracted via the action of an antagonistic retraction motor ATPase called PilT. These motors are generally functionally independent, and loss of PilT commonly results in T4aP hyperpiliation due to undeterred pilus extension. However, for the mannose-sensitive hemagglutinin (MSHA) T4aP of Vibrio cholerae, the loss of PilT unexpectedly results in a loss of surface piliation. Here, we employ a combination of genetic and cell biological approaches to dissect the underlying mechanism. Our results demonstrate that PilT is necessary for MSHA pilus extension in addition to its well-established role in promoting MSHA pilus retraction. Through a suppressor screen, we also provide genetic evidence that the MshA major pilin impacts pilus extension. Together, these findings contribute to our understanding of the factors that regulate pilus extension and describe a previously uncharacterized function for the PilT motor ATPase.

Efficient In Vitro Full-Sense-Codons Protein Synthesis

Termination of translation is essential but hinders applications of genetic code engineering, e.g., unnatural amino acids incorporation and codon randomization mediated saturation mutagenesis. Here, for the first time, it is demonstrated that E. coli Pth and ArfB together play an efficient translation termination without codon preference in the absence of class-I release factors. By degradation of the targeted protein, both essential and alternative termination types of machinery are completely removed to disable codon-dependent termination in cell extract. Moreover, a total of 153 engineered tRNAs are screened for efficient all stop-codons decoding to construct a codon-dependent termination defect in vitro protein synthesis with all 64 sense-codons, iPSSC. Finally, this full sense genetic code achieves significant improvement in the incorporation of distinct unnatural amino acids at up to 12 positions and synthesis of protein encoding consecutive NNN codons. By decoding all information in nucleotides to amino acids, iPSSC may hold great potential in building artificial protein synthesis beyond the cell.

Overcoming Leak Sensitivity in CRISPRi Circuits Using Antisense RNA Sequestration and Regulatory Feedback

The controlled binding of the catalytically dead CRISPR nuclease (dCas) to DNA can be used to create complex, programmable transcriptional genetic circuits, a fundamental goal of synthetic biology. This approach, called CRISPR interference (CRISPRi), is advantageous over existing methods because the programmable nature of CRISPR proteins in principle enables the simultaneous regulation of many different targets without crosstalk. However, the performance of dCas-based genetic circuits is limited by both the sensitivity to leaky repression within CRISPRi logic gates and retroactive effects due to a shared pool of dCas proteins. By utilizing antisense RNAs (asRNAs) to sequester gRNA transcripts as well as CRISPRi feedback to self-regulate asRNA production, we demonstrate a mechanism that suppresses unwanted repression by CRISPRi and improves logical gene circuit function in Escherichia coli. This improvement is particularly pronounced during stationary expression when CRISPRi circuits do not achieve the expected regulatory dynamics. Furthermore, the use of dual CRISPRi/asRNA inverters restores the logical performance of layered circuits such as a double inverter. By studying circuit induction at the single-cell level in microfluidic channels, we provide insight into the dynamics of antisense sequestration of gRNA and regulatory feedback on dCas-based repression and derepression. These results demonstrate how CRISPRi inverters can be improved for use in more complex genetic circuitry without sacrificing the programmability and orthogonality of dCas proteins.

Mobilome-driven segregation of the resistome in biological wastewater treatment

Biological wastewater treatment plants (BWWTP) are considered to be hotspots for the evolution and subsequent spread of antimicrobial resistance (AMR). Mobile genetic elements (MGEs) promote the mobilization and dissemination of antimicrobial resistance genes (ARGs) and are thereby critical mediators of AMR within the BWWTP microbial community. At present, it is unclear whether specific AMR categories are differentially disseminated via bacteriophages (phages) or plasmids. To understand the segregation of AMR in relation to MGEs, we analyzed meta-omic (metagenomic, metatranscriptomic and metaproteomic) data systematically collected over 1.5 years from a BWWTP. Our results showed a core group of 15 AMR categories which were found across all timepoints. Some of these AMR categories were disseminated exclusively (bacitracin) or primarily (aminoglycoside, MLS and sulfonamide) via plasmids or phages (fosfomycin and peptide), whereas others were disseminated equally by both. Combined and timepoint-specific analyses of gene, transcript and protein abundances further demonstrated that aminoglycoside, bacitracin and sulfonamide resistance genes were expressed more by plasmids, in contrast to fosfomycin and peptide AMR expression by phages, thereby validating our genomic findings. In the analyzed communities, the dominant taxon Candidatus Microthrix parvicella was a major contributor to several AMR categories whereby its plasmids primarily mediated aminoglycoside resistance. Importantly, we also found AMR associated with ESKAPEE pathogens within the BWWTP, and here MGEs also contributed differentially to the dissemination of the corresponding ARGs. Collectively our findings pave the way toward understanding the segmentation of AMR within MGEs, thereby shedding new light on resistome populations and their mediators, essential elements that are of immediate relevance to human health.

A Plasmid-Based Fluorescence Reporter System for Monitoring Oxidative Damage in E. coli

Quantitating intracellular oxidative damage caused by reactive oxygen species (ROS) is of interest in many fields of biological research. The current systems primarily rely on supplemented oxygen-sensitive substrates that penetrate the target cells, and react with ROS to produce signals that can be monitored with spectroscopic or imaging techniques. The objective here was to design a new non-invasive analytical strategy for measuring ROS-induced damage inside living cells by taking advantage of the native redox sensor system of E. coli. The developed plasmid-based sensor relies on an oxygen-sensitive transcriptional repressor IscR that controls the expression of a fluorescent marker in vivo. The system was shown to quantitatively respond to oxidative stress induced by supplemented H₂O₂ and lowered cultivation temperatures. Comparative analysis with fluorescence microscopy further demonstrated that the specificity of the reporter system was equivalent to the commercial chemical probe (CellROX). The strategy introduced here is not dependent on chemical probes, but instead uses a fluorescent expression system to detect enzyme-level oxidative damage in microbial cells. This provides a cheap and simple means for analysing enzyme-level oxidative damage in a biological context in E. coli.

The context matrix: Navigating biological complexity for advanced biodesign

Synthetic biology offers many solutions in healthcare, production, sensing and agriculture. However, the ability to rationally engineer synthetic biosystems with predictable and robust functionality remains a challenge. A major reason is the complex interplay between the synthetic genetic construct, its host, and the environment. Each of these contexts contains a number of input factors which together can create unpredictable behaviours in the engineered biosystem. It has become apparent that for the accurate assessment of these contextual effects a more holistic approach to design and characterisation is required. In this perspective article, we present the context matrix, a conceptual framework to categorise and explore these contexts and their net effect on the designed synthetic biosystem. We propose the use and community-development of the context matrix as an aid for experimental design that simplifies navigation through the complex design space in synthetic biology.

Bacterial degrons in synthetic circuits

Bacterial proteases are a promising post-translational regulation strategy in synthetic circuits because they recognize specific amino acid degradation tags (degrons) that can be fine-tuned to modulate the degradation levels of tagged proteins. For this reason, recent efforts have been made in the search for new degrons. Here we review the up-to-date applications of degradation tags for circuit engineering in bacteria. In particular, we pay special attention to the effects of degradation bottlenecks in synthetic oscillators and introduce mathematical approaches to study queueing that enable the quantitative modelling of proteolytic queues.

An engineered live biotherapeutic for the prevention of antibiotic-induced dysbiosis

Antibiotic-induced alterations in the gut microbiota are implicated in many metabolic and inflammatory diseases, increase the risk of secondary infections and contribute to the emergence of antimicrobial resistance. Here we report the design and in vivo performance of an engineered strain of Lactococcus lactis that altruistically degrades the widely used broad-spectrum antibiotics β-lactams (which disrupt commensal bacteria in the gut) through the secretion and extracellular assembly of a heterodimeric β-lactamase. The engineered β-lactamase-expression system does not confer β-lactam resistance to the producer cell, and is encoded via a genetically unlinked two-gene biosynthesis strategy that is not susceptible to dissemination by horizontal gene transfer. In a mouse model of parenteral ampicillin treatment, oral supplementation with the engineered live biotherapeutic minimized gut dysbiosis without affecting the ampicillin concentration in serum, precluded the enrichment of antimicrobial resistance genes in the gut microbiome and prevented the loss of colonization resistance against Clostridioides difficile. Engineered live biotherapeutics that safely degrade antibiotics in the gut may represent a suitable strategy for the prevention of dysbiosis and its associated pathologies.

De Novo Design of the ArsR Regulated Pars Promoter Enables a Highly Sensitive Whole-Cell Biosensor for Arsenic Contamination

Whole-cell biosensors for arsenic contamination are typically designed based on natural bacterial sensing systems, which are often limited by their poor performance for precisely tuning the genetic response to environmental stimuli. Promoter design remains one of the most important approaches to address such issues. Here, we use the arsenic-responsive ArsR-P_ars regulation system from Escherichia coli MG1655 as the sensing element and coupled gfp or lacZ as the reporter gene to construct the genetic circuit for characterizing the refactored promoters. We first analyzed the ArsR binding site and a library of RNA polymerase binding sites to mine potential promoter sequences. A set of tightly regulated P_ars promoters by ArsR was designed by placing the ArsR binding sites into the promoter's core region, and a novel promoter with maximal repression efficiency and optimal fold change was obtained. The fluorescence sensor P_lacV-P_arsOC2 constructed with the optimized P_arsOC2 promoter showed a fold change of up to 63.80-fold (with green fluorescence visible to the naked eye) at 9.38 ppb arsenic, and the limit of detection was as low as 0.24 ppb. Further, the optimized colorimetric sensor P_lacV-P_arsOC2-lacZ with a linear response between 0 and 5 ppb was used to perform colorimetric reactions in 24-well plates combined with a smartphone application for the quantification of the arsenic level in groundwater. This study offers a new approach to improve the performance of bacterial sensing promoters and will facilitate the on-site application of arsenic whole-cell biosensors.

Gradients in gene essentiality reshape antibacterial research

Essential genes encode the processes that are necessary for life. Until recently, commonly applied binary classifications left no space between essential and non-essential genes. In this review, we frame bacterial gene essentiality in the context of genetic networks. We explore how the quantitative properties of gene essentiality are influenced by the nature of the encoded process, environmental conditions and genetic background, including a strain's distinct evolutionary history. The covered topics have important consequences for antibacterials, which inhibit essential processes. We argue that the quantitative properties of essentiality can thus be used to prioritize antibacterial cellular targets and desired spectrum of activity in specific infection settings. We summarize our points with a case study on the core essential genome of the cystic fibrosis pathobiome and highlight avenues for targeted antibacterial development.

Design and optimization of E. coli artificial genetic circuits for detection of explosive composition 2,4-dinitrotoluene

The detection of mine-based explosives poses a serious threat to the lives of deminers, and carcinogenic residues may cause severe environmental pollution. Whole-cell biosensors that can detect on-site in dangerous or inaccessible environments have great potential to replace conventional methods. Synthetic biology based on engineering modularity serves as a new tool that could be used to engineer microbes to acquire desired functions through artificial design and precise regulation. In this study, we designed artificial genetic circuits in Escherichia coli MG1655 by reconstructing the transcription factor YhaJ-based system to detect explosive composition 2,4-dinitrotoluene (2,4-DNT). These genetic circuits were optimized at the transcriptional, translational, and post-translational levels. The binding affinity of the transcription factor YhaJ with inducer 2,4-DNT metabolites was enhanced via directed evolution, and several activator binding sites were inserted in sensing yqjF promoter (P_yqjF) to further improve the output level. The optimized biosensor P_yqjF×2-TEV-(mYhaJ + GFP)-Ssr had a maximum induction ratio of 189 with green fluorescent signal output, and it could perceive at least 1 μg/mL 2,4-DNT. Its effective and robust performance was verified in different water samples. Our results demonstrate the use of synthetic biology tools to systematically optimize the performance of sensors for 2,4-DNT detection, that lay the foundation for practical applications.

Improving the Robustness of Engineered Bacteria to Nutrient Stress Using Programmed Proteolysis

The use of short peptide tags in synthetic genetic circuits allows for the tuning of gene expression dynamics and release of amino acid resources through targeted protein degradation. Here, we use elements of the Escherichia coli and Mesoplasma florum transfer-mRNA (tmRNA) ribosome rescue systems to compare endogenous and foreign proteolysis systems in E. coli. We characterize the performance and burden of each and show that, while both greatly shorten the half-life of a tagged protein, the endogenous system is approximately 10 times more efficient. On the basis of these results we then demonstrate using mathematical modeling and experiments how proteolysis can improve cellular robustness through targeted degradation of a reporter protein in auxotrophic strains, providing a limited secondary source of essential amino acids that help partially restore growth when nutrients become scarce. These findings provide avenues for controlling the functional lifetime of engineered cells once deployed and increasing their tolerance to fluctuations in nutrient availability.

Biotechnological Innovations and Therapeutic Application of Pediococcus and Lactic Acid Bacteria: The Next-Generation Microorganism

Lactic acid bacteria represent a worthwhile organism within the microbial consortium for the food sector, health, and biotechnological applications. They tend to offer high stability to environmental conditions, with an indicated increase in product yield, alongside their moderate antimicrobial activity. Lack of endotoxins and inclusion bodies, extracellular secretion, and surface display with other unique properties, are all winning attributes of these Gram-positive lactic acid bacteria, of which, Pediococcus is progressively becoming an attractive and promising host, as the next-generation probiotic comparable with other well-known model systems. Here, we presented the biotechnological developments in Pediococcal bacteriocin expression system, contemporary variegated models of Pediococcus and lactic acid bacteria strains as microbial cell factory, most recent applications as possible live delivery vector for use as therapeutics, as well as upsurging challenges and future perspective. With the radical introduction of artificial intelligence and neural network in Synthetic Biology, the microbial usage of lactic acid bacteria as an alternative eco-friendly strain, with safe use properties compared with the already known conventional strains is expected to see an increase in various food and biotechnological applications in years to come as it offers better hope of safety, accuracy, and higher efficiency.

Bifunctional optogenetic switch for improving shikimic acid production in E. coli

BACKGROUND

Biomass formation and product synthesis decoupling have been proven to be promising to increase the titer of desired value add products. Optogenetics provides a potential strategy to develop light-induced circuits that conditionally control metabolic flux redistribution for enhanced microbial production. However, the limited number of light-sensitive proteins available to date hinders the progress of light-controlled tools.

RESULTS

To address these issues, two optogenetic systems (TPRS and TPAS) were constructed by reprogramming the widely used repressor TetR and protease TEVp to expand the current optogenetic toolkit. By merging the two systems, a bifunctional optogenetic switch was constructed to enable orthogonally regulated gene transcription and protein accumulation. Application of this bifunctional switch to decouple biomass formation and shikimic acid biosynthesis allowed 35 g/L of shikimic acid production in a minimal medium from glucose, representing the highest titer reported to date by E. coli without the addition of any chemical inducers and expensive aromatic amino acids. This titer was further boosted to 76 g/L when using rich medium fermentation.

CONCLUSION

The cost effective and light-controlled switch reported here provides important insights into environmentally friendly tools for metabolic pathway regulation and should be applicable to the production of other value-add chemicals.

Transport Across Two Membrane Bilayers in E. coli by Efflux Pumps of Different Dimensions

AcrAB-TolC and CusBAC are two of the most well-studied Resistance-Nodulation-Division (RND) family tripartite efflux pumps in E. coli. AcrAB-TolC is a multidrug efflux system, while CusBAC transports Cu(I), Cu(II) and Ag(I). The RND pump complexes span both the inner membrane (IM) and the outer membrane (OM). The long axis dimension of the fully assembled AcrAB-TolC is ∼3 nm longer than that of CusBAC. To probe if these two efflux systems with different dimensions affect each other when they need to work simultaneously in the same cell, two real-time assays were used to monitor the efflux activities of these two pumps and their impact on each other. The results showed that the presence of AcrAB-TolC substrates accelerated the accumulation of Cu(I) in BW25113 but not in BW25113ΔcusBA or BW25113ΔtolC strains. Similarly, the presence of Ag(I) slowed down the Nile red efflux in the parent strain more significantly than in the CusBA deficient mutant. To further investigate the impact of the OM/IM distance on the function of these tripartite complexes, we experimented with strains lacking the lipoprotein Lpp or containing Lpp mutant of different lengths. Data from efflux/accumulation assays and susceptibility tests revealed that mutation of Lpp resulted in functional deficiency of both AcrAB-TolC and CusBAC. In conclusion, this study demonstrated that when AcrAB-TolC and CusBAC functioned simultaneously, it took the cell a few minutes to adjust. Furthermore, the presence of Lpp of proper length is important to support full efflux activity of transporters spanning both membrane layers in E. coli.

Removing the Bottleneck: Introducing cMatch - A Lightweight Tool for Construct-Matching in Synthetic Biology

We present a software tool, called cMatch, to reconstruct and identify synthetic genetic constructs from their sequences, or a set of sub-sequences—based on two practical pieces of information: their modular structure, and libraries of components. Although developed for combinatorial pathway engineering problems and addressing their quality control (QC) bottleneck, cMatch is not restricted to these applications. QC takes place post assembly, transformation and growth. It has a simple goal, to verify that the genetic material contained in a cell matches what was intended to be built - and when it is not the case, to locate the discrepancies and estimate their severity. In terms of reproducibility/reliability, the QC step is crucial. Failure at this step requires repetition of the construction and/or sequencing steps. When performed manually or semi-manually QC is an extremely time-consuming, error prone process, which scales very poorly with the number of constructs and their complexity. To make QC frictionless and more reliable, cMatch performs an operation we have called “construct-matching” and automates it. Construct-matching is more thorough than simple sequence-matching, as it matches at the functional level-and quantifies the matching at the individual component level and across the whole construct. Two algorithms (called CM_1 and CM_2) are presented. They differ according to the nature of their inputs. CM_1 is the core algorithm for construct-matching and is to be used when input sequences are long enough to cover constructs in their entirety (e.g., obtained with methods such as next generation sequencing). CM_2 is an extension designed to deal with shorter data (e.g., obtained with Sanger sequencing), and that need recombining. Both algorithms are shown to yield accurate construct-matching in a few minutes (even on hardware with limited processing power), together with a set of metrics that can be used to improve the robustness of the decision-making process. To ensure reliability and reproducibility, cMatch builds on the highly validated pairwise-matching Smith-Waterman algorithm. All the tests presented have been conducted on synthetic data for challenging, yet realistic constructs - and on real data gathered during studies on a metabolic engineering example (lycopene production).