Sort-Seq Approach to Engineering a Formaldehyde-Inducible Promoter for Dynamically Regulated Escherichia coli Growth on Methanol

Delaying production with prokaryotic inducible expression systems

BACKGROUND

Engineering bacteria with the purpose of optimizing the production of interesting molecules often leads to a decrease in growth due to metabolic burden or toxicity. By delaying the production in time, these negative effects on the growth can be avoided in a process called a two-stage fermentation.

MAIN TEXT

During this two-stage fermentation process, the production stage is only activated once sufficient cell mass is obtained. Besides the possibility of using external triggers, such as chemical molecules or changing fermentation parameters to induce the production stage, there is a renewed interest towards autoinducible systems. These systems, such as quorum sensing, do not require the extra interference with the fermentation broth to start the induction. In this review, we discuss the different possibilities of both external and autoinduction methods to obtain a two-stage fermentation. Additionally, an overview is given of the tuning methods that can be applied to optimize the induction process. Finally, future challenges and prospects of (auto)inducible expression systems are discussed.

CONCLUSION

There are numerous methods to obtain a two-stage fermentation process each with their own advantages and disadvantages. Even though chemically inducible expression systems are well-established, an increasing interest is going towards autoinducible expression systems, such as quorum sensing. Although these newer techniques cannot rely on the decades of characterization and applications as is the case for chemically inducible promoters, their advantages might lead to a shift in future inducible expression systems.

Engineering a Novel Probiotic Toolkit in Escherichia coli Nissle 1917 for Sensing and Mitigating Gut Inflammatory Diseases

Inflammatory bowel disease (IBD) is characterized by chronic intestinal inflammation with no cure and limited treatment options that often have systemic side effects. In this study, we developed a target-specific system to potentially treat IBD by engineering the probiotic bacterium Escherichia coli Nissle 1917 (EcN). Our modular system comprises three components: a transcription factor-based sensor (NorR) capable of detecting the inflammation biomarker nitric oxide (NO), a type 1 hemolysin secretion system, and a therapeutic cargo consisting of a library of humanized anti-TNFα nanobodies. Despite a reduction in sensitivity, our system demonstrated a concentration-dependent response to NO, successfully secreting functional nanobodies with binding affinities comparable to the commonly used drug Adalimumab, as confirmed by enzyme-linked immunosorbent assay and in vitro assays. This newly validated nanobody library expands EcN therapeutic capabilities. The adopted secretion system, also characterized for the first time in EcN, can be further adapted as a platform for screening and purifying proteins of interest. Additionally, we provided a mathematical framework to assess critical parameters in engineering probiotic systems, including the production and diffusion of relevant molecules, bacterial colonization rates, and particle interactions. This integrated approach expands the synthetic biology toolbox for EcN-based therapies, providing novel parts, circuits, and a model for tunable responses at inflammatory hotspots.

Optimizing enzyme properties to enhance dihydroxyacetone production via methylglyoxal biosensor development

BACKGROUND

Dihydroxyacetone (DHA) stands as a crucial chemical material extensively utilized in the cosmetics industry. DHA production through the dephosphorylation of dihydroxyacetone phosphate, an intermediate product of the glycolysis pathway in Escherichia coli, presents a prospective alternative for industrial production. However, insights into the pivotal enzyme, dihydroxyacetone phosphate dephosphorylase (HdpA), remain limited for informed engineering. Consequently, the development of an efficient tool for high-throughput screening of HdpA hypermutants becomes imperative.

RESULTS

This study introduces a methylglyoxal biosensor, based on the formaldehyde-responding regulator FrmR, for the selection of HdpA. Initial modifications involved the insertion of the FrmR binding site upstream of the -35 region and into the spacer region between the -10 and -35 regions of the constitutive promoter J23110. Although the hybrid promoter retained constitutive expression, expression of FrmR led to complete repression. The addition of 350 μM methylglyoxal promptly alleviated FrmR inhibition, enhancing promoter activity by more than 40-fold. The methylglyoxal biosensor system exhibited a gradual increase in fluorescence intensity with methylglyoxal concentrations ranging from 10 to 500 μM. Notably, the biosensor system responded to methylglyoxal spontaneously converted from added DHA, facilitating the separation of DHA producing and non-producing strains through flow cytometry sorting. Subsequently, the methylglyoxal biosensor was successfully applied to screen a library of HdpA mutants, identifying two strains harboring specific mutants 267G > T and D110G/G151C that showed improved DHA production by 68% and 114%, respectively. Expressing of these two HdpA mutants directly in a DHA-producing strain also increased DHA production from 1.45 to 1.92 and 2.29 g/L, respectively, demonstrating the enhanced enzyme properties of the HdpA mutants.

CONCLUSIONS

The methylglyoxal biosensor offers a novel strategy for constructing genetically encoded biosensors and serves as a robust platform for indirectly determining DHA levels by responding to methylglyoxal. This property enables efficiently screening of HdpA hypermutants to enhance DHA production.

Highly multiplexed design of an allosteric transcription factor to sense novel ligands

Allosteric transcription factors (aTF), widely used as biosensors, have proven challenging to design for detecting novel molecules because mutation of ligand-binding residues often disrupts allostery. We developed Sensor-seq, a high-throughput platform to design and identify aTF biosensors that bind to non-native ligands. We screened a library of 17,737 variants of the aTF TtgR, a regulator of a multidrug exporter, against six non-native ligands of diverse chemical structures - four derivatives of the cancer therapeutic tamoxifen, the antimalarial drug quinine, and the opiate analog naltrexone - as well as two native flavonoid ligands, naringenin and phloretin. Sensor-seq identified novel biosensors for each of these ligands with high dynamic range and diverse specificity profiles. The structure of a naltrexone-bound design showed shape-complementary methionine-aromatic interactions driving ligand specificity. To demonstrate practical utility, we developed cell-free detection systems for naltrexone and quinine. Sensor-seq enables rapid, scalable design of new biosensors, overcoming constraints of natural biosensors.

Toolbox of Characterized Genetic Parts for Staphylococcus aureus

Staphylococcus aureus is an important clinical bacterium prevalent in human-associated microbiomes and the cause of many diseases. However, S. aureus has been intractable to synthetic biology approaches due to limited characterized genetic parts for this nonmodel Gram-positive bacterium. Moreover, genetic manipulation of S. aureus has relied on cumbersome and inefficient cloning strategies. Here, we report the first standardized genetic parts toolbox for S. aureus, which includes characterized promoters, ribosome binding sites, terminators, and plasmid replicons from a variety of bacteria for precise control of gene expression. We established a standard relative expression unit (REU) for S. aureus using a plasmid reference and characterized genetic parts in standardized REUs using S. aureus ATCC 12600. We constructed promoter and terminator part plasmids that are compatible with an efficient Type IIS DNA assembly strategy to effectively build multipart DNA constructs. A library of 24 constitutive promoters was built and characterized in S. aureus, which showed a 380-fold activity range. This promoter library was also assayed in Bacillus subtilis (122-fold activity range) to demonstrate the transferability of the constitutive promoters between these Gram-positive bacteria. By applying an iterative design-build-test-learn cycle, we demonstrated the use of our toolbox for the rational design and engineering of a tetracycline sensor in S. aureus using the PXyl-TetO aTc-inducible promoter that achieved 25.8-fold induction. This toolbox greatly expands the growing number of genetic parts for Gram-positive bacteria and will allow researchers to leverage synthetic biology approaches to study and engineer cellular processes in S. aureus.

Deciphering cell wall sensors enabling the construction of robust P. pastoris for single-cell protein production

Single-cell protein (SCP) production in the methylotrophic yeast Pichia pastoris has the potential to achieve a sustainable protein supply. However, improving the methanol fermentation efficiency and reducing carbon loss has been a long-standing challenge with far-reaching scientific and practical implications. Here, comparative transcriptomics revealed that PAS_0305, a gene directly associated with cell wall thickness under methanol stress, can be used as a target for unlocking cell wall sensors. Intracellular trehalose accumulation confirmed that cell wall sensors were activated after knocking out PAS_0305, which resulted in increased cell wall permeability. Genome-wide signal perturbations were transduced through the HOG module and the CWI pathway, which was confirmed to connected by Pbs2-Mkk. As a consequence of CWI pathway activation, ΔPAS_0305 elicited a rescue response of cell wall remodeling by increasing the β-1,3-glucan content and decreasing the chitin/mannose content. Remarkably, perturbations in global stress signals led to a fine-tuning of the metabolic network of ΔPAS_0305, resulting in a superior phenotype with highest crude protein and methanol conversion rate of 67.21% and 0.46 gDCW/g. Further genome-scale metabolic models were constructed to validate the experimental results, confirming that unlocking cell wall sensors resulted in maximized flux from methanol towards SCP and effectively addressing the issue of carbon loss in methanol fermentation. This work sheds new light on the potential of manipulating cellular signaling pathways to optimize metabolic networks and achieve exceptional phenotypic characteristics, providing new strategies for constructing versatile cell factories in P. pastoris.

Deep flanking sequence engineering for efficient promoter design using DeepSEED

Designing promoters with desirable properties is essential in synthetic biology. Human experts are skilled at identifying strong explicit patterns in small samples, while deep learning models excel at detecting implicit weak patterns in large datasets. Biologists have described the sequence patterns of promoters via transcription factor binding sites (TFBSs). However, the flanking sequences of cis-regulatory elements, have long been overlooked and often arbitrarily decided in promoter design. To address this limitation, we introduce DeepSEED, an AI-aided framework that efficiently designs synthetic promoters by combining expert knowledge with deep learning techniques. DeepSEED has demonstrated success in improving the properties of Escherichia coli constitutive, IPTG-inducible, and mammalian cell doxycycline (Dox)-inducible promoters. Furthermore, our results show that DeepSEED captures the implicit features in flanking sequences, such as k-mer frequencies and DNA shape features, which are crucial for determining promoter properties.

Directed evolution of a neutrophilic and mesophilic methanol dehydrogenase based on high-throughput and accurate measurement of formaldehyde

Methanol is a promising one-carbon feedstock for biomanufacturing, which can be sustainably produced from carbon dioxide and natural gas. However, the efficiency of methanol bioconversion is limited by the poor catalytic properties of nicotinamide adenine dinucleotide (NAD⁺)-dependent methanol dehydrogenase (Mdh) that oxidizes methanol to formaldehyde. Herein, the neutrophilic and mesophilic NAD⁺-dependent Mdh from Bacillus stearothermophilus DSM 2334 (Mdh_Bs) was subjected to directed evolution for enhancing the catalytic activity. The combination of formaldehyde biosensor and Nash assay allowed high-throughput and accurate measurement of formaldehyde and facilitated efficient selection of desired variants. Mdh_Bs variants with up to 6.5-fold higher K_cat/K_M value for methanol were screened from random mutation libraries. The T153 residue that is spatially proximal to the substrate binding pocket has significant influence on enzyme activity. The beneficial T153P mutation changes the interaction network of this residue and breaks the α-helix important for substrate binding into two short α-helices. Reconstructing the interaction network of T153 with surrounding residues may represent a promising strategy to further improve Mdh_Bs, and this study provides an efficient strategy for directed evolution of Mdh.

Methanol-based biomanufacturing of fuels and chemicals using native and synthetic methylotrophs

Methanol has recently gained significant attention as a potential carbon substrate for the production of fuels and chemicals, owing to its high degree of reduction, abundance, and low price. Native methylotrophic yeasts and bacteria have been investigated for the production of fuels and chemicals. Alternatively, synthetic methylotrophic strains are also being developed by reconstructing methanol utilization pathways in model microorganisms, such as Escherichia coli. Owing to the complex metabolic pathways, limited availability of genetic tools, and methanol/formaldehyde toxicity, the high-level production of target products for industrial applications are still under development to satisfy commercial feasibility. This article reviews the production of biofuels and chemicals by native and synthetic methylotrophic microorganisms. It also highlights the advantages and limitations of both types of methylotrophs and provides an overview of ways to improve their efficiency for the production of fuels and chemicals from methanol.

Generation of an Escherichia coli strain growing on methanol via the ribulose monophosphate cycle

Methanol is a liquid with high energy storage capacity that holds promise as an alternative substrate to replace sugars in the biotechnology industry. It can be produced from CO₂ or methane and its use does not compete with food and animal feed production. However, there are currently only limited biotechnological options for the valorization of methanol, which hinders its widespread adoption. Here, we report the conversion of the industrial platform organism Escherichia coli into a synthetic methylotroph that assimilates methanol via the energy efficient ribulose monophosphate cycle. Methylotrophy is achieved after evolution of a methanol-dependent E. coli strain over 250 generations in continuous chemostat culture. We demonstrate growth on methanol and biomass formation exclusively from the one-carbon source by ¹³C isotopic tracer analysis. In line with computational modeling, the methylotrophic E. coli strain optimizes methanol oxidation by upregulation of an improved methanol dehydrogenase, increasing ribulose monophosphate cycle activity, channeling carbon flux through the Entner-Doudoroff pathway and downregulating tricarboxylic acid cycle enzymes. En route towards sustainable bioproduction processes, our work lays the foundation for the efficient utilization of methanol as the dominant carbon and energy resource.

Using one carbon compounds as feedstock is a promising approach in abating climate change. Here, the authors report the conversion of E. coli into a synthetic methylotroph that assimilates methanol via the ribulose monophosphate cycle and a set of distinctive mutations.

From a Hetero- to a Methylotrophic Lifestyle: Flash Back on the Engineering Strategies to Create Synthetic Methanol-User Strains

Engineering microorganisms to grow on alternative feedstocks is crucial not just because of the indisputable biotechnological applications but also to deepen our understanding of microbial metabolism. One-carbon (C1) substrate metabolism has been the focus of extensive research for the prominent role of C1 compounds in establishing a circular bioeconomy. Methanol in particular holds great promise as it can be produced directly from greenhouse gases methane and carbon dioxide using renewable resources. Synthetic methylotrophy, i.e. introducing a non-native methanol utilization pathway into a model host, has therefore been the focus of long-time efforts and is perhaps the pinnacle of metabolic engineering. It entails completely changing a microorganism's lifestyle, from breaking up multi-carbon nutrients for growth to building C-C bonds from a single-carbon molecule to obtain all metabolites necessary to biomass formation as well as energy. The frontiers of synthetic methylotrophy have been pushed further than ever before and in this review, we outline the advances that paved the way for the more recent accomplishments. These include optimizing the host's metabolism, "copy and pasting" naturally existing methylotrophic pathways, "mixing and matching" enzymes to build new pathways, and even creating novel enzymatic functions to obtain strains that are able to grow solely on methanol. Finally, new approaches are contemplated to further advance the field and succeed in obtaining a strain that efficiently grows on methanol and allows C1-based production of added-value compounds.

Approaches to Formaldehyde Measurement: From Liquid Biological Samples to Cells and Organisms

Formaldehyde (FA) is the simplest aldehyde present both in the environment and in living organisms. FA is an extremely reactive compound capable of protein crosslinking and DNA damage. For a long time, FA was considered a "biochemical waste" and a by-product of normal cellular metabolism, but in recent decades the picture has changed. As a result, the need arose for novel instruments and approaches to monitor and measure not only environmental FA in water, cosmetics, and household products, but also in food, beverages and biological samples including cells and even organisms. Despite numerous protocols being developed for in vitro and in cellulo FA assessment, many of them have remained at the "proof-of-concept" stage. We analyze the suitability of different methods developed for non-biological objects, and present an overview of the recently developed approaches, including chemically-synthesized probes and genetically encoded FA-sensors for in cellulo and in vivo FA monitoring. We also discuss the prospects of classical methods such as chromatography and spectrophotometry, and how they have been adapted in response to the demand for precise, selective and highly sensitive evaluation of FA concentration fluctuations in biological samples. The main objectives of this review is to summarize data on the main approaches for FA content measurement in liquid biological samples, pointing out the advantages and disadvantages of each method; to report the progress in development of novel molecules suitable for application in living systems; and, finally, to discuss genetically encoded FA-sensors based on existing natural biological FA-responsive elements.

Elucidation of Sequence-Function Relationships for an Improved Biobutanol In Vivo Biosensor in E. coli

Transcription factor (TF)–promoter pairs have been repurposed from native hosts to provide tools to measure intracellular biochemical production titer and dynamically control gene expression. Most often, native TF–promoter systems require rigorous screening to obtain desirable characteristics optimized for biotechnological applications. High-throughput techniques may provide a rational and less labor-intensive strategy to engineer user-defined TF–promoter pairs using fluorescence-activated cell sorting and deep sequencing methods (sort-seq). Based on the designed promoter library’s distribution characteristics, we elucidate sequence–function interactions between the TF and DNA. In this work, we use the sort-seq method to study the sequence–function relationship of a σ⁵⁴-dependent, butanol-responsive TF–promoter pair, BmoR-P_BMO derived from Thauera butanivorans, at the nucleotide level to improve biosensor characteristics, specifically an improved dynamic range. Activities of promoters from a mutagenized P_BMO library were sorted based on gfp expression and subsequently deep sequenced to correlate site-specific sequences with changes in dynamic range. We identified site-specific mutations that increase the sensor output. Double mutant and a single mutant, CA(129,130)TC and G(205)A, in P_BMO promoter increased dynamic ranges of 4-fold and 1.65-fold compared with the native system, respectively. In addition, sort-seq identified essential sites required for the proper function of the σ⁵⁴-dependent promoter biosensor in the context of the host. This work can enable high-throughput screening methods for strain development.

CRISPR-assisted rational flux-tuning and arrayed CRISPRi screening of an L-proline exporter for L-proline hyperproduction

Development of hyperproducing strains is important for biomanufacturing of biochemicals and biofuels but requires extensive efforts to engineer cellular metabolism and discover functional components. Herein, we optimize and use the CRISPR-assisted editing and CRISPRi screening methods to convert a wild-type Corynebacterium glutamicum to a hyperproducer of L-proline, an amino acid with medicine, feed, and food applications. To facilitate L-proline production, feedback-deregulated variants of key biosynthetic enzyme γ-glutamyl kinase are screened using CRISPR-assisted single-stranded DNA recombineering. To increase the carbon flux towards L-proline biosynthesis, flux-control genes predicted by in silico analysis are fine-tuned using tailored promoter libraries. Finally, an arrayed CRISPRi library targeting all 397 transporters is constructed to discover an L-proline exporter Cgl2622. The final plasmid-, antibiotic-, and inducer-free strain produces L-proline at the level of 142.4 g/L, 2.90 g/L/h, and 0.31 g/g. The CRISPR-assisted strain development strategy can be used for engineering industrial-strength strains for efficient biomanufacturing.

Synergistic Metabolism of Glucose and Formate Increases the Yield of Short-Chain Organic Acids in Escherichia coli

Microbial cell factories using a single carbon source (e.g., sugars) have been used to produce a wide variety of chemicals. However, this process is often accompanied by stoichiometric constraints on carbons and redox cofactors. Here, a synthetic pathway was designed and constructed in Escherichia coli to synergistically use glucose and formate as mixed carbon sources. By optimizing this synthetic pathway via enzyme mining, protein engineering, and bioprocess approaches, the yield of pyruvate from glucose was enhanced to 94% of the theoretical glycolysis yield, reaching 1.88 mol/mol. Finally, the optimized synthetic pathway was integrated with a phosphite reductase-based NADH regeneration system in malate-producing E. coli, resulting in the conversion of glucose into l-malate with a high yield of up to 1.65 mol/mol. This synergistic carbon metabolism strategy can be used to establish carbon- and energy-efficient productive processes.

Unravelling Formaldehyde Metabolism in Bacteria: Road towards Synthetic Methylotrophy

Formaldehyde metabolism is prevalent in all organisms, where the accumulation of formaldehyde can be prevented through the activity of dissimilation pathways. Furthermore, formaldehyde assimilatory pathways play a fundamental role in many methylotrophs, which are microorganisms able to build biomass and obtain energy from single- and multicarbon compounds with no carbon–carbon bonds. Here, we describe how formaldehyde is formed in the environment, the mechanisms of its toxicity to the cells, and the cell’s strategies to circumvent it. While their importance is unquestionable for cell survival in formaldehyde rich environments, we present examples of how the modification of native formaldehyde dissimilation pathways in nonmethylotrophic bacteria can be applied to redirect carbon flux toward heterologous, synthetic formaldehyde assimilation pathways introduced into their metabolism. Attempts to engineer methylotrophy into nonmethylotrophic hosts have gained interest in the past decade, with only limited successes leading to the creation of autonomous synthetic methylotrophy. Here, we discuss how native formaldehyde assimilation pathways can additionally be employed as a premise to achieving synthetic methylotrophy. Lastly, we discuss how emerging knowledge on regulation of formaldehyde metabolism can contribute to creating synthetic regulatory circuits applied in metabolic engineering strategies.

SpeedyGenesXL: an Automated, High-Throughput Platform for the Preparation of Bespoke Ultralarge Variant Libraries for Directed Evolution

Directed evolution of proteins is a highly effective strategy for tailoring biocatalysts to a particular application, and is capable of engineering improvements such as k_cat, thermostability and organic solvent tolerance. It is recognized that large and systematic libraries are required to navigate a protein's vast and rugged sequence landscape effectively, yet their preparation is nontrivial and commercial libraries are extremely costly. To address this, we have developed SpeedyGenesXL, an automated, high-throughput platform for the production of wild-type genes, Boolean OR, combinatorial, or combinatorial-OR-type libraries based on the SpeedyGenes methodology. Together this offers a flexible platform for library synthesis, capable of generating many different bespoke, diverse libraries simultaneously.

Importance of the 5' regulatory region to bacterial synthetic biology applications

The field of synthetic biology is evolving at a fast pace. It is advancing beyond single-gene alterations in single hosts to the logical design of complex circuits and the development of integrated synthetic genomes. Recent breakthroughs in deep learning, which is increasingly used in de novo assembly of DNA components with predictable effects, are also aiding the discipline. Despite advances in computing, the field is still reliant on the availability of pre-characterized DNA parts, whether natural or synthetic, to regulate gene expression in bacteria and make valuable compounds. In this review, we discuss the different bacterial synthetic biology methodologies employed in the creation of 5' regulatory regions - promoters, untranslated regions and 5'-end of coding sequences. We summarize methodologies and discuss their significance for each of the functional DNA components, and highlight the key advances made in bacterial engineering by concentrating on their flaws and strengths. We end the review by outlining the issues that the discipline may face in the near future.

Recent advances toward the bioconversion of methane and methanol in synthetic methylotrophs

Abundant natural gas reserves, along with increased biogas production, have prompted recent interest in harnessing methane as an industrial feedstock for the production of liquid fuels and chemicals. Methane can either be used directly for fermentation or first oxidized to methanol via biological or chemical means. Methanol is advantageous due to its liquid state under normal conditions. Methylotrophy, defined as the ability of microorganisms to utilize reduced one-carbon compounds like methane and methanol as sole carbon and energy sources for growth, is widespread in bacterial communities. However, native methylotrophs lack the extensive and well-characterized synthetic biology toolbox of platform microorganisms like Escherichia coli, which results in slow and inefficient design-build-test cycles. If a heterologous production pathway can be engineered, the slow growth and uptake rates of native methylotrophs generally limit their industrial potential. Therefore, much focus has been placed on engineering synthetic methylotrophs, or non-methylotrophic platform microorganisms, like E. coli, that have been engineered with synthetic methanol utilization pathways. These platform hosts allow for rapid design-build-test cycles and are well-suited for industrial application at the current time. In this review, recent progress made toward synthetic methylotrophy (including methanotrophy) is discussed. Specifically, the importance of amino acid metabolism and alternative one-carbon assimilation pathways are detailed. A recent study that has achieved methane bioconversion to liquid chemicals in a synthetic E. coli methanotroph is also briefly discussed. We also discuss strategies for the way forward in order to realize the industrial potential of synthetic methanotrophs and methylotrophs.

Strategies and challenges with the microbial conversion of methanol to high-value chemicals

As alternatives to traditional fermentation substrates, methanol (CH₃ OH), carbon dioxide (CO₂ ) and methane (CH₄ ) represent promising one-carbon (C1) sources that are readily available at low-cost and share similar metabolic pathway. Of these C1 compounds, methanol is used as a carbon and energy source by native methylotrophs, and can be obtained from CO₂ and CH₄ by chemical catalysis. Therefore, constructing and rewiring methanol utilization pathways may enable the use of one-carbon sources for microbial fermentations. Recent bioengineering efforts have shown that both native and nonnative methylotrophic organisms can be engineered to convert methanol, together with other carbon sources, into biofuels and other commodity chemicals. However, many challenges remain and must be overcome before industrial-scale bioprocessing can be established using these engineered cell refineries. Here, we provide a comprehensive summary and comparison of methanol metabolic pathways from different methylotrophs, followed by a review of recent progress in engineering methanol metabolic pathways in vitro and in vivo to produce chemicals. We discuss the major challenges associated with establishing efficient methanol metabolic pathways in microbial cells, and propose improved designs for future engineering.

Omics-Driven Biotechnology for Industrial Applications

Biomanufacturing is a key component of biotechnology that uses biological systems to produce bioproducts of commercial relevance, which are of great interest to the energy, material, pharmaceutical, food, and agriculture industries. Biotechnology-based approaches, such as synthetic biology and metabolic engineering are heavily reliant on "omics" driven systems biology to characterize and understand metabolic networks. Knowledge gained from systems biology experiments aid the development of synthetic biology tools and the advancement of metabolic engineering studies toward establishing robust industrial biomanufacturing platforms. In this review, we discuss recent advances in "omics" technologies, compare the pros and cons of the different "omics" technologies, and discuss the necessary requirements for carrying out multi-omics experiments. We highlight the influence of "omics" technologies on the production of biofuels and bioproducts by metabolic engineering. Finally, we discuss the application of "omics" technologies to agricultural and food biotechnology, and review the impact of "omics" on current COVID-19 research.

Improving the Methanol Tolerance of an Escherichia coli Methylotroph via Adaptive Laboratory Evolution Enhances Synthetic Methanol Utilization

There is great interest in developing synthetic methylotrophs that harbor methane and methanol utilization pathways in heterologous hosts such as Escherichia coli for industrial bioconversion of one-carbon compounds. While there are recent reports that describe the successful engineering of synthetic methylotrophs, additional efforts are required to achieve the robust methylotrophic phenotypes required for industrial realization. Here, we address an important issue of synthetic methylotrophy in E. coli: methanol toxicity. Both methanol, and its oxidation product, formaldehyde, are cytotoxic to cells. Methanol alters the fluidity and biological properties of cellular membranes while formaldehyde reacts readily with proteins and nucleic acids. Thus, efforts to enhance the methanol tolerance of synthetic methylotrophs are important. Here, adaptive laboratory evolution was performed to improve the methanol tolerance of several E. coli strains, both methylotrophic and non-methylotrophic. Serial batch passaging in rich medium containing toxic methanol concentrations yielded clones exhibiting improved methanol tolerance. In several cases, these evolved clones exhibited a > 50% improvement in growth rate and biomass yield in the presence of high methanol concentrations compared to the respective parental strains. Importantly, one evolved clone exhibited a two to threefold improvement in the methanol utilization phenotype, as determined via ¹³C-labeling, at non-toxic, industrially relevant methanol concentrations compared to the respective parental strain. Whole genome sequencing was performed to identify causative mutations contributing to methanol tolerance. Common mutations were identified in 30S ribosomal subunit proteins, which increased translational accuracy and provided insight into a novel methanol tolerance mechanism. This study addresses an important issue of synthetic methylotrophy in E. coli and provides insight as to how methanol toxicity can be alleviated via enhancing methanol tolerance. Coupled improvement of methanol tolerance and synthetic methanol utilization is an important advancement for the field of synthetic methylotrophy.

Translating New Synthetic Biology Advances for Biosensing Into the Earth and Environmental Sciences

The rapid diversification of synthetic biology tools holds promise in making some classically hard-to-solve environmental problems tractable. Here we review longstanding problems in the Earth and environmental sciences that could be addressed using engineered microbes as micron-scale sensors (biosensors). Biosensors can offer new perspectives on open questions, including understanding microbial behaviors in heterogeneous matrices like soils, sediments, and wastewater systems, tracking cryptic element cycling in the Earth system, and establishing the dynamics of microbe-microbe, microbe-plant, and microbe-material interactions. Before these new tools can reach their potential, however, a suite of biological parts and microbial chassis appropriate for environmental conditions must be developed by the synthetic biology community. This includes diversifying sensing modules to obtain information relevant to environmental questions, creating output signals that allow dynamic reporting from hard-to-image environmental materials, and tuning these sensors so that they reliably function long enough to be useful for environmental studies. Finally, ethical questions related to the use of synthetic biosensors in environmental applications are discussed.

Adaptive laboratory evolution of methylotrophic Escherichia coli enables synthesis of all amino acids from methanol-derived carbon

Recent attempts to create synthetic Escherichia coli methylotrophs identified that de novo biosynthesis of amino acids, in the presence of methanol, presents significant challenges in achieving autonomous methylotrophic growth. Previously engineered methanol-dependent strains required co-utilization of stoichiometric amounts of co-substrates and methanol. As such, these strains could not be evolved to grow on methanol alone. In this work, we have explored an alternative approach to enable biosynthesis of all amino acids from methanol-derived carbon in minimal media without stoichiometric coupling. First, we identified that biosynthesis of threonine was limiting the growth of our methylotrophic E. coli. To address this, we performed adaptive laboratory evolution to generate a strain that grew efficiently in minimal medium with methanol and threonine. Methanol assimilation and growth of the evolved strain were analyzed, and, interestingly, we found that the evolved strain synthesized all amino acids, including threonine, from methanol-derived carbon. The evolved strain was then further engineered through overexpression of an optimized threonine biosynthetic pathway. We show that the resulting methylotrophic E. coli strain has a methanol-dependent growth phenotype with homoserine as co-substrate. In contrast to previous methanol-dependent strains, co-utilization of homoserine is not stoichiometrically linked to methanol assimilation. As such, future engineering of this strain and successive adaptive evolution could enable autonomous growth on methanol as the sole carbon source. KEY POINTS: • Adaptive evolution of E. coli enables biosynthesis of all amino acids from methanol. • Overexpression of threonine biosynthesis pathway improves methanol assimilation. • Methanol-dependent growth is seen in minimal media with homoserine as co-substrate.

Controlled expression of lysis gene E by a mutant of the promoter pL of the thermo-inducible λcI857-pL system

AIMS

To identify a lambda promoter pL mutant that could extend the thermal stability of the thermo-inducible λcI857-pR/pL system and to evaluate the effects of the modified system for the controlled expression of lysis gene E during the production of bacterial ghosts (BGs).

METHODS AND RESULTS

The promoter pL mutant was identified by random mutagenesis and site-directed mutagenesis. The results showed that a T → 35C mutation in the pL promoter was responsible for the phenotype alteration. Under the same induction conditions, the lysis rates of the modified lytic system on Escherichia coli and Salmonella enteritidis were significantly lower than that of the control, while the lysis rates of Escherichia coli with the thermo-inducible lytic system were significantly higher than that of S. enteritidis with the corresponding plasmid (P < 0·05).

CONCLUSIONS

Increasing the heat stability of the thermo-inducible lytic systems decreased lysis efficiency during the production of BGs. There exist differences in the lysis efficiency of thermo-inducible lytic systems between different bacterial strains.

SIGNIFICANCE AND IMPACT OF THE STUDY

These findings enrich current knowledge about modifications to thermo-inducible systems and provide a reference for the application of these modified systems for the production of BGs and controlled gene expression in bacteria.

Methanol-dependent Escherichia coli strains with a complete ribulose monophosphate cycle

Methanol is a biotechnologically promising substitute for food and feed substrates since it can be produced renewably from electricity, water and CO2. Although progress has been made towards establishing Escherichia coli as a platform organism for methanol conversion via the energy efficient ribulose monophosphate (RuMP) cycle, engineering strains that rely solely on methanol as a carbon source remains challenging. Here, we apply flux balance analysis to comprehensively identify methanol-dependent strains with high potential for adaptive laboratory evolution. We further investigate two out of 1200 candidate strains, one with a deletion of fructose-1,6-bisphosphatase (fbp) and another with triosephosphate isomerase (tpiA) deleted. In contrast to previous reported methanol-dependent strains, both feature a complete RuMP cycle and incorporate methanol to a high degree, with up to 31 and 99% fractional incorporation into RuMP cycle metabolites. These strains represent ideal starting points for evolution towards a fully methylotrophic lifestyle.

Using fluorescence flow cytometry data for single-cell gene expression analysis in bacteria

Fluorescence flow cytometry is increasingly being used to quantify single-cell expression distributions in bacteria in high-throughput. However, there has been no systematic investigation into the best practices for quantitative analysis of such data, what systematic biases exist, and what accuracy and sensitivity can be obtained. We investigate these issues by measuring the same E. coli strains carrying fluorescent reporters using both flow cytometry and microscopic setups and systematically comparing the resulting single-cell expression distributions. Using these results, we develop methods for rigorous quantitative inference of single-cell expression distributions from fluorescence flow cytometry data. First, we present a Bayesian mixture model to separate debris from viable cells using all scattering signals. Second, we show that cytometry measurements of fluorescence are substantially affected by autofluorescence and shot noise, which can be mistaken for intrinsic noise in gene expression, and present methods to correct for these using calibration measurements. Finally, we show that because forward- and side-scatter signals scale non-linearly with cell size, and are also affected by a substantial shot noise component that cannot be easily calibrated unless independent measurements of cell size are available, it is not possible to accurately estimate the variability in the sizes of individual cells using flow cytometry measurements alone. To aid other researchers with quantitative analysis of flow cytometry expression data in bacteria, we distribute E-Flow, an open-source R package that implements our methods for filtering debris and for estimating true biological expression means and variances from the fluorescence signal. The package is available at https://github.com/vanNimwegenLab/E-Flow.

Measurements drive progress in directed evolution for precise engineering of biological systems

Precise engineering of biological systems requires quantitative, high-throughput measurements, exemplified by progress in directed evolution. New approaches allow high-throughput measurements of phenotypes and their corresponding genotypes. When integrated into directed evolution, these quantitative approaches enable the precise engineering of biological function. At the same time, the increasingly routine availability of large, high-quality data sets supports the integration of machine learning with directed evolution. Together, these advances herald striking capabilities for engineering biology.

Development of Strong Anaerobic Fluorescent Reporters for Clostridium acetobutylicum and Clostridium ljungdahlii Using HaloTag and SNAP-tag Proteins

One of the biggest limitations in the study and engineering of anaerobic Clostridium organisms is the lack of strong fluorescent reporters capable of strong and real-time fluorescence. Recently, we developed a strong fluorescent reporter system for Clostridium organisms based on the FAST protein. Here, we report the development of two new strong fluorescent reporter systems for Clostridium organisms based on the HaloTag and SNAP-tag proteins, which produce strong fluorescent signals when covalently bound to fluorogenic ligands. These new fluorescent reporters are orthogonal to the FAST ligands and to each other, allowing for simultaneous labeling and visualization. We used HaloTag and SNAP-tag to label the strictly anaerobic organisms Clostridium acetobutylicum and Clostridium ljungdahlii We have also identified a new strong promoter for protein expression in C. acetobutylicum, based on the phosphotransacetylase gene (pta) from C. ljungdahlii Furthermore, the HaloTag and the SNAP-tag, in combination with the previously described FAST system, were successfully used to measure cell populations in bacterial mixed cultures and showed the simultaneous orthogonal labeling of HaloTag and SNAP-tag together with the FAST protein reporter. Finally, we show the expression of recombinant fusion protein of FAST and the ZapA division protein (from C. acetobutylicum) in C. ljungdahlii. The availability of multiple strong fluorescent reporters is a major addition to the genetic toolkit of Clostridium and other anaerobes that will lead to better understanding of these unique organisms.IMPORTANCE Up to this point, assays and methods involving fluorescent reporter proteins were unavailable or limited in Clostridium organisms and other strict anaerobes. Green fluorescent protein (GFP), mCherry, and flavin-binding proteins (and their derivatives) have been used only in a few clostridia with limited success and yielded low fluorescence compared to aerobic microbial systems. Recently, we reported a new strong fluorescent reporter system based on the FAST protein as a first step in expanding the fluorescence-based reporters for Clostridium and other anaerobic microbial platforms. Additional strong orthogonal fluorescent proteins, with distinct emission spectra are needed to allow for (i) multispecies tracking within the growing field of microbial cocultures and microbiomes, (ii) protein localization and tracking in anaerobes, and (iii) identification and development of natural and synthetic promoters, ribosome-binding sites (RBS), and terminators for optimal protein expression in anaerobes. Here, we present two new strong fluorescent reporter systems based on the HaloTag and SNAP-tag proteins.

Regulatory interventions improve the biosynthesis of limiting amino acids from methanol carbon to improve synthetic methylotrophy in Escherichia coli

Synthetic methylotrophy aims to engineer methane and methanol utilization pathways in platform hosts like Escherichia coli for industrial bioprocessing of natural gas and biogas. While recent attempts to engineer synthetic methylotrophs have proved successful, autonomous methylotrophy, that is, the ability to utilize methane or methanol as sole carbon and energy substrates, has not yet been realized. Here, we address an important limitation of autonomous methylotrophy in E. coli: the inability of the organism to synthesize several amino acids when grown on methanol. We targeted global and local amino acid regulatory networks. Those include removal of amino acid allosteric feedback inhibition (argA^H15Y , ilvA^L447F , hisG^E271K , leuA^G462D , proB^D107N , thrA^S345F , trpE^S40F ), knockouts of transcriptional repressors (ihfA, metJ); and overexpression of amino acid biosynthetic operons (hisGDCBHAFI, leuABCD, thrABC, trpEDCBA) and transcriptional regulators (crp, purR). Compared to the parent methylotrophic E. coli strain that was unable to synthesize these amino acids from methanol carbon, these strategies resulted in improved biosynthesis of limiting proteinogenic amino acids (histidine, leucine, lysine, methionine, phenylalanine, threonine, tyrosine) from methanol carbon. In several cases, improved amino acid biosynthesis from methanol carbon led to improvements in methylotrophic growth in methanol minimal medium supplemented with a small amount of yeast extract. This study addresses a key limitation currently preventing autonomous methylotrophy in E. coli and possibly other synthetic methylotrophs and provides insight as to how this limitation can be alleviated via global and local regulatory modifications.

Mixing and matching methylotrophic enzymes to design a novel methanol utilization pathway in E. coli

One-carbon (C1) compounds, such as methanol, have recently gained attention as alternative low-cost and non-food feedstocks for microbial bioprocesses. Considerable research efforts are thus currently focused on the generation of synthetic methylotrophs by transferring methanol assimilation pathways into established bacterial production hosts. In this study, we used an iterative combination of dry and wet approaches to design, implement and optimize this metabolic trait in the most common chassis, E. coli. Through in silico modelling, we designed a new route that "mixed and matched" two methylotrophic enzymes: a bacterial methanol dehydrogenase (Mdh) and a dihydroxyacetone synthase (Das) from yeast. To identify the best combination of enzymes to introduce into E. coli, we built a library of 266 pathway variants containing different combinations of Mdh and Das homologues and screened it using high-throughput ¹³C-labeling experiments. The highest level of incorporation of methanol into central metabolism intermediates (e.g. 22% into the PEP), was obtained using a variant composed of a Mdh from A. gerneri and a codon-optimized version of P. angusta Das. Finally, the activity of this new synthetic pathway was further improved by engineering strategic metabolic targets identified using omics and modelling approaches. The final synthetic strain had 1.5 to 5.9 times higher methanol assimilation in intracellular metabolites and proteinogenic amino acids than the starting strain did. Broadening the repertoire of methanol assimilation pathways is one step further toward synthetic methylotrophy in E. coli.

Development and optimization of N-acetylneuraminic acid biosensors in Bacillus subtilis

Transcriptional factor (TF)-based metabolite-responsive biosensors are important tools for screening engineered enzymes with desired properties and for the dynamic regulation of biosynthetic pathways. However, TF-based biosensor construction is often constrained by undesired effects of TF-binding site sequence insertion on gene expression and unpredictable optimal TF expression levels. In the present study, a stepwise TF-based biosensor construction approach was developed using an N-acetylneuraminic acid (NeuAc) biosensor for Bacillus subtilis, as a case study. Specifically, 12 promoters with various strengths were selected as the first promoter library. Next, binding site sequences for the NanR were inserted into various positions of the selected promoter sequences to develop the second promoter library, resulting in 6 engineered promoters containing TF-binding site sequences (NanO), without major effects on promoter strength. NanR expression cassettes with different expression levels were further integrated to construct the biosensor library, yielding 9 NeuAc biosensors with efficient repression in the absence of NeuAc. Finally, biosensor activation was characterized by testing fold changes in expression levels of the green fluorescent protein reporter in the presence of NeuAc in vivo, which revealed 61-fold activation when NeuAc was present. The NeuAc biosensor developed in this study can be used for screening engineered enzymes for enhanced NeuAc biosynthesis in B. subtilis.

Triggering the stringent response enhances synthetic methanol utilization in Escherichia coli

Synthetic methylotrophy aims to engineer methane and methanol utilization pathways in platform hosts like Escherichia coli for industrial bioprocessing of natural gas and biogas. While recent attempts to engineer synthetic methylotrophs have proved successful, autonomous methylotrophy, i.e. the ability to utilize methane or methanol as sole carbon and energy substrates, has not yet been realized. Here, we address an important limitation of autonomous methylotrophy in E. coli: the inability of the organism to synthesize several amino acids when grown on methanol. By activating the stringent/stress response via ppGpp overproduction, or DksA and RpoS overexpression, we demonstrate improved biosynthesis of proteinogenic amino acids via endogenous upregulation of amino acid synthesis pathway genes. Thus, we were able to achieve biosynthesis of several limiting amino acids from methanol-derived carbon, in contrast to the control methylotrophic E. coli strain. This study addresses a key limitation currently preventing autonomous methylotrophy in E. coli and possibly other synthetic methylotrophs and provides insight as to how this limitation can be alleviated via stringent/stress response activation.

Sensitive and Rapid Phenotyping of Microbes With Soluble Methane Monooxygenase Using a Droplet-Based Assay

Methanotrophs with soluble methane monooxygenase (sMMO) show high potential for various ecological and biotechnological applications. Here, we developed a high throughput method to identify sMMO-producing microbes by integrating droplet microfluidics and a genetic circuit-based biosensor system. sMMO-producers and sensor cells were encapsulated in monodispersed droplets with benzene as the substrate and incubated for 5 h. The sensor cells were analyzed as the reporter for phenol-sensitive transcription activation of fluorescence. Various combinations of methanotrophs and biosensor cells were investigated to optimize the performance of our droplet-integrated transcriptional factor biosensor system. As a result, the conditions to ensure sMMO activity to convert the starting material, benzene, into phenol, were determined. The biosensor signals were sensitive and quantitative under optimal conditions, showing that phenol is metabolically stable within both cell species and accumulates in picoliter-sized droplets, and the biosensor cells are healthy enough to respond quantitatively to the phenol produced. These results show that our system would be useful for rapid evaluation of phenotypes of methanotrophs showing sMMO activity, while minimizing the necessity of time-consuming cultivation and enzyme preparation, which are required for conventional analysis of sMMO activity.

Engineering Escherichia coli for methanol-dependent growth on glucose for metabolite production

Synthetic methylotrophy aims to engineer methane and methanol utilization pathways in platform hosts like Escherichia coli for industrial bioprocessing of natural gas and biogas. While recent attempts to engineer synthetic methanol auxotrophs have proved successful, these studies focused on scarce and expensive co-substrates. Here, we engineered E. coli for methanol-dependent growth on glucose, an abundant and inexpensive co-substrate, via deletion of glucose 6-phosphate isomerase (pgi), phosphogluconate dehydratase (edd), and ribose 5-phosphate isomerases (rpiAB). Since the parental strain did not exhibit methanol-dependent growth on glucose in minimal medium, we first achieved methanol-dependent growth via amino acid supplementation and used this medium to evolve the strain for methanol-dependent growth in glucose minimal medium. The evolved strain exhibited a maximum growth rate of 0.15 h^-1 in glucose minimal medium with methanol, which is comparable to that of other synthetic methanol auxotrophs. Whole genome sequencing and ¹³C-metabolic flux analysis revealed the causative mutations in the evolved strain. A mutation in the phosphotransferase system enzyme I gene (ptsI) resulted in a reduced glucose uptake rate to maintain a one-to-one molar ratio of substrate utilization. Deletion of the e14 prophage DNA region resulted in two non-synonymous mutations in the isocitrate dehydrogenase (icd) gene, which reduced TCA cycle carbon flux to maintain the internal redox state. In high cell density glucose fed-batch fermentation, methanol-dependent acetone production resulted in 22% average carbon labeling of acetone from ¹³C-methanol, which far surpasses that of the previous best (2.4%) found with methylotrophic E. coli Δpgi. This study addresses the need to identify appropriate co-substrates for engineering synthetic methanol auxotrophs and provides a basis for the next steps toward industrial one-carbon bioprocessing.

Figure 1 Theory Meets Figure 2 Experiments in the Study of Gene Expression

It is tempting to believe that we now own the genome. The ability to read and rewrite it at will has ushered in a stunning period in the history of science. Nonetheless, there is an Achilles' heel exposed by all of the genomic data that has accrued: We still do not know how to interpret them. Many genes are subject to sophisticated programs of transcriptional regulation, mediated by DNA sequences that harbor binding sites for transcription factors, which can up- or down-regulate gene expression depending upon environmental conditions. This gives rise to an input-output function describing how the level of expression depends upon the parameters of the regulated gene-for instance, on the number and type of binding sites in its regulatory sequence. In recent years, the ability to make precision measurements of expression, coupled with the ability to make increasingly sophisticated theoretical predictions, has enabled an explicit dialogue between theory and experiment that holds the promise of covering this genomic Achilles' heel. The goal is to reach a predictive understanding of transcriptional regulation that makes it possible to calculate gene expression levels from DNA regulatory sequence. This review focuses on the canonical simple repression motif to ask how well the models that have been used to characterize it actually work. We consider a hierarchy of increasingly sophisticated experiments in which the minimal parameter set learned at one level is applied to make quantitative predictions at the next. We show that these careful quantitative dissections provide a template for a predictive understanding of the many more complex regulatory arrangements found across all domains of life.

Growth of E. coli on formate and methanol via the reductive glycine pathway

Engineering a biotechnological microorganism for growth on one-carbon intermediates, produced from the abiotic activation of CO₂, is a key synthetic biology step towards the valorization of this greenhouse gas to commodity chemicals. Here we redesign the central carbon metabolism of the model bacterium Escherichia coli for growth on one-carbon compounds using the reductive glycine pathway. Sequential genomic introduction of the four metabolic modules of the synthetic pathway resulted in a strain capable of growth on formate and CO₂ with a doubling time of ~70 h and growth yield of ~1.5 g cell dry weight (gCDW) per mol-formate. Short-term evolution decreased doubling time to less than 8 h and improved biomass yield to 2.3 gCDW per mol-formate. Growth on methanol and CO₂ was achieved by further expression of a methanol dehydrogenase. Establishing synthetic formatotrophy and methylotrophy, as demonstrated here, paves the way for sustainable bioproduction rooted in CO₂ and renewable energy.

An autoinducible trp-T7 expression system for production of proteins and biochemicals in Escherichia coli

Inducible expression systems can be applied to control the expression of proteins or biochemical pathways in cell factories. However, several of the established systems require the addition of expensive inducers, making them unfeasible for large‐scale production. Here, we establish a genome integrated trp‐T7 expression system where tryptophan can be used to control the induction of a gene or a metabolic pathway. We show that the initiation of gene expression from low‐ and high‐copy vectors can be tuned by varying the initial concentration of tryptophan or yeast extract, and that expression is tightly regulated and homogenous when compared with the commonly used lac‐T7 system. Finally, we apply the trp‐T7 expression system for the production of l‐serine, where we reach titers of 26 g/L in fed‐batch fermentation.

Synthetic Methylotrophy: A Practical Solution for Methanol-Based Biomanufacturing

The increasing availability and affordability of natural gas has renewed interest in using methanol for bioproduction of useful chemicals. Engineering synthetic methylotrophy based on natural or artificial methanol assimilation pathways and genetically tractable platform microorganisms for methanol-based biomanufacturing is drawing particular attention. Recently, intensive efforts have been devoted to demonstrating the feasibility and improving the efficiency of synthetic methylotrophy. Various fuel, bulk, and fine chemicals have been synthesized using methanol as a feedstock. However, fully synthetic methylotrophs utilizing methanol as the sole carbon source and commercially viable bioproduction from methanol remain to be developed. Here, we review ongoing efforts to identify limiting factors, optimize synthetic methylotrophs, and implement methanol-based biomanufacturing. Future challenges and prospects are also discussed.

Improving synthetic methylotrophy via dynamic formaldehyde regulation of pentose phosphate pathway genes and redox perturbation

Escherichia coli is an ideal choice for constructing synthetic methylotrophs capable of utilizing the non-native substrate methanol as a carbon and energy source. All current E. coli-based synthetic methylotrophs require co-substrates. They display variable levels of methanol-carbon incorporation due to a lack of native regulatory control of biosynthetic pathways, as E. coli does not recognize methanol as a proper substrate despite its ability to catabolize it. Here, using the E. coli formaldehyde-inducible promoter P_frm, we implement dynamic expression control of select pentose-phosphate genes in response to the formaldehyde produced upon methanol oxidation. Genes under P_frm control exhibited 8- to 30-fold transcriptional upregulation during growth on methanol. Formaldehyde-induced episomal expression of the B. methanolicus rpe and tkt genes involved in the regeneration of ribulose 5-phosphate required for formaldehyde fixation led to significantly improved methanol assimilation into intracellular metabolites, including a 2-fold increase of ¹³C-methanol into glutamate. Using a simple strategy for redox perturbation by deleting the E. coli NAD-dependent malate dehydrogenase gene maldh, we demonstrate 5-fold improved biomass formation of cells growing on methanol in the presence of a small concentration of yeast extract. Further improvements in methanol utilization are achieved via adaptive laboratory evolution and heterologous rpe and tkt expression. A short-term in vivo¹³C-methanol labeling assay was used to determine methanol assimilation activity for Δmaldh strains, and demonstrated dramatically higher labeling in intracellular metabolites, including a 6-fold and 1.8-fold increase in glycine labeling for the rpe/tkt and evolved strains, respectively. The combination of formaldehyde-controlled pentose phosphate pathway expression and redox perturbation with the maldh knock-out greatly improved both growth benefit with methanol and methanol carbon incorporation into intracellular metabolites.

De novo design of programmable inducible promoters

Ligand-responsive allosteric transcription factors (aTF) play a vital role in genetic circuits and high-throughput screening because they transduce biochemical signals into gene expression changes. Programmable control of gene expression from aTF-regulated promoter is important because different downstream effector genes function optimally at different expression levels. However, tuning gene expression of native promoters is difficult due to complex layers of homeostatic regulation encoded within them. We engineered synthetic promoters de novo by embedding operator sites with varying affinities and radically reshaped binding preferences within a minimal, constitutive Escherichia coli promoter. Multiplexed cell-based screening of promoters for three TetR-like aTFs generated with this approach gave rich diversity of gene expression levels, dynamic ranges and ligand sensitivities and were 50- to 100-fold more active over their respective native promoters. Machine learning on our dataset revealed that relative position of the core motif and bases flanking the core motif play an important role in modulating induction response. Our generalized approach yields customizable and programmable aTF-regulated promoters for engineering cellular pathways and enables the discovery of new small molecule biosensors.

Synthetic methylotrophy: Strategies to assimilate methanol for growth and chemicals production

Methanol is an attractive and broadly available substrate for large-scale bioproduction of fuels and chemicals. It contains more energy and electrons per carbon than carbohydrates and can be cheaply produced from natural gas. Synthetic methylotrophy refers to the development of non-native methylotrophs such as Escherichia coli and Corynebacterium glutamicum to utilize methanol as a carbon source. Here, we discuss recent advances in engineering these industrial hosts to assimilate methanol for growth and chemicals production through the introduction of the ribulose monophosphate (RuMP) cycle. In addition, we present novel strategies based on flux coupling and adaptive laboratory evolution to engineer new strains that can grow exclusively on methanol.

A Strongly Fluorescing Anaerobic Reporter and Protein-Tagging System for Clostridium Organisms Based on the Fluorescence-Activating and Absorption-Shifting Tag Protein (FAST)

Visualizing protein localization and characterizing gene expression activity in live Clostridium cells is limited for lack of a real-time, highly fluorescent, oxygen-independent reporter system. Enzymatic reporter systems have been used successfully for many years with Clostridium spp.; however, these assays do not allow for real-time analysis of gene expression activity with flow cytometry or for visualizing protein localization through fusion proteins. Commonly used fluorescent reporter proteins require oxygen for chromophore maturation and cannot be used for most strictly anaerobic Clostridium organisms. Here we show that the fluorescence-activating and absorption-shifting tag protein (FAST), when associated with the fluorogenic ligand 4-hydroxy-3-methylbenzylidene-rhodanine (HMBR; now commercially available) and other commercially available ligands, is highly fluorescent in Clostridium acetobutylicum under anaerobic conditions. Using flow cytometry and a fluorescence microplate reader, we demonstrated FAST as a reporter system by employing the promoters of the C. acetobutylicum thiolase (thl), acetoacetate decarboxylase (adc), and phosphotransbutyrylase (ptb) metabolic genes, as well as a mutant P_thl and modified ribosome binding site (RBS) versions of P_adc and P_ptb Flow cytometry-based sorting was efficient and fast in sorting FAST-expressing cells, and positively and negatively sorted cells could be effectively recultured. FAST was also used to tag and examine protein localization of the predicted cell division FtsZ partner protein, ZapA, to visualize the divisome localization in live C. acetobutylicum cells. Our findings suggest that FAST can be used to further investigate Clostridium divisomes and more broadly the localization and expression levels of other proteins in Clostridium organisms, thus enabling cell biology studies with these organisms.IMPORTANCE FAST in association with the fluorogenic ligand HMBR is characterized as a successful, highly fluorescent reporter system in C. acetobutylicum FAST can be used to distinguish between promoters in live cells using flow cytometry or a fluorescence microplate reader and can be used to tag and examine protein localization in live, anaerobically grown cells. Given that FAST is highly fluorescent under anaerobic conditions, it can be used in several applications of this and likely many Clostridium organisms and other strict anaerobes, including studies involving cell sorting, sporulation dynamics, and population characterization in pure as well as mixed cultures, such as those in various native or synthetic microbiomes and syntrophic cultures.