Model-guided dynamic control of essential metabolic nodes boosts acetyl-coenzyme A-dependent bioproduction in rewired Pseudomonas putida

LowTempGAL: a highly responsive low temperature-inducible GAL system in Saccharomyces cerevisiae

Temperature is an important control factor for biologics biomanufacturing in precision fermentation. Here, we explored a highly responsive low temperature-inducible genetic system (LowTempGAL) in the model yeast Saccharomyces cerevisiae. Two temperature biosensors, a heat-inducible degron and a heat-inducible protein aggregation domain, were used to regulate the GAL activator Gal4p, rendering the leaky LowTempGAL systems. Boolean-type induction was achieved by implementing a second-layer control through low-temperature-mediated repression on GAL repressor gene GAL80, but suffered delayed response to low-temperature triggers and a weak response at 30°C. Application potentials were validated for protein and small molecule production. Proteomics analysis suggested that residual Gal80p and Gal4p insufficiency caused suboptimal induction. 'Turbo' mechanisms were engineered through incorporating a basal Gal4p expression and a galactose-independent Gal80p-supressing Gal3p mutant (Gal3Cp). Varying Gal3Cp configurations, we deployed the LowTempGAL systems capable for a rapid stringent high-level induction upon the shift from a high temperature (37-33°C) to a low temperature (≤30°C). Overall, we present a synthetic biology procedure that leverages 'leaky' biosensors to deploy highly responsive Boolean-type genetic circuits. The key lies in optimisation of the intricate layout of the multi-factor system. The LowTempGAL systems may be applicable in non-conventional yeast platforms for precision biomanufacturing.

New strategies to study in depth the metabolic mechanism of astaxanthin biosynthesis in Phaffia rhodozyma

Astaxanthin, a ketone carotenoid known for its high antioxidant activity, holds significant potential for application in nutraceuticals, aquaculture, and cosmetics. The increasing market demand necessitates a higher production of astaxanthin using Phaffia rhodozyma. Despite extensive research efforts focused on optimizing fermentation conditions, employing mutagenesis treatments, and utilizing genetic engineering technologies to enhance astaxanthin yield in P. rhodozyma, progress in this area remains limited. This review provides a comprehensive summary of the current understanding of rough metabolic pathways, regulatory mechanisms, and preliminary strategies for enhancing astaxanthin yield. However, further investigation is required to fully comprehend the intricate and essential metabolic regulation mechanism underlying astaxanthin synthesis. Specifically, the specific functions of key genes, such as crtYB, crtS, and crtI, need to be explored in detail. Additionally, a thorough understanding of the action mechanism of bifunctional enzymes and alternative splicing products is imperative. Lastly, the regulation of metabolic flux must be thoroughly investigated to reveal the complete pathway of astaxanthin synthesis. To obtain an in-depth mechanism and improve the yield of astaxanthin, this review proposes some frontier methods, including: omics, genome editing, protein structure-activity analysis, and synthetic biology. Moreover, it further elucidates the feasibility of new strategies using these advanced methods in various effectively combined ways to resolve these problems mentioned above. This review provides theory and method for studying the metabolic pathway of astaxanthin in P. rhodozyma and the industrial improvement of astaxanthin, and provides new insights into the flexible combined use of multiple modern advanced biotechnologies.

Enzymatic synthesis of mono- and trifluorinated alanine enantiomers expands the scope of fluorine biocatalysis

Fluorinated amino acids serve as an entry point for establishing new-to-Nature chemistries in biological systems, and novel methods are needed for the selective synthesis of these building blocks. In this study, we focused on the enzymatic synthesis of fluorinated alanine enantiomers to expand fluorine biocatalysis. The alanine dehydrogenase from Vibrio proteolyticus and the diaminopimelate dehydrogenase from Symbiobacterium thermophilum were selected for in vitro production of (R)-3-fluoroalanine and (S)-3-fluoroalanine, respectively, using 3-fluoropyruvate as the substrate. Additionally, we discovered that an alanine racemase from Streptomyces lavendulae, originally selected for setting an alternative enzymatic cascade leading to the production of these non-canonical amino acids, had an unprecedented catalytic efficiency in β-elimination of fluorine from the monosubstituted fluoroalanine. The in vitro enzymatic cascade based on the dehydrogenases of V. proteolyticus and S. thermophilum included a cofactor recycling system, whereby a formate dehydrogenase from Pseudomonas sp. 101 (either native or engineered) coupled formate oxidation to NAD(P)H formation. Under these conditions, the reaction yields for (R)-3-fluoroalanine and (S)-3-fluoroalanine reached >85% on the fluorinated substrate and proceeded with complete enantiomeric excess. The selected dehydrogenases also catalyzed the conversion of trifluoropyruvate into trifluorinated alanine as a first-case example of fluorine biocatalysis with amino acids carrying a trifluoromethyl group.

The Impact of Aboveground Epichloë Endophytic Fungi on the Rhizosphere Microbial Functions of the Host Melica transsilvanica

In nature, the symbiotic relationship between plants and microorganisms is crucial for ecosystem balance and plant growth. This study investigates the impact of Epichloë endophytic fungi, which are exclusively present aboveground, on the rhizosphere microbial functions of the host Melica transsilvanica. Using metagenomic methods, we analyzed the differences in microbial functional groups and functional genes in the rhizosphere soil between symbiotic (EI) and non-symbiotic (EF) plants. The results reveal that the presence of Epichloë altered the community structure of carbon and nitrogen cycling-related microbial populations in the host's rhizosphere, significantly increasing the abundance of the genes (porA, porG, IDH1) involved in the rTCA cycle of the carbon fixation pathway, as well as the abundance of nxrAB genes related to nitrification in the nitrogen-cycling pathway. Furthermore, the presence of Epichloë reduces the enrichment of virulence factors in the host rhizosphere microbiome, while significantly increasing the accumulation of resistance genes against heavy metals such as Zn, Sb, and Pb. This study provides new insights into the interactions among endophytic fungi, host plants, and rhizosphere microorganisms, and offers potential applications for utilizing endophytic fungi resources to improve plant growth and soil health.

Synthesis of fluorinated amino acids by low-specificity, promiscuous aldolases coupled to in situ fluorodonor generation

Fluorine (F) is an important element in the synthesis of molecules broadly used in medicine, agriculture, and materials. F addition to organic structures represents a unique strategy for tuning molecular properties, yet this atom is rarely found in Nature and approaches to produce fluorometabolites (such as fluorinated amino acids, key building blocks for synthesis) are relatively scarce. This chapter discusses the use of L-threonine aldolase enzymes (LTAs), a class of enzymes that catalyze reversible aldol addition to the α-carbon of glycine. The C-C bond formation ability of LTAs, together with their known substrate promiscuity, make them ideal for in vitro F biocatalysis. Here, we describe protocols to harness the activity of the low-specificity LTAs isolated from Escherichia coli and Pseudomonas putida on 2-fluoroacetaldehyde to efficiently synthesize 4-fluoro-L-threonine in vitro. This chapter also provides a comprehensive account of experimental protocols to implement these activities in vivo. These methods are illustrative and can be adapted to produce other fluorometabolites of interest.

Genome-scale and pathway engineering for the sustainable aviation fuel precursor isoprenol production in Pseudomonas putida

Sustainable aviation fuel (SAF) will significantly impact global warming in the aviation sector, and important SAF targets are emerging. Isoprenol is a precursor for a promising SAF compound DMCO (1,4-dimethylcyclooctane) and has been produced in several engineered microorganisms. Recently, Pseudomonas putida has gained interest as a future host for isoprenol bioproduction as it can utilize carbon sources from inexpensive plant biomass. Here, we engineer metabolically versatile host P. putida for isoprenol production. We employ two computational modeling approaches (Bilevel optimization and Constrained Minimal Cut Sets) to predict gene knockout targets and optimize the "IPP-bypass" pathway in P. putida to maximize isoprenol production. Altogether, the highest isoprenol production titer from P. putida was achieved at 3.5 g/L under fed-batch conditions. This combination of computational modeling and strain engineering on P. putida for an advanced biofuels production has vital significance in enabling a bioproduction process that can use renewable carbon streams.

KETCHUP: Parameterizing of large-scale kinetic models using multiple datasets with different reference states

Large-scale kinetic models provide the computational means to dynamically link metabolic reaction fluxes to metabolite concentrations and enzyme levels while also conforming to substrate level regulation. However, the development of broadly applicable frameworks for efficiently and robustly parameterizing models remains a challenge. Challenges arise due to both the heterogeneity, paucity, and difficulty in obtaining flux and/or concentration data but also due to the computational difficulties of the underlying parameter identification problem. Both the computational demands for parameterization, degeneracy of obtained parameter solutions and interpretability of results has so far limited widespread adoption of large-scale kinetic models despite their potential. Herein, we introduce the Kinetic Estimation Tool Capturing Heterogeneous Datasets Using Pyomo (KETCHUP), a flexible parameter estimation tool that leverages a primal-dual interior-point algorithm to solve a nonlinear programming (NLP) problem that identifies a set of parameters capable of recapitulating the (non)steady-state fluxes and concentrations in wild-type and perturbed metabolic networks. KETCHUP is benchmarked against previously parameterized large-scale kinetic models demonstrating an at least an order of magnitude faster convergence than the tool K-FIT while at the same time attaining better data fits. This versatile toolbox accepts different kinetic descriptions, metabolic fluxes, enzyme levels and metabolite concentrations, under either steady-state or instationary conditions to enable robust kinetic model construction and parameterization. KETCHUP supports the SBML format and can be accessed at https://github.com/maranasgroup/KETCHUP.

The pAblo·pCasso self-curing vector toolset for unconstrained cytidine and adenine base-editing in Gram-negative bacteria

A synthetic biology toolkit, exploiting clustered regularly interspaced short palindromic repeats (CRISPR) and modified CRISPR-associated protein (Cas) base-editors, was developed for genome engineering in Gram-negative bacteria. Both a cytidine base-editor (CBE) and an adenine base-editor (ABE) have been optimized for precise single-nucleotide modification of plasmid and genome targets. CBE comprises a cytidine deaminase conjugated to a Cas9 nickase from Streptococcus pyogenes (SpnCas9), resulting in C→T (or G→A) substitutions. Conversely, ABE consists of an adenine deaminase fused to SpnCas9 for A→G (or T→C) editing. Several nucleotide substitutions were achieved using these plasmid-borne base-editing systems and a novel protospacer adjacent motif (PAM)-relaxed SpnCas9 (SpRY) variant. Base-editing was validated in Pseudomonas putida and other Gram-negative bacteria by inserting premature STOP codons into target genes, thereby inactivating both fluorescent proteins and metabolic (antibiotic-resistance) functions. The functional knockouts obtained by engineering STOP codons via CBE were reverted to the wild-type genotype using ABE. Additionally, a series of induction-responsive vectors was developed to facilitate the curing of the base-editing platform in a single cultivation step, simplifying complex strain engineering programs without relying on homologous recombination and yielding plasmid-free, modified bacterial cells.

Metabolomics-based development of bioproduction processes toward industrial-scale production

Microbial biomanufacturing offers a promising, environment-friendly platform for next-generation chemical production. However, its limited industrial implementation is attributed to the slow production rates of target compounds and the time-intensive engineering of high-yield strains. This review highlights how metabolomics expedites bioproduction development, as demonstrated through case studies of its integration into microbial strain engineering, culture optimization, and model construction. The Design-Build-Test-Learn (DBTL) cycle serves as a standard workflow for strain engineering. Process development, including the optimization of culture conditions and scale-up, is crucial for industrial production. In silico models facilitate the development of strains and processes. Metabolomics is a powerful driver of the DBTL framework, process development, and model construction.

Genetic and process engineering for polyhydroxyalkanoate production from pre- and post-consumer food waste

Biopolymers produced as microbial carbon storage systems, such as polyhydroxyalkanoates (PHAs), offer potential to be used in place of petrochemically derived plastics. Low-value organic feedstocks, such as food waste, have been explored as a potential substrate for the microbial production of PHAs. In this review, we discuss the biosynthesis, composition and producers of PHAs, with a particular focus on the genetic and process engineering efforts to utilise non-native substrates, derived from food waste from across the entire supply chain, for microbial growth and PHA production. We highlight a series of studies that have achieved impressive advances and discuss the challenges of producing PHAs with consistent composition and properties from mixed and variable food waste and by-products.

Metabolic impact of heterologous protein production in Pseudomonas putida: Insights into carbon and energy flux control

For engineered microorganisms, the production of heterologous proteins that are often useless to host cells represents a burden on resources, which have to be shared with normal cellular processes. Within a certain metabolic leeway, this competitive process has no impact on growth. However, once this leeway, or free capacity, is fully utilized, the extra load becomes a metabolic burden that inhibits cellular processes and triggers a broad cellular response, reducing cell growth and often hindering the production of heterologous proteins. In this study, we sought to characterize the metabolic rearrangements occurring in the central metabolism of Pseudomonas putida at different levels of metabolic load. To this end, we constructed a P. putida KT2440 strain that expressed two genes encoding fluorescent proteins, one in the genome under constitutive expression to monitor the free capacity, and the other on an inducible plasmid to probe heterologous protein production. We found that metabolic fluxes are considerably reshuffled, especially at the level of periplasmic pathways, as soon as the metabolic load exceeds the free capacity. Heterologous protein production leads to the decoupling of anabolism and catabolism, resulting in large excess energy production relative to the requirements of protein biosynthesis. Finally, heterologous protein production was found to exert a stronger control on carbon fluxes than on energy fluxes, indicating that the flexible nature of P. putida's central metabolic network is solicited to sustain energy production.

Improving microbial bioproduction under low-oxygen conditions

Microbial bioconversion provides access to a wide range of sustainably produced chemicals and commodities. However, industrial-scale bioproduction process operations are preferred to be anaerobic due to the cost associated with oxygen transfer. Anaerobic bioconversion generally offers limited substrate utilization profiles, lower product yields, and reduced final product diversity compared with aerobic processes. Bioproduction under conditions of reduced oxygen can overcome the limitations of fully aerobic and anaerobic bioprocesses, but many microbial hosts are not developed for low-oxygen bioproduction. Here, we describe advances in microbial strain engineering involving the use of redox cofactor engineering, genome-scale metabolic modeling, and functional genomics to enable improved bioproduction processes under low oxygen and provide a viable path for scaling these bioproduction systems to industrial scales.

Recursive genome engineering decodes the evolutionary origin of an essential thymidylate kinase activity in Pseudomonas putida KT2440

IMPORTANCE

Investigating fundamental aspects of metabolism is vital for advancing our understanding of the diverse biochemical capabilities and biotechnological applications of bacteria. The origin of the essential thymidylate kinase function in the model bacterium Pseudomonas putida KT2440, seemingly interrupted due to the presence of a large genomic island that disrupts the cognate gene, eluded a satisfactory explanation thus far. This is a first-case example of an essential metabolic function, likely acquired by horizontal gene transfer, which "landed" in a locus encoding the same activity. As such, foreign DNA encoding an essential dNMPK could immediately adjust to the recipient host-instead of long-term accommodation and adaptation. Understanding how these functions evolve is a major biological question, and the work presented here is a decisive step toward this direction. Furthermore, identifying essential and accessory genes facilitates removing those deemed irrelevant in industrial settings-yielding genome-reduced cell factories with enhanced properties and genetic stability.

Omics data for sampling thermodynamically feasible kinetic models

Kinetic models are key to understanding and predicting the dynamic behaviour of metabolic systems. Traditional models require kinetic parameters which are not always available and are often estimated in vitro. Ensemble models overcome this challenge by sampling thermodynamically feasible models around a measured reference point. However, it is unclear if the convenient distributions used to generate the ensemble produce a natural distribution of model parameters and hence if the model predictions are reasonable. In this paper, we produced a detailed kinetic model for the central carbon metabolism of Escherichia coli. The model consists of 82 reactions (including 13 reactions with allosteric regulation) and 79 metabolites. To sample the model, we used metabolomic and fluxomic data from a single steady-state time point for E. coli K-12 MG1655 growing on glucose minimal M9 medium (average sampling time for 1000 models: 11.21 ± 0.14 min). Afterwards, in order to examine whether our sampled models are biologically sound, we calculated Km, Vmax and kcat for the reactions and compared them to previously published values. Finally, we used metabolic control analysis to identify enzymes with high control over the fluxes in the central carbon metabolism. Our analyses demonstrate that our platform samples thermodynamically feasible kinetic models, which are in agreement with previously published experimental results and can be used to investigate metabolic control patterns within cells. This renders it a valuable tool for the study of cellular metabolism and the design of metabolic pathways.

Automating the design-build-test-learn cycle towards next-generation bacterial cell factories

Automation is playing an increasingly significant role in synthetic biology. Groundbreaking technologies, developed over the past 20 years, have enormously accelerated the construction of efficient microbial cell factories. Integrating state-of-the-art tools (e.g. for genome engineering and analytical techniques) into the design-build-test-learn cycle (DBTLc) will shift the metabolic engineering paradigm from an almost artisanal labor towards a fully automated workflow. Here, we provide a perspective on how a fully automated DBTLc could be harnessed to construct the next-generation bacterial cell factories in a fast, high-throughput fashion. Innovative toolsets and approaches that pushed the boundaries in each segment of the cycle are reviewed to this end. We also present the most recent efforts on automation of the DBTLc, which heralds a fully autonomous pipeline for synthetic biology in the near future.

A Pseudomonas taiwanensis malonyl-CoA platform strain for polyketide synthesis

Malonyl-CoA is a central precursor for biosynthesis of a wide range of complex secondary metabolites. The development of platform strains with increased malonyl-CoA supply can contribute to the efficient production of secondary metabolites, especially if such strains exhibit high tolerance towards these chemicals. In this study, Pseudomonas taiwanensis VLB120 was engineered for increased malonyl-CoA availability to produce bacterial and plant-derived polyketides. A multi-target metabolic engineering strategy focusing on decreasing the malonyl-CoA drain and increasing malonyl-CoA precursor availability, led to an increased production of various malonyl-CoA-derived products, including pinosylvin, resveratrol and flaviolin. The production of flaviolin, a molecule deriving from five malonyl-CoA molecules, was doubled compared to the parental strain by this malonyl-CoA increasing strategy. Additionally, the engineered platform strain enabled production of up to 84 mg L-1 resveratrol from supplemented p-coumarate. One key finding of this study was that acetyl-CoA carboxylase overexpression majorly contributed to an increased malonyl-CoA availability for polyketide production in dependence on the used strain-background and whether downstream fatty acid synthesis was impaired, reflecting its complexity in metabolism. Hence, malonyl-CoA availability is primarily determined by competition of the production pathway with downstream fatty acid synthesis, while supply reactions are of secondary importance for compounds that derive directly from malonyl-CoA in Pseudomonas.

Advances in the optimization of central carbon metabolism in metabolic engineering

Central carbon metabolism (CCM), including glycolysis, tricarboxylic acid cycle and the pentose phosphate pathway, is the most fundamental metabolic process in the activities of living organisms that maintains normal cellular growth. CCM has been widely used in microbial metabolic engineering in recent years due to its unique regulatory role in cellular metabolism. Using yeast and Escherichia coli as the representative organisms, we summarized the metabolic engineering strategies on the optimization of CCM in eukaryotic and prokaryotic microbial chassis, such as the introduction of heterologous CCM metabolic pathways and the optimization of key enzymes or regulatory factors, to lay the groundwork for the future use of CCM optimization in metabolic engineering. Furthermore, the bottlenecks in the application of CCM optimization in metabolic engineering and future application prospects are summarized.

Protocol for absolute quantification of proteins in Gram-negative bacteria based on QconCAT-based labeled peptides

Mass-spectrometry-based absolute protein quantification uses labeled quantification concatamer (QconCAT) as internal standards (ISs). To calculate the amount of protein(s), the ion intensity ratio between the analyte and its cognate IS is compared in each biological sample. The present protocol describes a systematic workflow to design, produce, and purify QconCATs and to quantify soluble proteins in Pseudomonas putida KT2440. Our methodology enables the quantification of detectable peptide and serves as a versatile platform to produce ISs for different biological systems.

Recent Advances in CRISPR-Cas Technologies for Synthetic Biology

With developments in synthetic biology, "engineering biology" has emerged through standardization and platformization based on hierarchical, orthogonal, and modularized biological systems. Genome engineering is necessary to manufacture and design synthetic cells with desired functions by using bioparts obtained from sequence databases. Among various tools, the CRISPR-Cas system is modularly composed of guide RNA and Cas nuclease; therefore, it is convenient for editing the genome freely. Recently, various strategies have been developed to accurately edit the genome at a single nucleotide level. Furthermore, CRISPR-Cas technology has been extended to molecular diagnostics for nucleic acids and detection of pathogens, including disease-causing viruses. Moreover, CRISPR technology, which can precisely control the expression of specific genes in cells, is evolving to find the target of metabolic biotechnology. In this review, we summarize the status of various CRISPR technologies that can be applied to synthetic biology and discuss the development of synthetic biology combined with CRISPR technology in microbiology.

Engineering of Pseudomonas putida for accelerated co-utilization of glucose and cellobiose yields aerobic overproduction of pyruvate explained by an upgraded metabolic model

Pseudomonas putida KT2440 is an attractive bacterial host for biotechnological production of valuable chemicals from renewable lignocellulosic feedstocks as it can valorize lignin-derived aromatics or glucose obtainable from cellulose. P. putida EM42, a genome-reduced variant of strain KT2440 endowed with advantageous physiological properties, was recently engineered for growth on cellobiose, a major cellooligosaccharide product of enzymatic cellulose hydrolysis. Co-utilization of cellobiose and glucose was achieved in a mutant lacking periplasmic glucose dehydrogenase Gcd (PP_1444). However, the cause of the co-utilization phenotype remained to be understood and the Δgcd strain had a significant growth defect. In this study, we investigated the basis of the simultaneous uptake of the two sugars and accelerated the growth of P. putida EM42 Δgcd mutant for the bioproduction of valuable compounds from glucose and cellobiose. We show that the gcd deletion lifted the inhibition of the exogenous β-glucosidase BglC from Thermobifida fusca exerted by the intermediates of the periplasmic glucose oxidation pathway. The additional deletion of hexR gene, which encodes a repressor of the upper glycolysis genes, failed to restore rapid growth on glucose. The reduced growth rate of the Δgcd mutant was partially compensated by the implantation of heterologous glucose and cellobiose transporters (Glf from Zymomonas mobilis and LacY from Escherichia coli, respectively). Remarkably, this intervention resulted in the accumulation of pyruvate in aerobic P. putida cultures. We demonstrated that the excess of this key metabolic intermediate can be redirected to the enhanced biosynthesis of ethanol and lactate. The pyruvate overproduction phenotype was then unveiled by an upgraded genome-scale metabolic model constrained with proteomic and kinetic data. The model pointed to the saturation of glucose catabolism enzymes due to unregulated substrate uptake and it predicted improved bioproduction of pyruvate-derived chemicals by the engineered strain. This work sheds light on the co-metabolism of cellulosic sugars in an attractive biotechnological host and introduces a novel strategy for pyruvate overproduction in bacterial cultures under aerobic conditions.

Systems engineering of Escherichia coli for high-level shikimate production

To further increase the production efficiency of microbial shikimate, a valuable compound widely used in the pharmaceutical and chemical industries, ten key target genes contributing to shikimate production were identified by exploiting the enzyme constraint model ec_iML1515, and subsequently used for promoting metabolic flux towards shikimate biosynthesis in the tryptophan-overproducing strain Escherichia coli TRP0. The engineered E. coli SA05 produced 78.4 g/L shikimate via fed-batch fermentation. Deletion of quinate dehydrogenase and introduction of the hydroaromatic equilibration-alleviating shikimate dehydrogenase mutant AroE^T61W/L241I reduced the contents of byproducts quinate (7.5 g/L) and 3-dehydroshikimic acid (21.4 g/L) by 89.1% and 52.1%, respectively. Furthermore, a high concentration shikimate responsive promoter P_rpoS was recruited to dynamically regulate the expression of the tolerance target ProV to enhance shikimate productivity by 23.2% (to 2 g/L/h). Finally, the shikimate titer was increased to 126.4 g/L, with a yield of 0.50 g/g glucose and productivity of 2.63 g/L/h, using a 30-L fermenter and the engineered strain E. coli SA09. This is, to the best of our knowledge, the highest reported shikimate titer and productivity in E. coli.

Synthetic metabolism for in vitro acetone biosynthesis driven by ATP regeneration

In vitro ketone production continues to be a challenge due to the biochemical features of the enzymes involved-even when some of them have been extensively characterized (e.g. thiolase from Clostridium acetobutylicum), the assembly of synthetic enzyme cascades still face significant limitations (including issues with protein aggregation and multimerization). Here, we designed and assembled a self-sustaining enzyme cascade with acetone yields close to the theoretical maximum using acetate as the only carbon input. The efficiency of this system was further boosted by coupling the enzymatic sequence to a two-step ATP-regeneration system that enables continuous, cost-effective acetone biosynthesis. Furthermore, simple methods were implemented for purifying the enzymes necessary for this synthetic metabolism, including a first-case example on the isolation of a heterotetrameric acetate:coenzyme A transferase by affinity chromatography.

Role of the CrcB transporter of Pseudomonas putida in the multi-level stress response elicited by mineral fluoride

The presence of mineral fluoride (F^- ) in the environment has both a geogenic and anthropogenic origin, and the halide has been described to be toxic in virtually all living organisms. While the evidence gathered in different microbial species supports this notion, a systematic exploration of the effects of F^- salts on the metabolism and physiology of environmental bacteria remained underexplored thus far. In this work, we studied and characterized tolerance mechanisms deployed by the model soil bacterium Pseudomonas putida KT2440 against NaF. By adopting systems-level omic approaches, including functional genomics and metabolomics, we gauged the impact of this anion at different regulatory levels under conditions that impair bacterial growth. Several genes involved in halide tolerance were isolated in a genome-wide Tn-Seq screening-among which crcB, encoding an F^- -specific exporter, was shown to play the predominant role in detoxification. High-resolution metabolomics, combined with the assessment of intracellular and extracellular pH values and quantitative physiology experiments, underscored the key nodes in central carbon metabolism affected by the presence of F^- . Taken together, our results indicate that P. putida undergoes a general, multi-level stress response when challenged with NaF that significantly differs from that caused by other saline stressors. While microbial stress responses to saline and oxidative challenges have been extensively studied and described in the literature, very little is known about the impact of fluoride (F^- ) on bacterial physiology and metabolism. This state of affairs contrasts with the fact that F^- is more abundant than other halides in the Earth crust (e.g. in some soils, the F^- concentration can reach up to 1 mg g_soil ^-1 ). Understanding the global effects of NaF treatment on bacterial physiology is not only relevant to unveil distinct mechanisms of detoxification but it could also guide microbial engineering approaches for the target incorporation of fluorine into value-added organofluorine molecules. In this regard, the soil bacterium P. putida constitutes an ideal model to explore such scenarios, since this species is particularly known for its high level of stress resistance against a variety of physicochemical perturbations.

GRASP: a computational platform for building kinetic models of cellular metabolism

Summary

Kinetic models of metabolism are crucial to understand the inner workings of cell metabolism. By taking into account enzyme regulation, detailed kinetic models can provide accurate predictions of metabolic fluxes. Comprehensive consideration of kinetic regulation requires highly parameterized non-linear models, which are challenging to build and fit using available modelling tools. Here, we present a computational package implementing the GRASP framework for building detailed kinetic models of cellular metabolism. By defining the mechanisms of enzyme regulation and a reference state described by reaction fluxes and their corresponding Gibbs free energy ranges, GRASP can efficiently sample an arbitrarily large population of thermodynamically feasible kinetic models. If additional experimental data are available (fluxes, enzyme and metabolite concentrations), these can be integrated to generate models that closely reproduce these observations using an approximate Bayesian computation fitting framework. Within the same framework, model selection tasks can be readily performed.

Availability and implementation

GRASP is implemented as an open-source package in the MATLAB environment. The software runs in Windows, macOS and Linux, is documented (graspk.readthedocs.io) and unit-tested. GRASP is freely available at github.com/biosustain/GRASP.

Supplementary information

Supplementary data are available at Bioinformatics Advances online.

A synthetic C2 auxotroph of Pseudomonas putida for evolutionary engineering of alternative sugar catabolic routes

Acetyl-coenzyme A (AcCoA) is a metabolic hub in virtually all living cells, serving as both a key precursor of essential biomass components and a metabolic sink for catabolic pathways for a large variety of substrates. Owing to this dual role, tight growth-production coupling schemes can be implemented around the AcCoA node. Building on this concept, a synthetic C2 auxotrophy was implemented in the platform bacterium Pseudomonas putida through an in silico-informed engineering approach. A growth-coupling strategy, driven by AcCoA demand, allowed for direct selection of an alternative sugar assimilation route-the phosphoketolase (PKT) shunt from bifidobacteria. Adaptive laboratory evolution forced the synthetic P. putida auxotroph to rewire its metabolic network to restore C2 prototrophy via the PKT shunt. Large-scale structural chromosome rearrangements were identified as possible mechanisms for adjusting the network-wide proteome profile, resulting in improved PKT-dependent growth phenotypes. ¹³C-based metabolic flux analysis revealed an even split between the native Entner-Doudoroff pathway and the synthetic PKT bypass for glucose processing, leading to enhanced carbon conservation. These results demonstrate that the P. putida metabolism can be radically rewired to incorporate a synthetic C2 metabolism, creating novel network connectivities and highlighting the importance of unconventional engineering strategies to support efficient microbial production.

Engineering cell morphology by CRISPR interference in Acinetobacter baylyi ADP1

Microbial production of intracellular compounds can be engineered by redirecting the carbon flux towards products and increasing the cell size. Potential engineering strategies include exploiting clustered regularly interspaced short palindromic repeats interference (CRISPRi)-based tools for controlling gene expression. Here, we applied CRISPRi for engineering Acinetobacter baylyi ADP1, a model bacterium for synthesizing intracellular storage lipids, namely wax esters. We first established an inducible CRISPRi system for strain ADP1, which enables tightly controlled repression of target genes. We then targeted the glyoxylate shunt to redirect carbon flow towards wax esters. Second, we successfully employed CRISPRi for modifying cell morphology by repressing ftsZ, an essential gene required for cell division, in combination with targeted knock-outs to generate significantly enlarged filamentous or spherical cells respectively. The engineered cells sustained increased wax ester production metrics, demonstrating the potential of cell morphology engineering in the production of intracellular lipids.

The application of CRISPR /Cas mediated gene editing in synthetic biology: Challenges and optimizations

Clustered regularly interspaced short palindromic repeats (CRISPR) and its associated enzymes (Cas) is a simple and convenient genome editing tool that has been used in various cell factories and emerging synthetic biology in the recent past. However, several problems, including off-target effects, cytotoxicity, and low efficiency of multi-gene editing, are associated with the CRISPR/Cas system, which have limited its application in new species. In this review, we briefly describe the mechanisms of CRISPR/Cas engineering and propose strategies to optimize the system based on its defects, including, but not limited to, enhancing targeted specificity, reducing toxicity related to Cas protein, and improving multi-point editing efficiency. In addition, some examples of improvements in synthetic biology are also highlighted. Finally, future perspectives of system optimization are discussed, providing a reference for developing safe genome-editing tools for new species.

The topology of genome-scale metabolic reconstructions unravels independent modules and high network flexibility

The topology of metabolic networks is recognisably modular with modules weakly connected apart from sharing a pool of currency metabolites. Here, we defined modules as sets of reversible reactions isolated from the rest of metabolism by irreversible reactions except for the exchange of currency metabolites. Our approach identifies topologically independent modules under specific conditions associated with different metabolic functions. As case studies, the E.coli iJO1366 and Human Recon 2.2 genome-scale metabolic models were split in 103 and 321 modules respectively, displaying significant correlation patterns in expression data. Finally, we addressed a fundamental question about the metabolic flexibility conferred by reversible reactions: “Of all Directed Topologies (DTs) defined by fixing directions to all reversible reactions, how many are capable of carrying flux through all reactions?”. Enumeration of the DTs for iJO1366 model was performed using an efficient depth-first search algorithm, rejecting infeasible DTs based on mass-imbalanced and loopy flux patterns. We found the direction of 79% of reversible reactions must be defined before all directions in the network can be fixed, granting a high degree of flexibility.

Genome-scale metabolic reconstructions represent all biochemical reactions that an organism can accomplish. These reconstructions are complex and often difficult to study in great detail. A way to overcome this limitation is to focus on specific pathways or subsystems. We present a novel method to identify metabolic modules based on the network topology. The method relies on reaction directions and ignores currency metabolites, which artificially connect distant metabolic reactions. In this way, topologically independent modules are built, where inputs and outputs are controlled by irreversible reactions. The method is automatic and unbiased, and, the result is a set of condition specific modules with defined metabolic functions. As a proof-of-concept we generated biologically relevant modules for the E.coli and Human genome-scale metabolic reconstructions supported by transcriptomic data. Finally, we applied the novel approach to study the network flexibility conferred by reversible reactions. In the case of the E. coli model, we found that the direction of 79% of structurally reversible reactions (those not directionally constrained by surrounding irreversible reactions) must be fixed to determine all the reaction directions in the network. Therefore, reversible reactions operate practically independent of each other.

CRISPR-Based Approaches for Gene Regulation in Non-Model Bacteria

CRISPR interference (CRISPRi) and CRISPR activation (CRISPRa) have become ubiquitous approaches to control gene expression in bacteria due to their simple design and effectiveness. By regulating transcription of a target gene(s), CRISPRi/a can dynamically engineer cellular metabolism, implement transcriptional regulation circuitry, or elucidate genotype-phenotype relationships from smaller targeted libraries up to whole genome-wide libraries. While CRISPRi/a has been primarily established in the model bacteria Escherichia coli and Bacillus subtilis, a growing numbering of studies have demonstrated the extension of these tools to other species of bacteria (here broadly referred to as non-model bacteria). In this mini-review, we discuss the challenges that contribute to the slower creation of CRISPRi/a tools in diverse, non-model bacteria and summarize the current state of these approaches across bacterial phyla. We find that despite the potential difficulties in establishing novel CRISPRi/a in non-model microbes, over 190 recent examples across eight bacterial phyla have been reported in the literature. Most studies have focused on tool development or used these CRISPRi/a approaches to interrogate gene function, with fewer examples applying CRISPRi/a gene regulation for metabolic engineering or high-throughput screens and selections. To date, most CRISPRi/a reports have been developed for common strains of non-model bacterial species, suggesting barriers remain to establish these genetic tools in undomesticated bacteria. More efficient and generalizable methods will help realize the immense potential of programmable CRISPR-based transcriptional control in diverse bacteria.

Dynamic flux regulation for high-titer anthranilate production by plasmid-free, conditionally-auxotrophic strains of Pseudomonas putida

Anthranilate, an intermediate of the shikimate pathway, is a high-value aromatic compound widely used as a precursor in the production of dyes, fragrances, plastics and pharmaceuticals. Traditional strategies adopted for microbial anthranilate production rely on the implementation of auxotrophic strains-which requires aromatic amino acids or complex additives to be supplemented in the culture medium, negatively impacting production costs. In this work, we engineered the soil bacterium Pseudomonas putida for high-titer, glucose-dependent anthranilate production by repurposing elements of the Esa quorum sensing (QS) system of Pantoea stewartii. The P_esaS promoter mediated a self-regulated transcriptional response that effectively knocked-down the expression of the trpDC genes. Next, we harnessed the synthetic QS elements to engineer a growth-to-anthranilate production switch. The resulting plasmid-free P. putida strain produced the target compound at 3.8 ± 0.3 mM in shaken-flask cultures after 72 h-a titer >2-fold higher than anthranilate levels reported thus far. Our results highlight the value of dynamic flux regulation for the production of intermediate metabolites within highly-regulated routes (such as the shikimate pathway), thereby circumventing the need of expensive additives.

Modular (de)construction of complex bacterial phenotypes by CRISPR/nCas9-assisted, multiplex cytidine base-editing

CRISPR/Cas technologies constitute a powerful tool for genome engineering, yet their use in non-traditional bacteria depends on host factors or exogenous recombinases, which limits both efficiency and throughput. Here we mitigate these practical constraints by developing a widely-applicable genome engineering toolset for Gram-negative bacteria. The challenge is addressed by tailoring a CRISPR base editor that enables single-nucleotide resolution manipulations (C·G → T·A) with >90% efficiency. Furthermore, incorporating Cas6-mediated processing of guide RNAs in a streamlined protocol for plasmid assembly supports multiplex base editing with >85% efficiency. The toolset is adopted to construct and deconstruct complex phenotypes in the soil bacterium Pseudomonas putida. Single-step engineering of an aromatic-compound production phenotype and multi-step deconstruction of the intricate redox metabolism illustrate the versatility of multiplex base editing afforded by our toolbox. Hence, this approach overcomes typical limitations of previous technologies and empowers engineering programs in Gram-negative bacteria that were out of reach thus far.

Rapid engineering of bacterial genomes is a requisite for both fundamental and applied studies. Here the authors develop an enhanced, broad-host-range cytidine base editor that enables multiplexed and efficient genome editing of Gram-negative bacteria.

New synthetic biology tools for metabolic control

In industrial bioprocesses, microbial metabolism dictates the product yields, and therefore, our capacity to control it has an enormous potential to help us move towards a bio-based economy. The rapid development of multiomics data has accelerated our systematic understanding of complex metabolic regulatory mechanisms, which allow us to develop tools to manipulate them. In the last few years, machine learning-based metabolic modeling, Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) derived synthetic biology tools, and synthetic genetic circuits have been widely used to control the metabolism of microorganisms, manipulate gene expression, and build synthetic pathways for bioproduction. This review describes the latest developments for metabolic control, and focuses on the trends and challenges of metabolic engineering strategies.

Investigating Differential Expressed Genes of Limosilactobacillus reuteri LR08 Regulated by Soybean Protein and Peptides

Soybean protein and peptides have the potential to promote the growth of Lactobacillus, but the mechanisms involved are not well understood. The purpose of this study is to investigate differentially expressed genes (DEGs) of Limosilactobacillus reuteri (L. reuteri) LR08 responding to soybean protein and peptides using transcriptome. The results showed that both digested protein (dpro) and digested peptides (dpep) could enhance a purine biosynthesis pathway which could provide more nucleic acid and ATP for bacteria growth. Moreover, dpep could be used instead of dpro to promote the ABC transporters, especially the genes involved in the transportation of various amino acids. Interestingly, dpro and dpep played opposite roles in modulating DEGs from the acc and fab gene families which participate in fatty acid biosynthesis. These not only provide a new direction for developing nitrogen-sourced prebiotics in the food industry but could also help us to understand the fundamental mechanism of the effects of dpro and dpep on their growth and metabolisms and provides relevant evidence for further investigation.