Dissecting the genetic and metabolic mechanisms of adaptation to the knockout of a major metabolic enzyme in Escherichia coli

A citric acid cycle-deficient Escherichia coli as an efficient chassis for aerobic fermentations

Tricarboxylic acid cycle (TCA cycle) plays an important role for aerobic growth of heterotrophic bacteria. Theoretically, eliminating TCA cycle would decrease carbon dissipation and facilitate chemicals biosynthesis. Here, we construct an E. coli strain without a functional TCA cycle that can serve as a versatile chassis for chemicals biosynthesis. We first use adaptive laboratory evolution to recover aerobic growth in minimal medium of TCA cycle-deficient E. coli. Inactivation of succinate dehydrogenase is a key event in the evolutionary trajectory. Supply of succinyl-CoA is identified as the growth limiting factor. By replacing endogenous succinyl-CoA dependent enzymes, we obtain an optimized TCA cycle-deficient E. coli strain. As a proof of concept, the strain is engineered for high-yield production of four separate products. This work enhances our understanding of the role of the TCA cycle in E. coli metabolism and demonstrates the advantages of using TCA cycle-deficient E. coli strain for biotechnological applications.

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.

The pentose phosphate pathway in health and disease

The pentose phosphate pathway (PPP) is a glucose-oxidizing pathway that runs in parallel to upper glycolysis to produce ribose 5-phosphate and nicotinamide adenine dinucleotide phosphate (NADPH). Ribose 5-phosphate is used for nucleotide synthesis, while NADPH is involved in redox homoeostasis as well as in promoting biosynthetic processes, such as the synthesis of tetrahydrofolate, deoxyribonucleotides, proline, fatty acids and cholesterol. Through NADPH, the PPP plays a critical role in suppressing oxidative stress, including in certain cancers, in which PPP inhibition may be therapeutically useful. Conversely, PPP-derived NADPH also supports purposeful cellular generation of reactive oxygen species (ROS) and reactive nitrogen species (RNS) for signalling and pathogen killing. Genetic deficiencies in the PPP occur relatively commonly in the committed pathway enzyme glucose-6-phosphate dehydrogenase (G6PD). G6PD deficiency typically manifests as haemolytic anaemia due to red cell oxidative damage but, in severe cases, also results in infections due to lack of leucocyte oxidative burst, highlighting the dual redox roles of the pathway in free radical production and detoxification. This Review discusses the PPP in mammals, covering its roles in biochemistry, physiology and disease.

Valorization of whey-based side streams for microbial biomass, molecular hydrogen, and hydrogenase production

Side streams of the dairy industry are a suitable nutrient source for cultivating microorganisms, producing enzymes, and high-value chemical compounds. The heterotrophic Escherichia coli and chemolithoautotroph Ralstonia eutropha are of major biotechnological interest. R. eutropha is a model organism for producing O₂-tolerant [NiFe]-hydrogenases (Hyds) (biocatalysts), and E. coli has found widespread use as an expression platform for producing recombinant proteins, molecular hydrogen (H₂), and other valuable products. Aiming at developing suitable cultivation media from side streams of the dairy industry, the pre-treatment (filtration, dilution, and pH adjustment) of cheese (sweet) whey (SW) and curd (acid) whey (AW), with and without the use of ß-glucosidase, has been performed. Growth parameters (oxidation-reduction potential (ORP), pH changes, specific growth rate, biomass formation) of E. coli BW25113 and R. eutropha H16 type strains were monitored during cultivation on filtered and non-filtered SW and AW at 37 °C, pH 7.5 and 30 °C, pH 7.0, respectively. Along with microbial growth, measurements of pH and ORP indicated good fermentative growth. Compared to growth on fructose-nitrogen minimal salt medium (control), a maximum cell yield (OD₆₀₀ 4.0) and H₂-oxidizing Hyd activity were achieved in the stationary growth phase for R. eutropha. Hyd-3-dependent H₂ production by E. coli utilizing whey as a growth substrate was demonstrated. Moreover, good biomass production and prolonged H₂ yields of ~ 5 mmol/L and cumulative H₂ ~ 94 mL g/L dry whey (DW) (ß-glucosidase-treated) were observed during the cultivation of the engineered E. coli strain. These results open new avenues for effective whey treatment using thermostable β-glucosidase and confirm whey as an economically viable commodity for biomass and biocatalyst production. KEY POINTS: • Archaeal thermostable β-glucosidase isolated from the metagenome of a hydrothermal spring was used for lactose hydrolysis in whey. • Hydrogenase enzyme activity was induced during the growth of Ralstonia eutropha H16 on whey. • Enhanced biomass and H₂ production was shown in a genetically modified strain of Escherichia coli.

High-level co-production of 3-hydroxypropionic acid and 1,3-propanediol from glycerol: Metabolic engineering and process optimization

3-Hydroxypropionic acid (3-HP) and 1,3-propanediol (1,3-PDO) are value-added chemicals with versatile applications in the chemical, pharmaceutical, and food industries. Nevertheless, sustainable production of 3-HP and 1,3-PDO is often limited by the lack of efficient strains and suitable fermentation configurations. Herein, attempts have been made to improve the co-production of both metabolites through metabolic engineering of Escherichia coli and process optimization. First, the 3-HP and 1,3-PDO co-biosynthetic pathways were recruited and optimized in E. coli, followed by coupling the pathways to the transhydrogenase-mediated cofactor regeneration systems that increased cofactor availability and product synthesis. Next, pathway rebalancing and block of by-product formation significantly improved 3-HP and 1,3-PDO net titer. Subsequently, glycerol flux toward 3-HP and 1,3-PDO synthesis was maximized by removing metabolic repression and fine-tuning the glycerol oxidation pathway. Lastly, the combined fermentation process optimization and two-stage pH-controlled fed-batch fermentation co-produced 140.50 g/L 3-HP and 1,3-PDO, with 0.85 mol/mol net yield.

Experimental Evolution Reveals Unifying Systems-Level Adaptations but Diversity in Driving Genotypes

Genotype-fitness maps of evolution have been well characterized for biological components, such as RNA and proteins, but remain less clear for systems-level properties, such as those of metabolic and transcriptional regulatory networks. Here, we take multi-omics measurements of 6 different E. coli strains throughout adaptive laboratory evolution (ALE) to maximal growth fitness. The results show the following: (i) convergence in most overall phenotypic measures across all strains, with the notable exception of divergence in NADPH production mechanisms; (ii) conserved transcriptomic adaptations, describing increased expression of growth promoting genes but decreased expression of stress response and structural components; (iii) four groups of regulatory trade-offs underlying the adjustment of transcriptome composition; and (iv) correlates that link causal mutations to systems-level adaptations, including mutation-pathway flux correlates and mutation-transcriptome composition correlates. We thus show that fitness landscapes for ALE can be described with two layers of causation: one based on system-level properties (continuous variables) and the other based on mutations (discrete variables). IMPORTANCE Understanding the mechanisms of microbial adaptation will help combat the evolution of drug-resistant microbes and enable predictive genome design. Although experimental evolution allows us to identify the causal mutations underlying microbial adaptation, it remains unclear how causal mutations enable increased fitness and is often explained in terms of individual components (i.e., enzyme rate) as opposed to biological systems (i.e., pathways). Here, we find that causal mutations in E. coli are linked to systems-level changes in NADPH balance and expression of stress response genes. These systems-level adaptation patterns are conserved across diverse E. coli strains and thus identify cofactor balance and proteome reallocation as dominant constraints governing microbial adaptation.

Orthogonal glycolytic pathway enables directed evolution of noncanonical cofactor oxidase

Noncanonical cofactor biomimetics (NCBs) such as nicotinamide mononucleotide (NMN+) provide enhanced scalability for biomanufacturing. However, engineering enzymes to accept NCBs is difficult. Here, we establish a growth selection platform to evolve enzymes to utilize NMN+-based reducing power. This is based on an orthogonal, NMN+-dependent glycolytic pathway in Escherichia coli which can be coupled to any reciprocal enzyme to recycle the ensuing reduced NMN+. With a throughput of >106 variants per iteration, the growth selection discovers a Lactobacillus pentosus NADH oxidase variant with ~10-fold increase in NMNH catalytic efficiency and enhanced activity for other NCBs. Molecular modeling and experimental validation suggest that instead of directly contacting NCBs, the mutations optimize the enzyme's global conformational dynamics to resemble the WT with the native cofactor bound. Restoring the enzyme's access to catalytically competent conformation states via deep navigation of protein sequence space with high-throughput evolution provides a universal route to engineer NCB-dependent enzymes.

Characterization of an Entner-Doudoroff pathway-activated Escherichia coli

BACKGROUND

Escherichia coli have both the Embden-Meyerhof-Parnas pathway (EMPP) and Entner-Doudoroff pathway (EDP) for glucose breakdown, while the EDP primarily remains inactive for glucose metabolism. However, EDP is a more favorable route than EMPP for the production of certain products.

RESULTS

EDP was activated by deleting the pfkAB genes in conjunction with subsequent adaptive laboratory evolution (ALE). The evolved strains acquired mutations in transcriptional regulatory genes for glycolytic process (crp, galR, and gntR) and in glycolysis-related genes (gnd, ptsG, and talB). The genotypic, transcriptomic and phenotypic analyses of those mutations deepen our understanding of their beneficial effects on cellulosic biomass bio-conversion. On top of these scientific understandings, we further engineered the strain to produce higher level of lycopene and 3-hydroxypropionic acid.

CONCLUSIONS

These results indicate that the E. coli strain has innate capability to use EDP in lieu of EMPP for glucose metabolism, and this versatility can be harnessed to further engineer E. coli for specific biotechnological applications.

Mutants lacking global regulators, fis and arcA, in Escherichia coli enhanced growth fitness under acetate metabolism by pathway reprogramming

Global regulatory transcription factors play a significant role in controlling microbial metabolism under genetic and environmental perturbations. A system-level effect of carbon sources such as acetate on microbial metabolism under disrupted global regulators has not been well established. Acetate is one of the major substrates available in various nutrient niches such as the mammalian gut and a keto diet. A substantial amount of acetate gets secreted in aerobic metabolism. Therefore, investigating the study on acetate metabolism is highly significant. It is known that the global regulators fis and arcA regulate acetate uptake genes in E. coli under glucose conditions. This study deciphered the growth and flux distribution of E. coli transcription regulatory knockouts Δfis, ΔarcA and double deletion mutant, ΔarcAΔfis under acetate using ¹³C-metabolic flux analysis (MFA), which has not been investigated before. We observed that the mutants exhibited an expeditious growth rate (~ 1.2-1.6-fold) with a proportionate increase in acetate uptake rates compared to the wild type. ¹³C-MFA displayed the distinct metabolic reprogramming of intracellular fluxes via the TCA cycle, anaplerotic pathway and gluconeogenesis, which conferred an advantage of a faster growth rate with better carbon usage in all the mutants. This resulted in higher metabolic fluxes through the TCA cycle (~ 18-90%), lower gluconeogenesis (~ 15-35%) and higher CO₂ and ATP production with the proportional increase in growth rate. The study reveals a novel insight by stating the sub-optimality of the wild-type strain grown under acetate substrate aerobically. These mutant strains efficiently oxidize acetate, thus acting as potential candidates for the biosynthesis of isoprenoids, biofuels, vitamins and various pharmaceutical products.Key Points• Mutants exhibited a better balance between energy and precursor synthesis than WT.• Leveraged in the unravelling of regulatory control under various nutrient shifts.• Metabolic readjustment resulted in optimal biomass requirement and faster growth.

Optogenetic reprogramming of carbon metabolism using light-powering microbial proton pump systems

In microbial fermentative production, ATP regeneration, while crucial for cellular processes, conflicts with efficient target chemical production because ATP regeneration exhausts essential carbon sources also required for target chemical biosynthesis. To wrestle with this dilemma, we harnessed the power of microbial rhodopsins with light-driven proton pumping activity to supplement with ATP, thereby facilitating the bioproduction of various chemicals. We first demonstrated a photo-driven ATP supply and redistribution of metabolic carbon flows to target chemical synthesis by installing already-known delta rhodopsin (dR) in Escherichia coli. In addition, we identified novel rhodopsins with higher proton pumping activities than dR, and created an engineered cell for in vivo self-supply of the rhodopsin-activator, all-trans-retinal. Our concept exploiting the light-powering ATP supplier offers a potential increase in carbon use efficiency for microbial productions through metabolic reprogramming.

Analogous Metabolic Decoupling in Pseudomonas putida and Comamonas testosteroni Implies Energetic Bypass to Facilitate Gluconeogenic Growth

Gluconeogenic carbon metabolism is not well understood, especially within the context of flux partitioning between energy generation and biomass production, despite the importance of gluconeogenic carbon substrates in natural and engineered carbon processing. Here, using multiple omics approaches, we elucidate the metabolic mechanisms that facilitate gluconeogenic fast-growth phenotypes in Pseudomonas putida and Comamonas testosteroni, two Proteobacteria species with distinct metabolic networks. In contrast to the genetic constraint of C. testosteroni, which lacks the enzymes required for both sugar uptake and a complete oxidative pentose phosphate (PP) pathway, sugar metabolism in P. putida is known to generate surplus NADPH by relying on the oxidative PP pathway within its characteristic cyclic connection between the Entner-Doudoroff (ED) and Embden-Meyerhoff-Parnas (EMP) pathways. Remarkably, similar to the genome-based metabolic decoupling in C. testosteroni, our 13C-fluxomics reveals an inactive oxidative PP pathway and disconnected EMP and ED pathways in P. putida during gluconeogenic feeding, thus requiring transhydrogenase reactions to supply NADPH for anabolism in both species by leveraging the high tricarboxylic acid cycle flux during gluconeogenic growth. Furthermore, metabolomics and proteomics analyses of both species during gluconeogenic feeding, relative to glycolytic feeding, demonstrate a 5-fold depletion in phosphorylated metabolites and the absence of or up to a 17-fold decrease in proteins of the PP and ED pathways. Such metabolic remodeling, which is reportedly lacking in Escherichia coli exhibiting a gluconeogenic slow-growth phenotype, may serve to minimize futile carbon cycling while favoring the gluconeogenic metabolic regime in relevant proteobacterial species. IMPORTANCE Glycolytic metabolism of sugars is extensively studied in the Proteobacteria, but gluconeogenic carbon sources (e.g., organic acids, amino acids, aromatics) that feed into the tricarboxylic acid (TCA) cycle are widely reported to produce a fast-growth phenotype, particularly in species with biotechnological relevance. Much remains unknown about the importance of glycolysis-associated pathways in the metabolism of gluconeogenic carbon substrates. Here, we demonstrate that two distinct proteobacterial species, through genetic constraints or metabolic regulation at specific metabolic nodes, bypass the oxidative PP pathway during gluconeogenic growth and avoid unnecessary carbon fluxes by depleting protein investment into connected glycolysis pathways. Both species can leverage instead the high TCA cycle flux during gluconeogenic feeding to meet NADPH demand. Importantly, lack of a complete oxidative pentose phosphate pathway is a widespread metabolic trait in Proteobacteria with a gluconeogenic carbon preference, thus highlighting the important relevance of our findings toward elucidating the metabolic architecture in these bacteria.

Microbial protein cell factories fight back?

The biopharmaceutical market is growing faster than ever, with two production systems competing for market dominance: mammalian cells and microorganisms. In recent years, based on the rise of antibody-based therapies, new biotherapeutic approvals have favored mammalian hosts. However, not only has extensive research elevated our understanding of microbes to new levels, but emerging therapeutic molecules also facilitate their use; thus, is it time for microbes to fight back? In this review, we answer this timely question by cross-comparing four microbial production hosts and examining the innovations made to both their secretion and post-translational modification (PTM) capabilities. Furthermore, we discuss the impact of tools, such as omics and systems biology, as well as alternative production systems and emerging biotherapeutics.

Pyridoxal and α-ketoglutarate independently improve function of Saccharomyces cerevisiae Thi5 in the metabolic network of Salmonella enterica

Microbial metabolism is often considered modular, but metabolic engineering studies have shown that transferring pathways, or modules, between organisms is not always straightforward. The Thi5-dependent pathway(s) for synthesis of the pyrimidine moiety of thiamine from Saccharomyces cerevisiae and Legionella pneumophila functioned differently when incorporated into the metabolic network of Salmonella enterica. Function of Thi5 from Saccharomyces cerevisiae (ScThi5) required modification of the underlying metabolic network, while LpThi5 functioned with the native network. Here we probe the metabolic requirements for heterologous function of ScThi5 and report a strong genetic and physiological evidence for a connection between alpha-ketoglutarate (αKG) levels and ScThi5 function. The connection was built with two classes of genetic suppressors linked to metabolic flux or metabolite pool changes. Further, direct modulation of nitrogen assimilation through nutritional or genetic modification implicated αKG levels in Thi5 function. Exogenous pyridoxal similarly improved ScThi5 function in S. enterica. Finally, directly increasing αKG and PLP with supplementation improved function of both ScThi5 and relevant variants of Thi5 from Legionella pneumophila (LpThi5). The data herein suggest structural differences between ScThi5 and LpThi5 impact their level of function in vivo and implicate αKG in supporting function of the Thi5 pathway when placed in the heterologous metabolic network of S. enterica. IMPORTANCE Thiamine biosynthesis is a model metabolic node that has been used to extend our understanding of metabolic network structure and individual enzyme function. The requirements for in vivo function of the Thi5-dependent pathway found in Legionella and yeast are poorly characterized. Here we suggest that αKG modulates function of the Thi5 pathway in S. enterica and provide evidence that structural variation between ScThi5 and LpThi5 contribute to their functional differences in a Salmonella enterica host.

Improved Yield of Recombinant Protein via Flagella Regulator Deletion in Escherichia coli

Protein production requires a significant amount of intracellular energy. Eliminating the flagella has been proposed to help Escherichia coli improve protein production by reducing energy consumption. In this study, the gene encoding a subunit of FlhC, a master regulator of flagella assembly, was deleted to reduce the expression of flagella-related genes. FlhC knockout in the ptsG-deleted strain triggered significant growth retardation with increased ATP levels and a higher NADPH/NADP⁺ ratio. Metabolic flux analysis using a ¹³C-labeled carbon substrate showed increased fluxes toward the pentose phosphate and tricarboxylic acid cycle pathways in the flhC- and ptsG-deleted strains. Introduction of a high copy number plasmid or overexpression of the recombinant protein in this strain restored growth rate without increasing glucose consumption. These results suggest that the metabolic burden caused by flhC deletion was resolved by recombinant protein production. The recombinant enhanced green fluorescent protein yield per glucose consumption increased 1.81-fold in the flhC mutant strain. Thus, our study demonstrates that high-yield production of the recombinant protein was achieved with reduced flagella formation.

Why? - Successful Pseudomonas aeruginosa clones with a focus on clone C

The environmental species Pseudomonas aeruginosa thrives in a variety of habitats. Within the epidemic population structure of P. aeruginosa, occassionally highly successful clones that are equally capable to succeed in the environment and the human host arise. Framed by a highly conserved core genome, individual members of successful clones are characterized by a high variability in their accessory genome. The abundance of successful clones might be funded in specific features of the core genome or, although not mutually exclusive, in the variability of the accessory genome. In clone C, one of the most predominant clones, the plasmid pKLC102 and the PACGI-1 genomic island are two ubiquitous accessory genetic elements. The conserved transmissible locus of protein quality control (TLPQC) at the border of PACGI-1 is a unique horizontally transferred compository element, which codes predominantly for stress-related cargo gene products such as involved in protein homeostasis. As a hallmark, most TLPQC xenologues possess a core genome equivalent. With elevated temperature tolerance as a characteristic of clone C strains, the unique P. aeruginosa and clone C specific disaggregase ClpG is a major contributor to tolerance. As other successful clones, such as PA14, do not encode the TLPQC locus, ubiquitous denominators of success, if existing, need to be identified.

A guide to metabolic flux analysis in metabolic engineering: Methods, tools and applications

The field of metabolic engineering is primarily concerned with improving the biological production of value-added chemicals, fuels and pharmaceuticals through the design, construction and optimization of metabolic pathways, redirection of intracellular fluxes, and refinement of cellular properties relevant for industrial bioprocess implementation. Metabolic network models and metabolic fluxes are central concepts in metabolic engineering, as was emphasized in the first paper published in this journal, "Metabolic fluxes and metabolic engineering" (Metabolic Engineering, 1: 1-11, 1999). In the past two decades, a wide range of computational, analytical and experimental approaches have been developed to interrogate the capabilities of biological systems through analysis of metabolic network models using techniques such as flux balance analysis (FBA), and quantify metabolic fluxes using constrained-based modeling approaches such as metabolic flux analysis (MFA) and more advanced experimental techniques based on the use of stable-isotope tracers, i.e. ¹³C-metabolic flux analysis (¹³C-MFA). In this review, we describe the basic principles of metabolic flux analysis, discuss current best practices in flux quantification, highlight potential pitfalls and alternative approaches in the application of these tools, and give a broad overview of pragmatic applications of flux analysis in metabolic engineering practice.

A Two-Enzyme Adaptive Unit within Bacterial Folate Metabolism

Enzyme function and evolution are influenced by the larger context of a metabolic pathway. Deleterious mutations or perturbations in one enzyme can often be compensated by mutations to others. We used comparative genomics and experiments to examine evolutionary interactions with the essential metabolic enzyme dihydrofolate reductase (DHFR). Analyses of synteny and co-occurrence across bacterial species indicate that DHFR is coupled to thymidylate synthase (TYMS) but relatively independent from the rest of folate metabolism. Using quantitative growth rate measurements and forward evolution in Escherichia coli, we demonstrate that the two enzymes adapt as a relatively independent unit in response to antibiotic stress. Metabolomic profiling revealed that TYMS activity must not exceed DHFR activity to prevent the depletion of reduced folates and the accumulation of the intermediate dihydrofolate. Comparative genomics analyses identified >200 gene pairs with similar statistical signatures of modular co-evolution, suggesting that cellular pathways may be decomposable into small adaptive units.

Causal mutations from adaptive laboratory evolution are outlined by multiple scales of genome annotations and condition-specificity

BACKGROUND

Adaptive Laboratory Evolution (ALE) has emerged as an experimental approach to discover mutations that confer phenotypic functions of interest. However, the task of finding and understanding all beneficial mutations of an ALE experiment remains an open challenge for the field. To provide for better results than traditional methods of ALE mutation analysis, this work applied enrichment methods to mutations described by a multiscale annotation framework and a consolidated set of ALE experiment conditions. A total of 25,321 unique genome annotations from various sources were leveraged to describe multiple scales of mutated features in a set of 35 Escherichia coli based ALE experiments. These experiments totalled 208 independent evolutions and 2641 mutations. Additionally, mutated features were statistically associated across a total of 43 unique experimental conditions to aid in deconvoluting mutation selection pressures.

RESULTS

Identifying potentially beneficial, or key, mutations was enhanced by seeking coding and non-coding genome features significantly enriched by mutations across multiple ALE replicates and scales of genome annotations. The median proportion of ALE experiment key mutations increased from 62%, with only small coding and non-coding features, to 71% with larger aggregate features. Understanding key mutations was enhanced by considering the functions of broader annotation types and the significantly associated conditions for key mutated features. The approaches developed here were used to find and characterize novel key mutations in two ALE experiments: one previously unpublished with Escherichia coli grown on glycerol as a carbon source and one previously published with Escherichia coli tolerized to high concentrations of L-serine.

CONCLUSIONS

The emergent adaptive strategies represented by sets of ALE mutations became more clear upon observing the aggregation of mutated features across small to large scale genome annotations. The clarification of mutation selection pressures among the many experimental conditions also helped bring these strategies to light. This work demonstrates how multiscale genome annotation frameworks and data-driven methods can help better characterize ALE mutations, and thus help elucidate the genotype-to-phenotype relationship of the studied organism.

Engineering Carboxylic Acid Reductase (CAR) through a Whole-Cell Growth-Coupled NADPH Recycling Strategy

Rapid evolution of enzyme activities is often hindered by the lack of efficient and affordable methods to identify beneficial mutants. We report the development of a new growth-coupled selection method for evolving NADPH-consuming enzymes based on the recycling of this redox cofactor. The method relies on a genetically modified Escherichia coli strain, which overaccumulates NADPH. This method was applied to the engineering of a carboxylic acid reductase (CAR) for improved catalytic activities on 2-methoxybenzoate and adipate. Mutant enzymes with up to 17-fold improvement in catalytic efficiency were identified from single-site saturated mutagenesis libraries. Obtained mutants were successfully applied to whole-cell conversions of adipate into 1,6-hexanediol, a C₆ monomer commonly used in polymer industry.

Metabolic role of pyrophosphate-linked phosphofructokinase pfk for C1 assimilation in Methylotuvimicrobium alcaliphilum 20Z

BACKGROUND

Methanotrophs is a promising biocatalyst in biotechnological applications with their ability to utilize single carbon (C1) feedstock to produce high-value compounds. Understanding the behavior of biological networks of methanotrophic bacteria in different parameters is vital to systems biology and metabolic engineering. Interestingly, methanotrophic bacteria possess the pyrophosphate-dependent 6-phosphofructokinase (PPi-PFK) instead of the ATP-dependent 6-phosphofructokinase, indicating their potentials to serve as promising model for investigation the role of inorganic pyrophosphate (PPi) and PPi-dependent glycolysis in bacteria. Gene knockout experiments along with global-omics approaches can be used for studying gene functions as well as unraveling regulatory networks that rely on the gene product.

RESULTS

In this study, we performed gene knockout and RNA-seq experiments in Methylotuvimicrobium alcaliphilum 20Z to investigate the functional roles of PPi-PFK in C1 metabolism when cells were grown on methane and methanol, highlighting its metabolic importance in C1 assimilation in M. alcaliphilum 20Z. We further conducted adaptive laboratory evolution (ALE) to investigate regulatory architecture in pfk knockout strain. Whole-genome resequencing and RNA-seq approaches were performed to characterize the genetic and metabolic responses of adaptation to pfk knockout. A number of mutations, as well as gene expression profiles, were identified in pfk ALE strain to overcome insufficient C1 assimilation pathway which limits the growth in the unevolved strain.

CONCLUSIONS

This study first revealed the regulatory roles of PPi-PFK on C1 metabolism and then provided novel insights into mechanism of adaptation to the loss of this major metabolic enzyme as well as an improved basis for future strain design in type I methanotrophs.

ALEdb 1.0: a database of mutations from adaptive laboratory evolution experimentation

Adaptive Laboratory Evolution (ALE) has emerged as an experimental approach to discover causal mutations that confer desired phenotypic functions. ALE not only represents a controllable experimental approach to systematically discover genotype-phenotype relationships, but also allows for the revelation of the series of genetic alterations required to acquire the new phenotype. Numerous ALE studies have been published, providing a strong impetus for developing databases to warehouse experimental evolution information and make it retrievable for large-scale analysis. Here, the first step towards establishing this resource is presented: ALEdb (http://aledb.org). This initial release contains over 11 000 mutations that have been discovered from eleven ALE publications. ALEdb (i) is a web-based platform that comprehensively reports on ALE acquired mutations and their conditions, (ii) reports key mutations using previously established trends, (iii) enables a search-driven workflow to enhance user mutation functional analysis through mutation cross-reference, (iv) allows exporting of mutation query results for custom analysis, (v) includes a bibliome describing the databased experiment publications and (vi) contains experimental evolution mutations from multiple model organisms. Thus, ALEdb is an informative platform which will become increasingly revealing as the number of reported ALE experiments and identified mutations continue to expand.

Evolutionary Repair Experiments as a Window to the Molecular Diversity of Life

Comparative genomics reveals an unexpected diversity in the molecular mechanisms underlying conserved cellular functions, such as DNA replication and cytokinesis. However, the genetic bases and evolutionary processes underlying this 'molecular diversity' remain to be explained. Here, we review a tool to generate alternative mechanisms for conserved cellular functions and test hypotheses concerning the generation of molecular diversity - evolutionary repair experiments, in which laboratory microbial populations adapt in response to a genetic perturbation. We summarize the insights gained from evolutionary repair experiments, the spectrum and dynamics of compensatory mutations, and the alternative molecular mechanisms used to repair perturbed cellular functions. We relate these experiments to the modifications of conserved functions that have occurred outside the laboratory. We end by proposing strategies to improve evolutionary repair experiments as a tool to explore the molecular diversity of life.

Metabolic engineering strategies for butanol production in Escherichia coli

The global market of butanol is increasing due to its growing applications as solvent, flavoring agent, and chemical precursor of several other compounds. Recently, the superior properties of n-butanol as a biofuel over ethanol have stimulated even more interest. (Bio)butanol is natively produced together with ethanol and acetone by Clostridium species through acetone-butanol-ethanol fermentation, at noncompetitive, low titers compared to petrochemical production. Different butanol production pathways have been expressed in Escherichia coli, a more accessible host compared to Clostridium species, to improve butanol titers and rates. The bioproduction of butanol is here reviewed from a historical and theoretical perspective. All tested rational metabolic engineering strategies in E. coli to increase butanol titers are reviewed: manipulation of central carbon metabolism, elimination of competing pathways, cofactor balancing, development of new pathways, expression of homologous enzymes, consumption of different substrates, and molecular biology strategies. The progress in the field of metabolic modeling and pathway generation algorithms and their potential application to butanol production are also summarized here. The main goals are to gather all the strategies, evaluate the respective progress obtained, identify, and exploit the outstanding challenges.

Controlled replication of 'Candidatus Liberibacter asiaticus' DNA in citrus leaf discs

'Candidatus Liberibacter asiaticus' is a fastidious bacterium and a putative agent of citrus greening disease (a.k.a., huanglongbing, HLB), a significant agricultural disease that affects citrus fruit quality and tree health. In citrus, 'Ca. L. asiaticus' is phloem limited. Lack of culture tools to study 'Ca. L. asiaticus' complicates analysis of this important organism. To improve understanding of 'Ca. L. asiaticus'-host interactions including parameters that affect 'Ca. L. asiaticus' replication, methods suitable for screening pathogen responses to physicochemical and nutritional variables are needed. We describe a leaf disc-based culture assay that allows highly selective measurement of changes in 'Ca. L. asiaticus' DNA within plant tissue incubated under specific physicochemical and nutritional conditions. qPCR analysis targeting the hypothetical gene CD16-00155 (strain A4) allowed selective quantification of 'Ca. L. asiaticus' DNA content within infected tissue. 'Ca. L. asiaticus' DNA replication was observed in response to glucose exclusively under microaerobic conditions, and the antibiotic amikacin further enhanced 'Ca. L. asiaticus' DNA replication. Metabolite profiling revealed a moderate impact of 'Ca. L. asiaticus' on the ability of leaf tissue to metabolize and respond to glucose.

Computer-Aided Rational Design of Efficient NADPH Production System by Escherichia coli pgi Mutant Using a Mixture of Glucose and Xylose

Lignocellulosic biomass can be hydrolyzed into two major sugars of glucose and xylose, and thus the strategy for the efficient consumption of both sugars is highly desirable. NADPH is the essential molecule for the production of industrially important value-added chemicals, and thus its availability is quite important. Escherichia coli mutant lacking the pgi gene encoding phosphoglucose isomerase (Pgi) has been preferentially used to overproduce the NADPH. However, there exists a disadvantage that the cell growth rate becomes low for the mutant grown on glucose. This limits the efficient NADPH production, and therefore, it is quite important to investigate how addition of different carbon source such as xylose (other than glucose) effectively improves the NADPH production. In this study, we have developed a kinetic model to propose an efficient NADPH production system using E. coli pgi-knockout mutant with a mixture of glucose and xylose. The proposed system adds xylose to glucose medium to recover the suppressed growth of the pgi mutant, and determines the xylose content to maximize the NADPH productivity. Finally, we have designed a mevalonate (MVA) production system by implementing ArcA overexpression into the pgi-knockout mutant using a mixture of glucose and xylose. In addition to NADPH overproduction, the accumulation of acetyl-CoA (AcCoA) is necessary for the efficient MVA production. In the present study, therefore, we considered to overexpress ArcA, where ArcA overexpression suppresses the TCA cycle, causing the overflow of AcCoA, a precursor of MVA. We predicted the xylose content that maximizes the MVA production. This approach demonstrates the possibility of a great progress in the computer-aided rational design of the microbial cell factories for useful metabolite production.

Contextual Flexibility in Pseudomonas aeruginosa Central Carbon Metabolism during Growth in Single Carbon Sources

Pseudomonas aeruginosa is an opportunistic human pathogen that is well known for causing infections in the airways of people with cystic fibrosis. Although it is clear that P. aeruginosa is metabolically well adapted to life in the CF lung, little is currently known about how the organism metabolizes the nutrients available in the airways. In this work, we used a combination of gene expression and isotope tracer (“fluxomic”) analyses to find out exactly where the input carbon goes during growth on two CF-relevant carbon sources, acetate and glycerol (derived from the breakdown of lung surfactant). We found that carbon is routed (“fluxed”) through very different pathways during growth on these substrates and that this is accompanied by an unexpected remodeling of the cell’s electron transfer pathways. Having access to this “blueprint” is important because the metabolism of P. aeruginosa is increasingly being recognized as a target for the development of much-needed antimicrobial agents.

Pseudomonas aeruginosa is an opportunistic human pathogen, particularly noted for causing infections in the lungs of people with cystic fibrosis (CF). Previous studies have shown that the gene expression profile of P. aeruginosa appears to converge toward a common metabolic program as the organism adapts to the CF airway environment. However, we still have only a limited understanding of how these transcriptional changes impact metabolic flux at the systems level. To address this, we analyzed the transcriptome, proteome, and fluxome of P. aeruginosa grown on glycerol or acetate. These carbon sources were chosen because they are the primary breakdown products of an airway surfactant, phosphatidylcholine, which is known to be a major carbon source for P. aeruginosa in CF airways. We show that the fluxes of carbon throughout central metabolism are radically different among carbon sources. For example, the newly recognized “EDEMP cycle” (which incorporates elements of the Entner-Doudoroff [ED] pathway, the Embden-Meyerhof-Parnas [EMP] pathway, and the pentose phosphate [PP] pathway) plays an important role in supplying NADPH during growth on glycerol. In contrast, the EDEMP cycle is attenuated during growth on acetate, and instead, NADPH is primarily supplied by the reaction catalyzed by isocitrate dehydrogenase(s). Perhaps more importantly, our proteomic and transcriptomic analyses revealed a global remodeling of gene expression during growth on the different carbon sources, with unanticipated impacts on aerobic denitrification, electron transport chain architecture, and the redox economy of the cell. Collectively, these data highlight the remarkable metabolic plasticity of P. aeruginosa; that plasticity allows the organism to seamlessly segue between different carbon sources, maximizing the energetic yield from each.

High-throughput enrichment of temperature-sensitive argininosuccinate synthetase for two-stage citrulline production in E. coli

Controlling metabolism of engineered microbes is important to modulate cell growth and production during a bioprocess. For example, external parameters such as light, chemical inducers, or temperature can act on metabolism of production strains by changing the abundance or activity of enzymes. Here, we created temperature-sensitive variants of an essential enzyme in arginine biosynthesis of Escherichia coli (argininosuccinate synthetase, ArgG) and used them to dynamically control citrulline overproduction and growth of E. coli. We show a method for high-throughput enrichment of temperature-sensitive ArgG variants with a fluorescent TIMER protein and flow cytometry. With 90 of the thus derived ArgG variants, we complemented an ArgG deletion strain showing that 90% of the strains exhibit temperature-sensitive growth and 69% of the strains are auxotrophic for arginine at 42 °C and prototrophic at 30 °C. The best temperature-sensitive ArgG variant enabled precise and tunable control of cell growth by temperature changes. Expressing this variant in a feedback-dysregulated E. coli strain allowed us to realize a two-stage bioprocess: a 33 °C growth-phase for biomass accumulation and a 39 °C stationary-phase for citrulline production. With this two-stage strategy, we produced 3 g/L citrulline during 45 h cultivation in a 1-L bioreactor. These results show that temperature-sensitive enzymes can be created en masse and that they may function as metabolic valves in engineered bacteria.

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Method to enrich temperature-sensitive enzymes en masse.

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Temperature-sensitive enzymes function as metabolic valve.

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Temperature controlled two-stage production of citrulline.

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.

A Compendium of Genetic Modifiers of Mitochondrial Dysfunction Reveals Intra-organelle Buffering

Mitochondrial dysfunction is associated with a spectrum of human conditions, ranging from rare, inborn errors of metabolism to the aging process. To identify pathways that modify mitochondrial dysfunction, we performed genome-wide CRISPR screens in the presence of small-molecule mitochondrial inhibitors. We report a compendium of chemical-genetic interactions involving 191 distinct genetic modifiers, including 38 that are synthetic sick/lethal and 63 that are suppressors. Genes involved in glycolysis (PFKP), pentose phosphate pathway (G6PD), and defense against lipid peroxidation (GPX4) scored high as synthetic sick/lethal. A surprisingly large fraction of suppressors are pathway intrinsic and encode mitochondrial proteins. A striking example of such "intra-organelle" buffering is the alleviation of a chemical defect in complex V by simultaneous inhibition of complex I, which benefits cells by rebalancing redox cofactors, increasing reductive carboxylation, and promoting glycolysis. Perhaps paradoxically, certain forms of mitochondrial dysfunction may best be buffered with "second site" inhibitors to the organelle.

Bayesian inference of metabolic kinetics from genome-scale multiomics data

Modern biological tools generate a wealth of data on metabolite and protein concentrations that can be used to help inform new strain designs. However, learning from these data to predict how a cell will respond to genetic changes, a key need for engineering, remains challenging. A promising technique for leveraging omics measurements in metabolic modeling involves the construction of kinetic descriptions of the enzymatic reactions that occur within a cell. Parameterizing these models from biological data can be computationally difficult, since methods must also quantify the uncertainty in model parameters resulting from the observed data. While the field of Bayesian inference offers a wide range of methods for efficiently estimating distributions in parameter uncertainty, such techniques are poorly suited to traditional kinetic models due to their complex rate laws and resulting nonlinear dynamics. In this paper, we employ linear-logarithmic kinetics to simplify the calculation of steady-state flux distributions and enable efficient sampling and inference methods. We demonstrate that detailed information on the posterior distribution of parameters can be obtained efficiently at a variety of problem scales, including nearly genome-scale kinetic models trained on multiomics datasets. These results allow modern Bayesian machine learning tools to be leveraged in understanding biological data and in developing new, efficient strain designs.

Metabolic perturbations in mutants of glucose transporters and their applications in metabolite production in Escherichia coli

BACKGROUND

Most microorganisms have evolved to maximize growth rate, with rapid consumption of carbon sources from the surroundings. However, fast growing phenotypes usually feature secretion of organic compounds. For example, E. coli mainly produced acetate in fast growing condition such as glucose rich and aerobic condition, which is troublesome for metabolic engineering because acetate causes acidification of surroundings, growth inhibition and decline of production yield. The overflow metabolism can be alleviated by reducing glucose uptake rate.

RESULTS

As glucose transporters or their subunits were knocked out in E. coli, the growth and glucose uptake rates decreased and biomass yield was improved. Alteration of intracellular metabolism caused by the mutations was investigated with transcriptome analysis and 13C metabolic flux analysis (13C MFA). Various transcriptional and metabolic perturbations were identified in the sugar transporter mutants. Transcription of genes related to glycolysis, chemotaxis, and flagella synthesis was downregulated, and that of gluconeogenesis, Krebs cycle, alternative transporters, quorum sensing, and stress induced proteins was upregulated in the sugar transporter mutants. The specific production yields of value-added compounds (enhanced green fluorescent protein, γ-aminobutyrate, lycopene) were improved significantly in the sugar transporter mutants.

CONCLUSIONS

The elimination of sugar transporter resulted in alteration of global gene expression and redirection of carbon flux distribution, which was purposed to increase energy yield and recycle carbon sources. When the pathways for several valuable compounds were introduced to mutant strains, specific yield of them were highly improved. These results showed that controlling the sugar uptake rate is a good strategy for ameliorating metabolite production.

Adaptation to mutational inactivation of an essential gene converges to an accessible suboptimal fitness peak

The mechanisms of adaptation to inactivation of essential genes remain unknown. Here we inactivate E. coli dihydrofolate reductase (DHFR) by introducing D27G,N,F chromosomal mutations in a key catalytic residue with subsequent adaptation by an automated serial transfer protocol. The partial reversal G27- > C occurred in three evolutionary trajectories. Conversely, in one trajectory for D27G and in all trajectories for D27F,N strains adapted to grow at very low metabolic supplement (folAmix) concentrations but did not escape entirely from supplement auxotrophy. Major global shifts in metabolome and proteome occurred upon DHFR inactivation, which were partially reversed in adapted strains. Loss-of-function mutations in two genes, thyA and deoB, ensured adaptation to low folAmix by rerouting the 2-Deoxy-D-ribose-phosphate metabolism from glycolysis towards synthesis of dTMP. Multiple evolutionary pathways of adaptation converged to a suboptimal solution due to the high accessibility to loss-of-function mutations that block the path to the highest, yet least accessible, fitness peak.

Predicting how viruses and bacteria evolve remains a challenge. The ability to anticipate when and how bacteria might develop drug resistance would make treating life-threatening diseases easier and could potentially help prevent drug resistance altogether. Studying bacterial evolution under different conditions and cataloguing all possible DNA mutations that allow these bacteria to survive are crucial steps in predicting the appearance of drug resistance.

Studies have revealed that bacteria can adapt to sources of stress, such as antibiotics, in different ways – each involving mutations in distinct genes. However, not all the mutations provide the same benefits to the organism, and the factors that influence how bacteria will adapt are unclear.

Now, Rodrigues and Shakhnovich have used a new approach to push the adaptation ability of the bacterium Escherichia coli to the limit. First, they genetically engineered different E. coli strains by introducing distinct mutations to an enzyme the bacterium needs to make DNA. These mutations make the resulting strains dependent on external molecules to synthesize new DNA. Next, the cells were grown in conditions where the supply of these DNA precursors was progressively decreased, forcing them to adapt. The obvious way for bacteria to adapt to these conditions would be to ‘revert’ the mutations that Rodrigues and Shakhnovich introduced in the first place. By using this approach, Rodrigues and Shakhnovich were able to test how often the obvious evolutionary solution happens compared with presumably less-preferred alternative routes.

In rare cases, a specific mutation did restore the activity of the enzyme that enabled DNA synthesis. However, in most cases the bacteria found a different evolutionary solution whereby they all adapt to the decrease in external DNA precursors in the same way, but not by reverting the original mutation. Instead, further mutations disrupt the activity of two metabolic genes, allowing the cells to use the external DNA precursors more efficiently, and keep building DNA. These cells are therefore able to survive even when the levels of the external DNA components are very low, but they will die in the complete absence of these precursor molecules.

This evolutionary solution leads to a non-optimal effect: mutations that restore the activity of the original enzyme, which are the best solution when the two metabolic genes are intact, are no longer as effective. This finding represents a clear example of interactions between genes determining evolutionary outcomes. Rodrigues and Shakhnovich showed that, since it is more likely for a random mutation to disrupt a gene than to revert a previous mutation, adaptations that are less-than-optimal but still work might predominate simply because they happen faster.

Understanding why certain evolutionary adaptations prevail is an important step in predicting evolution and may lead to breakthroughs in many areas. For example, if scientists can identify mutations likely to make bacteria resistant to drugs, it may be possible to act proactively against the bacterial strains that carry those mutations. Eventually, if the factors that lead to specific adaptations are known, it may be possible to exploit this knowledge to create weaknesses in the bacteria’s own defences.

High-resolution 13C metabolic flux analysis

Precise quantification of metabolic pathway fluxes in biological systems is of major importance in guiding efforts in metabolic engineering, biotechnology, microbiology, human health, and cell culture. ¹³C metabolic flux analysis (¹³C-MFA) is the predominant technique used for determining intracellular fluxes. Here, we present a protocol for ¹³C-MFA that incorporates recent advances in parallel labeling experiments, isotopic labeling measurements, and statistical analysis, as well as best practices developed through decades of experience. Experimental design to ensure that fluxes are estimated with the highest precision is an integral part of the protocol. The protocol is based on growing microbes in two (or more) parallel cultures with ¹³C-labeled glucose tracers, followed by gas chromatography-mass spectrometry (GC-MS) measurements of isotopic labeling of protein-bound amino acids, glycogen-bound glucose, and RNA-bound ribose. Fluxes are then estimated using software for ¹³C-MFA, such as Metran, followed by comprehensive statistical analysis to determine the goodness of fit and calculate confidence intervals of fluxes. The presented protocol can be completed in 4 d and quantifies metabolic fluxes with a standard deviation of ≤2%, a substantial improvement over previous implementations. The presented protocol is exemplified using an Escherichia coli ΔtpiA case study with full supporting data, providing a hands-on opportunity to step through a complex troubleshooting scenario. Although applications to prokaryotic microbial systems are emphasized, this protocol can be easily adjusted for application to eukaryotic organisms.

Redox rebalance against genetic perturbations and modulation of central carbon metabolism by the oxidative stress regulation

The micro-aerophilic organisms and aerobes as well as yeast and higher organisms have evolved to gain energy through respiration (via oxidative phosphorylation), thereby enabling them to grow much faster than anaerobes. However, during respiration, reactive oxygen species (ROSs) are inherently (inevitably) generated, and threaten the cell's survival. Therefore, living organisms (or cells) must furnish the potent defense systems to keep such ROSs at harmless level, where the cofactor balance plays crucial roles. Namely, NADH is the source of energy generation (catabolism) in the respiratory chain reactions, through which ROSs are generated, while NADPH plays important roles not only for the cell synthesis (anabolism) but also for detoxifying ROSs. Therefore, the cell must rebalance the redox ratio by modulating the fluxes of the central carbon metabolism (CCM) by regulating the multi-level regulation machinery upon genetic perturbations and the change in the growth conditions. Here, we discuss about how aerobes accomplish such cofactor homeostasis against redox perturbations. In particular, we consider how single-gene mutants (including pgi, pfk, zwf, gnd and pyk mutants) modulate their metabolisms in relation to cofactor rebalance (and also by adaptive laboratory evolution). We also discuss about how the overproduction of NADPH (by the pathway gene mutation) can be utilized for the efficient production of useful value-added chemicals such as medicinal compounds, polyhydroxyalkanoates, and amino acids, all of which require NADPH in their synthetic pathways. We then discuss about the metabolic responses against oxidative stress, where αketoacids play important roles not only for the coordination between catabolism and anabolism, but also for detoxifying ROSs by non-enzymatic reactions, as well as for reducing the production of ROSs by repressing the activities of the TCA cycle and respiration (via carbon catabolite repression). Thus, we discuss about the mechanisms (basic strategies) that modulate the metabolism from respiration to respiro-fermentative metabolism causing overflow, based on the role of Pyk activity, affecting the NADPH production at the oxidative pentose phosphate (PP) pathway, and the roles of αketoacids for the change in the source of energy generation from the oxidative phosphorylation to the substrate level phosphorylation.

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.

The emergence of adaptive laboratory evolution as an efficient tool for biological discovery and industrial biotechnology

Harnessing the process of natural selection to obtain and understand new microbial phenotypes has become increasingly possible due to advances in culturing techniques, DNA sequencing, bioinformatics, and genetic engineering. Accordingly, Adaptive Laboratory Evolution (ALE) experiments represent a powerful approach both to investigate the evolutionary forces influencing strain phenotypes, performance, and stability, and to acquire production strains that contain beneficial mutations. In this review, we summarize and categorize the applications of ALE to various aspects of microbial physiology pertinent to industrial bioproduction by collecting case studies that highlight the multitude of ways in which evolution can facilitate the strain construction process. Further, we discuss principles that inform experimental design, complementary approaches such as computational modeling that help maximize utility, and the future of ALE as an efficient strain design and build tool driven by growing adoption and improvements in automation.

Developing a pyruvate-driven metabolic scenario for growth-coupled microbial production

Microbial-based chemical synthesis serves as a promising approach for sustainable production of industrially important products. However, limited production performance caused by metabolic burden or genetic variations poses one of the major challenges in achieving an economically viable biomanufacturing process. To address this issue, one superior strategy is to couple the product synthesis with cellular growth, which renders production obligatory for cell survival. Here we create a pyruvate-driven metabolic scenario in engineered Escherichia coli for growth-coupled bioproduction, with which we demonstrate its application in boosting production of anthranilate and its derivatives. Deletion of a minimal set of endogenous pyruvate-releasing pathways engenders anthranilate synthesis as the salvage route for pyruvate generation to support cell growth, concomitant with simultaneous anthranilate production. Further introduction of native and non-native downstream pathways affords production enhancement of two anthranilate-derived high-value products including L-tryptophan and cis, cis-muconic acid from different carbon sources. The work reported here presents a new growth-coupled strategy with demonstrated feasibility for promoting microbial production.

Reconstruction of metabolic pathway for isobutanol production in Escherichia coli

Background

The microbial production of useful fuels and chemicals has been widely studied. In several cases, glucose is used as the raw material, and almost all microbes adopt the Embden–Meyerhof (EM) pathway to degrade glucose into compounds of interest. Recently, the Entner–Doudoroff (ED) pathway has been gaining attention as an alternative strategy for microbial production.

Results

In the present study, we attempted to apply the ED pathway for isobutanol production in Escherichia coli because of the complete redox balance involved. First, we generated ED pathway-dependent isobutanol-producing E. coli. Thereafter, the inactivation of the genes concerning organic acids as the byproducts was performed to improve the carbon flux to isobutanol from glucose. Finally, the expression of the genes concerning the ED pathway was modified.

Conclusions

The optimized isobutanol-producing E. coli produced 15.0 g/L of isobutanol as the final titer, and the yield from glucose was 0.37 g/g (g-glucose/g-isobutanol).

Electronic supplementary material

The online version of this article (10.1186/s12934-019-1171-4) contains supplementary material, which is available to authorized users.

Theophylline-inducible riboswitch accurately regulates protein expression at low level in Escherichia coli

OBJECTIVES

Fine-tuning of enzyme expression at low levels is an important challenge for metabolic engineers. Here, theophylline-inducible riboswitch for translational regulation was evaluated. The background expression, translation rate, and time delay for its induction was reported.

RESULTS

To evaluate the effect of the amount of mRNA on its translation rate, transcription of the riboswitch RNA with red fluorescent protein (RFP) was controlled by the lac system with addition of isopropyl β-D-1-thiogalactopyranoside in Escherichia coli. Regardless of the amount of riboswitch mRNA, the translation of RFP was completely suppressed without theophylline during both growth and stationary phases. Furthermore, a strong positive correlation between theophylline concentration (0 to 1 mM) and specific RFP production rate was observed. The specific RFP production rate with the riboswitch was approximately 2.3% of that without the riboswitch. Furthermore, 60 min of time delay for RFP expression was observed after adding theophylline during the stationary phase.

CONCLUSION

Theophylline-inducible riboswitch precisely controls protein translation at low expression levels with significantly low background expression. It can emerge as a powerful tool for fine tuning of enzyme expression.

LC-MS/MS-based metabolic profiling of Escherichia coli under heterologous gene expression stress

Escherichia coli is frequently exploited for genetic manipulations and heterologous gene expression studies. We have evaluated the metabolic profile of E. coli strain BL21 (DE3) RIL CodonPlus after genetic modifications and subjecting to the production of recombinant protein. Three genetically variable E. coli cell types were studied, normal cells (susceptible to antibiotics) cultured in simple LB medium, cells harboring ampicillin-resistant plasmid pET21a (+), grown under antibiotic stress, and cells having recombinant plasmid pET21a (+) ligated with bacterial lactate dehydrogenase gene grown under ampicillin and standard isopropyl thiogalactoside (IPTG)-induced gene expression conditions. A total of 592 metabolites were identified through liquid chromatography-mass spectrometry/mass spectrometry analysis, feature and peak detection using XCMS and CAMERA followed by precursor identification by METLIN-based procedures. Overall, 107 metabolites were found differentially regulated among genetically modified cells. Quantitative analysis has shown a significant modulation in DHNA-CoA, p-aminobenzoic acid, and citrulline levels, indicating an alteration in vitamin K, folic acid biosynthesis, and urea cycle of E. coli cells during heterologous gene expression. Modulations in energy metabolites including NADH, AMP, ADP, ATP, carbohydrate, terpenoids, fatty acid metabolites, diadenosine tetraphosphate (Ap4A), and l-carnitine advocate major metabolic rearrangements. Our study provides a broader insight into the metabolic adaptations of bacterial cells during gene manipulation experiments that can be prolonged to improve the yield of heterologous gene products and concomitant production of valuable biomolecules.

Designing Metabolic Division of Labor in Microbial Communities

Microbes face a trade-off between being metabolically independent and relying on neighboring organisms for the supply of some essential metabolites. This balance of conflicting strategies affects microbial community structure and dynamics, with important implications for microbiome research and synthetic ecology. A "gedanken" (thought) experiment to investigate this trade-off would involve monitoring the rise of mutual dependence as the number of metabolic reactions allowed in an organism is increasingly constrained. The expectation is that below a certain number of reactions, no individual organism would be able to grow in isolation and cross-feeding partnerships and division of labor would emerge. We implemented this idealized experiment using in silico genome-scale models. In particular, we used mixed-integer linear programming to identify trade-off solutions in communities of Escherichia coli strains. The strategies that we found revealed a large space of opportunities in nuanced and nonintuitive metabolic division of labor, including, for example, splitting the tricarboxylic acid (TCA) cycle into two separate halves. The systematic computation of possible solutions in division of labor for 1-, 2-, and 3-strain consortia resulted in a rich and complex landscape. This landscape displayed a nonlinear boundary, indicating that the loss of an intracellular reaction was not necessarily compensated for by a single imported metabolite. Different regions in this landscape were associated with specific solutions and patterns of exchanged metabolites. Our approach also predicts the existence of regions in this landscape where independent bacteria are viable but are outcompeted by cross-feeding pairs, providing a possible incentive for the rise of division of labor. IMPORTANCE Understanding how microbes assemble into communities is a fundamental open issue in biology, relevant to human health, metabolic engineering, and environmental sustainability. A possible mechanism for interactions of microbes is through cross-feeding, i.e., the exchange of small molecules. These metabolic exchanges may allow different microbes to specialize in distinct tasks and evolve division of labor. To systematically explore the space of possible strategies for division of labor, we applied advanced optimization algorithms to computational models of cellular metabolism. Specifically, we searched for communities able to survive under constraints (such as a limited number of reactions) that would not be sustainable by individual species. We found that predicted consortia partition metabolic pathways in ways that would be difficult to identify manually, possibly providing a competitive advantage over individual organisms. In addition to helping understand diversity in natural microbial communities, our approach could assist in the design of synthetic consortia.

Identification of growth-coupled production strains considering protein costs and kinetic variability

Conversion of renewable biomass to useful molecules in microbial cell factories can be approached in a rational and systematic manner using constraint-based reconstruction and analysis. Filtering for high confidence in silico designs is critical because in vivo construction and testing of strains is expensive and time consuming. As such, a workflow was devised to analyze the robustness of growth-coupled production when considering the biosynthetic costs of the proteome and variability in enzyme kinetic parameters using a genome-scale model of metabolism and gene expression (ME-model). A collection of 2632 unfiltered knockout designs in Escherichia coli was evaluated by the workflow. A ME-model was used in the workflow to test the designs' growth-coupled production in addition to a less complex genome-scale metabolic model (M-model). The workflow identified 634 M-model growth-coupled designs which met the filtering criteria and 42 robust designs, which met growth-coupled production criteria using both M and ME-models. Knockouts were found to follow a pattern of controlling intermediate metabolite consumption such as pyruvate consumption and high flux subsystems such as glycolysis. Kinetic parameter sampling using the ME-model revealed how enzyme efficiency and pathway tradeoffs can affect growth-coupled production phenotypes.

How adaptive evolution reshapes metabolism to improve fitness: recent advances and future outlook

Adaptive laboratory evolution (ALE) has emerged as a powerful tool in basic microbial research and strain development. In the context of metabolic science and engineering, it has been applied to study gene knockout responses, expand substrate ranges, improve tolerance to process conditions, and to improve productivity via designed growth coupling. In recent years, advancements in ALE methods and systems biology measurement technologies, particularly genome sequencing and ¹³C metabolic flux analysis (¹³C-MFA), have enabled detailed study of the mechanisms and dynamics of evolving metabolism. In this review, we discuss a range of studies that have applied flux analysis to adaptively evolved strains, as well as modeling frameworks developed to predict and interpret evolved fluxes. These efforts link mutations to fitness-enhanced phenotypes, identify bottlenecks and approaches to resolve them, and address systems concepts such as optimality.