Fast growth phenotype of E. coli K-12 from adaptive laboratory evolution does not require intracellular flux rewiring

Model-guided metabolic rewiring to bypass pyruvate oxidation for pyruvate derivative synthesis by minimizing carbon loss

Engineering microbial hosts to synthesize pyruvate derivatives depends on blocking pyruvate oxidation, thereby causing severe growth defects in aerobic glucose-based bioprocesses. To decouple pyruvate metabolism from cell growth to improve pyruvate availability, a genome-scale metabolic model combined with constraint-based flux balance analysis, geometric flux balance analysis, and flux variable analysis was used to identify genetic targets for strain design. Using translation elements from a ~3,000 cistronic library to modulate fxpK expression in a bicistronic cassette, a bifido shunt pathway was introduced to generate three molecules of non-pyruvate-derived acetyl-CoA from one molecule of glucose, bypassing pyruvate oxidation and carbon dioxide generation. The dynamic control of flux distribution by T7 RNAP-mediated synthetic small RNA decoupled pyruvate catabolism from cell growth. Adaptive laboratory evolution and multi-omics analysis revealed that a mutated isocitrate dehydrogenase functioned as a metabolic switch to activate the glyoxylate shunt as the only C4 anaplerotic pathway to generate malate from two molecules of acetyl-CoA input and bypass two decarboxylation reactions in the tricarboxylic acid cycle. A chassis strain for pyruvate derivative synthesis was constructed to reduce carbon loss by using the glyoxylate shunt as the only C4 anaplerotic pathway and the bifido shunt as a non-pyruvate-derived acetyl-CoA synthetic pathway and produced 22.46, 27.62, and 6.28 g/L of l-leucine, l-alanine, and l-valine by a controlled small RNA switch, respectively. Our study establishes a novel metabolic pattern of glucose-grown bacteria to minimize carbon loss under aerobic conditions and provides valuable insights into cell design for manufacturing pyruvate-derived products.IMPORTANCEBio-manufacturing from biomass-derived carbon sources using microbes as a cell factory provides an eco-friendly alternative to petrochemical-based processes. Pyruvate serves as a crucial building block for the biosynthesis of industrial chemicals; however, it is different to improve pyruvate availability in vivo due to the coupling of pyruvate-derived acetyl-CoA with microbial growth and energy metabolism via the oxidative tricarboxylic acid cycle. A genome-scale metabolic model combined with three algorithm analyses was used for strain design. Carbon metabolism was reprogrammed using two genetic control tools to fine-tune gene expression. Adaptive laboratory evolution and multi-omics analysis screened the growth-related regulatory targets beyond rational design. A novel metabolic pattern of glucose-grown bacteria is established to maintain growth fitness and minimize carbon loss under aerobic conditions for the synthesis of pyruvate-derived products. This study provides valuable insights into the design of a microbial cell factory for synthetic biology to produce industrial bio-products of interest.

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.

A robust yeast chassis: comprehensive characterization of a fast-growing Saccharomyces cerevisiae

Robust chassis are critical to facilitate advances in synthetic biology. This study describes a comprehensive characterization of a new yeast isolate Saccharomyces cerevisiae XP that grows faster than commonly used research and industrial S. cerevisiae strains. The genomic, transcriptomic, and metabolomic analyses suggest that the fast growth rate is, in part, due to the efficient electron transport chain and key growth factor synthesis. A toolbox for genetic manipulation of the yeast was developed; we used it to construct l-lactic acid producers for high lactate production. The development of genetically malleable yeast strains that grow faster than currently used strains may significantly enhance the uses of S. cerevisiae in biotechnology.IMPORTANCEYeast is known as an outstanding starting strain for constructing microbial cell factories. However, its growth rate restricts its application. A yeast strain XP, which grows fast in high concentrations of sugar and acidic environments, is revealed to demonstrate the potential in industrial applications. A toolbox was also built for its genetic manipulation including gene insertion, deletion, and ploidy transformation. The knowledge of its metabolism, which could guide the designing of genetic experiments, was generated with multi-omics analyses. This novel strain along with its toolbox was then tested by constructing an l-lactic acid efficient producer, which is conducive to the development of degradable plastics. This study highlights the remarkable competence of nonconventional yeast for applications in biotechnology.

Expanding Pseudomonas taiwanensis VLB120's acyl-CoA portfolio: Propionate production in mineral salt medium

As one of the main precursors, acetyl-CoA leads to the predominant production of even-chain products. From an industrial biotechnology perspective, extending the acyl-CoA portfolio of a cell factory is vital to producing industrial relevant odd-chain alcohols, acids, ketones and polyketides. The bioproduction of odd-chain molecules can be facilitated by incorporating propionyl-CoA into the metabolic network. The shortest pathway for propionyl-CoA production, which relies on succinyl-CoA catabolism encoded by the sleeping beauty mutase operon, was evaluated in Pseudomonas taiwanensis VLB120. A single genomic copy of the sleeping beauty mutase genes scpA, argK and scpB combined with the deletion of the methylcitrate synthase PVLB_08385 was sufficient to observe propionyl-CoA accumulation in this Pseudomonas. The chassis' capability for odd-chain product synthesis was assessed by expressing an acyl-CoA hydrolase, which enabled propionate synthesis. Three fed-batch strategies during bioreactor fermentations were benchmarked for propionate production, in which a maximal propionate titre of 2.8 g L-1 was achieved. Considering that the fermentations were carried out in mineral salt medium under aerobic conditions and that a single genome copy drove propionyl-CoA production, this result highlights the potential of Pseudomonas to produce propionyl-CoA derived, odd-chain products.

Integrating gene expression data into a genome-scale metabolic model to identify reprogramming during adaptive evolution

The development of a method for identifying latent reprogramming in gene expression data resulting from adaptive laboratory evolution (ALE) in response to genetic or environmental perturbations has been a challenge. In this study, a method called Metabolic Reprogramming Identifier (MRI), based on the integration of expression data to a genome-scale metabolic model has been developed. To identify key genes playing the main role in reprogramming, a MILP problem is presented and maximization of an adaptation score as a criterion indicating a pattern of using metabolism with maximum utilization of gene expression resources is defined as an objective function. Then, genes with complete expression usage and significant expression differences between wild-type and evolved strains were selected as key genes for reprogramming. This score is also applied to evaluate the compatibility of expression patterns with maximal use of key genes. The method was implemented to investigate the reprogramming of Escherichia coli during adaptive evolution caused by changing carbon sources. cyoC and cydB responsible for establishing proton gradient across the inner membrane were identified to be vital in the E. coli reprogramming when switching from glucose to lactate. These results indicate the importance of the inner membrane in reprogramming of E. coli to adapt to the new environment. The method predicts no reprogramming occurs during the evolution for growth on glycerol.

H+-Translocating Membrane-Bound Pyrophosphatase from Rhodospirillum rubrum Fuels Escherichia coli Cells via an Alternative Pathway for Energy Generation

Inorganic pyrophosphatases (PPases) catalyze an essential reaction, namely, the hydrolysis of PP_i, which is formed in large quantities as a side product of numerous cellular reactions. In the majority of living species, PP_i hydrolysis is carried out by soluble cytoplasmic PPase (S-PPases) with the released energy dissipated in the form of heat. In Rhodospirillum rubrum, part of this energy can be conserved by proton-pumping pyrophosphatase (H⁺-PPase^Rru) in the form of a proton electrochemical gradient for further ATP synthesis. Here, the codon-harmonized gene hppa^Rru encoding H⁺-PPase^Rru was expressed in the Escherichia coli chromosome. We demonstrate, for the first time, that H⁺-PPase^Rru complements the essential native S-PPase in E. coli cells. ¹³C-MFA confirmed that replacing native PPase to H⁺-PPase^Rru leads to the re-distribution of carbon fluxes; a statistically significant 36% decrease in tricarboxylic acid (TCA) cycle fluxes was found compared with wild-type E. coli MG1655. Such a flux re-distribution can indicate the presence of an additional method for energy generation (e.g., ATP), which can be useful for the microbiological production of a number of compounds, the biosynthesis of which requires the consumption of ATP.

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.

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.

Selection for Cell Yield Does Not Reduce Overflow Metabolism in Escherichia coli

Overflow metabolism is ubiquitous in nature, and it is often considered inefficient because it leads to a relatively low biomass yield per consumed carbon. This metabolic strategy has been described as advantageous because it supports high growth rates during nutrient competition. Here, we experimentally evolved bacteria without nutrient competition by repeatedly growing and mixing millions of parallel batch cultures of Escherichia coli. Each culture originated from a water-in-oil emulsion droplet seeded with a single cell. Unexpectedly we found that overflow metabolism (acetate production) did not change. Instead, the numerical cell yield during the consumption of the accumulated acetate increased as a consequence of a reduction in cell size. Our experiments and a mathematical model show that fast growth and overflow metabolism, followed by the consumption of the overflow metabolite, can lead to a higher numerical cell yield and therefore a higher fitness compared with full respiration of the substrate. This provides an evolutionary scenario where overflow metabolism can be favorable even in the absence of nutrient competition.

Kinetic analysis and modeling of L-valine production in fermentation batch from E. coli using glucose, lactose and whey as carbon sources

In this study the effect of the carbon source on L-valine production kinetics using genetically modified E. coli was researched. Glucose, lactose, Whey (W) and deproteinized whey (DW) were tested as carbon sources, keeping the carbon/nitrogen (C/N) ratio constant. Biomass generation and substrate consumption were modeled with Contois and Mass Conservation models, respectively, whereas Mass Conservation Balance and Luedeking-Piret models were used for product obtaining. Results showed that L-valine production is partially associated to growth, with values of 0.485 g L-valine/(g dry cell weight.h), and a product loss effect at a specific rate (β) of 0.019 g L-valine/(g dry cell weight.h) with W. The yield of this product increased 36 % using W concerning glucose or lactose as carbon sources. On the other hand, Mass Balance and Luedeking-Piret models adjust properly to experimental data (R2 >0.90). In conclusion whey is a promising substrate for obtaining L-valine using genetically-modified E. coli.

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.

Bacterial fitness landscapes stratify based on proteome allocation associated with discrete aero-types

The fitness landscape is a concept commonly used to describe evolution towards optimal phenotypes. It can be reduced to mechanistic detail using genome-scale models (GEMs) from systems biology. We use recently developed GEMs of Metabolism and protein Expression (ME-models) to study the distribution of Escherichia coli phenotypes on the rate-yield plane. We found that the measured phenotypes distribute non-uniformly to form a highly stratified fitness landscape. Systems analysis of the ME-model simulations suggest that this stratification results from discrete ATP generation strategies. Accordingly, we define "aero-types", a phenotypic trait that characterizes how a balanced proteome can achieve a given growth rate by modulating 1) the relative utilization of oxidative phosphorylation, glycolysis, and fermentation pathways; and 2) the differential employment of electron-transport-chain enzymes. This global, quantitative, and mechanistic systems biology interpretation of fitness landscape formed upon proteome allocation offers a fundamental understanding of bacterial physiology and evolution dynamics.

Random Chromosomal Integration and Screening Yields E. coli K-12 Derivatives Capable of Efficient Sucrose Utilization

Chromosomal expression of heterologous genes offers stability and maintenance advantages over episomal expression, yet remains difficult to optimize through site-specific integration. The challenge has in large part been due to the variability of chromosomal gene expression, which has only recently been shown to be affected by multiple factors, including the local genomic context. In this work we utilize Tn5 transposase to randomly integrate a three-gene csc operon encoding nonphosphotransferase sucrose catabolism into the E. coli K-12 chromosome. Isolates from the transposon library yielded a range of growth rates on sucrose as the sole carbon source, including some that were comparable to that of E. coli K-12 on glucose (μ_max = 0.70 ± 0.03 h^-1). Narrowness of the growth rate distributions and faster growth compared to plasmids indicate that efficient csc expression is attainable. Furthermore, enhanced growth rate upon transduction into strains that underwent adaptive laboratory evolution indicate that sucrose catabolism is not limiting to cellular growth. We also show that transduction of a csc fast-growth locus into an isobutanol production strain yields high titer (7.56 ± 0.25 g/L) on sucrose as the sole carbon source. Our results demonstrate that random integration is an effective strategy for optimizing heterologous expression within the context of cellular metabolism for both fast growth and biochemical production phenotypes.

Prokaryotic life finds a way: insights from evolutionary experimentation in bacteria

While evolution proceeds through the generation of random variant alleles, the application of selective pressures can select for subsets of mutations that confer fitness-improving physiological benefits. This, in essence, defines the process of adaptive evolution. The rapid replication rate of bacteria has allowed for the design of experiments to study these processes over a reasonable timeframe within a laboratory setting. This has been greatly assisted by advances in tractability of diverse microorganisms, next generation sequencing technologies and bioinformatic analysis pipelines. Examining the processes by which organisms adapt their genetic code to cope with sub-optimal growth conditions has yielded a wealth of molecular insight into diverse biological processes. Here we discuss how the study of adaptive evolutionary trajectories in bacteria has allowed for improved understanding of stress responses, revealed important insight into microbial physiology, allowed for the production of highly optimised strains for use in biotechnology and increased our knowledge of the role of genomic plasticity in chronic infections.

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.

Evolution of an Escherichia coli PTS- strain: a study of reproducibility and dynamics of an adaptive evolutive process

Adaptive laboratory evolution (ALE) has been used to study and solve pressing questions about evolution, especially for the study of the development of mutations that confer increased fitness during evolutionary processes. In this contribution, we investigated how the evolutionary process conducted with the PTS^- mutant of Escherichia coli PB11 in three parallel batch cultures allowed the restoration of rapid growth with glucose as the carbon source. The significant findings showed that genomic sequence analysis of a set of newly evolved mutants isolated from ALE experiments 2-3 developed some essential mutations, which efficiently improved the fast-growing phenotypes throughout different fitness landscapes. Regulator galR was the target of several mutations such as SNPs, partial and total deletions, and insertion of an IS1 element and thus indicated the relevance of a null mutation of this gene in the adaptation of the evolving population of PB11 during the parallel ALE experiments. These mutations resulted in the selection of MglB and GalP as the primary glucose transporters by the evolving population, but further selection of at least a second adaptive mutation was also necessary. We found that mutations in the yfeO, rppH, and rng genes improved the fitness advantage of evolving PTS^- mutants and resulted in amplification of leaky activity in Glk for glucose phosphorylation and upregulation of glycolytic and other growth-related genes. Notably, we determined that these mutations appeared and were fixed in the evolving populations between 48 and 72 h of cultivation, which resulted in the selection of fast-growing mutants during one ALE experiments in batch cultures of 80 h duration.Key points• ALE experiments selected evolved mutants through different fitness landscapes in which galR was the target of different mutations: SNPs, deletions, and insertion of IS.• Key mutations in evolving mutants appeared and fixed at 48-72 h of cultivation.• ALE experiments led to increased understanding of the genetics of cellular adaptation to carbon source limitation.

Developing rapid growing Bacillus subtilis for improved biochemical and recombinant protein production

Bacillus subtilis is a model Gram-positive bacterium, which has been widely used as industrially important chassis in synthetic biology and metabolic engineering. Rapid growth of chassis is beneficial for shortening the fermentation period and enhancing production of target product. However, engineered B. subtilis with faster growth phenotype is lacking. Here, fast-growing B. subtilis were constructed through rational gene knockout and adaptive laboratory evolution using wild type strain B. subtilis 168 (BS168) as starting strain. Specifically, strains BS01, BS02, and BS03 were obtained through gene knockout of oppD, hag, and flgD genes, respectively, resulting 15.37%, 24.18% and 36.46% increases of specific growth rate compared with BS168. Next, strains A28 and A40 were obtained through adaptive laboratory evolution, whose specific growth rates increased by 39.88% and 43.53% compared to BS168, respectively. Then these two methods were combined via deleting oppD, hag, and flgD genes respectively on the basis of evolved strain A40, yielding strain A4003 with further 7.76% increase of specific growth rate, reaching 0.75 h^-1 in chemical defined M9 medium. Finally, bioproduction efficiency of intracellular product (ribonucleic acid, RNA), extracellular product (acetoin), and recombinant proteins (green fluorescent protein (GFP) and ovalbumin) by fast-growing strain A4003 was tested. And the production of RNA, acetoin, GFP, and ovalbumin increased 38.09%, 5.40%, 9.47% and 19.79% using fast-growing strain A4003 as chassis compared with BS168, respectively. The developed fast-growing B. subtilis strains and strategies used for developing these strains should be useful for improving bioproduction efficiency and constructing other industrially important bacterium with faster growth phenotype.

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Fast-growing Bacillus subtilis were constructed through rational gene knockout and adaptive laboratory evolution.

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Specific growth rate of engineered B. subtilis ​increased 53.06% compared with ​B. subtilis 168, reaching 0.75 h^-1 ​in M9 medium.

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Production of RNA, acetoin, and ovalbumin increased 38.09%, 5.40%, and 19.79% using fast-growing strain as chassis.

A quantitative method for proteome reallocation using minimal regulatory interventions

Engineering resource allocation in biological systems is an ongoing challenge. Organisms allocate resources for ensuring survival, reducing the productivity of synthetic biology functions. Here we present a new approach for engineering the resource allocation of Escherichia coli by rationally modifying its transcriptional regulatory network. Our method (ReProMin) identifies the minimal set of genetic interventions that maximizes the savings in cell resources. To this end, we categorized transcription factors according to the essentiality of its targets and we used proteomic data to rank them. We designed the combinatorial removal of transcription factors that maximize the release of resources. Our resulting strain containing only three mutations, theoretically releasing 0.5% of its proteome, had higher proteome budget, increased production of an engineered metabolic pathway and showed that the regulatory interventions are highly specific. This approach shows that combining proteomic and regulatory data is an effective way of optimizing strains using conventional molecular methods.

Rapid Growth and Metabolism of Uropathogenic Escherichia coli in Relation to Urine Composition

Uropathogenic Escherichia coli (UPEC) strains cause a majority of urinary tract infections (UTIs). Since UPEC strains can become antibiotic resistant, adjunct or alternate therapies are urgently needed. UPEC strains grow extremely rapidly in patients with UTIs. Thus, this review focuses on the relation between urine composition and UPEC growth and metabolism. Compilation of urinary components from two major data sources suggests the presence of sufficient amino acids and carbohydrates as energy sources and abundant phosphorus, sulfur, and nitrogen sources. In a mouse UTI model, mutants lacking enzymes of the tricarboxylic acid cycle, gluconeogenesis, and the nonoxidative branch of the pentose cycle are less competitive than the corresponding parental strains, which is consistent with amino acids as major energy sources. Other evidence suggests that carbohydrates are required energy sources. UPEC strains in urine ex vivo and in vivo express transporters for peptides, amino acids, carbohydrates, and iron and genes associated with nitrogen limitation, amino acid synthesis, nucleotide synthesis, and nucleotide salvage. Mouse models confirm the requirement for many, but not all, of these genes. Laboratory evolution studies suggest that rapid nutrient uptake without metabolic rewiring is sufficient to account for rapid growth. Proteins and pathways required for rapid growth should be considered potential targets for alternate or adjunct therapies.

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.

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.

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.

Generation of an E. coli platform strain for improved sucrose utilization using adaptive laboratory evolution

Background

Sucrose is an attractive industrial carbon source due to its abundance and the fact that it can be cheaply generated from sources such as sugarcane. However, only a few characterized Escherichia coli strains are able to metabolize sucrose, and those that can are typically slow growing or pathogenic strains.

Methods

To generate a platform strain capable of efficiently utilizing sucrose with a high growth rate, adaptive laboratory evolution (ALE) was utilized to evolve engineered E. coli K-12 MG1655 strains containing the sucrose utilizing csc genes (cscB, cscK, cscA) alongside the native sucrose consuming E. coli W.

Results

Evolved K-12 clones displayed an increase in growth and sucrose uptake rates of 1.72- and 1.40-fold on sugarcane juice as compared to the original engineered strains, respectively, while E. coli W clones showed a 1.4-fold increase in sucrose uptake rate without a significant increase in growth rate. Whole genome sequencing of evolved clones and populations revealed that two genetic regions were frequently mutated in the K-12 strains; the global transcription regulatory genes rpoB and rpoC, and the metabolic region related to a pyrimidine biosynthetic deficiency in K-12 attributed to pyrE expression. These two mutated regions have been characterized to confer a similar benefit when glucose is the main carbon source, and reverse engineering revealed the same causal advantages on M9 sucrose. Additionally, the most prevalent mutation found in the evolved E. coli W lineages was the inactivation of the cscR gene, the transcriptional repression of sucrose uptake genes.

Conclusion

The generated K-12 and W platform strains, and the specific sets of mutations that enable their phenotypes, are available as valuable tools for sucrose-based industrial bioproduction in the facile E. coli chassis.

Electronic supplementary material

The online version of this article (10.1186/s12934-019-1165-2) contains supplementary material, which is available to authorized users.

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.

Regulation of glycolytic flux and overflow metabolism depending on the source of energy generation for energy demand

Overflow metabolism is a common phenomenon observed at higher glycolytic flux in many bacteria, yeast (known as Crabtree effect), and mammalian cells including cancer cells (known as Warburg effect). This phenomenon has recently been characterized as the trade-offs between protein costs and enzyme efficiencies based on coarse-graining approaches. Moreover, it has been recognized that the glycolytic flux increases as the source of energy generation changes from energetically efficient respiration to inefficient respiro-fermentative or fermentative metabolism causing overflow metabolism. It is highly desired to clarify the metabolic regulation mechanisms behind such phenomena. Metabolic fluxes are located on top of the hierarchical regulation systems, and represent the outcome of the integrated response of all levels of cellular regulation systems. In the present article, we discuss about the different levels of regulation systems for the modulation of fluxes depending on the growth rate, growth condition such as oxygen limitation that alters the metabolism towards fermentation, and genetic perturbation affecting the source of energy generation from respiration to respiro-fermentative metabolism in relation to overflow metabolism. The intracellular metabolite of the upper glycolysis such as fructose 1,6-bisphosphate (FBP) plays an important role not only for flux sensing, but also for the regulation of the respiratory activity either directly or indirectly (via transcription factors) at higher growth rate. The glycolytic flux regulation is backed up (enhanced) by unphosphorylated EIIA and HPr of the phosphotransferase system (PTS) components, together with the sugar-phosphate stress regulation, where the transcriptional regulation is further modulated by post-transcriptional regulation via the degradation of mRNA (stability of mRNA) in Escherichia coli. Moreover, the channeling may also play some role in modulating the glycolytic cascade reactions.

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.

Enhanced Metabolite Productivity of Escherichia coli Adapted to Glucose M9 Minimal Medium

High productivity of biotechnological strains is important to industrial fermentation processes and can be constrained by precursor availability and substrate uptake rate. Adaptive laboratory evolution (ALE) of Escherichia coli MG1655 to glucose minimal M9 medium has been shown to increase strain fitness, mainly through a key mutation in the transcriptional regulator rpoB, which increases flux through central carbon metabolism and the glucose uptake rate. We wanted to test the hypothesis that a substrate uptake enhancing rpoB mutation can translate to increased productivity in a strain possessing a heterologous metabolite pathway. When engineered for heterologous mevalonate production, we found that E. coli rpoB E672K strains displayed 114–167% higher glucose uptake rates and 48–77% higher mevalonate productivities in glucose minimal M9 medium. This improvement in heterologous mevalonate productivity of the rpoB E672K strain is likely mediated by the elevated glucose uptake rate of such strains, which favors overflow metabolism toward acetate production and availability of acetyl-CoA as precursor. These results demonstrate the utility of adaptive laboratory evolution (ALE) to generate a platform strain for an increased production rate for a heterologous product.

Metabolic network reconstruction and phenome analysis of the industrial microbe, Escherichia coli BL21(DE3)

Escherichia coli BL21(DE3) is an industrial model microbe for the mass-production of bioproducts such as biofuels, biorefineries, and recombinant proteins. However, despite its important role in scientific research and biotechnological applications, a high-quality metabolic network model for metabolic engineering is yet to be developed. Here, we present the comprehensive metabolic network model of E. coli BL21(DE3), named iHK1487, based on the latest genome reannotation and phenome analysis. The metabolic model consists of 1,164 unique metabolites, 2,701 metabolic reactions, and 1,487 genes. The model was validated and improved by comparing the simulation results with phenome data from phenotype microarray tests. Previous transcriptome profile data was incorporated during model reconstruction, and flux prediction was simulated using the model. iHK1487 was simulated to explore the metabolic features of BL21(DE3) such as broad spectrum amino acid utilization and enhanced flux through the upper glycolytic pathway and TCA cycle. iHK1487 will contribute to systematic understanding of cellular physiology and metabolism of E. coli BL21(DE3) and highlight its biotechnological applications.

Metabolic enzyme cost explains variable trade-offs between microbial growth rate and yield

Microbes may maximize the number of daughter cells per time or per amount of nutrients consumed. These two strategies correspond, respectively, to the use of enzyme-efficient or substrate-efficient metabolic pathways. In reality, fast growth is often associated with wasteful, yield-inefficient metabolism, and a general thermodynamic trade-off between growth rate and biomass yield has been proposed to explain this. We studied growth rate/yield trade-offs by using a novel modeling framework, Enzyme-Flux Cost Minimization (EFCM) and by assuming that the growth rate depends directly on the enzyme investment per rate of biomass production. In a comprehensive mathematical model of core metabolism in E. coli, we screened all elementary flux modes leading to cell synthesis, characterized them by the growth rates and yields they provide, and studied the shape of the resulting rate/yield Pareto front. By varying the model parameters, we found that the rate/yield trade-off is not universal, but depends on metabolic kinetics and environmental conditions. A prominent trade-off emerges under oxygen-limited growth, where yield-inefficient pathways support a 2-to-3 times higher growth rate than yield-efficient pathways. EFCM can be widely used to predict optimal metabolic states and growth rates under varying nutrient levels, perturbations of enzyme parameters, and single or multiple gene knockouts.

Modeling the multi-scale mechanisms of macromolecular resource allocation

As microbes face changing environments, they dynamically allocate macromolecular resources to produce a particular phenotypic state. Broad 'omics' data sets have revealed several interesting phenomena regarding how the proteome is allocated under differing conditions, but the functional consequences of these states and how they are achieved remain open questions. Various types of multi-scale mathematical models have been used to elucidate the genetic basis for systems-level adaptations. In this review, we outline several different strategies by which microbes accomplish resource allocation and detail how mathematical models have aided in our understanding of these processes. Ultimately, such modeling efforts have helped elucidate the principles of proteome allocation and hold promise for further discovery.

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

Unraveling the mechanisms of microbial adaptive evolution following genetic or environmental challenges is of fundamental interest in biological science and engineering. When the challenge is the loss of a metabolic enzyme, adaptive responses can also shed significant insight into metabolic robustness, regulation, and areas of kinetic limitation. In this study, whole-genome sequencing and high-resolution ¹³C-metabolic flux analysis were performed on 10 adaptively evolved pgi knockouts of Escherichia coliPgi catalyzes the first reaction in glycolysis, and its loss results in major physiological and carbon catabolism pathway changes, including an 80% reduction in growth rate. Following adaptive laboratory evolution (ALE), the knockouts increase their growth rate by up to 3.6-fold. Through combined genomic-fluxomic analysis, we characterized the mutations and resulting metabolic fluxes that enabled this fitness recovery. Large increases in pyridine cofactor transhydrogenase flux, correcting imbalanced production of NADPH and NADH, were enabled by direct mutations to the transhydrogenase genes sthA and pntAB The phosphotransferase system component crr was also found to be frequently mutated, which corresponded to elevated flux from pyruvate to phosphoenolpyruvate. The overall energy metabolism was found to be strikingly robust, and what have been previously described as latently activated Entner-Doudoroff and glyoxylate shunt pathways are shown here to represent no real increases in absolute flux relative to the wild type. These results indicate that the dominant mechanism of adaptation was to relieve the rate-limiting steps in cofactor metabolism and substrate uptake and to modulate global transcriptional regulation from stress response to catabolism.

Methanol assimilation in Escherichia coli is improved by co-utilization of threonine and deletion of leucine-responsive regulatory protein

Methane, the main component of natural gas, can be used to produce methanol which can be further converted to other valuable products. There is increasing interest in using biological systems for the production of fuels and chemicals from methanol, termed methylotrophy. In this work, we have examined methanol assimilation metabolism in a synthetic methylotrophic E. coli strain. Specifically, we applied ¹³C-tracers and evaluated 25 different co-substrates for methanol assimilation, including amino acids, sugars and organic acids. In particular, co-utilization of threonine significantly enhanced methylotrophy. Through our investigations, we proposed specific metabolic pathways that, when activated, correlated with increased methanol assimilation. These pathways are normally repressed by the leucine-responsive regulatory protein (lrp), a global regulator of metabolism associated with the feast-or-famine response in E. coli. By deleting lrp, we were able to further enhance the methylotrophic ability of our synthetic strain, as demonstrated through increased incorporation of ¹³C carbon from ¹³C-methanol into biomass.

13C metabolic flux analysis of three divergent extremely thermophilic bacteria: Geobacillus sp. LC300, Thermus thermophilus HB8, and Rhodothermus marinus DSM 4252

Thermophilic organisms are being increasingly investigated and applied in metabolic engineering and biotechnology. The distinct metabolic and physiological characteristics of thermophiles, including broad substrate range and high uptake rates, coupled with recent advances in genetic tool development, present unique opportunities for strain engineering. However, poor understanding of the cellular physiology and metabolism of thermophiles has limited the application of systems biology and metabolic engineering tools to these organisms. To address this concern, we applied high resolution 13C metabolic flux analysis to quantify fluxes for three divergent extremely thermophilic bacteria from separate phyla: Geobacillus sp. LC300, Thermus thermophilus HB8, and Rhodothermus marinus DSM 4252. We performed 18 parallel labeling experiments, using all singly labeled glucose tracers for each strain, reconstructed and validated metabolic network models, measured biomass composition, and quantified precise metabolic fluxes for each organism. In the process, we resolved many uncertainties regarding gaps in pathway reconstructions and elucidated how these organisms maintain redox balance and generate energy. Overall, we found that the metabolisms of the three thermophiles were highly distinct, suggesting that adaptation to growth at high temperatures did not favor any particular set of metabolic pathways. All three strains relied heavily on glycolysis and TCA cycle to generate key cellular precursors and cofactors. None of the investigated organisms utilized the Entner-Doudoroff pathway and only one strain had an active oxidative pentose phosphate pathway. Taken together, the results from this study provide a solid foundation for future model building and engineering efforts with these and related thermophiles.

Metabolism of the fast-growing bacterium Vibrio natriegens elucidated by 13C metabolic flux analysis

Vibrio natriegens is a fast-growing, non-pathogenic bacterium that is being considered as the next-generation workhorse for the biotechnology industry. However, little is known about the metabolism of this organism which is limiting our ability to apply rational metabolic engineering strategies. To address this critical gap in current knowledge, here we have performed a comprehensive analysis of V. natriegens metabolism. We constructed a detailed model of V. natriegens core metabolism, measured the biomass composition, and performed high-resolution ¹³C metabolic flux analysis (¹³C-MFA) to estimate intracellular fluxes using parallel labeling experiments with the optimal tracers [1,2-¹³C]glucose and [1,6-¹³C]glucose. During exponential growth in glucose minimal medium, V. natriegens had a growth rate of 1.70 1/h (doubling time of 24min) and a glucose uptake rate of 3.90g/g/h, which is more than two 2-fold faster than E. coli, although slower than the fast-growing thermophile Geobacillus LC300. ¹³C-MFA revealed that the core metabolism of V. natriegens is similar to that of E. coli, with the main difference being a 33% lower normalized flux through the oxidative pentose phosphate pathway. Quantitative analysis of co-factor balances provided additional insights into the energy and redox metabolism of V. natriegens. Taken together, the results presented in this study provide valuable new information about the physiology of V. natriegens and establish a solid foundation for future metabolic engineering efforts with this promising microorganism.