Evolving the L-lysine high-producing strain of Escherichia coli using a newly developed high-throughput screening method

Relieving metabolic burden to improve robustness and bioproduction by industrial microorganisms

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

Recent Advances in Metabolic Engineering for the Biosynthesis of Phosphoenol Pyruvate-Oxaloacetate-Pyruvate-Derived Amino Acids

The phosphoenol pyruvate-oxaloacetate-pyruvate-derived amino acids (POP-AAs) comprise native intermediates in cellular metabolism, within which the phosphoenol pyruvate-oxaloacetate-pyruvate (POP) node is the switch point among the major metabolic pathways existing in most living organisms. POP-AAs have widespread applications in the nutrition, food, and pharmaceutical industries. These amino acids have been predominantly produced in Escherichia coli and Corynebacterium glutamicum through microbial fermentation. With the rapid increase in market requirements, along with the global food shortage situation, the industrial production capacity of these two bacteria has encountered two bottlenecks: low product conversion efficiency and high cost of raw materials. Aiming to push forward the update and upgrade of engineered strains with higher yield and productivity, this paper presents a comprehensive summarization of the fundamental strategy of metabolic engineering techniques around phosphoenol pyruvate-oxaloacetate-pyruvate node for POP-AA production, including L-tryptophan, L-tyrosine, L-phenylalanine, L-valine, L-lysine, L-threonine, and L-isoleucine. Novel heterologous routes and regulation methods regarding the carbon flux redistribution in the POP node and the formation of amino acids should be taken into consideration to improve POP-AA production to approach maximum theoretical values. Furthermore, an outlook for future strategies of low-cost feedstock and energy utilization for developing amino acid overproducers is proposed.

Design of a dual-responding genetic circuit for high-throughput identification of L-threonine-overproducing Escherichia coli

L-threonine is a crucial amino acid that is extensively employed in the realms of food, animal feed and pharmaceuticals. Unfortunately, the lack of an appropriate biosensor has hindered the establishment of a robust high-throughput screening (HTS) system for the identification of the desired strains from random mutants. In this study, a dual-responding genetic circuit that capitalizes on the L-threonine inducer-like effect, the L-threonine riboswitch, and a signal amplification system was designed for the purpose of screening L-threonine overproducers. This platform effectively enhanced the performance of the enzyme and facilitated the identification of high L-threonine-producing strains from a random mutant library. Consequently, pathway optimization and directed evolution of the key enzyme enhanced L-threonine production by 4 and 7-fold, respectively. These results demonstrate the potential of biosensor design for dynamic metabolite detection and offer a promising tool for HTS and metabolic regulation for the development of L-threonine-hyperproducing strains.

Genetically Encoded Biosensor Engineering for Application in Directed Evolution

Although rational genetic engineering is nowadays the favored method for microbial strain improvement, building up mutant libraries based on directed evolution for improvement is still in many cases the better option. In this regard, the demand for precise and efficient screening methods for mutants with high performance has stimulated the development of biosensor-based high-throughput screening strategies. Genetically encoded biosensors provide powerful tools to couple the desired phenotype to a detectable signal, such as fluorescence and growth rate. Herein, we review recent advances in engineering several classes of biosensors and their applications in directed evolution. Furthermore, we compare and discuss the screening advantages and limitations of two-component biosensors, transcription-factor-based biosensors, and RNA-based biosensors. Engineering these biosensors has focused mainly on modifying the expression level or structure of the biosensor components to optimize the dynamic range, specificity, and detection range. Finally, the applications of biosensors in the evolution of proteins, metabolic pathways, and genome-scale metabolic networks are described. This review provides potential guidance in the design of biosensors and their applications in improving the bioproduction of microbial cell factories through directed evolution.

Recent advances in microbial production of diamines, aminocarboxylic acids, and diacids as potential platform chemicals and bio-based polyamides monomers

Recently, bio-based manufacturing processes of value-added platform chemicals and polymers in biorefineries using renewable resources have extensively been developed for sustainable and carbon dioxide (CO₂) neutral-based industry. Among them, bio-based diamines, aminocarboxylic acids, and diacids have been used as monomers for the synthesis of polyamides having different carbon numbers and ubiquitous and versatile industrial polymers and also as precursors for further chemical and biological processes to afford valuable chemicals. Until now, these platform bio-chemicals have successfully been produced by biorefinery processes employing enzymes and/or microbial host strains as main catalysts. In this review, we discuss recent advances in bio-based production of diamines, aminocarboxylic acids, and diacids, which has been developed and improved by systems metabolic engineering strategies of microbial consortia and optimization of microbial conversion processes including whole cell bioconversion and direct fermentative production.

Metabolic engineering of Escherichia coli W3110 for efficient production of homoserine from glucose

Efficient microbial cell factory for the production of homoserine from glucose has been developed by iterative and rational engineering of Escherichia coli W3110. The whole pathway from glucose to homoserine was divided into three groups, namely, glucose transport and glycolysis ('up-stream'), TCA and glyoxylate cycles ('mid-stream'), and homoserine module (conversion of aspartate to homoserine and its secretion; 'down-stream'), and the carbon flux in each group as well as between the groups were accelerated and balanced. Altogether, ∼18 genes were modified for active and consistent production of homoserine during both the actively-growing and non-growing stages of cultivation. Finally, fed-batch, two-stage bioreactor experiments, separating the growth from the production stage, were conducted for 61 h, which gave the high titer of 110.8 g/L, yield of 0.64 g/g glucose and volumetric productivity of 1.82 g/L/h, with an insignificant amount of acetate (<0.5 g/L) as the only noticeable byproduct. The metabolic engineering strategy employed in this study should be applicable for the biosynthesis of other amino acids or chemicals derived from aspartic acid.

MarR-type transcription factor RosR regulates glutamate metabolism network and promotes accumulation of L-glutamate in Corynebacterium glutamicum G01

Transcription factors (TFs) perform a crucial function in the regulation of amino acids biosynthesis. Here, TFs involved in L-glutamate biosynthesis in Corynebacterium glutamicum were investigated. Compared to transcriptomic results of C. glutamicum 13032, 7 TFs regulated to glutamate biosynthesis were indentifed in G01 and E01. Among them, RosR was demonstrated to regulate L-glutamate metabolic network by binding to the promoters of glnA, pqo, ilvB, ilvN, ilvC, ldhA, odhA, dstr1, fas, argJ, ak and pta. Overexpression of RosR in G01 resulted in significantly decreased by-products yield and improved L-glutamate titer (130.6 g/L) and yield (0.541 g/g from glucose) in fed-batch fermentation. This study demonstrated the L-glutamate production improved by the expression of TFs in C. glutamicum, which provided a good reference for the transcriptional regulation engineering of strains for amino acid biosynthesis and suggested further metabolic engineering of C. glutamicum for L-glutamate production.

Intelligent host engineering for metabolic flux optimisation in biotechnology

Optimising the function of a protein of length N amino acids by directed evolution involves navigating a 'search space' of possible sequences of some 20N. Optimising the expression levels of P proteins that materially affect host performance, each of which might also take 20 (logarithmically spaced) values, implies a similar search space of 20P. In this combinatorial sense, then, the problems of directed protein evolution and of host engineering are broadly equivalent. In practice, however, they have different means for avoiding the inevitable difficulties of implementation. The spare capacity exhibited in metabolic networks implies that host engineering may admit substantial increases in flux to targets of interest. Thus, we rehearse the relevant issues for those wishing to understand and exploit those modern genome-wide host engineering tools and thinking that have been designed and developed to optimise fluxes towards desirable products in biotechnological processes, with a focus on microbial systems. The aim throughput is 'making such biology predictable'. Strategies have been aimed at both transcription and translation, especially for regulatory processes that can affect multiple targets. However, because there is a limit on how much protein a cell can produce, increasing kcat in selected targets may be a better strategy than increasing protein expression levels for optimal host engineering.

Expanding the lysine industry: biotechnological production of l-lysine and its derivatives

l-lysine is an essential amino acid that contains various functional groups including α-amino, ω-amino, and α-carboxyl groups, exhibiting high reaction potential. The derivatization of these functional groups produces a series of value-added chemicals, such as cadaverine, glutarate, and d-lysine, that are widely applied in the chemical synthesis, cosmetics, food, and pharmaceutical industries. Here, we review recent advances in the biotechnological production of l-lysine and its derivatives and expatiate key technological strategies. Furthermore, we also discuss the existing challenges and potential strategies for more efficient production of these chemicals.

Isoleucyl-tRNA synthetase mutant based whole-cell biosensor for high-throughput selection of isoleucine overproducers

Whole-cell amino acid biosensors can sense the concentrations of certain amino acids and output easily detectable signals, which are important for construction of microbial producers. However, many reported biosensors have poor specificity because they also sense non-target amino acids. Besides, biosensors for many amino acids are still unavailable. In this study, we proposed a new strategy for constructing whole-cell biosensors based on aminoacyl-tRNA synthetases (aaRSs), which take the advantage of their universality and intrinsically specific binding ability to corresponding amino acids. Taking isoleucine biosensor as an example, we first mutated the isoleucyl-tRNA synthetase in Escherichia coli to dramatically decrease its affinity to isoleucine. The engineered cells specifically sensed isoleucine and output isoleucine dose-dependent cell growth as an easily detectable signal. To further expand the sensing range, an isoleucine exporter was overexpressed to enhance excretion of intracellular isoleucine. Since cells equipped with the optimized whole-cell biosensor showed accelerated growth when cells produced higher concentrations of isoleucine, the biosensor was successfully applied in high-throughput selection of isoleucine overproducers from random mutation libraries. This work demonstrates the feasibility of engineering aaRSs to construct a new kind of whole-cell biosensors for amino acids. Considering all twenty proteinogenic and many non-canonical amino acids have their specific aaRSs, this strategy should be useful for developing biosensors for various amino acids.

A unified design allows fine-tuning of biosensor parameters and application across bacterial species

In recent years, transcriptional biosensors have become valuable tools in metabolic engineering as they allow semiquantitative determination of metabolites in single cells. Although being perfectly suitable tools for high-throughput screenings, application of transcriptional biosensors is often limited by the intrinsic characteristics of the individual sensor components and their interplay. In addition, biosensors often fail to work properly in heterologous host systems due to signal saturation at low intracellular metabolite concentrations, which typically limits their use in high-level producer strains at advanced engineering stages.

We here introduce a biosensor design, which allows fine-tuning of important sensor parameters and restores the sensor response in a heterologous expression host. As a key feature of our design, the regulator activity is controlled through the expression level of the respective gene by different (synthetic) constitutive promoters selected for the used expression host. In this context, we constructed biosensors responding to basic amino acids or ring-hydroxylated phenylpropanoids for applications in Corynebacterium glutamicum and Escherichia coli. Detailed characterization of these biosensors in liquid cultures and during single-cell analysis using flow cytometry showed that the presented sensor design enables customization of important biosensor parameters as well as application of these sensors in relevant heterologous hosts.

•

Development of a unified biosensor design for C. glutamicum and E. coli.

•

Gradual expression of the regulator gene allows for biosensor fine-tuning.

•

Biosensor response in a heterologous host can be restored.

•

Biosensor characterization on the single-cell level prior to FACS is mandatory.

Improving lysine production through construction of an Escherichia coli enzyme-constrained model

Microbial cell factories are widely used for the production of high-value chemicals. However, maximizing production titers is made difficult by the complicated regulatory mechanisms of these cell platforms. Here, k_cat values were incorporated to construct an Escherichia coli enzyme-constrained model. The resulting ec_iML1515 model showed that the protein demand and protein synthesis rate were the key factors affecting lysine production. By optimizing the expression of the 20 top-demanded proteins, lysine titers reached 95.7 ± 0.7 g/L, with a 0.45 g/g glucose yield. Moreover, adjusting NH₄ ⁺ and dissolved oxygen levels to regulate the synthesis rate of energy metabolism-related proteins caused lysine titers and glucose yields to increase to 193.6 ± 1.8 g/L and 0.74 g/g, respectively. The ec_iML1515 model provides insight into how enzymes required for the biosynthesis of certain products are distributed between and within metabolic pathways. This information can be used to accurately predict and rationally design lysine production.

Discovery and identification of medium-chain fatty acid responsive promoters in Saccharomyces cerevisiae

Medium-chain fatty acids (MCFAs) and their derivatives are important chemicals that can be used in lubricants, detergents, and cosmetics. MCFAs can be produced in several microbes, although production is not high. Dynamic regulation by synthetic biology is a good method of improving production of chemicals that avoids toxic intermediates, but chemical-responsive promoters are required. Several MCFA sensors or promoters have been reported in Saccharomyces cerevisiae. In this study, by using transcriptomic analysis of S. cerevisiae exposed to fatty acids with 6-, 12-, and 16-carbon chains, we identified 58 candidate genes that may be responsive to MCFAs. Using a fluorescence-based screening method, we identified MCFA-responsive promoters, four that upregulated gene expression, and three that downregulated gene expression. Dose-response analysis revealed that some of the promoters were sensitive to fatty acid concentrations as low as 0.02-0.06 mM. The MCFA-responsive promoters reported in this study could be used in dynamic regulation of fatty acids and fatty acid-derived products in S. cerevisiae.

Transcription Factor Engineering for High-Throughput Strain Evolution and Organic Acid Bioproduction: A Review

Metabolic regulation of gene expression for the microbial production of fine chemicals, such as organic acids, is an important research topic in post-genomic metabolic engineering. In particular, the ability of transcription factors (TFs) to respond precisely in time and space to various small molecules, signals and stimuli from the internal and external environment is essential for metabolic pathway engineering and strain development. As a key component, TFs are used to construct many biosensors in vivo using synthetic biology methods, which can be used to monitor the concentration of intracellular metabolites in organic acid production that would otherwise remain “invisible” within the intracellular environment. TF-based biosensors also provide a high-throughput screening method for rapid strain evolution. Furthermore, TFs are important global regulators that control the expression levels of key enzymes in organic acid biosynthesis pathways, therefore determining the outcome of metabolic networks. Here we review recent advances in TF identification, engineering, and applications for metabolic engineering, with an emphasis on metabolite monitoring and high-throughput strain evolution for the organic acid bioproduction.

High-Throughput Screening Technology in Industrial Biotechnology

Based on the development of automatic devices and rapid assay methods, various high-throughput screening (HTS) strategies have been established for improving the performance of industrial microorganisms. We discuss the most significant factors that can improve HTS efficiency, including the construction of screening libraries with high diversity and the use of new detection methods to expand the search range and highlight target compounds. We also summarize applications of HTS for enhancing the performance of industrial microorganisms. Current challenges and potential improvements to HTS in industrial biotechnology are discussed in the context of rapid developments in synthetic biology, nanotechnology, and artificial intelligence. Rational integration will be an important driving force for constructing more efficient industrial microorganisms with wider applications in biotechnology.

Metabolic engineering of glucose uptake systems in Corynebacterium glutamicum for improving the efficiency of l-lysine production

Traditional amino acid producers typically exhibit the low glucose uptake rate and growth deficiency, resulting in a long fermentation time because of the accumulation of side mutations in breeding of strains. In this study, we demonstrate that the efficiency of l-lysine production in traditional l-lysine producer Corynebacterium glutamicum ZL-9 can be improved by rationally engineering glucose uptake systems. To do this, different bypasses for glucose uptake were investigated to reveal the best glucose uptake system for l-lysine production in traditional l-lysine producer. This study showed that overexpression of the key genes in PTSGlc or non-PTSGlc increased the glucose consumption, growth rate, and l-lysine production. However, increasing the function of PTSGlc in glucose uptake led to the increase of by-products, especially for plasmid-mediated expression system. Increasing the participation of non-PTSGlc in glucose utilization showed the best glucose uptake system for l-lysine production. The final strain ZL-92 with increasing the expression level of iolT1, iolT2 and ppgK could produce 201.6 ± 13.8 g/L of l-lysine with a productivity of 5.04 g/L/h and carbon yield of 0.65 g/(g glucose) in fed-batch culture. This is the first report of a rational modification of glucose uptake systems that improve the efficiency of l-lysine production through increasing the participation of non-PTSGlc in glucose utilization in traditional l-lysine producer. Similar strategies can be also used for producing other amino acids or their derivatives.

GREACE-assisted adaptive laboratory evolution in endpoint fermentation broth enhances lysine production by Escherichia coli

BACKGROUND

Late-stage fermentation broth contains high concentrations of target chemicals. Additionally, it contains various cellular metabolites which have leaked from lysed cells, which would exert multifactorial stress to industrial hyperproducers and perturb both cellular metabolism and product formation. Although adaptive laboratory evolution (ALE) has been wildly used to improve stress tolerance of microbial cell factories, single-factor stress condition (i.e. target product or sodium chloride at a high concentration) is currently provided. In order to enhance bacterial stress tolerance to actual industrial production conditions, ALE in late-stage fermentation broth is desired. Genome replication engineering assisted continuous evolution (GREACE) employs mutants of the proofreading element of DNA polymerase complex (DnaQ) to facilitate mutagenesis. Application of GREACE coupled-with selection under stress conditions is expected to accelerate the ALE process.

RESULTS

In this study, GREACE was first modified by expressing a DnaQ mutant KR5-2 using an arabinose inducible promoter on a temperature-sensitive plasmid, which resulted in timed mutagenesis introduction. Using this method, tolerance of a lysine hyperproducer E. coli MU-1 was improved by enriching mutants in a lysine endpoint fermentation broth. Afterwards, the KR5-2 expressing plasmid was cured to stabilize acquired genotypes. By subsequent fermentation evaluation, a mutant RS3 with significantly improved lysine production capacity was selected. The final titer, yield and total amount of lysine produced by RS3 in a 5-L batch fermentation reached 155.0 ± 1.4 g/L, 0.59 ± 0.02 g lysine/g glucose, and 605.6 ± 23.5 g, with improvements of 14.8%, 9.3%, and 16.7%, respectively. Further metabolomics and genomics analyses, coupled with molecular biology studies revealed that mutations SpeB^A302V, AtpB^S165N and SecY^M145V mainly contributed both to improved cell integrity under stress conditions and enhanced metabolic flux into lysine synthesis.

CONCLUSIONS

Our present study indicates that improving a lysine hyperproducer by GREACE-assisted ALE in its stressful living environment is efficient and effective. Accordingly, this is a promising method for improving other valuable chemical hyperproducers.

High-yield production of L-serine from glycerol by engineered Escherichia coli

L-Serine is widely used in pharmaceutical, food and cosmetic industries, and the direct fermentation to produce L-serine from cheap carbon sources such as glycerol is greatly desired. The production of L-serine by engineered Escherichia coli from glycerol has not been achieved so far. In this study, E. coli was engineered to efficiently produce L-serine from glycerol. To this end, three L-serine deaminase genes were deleted in turn, and all of the deletions caused the maximal accumulation of L-serine at 0.06 g/L. Furthermore, removal of feedback inhibition by L-serine resulted in a titer of 1.1 g/L. Additionally, adaptive laboratory evolution was employed to improve glycerol utilization in combination with the overexpression of the cysteine/acetyl serine transporter gene eamA, leading to 2.36 g/L L-serine (23.6% of the theoretical yield). In 5-L bioreactor, L-serine titer could reach up to 7.53 g/L from glycerol, demonstrating the potential of the established strain and bioprocess.

Deep scanning lysine metabolism in Escherichia coli

Our limited ability to predict genotype-phenotype relationships has called for strategies that allow testing of thousands of hypotheses in parallel. Deep scanning mutagenesis has been successfully implemented to map genotype-phenotype relationships at a single-protein scale, allowing scientists to elucidate properties that are difficult to predict. However, most phenotypes are dictated by several proteins that are interconnected through complex and robust regulatory and metabolic networks. These sophisticated networks hinder our understanding of the phenotype of interest and limit our capabilities to rewire cellular functions. Here, we leveraged CRISPR-EnAbled Trackable genome Engineering to attempt a parallel and high-resolution interrogation of complex networks, deep scanning multiple proteins associated with lysine metabolism in Escherichia coli We designed over 16,000 mutations to perturb this pathway and mapped their contribution toward resistance to an amino acid analog. By doing so, we identified different routes that can alter pathway function and flux, uncovering mechanisms that would be difficult to rationally design. This approach sets a framework for forward investigation of complex multigenic phenotypes.

In vivo biosensors: mechanisms, development, and applications

In vivo biosensors can recognize and respond to specific cellular stimuli. In recent years, biosensors have been increasingly used in metabolic engineering and synthetic biology, because they can be implemented in synthetic circuits to control the expression of reporter genes in response to specific cellular stimuli, such as a certain metabolite or a change in pH. There are many types of natural sensing devices, which can be generally divided into two main categories: protein-based and nucleic acid-based. Both can be obtained either by directly mining from natural genetic components or by engineering the existing genetic components for novel specificity or improved characteristics. A wide range of new technologies have enabled rapid engineering and discovery of new biosensors, which are paving the way for a new era of biotechnological progress. Here, we review recent advances in the design, optimization, and applications of in vivo biosensors in the field of metabolic engineering and synthetic biology.

Production of amino acids - Genetic and metabolic engineering approaches

The biotechnological production of amino acids occurs at the million-ton scale and annually about 6milliontons of l-glutamate and l-lysine are produced by Escherichia coli and Corynebacterium glutamicum strains. l-glutamate and l-lysine production from starch hydrolysates and molasses is very efficient and access to alternative carbon sources and new products has been enabled by metabolic engineering. This review focusses on genetic and metabolic engineering of amino acid producing strains. In particular, rational approaches involving modulation of transcriptional regulators, regulons, and attenuators will be discussed. To address current limitations of metabolic engineering, this article gives insights on recent systems metabolic engineering approaches based on functional tools and method such as genome reduction, amino acid sensors based on transcriptional regulators and riboswitches, CRISPR interference, small regulatory RNAs, DNA scaffolding, and optogenetic control, and discusses future prospects.

Engineering 'cell robots' for parallel and highly sensitive screening of biomolecules under in vivo conditions

Cells are capable of rapid replication and performing tasks adaptively and ultra-sensitively and can be considered as cheap "biological-robots". Here we propose to engineer cells for screening biomolecules in parallel and with high sensitivity. Specifically, we place the biomolecule variants (library) on the bacterial phage M13. We then design cells to screen the library based on cell-phage interactions mediated by a specific intracellular signal change caused by the biomolecule of interest. For proof of concept, we used intracellular lysine concentration in E. coli as a signal to successfully screen variants of functional aspartate kinase III (AK-III) under in vivo conditions, a key enzyme in L-lysine biosynthesis which is strictly inhibited by L-lysine. Comparative studies with flow cytometry method failed to distinguish the wild-type from lysine resistance variants of AK-III, confirming a higher sensitivity of the method. It opens up a new and effective way of in vivo high-throughput screening for functional molecules and can be easily implemented at low costs.