Adaptive laboratory evolution of Escherichia coli W enhances gamma-aminobutyric acid production using glycerol as the carbon source

Fast-track adaptive laboratory evolution of Cupriavidus necator H16 with divalent metal cations

Microbial strain improvement through adaptive laboratory evolution (ALE) has been a key strategy in biotechnology for enhancing desired phenotypic traits. In this Biotech Method paper, we present an accelerated ALE (aALE) workflow and its successful implementation in evolving Cupriavidus necator H16 for enhanced tolerance toward elevated glycerol concentrations. The method involves the deliberate induction of genetic diversity through controlled exposure to divalent metal cations, enabling the rapid identification of improved variants. Through this approach, we observed the emergence of robust variants capable of growing in high glycerol concentration environments, demonstrating the efficacy of our aALE workflow. When cultivated in 10% v/v glycerol, the adapted variant Mn-C2-B11, selected through aALE, achieved a final OD600 value of 56.0 and a dry cell weight of 15.2 g L-1, compared to the wild type (WT) strain's final OD600 of 39.1 and dry cell weight of 8.4 g L-1. At an even higher glycerol concentration of 15% v/v, Mn-C2-B11 reached a final OD600 of 48.9 and a dry cell weight of 12.7 g L-1, in contrast to the WT strain's final OD600 of 9.0 and dry cell weight of 3.1 g L-1. Higher glycerol consumption by Mn-C2-B11 was also confirmed by high-performance liquid chromatography (HPLC) analysis. This adapted variant consumed 34.5 times more glycerol compared to the WT strain at 10% v/v glycerol. Our method offers several advantages over other reported ALE approaches, including its independence from genetically modified strains, specialized genetic tools, and potentially carcinogenic DNA-modifying agents. By utilizing divalent metal cations as mutagens, we offer a safer, more efficient, and cost-effective alternative for expansion of genetic diversity. With its ability to foster rapid microbial evolution, aALE serves as a valuable addition to the ALE toolbox, holding significant promise for the advancement of microbial strain engineering and bioprocess optimization.

Systems metabolic engineering of Escherichia coli for high-yield production of Para-hydroxybenzoic acid

Para-hydroxybenzoic acid (PHBA) is extensively used as an additive in the food and cosmetics industries, significantly enhancing product shelf life and stability. While microbial fermentation offers an environment-friendly and sustainable method for producing PHBA, the titer and productivity are limited due to product toxicity and complex metabolic flux distributions. Here, we initially redesigned a L-phenylalanine-producing Escherichia coli by employing rational metabolic engineering strategies, resulting in the production of PHBA reached the highest reported level of 14.17 g/L. Subsequently, a novel accelerated evolution system was devised comprising deaminase, the alpha subunit of RNA polymerase, an uracil-DNA glycosylase inhibitor, and the PHBA-responsive promoter PyhcN. This system enabled us to obtain a mutant strain exhibiting a 47% increase in the half-inhibitory concentration (IC50) for PHBA within 15 days. Finally, the evolved strain achieved a production of 21.35 g/L PHBA in a 5-L fermenter, with a yield of 0.19 g/g glucose and a productivity rate of 0.44 g/L/h. This engineered strain emerges as a promising candidate for industrial production of PHBA through an eco-friendly approach.

Stepwise Flux Optimization for Enhanced GABA Production from Acetate in Escherichia coli

Strategic allocation of metabolic flux is essential for achieving a higher production performance in genetically engineered organisms. Flux optimization between cell growth and chemical production has led to the establishment of cost-effective chemical production methods in microbial cell factories. This effect is amplified when utilizing a low-cost carbon source. γ-Aminobutyric acid (GABA), crucial in pharmaceuticals and biodegradable polymers, can be efficiently produced from acetate, a cost-effective substrate. However, a balanced distribution of acetate-derived flux is essential for optimizing the production without hindering growth. In this study, we demonstrated GABA production from acetate using Escherichia coli by focusing on optimizing the metabolic flux at isocitrate and α-ketoglutarate nodes. Through a series of flux optimizations, the final strain produced 2.54 g/L GABA from 5.91 g/L acetate in 24 h (0.43 g/g yield). These findings suggest that delicate flux balancing with the application of a cheap substrate can contribute to cost-effective production of GABA.

Serial adaptive laboratory evolution enhances mixed carbon metabolic capacity of Escherichia coli

Microbes have inherent capacities for utilizing various carbon sources, however they often exhibit sub-par fitness due to low metabolic efficiency. To test whether a bacterial strain can optimally utilize multiple carbon sources, Escherichia coli was serially evolved in L-lactate and glycerol. This yielded two end-point strains that evolved first in L-lactate then in glycerol, and vice versa. The end-point strains displayed a universal growth advantage on single and a mixture of adaptive carbon sources, enabled by a concerted action of carbon source-specialists and generalist mutants. The combination of just four variants of glpK, ppsA, ydcI, and rph-pyrE, accounted for more than 80% of end-point strain fitness. In addition, machine learning analysis revealed a coordinated activity of transcriptional regulators imparting condition-specific regulation of gene expression. The effectiveness of the serial adaptive laboratory evolution (ALE) scheme in bioproduction applications was assessed under single and mixed-carbon culture conditions, in which serial ALE strain exhibited superior productivity of acetoin compared to ancestral strains. Together, systems-level analysis elucidated the molecular basis of serial evolution, which hold potential utility in bioproduction applications.

Microbial chassis design and engineering for production of gamma-aminobutyric acid

Gamma-aminobutyric acid (GABA) is a non-protein amino acid which is widely applied in agriculture and pharmaceutical additive industries. GABA is synthesized from glutamate through irreversible α-decarboxylation by glutamate decarboxylase. Recently, microbial synthesis has become an inevitable trend to produce GABA due to its sustainable characteristics. Therefore, reasonable microbial platform design and metabolic engineering strategies for improving production of GABA are arousing a considerable attraction. The strategies concentrate on microbial platform optimization, fermentation process optimization, rational metabolic engineering as key metabolic pathway modification, promoter optimization, site-directed mutagenesis, modular transporter engineering, and dynamic switch systems application. In this review, the microbial producers for GABA were summarized, including lactic acid bacteria, Corynebacterium glutamicum, and Escherichia coli, as well as the efficient strategies for optimizing them to improve the production of GABA.

Effect of adaptive laboratory evolution of engineered Escherichia coli in acetate on the biosynthesis of succinic acid from glucose in two-stage cultivation

Escherichia coli MLB (MG1655 ΔpflB ΔldhA), which can hardly grow on glucose with little succinate accumulation under anaerobic conditions. Two-stage fermentation is a fermentation in which the first stage is used for cell growth and the second stage is used for product production. The ability of glucose consumption and succinate production of MLB under anaerobic conditions can be improved significantly by using acetate as the solo carbon source under aerobic condition during the two-stage fermentation. Then, the adaptive laboratory evolution (ALE) of growing on acetate was applied here. We assumed that the activities of succinate production related enzymes might be further improved in this study. E. coli MLB46-05 evolved from MLB and it had an improved growth phenotype on acetate. Interestingly, in MLB46-05, the yield and tolerance of succinic acid in the anaerobic condition of two-stage fermentation were improved significantly. According to transcriptome analysis, upregulation of the glyoxylate cycle and the activity of stress regulatory factors are the possible reasons for the elevated yield. And the increased tolerance to acetate made it more tolerant to high concentrations of glucose and succinate. Finally, strain MLB46-05 produced 111 g/L of succinic acid with a product yield of 0.74 g/g glucose. SYNOPSIS.

Engineering Bacillus subtilis J46 for efficient utilization of galactose through adaptive laboratory evolution

Efficient utilization of galactose by microorganisms can lead to the production of valuable bio-products and improved metabolic processes. While Bacillus subtilis has inherent pathways for galactose metabolism, there is potential for enhancement via evolutionary strategies. This study aimed to boost galactose utilization in B. subtilis using adaptive laboratory evolution (ALE) and to elucidate the genetic and metabolic changes underlying the observed enhancements. The strains of B. subtilis underwent multiple rounds of adaptive laboratory evolution (approximately 5000 generations) in an environment that favored the use of galactose. This process resulted in an enhanced specific growth rate of 0.319 ± 0.005 h-1, a significant increase from the 0.03 ± 0.008 h-1 observed in the wild-type strains. Upon selecting the evolved strain BSGA14, a comprehensive whole-genome sequencing revealed the presence of 63 single nucleotide polymorphisms (SNPs). Two of them, located in the coding sequences of the genes araR and glcR, were found to be the advantageous mutations after reverse engineering. The strain with these two accumulated mutations, BSGALE4, exhibited similar specific growth rate on galactose to the evolved strain BSGA14 (0.296 ± 0.01 h-1). Furthermore, evolved strain showed higher productivity of protease and β-galactosidase in mock soybean biomass medium. ALE proved to be a potent tool for enhancing galactose metabolism in B. subtilis. The findings offer valuable insights into the potential of evolutionary strategies in microbial engineering and pave the way for industrial applications harnessing enhanced galactose conversion.

Integrating Enzyme Evolution and Metabolic Engineering to Improve the Productivity of Γ-Aminobutyric Acid by Whole-Cell Biosynthesis in Escherichia Coli

γ-Aminobutyric acid (GABA) is used widely in various fields, such as agriculture, food, pharmaceuticals, and biobased chemicals. Based on glutamate decarboxylase (GadBM4) derived from our previous work, three mutants, GadM4-2, GadM4-8, and GadM4-31, were obtained by integrating enzyme evolution and high-throughput screening methods. The GABA productivity obtained through whole-cell bioconversion using recombinant Escherichia coli cells harboring mutant GadBM4-2 was enhanced by 20.27% compared to that of the original GadBM4. Further introduction of the central regulator GadE of the acid resistance system and the enzymes from the deoxyxylulose-5-phosphate-independent pyridoxal 5'-phosphate biosynthesis pathway resulted in a 24.92% improvement in GABA productivity, reaching 76.70 g/L/h without any cofactor addition with a greater than 99% conversion ratio. Finally, when one-step bioconversion was applied for the whole-cell catalysis in a 5 L bioreactor, the titer of GABA reached 307.5 ± 5.94 g/L with a productivity of 61.49 g/L/h by using crude l-glutamic acid (l-Glu) as the substrate. Thus, the biocatalyst constructed above combined with the whole-cell bioconversion method represents an effective approach for industrial GABA production.

Adaptive Laboratory Evolution of Microorganisms: Methodology and Application for Bioproduction

Adaptive laboratory evolution (ALE) is a useful experimental methodology for fundamental scientific research and industrial applications to create microbial cell factories. By using ALE, cells are adapted to the environment that researchers set based on their objectives through the serial transfer of cell populations in batch cultivations or continuous cultures and the fitness of the cells (i.e., cell growth) under such an environment increases. Then, omics analyses of the evolved mutants, including genome sequencing, transcriptome, proteome and metabolome analyses, are performed. It is expected that researchers can understand the evolutionary adaptation processes, and for industrial applications, researchers can create useful microorganisms that exhibit increased carbon source availability, stress tolerance, and production of target compounds based on omics analysis data. In this review article, the methodologies for ALE in microorganisms are introduced. Moreover, the application of ALE for the creation of useful microorganisms as cell factories has also been introduced.

Minireview: Engineering evolution to reconfigure phenotypic traits in microbes for biotechnological applications

Adaptive laboratory evolution (ALE) has long been used as the tool of choice for microbial engineering applications, ranging from the production of commodity chemicals to the innovation of complex phenotypes. With the advent of systems and synthetic biology, the ALE experimental design has become increasingly sophisticated. For instance, implementation of in silico metabolic model reconstruction and advanced synthetic biology tools have facilitated the effective coupling of desired traits to adaptive phenotypes. Furthermore, various multi-omic tools now enable in-depth analysis of cellular states, providing a comprehensive understanding of the biology of even the most genomically perturbed systems. Emerging machine learning approaches would assist in streamlining the interpretation of massive and multiplexed datasets and promoting our understanding of complexity in biology. This review covers some of the representative case studies among the 700 independent ALE studies reported to date, outlining key ideas, principles, and important mechanisms underlying ALE designs in bioproduction and synthetic cell engineering, with evidence from literatures to aid comprehension.

Recent progress in adaptive laboratory evolution of industrial microorganisms

Adaptive laboratory evolution (ALE) is a technique for the selection of strains with better phenotypes by long-term culture under a specific selection pressure or growth environment. Because ALE does not require detailed knowledge of a variety of complex and interactive metabolic networks, and only needs to simulate natural environmental conditions in the laboratory to design a selection pressure, it has the advantages of broad adaptability, strong practicability, and more convenient transformation of strains. In addition, ALE provides a powerful method for studying the evolutionary forces that change the phenotype, performance, and stability of strains, resulting in more productive industrial strains with beneficial mutations. In recent years, ALE has been widely used in the activation of specific microbial metabolic pathways and phenotypic optimization, the efficient utilization of specific substrates, the optimization of tolerance to toxic substance, and the biosynthesis of target products, which is more conducive to the production of industrial strains with excellent phenotypic characteristics. In this paper, typical examples of ALE applications in the development of industrial strains and the research progress of this technology are reviewed, followed by a discussion of its development prospects.