Adaptive evolution of Escherichia coli K-12 MG1655 during growth on a Nonnative carbon source, L-1,2-propanediol

Synonymous edits in the Escherichia coli genome have substantial and condition-dependent effects on fitness

CRISPR-Cas-based genome editing is widely used in bacteria at scales ranging from construction of individual mutants to massively parallel libraries. This procedure relies on guide RNA-directed cleavage of the genome followed by repair with a template that introduces a desired mutation along with synonymous "immunizing" mutations to prevent re-cleavage of the genome after editing. Because the immunizing mutations do not change the protein sequence, they are often assumed to be neutral. However, synonymous mutations can change mRNA structures in ways that alter levels of the encoded proteins. We have tested the assumption that immunizing mutations are neutral by constructing a library of over 50,000 edits that consist of only synonymous mutations in Escherichia coli. Thousands of edits had substantial effects on fitness during growth of E. coli on acetate, a poor carbon source that is toxic at high concentrations. The percentage of high-impact edits varied considerably between genes and at different positions within genes. We reconstructed clones with high-impact edits and found that 69% indeed had significant effects on growth in acetate. Interestingly, fewer edits affected fitness during growth in glucose, a preferred carbon source, suggesting that changes in protein expression caused by synonymous mutations may be most important when an organism encounters challenging conditions. Finally, we showed that synonymous edits can have widespread effects; a synonymous edit at the 5' end of ptsI altered expression of hundreds of genes. Our results suggest that the synonymous immunizing edits introduced during CRISPR-Cas-based genome editing should not be assumed to be innocuous.

Adaptive Laboratory Evolution to Improve Recombinant Protein Production Using Insect Cells

Adaptive laboratory evolution (ALE) is a powerful tool for enhancing the fitness of cell lines in specific applications, including recombinant protein production. Through adaptation to nonstandard culture conditions, cells can develop specific traits that make them high producers. Despite being widely used for microorganisms and, to lesser extent, for mammalian cells, ALE has been poorly leveraged for insect cells. Here, we describe a method for adapting insect High Five and Sf9 cells to nonstandard culture conditions via an ALE approach. Aiming to demonstrate the potential of ALE to improve productivity of insect cells, two case studies are demonstrated. In the first, we adapted insect High Five cells from their standard pH (6.2) to neutral pH (7.0); this adaptation allowed to improve production of influenza virus-like particles (VLPs) by threefold, using the transient baculovirus expression vector system. In the second, we adapted insect Sf9 cells from their standard culture temperature (27 °C) to hypothermic growth (22 °C); this adaptation allowed to improve production of influenza VLPs by sixfold, using stable cell lines. These examples demonstrate the potential of ALE for enhancing productivity within distinct insect cell hosts and expression systems by manipulating different culture conditions.

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.

In Silico and In Vitro Investigation of the Distribution and Expression of Key Genes in the Fucose Operon of Escherichia coli

Many gut bacteria degrade polysaccharides, providing nutritional advantages to their hosts. Fucose, a mucin degradation product, was suggested as a communication molecule between the resident microbiota and external pathogens. However, the precise role and variants of the fucose utilization pathway remain to be elucidated. Here, we computationally and experimentally investigated the fucose utilization operon of E. coli. While the operon is conserved among E. coli genomes, a variant pathway, in which an ABC transporter system replaces the fucose permease gene (fucP), was computationally identified in 50 out of 1058 genomes. Comparative genomics and subsystems analysis results were confirmed by polymerase chain reaction-based screening of 40 human E. coli isolates, which indicated the conservation of fucP in 92.5% of the isolates (vs. 7.5% of its suggested alternative, yjfF). The in silico predictions were confirmed by in vitro experiments comparing the growth of E. coli strains K12, BL21, and isogenic fucose-utilization K12 mutants. Additionally, fucP and fucI transcripts were quantified in E. coli K12 and BL21, after in silico analysis of their expression in 483 public transcriptomes. In conclusion, E. coli utilizes fucose by two pathway variants, with measurable transcriptional differences. Future studies will explore this variation's impact on signaling and virulence.

Trait drift in microalgae and applications for strain improvement

Microalgae are increasingly used to generate a wide range of commercial products, and there is growing evidence that microalgae-based products can be produced sustainably. However, industrial production of microalgal biomass is not as developed as other biomanufacturing platform technologies. In addition, results of bench-scale research often fail to translate to large-scale or mass production systems. This disconnect may result from trait drift and evolution occurring, through time, in response to unique drivers in each environment, such as cultivation regimes, weather, and pests. Moreover, outdoor and indoor cultivation of microalgae has the potential to impose negative selection pressures, which makes the maintenance of desired traits a challenge. In this context, this review sheds the light on our current understanding of trait drift and evolution in microalgae. We delineate the basics of phenotype plasticity and evolution, with a focus on how microalgae respond under various conditions. In addition, we review techniques that exploit phenotypic plasticity and evolution for strain improvement in view of industrial commercial applications, highlighting associated advantages and shortcomings. Finally, we suggest future research directions and recommendations to overcome unwanted trait drift and evolution in microalgae cultivation.

Better under stress: Improving bacterial cellulose production by Komagataeibacter xylinus K2G30 (UMCC 2756) using adaptive laboratory evolution

Among naturally produced polymers, bacterial cellulose is receiving enormous attention due to remarkable properties, making it suitable for a wide range of industrial applications. However, the low yield, the instability of microbial strains and the limited knowledge of the mechanisms regulating the metabolism of producer strains, limit the large-scale production of bacterial cellulose. In this study, Komagataeibacter xylinus K2G30 was adapted in mannitol based medium, a carbon source that is also available in agri-food wastes. K. xylinus K2G30 was continuously cultured by replacing glucose with mannitol (2% w/v) for 210 days. After a starting lag-phase, in which no changes were observed in the utilization of mannitol and in bacterial cellulose production (cycles 1-25), a constant improvement of the phenotypic performances was observed from cycle 26 to cycle 30, accompanied by an increase in mannitol consumption. At cycle 30, the end-point of the experiment, bacterial cellulose yield increased by 38% in comparision compared to cycle 1. Furthermore, considering the mannitol metabolic pathway, D-fructose is an intermediate in the bioconversion of mannitol to glucose. Based on this consideration, K. xylinus K2G30 was tested in fructose-based medium, obtaining the same trend of bacterial cellulose production observed in mannitol medium. The adaptive laboratory evolution approach used in this study was suitable for the phenotypic improvement of K. xylinus K2G30 in bacterial cellulose production. Metabolic versatility of the strain was confirmed by the increase in bacterial cellulose production from D-fructose-based medium. Moreover, the adaptation on mannitol did not occur at the expense of glucose, confirming the versatility of K2G30 in producing bacterial cellulose from different carbon sources. Results of this study contribute to the knowledge for designing new strategies, as an alternative to the genetic engineering approach, for bacterial cellulose production.

Rapid acquisition of microorganisms and microbial genes can help explain punctuated evolution

The punctuated mode of evolution posits that evolution occurs in rare bursts of rapid evolutionary change followed by long periods of genetic stability (stasis). The accepted cause for the rapid changes in punctuated evolution is special ecological circumstances – selection forces brought about by changes in the environment. This article presents a complementary explanation for punctuated evolution by the rapid formation of genetic variants in animals and plants by the acquisition of microorganisms from the environment into microbiomes and microbial genes into host genomes by horizontal gene transfer. Several examples of major evolutionary events driven by microorganisms are discussed, including the formation of the first eukaryotic cell, the ability of some animals to digest cellulose and other plant cell-wall complex polysaccharides, dynamics of root system architecture, and the formation of placental mammals. These changes by cooperation were quantum leaps in the evolutionary development of complex bilolgical systems and can contribute to an understanding of the mechanisms underlying punctuated evolution.

Asexual Blood-Stage Malaria Vaccine Candidate PfRipr5: Enhanced Production in Insect Cells

The malaria asexual blood-stage antigen PfRipr and its most immunogenic fragment PfRipr5 have recently risen as promising vaccine candidates against this infectious disease. Continued development of high-yielding, scalable production platforms is essential to advance the malaria vaccine research. Insect cells have supplied the production of numerous vaccine antigens in a fast and cost-effective manner; improving this platform further could prove key to its wider use. In this study, insect (Sf9 and High Five) and human (HEK293) cell hosts as well as process-optimizing strategies (new baculovirus construct designs and a culture temperature shift to hypothermic conditions) were employed to improve the production of the malaria asexual blood-stage vaccine candidate PfRipr5. Protein expression was maximized using High Five cells at CCI of 2 × 10⁶ cell/mL and MOI of 0.1 pfu/cell (production yield = 0.49 mg/ml), with high-purity PfRipr5 binding to a conformational anti-PfRipr monoclonal antibody known to hold GIA activity and parasite PfRipr staining capacity. Further improvements in the PfRipr5 expression were achieved by designing novel expression vector sequences and performing a culture temperature shift to hypothermic culture conditions. Addition of one alanine (A) amino acid residue adjacent to the signal peptide cleavage site and a glycine-serine linker (GGSGG) between the PfRipr5 sequence and the purification tag (His₆) induced a 2.2-fold increase in the expression of secreted PfRipr5 over using the expression vector with none of these additions. Performing a culture temperature shift from the standard 27–22°C at the time of infection improved the PfRipr5 expression by up to 1.7 fold. Notably, a synergistic effect was attained when combining both strategies, enabling to increase production yield post-purification by 5.2 fold, with similar protein quality (i.e., purity and binding to anti-PfRipr monoclonal antibody). This work highlights the potential of insect cells to produce the PfRipr5 malaria vaccine candidate and the importance of optimizing the expression vector and culture conditions to boost the expression of secreted proteins.

Evolution of enzyme levels in metabolic pathways: A theoretical approach

The central role of metabolism in cell functioning and adaptation has given rise to countless studies on the evolution of enzyme-coding genes and network topology. However, very few studies have addressed the question of how enzyme concentrations change in response to positive selective pressure on the flux, considered a proxy of fitness. In particular, the way cellular constraints, such as resource limitations and co-regulation, affect the adaptive landscape of a pathway under selection has never been analyzed theoretically. To fill this gap, we developed a model of the evolution of enzyme concentrations that combines metabolic control theory and an adaptive dynamics approach, and integrates possible dependencies between enzyme concentrations. We determined the evolutionary equilibria of enzyme concentrations and their range of neutral variation, and showed that they differ with the properties of the enzymes, the constraints applied to the system and the initial enzyme concentrations. Simulations of long-term evolution confirmed all analytical and numerical predictions, even though we relaxed the simplifying assumptions used in the analytical treatment.

Escherichia coli Data-Driven Strain Design Using Aggregated Adaptive Laboratory Evolution Mutational Data

Microbes are being engineered for an increasingly large and diverse set of applications. However, the designing of microbial genomes remains challenging due to the general complexity of biological systems. Adaptive Laboratory Evolution (ALE) leverages nature’s problem-solving processes to generate optimized genotypes currently inaccessible to rational methods. The large amount of public ALE data now represents a new opportunity for data-driven strain design. This study describes how novel strain designs, or genome sequences not yet observed in ALE experiments or published designs, can be extracted from aggregated ALE data and demonstrates this by designing, building, and testing three novel Escherichia coli strains with fitnesses comparable to ALE mutants. These designs were achieved through a meta-analysis of aggregated ALE mutations data (63 Escherichia coli K-12 MG1655 based ALE experiments, described by 93 unique environmental conditions, 357 independent evolutions, and 13 957 observed mutations), which additionally revealed global ALE mutation trends that inform on ALE-derived strain design principles. Such informative trends anticipate ALE-derived strain designs as largely gene-centric, as opposed to noncoding, and composed of a relatively small number of beneficial variants (approximately 6). These results demonstrate how strain design efforts can be enhanced by the meta-analysis of aggregated ALE data.

Characterization of highly ferulate-tolerant Acinetobacter baylyi ADP1 isolates by a rapid reverse-engineering method

Adaptive laboratory evolution (ALE) is a powerful approach for improving phenotypes of microbial hosts. Evolved strains typically contain numerous mutations that can be revealed by whole-genome sequencing. However, determining the contribution of specific mutations to new phenotypes is typically challenging and laborious. This task is complicated by factors such as the mutation type, the genomic context, and the interplay between different mutations. Here, a novel approach was developed to identify the significance of mutations in strains evolved from Acinetobacter baylyi ADP1. This method, termed Rapid Advantageous Mutation ScrEening and Selection (RAMSES), was used to analyze mutants that emerged from stepwise adaptation to, and consumption of, high levels of ferulate, a common lignin-derived aromatic compound. After whole-genome sequence analysis, RAMSES allowed rapid determination of effective mutations and seamless introduction of the beneficial mutations into the chromosomes of new strains with different genetic backgrounds. This simple approach to reverse-engineering exploits the natural competence and high recombination efficiency of ADP1. Mutated DNA, added directly to growing cells, replaces homologous chromosomal regions to generate transformants that will become enriched if there is selective benefit. Thus, advantageous mutations can be rapidly identified. Here, the growth advantage of transformants under selective pressure revealed key mutations in genes related to aromatic transport, including hcaE, hcaK, and vanK, and a gene, ACIAD0482, which is associated with lipopolysaccharide synthesis. This study provides insights into enhanced utilization of industrially relevant aromatic substrates and demonstrates the use of A. baylyi ADP1 as a convenient platform for strain development and evolution studies. Importance Microbial conversion of lignin-enriched streams is a promising approach for lignin valorization. However, the lignin-derived aromatic compounds are toxic to cells at relevant concentrations. Although adaptive laboratory evolution (ALE) is a powerful approach to develop more tolerant strains, it is typically laborious to identify the mechanisms underlying phenotypic improvement. We employed Acinetobacter baylyi ADP1, an aromatic compound degrading strain that may be useful for biotechnology. The natural competence and high recombination efficiency of this strain can be exploited for critical applications such as the breakdown of lignin and plastics, abundant polymers composed of aromatic subunits. The natural transformability of this bacterium enabled us to develop a novel approach for rapid screening of advantageous mutations from ALE-derived aromatic-tolerant ADP1-derived strains. We clarified the mechanisms and genetic targets for improved tolerance towards common lignin-derived aromatic compounds. This study facilitates metabolic engineering for lignin valorization.

Microbial adaptive evolution

Bacterial species can adapt to significant changes in their environment by mutation followed by selection, a phenomenon known as “adaptive evolution.” With the development of bioinformatics and genetic engineering, research on adaptive evolution has progressed rapidly, as have applications of the process. In this review, we summarize various mechanisms of bacterial adaptive evolution, the technologies used for studying it, and successful applications of the method in research and industry. We particularly highlight the contributions of Dr. L. O. Ingram. Microbial adaptive evolution has significant impact on our society not only from its industrial applications, but also in the evolution, emergence, and control of various pathogens.

Genetic Diversity for Accelerating Microbial Adaptive Laboratory Evolution

Adaptive laboratory evolution (ALE) is a widely used and highly effective tool for improving microbial phenotypes and investigating the evolutionary roots of biological phenomena. Serving as the raw materials of evolution, mutations have been extensively utilized to increase the chances of engineering molecules or microbes with tailor-made functions. The generation of genetic diversity is therefore a core technology for accelerating ALE, and a high-quality mutant library is crucial to its success. Because of its importance, technologies for generating genetic diversity have undergone rapid development in recent years. Here, we review the existing techniques for the construction of mutant libraries, briefly introduce their mechanisms and applications, discuss ongoing and emerging efforts to apply engineering technologies in the construction of mutant libraries, and suggest future perspectives for library construction.

Programming adaptive laboratory evolution of 4-hydroxyisoleucine production driven by a lysine biosensor in Corynebacterium glutamicum

4-Hydroxyisoleucine (4-HIL) is a promising drug for treating diabetes. In our previous study, 4-HIL was synthesized from self-produced L-isoleucine (Ile) in Corynebacterium glutamicum by expressing an Ile dioxygenase gene. Although the 4-HIL production of recombinant strain SZ06 increased significantly, a by-product, L-lysine (Lys) was accumulated because of the share of the first several enzymes in Ile and Lys biosynthetic pathways. In this study, programming adaptive laboratory evolution (ALE) was designed and conducted in SZ06 to promote 4-HIL biosynthesis. At first, a programming evolutionary system pMK was constructed, which contains a Lys biosensor LysG-P_lysE and an evolutionary actuator composed of a mutagenesis gene and a fluorescent protein gene. The evolutionary strain SZ06/pMK was then let to be evolved programmatically and spontaneously by sensing Lys concentration. After successive rounds of evolution, nine mutant strains K1 - K9 with significantly increased 4-HIL production and growth performance were obtained. The maximum 4-HIL titer was 152.19 ± 14.60 mM, 28.4% higher than that in SZ06. This titer was higher than those of all the metabolic engineered C. glutamicum strains ever constructed. The whole genome sequencing of the nine evolved strains revealed approximately 30 genetic mutations in each strain. Only one mutation was directly related to the Lys biosynthetic pathway. Therefore, programming ALE driven by Lys biosensor can be used as an effective strategy to increase 4-HIL production in C. glutamicum.

Setting the stage for evolution of a new enzyme

The evolution of novel enzymes has fueled the diversification of life on earth for billions of years. Insights into events that set the stage for the evolution of a new enzyme can be obtained from ancestral reconstruction and laboratory evolution. Ancestral reconstruction can reveal the emergence of a promiscuous activity in a pre-existing protein and the impact of subsequent mutations that enhance a new activity. Laboratory evolution provides a more holistic view by revealing mutations elsewhere in the genome that indirectly enhance the level of a newly important enzymatic activity. This review will highlight recent studies that probe the early stages of the evolution of a new enzyme from these complementary points of view.

Acetate as a potential feedstock for the production of value-added chemicals: Metabolism and applications

Acetate is regarded as a promising carbon feedstock in biological production owing to its possible derivation from C₁ gases such as CO, CO₂ and methane. To best use of acetate, comprehensive understanding of acetate metabolisms from genes and enzymes to pathways and regulations is needed. This review aims to provide an overview on the potential of acetate as carbon feedstock for industrial biotechnology. Biochemical, microbial and biotechnological aspects of acetate metabolism are described. Especially, the current state-of-the art in the production of value-added chemicals from acetate is summarized. Challenges and future perspectives are also provided.

In silico Design for Systems-Based Metabolic Engineering for the Bioconversion of Valuable Compounds From Industrial By-Products

Selecting appropriate metabolic engineering targets to build efficient cell factories maximizing the bioconversion of industrial by-products to valuable compounds taking into account time restrictions is a significant challenge in industrial biotechnology. Microbial metabolism engineering following a rational design has been widely studied. However, it is a cost-, time-, and laborious-intensive process because of the cell network complexity; thus, it is important to use tools that allow predicting gene deletions. An in silico experiment was performed to model and understand the metabolic engineering effects on the cell factory considering a second complexity level by transcriptomics data integration. In this study, a systems-based metabolic engineering target prediction was used to increase glycerol bioconversion to succinic acid based on Escherichia coli. Transcriptomics analysis suggests insights on how to increase cell glycerol utilization to further design efficient cell factories. Three E. coli models were used: a core model, a second model based on the integration of transcriptomics data obtained from growth in an optimized culture media, and a third one obtained after integration of transcriptomics data from adaptive laboratory evolution (ALE) experiments. A total of 2,402 strains were obtained with fumarase and pyruvate dehydrogenase being frequently predicted for all the models, suggesting these reactions as essential to increase succinic acid production. Finally, based on using flux balance analysis (FBA) results for all the mutants predicted, a machine learning method was developed to predict new mutants as well as to propose optimal metabolic engineering targets and mutants based on the measurement of the importance of each knockout's (feature's) contribution. Glycerol has become an interesting carbon source for industrial processes due to biodiesel business growth since it has shown promising results in terms of biomass/substrate yields. The combination of transcriptome, systems metabolic modeling, and machine learning analyses revealed the versatility of computational models to predict key metabolic engineering targets in a less cost-, time-, and laborious-intensive process. These data provide a platform to improve the prediction of metabolic engineering targets to design efficient cell factories. Our results may also work as a guide and platform for the selection/engineering of microorganisms for the production of interesting chemical compounds.

Engineering of primary metabolic pathways for titer improvement of milbemycins in Streptomyces bingchenggensis

Milbemycins are used commercially as insect repellents and acaricides; however, their high cost remains a significant challenge to commercial production. Hence, improving the titer of milbemycins for commercial application is an urgent priority. The present study aimed to effectively increase the titer of milbemycins using a combination of genome re-sequencing and metabolic engineering. First, 133 mutation sites were identified by genome re-sequencing in the mutagenized high-yielding strain BC04. Among them, three modifiable candidate genes (sbi_04868 encoding citrate synthase, sbi_06921 and sbi_06922 encoding alpha and beta subunits of acetyl-CoA carboxylase, and sbi_04683 encoding carbon uptake system gluconate transporter) related to primary metabolism were screened and identified. Next, the DNase-deactivated Cpf1-based integrative CRISPRi system was used in S. bingchenggensis to downregulate the transcription level of gene sbi_04868. Then, overexpression of the potential targets sbi_06921-06922 and sbi_04683 further facilitated milbemycin biosynthesis. Finally, those candidate genes were engineered to produce strains with combinatorial downregulation and overexpression, which resulted in the titer of milbemycin A3/A4 increased by 27.6% to 3164.5 mg/L. Our research not only identified three genes in S. bingchenggensis that are closely related to the production of milbemycins, but also offered an efficient engineering strategy to improve the titer of milbemycins using genome re-sequencing. KEY POINTS: • We compared the genomes of two strains with different titers of milbemycins. • We found three genes belonging to primary metabolism influence milbemycin production. • We improved titer of milbemycins by a combinatorial engineering of three targets.

Engineering Escherichia coli for the utilization of ethylene glycol

Background

A considerable challenge in the development of bioprocesses for producing chemicals and fuels has been the high cost of feedstocks relative to oil prices, making it difficult for these processes to compete with their conventional petrochemical counterparts. Hence, in the absence of high oil prices in the near future, there has been a shift in the industry to produce higher value compounds such as fragrances for cosmetics. Yet, there is still a need to address climate change and develop biotechnological approaches for producing large market, lower value chemicals and fuels.

Results

In this work, we study ethylene glycol (EG), a novel feedstock that we believe has promise to address this challenge. We engineer Escherichia coli (E. coli) to consume EG and examine glycolate production as a case study for chemical production. Using a combination of modeling and experimental studies, we identify oxygen concentration as an important metabolic valve in the assimilation and use of EG as a substrate. Two oxygen-based strategies are thus developed and tested in fed-batch bioreactors. Ultimately, the best glycolate production strategy employed a target respiratory quotient leading to the highest observed fermentation performance. With this strategy, a glycolate titer of 10.4 g/L was reached after 112 h of production time in a fed-batch bioreactor. Correspondingly, a yield of 0.8 g/g from EG and productivity of 0.1 g/L h were measured during the production stage. Our modeling and experimental results clearly suggest that oxygen concentration is an important factor in the assimilation and use of EG as a substrate. Finally, our use of metabolic modeling also sheds light on the intracellular distribution through central metabolism, implicating flux to 2-phosphoglycerate as the primary route for EG assimilation.

Conclusion

Overall, our work suggests that EG could provide a renewable starting material for commercial biosynthesis of fuels and chemicals that may achieve economic parity with petrochemical feedstocks while sequestering carbon dioxide.

Genome-scale reconstructions to assess metabolic phylogeny and organism clustering

Approaches for systematizing information of relatedness between organisms is important in biology. Phylogenetic analyses based on sets of highly conserved genes are currently the basis for the Tree of Life. Genome-scale metabolic reconstructions contain high-quality information regarding the metabolic capability of an organism and are typically restricted to metabolically active enzyme-encoding genes. While there are many tools available to generate draft reconstructions, expert-level knowledge is still required to generate and manually curate high-quality genome-scale metabolic models and to fill gaps in their reaction networks. Here, we use the tool AutoKEGGRec to construct 975 genome-scale metabolic draft reconstructions encoded in the KEGG database without further curation. The organisms are selected across all three domains, and their metabolic networks serve as basis for generating phylogenetic trees. We find that using all reactions encoded, these metabolism-based comparisons give rise to a phylogenetic tree with close similarity to the Tree of Life. While this tree is quite robust to reasonable levels of noise in the metabolic reaction content of an organism, we find a significant heterogeneity in how much noise an organism may tolerate before it is incorrectly placed in the tree. Furthermore, by using the protein sequences for particular metabolic functions and pathway sets, such as central carbon-, nitrogen-, and sulfur-metabolism, as basis for the organism comparisons, we generate highly specific phylogenetic trees. We believe the generation of phylogenetic trees based on metabolic reaction content, in particular when focused on specific functions and pathways, could aid the identification of functionally important metabolic enzymes and be of value for genome-scale metabolic modellers and enzyme-engineers.

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.

Improving Influenza HA-Vlps Production in Insect High Five Cells via Adaptive Laboratory Evolution

The use of non-standard culture conditions has proven efficient to increase cell performance and recombinant protein production in different cell hosts. However, the establishment of high-producing cell populations through adaptive laboratory evolution (ALE) has been poorly explored, in particular for insect cells. In this study, insect High Five cells were successfully adapted to grow at a neutral culture pH (7.0) through ALE for an improved production of influenza hemagglutinin (HA)-displaying virus-like particles (VLPs). A stepwise approach was used for the adaptation process, in which the culture pH gradually increased from standard 6.2 to 7.0 (ΔPh = 0.2–0.3), and cells were maintained at each pH value for 2–3 weeks until a constant growth rate and a cell viability over 95% were observed. These adapted cells enabled an increase in cell-specific HA productivity up to three-fold and volumetric HA titer of up to four-fold as compared to non-adapted cells. Of note, the adaptation process is the element driving increased specific HA productivity as a pH shift alone was inefficient at improving productivities. The production of HA-VLPs in adapted cells was successfully demonstrated at the bioreactor scale. The produced HA-VLPs show the typical size and morphology of influenza VLPs, thus confirming the null impact of the adaptation process and neutral culture pH on the quality of HA-VLPs produced. This work strengthens the potential of ALE as a bioprocess engineering strategy to improve the production of influenza HA-VLPs in insect High Five cells.

Adaptive laboratory evolution of Escherichia coli lacking cellular byproduct formation for enhanced acetate utilization through compensatory ATP consumption

Acetate has attracted great attention as a carbon source to develop economically feasible bioprocesses for sustainable bioproducts. Acetate is a less-preferred carbon source and a well-known growth inhibitor of Escherichia coli. In this study, we carried out adaptive laboratory evolution of an E. coli strain lacking four genes (adhE, pta, ldhA, and frdA) involved in acetyl-CoA consumption, allowing the efficient utilization of acetate as its sole carbon and energy source. Four genomic mutations were found in the evolved strain through whole-genome sequencing, and two major mutations (in cspC and patZ) mainly contributed to efficient utilization of acetate and tolerance to acetate. Transcriptomic reprogramming was examined by analyzing the genome-wide transcriptome with different carbon sources. The evolved strain showed high levels of intracellular ATP by upregulation of genes involved in NADH and ATP biosynthesis, which facilitated the production of enhanced green fluorescent protein, mevalonate, and n-butanol using acetate alone. This new strain, given its high acetate tolerance and high ATP levels, has potential as a starting host for cell factories targeting the production of acetyl-CoA-derived products from acetate or of products requiring high ATP levels.

Genomic plasticity of pathogenic Escherichia coli mediates d-serine tolerance via multiple adaptive mechanisms

Pathogens ensure infection of favored sites in the body by responding to chemical signals. One chemical abundant in urine, the amino acid d-Ser, is toxic to EHEC and reduces expression of the machinery used for host cell attachment, making the bladder an unfavorable environment. We observed that under d-Ser stress, EHEC acquires genetic changes that lead to blocking d-Ser uptake into the cell or activating a silent enzyme for degrading d-Ser. This prevents growth inhibition and, critically, inhibits the repression of attachment machinery normally caused by d-Ser. These findings highlight the importance of pathogen evolution in determining how host molecules regulate colonization. These interactions underpin a process known as niche restriction that is important for pathogen success within the host.

The molecular environment of the host can have profound effects on the behavior of resident bacterial species. We recently established how the sensing and response of enterohemorrhagic Escherichia coli (EHEC) to d-serine (d-Ser) resulted in down-regulation of type 3 secretion system-dependent colonization, thereby avoiding unfavorable environments abundant in this toxic metabolite. However, this model ignores a key determinant of the success of bacterial pathogens, adaptive evolution. In this study, we have explored the adaptation of EHEC to d-Ser and its consequences for pathogenesis. We rapidly isolated multiple, independent, EHEC mutants whose growth was no longer compromised in the presence of d-Ser. Through a combination of whole-genome sequencing and transcriptomics, we showed that tolerance could be attributed to disruption of one of two d-Ser transporters and/or activation of a previously nonfunctional d-Ser deaminase. While the implication of cytoplasmic transport in d-Ser toxicity was unsurprising, disruption of a single transporter, CycA, was sufficient to completely overcome the repression of type 3 secretion system activity normally associated with exposure to d-Ser. Despite the fact that this reveals a mechanism by which evolution could drive a pathogen to colonize new niches, interrogation of sequenced E. coli O157:H7 genomes showed a high level of CycA conservation, highlighting a strong selective pressure for functionality. Collectively, these data show that CycA is a critically important conduit for d-Ser uptake that is central to the niche restriction of EHEC.

Underground isoleucine biosynthesis pathways in E. coli

The promiscuous activities of enzymes provide fertile ground for the evolution of new metabolic pathways. Here, we systematically explore the ability of E. coli to harness underground metabolism to compensate for the deletion of an essential biosynthetic pathway. By deleting all threonine deaminases, we generated a strain in which isoleucine biosynthesis was interrupted at the level of 2-ketobutyrate. Incubation of this strain under aerobic conditions resulted in the emergence of a novel 2-ketobutyrate biosynthesis pathway based upon the promiscuous cleavage of O-succinyl-L-homoserine by cystathionine γ-synthase (MetB). Under anaerobic conditions, pyruvate formate-lyase enabled 2-ketobutyrate biosynthesis from propionyl-CoA and formate. Surprisingly, we found this anaerobic route to provide a substantial fraction of isoleucine in a wild-type strain when propionate is available in the medium. This study demonstrates the selective advantage underground metabolism offers, providing metabolic redundancy and flexibility which allow for the best use of environmental carbon sources.

Current Status and Applications of Adaptive Laboratory Evolution in Industrial Microorganisms

Adaptive laboratory evolution (ALE) is an evolutionary engineering approach in artificial conditions that improves organisms through the imitation of natural evolution. Due to the development of multi-level omics technologies in recent decades, ALE can be performed for various purposes at the laboratory level. This review delineates the basics of the experimental design of ALE based on several ALE studies of industrial microbial strains and updates current strategies combined with progressed metabolic engineering, in silico modeling and automation to maximize the evolution efficiency. Moreover, the review sheds light on the applicability of ALE as a strain development approach that complies with non-recombinant preferences in various food industries. Overall, recent progress in the utilization of ALE for strain development leading to successful industrialization is discussed.

Tracking Bacterial Spoilage in Cosmetics by a New Bioanalytical Approach: API-SPME-GC-MS to Monitor MVOCs

The main goal of this work was the use of the powerful solid-phase microextraction-gas chromatography-mass spectrometry (SPME-GC-MS) technique to unequivocally identify microbial volatile organic compounds (MVOCs) derived from the enzymatic activity produced during metabolic processes using analytical profile index (API) biochemical tests. Three bacteria were selected for this study: Escherichia coli, Proteus mirabilis, and Pseudomonas aeruginosa. They were inoculated and incubated to both API components and real cosmetics, as well as to a mixture of them. Specific MVOCs were successfully identified as biomarkers for each one of the studied microorganisms: Indole and 2-nitrophenol as Escherichia coli markers, 2-undecanone and phenylethyl alcohol as Proteus mirabilis-specific markers, and 1-undecene and 2′-aminoacetophenone as Pseudomonas aeruginosa ones. In addition, a high number of MVOCs were identified as general markers of bacterial presence. The results revealed that the MVOCs’ formation is highly subtract dependent. Therefore, the ultimate and most challenging objective is to establish a relationship between the identified MVOCs and the original compound present in the substrate. This work establishes the design and development of this original approach, and its practical application to the control of microbial contamination in real cosmetic samples.

Metabolomics Analysis Reveals Global Metabolic Changes in the Evolved E. coli Strain with Improved Growth and 1-Butanol Production in Minimal Medium

Production of 1-butanol from microorganisms has garnered significant interest due to its prospect as a drop-in biofuel and precursor for a variety of commercially relevant chemicals. Previously, high 1-butanol titer has been reported in Escherichia coli strain JCL166, which contains a modified clostridial 1-butanol pathway. Although conventional and metabolomics-based strain improvement strategies of E. coli strain JCL166 have been successful in improving production in rich medium, 1-butanol titer was severely limited in minimal medium. To further improve growth and consequently 1-butanol production in minimal medium, adaptive laboratory evolution (ALE) using mutD5 mutator plasmid was done on JCL166. Comparative metabolomics analysis of JCL166 and BP1 revealed global perturbations in the evolved strain BP1 compared to JCL166 (44 out of 64 metabolites), encompassing major metabolic pathways such as glycolysis, nucleotide biosynthesis, and CoA-related processes. Collectively, these metabolic changes in BP1 result in improved growth and, consequently, 1-butanol production in minimal medium. Furthermore, we found that the mutation in ihfB caused by ALE had a significant effect on the metabolome profile of the evolved strain. This study demonstrates how metabolomics was utilized for characterization of ALE-developed strains to understand the overall effect of mutations acquired through evolution.

Understanding metabolic adaptation by using bacterial laboratory evolution and trans-omics analysis

Many diseases such as metabolic syndrome, cancer, inflammatory diseases, and pathological phenomena can be understood as an adaptive reconstitution of the metabolic state (metabolic adaptation). One of the effective approaches to reveal the property of metabolic networks is using model organisms such as microorganisms that are easier to experiment with than higher organisms. Using the laboratory evolution approach, we can elucidate the evolutionary dynamics in various stress environments, which provide us an understanding of the metabolic adaptation. In addition, the integration of omics data and phenotypic data enables us to clarify the genetic and phenotypic alterations during adaptation. In this review, we describe our recent studies on bacterial laboratory evolution and the omics approach to clarify the stress adaptation process. We have also obtained high-dimensional phenotypic data using our automated culture system. By combining these genomic and transcriptomic data within high-throughput phenotypic data, we can discuss the complex trans-omics network of metabolic adaptation.

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.

Continuous Adaptive Evolution of a Fast-Growing Corynebacterium glutamicum Strain Independent of Protocatechuate

Corynebacterium glutamicum is a commonly applied host for the industrial production of amino acids. While valued for its robustness, it is somewhat inferior to competing strains such as Escherichia coli because of the relatively low growth rate of 0.40 h-1 in synthetic, industrial media. Accordingly, adaptive laboratory evolution (ALE) experiments were performed in continuous cultivation mode to select for a growth-improved host. To ensure industrial attractiveness, this ALE study aimed at a reduction of dependency on costly growth-boosting additives such as protocatechuate (PCA) or complex media supplements. Consequently, double selection pressures were installed consisting of a steady increase in growth rate demands and a parallel reduction of complex medium fractions. Selection yielded C. glutamicum EVO5 achieving 0.54 h-1 and 1.03 gGlc gCDW -1 h-1 in minimal medium without abovementioned supplements. Sequencing revealed 10 prominent mutations, three of them in key regulator genes.

Experimental Evolution of Innovation and Novelty

How does novelty, a new, genetically based function, evolve? A compelling answer has been elusive because there are few model systems where both the genetic mechanisms generating novel functions and the ecological conditions that govern their origin and spread can be studied in detail. This review article considers what we have learned about the evolution of novelty from microbial selection experiments. This work reveals that the genetic routes to novelty can be more highly variable than standard models have led us to believe and underscores the importance of considering both genetics and ecology in this process.

Evolutionary design principles in metabolism

Microorganisms are ubiquitous and adapt to various dynamic environments to sustain growth. These adaptations accumulate, generating new traits forming the basis of evolution. Organisms adapt at various levels, such as gene regulation, signalling, protein-protein interactions and metabolism. Of these, metabolism forms the integral core of an organism for maintaining the growth and function of a cell. Therefore, studying adaptations in metabolic networks is crucial to understand the emergence of novel metabolic capabilities. Metabolic networks, composed of enzyme-catalysed reactions, exhibit certain repeating paradigms or design principles that arise out of different selection pressures. In this review, we discuss the design principles that are known to exist in metabolic networks, such as functional redundancy, modularity, flux coupling and exaptations. We elaborate on the studies that have helped gain insights highlighting the interplay of these design principles and adaptation. Further, we discuss how evolution plays a role in exploiting such paradigms to enhance the robustness of organisms. Looking forward, we predict that with the availability of ever-increasing numbers of bacterial, archaeal and eukaryotic genomic sequences, novel design principles will be identified, expanding our understanding of these paradigms shaped by varied evolutionary processes.

Adaptive laboratory evolution of a genome-reduced Escherichia coli

Synthetic biology aims to design and construct bacterial genomes harboring the minimum number of genes required for self-replicable life. However, the genome-reduced bacteria often show impaired growth under laboratory conditions that cannot be understood based on the removed genes. The unexpected phenotypes highlight our limited understanding of bacterial genomes. Here, we deploy adaptive laboratory evolution (ALE) to re-optimize growth performance of a genome-reduced strain. The basis for suboptimal growth is the imbalanced metabolism that is rewired during ALE. The metabolic rewiring is globally orchestrated by mutations in rpoD altering promoter binding of RNA polymerase. Lastly, the evolved strain has no translational buffering capacity, enabling effective translation of abundant mRNAs. Multi-omic analysis of the evolved strain reveals transcriptome- and translatome-wide remodeling that orchestrate metabolism and growth. These results reveal that failure of prediction may not be associated with understanding individual genes, but rather from insufficient understanding of the strain's systems biology.

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.

Directed strain evolution restructures metabolism for 1-butanol production in minimal media

Engineering a microbial strain for production sometimes entails metabolic modifications that impair essential physiological processes for growth or production. Restoring these functions may require amending a variety of non-obvious physiological networks, and thus, rational design strategies may not be practical. Here we demonstrate that growth and production may be restored by evolution that repairs impaired metabolic function. Furthermore, we use genomics, metabolomics and proteomics to identify several underlying mutations and metabolic perturbations that allow metabolism to repair. Previously, high titers of butanol production were achieved by Escherichia coli using a growth-coupled, modified Clostridial CoA-dependent pathway after all native fermentative pathways were deleted. However, production was only observed in rich media. Native metabolic function of the host was unable to support growth and production in minimal media. We use directed cell evolution to repair this phenotype and observed improved growth, titers and butanol yields. We found a mutation in pcnB which resulted in decreased plasmid copy numbers and pathway enzymes to balance resource utilization. Increased protein abundance was measured for biosynthetic pathways, glycolytic enzymes have increased activity, and adenosyl energy charge was increased. We also found mutations in the ArcAB two-component system and integration host factor (IHF) that tune redox metabolism to alter byproduct formation. These results demonstrate that directed strain evolution can enable systematic adaptations to repair metabolic function and enhance microbial production. Furthermore, these results demonstrate the versatile repair capabilities of cell metabolism and highlight important aspects of cell physiology that are required for production in minimal media.

Engineering Corynebacterium glutamicum for methanol-dependent growth and glutamate production

Methanol is a promising feedstock for bioproduction of fuels and chemicals, thus massive efforts have been devoted to engineering non-native methylotrophic platform microorganisms to utilize methanol. Herein, we rationally designed and experimentally engineered the industrial workhorse Corynebacterium glutamicum to serve as a methanol-dependent synthetic methylotroph. The cell growth of the methanol-dependent strain relies on co-utilization of methanol and xylose, and most notably methanol is an indispensable carbon source. Due to the methanol-dependent characteristic, adaptive laboratory evolution was successfully applied to improving methanol utilization. The evolved mutant showed a 20-fold increase in cell growth on methanol-xylose minimal medium and utilized methanol and xylose with a high mole ratio of 3.83:1. ¹³C-labeling experiments demonstrated that the carbon derived from methanol was assimilated into intracellular building blocks, high-energy carriers, cofactors, and biomass (up to 63% ¹³C-labeling). By inhibiting cell wall biosynthesis, methanol-dependent glutamate production was also achieved, demonstrating the potential application in bioconversion of methanol into useful chemicals. Genetic mutations detected in the evolved strains indicate the importance of intracellular NAD⁺/NADH ratio, substrate uptake, and methanol tolerance on methanol utilization. This study reports significant improvement in the area of developing fully synthetic methylotrophs.

Accelerating pathway evolution by increasing the gene dosage of chromosomal segments

Experimental evolution is a critical tool in many disciplines, including metabolic engineering and synthetic biology. However, current methods rely on the chance occurrence of a key step that can dramatically accelerate evolution in natural systems, namely increased gene dosage. Our studies sought to induce the targeted amplification of chromosomal segments to facilitate rapid evolution. Since increased gene dosage confers novel phenotypes and genetic redundancy, we developed a method, Evolution by Amplification and Synthetic Biology (EASy), to create tandem arrays of chromosomal regions. In Acinetobacter baylyi, EASy was demonstrated on an important bioenergy problem, the catabolism of lignin-derived aromatic compounds. The initial focus on guaiacol (2-methoxyphenol), a common lignin degradation product, led to the discovery of Amycolatopsis genes (gcoAB) encoding a cytochrome P450 enzyme that converts guaiacol to catechol. However, chromosomal integration of gcoAB in Pseudomonas putida or A. baylyi did not enable guaiacol to be used as the sole carbon source despite catechol being a growth substrate. In ∼1,000 generations, EASy yielded alleles that in single chromosomal copy confer growth on guaiacol. Different variants emerged, including fusions between GcoA and CatA (catechol 1,2-dioxygenase). This study illustrates the power of harnessing chromosomal gene amplification to accelerate the evolution of desirable traits.

Enhancement of Metallosphaera sedula Bioleaching by Targeted Recombination and Adaptive Laboratory Evolution

Thermophilic and lithoautotrophic archaea such as Metallosphaera sedula occupy acidic, metal-rich environments and are used in biomining processes. Biotechnological approaches could accelerate these processes and improve metal recovery by biomining organisms, but systems for genetic manipulation in these organisms are currently lacking. To gain a better understanding of the interplay between metal resistance, autotrophy, and lithotrophic metabolism, a genetic system was developed for M. sedula and used to evaluate parameters governing the efficiency of copper bioleaching. Additionally, adaptive laboratory evolution was used to select for naturally evolved M. sedula cell lines with desirable phenotypes for biomining, and these adapted cell lines were shown to have increased bioleaching capacity and efficiency. Genomic methods were used to analyze mutations that led to resistance in the experimentally evolved cell lines, while transcriptomics was used to examine changes in stress-inducible gene expression specific to the environmental conditions.

Random sequences rapidly evolve into de novo promoters

How new functions arise de novo is a fundamental question in evolution. We studied de novo evolution of promoters in Escherichia coli by replacing the lac promoter with various random sequences of the same size (~100 bp) and evolving the cells in the presence of lactose. We find that ~60% of random sequences can evolve expression comparable to the wild-type with only one mutation, and that ~10% of random sequences can serve as active promoters even without evolution. Such a short mutational distance between random sequences and active promoters may improve the evolvability, yet may also lead to accidental promoters inside genes that interfere with normal expression. Indeed, our bioinformatic analyses indicate that E. coli was under selection to reduce accidental promoters inside genes by avoiding promoter-like sequences. We suggest that a low threshold for functionality balanced by selection against undesired targets can increase the evolvability by making new beneficial features more accessible.

Bacterial promoters initiate gene transcription and have distinct sequence features. Here, the authors show that random sequences that contain no information are just on the verge of functioning as promoters in Escherichia coli.

Experimental evolution of diverse Escherichia coli metabolic mutants identifies genetic loci for convergent adaptation of growth rate

Cell growth is determined by substrate availability and the cell’s metabolic capacity to assimilate substrates into building blocks. Metabolic genes that determine growth rate may interact synergistically or antagonistically, and can accelerate or slow growth, depending on genetic background and environmental conditions. We evolved a diverse set of Escherichia coli single-gene deletion mutants with a spectrum of growth rates and identified mutations that generally increase growth rate. Despite the metabolic differences between parent strains, mutations that enhanced growth largely mapped to core transcription machinery, including the β and β’ subunits of RNA polymerase (RNAP) and the transcription elongation factor, NusA. The structural segments of RNAP that determine enhanced growth have been previously implicated in antibiotic resistance and in the control of transcription elongation and pausing. We further developed a computational framework to characterize how the transcriptional changes that occur upon acquisition of these mutations affect growth rate across strains. Our experimental and computational results provide evidence for cases in which RNAP mutations shift the competitive balance between active transcription and gene silencing. This study demonstrates that mutations in specific regions of RNAP are a convergent adaptive solution that can enhance the growth rate of cells from distinct metabolic states.

The loss of a metabolic function caused by gene deletion can be compensated, in certain cases, by the concurrent mutation of a second gene. Whether such gene pairs share a local chemical or regulatory relationship or interact via a non-local mechanism has implications for the co-evolution of genetic changes, development of alternatives to gene therapy, and the design of combination antimicrobial therapies that select against resistance. Yet, we lack a comprehensive knowledge of adaptive responses to metabolic mutations, and our understanding of the mechanisms underlying genetic rescue remains limited. We present results of a laboratory evolution approach that has the potential to address both challenges, showing that mutations in specific regions of RNA polymerase enhance growth rates of distinct mutant strains of Escherichia coli with a spectrum of growth defects. Several of these adaptive mutations are deleterious when engineered directly into the original wild-type strain under alternative cultivation conditions, and thus have epistatic rescue properties when paired with the corresponding primary metabolic gene deletions. Our combination of adaptive evolution, directed genetic engineering, and mathematical analysis of transcription and growth rate distinguishes between rescue interactions that are specific or non-specific to a particular deletion. Our study further supports a model for RNA polymerase as a locus of convergent adaptive evolution from different sub-optimal metabolic starting points.

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.

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

Adaptive laboratory evolution (ALE) is a widely-used method for improving the fitness of microorganisms in selected environmental conditions. It has been applied previously to Escherichia coli K-12 MG1655 during aerobic exponential growth on glucose minimal media, a frequently used model organism and growth condition, to probe the limits of E. coli growth rate and gain insights into fast growth phenotypes. Previous studies have described up to 1.6-fold increases in growth rate following ALE, and have identified key causal genetic mutations and changes in transcriptional patterns. Here, we report for the first time intracellular metabolic fluxes for six such adaptively evolved strains, as determined by high-resolution ¹³C-metabolic flux analysis. Interestingly, we found that intracellular metabolic pathway usage changed very little following adaptive evolution. Instead, at the level of central carbon metabolism the faster growth was facilitated by proportional increases in glucose uptake and all intracellular rates. Of the six evolved strains studied here, only one strain showed a small degree of flux rewiring, and this was also the strain with unique genetic mutations. A comparison of fluxes with two other wild-type (unevolved) E. coli strains, BW25113 and BL21, showed that inter-strain differences are greater than differences between the parental and evolved strains. Principal component analysis highlighted that nearly all flux differences (95%) between the nine strains were captured by only two principal components. The distance between measured and flux balance analysis predicted fluxes was also investigated. It suggested a relatively wide range of similar stoichiometric optima, which opens new questions about the path-dependency of adaptive evolution.

Biosensor-Enabled Directed Evolution to Improve Muconic Acid Production in Saccharomyces cerevisiae

Muconic acid is a valuable platform chemical with potential applications in the production of polymers such as nylon and polyethylene terephthalate (PET). The conjugate base, muconate, has been previously biosynthesized in the bacterial host Escherichia coli. Likewise, previous significant pathway engineering lead to the first reported instance of rationally engineered production of muconic acid in the yeast Saccharomyces cerevisiae. To further increase muconic acid production in this host, a combined adaptive laboratory evolution (ALE) strategy and rational metabolic engineering is employed. To this end, a biosensor module that responds to the endogenous aromatic amino acid (AAA) as a surrogate for pathway flux is adapted. Following two rounds of ALE coupled with an anti-metabolite feeding strategy, the strains with improved AAA pathway flux is isolated. Next, it is demonstrated that this increased flux can be redirected into the composite muconic acid pathway with a threefold increase in the total titer of the composite pathway compared to our previously engineered strain. Finally, a truncation of the penta-functional ARO1 protein is complemented and overexpress an endogenous aromatic decarboxylase to establish a final strain capable of producing 0.5 g L^-1 muconic acid in shake flasks and 2.1 g L^-1 in a fed-batch bioreactor with a yield of 12.9 mg muconic acid/g glucose at the rate of 9.0 mg h^-1 . This value represents the highest titer of muconic acid reported to date in S. cerevisiae, in addition to the highest reported titer of a shikimate pathway derivative in this host.

ROS mediated selection for increased NADPH availability in Escherichia coli

The economical production of chemicals and fuels by microbial processes remains an intense area of interest in biotechnology. A key limitation in such efforts concerns the availability of key co-factors, in this case NADPH, required for target pathways. Many of the strategies pursued for increasing NADPH availability in Escherichia coli involve manipulations to the central metabolism, which can create redox imbalances and overall growth defects. In this study we used a reactive oxygen species based selection to search for novel methods of increasing NADPH availability. We report a loss of function mutation in the gene hdfR appears to increase NADPH availability in E. coli. Additionally, we show this excess NADPH can be used to improve the production of 3HP in E. coli.