Co-utilization of glucose and xylose by evolved Thermus thermophilus LC113 strain elucidated by (13)C metabolic flux analysis and whole genome sequencing

Current status of metabolic engineering of microorganisms for bioethanol production by effective utilization of pentose sugars of lignocellulosic biomass

Lignocellulosic biomass, consisting of homo- and heteropolymeric sugars, acts as a substrate for the generation of valuable biochemicals and biomaterials. The readily available hexoses are easily utilized by microbes due to the presence of transporters and native metabolic pathways. But, utilization of pentose sugar viz., xylose and arabinose are still challenging due to several reasons including (i) the absence of the particular native pathways and transporters, (ii) the presence of inhibitors, and (iii) lower uptake of pentose sugars. These challenges can be overcome by manipulating metabolic pathways/glycosidic enzymes cascade by using genetic engineering tools involving inverse-metabolic engineering, ex-vivo isomerization, Adaptive Laboratory Evolution, Directed Metabolic Engineering, etc. Metabolic engineering of bacteria and fungi for the utilization of pentose sugars for bioethanol production is the focus area of research in the current decade. This review outlines current approaches to biofuel development and strategies involved in the metabolic engineering of different microbes that can uptake pentose for bioethanol production.

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.

Identification of Thermostable Xylose Reductase from Thermothelomyces thermophilus: A Biochemical Characterization Approach to Meet Biofuel Challenges

The constant rise in energy demands, costs, and concerns about global warming has created a demand for new renewable alternative fuels that can be produced sustainably. Lignocellulose biomass can act as an excellent energy source and various value-added compounds like xylitol. In this research study, we have explored the xylose reductase that was obtained from the genome of a thermophilic fungus Thermothelomyces thermophilus while searching for an enzyme to convert xylose to xylitol at higher temperatures. The recombinant thermostable TtXR histidine-tagged fusion protein was expressed in Escherichia coli and successfully purified for the first time. Further, it was characterized for its function and novel structure at varying temperatures and pH. The enzyme showed maximal activity at 7.0 pH and favored  d-xylose over other pentoses and hexoses. Biophysical approaches such as ultraviolet-visible (UV-visible), fluorescence spectrometry, and far-UV circular dichroism (CD) spectroscopy were used to investigate the structural integrity of pure TtXR. This research highlights the potential application of uncharacterized xylose reductase as an alternate source for the effective utilization of lignocellulose in fermentation industries at elevated temperatures. Moreover, this research would give environment-friendly and long-term value-added products, like xylitol, from lignocellulosic feedstock for both scientific and commercial purposes.

Genome mining discovery of hydrogen production pathway of Klebsiella sp. WL1316 fermenting cotton stalk hydrolysate

Genome sequencing was used to identify key genes for the generation of hydrogen gas through cotton stalk hydrolysate fermentation by Klebsiella sp. WL1316. Genome annotation indicated that the genome size was 5.2 Mb with GC content 57.6%. Xylose was metabolized in the pentose phosphate pathway via the conversion of xylose to xylulose in Klebsiella sp. WL1316. This strain contained diverse formate-hydrogen lyases and hydrogenases with gene numbers higher than closely related species. A metabolic network involving glucose, xylose utilisation, and fermentative hydrogen production was reconstructed. Metabolic analysis of key node metabolites showed that glucose and xylose metabolism influenced biomass synthesis and biohydrogen production. Formic acid accumulated during fermentation at 24-48 h but decreased sharply after 48 h, illustrating the splitting of formic acid to hydrogen gas during early-to-mid fermentation. The Kreb's cycle was the main competitive metabolic branch of biohydrogen synthesis at 24 h of fermentation. Lactic and acetic acid fermentation and late ethanol accumulation competed the carbon skeleton of biohydrogen synthesis after 72 h of fermentation, indicating that these competitive pathways are regulated in middle-to-late fermentation (48-96 h). This study is the first to elucidate the metabolic mechanisms of mixed sugar utilisation and biohydrogen synthesis based on genomic information.

Recent advances in metabolic engineering-integration of in silico design and experimental analysis of metabolic pathways

Microorganisms are widely used to produce valuable compounds. Because thousands of metabolic reactions occur simultaneously and many metabolic reactions are related to target production and cell growth, the development of a rational design method for metabolic pathway modification to optimize target production is needed. In this paper, recent advances in metabolic engineering are reviewed, specifically considering computational pathway modification design and experimental evaluation of metabolic fluxes by ¹³C-metabolic flux analysis. Computational tools for seeking effective gene deletion targets and recruiting heterologous genes are described in flux balance analysis approaches. A kinetic model and adaptive laboratory evolution were applied to identify and eliminate the rate-limiting step in metabolic pathways. Data science-based approaches for process monitoring and control are described to maximize the performance of engineered cells in bioreactors.

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

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

High-resolution 13C metabolic flux analysis

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

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.

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.

Predicting Dynamic Metabolic Demands in the Photosynthetic Eukaryote Chlorella vulgaris

Phototrophic organisms exhibit a highly dynamic proteome, adapting their biomass composition in response to diurnal light/dark cycles and nutrient availability. Here, we used experimentally determined biomass compositions over the course of growth to determine and constrain the biomass objective function (BOF) in a genome-scale metabolic model of Chlorella vulgaris UTEX 395 over time. Changes in the BOF, which encompasses all metabolites necessary to produce biomass, influence the state of the metabolic network thus directly affecting predictions. Simulations using dynamic BOFs predicted distinct proteome demands during heterotrophic or photoautotrophic growth. Model-driven analysis of extracellular nitrogen concentrations and predicted nitrogen uptake rates revealed an intracellular nitrogen pool, which contains 38% of the total nitrogen provided in the medium for photoautotrophic and 13% for heterotrophic growth. Agreement between flux and gene expression trends was determined by statistical comparison. Accordance between predicted flux trends and gene expression trends was found for 65% of multisubunit enzymes and 75% of allosteric reactions. Reactions with the highest agreement between simulations and experimental data were associated with energy metabolism, terpenoid biosynthesis, fatty acids, nucleotides, and amino acid metabolism. Furthermore, predicted flux distributions at each time point were compared with gene expression data to gain new insights into intracellular compartmentalization, specifically for transporters. A total of 103 genes related to internal transport reactions were identified and added to the updated model of C. vulgaris, iCZ946, thus increasing our knowledgebase by 10% for this model green alga.

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

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

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

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

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.

Physiological, metabolic and biotechnological features of extremely thermophilic microorganisms

The current upper thermal limit for life as we know it is approximately 120°C. Microorganisms that grow optimally at temperatures of 75°C and above are usually referred to as 'extreme thermophiles' and include both bacteria and archaea. For over a century, there has been great scientific curiosity in the basic tenets that support life in thermal biotopes on earth and potentially on other solar bodies. Extreme thermophiles can be aerobes, anaerobes, autotrophs, heterotrophs, or chemolithotrophs, and are found in diverse environments including shallow marine fissures, deep sea hydrothermal vents, terrestrial hot springs-basically, anywhere there is hot water. Initial efforts to study extreme thermophiles faced challenges with their isolation from difficult to access locales, problems with their cultivation in laboratories, and lack of molecular tools. Fortunately, because of their relatively small genomes, many extreme thermophiles were among the first organisms to be sequenced, thereby opening up the application of systems biology-based methods to probe their unique physiological, metabolic and biotechnological features. The bacterial genera Caldicellulosiruptor, Thermotoga and Thermus, and the archaea belonging to the orders Thermococcales and Sulfolobales, are among the most studied extreme thermophiles to date. The recent emergence of genetic tools for many of these organisms provides the opportunity to move beyond basic discovery and manipulation to biotechnologically relevant applications of metabolic engineering. WIREs Syst Biol Med 2017, 9:e1377. doi: 10.1002/wsbm.1377 For further resources related to this article, please visit the WIREs website.

Complete genome sequence of Thermus brockianus GE-1 reveals key enzymes of xylan/xylose metabolism

Thermus brockianus strain GE-1 is a thermophilic, Gram-negative, rod-shaped and non-motile bacterium that was isolated from the Geysir geothermal area, Iceland. Like other thermophiles, Thermus species are often used as model organisms to understand the mechanism of action of extremozymes, especially focusing on their heat-activity and thermostability. Genome-specific features of T. brockianus GE-1 and their properties further help to explain processes of the adaption of extremophiles at elevated temperatures. Here we analyze the first whole genome sequence of T. brockianus strain GE-1. Insights of the genome sequence and the methodologies that were applied during de novo assembly and annotation are given in detail. The finished genome shows a phred quality value of QV50. The complete genome size is 2.38 Mb, comprising the chromosome (2,035,182 bp), the megaplasmid pTB1 (342,792 bp) and the smaller plasmid pTB2 (10,299 bp). Gene prediction revealed 2,511 genes in total, including 2,458 protein-encoding genes, 53 RNA and 66 pseudo genes. A unique genomic region on megaplasmid pTB1 was identified encoding key enzymes for xylan depolymerization and xylose metabolism. This is in agreement with the growth experiments in which xylan is utilized as sole source of carbon. Accordingly, we identified sequences encoding the xylanase Xyn10, an endoglucanase, the membrane ABC sugar transporter XylH, the xylose-binding protein XylF, the xylose isomerase XylA catalyzing the first step of xylose metabolism and the xylulokinase XylB, responsible for the second step of xylose metabolism. Our data indicate that an ancestor of T. brockianus obtained the ability to use xylose as alternative carbon source by horizontal gene transfer.

Engineering Bacillus licheniformis as a thermophilic platform for the production of l-lactic acid from lignocellulose-derived sugars

BACKGROUND

Bacillus licheniformis MW3 as a GRAS and thermophilic strain is a promising microorganism for chemical and biofuel production. However, its capacity to co-utilize glucose and xylose, the major sugars found in lignocellulosic biomass, is severely impaired by glucose-mediated carbon catabolite repression (CCR). In this study, a "dual-channel" process was implemented to engineer strain MW3 for simultaneous utilization of glucose and xylose, using l-lactic acid as a target product.

RESULTS

A non-phosphotransferase system (PTS) glucose uptake route was activated via deletion of the glucose transporter gene ptsG and introduction of the galactose permease gene galP. After replacing the promoter of glucokinase gene glck with the strong promoter P_als, the engineered strain recovered glucose consumption and utilized glucose and xylose simultaneously. Meanwhile, to improve the consumption rate of xylose in this strain, several measures were undertaken, such as relieving the regulation of the xylose repressor XylR, reducing the catabolite-responsive element, and optimizing the rate-limiting step. Knockout of ethanol and acetic acid pathway genes further increased lactic acid yield by 6.2%. The resultant strain, RH15, was capable of producing 121.9 g/L l-lactic acid at high yield (95.3%) after 40 h of fermentation from a mixture of glucose and xylose. When a lignocellulosic hydrolysate was used as the substrate, 99.3 g/L l-lactic acid was produced within 40 h, with a specific productivity of 2.48 g/[L h] and a yield of 94.6%.

CONCLUSIONS

Our engineered strain B. licheniformis RH15 could thermophilically produced l-lactic acid from lignocellulosic hydrolysate with relatively high concentration and productivity at levels that were competitive with most reported cases of l-lactic acid-producers. Thus, the engineered strain might be used as a platform for the production of other chemicals. In addition to engineering the B. licheniformis strain, the "dual-channel" process might serve as an alternative method for engineering a variety of other strains.

Recent applications of metabolomics to advance microbial biofuel production

Biofuel production from plant biomass is a promising source of renewable energy [1]. However, efficient biofuel production involves the complex task of engineering high-performance microorganisms, which requires detailed knowledge of metabolic function and regulation. This review highlights the potential of mass-spectrometry-based metabolomic analysis to guide rational engineering of biofuel-producing microbes. We discuss recent studies that apply knowledge gained from metabolomic analyses to increase the productivity of engineered pathways, characterize the metabolism of emerging biofuel producers, generate novel bioproducts, enable utilization of lignocellulosic feedstock, and improve the stress tolerance of biofuel producers.

Comprehensive analysis of glucose and xylose metabolism in Escherichia coli under aerobic and anaerobic conditions by 13C metabolic flux analysis

Glucose and xylose are the two most abundant sugars derived from the breakdown of lignocellulosic biomass. While aerobic glucose metabolism is relatively well understood in E. coli, until now there have been only a handful of studies focused on anaerobic glucose metabolism and no ¹³C-flux studies on xylose metabolism. In the absence of experimentally validated flux maps, constraint-based approaches such as MOMA and RELATCH cannot be used to guide new metabolic engineering designs. In this work, we have addressed this critical gap in current understanding by performing comprehensive characterizations of glucose and xylose metabolism under aerobic and anaerobic conditions, using recent state-of-the-art techniques in ¹³C metabolic flux analysis (¹³C-MFA). Specifically, we quantified precise metabolic fluxes for each condition by performing parallel labeling experiments and analyzing the data through integrated ¹³C-MFA using the optimal tracers [1,2-¹³C]glucose, [1,6-¹³C]glucose, [1,2-¹³C]xylose and [5-¹³C]xylose. We also quantified changes in biomass composition and confirmed turnover of macromolecules by applying [U-¹³C]glucose and [U-¹³C]xylose tracers. We demonstrated that under anaerobic growth conditions there is significant turnover of lipids and that a significant portion of CO₂ originates from biomass turnover. Using knockout strains, we also demonstrated that β-oxidation is critical for anaerobic growth on xylose. Quantitative analysis of co-factor balances (NADH/FADH₂, NADPH, and ATP) for different growth conditions provided new insights regarding the interplay of energy and redox metabolism and the impact on E. coli cell physiology.

Tracing metabolism from lignocellulosic biomass and gaseous substrates to products with stable-isotopes

Engineered microbes offer a practical and sustainable alternative to traditional industrial approaches. To increase the economic feasibility of biological processes, microbial isolates are engineered to take up inexpensive feedstocks (including lignocellulosic biomass, syngas, methane, and carbon dioxide), and convert them into substrates of central metabolism and further into value-added products. To trace the metabolism of these feedstocks into products, isotopic tracers are applied together with isotopomer analysis techniques such as ¹³C-metabolic flux analysis to provide a detailed picture of pathway utilization. Flux data is then integrated with kinetic models and constraint-based approaches to identify metabolic bottlenecks, propose novel metabolic engineering strategies, and improve process performance.