Advancing metabolic engineering through systems biology of industrial microorganisms

Integration of metabolism and regulation reveals rapid adaptability to growth on non-native substrates

Engineering synthetic heterotrophy is a key to the efficient bio-based valorization of renewable and waste substrates. Among these, engineering hemicellulosic pentose utilization has been well-explored in Saccharomyces cerevisiae (yeast) over several decades-yet the answer to what makes their utilization inherently recalcitrant remains elusive. Through implementation of a semi-synthetic regulon, we find that harmonizing cellular and engineering objectives are a key to obtaining highest growth rates and yields with minimal metabolic engineering effort. Concurrently, results indicate that "extrinsic" factors-specifically, upstream genes that direct flux of pentoses into central carbon metabolism-are rate-limiting. We also reveal that yeast metabolism is innately highly adaptable to rapid growth on non-native substrates and that systems metabolic engineering (i.e., functional genomics, network modeling, etc.) is largely unnecessary. Overall, this work provides an alternate, novel, holistic (and yet minimalistic) approach based on integrating non-native metabolic genes with a native regulon system.

Systems Metabolic Engineering of Industrial Microorganisms

The green and sustainable production of chemicals, materials, fuels, food, and pharmaceuticals has become a key solution to the global energy and environmental crisis [...]

Heterologous production of Cannabis sativa-derived specialised metabolites of medicinal significance - Insights into engineering strategies

Cannabis sativa L. has been known for at least 2000 years as a source of important, medically significant specialised metabolites and several bio-active molecules have been enriched from multiple chemotypes. However, due to the many levels of complexity in both the commercial cultivation of cannabis and extraction of its specialised metabolites, several heterologous production approaches are being pursued in parallel. In this review, we outline the recent achievements in engineering strategies used for heterologous production of cannabinoids, terpenes and flavonoids along with their strength and weakness. We provide an overview of the specialised metabolism pathway in C. sativa and a comprehensive list of the specialised metabolites produced along with their medicinal significance. We highlight cannabinoid-like molecules produced by other species. We discuss the key biosynthetic enzymes and their heterologous production using various hosts such as microbial and eukaryotic systems. A brief discussion on complementary production strategies using co-culturing and cell-free systems is described. Various approaches to optimise specialised metabolite production through co-expression, enzyme engineering and pathway engineering are discussed. We derive insights from recent advances in metabolic engineering of hosts with improved precursor supply and suggest their application for the production of C. sativa speciality metabolites. We present a collation of non-conventional hosts with speciality traits that can improve the feasibility of commercial heterologous production of cannabis-based specialised metabolites. We provide a perspective of emerging research in synthetic biology, allied analytical techniques and plant heterologous platforms as focus areas for heterologous production of cannabis specialised metabolites in the future.

Engineering microbial cell viability for enhancing chemical production by second codon engineering

Microbial cell factories offer a promising strategy for the sustainable production of industrial chemicals from renewable biomass feedstock. However, their performance is often limited by poor microbial cell viability (MCV). Here, MCV was engineered to enhance chemical production by optimizing the regulation of lifespan-specific genes to reduce the accumulation of reactive oxygen species (ROS). In Escherichia coli, MCV was improved by reducing ROS accumulation using second codon engineering to regulate hypoxia-inducible transcription factor (arcA), resulting in lysine production up to 213 g L^-1 with its productivity 5.90 g L^-1·h^-1. In Saccharomyces cerevisiae, MCV was increased by decreasing ROS accumulation using second codon engineering to fine-tune ceramide synthase (lag1), leading to glucaric acid production up to 9.50 g L^-1 with its productivity 0.057 g L^-1·h^-1. These results demonstrate that engineering MCV is a potential strategy to boost the performance of microbial cell factories in industrial processes.

The Escherichia coli Amino Acid Uptake Protein CycA: Regulation of Its Synthesis and Practical Application in l-Isoleucine Production

Amino acid transport systems perform important physiological functions; their role should certainly be considered in microbial production of amino acids. Typically, in the context of metabolic engineering, efforts are focused on the search for and application of specific amino acid efflux pumps. However, in addition, importers can also be used to improve the industrial process as a whole. In this study, the protein CycA, which is known for uptake of nonpolar amino acids, was characterized from the viewpoint of regulating its expression and range of substrates. We prepared a cycA-overexpressing strain and found that it exhibited high sensitivity to branched-chain amino acids and their structural analogues, with relatively increased consumption of these amino acids, suggesting that they are imported by CycA. The expression of cycA was found to be dependent on the extracellular concentrations of substrate amino acids. The role of some transcription factors in cycA expression, including of Lrp and Crp, was studied using a reporter gene construct. Evidence for the direct binding of Crp to the cycA regulatory region was obtained using a gel-retardation assay. The enhanced import of named amino acids due to cycA overexpression in the l-isoleucine-producing strain resulted in a significant reduction in the generation of undesirable impurities. This work demonstrates the importance of uptake systems with respect to their application in metabolic engineering.

Modeling and Simulation of Batch Sugarcane Alcoholic Fermentation Using the Metabolic Model

The present work sought to implement a model different from the more traditional ones for the fermentation process of ethanol production by the action of the fungus Saccharomyces cerevisiae, using a relevant metabolic network based on the glycolytic Embden–Meyerhof–Parnas route, also called “EMP”. We developed two models to represent this phenomenon. In the first model, we used the simple and unbranched EMP route, with a constant concentration of microorganisms throughout the process and glucose as the whole substrate. We called this first model “SR”, regarding the Portuguese name “sem ramificações”, which means “no branches”. We developed the second model by simply adding some branches to the SR model. We called this model “CR”, regarding the Portuguese name “com ramificações”, which means “with branches”. Both models were implemented in MATLABTM software considering a constant temperature equal to 32 °C, similar to that practiced in sugar and ethanol plants, and a wide range of substrate concentrations, ranging from 30 to 100 g/L, and all the enzymes necessary for fermentation were already expressed in the cells so all the enzymes showed a constant concentration throughout the fermentation. The addition of common branches to the EMP route resulted in a considerable improvement in the results, especially predicting ethanol production closer to what we saw experimentally. Therefore, the results obtained are promising, making adjustments consistent with experimental data, meaning that all the models proposed here are a good basis for the development of future metabolic models of discontinuous fermentative processes.

Development and characterization of efficient xylose utilization strains of Zymomonas mobilis

BACKGROUND

Efficient use of glucose and xylose is a key for the economic production of lignocellulosic biofuels and biochemicals, and different recombinant strains have been constructed for xylose utilization including those using Zymomonas mobilis as the host. However, the xylose utilization efficiency still needs to be improved. In this work, the strategy of combining metabolic engineering and adaptive laboratory evolution (ALE) was employed to develop recombinant Z. mobilis strains that can utilize xylose efficiently at high concentrations, and NGS-based genome resequencing and RNA-Seq transcriptomics were performed for strains evolved after serial transfers in different media to understand the impact of xylose and differences among strains with different xylose-utilization capabilities at molecular level.

RESULTS

Heterologous genes encoding xylose isomerase and xylulokinase were evaluated, which were then introduced into xylose-utilizing strain Z. mobilis 8b to enhance its capacity of xylose utilization. The results demonstrated that the effect of three xylose isomerases on xylose utilization was different, and the increase of copy number of xylose metabolism genes can improve xylose utilization. Among various recombinant strains constructed, the xylose utilization capacity of the recombinant strain 8b-RsXI-xylB was the best, which was further improved through continuous adaption with 38 transfers over 100 days in 50 g/L xylose media. The fermentation performances of the parental strain 8b, the evolved 8b-S38 strain with the best xylose utilization capability, and the intermediate strain 8b-S8 in different media were compared, and the results showed that only 8b-S38 could completely consume xylose at 50 g/L and 100 g/L concentrations. In addition, the xylose consumption rate of 8b-S38 was faster than that of 8b at different xylose concentrations from 50 to 150 g/L, and the ethanol yield increased by 16 ~ 40%, respectively. The results of the mixed-sugar fermentation also demonstrated that 8b-S38 had a higher xylose consumption rate than 8b, and its maximum ethanol productivity was 1.2 ~ 1.4 times higher than that of 8b and 8b-S8. Whole-genome resequencing identified three common genetic changes in 8b-S38 compared with 8b and 8b-S8. RNA-Seq study demonstrated that the expression levels of genes encoding chaperone proteins, ATP-dependent proteases, phage shock proteins, ribosomal proteins, flagellar operons, and transcriptional regulators were significantly increased in xylose media in 8b-S38. The up-regulated expression of these genes may therefore contribute to the efficient xylose utilization of 8b-S38 by maintaining the normal cell metabolism and growth, repairing cellular damages, and rebalancing cellular energy to help cells resist the stressful environment.

CONCLUSIONS

This study provides gene candidates to improve xylose utilization, and the result of expressing an extra copy of xylose isomerase and xylulokinase improved xylose utilization also provides a direction for efficient xylose-utilization strain development in other microorganisms. In addition, this study demonstrated the necessity to combine metabolic engineering and ALE for industrial strain development. The recombinant strain 8b-S38 can efficiently metabolize xylose for ethanol fermentation at high xylose concentrations as well as in mixed sugars of glucose and xylose, which could be further developed as the microbial biocatalyst for the production of lignocellulosic biofuels and biochemicals.

D-Xylose Sensing in Saccharomyces cerevisiae: Insights from D-Glucose Signaling and Native D-Xylose Utilizers

Extension of the substrate range is among one of the metabolic engineering goals for microorganisms used in biotechnological processes because it enables the use of a wide range of raw materials as substrates. One of the most prominent examples is the engineering of baker's yeast Saccharomyces cerevisiae for the utilization of d-xylose, a five-carbon sugar found in high abundance in lignocellulosic biomass and a key substrate to achieve good process economy in chemical production from renewable and non-edible plant feedstocks. Despite many excellent engineering strategies that have allowed recombinant S. cerevisiae to ferment d-xylose to ethanol at high yields, the consumption rate of d-xylose is still significantly lower than that of its preferred sugar d-glucose. In mixed d-glucose/d-xylose cultivations, d-xylose is only utilized after d-glucose depletion, which leads to prolonged process times and added costs. Due to this limitation, the response on d-xylose in the native sugar signaling pathways has emerged as a promising next-level engineering target. Here we review the current status of the knowledge of the response of S. cerevisiae signaling pathways to d-xylose. To do this, we first summarize the response of the native sensing and signaling pathways in S. cerevisiae to d-glucose (the preferred sugar of the yeast). Using the d-glucose case as a point of reference, we then proceed to discuss the known signaling response to d-xylose in S. cerevisiae and current attempts of improving the response by signaling engineering using native targets and synthetic (non-native) regulatory circuits.

Utilization of a Wheat Sidestream for 5-Aminovalerate Production in Corynebacterium glutamicum

Production of plastics from petroleum-based raw materials extensively contributes to global pollution and CO2 emissions. Biotechnological production of functionalized monomers can reduce the environmental impact, in particular when using industrial sidestreams as feedstocks. Corynebacterium glutamicum, which is used in the million-ton-scale amino acid production, has been engineered for sustainable production of polyamide monomers. In this study, wheat sidestream concentrate (WSC) from industrial starch production was utilized for production of l-lysine-derived bifunctional monomers using metabolically engineered C. glutamicum strains. Growth of C. glutamicum on WSC was observed and could be improved by hydrolysis of WSC. By heterologous expression of the genes xylA Xc B Cg (xylA from Xanthomonas campestris) and araBAD Ec from E. coli, xylose, and arabinose in WSC hydrolysate (WSCH), in addition to glucose, could be consumed, and production of l-lysine could be increased. WSCH-based production of cadaverine and 5-aminovalerate (5AVA) was enabled. To this end, the lysine decarboxylase gene ldcC Ec from E. coli was expressed alone or for conversion to 5AVA cascaded either with putrescine transaminase and dehydrogenase genes patDA Ec from E. coli or with putrescine oxidase gene puo Rq from Rhodococcus qingshengii and patD Ec . Deletion of the l-glutamate dehydrogenase-encoding gene gdh reduced formation of l-glutamate as a side product for strains with either of the cascades. Since the former cascade (ldcC Ec -patDA Ec ) yields l-glutamate, 5AVA production is coupled to growth by flux enforcement resulting in the highest 5AVA titer obtained with WSCH-based media.

Sustainable metabolic engineering for sustainability optimisation of industrial biotechnology

Industrial biotechnology represents one of the most innovating and labour-productive industries with an estimated stable economic growth, thus giving space for improvement of the existing and setting up new value chains. In addition, biotechnology has clear environmental advantages over the chemical industry. Still, biotechnology’s environmental contribution is sometimes valued with controversy and societal aspects are frequently ignored. Environmental, economic and societal sustainability of various bioprocesses becomes increasingly important due to the growing understanding about complex and interlinked consequences of different human activities. Neglecting the sustainability issues in the development process of novel solutions may lead to sub-optimal biotechnological production, causing adverse environmental and societal problems proportional to the production volumes.

In the paper, sustainable metabolic engineering (SME) concept is proposed to assess and optimize the sustainability of biotechnological production that can be derived from the features of metabolism of the exploited organism. The SME concept is optimization of metabolism where economic, environmental and societal sustainability parameters of all incoming and outgoing fluxes and produced biomass of the applied organisms are considered. The extension of characterising features of strains designed by metabolic engineering methods with sustainability estimation enables ab initio improvement of the biotechnological production design.

Robustifying Experimental Tracer Design for13C-Metabolic Flux Analysis

¹³C metabolic flux analysis (MFA) has become an indispensable tool to measure metabolic reaction rates (fluxes) in living organisms, having an increasingly diverse range of applications. Here, the choice of the¹³C labeled tracer composition makes the difference between an information-rich experiment and an experiment with only limited insights. To improve the chances for an informative labeling experiment, optimal experimental design approaches have been devised for¹³C-MFA, all relying on some a priori knowledge about the actual fluxes. If such prior knowledge is unavailable, e.g., for research organisms and producer strains, existing methods are left with a chicken-and-egg problem. In this work, we present a general computational method, termed robustified experimental design (R-ED), to guide the decision making about suitable tracer choices when prior knowledge about the fluxes is lacking. Instead of focusing on one mixture, optimal for specific flux values, we pursue a sampling based approach and introduce a new design criterion, which characterizes the extent to which mixtures are informative in view of all possible flux values. The R-ED workflow enables the exploration of suitable tracer mixtures and provides full flexibility to trade off information and cost metrics. The potential of the R-ED workflow is showcased by applying the approach to the industrially relevant antibiotic producer Streptomyces clavuligerus, where we suggest informative, yet economic labeling strategies.

In-situ muconic acid extraction reveals sugar consumption bottleneck in a xylose-utilizing Saccharomyces cerevisiae strain

Background

The current shift from a fossil-resource based economy to a more sustainable, bio-based economy requires development of alternative production routes based on utilization of biomass for the many chemicals that are currently produced from petroleum. Muconic acid is an attractive platform chemical for the bio-based economy because it can be converted in chemicals with wide industrial applicability, such as adipic and terephthalic acid, and because its two double bonds offer great versatility for chemical modification.

Results

We have constructed a yeast cell factory converting glucose and xylose into muconic acid without formation of ethanol. We consecutively eliminated feedback inhibition in the shikimate pathway, inserted the heterologous pathway for muconic acid biosynthesis from 3-dehydroshikimate (DHS) by co-expression of DHS dehydratase from P. anserina, protocatechuic acid (PCA) decarboxylase (PCAD) from K. pneumoniae and oxygen-consuming catechol 1,2-dioxygenase (CDO) from C. albicans, eliminated ethanol production by deletion of the three PDC genes and minimized PCA production by enhancing PCAD overexpression and production of its co-factor. The yeast pitching rate was increased to lower high biomass formation caused by the compulsory aerobic conditions. Maximal titers of 4 g/L, 4.5 g/L and 3.8 g/L muconic acid were reached with glucose, xylose, and a mixture, respectively. The use of an elevated initial sugar level, resulting in muconic acid titers above 2.5 g/L, caused stuck fermentations with incomplete utilization of the sugar. Application of polypropylene glycol 4000 (PPG) as solvent for in situ product removal during the fermentation shows that this is not due to toxicity by the muconic acid produced.

Conclusions

This work has developed an industrial yeast strain able to produce muconic acid from glucose and also with great efficiency from xylose, without any ethanol production, minimal production of PCA and reaching the highest titers in batch fermentation reported up to now. Utilization of higher sugar levels remained conspicuously incomplete. Since this was not due to product inhibition by muconic acid or to loss of viability, an unknown, possibly metabolic bottleneck apparently arises during muconic acid fermentation with high sugar levels and blocks further sugar utilization.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12934-021-01594-3.

Microbial engineering to produce fatty alcohols and alkanes

Owing to their high energy density and composition, fatty acid-derived chemicals possess a wide range of applications such as biofuels, biomaterials, and other biochemical, and as a consequence, the global annual demand for products has surpassed 2 million tons. With the exhausting petroleum reservoirs and emerging environmental concerns on using petroleum feedstock, it has become indispensable to shift to a renewable-based industry. With the advancement in the field of synthetic biology and metabolic engineering, the use of microbes as factories for the production of fatty acid-derived chemicals is becoming a promising alternative approach for the production of these derivatives. Numerous metabolic approaches have been developed for conditioning the microbes to improve existing or develop new methodologies capable of efficient oleochemical production. However, there still exist several limitations that need to be addressed for the commercial viability of the microbial cell factory production. Though substantial advancement has been made toward successfully producing these fatty acids derived chemicals, a considerable amount of work needs to be done for improving the titers. In the present review, we aim to address the roadblocks impeding the heterologous production, the engineering pathway strategies implemented across the range of microbes in a detailed manner, and the commercial readiness of these molecules of immense application.

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.

A lysate proteome engineering strategy for enhancing cell-free metabolite production

Cell-free systems present a significant opportunity to harness the metabolic potential of diverse organisms. Removing the cellular context provides the ability to produce biological products without the need to maintain cell viability and enables metabolic engineers to explore novel chemical transformation systems. Crude extracts maintain much of a cell’s capabilities. However, only limited tools are available for engineering the contents of the extracts used for cell-free systems. Thus, our ability to take full advantage of the potential of crude extracts for cell-free metabolic engineering is constrained. Here, we employ Multiplex Automated Genomic Engineering (MAGE) to tag proteins for selective depletion from crude extracts so as to specifically direct chemical production. Specific edits to central metabolism are possible without significantly impacting cell growth. Selective removal of pyruvate degrading enzymes resulted in engineered crude lysates that are capable of up to 40-fold increases in pyruvate production when compared to the non-engineered extract. The described approach melds the tools of systems and synthetic biology to showcase the effectiveness of cell-free metabolic engineering for applications like bioprototyping and bioproduction.

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A method of engineering cell-free metabolism in lysates is described.

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Method enables design of cell lysates for enhancing specific metabolic processes.

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Pyruvate consuming enzymes tagged with 6xHis tags have minimal impact on growth.

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Post-lysis pull-down of tagged enzymes enables cell-free pyruvate pooling.

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Lysate engineering strategy permits metabolic states not possible in living cells.

Physicochemical and metabolic constraints for thermodynamics-based stoichiometric modelling under mesophilic growth conditions

Metabolic engineering in the post-genomic era is characterised by the development of new methods for metabolomics and fluxomics, supported by the integration of genetic engineering tools and mathematical modelling. Particularly, constraint-based stoichiometric models have been widely studied: (i) flux balance analysis (FBA) (in silico), and (ii) metabolic flux analysis (MFA) (in vivo). Recent studies have enabled the incorporation of thermodynamics and metabolomics data to improve the predictive capabilities of these approaches. However, an in-depth comparison and evaluation of these methods is lacking. This study presents a thorough analysis of two different in silico methods tested against experimental data (metabolomics and ¹³C-MFA) for the mesophile Escherichia coli. In particular, a modified version of the recently published matTFA toolbox was created, providing a broader range of physicochemical parameters. Validating against experimental data allowed the determination of the best physicochemical parameters to perform the TFA (Thermodynamics-based Flux Analysis). An analysis of flux pattern changes in the central carbon metabolism between ¹³C-MFA and TFA highlighted the limited capabilities of both approaches for elucidating the anaplerotic fluxes. In addition, a method based on centrality measures was suggested to identify important metabolites that (if quantified) would allow to further constrain the TFA. Finally, this study emphasised the need for standardisation in the fluxomics community: novel approaches are frequently released but a thorough comparison with currently accepted methods is not always performed.

Biotechnology has benefitted from the development of high throughput methods characterising living systems at different levels (e.g. concerning genes or proteins), allowing the industrial production of chemical commodities. Recently, focus has been placed on determining reaction rates (or metabolic fluxes) in the metabolic network of certain microorganisms, in order to identify bottlenecks hindering their exploitation. Two main approaches are commonly used, termed metabolic flux analysis (MFA) and flux balance analysis (FBA), based on measuring and estimating fluxes, respectively. While the influence of thermodynamics in living systems was accepted several decades ago, its application to study biochemical networks has only recently been enabled. In this sense, a multitude of different approaches constraining well-established modelling methods with thermodynamics has been suggested. However, physicochemical parameters are generally not properly adjusted to the experimental conditions, which might affect their predictive capabilities. In this study, we have explored the reliability of currently available tools by investigating the impact of varying said parameters in the simulation of metabolic fluxes and metabolite concentration values. Additionally, our in-depth analysis allowed us to highlight limitations and potential solutions that should be considered in future studies.

Improving the catalytic performance of Pichia pastoris whole-cell biocatalysts by fermentation process

Whole-cell biocatalysts have a wide range of applications in many fields. However, the transport of substrates is tricky when applying whole-cell biocatalysts for industrial production. In this research, P. pastoris whole-cell biocatalysts were constructed for rebaudioside A synthesis. Sucrose synthase was expressed intracellularly while UDP-glycosyltransferase was displayed on the cell wall surface simultaneously. As an alternative method, a fermentation process is applied to relieve the substrate transport-limitation of P. pastoris whole-cell biocatalysts. This fermentation process was much simpler, more energy-saving, and greener than additional operating after collecting cells to improve the catalytic ability of whole-cell biocatalysts. Compared with the general fermentation process, the protein production capacity of cells did not decrease. Meanwhile, the activity of whole-cell biocatalysts was increased to 262%, which indicates that the permeability and space resistance were improved to relieve the transport-limitations. Furthermore, the induction time was reduced from 60 h to 36 h. The fermentation process offered significant advantages over traditional permeabilizing reagent treatment and ultrasonication treatment based on the high efficiency and simplicity.

Fermentation process was applied to relieve the substrate transport-limitation of P. pastoris whole-cell biocatalysts, which was much simpler, more energy-saving and greener than c traditional permeabilizing reagent and ultrasonication treatment.

Metabolic engineering of an auto-regulated Corynebacterium glutamicum chassis for biosynthesis of 5-aminolevulinic acid

One challenge in metabolic engineering for industrial applications is the construction of highly efficient microbial cell factories. For this purpose, dynamic regulation of metabolic flux may be indispensable. In this study, an auto-regulated Corynebacterium glutamicum chassis for 5-aminolevulinic acid (5-ALA) biosynthesis was constructed. First, the expression of critical genes involved in 5-ALA synthesis and cofactor regeneration was precisely modulated. Furthermore, odhA expression was controlled using the strategies of static metabolic engineering (SME, with a weak promoter), dynamic metabolic engineering (DME, with a temperature-sensitive plasmid), and auto-inducible metabolic engineering (AME, with a growth-related promoter). The AME strategy showed the best effect and dynamically balanced the tradeoff between cell growth and 5-ALA synthesis. Additionally, the expression of exporter-encoding rhtA was regulated using AME strategy by the two-component system HrrSA in response to extracellular heme. The final strain A30 achieved the highest 5-ALA production (3.16 g/L) ever reported in C. glutamicum through C5 pathway.

Multiplex genome editing of microorganisms using CRISPR-Cas

Microbial production of chemical compounds often requires highly engineered microbial cell factories. During the last years, CRISPR-Cas nucleases have been repurposed as powerful tools for genome editing. Here, we briefly review the most frequently used CRISPR-Cas tools and describe some of their applications. We describe the progress made with respect to CRISPR-based multiplex genome editing of industrial bacteria and eukaryotic microorganisms. We also review the state of the art in terms of gene expression regulation using CRISPRi and CRISPRa. Finally, we summarize the pillars for efficient multiplexed genome editing and present our view on future developments and applications of CRISPR-Cas tools for multiplex genome editing.

Engineering endogenous ABC transporter with improving ATP supply and membrane flexibility enhances the secretion of β-carotene in Saccharomyces cerevisiae

BACKGROUND

Product toxicity is one of the bottlenecks for microbial production of biofuels, and transporter-mediated biofuel secretion offers a promising strategy to solve this problem. As a robust microbial host for industrial-scale production of biofuels, Saccharomyces cerevisiae contains a powerful transport system to export a wide range of toxic compounds to sustain survival. The aim of this study is to improve the secretion and production of the hydrophobic product (β-carotene) by harnessing endogenous ABC transporters combined with physiological engineering in S. cerevisiae.

RESULTS

Substrate inducibility is a prominent characteristic of most endogenous transporters. Through comparative proteomic analysis and transcriptional confirmation, we identified five potential ABC transporters (Pdr5p, Pdr10p, Snq2p, Yor1p, and Yol075cp) for β-carotene efflux. The accumulation of β-carotene also affects cell physiology in various aspects, including energy metabolism, mitochondrial translation, lipid metabolism, ergosterol biosynthetic process, and cell wall synthesis. Here, we adopted an inducible GAL promoter to overexpress candidate transporters and enhanced the secretion and intracellular production of β-carotene, in which Snq2p showed the best performance (a 4.04-fold and a 1.33-fold increase compared with its parental strain YBX-01, respectively). To further promote efflux capacity, two strategies of increasing ATP supply and improving membrane fluidity were following adopted. A 5.80-fold increase of β-carotene secretion and a 1.71-fold increase of the intracellular β-carotene production were consequently achieved in the engineered strain YBX-20 compared with the parental strain YBX-01.

CONCLUSIONS

Overall, our results showcase that engineering endogenous plasma membrane ABC transporters is a promising approach for hydrophobic product efflux in S. cerevisiae. We also highlight the importance of improving cell physiology to enhance the efficiency of ABC transporters, especially energy status and cell membrane properties.

Metabolomic and Transcriptomic Analyses of Escherichia coli for Efficient Fermentation of L-Fucose

L-Fucose, one of the major monomeric sugars in brown algae, possesses high potential for use in the large-scale production of bio-based products. Although fucose catabolic pathways have been enzymatically evaluated, the effects of fucose as a carbon source on intracellular metabolism in industrial microorganisms such as Escherichia coli are still not identified. To elucidate the effects of fucose on cellular metabolism and to find clues for efficient conversion of fucose into bio-based products, comparative metabolomic and transcriptomic analyses were performed on E. coli on L-fucose and on D-glucose as a control. When fucose was the carbon source for E. coli, integration of the two omics analyses revealed that excess gluconeogenesis and quorum sensing led to severe depletion of ATP, resulting in accumulation and export of fucose extracellularly. Therefore, metabolic engineering and optimization are needed for E. coil to more efficiently ferment fucose. This is the first multi-omics study investigating the effects of fucose on cellular metabolism in E. coli. These omics data and their biological interpretation could be used to assist metabolic engineering of E. coli producing bio-based products using fucose-containing brown macroalgae.

A Pareto approach to resolve the conflict between information gain and experimental costs: Multiple-criteria design of carbon labeling experiments

Science revolves around the best way of conducting an experiment to obtain insightful results. Experiments with maximal information content can be found by computational experimental design (ED) strategies that identify optimal conditions under which to perform the experiment. Several criteria have been proposed to measure the information content, each emphasizing different aspects of the design goal, i.e., reduction of uncertainty. Where experiments are complex or expensive, second sight is at the budget governing the achievable amount of information. In this context, the design objectives cost and information gain are often incommensurable, though dependent. By casting the ED task into a multiple-criteria optimization problem, a set of trade-off designs is derived that approximates the Pareto-frontier which is instrumental for exploring preferable designs. In this work, we present a computational methodology for multiple-criteria ED of information-rich experiments that accounts for virtually any set of design criteria. The methodology is implemented for the case of ¹³C metabolic flux analysis (MFA), which is arguably the most expensive type among the ‘omics’ technologies, featuring dozens of design parameters (tracer composition, analytical platform, measurement selection etc.). Supported by an innovative visualization scheme, we demonstrate with two realistic showcases that the use of multiple criteria reveals deep insights into the conflicting interplay between information carriers and cost factors that are not amendable to single-objective ED. For instance, tandem mass spectrometry turns out as best-in-class with respect to information gain, while it delivers this information quality cheaper than the other, routinely applied analytical technologies. Therewith, our Pareto approach to ED offers the investigator great flexibilities in the conception phase of a study to balance costs and benefits.

Designing experiments is obligatory in the biosciences to valorize their scientific outcome. When the experiments are expensive, unfortunately, in practice often the costs emerge to be showstoppers. In this situation the question arises: How to get the most out of the experiment for your invest in terms of time and money? We approach this question by formulating the design task as a multiple-criteria optimization problem. Its solution produces a set of Pareto-optimal design proposals that feature the trade-off between information gain, as measured by different metrics, and the costs. Then, exploration of the design proposals allows us to make the best decision on information-economic experiments under given circumstances. Implemented in the field of isotope-based metabolic flux analysis, practical application of the Pareto approach provides detailed insight into the tight interplay of plenty of information carriers and cost factors. Supported by an innovative tailored visual representation scheme, the investigator is enabled to explore the options before conducting the experiment. With a practical showcase at hand, our computational study highlights the benefits of incorporating multiple information criteria apart from the costs, balancing the shortcomings of conventional single-objective experimental design strategies.

Butyric acid: Applications and recent advances in its bioproduction

Butyric acid is an important C4 organic acid with broad applications. It is currently produced by chemosynthesis from petroleum-based feedstocks. However, the fermentative production of butyric acid from renewable feedstocks has received growing attention because of consumer demand for green products and natural ingredients in foods, pharmaceuticals, animal feed supplements, and cosmetics. In this review, strategies for improving microbial butyric acid production, including strain engineering and novel fermentation process development are discussed and compared regarding product yield, titer, purity and productivity. Future perspectives on strain and process improvements for butyric acid production are also discussed.

Promoter Engineering for Enhanced P(3HB- co-4HB) Production by Halomonas bluephagenesis

Promoters for the expression of heterologous genes in Halomonas bluephagenesis are quite limited, and many heterologous promoters function abnormally in this strain. P_porin, a promoter of the strongest expressed protein porin in H. bluephagenesis, is one of the few promoters available for heterologous expression in H. bluephagenesis, yet it has a fixed transcriptional activity that cannot be tuned. A stable promoter library with a wide range of activities is urgently needed. This study reports an approach to construct a promoter library based on the P_porin core region, namely, from the -35 box to the transcription start site, a spacer and an insulator. Saturation mutagenesis was conducted inside the promoter core region to significantly increase the diversity within the promoter library. The promoter library worked in both E. coli and H. bluephagenesis, covering a wide range of relative transcriptional strengths from 40 to 140 000. The library is therefore suitable for the transcription of many different heterologous genes, serving as a platform for protein expression and fine-tuned metabolic engineering of H. bluephagenesis TD01 and its derivative strains. H. bluephagenesis strains harboring the orfZ gene encoding 4HB-CoA transferase driven by selected promoters from the library were constructed, the best one produced over 100 g/L cell dry weight containing 80% poly(3-hydroxybutyrate- co-11 mol % 4-hydroxybutyrate) with a productivity of 1.59 g/L/h after 50 h growth under nonsterile fed-batch conditions. This strain was found the best for P(3HB- co-4HB) production in the laboratory scale.

Pathway Design, Engineering, and Optimization

The microbial metabolic versatility found in nature has inspired scientists to create microorganisms capable of producing value-added compounds. Many endeavors have been made to transfer and/or combine pathways, existing or even engineered enzymes with new function to tractable microorganisms to generate new metabolic routes for drug, biofuel, and specialty chemical production. However, the success of these pathways can be impeded by different complications from an inherent failure of the pathway to cell perturbations. Pursuing ways to overcome these shortcomings, a wide variety of strategies have been developed. This chapter will review the computational algorithms and experimental tools used to design efficient metabolic routes, and construct and optimize biochemical pathways to produce chemicals of high interest.

Metabolic Engineering of the Shikimate Pathway for Production of Aromatics and Derived Compounds-Present and Future Strain Construction Strategies

The aromatic nature of shikimate pathway intermediates gives rise to a wealth of potential bio-replacements for commonly fossil fuel-derived aromatics, as well as naturally produced secondary metabolites. Through metabolic engineering, the abundance of certain intermediates may be increased, while draining flux from other branches off the pathway. Often targets for genetic engineering lie beyond the shikimate pathway, altering flux deep in central metabolism. This has been extensively used to develop microbial production systems for a variety of compounds valuable in chemical industry, including aromatic and non-aromatic acids like muconic acid, para-hydroxybenzoic acid, and para-coumaric acid, as well as aminobenzoic acids and aromatic α-amino acids. Further, many natural products and secondary metabolites that are valuable in food- and pharma-industry are formed outgoing from shikimate pathway intermediates. (Re)construction of such routes has been shown by de novo production of resveratrol, reticuline, opioids, and vanillin. In this review, strain construction strategies are compared across organisms and put into perspective with requirements by industry for commercial viability. Focus is put on enhancing flux to and through shikimate pathway, and engineering strategies are assessed in order to provide a guideline for future optimizations.

Exploiting transcriptomic data for metabolic engineering: toward a systematic strain design

Transcriptomics is now recognized as a primary tool for metabolic engineering as it can be used for identifying new strain designs by diagnosing current states of microbial cells. This review summarizes current application of transcriptomic data for strain design. Along with a few successful examples, limitations of conventionally used differentially expressed gene-based strain design approaches have been discussed, which have been major reasons why transcriptomic data are considerably underutilized. Recently, integrative network-based approaches interpreting transcriptomic data in the context of biological networks were invented to provide complimentary solutions for metabolic engineering by overcoming the limitations of conventional approaches. Here, we highlight recent pioneering studies in which integrative network-based methods have been used for providing novel strain designs.

Combinatorial Evolution of DNA with RECODE

In past decades, DNA engineering protocols have led to the rapid development of synthetic biology. To engineer the natural proteins, many directed evolution methods based on molecular biology have been presented for generating genetic diversity or obtaining specific properties. Here, we provide a simple (PCR operation), efficient (larger amount of products), and powerful (multiple point mutations, deletions, insertions, and combinatorial multipoint mutagenesis) RECODE method, which is capable of reediting the target DNA flexibly to restructure regulatory regions and remodel enzymes by using the combined function of the thermostable DNA polymerase and DNA ligase in one pot. RECODE is expected to be an applicable choice to create diverse mutant libraries for rapid evolution and optimization of enzymes and synthetic pathways.

Computational Methods to Assess the Production Potential of Bio-Based Chemicals

Elevated costs and long implementation times of bio-based processes for producing chemicals represent a bottleneck for moving to a bio-based economy. A prospective analysis able to elucidate economically and technically feasible product targets at early research phases is mandatory. Computational tools can be implemented to explore the biological and technical spectrum of feasibility, while constraining the operational space for desired chemicals. In this chapter, two different computational tools for assessing potential for bio-based production of chemicals from different perspectives are described in detail. The first tool is GEM-Path: an algorithm to compute all structurally possible pathways from one target molecule to the host metabolome. The second tool is a framework for Modeling Sustainable Industrial Chemicals production (MuSIC), which integrates modeling approaches for cellular metabolism, bioreactor design, upstream/downstream processes, and economic impact assessment. Integrating GEM-Path and MuSIC will play a vital role in supporting early phases of research efforts and guide the policy makers with decisions, as we progress toward planning a sustainable chemical industry.

Enabling the valorization of guaiacol-based lignin: Integrated chemical and biochemical production of cis,cis-muconic acid using metabolically engineered Amycolatopsis sp ATCC 39116

Lignin is nature's second most abundant polymer and displays a largely unexploited renewable resource for value-added bio-production. None of the lignin-based fermentation processes so far managed to use guaiacol (2-methoxy phenol), the predominant aromatic monomer in depolymerized lignin. In this work, we describe metabolic engineering of Amycolatopsis sp. ATCC 39116 to produce cis,cis-muconic acid (MA), a precursor of recognized industrial value for commercial plastics, from guaiacol. The microbe utilized a very broad spectrum of lignin-based aromatics, such as catechol, guaiacol, phenol, toluene, p-coumarate, and benzoate, tolerated them in elevated amounts and even preferred them over sugars. As a next step, we developed a novel approach for genomic engineering of this challenging, GC-rich actinomycete. The successful introduction of conjugation and blue-white screening, using β-glucuronidase, enabled tailored genomic modifications within ten days. Successive deletion of two putative muconate cycloisomerases from the genome provided the mutant Amycolatopsis sp. ATCC 39116 MA-2, which accumulated 3.1gL^-1 MA from guaiacol within 24h, achieving a yield of 96%. The mutant was found also capable to produce MA from a guaiacol-rich true lignin hydrolysate, obtained from pine through hydrothermal conversion. This provides an important proof-of-concept to successfully coupling chemical and biochemical process steps into a value chain from the lignin polymer to an industrial chemical. In addition, Amycolatopsis sp. ATCC 39116 MA-2 was able to produce 2-methyl MA from o-cresol (2-methyl phenol), which opens possibilities towards polymers with novel architecture and properties.

Challenges and Advances for Genetic Engineering of Non-model Bacteria and Uses in Consolidated Bioprocessing

Metabolic diversity in microorganisms can provide the basis for creating novel biochemical products. However, most metabolic engineering projects utilize a handful of established model organisms and thus, a challenge for harnessing the potential of novel microbial functions is the ability to either heterologously express novel genes or directly utilize non-model organisms. Genetic manipulation of non-model microorganisms is still challenging due to organism-specific nuances that hinder universal molecular genetic tools and translatable knowledge of intracellular biochemical pathways and regulatory mechanisms. However, in the past several years, unprecedented progress has been made in synthetic biology, molecular genetics tools development, applications of omics data techniques, and computational tools that can aid in developing non-model hosts in a systematic manner. In this review, we focus on concerns and approaches related to working with non-model microorganisms including developing molecular genetics tools such as shuttle vectors, selectable markers, and expression systems. In addition, we will discuss: (1) current techniques in controlling gene expression (transcriptional/translational level), (2) advances in site-specific genome engineering tools [homologous recombination (HR) and clustered regularly interspaced short palindromic repeats (CRISPR)], and (3) advances in genome-scale metabolic models (GSMMs) in guiding design of non-model species. Application of these principles to metabolic engineering strategies for consolidated bioprocessing (CBP) will be discussed along with some brief comments on foreseeable future prospects.

Genome-scale modeling of yeast: chronology, applications and critical perspectives

Over the last 15 years, several genome-scale metabolic models (GSMMs) were developed for different yeast species, aiding both the elucidation of new biological processes and the shift toward a bio-based economy, through the design of in silico inspired cell factories. Here, an historical perspective of the GSMMs built over time for several yeast species is presented and the main inheritance patterns among the metabolic reconstructions are highlighted. We additionally provide a critical perspective on the overall genome-scale modeling procedure, underlining incomplete model validation and evaluation approaches and the quest for the integration of regulatory and kinetic information into yeast GSMMs. A summary of experimentally validated model-based metabolic engineering applications of yeast species is further emphasized, while the main challenges and future perspectives for the field are finally addressed.

Orthogonal partial least squares/projections to latent structures regression-based metabolomics approach for identification of gene targets for improvement of 1-butanol production in Escherichia coli

Metabolomics is the comprehensive analysis of metabolites in biological systems that uses multivariate analyses such as principal component analysis (PCA) or partial least squares/projections to latent structures regression (PLSR) to understand the metabolome state and extract important information from biological systems. In this study, orthogonal PLSR (OPLSR) model-based metabolomics approach was applied to 1-butanol producing Escherichia coli to facilitate in strain improvement strategies. Here, metabolite data obtained by liquid chromatography/mass spectrometry (LC/MS) was used to construct an OPLSR model to correlate metabolite changes with 1-butanol production and rationally identify gene targets for strain improvement. Using this approach, acetyl-CoA was determined as the rate-limiting step of the pathway while free CoA was found to be insufficient for 1-butanol production. By resolving the problems addressed by the OPLSR model, higher 1-butanol productivity was achieved. In this study, the usefulness of OPLSR-based metabolomics approach for understanding the whole metabolome state and determining the most relevant metabolites was demonstrated. Moreover, it was able to provide valuable insights for selection of rational gene targets for strain improvement.

A novel programmable lysozyme-based lysis system in Pseudomonas putida for biopolymer production

Cell lysis is crucial for the microbial production of industrial fatty acids, proteins, biofuels, and biopolymers. In this work, we developed a novel programmable lysis system based on the heterologous expression of lysozyme. The inducible lytic system was tested in two Gram-negative bacterial strains, namely Escherichia coli and Pseudomonas putida KT2440. Before induction, the lytic system did not significantly arrest essential physiological parameters in the recombinant E. coli (ECPi) and P. putida (JBOi) strain such as specific growth rate and biomass yield under standard growth conditions. A different scenario was observed in the recombinant JBOi strain when subjected to PHA-producing conditions, where biomass production was reduced by 25% but the mcl-PHA content was maintained at about 30% of the cell dry weight. Importantly, the genetic construct worked well under PHA-producing conditions (nitrogen-limiting phase), where more than 95% of the cell population presented membrane disruption 16 h post induction, with 75% of the total synthesized biopolymer recovered at the end of the fermentation period. In conclusion, this new lysis system circumvents traditional, costly mechanical and enzymatic cell-disrupting procedures.

IMGMD: A platform for the integration and standardisation of In silico Microbial Genome-scale Metabolic Models

Genome-scale metabolic models (GSMMs) constitute a platform that combines genome sequences and detailed biochemical information to quantify microbial physiology at the system level. To improve the unity, integrity, correctness, and format of data in published GSMMs, a consensus IMGMD database was built in the LAMP (Linux + Apache + MySQL + PHP) system by integrating and standardizing 328 GSMMs constructed for 139 microorganisms. The IMGMD database can help microbial researchers download manually curated GSMMs, rapidly reconstruct standard GSMMs, design pathways, and identify metabolic targets for strategies on strain improvement. Moreover, the IMGMD database facilitates the integration of wet-lab and in silico data to gain an additional insight into microbial physiology. The IMGMD database is freely available, without any registration requirements, at http://imgmd.jiangnan.edu.cn/database.

Respectful Modeling: Addressing Uncertainty in Dynamic System Models for Molecular Biology

Although there is still some skepticism in the biological community regarding the value and significance of quantitative computational modeling, important steps are continually being taken to enhance its accessibility and predictive power. We view these developments as essential components of an emerging 'respectful modeling' framework which has two key aims: (i) respecting the models themselves and facilitating the reproduction and update of modeling results by other scientists, and (ii) respecting the predictions of the models and rigorously quantifying the confidence associated with the modeling results. This respectful attitude will guide the design of higher-quality models and facilitate the use of models in modern applications such as engineering and manipulating microbial metabolism by synthetic biology.

Algal Cell Factories: Approaches, Applications, and Potentials

With the advent of modern biotechnology, microorganisms from diverse lineages have been used to produce bio-based feedstocks and bioactive compounds. Many of these compounds are currently commodities of interest, in a variety of markets and their utility warrants investigation into improving their production through strain development. In this review, we address the issue of strain improvement in a group of organisms with strong potential to be productive “cell factories”: the photosynthetic microalgae. Microalgae are a diverse group of phytoplankton, involving polyphyletic lineage such as green algae and diatoms that are commonly used in the industry. The photosynthetic microalgae have been under intense investigation recently for their ability to produce commercial compounds using only light, CO₂, and basic nutrients. However, their strain improvement is still a relatively recent area of work that is under development. Importantly, it is only through appropriate engineering methods that we may see the full biotechnological potential of microalgae come to fruition. Thus, in this review, we address past and present endeavors towards the aim of creating productive algal cell factories and describe possible advantageous future directions for the field.