From systems biology to metabolically engineered cells — an omics perspective on the development of industrial microbes

Medical properties, market potential, and microbial production of golden polyketide curcumin for food, biomedical, and cosmetic applications

Curcumin, a potent plant polyketide in turmeric, has gained recognition for its outstanding health benefits, including anti-inflammatory, antioxidant, and anticancer effects. Classical turmeric farming, which is widely used to produce curcumin, is linked to deforestation, soil degradation, excessive water use, and reduced biodiversity. In recent years, the microbial synthesis of curcumin has been achieved and optimized through novel strategies, offering increased safety, improved sustainability, and the potential to revolutionize production. Here, we discuss recent breakthroughs in microbial engineering and fermentation techniques, as well as their capacity to increase the yield, purity, and cost-effectiveness of curcumin production. The utilization of microbial systems not only addresses supply chain limitations but also helps meet the growing demand for curcumin in various industries, including pharmaceuticals, foods, and cosmetics.

Application of functional genomics for domestication of novel non-model microbes

With the expansion of domesticated microbes producing biomaterials and chemicals to support a growing circular bioeconomy, the variety of waste and sustainable substrates that can support microbial growth and production will also continue to expand. The diversity of these microbes also requires a range of compatible genetic tools to engineer improved robustness and economic viability. As we still do not fully understand the function of many genes in even highly studied model microbes, engineering improved microbial performance requires introducing genome-scale genetic modifications followed by screening or selecting mutants that enhance growth under prohibitive conditions encountered during production. These approaches include adaptive laboratory evolution, random or directed mutagenesis, transposon-mediated gene disruption, or CRISPR interference (CRISPRi). Although any of these approaches may be applicable for identifying engineering targets, here we focus on using CRISPRi to reduce the time required to engineer more robust microbes for industrial applications.

ONE-SENTENCE SUMMARY

The development of genome scale CRISPR-based libraries in new microbes enables discovery of genetic factors linked to desired traits for engineering more robust microbial systems.

Comparison of Five Escherichia coli Strains to Achieve the Maximum Yield of a Recombinant Immunotoxin Consisting of an Antibody against VEGF Conjugated with MAP30 Toxin in a Benchtop Bioreactor

BACKGROUND

Cancer is among the leading causes of death worldwide, imposing high costs on the health systems of all societies. Extensive biological studies are required to discover appropriate therapies. Escherichia coli has long been regarded as one of the main biotechnological bio-factories to produce recombinant protein-based therapeutics. In the present study, five strains of E. coli were compared to achieve the maximum production of a previously designed recombinant immunotoxin-carrying MAP30 toxin against VEGF-overexpressed cancer cells in a benchtop bioreactor.

METHODS

The recombinant immunotoxin coding gene sequence was extracted from the NCBI database. The host used to produce the recombinant immunotoxin were five E. coli strains of BL21 (DE3), DH5α, SHuffle®T7, XL1-Blue, and Rosetta-gamiTM (DE3). CaCl2 method was used for bacterial transformation. Bacterial growth measurements were performed using optical density measurements at 600 nm. The immunotoxin production was measured using SDS-PAGE analysis. The best-producing strain was cultivated in a 10-L benchtop stirred tank bioreactor. Recent patents on this field were also studied.

RESULTS

The results demonstrated that the BL21 (DE3) strain had the highest expression of recombinant protein in comparison to other strains. Moreover, the cell growth of E. coli BL21 (DE3) and SHuffle®T7 strains before transformation in the LB medium, were significantly higher in comparison to other strains. Additionally, the transformation of Rosettagami was associated with decreased cell proliferation. The transformation of the XL1-Blue strain did not effect cell growth. Analysis of the growth kinetics demonstrated appropriate proliferation of the transformed BL21 (DE3) cells in the laboratory benchtop bioreactor.

CONCLUSIONS

Based on the results of this study, the BL21 (DE3) strain could be used as a suitable host for the production of the recombinant immunotoxin against VEGF in stirred tank bioreactor, which can be employed for the treatment of tumors. Yet, its precise mechanism must be explored in extensive studies.

Streamlined identification of strain engineering targets for bioprocess improvement using metabolic pathway enrichment analysis

Metabolomics is a powerful tool for the identification of genetic targets for bioprocess optimisation. However, in most cases, only the biosynthetic pathway directed to product formation is analysed, limiting the identification of these targets. Some studies have used untargeted metabolomics, allowing a more unbiased approach, but data interpretation using multivariate analysis is usually not straightforward and requires time and effort. Here we show, for the first time, the application of metabolic pathway enrichment analysis using untargeted and targeted metabolomics data to identify genetic targets for bioprocess improvement in a more streamlined way. The analysis of an Escherichia coli succinate production bioprocess with this methodology revealed three significantly modulated pathways during the product formation phase: the pentose phosphate pathway, pantothenate and CoA biosynthesis and ascorbate and aldarate metabolism. From these, the two former pathways are consistent with previous efforts to improve succinate production in Escherichia coli. Furthermore, to the best of our knowledge, ascorbate and aldarate metabolism is a newly identified target that has so far never been explored for improving succinate production in this microorganism. This methodology therefore represents a powerful tool for the streamlined identification of strain engineering targets that can accelerate bioprocess optimisation.

Automating the design-build-test-learn cycle towards next-generation bacterial cell factories

Automation is playing an increasingly significant role in synthetic biology. Groundbreaking technologies, developed over the past 20 years, have enormously accelerated the construction of efficient microbial cell factories. Integrating state-of-the-art tools (e.g. for genome engineering and analytical techniques) into the design-build-test-learn cycle (DBTLc) will shift the metabolic engineering paradigm from an almost artisanal labor towards a fully automated workflow. Here, we provide a perspective on how a fully automated DBTLc could be harnessed to construct the next-generation bacterial cell factories in a fast, high-throughput fashion. Innovative toolsets and approaches that pushed the boundaries in each segment of the cycle are reviewed to this end. We also present the most recent efforts on automation of the DBTLc, which heralds a fully autonomous pipeline for synthetic biology in the near future.

Multi-Level Optimization and Strategies in Microbial Biotransformation of Nature Products

Continuously growing demand for natural products with pharmacological activities has promoted the development of microbial transformation techniques, thereby facilitating the efficient production of natural products and the mining of new active compounds. Furthermore, due to the shortcomings and defects of microbial transformation, it is an important scientific issue of social and economic value to improve and optimize microbial transformation technology in increasing the yield and activity of transformed products. In this review, the aspects regarding the optimization of fermentation and the cross-disciplinary strategy, leading to the microbial transformation of increased levels of the high-efficiency process from natural products of a plant or microbial origin, were discussed. Additionally, due to the increasing craving for targeted and efficient methods for detecting transformed metabolites, analytical methods based on multiomics were also discussed. Such strategies can be well exploited and applied to the production of more efficient and more natural products from microbial resources.

Global Cellular Metabolic Rewiring Adapts Corynebacterium glutamicum to Efficient Nonnatural Xylose Utilization

Xylose, the major component of lignocellulosic biomass, cannot be naturally or efficiently utilized by most microorganisms. Xylose (co)utilization is considered a cornerstone of efficient lignocellulose-based biomanufacturing. We evolved a rapidly xylose-utilizing strain, Cev2-18-5, which showed the highest reported specific growth rate (0.357 h^-1) on xylose among plasmid-free Corynebacterium glutamicum strains. A genetically clear chassis strain, CGS15, was correspondingly reconstructed with an efficient glucose-xylose coutilization performance based on comparative genomic analysis and mutation reconstruction. With the introduction of a succinate-producing plasmid, the resulting strain, CGS15-SA1, can efficiently produce 97.1 g/L of succinate with an average productivity of 8.09 g/L/h by simultaneously utilizing glucose and xylose from corn stalk hydrolysate. We further revealed a novel xylose regulatory mechanism mediated by the endogenous transcription factor IpsA with global regulatory effects on C. glutamicum. A synergistic effect on carbon metabolism and energy supply, motivated by three genomic mutations (P_sod(C131T)-xylAB, P_tuf(Δ21)-araE, and ipsA^C331T), was found to endow C. glutamicum with the efficient xylose utilization and rapid growth phenotype. Overall, this work not only provides promising C. glutamicum chassis strains for a lignocellulosic biorefinery but also enriches the understanding of the xylose regulatory mechanism. IMPORTANCE A novel xylose regulatory mechanism mediated by the transcription factor IpsA was revealed. A synergistic effect on carbon metabolism and energy supply was found to endow C. glutamicum with the efficient xylose utilization and rapid growth phenotype. The new xylose regulatory mechanism enriches the understanding of nonnatural substrate metabolism and encourages exploration new engineering targets for rapid xylose utilization. This work also provides a paradigm to understand and engineer the metabolism of nonnatural renewable substrates for sustainable biomanufacturing.

Whole-genome sequencing and genome-scale metabolic modeling of Chromohalobacter canadensis 85B to explore its salt tolerance and biotechnological use

Salt tolerant organisms are increasingly being used for the industrial production of high-value biomolecules due to their better adaptability compared to mesophiles. Chromohalobacter canadensis is one of the early halophiles to show promising biotechnology potential, which has not been explored to date. Advanced high throughput technologies such as whole-genome sequencing allow in-depth insight into the potential of organisms while at the frontiers of systems biology. At the same time, genome-scale metabolic models (GEMs) enable phenotype predictions through a mechanistic representation of metabolism. Here, we sequence and analyze the genome of C. canadensis 85B, and we use it to reconstruct a GEM. We then analyze the GEM using flux balance analysis and validate it against literature data on C. canadensis. We show that C. canadensis 85B is a metabolically versatile organism with many features for stress and osmotic adaptation. Pathways to produce ectoine and polyhydroxybutyrates were also predicted. The GEM reveals the ability to grow on several carbon sources in a minimal medium and reproduce osmoadaptation phenotypes. Overall, this study reveals insights from the genome of C. canadensis 85B, providing genomic data and a draft GEM that will serve as the first steps towards a better understanding of its metabolism, for novel applications in industrial biotechnology.

Molecular simulation of lignin-related aromatic compound permeation through gram-negative bacterial outer membranes

Lignin, an abundant aromatic heteropolymer in secondary plant cell walls, is the single largest source of renewable aromatics in the biosphere. Leveraging this resource for renewable bioproducts through targeted microbial action depends on lignin fragment uptake by microbial hosts and subsequent enzymatic action to obtain the desired product. Recent computational work has emphasized that bacterial inner membranes are permeable to many aromatic compounds expected from lignin depolymerization processes. In this study, we expand on these findings through simulations for 42 lignin-related compounds across a gram-negative bacterial outer membrane model. Unbiased simulation trajectories indicate that spontaneous crossing for the full outer membrane is relatively rare at molecular simulation timescales, primarily due to preferential membrane partitioning and slow diffusion within the lipopolysaccharide layer within the outer membrane. Membrane partitioning and permeability coefficients were determined through replica exchange umbrella sampling simulations to overcome sampling limitations. We find that the glycosylated lipopolysaccharides found in the outer membrane increase the permeation barrier to many lignin-related compounds, particularly the most hydrophobic compounds. However, the effect is relatively modest; at industrially relevant concentrations, uncharged lignin-related compounds will readily diffuse across the outer membrane without the need for specific porins. Together, our results provide insight into the permeability of the bacterial outer membrane for assessing lignin fragment uptake and the future production of renewable bioproducts.

13C metabolic flux analysis: Classification and characterization from the perspective of mathematical modeling and application in physiological research of neural cell

¹³C metabolic flux analysis (¹³C-MFA) has emerged as a forceful tool for quantifying in vivo metabolic pathway activity of different biological systems. This technology plays an important role in understanding intracellular metabolism and revealing patho-physiology mechanism. Recently, it has evolved into a method family with great diversity in experiments, analytics, and mathematics. In this review, we classify and characterize the various branch of ¹³C-MFA from a unified perspective of mathematical modeling. By linking different parts in the model to each step of its workflow, the specific technologies of ¹³C-MFA are put into discussion, including the isotope labeling model (ILM), isotope pattern measuring technique, optimization algorithm and statistical method. Its application in physiological research in neural cell has also been reviewed.

GC/MS-based 13C metabolic flux analysis resolves the parallel and cyclic photomixotrophic metabolism of Synechocystis sp. PCC 6803 and selected deletion mutants including the Entner-Doudoroff and phosphoketolase pathways

BACKGROUND

Cyanobacteria receive huge interest as green catalysts. While exploiting energy from sunlight, they co-utilize sugar and CO₂. This photomixotrophic mode enables fast growth and high cell densities, opening perspectives for sustainable biomanufacturing. The model cyanobacterium Synechocystis sp. PCC 6803 possesses a complex architecture of glycolytic routes for glucose breakdown that are intertwined with the CO₂-fixing Calvin-Benson-Bassham (CBB) cycle. To date, the contribution of these pathways to photomixotrophic metabolism has remained unclear.

RESULTS

Here, we developed a comprehensive approach for ¹³C metabolic flux analysis of Synechocystis sp. PCC 6803 during steady state photomixotrophic growth. Under these conditions, the Entner-Doudoroff (ED) and phosphoketolase (PK) pathways were found inactive but the microbe used the phosphoglucoisomerase (PGI) (63.1%) and the oxidative pentose phosphate pathway (OPP) shunts (9.3%) to fuel the CBB cycle. Mutants that lacked the ED pathway, the PK pathway, or phosphofructokinases were not affected in growth under metabolic steady-state. An ED pathway-deficient mutant (Δeda) exhibited an enhanced CBB cycle flux and increased glycogen formation, while the OPP shunt was almost inactive (1.3%). Under fluctuating light, ∆eda showed a growth defect, different to wild type and the other deletion strains.

CONCLUSIONS

The developed approach, based on parallel ¹³C tracer studies with GC-MS analysis of amino acids, sugars, and sugar derivatives, optionally adding NMR data from amino acids, is valuable to study fluxes in photomixotrophic microbes to detail. In photomixotrophic cells, PGI and OPP form glycolytic shunts that merge at switch points and result in synergistic fueling of the CBB cycle for maximized CO₂ fixation. However, redirected fluxes in an ED shunt-deficient mutant and the impossibility to delete this shunt in a GAPDH2 knockout mutant, indicate that either minor fluxes (below the resolution limit of ¹³C flux analysis) might exist that could provide catalytic amounts of regulatory intermediates or alternatively, that EDA possesses additional so far unknown functions. These ideas require further experiments.

Strategies to increase tolerance and robustness of industrial microorganisms

The development of a cost-competitive bioprocess requires that the cell factory converts the feedstock into the product of interest at high rates and yields. However, microbial cell factories are exposed to a variety of different stresses during the fermentation process. These stresses can be derived from feedstocks, metabolism, or industrial production processes, limiting production capacity and diminishing competitiveness. Improving stress tolerance and robustness allows for more efficient production and ultimately makes a process more economically viable. This review summarises general trends and updates the most recent developments in technologies to improve the stress tolerance of microorganisms. We first look at evolutionary, systems biology and computational methods as examples of non-rational approaches. Then we review the (semi-)rational approaches of membrane and transcription factor engineering for improving tolerance phenotypes. We further discuss challenges and perspectives associated with these different approaches.

Microbial protein cell factories fight back?

The biopharmaceutical market is growing faster than ever, with two production systems competing for market dominance: mammalian cells and microorganisms. In recent years, based on the rise of antibody-based therapies, new biotherapeutic approvals have favored mammalian hosts. However, not only has extensive research elevated our understanding of microbes to new levels, but emerging therapeutic molecules also facilitate their use; thus, is it time for microbes to fight back? In this review, we answer this timely question by cross-comparing four microbial production hosts and examining the innovations made to both their secretion and post-translational modification (PTM) capabilities. Furthermore, we discuss the impact of tools, such as omics and systems biology, as well as alternative production systems and emerging biotherapeutics.

Model-guided dynamic control of essential metabolic nodes boosts acetyl-coenzyme A-dependent bioproduction in rewired Pseudomonas putida

Pseudomonas putida is evolutionarily endowed with features relevant for bioproduction, especially under harsh operating conditions. The rich metabolic versatility of this species, however, comes at the price of limited formation of acetyl-coenzyme A (CoA) from sugar substrates. Since acetyl-CoA is a key metabolic precursor for a number of added-value products, in this work we deployed an in silico-guided rewiring program of central carbon metabolism for upgrading P. putida as a host for acetyl-CoA-dependent bioproduction. An updated kinetic model, integrating fluxomics and metabolomics datasets in addition to manually-curated information of enzyme mechanisms, identified targets that would lead to increased acetyl-CoA levels. Based on these predictions, a set of plasmids based on clustered regularly interspaced short palindromic repeats (CRISPR) and dead CRISPR-associated protein 9 (dCas9) was constructed to silence genes by CRISPR interference (CRISPRi). Dynamic reduction of gene expression of two key targets (gltA, encoding citrate synthase, and the essential accA gene, encoding subunit A of the acetyl-CoA carboxylase complex) mediated an 8-fold increase in the acetyl-CoA content of rewired P. putida. Poly(3-hydroxybutyrate) (PHB) was adopted as a proxy of acetyl-CoA availability, and two synthetic pathways were engineered for biopolymer accumulation. By including cell morphology as an extra target for the CRISPRi approach, fully rewired P. putida strains programmed for PHB accumulation had a 5-fold increase in PHB titers in bioreactor cultures using glucose. Thus, the strategy described herein allowed for rationally redirecting metabolic fluxes in P. putida from central metabolism towards product biosynthesis-especially relevant when deletion of essential pathways is not an option.

Advances in metabolic engineering of Corynebacterium glutamicum to produce high-value active ingredients for food, feed, human health, and well-being

The soil microbe Corynebacterium glutamicum is a leading workhorse in industrial biotechnology and has become famous for its power to synthetise amino acids and a range of bulk chemicals at high titre and yield. The product portfolio of the microbe is continuously expanding. Moreover, metabolically engineered strains of C. glutamicum produce more than 30 high value active ingredients, including signature molecules of raspberry, savoury, and orange flavours, sun blockers, anti-ageing sugars, and polymers for regenerative medicine. Herein, we highlight recent advances in engineering of the microbe into novel cell factories that overproduce these precious molecules from pioneering proofs-of-concept up to industrial productivity.

The essential role of mRNA degradation in understanding and engineering E. coli metabolism

Metabolic engineering strategies are crucial for the development of bacterial cell factories with improved performance. Until now, optimal metabolic networks have been designed based on systems biology approaches integrating large-scale data on the steady-state concentrations of mRNA, protein and metabolites, sometimes with dynamic data on fluxes, but rarely with any information on mRNA degradation. In this review, we compile growing evidence that mRNA degradation is a key regulatory level in E. coli that metabolic engineering strategies should take into account. We first discuss how mRNA degradation interacts with transcription and translation, two other gene expression processes, to balance transcription regulation and remove poorly translated mRNAs. The many reciprocal interactions between mRNA degradation and metabolism are also highlighted: metabolic activity can be controlled by changes in mRNA degradation and in return, the activity of the mRNA degradation machinery is controlled by metabolic factors. The mathematical models of the crosstalk between mRNA degradation dynamics and other cellular processes are presented and discussed with a view towards novel mRNA degradation-based metabolic engineering strategies. We show finally that mRNA degradation-based strategies have already successfully been applied to improve heterologous protein synthesis. Overall, this review underlines how important mRNA degradation is in regulating E. coli metabolism and identifies mRNA degradation as a key target for innovative metabolic engineering strategies in biotechnology.

Bio-prospecting the future in perspective of amidohydrolase L-glutaminase from marine habitats

In the current scenario, considerable attention is being given to the enzyme L-glutaminase (EC 3.5.1.2). It belongs to the amidohydrolase class adherent to the family of serine-reliant β-lactamases and the penicillin-binding proteins due to its higher affinity to polymerize and modify peptidoglycan synthesis. However, based on the catalytic proficiency, L-glutaminase is characterized as a proteolytic endopeptidase that cleaves peptide linkage and emancipates various byproducts, viz. ammonia along with glutamate. L-glutamine is considered the key amino acid reportedly involved in multiple metabolic pathways such as nitrogen metabolism. The present review is focused on the recent development and aspects concomitant to the biotechnological applicability of L-glutaminase predominantly from the marine habitat. Additionally, a majority of L-glutaminases finds application in cancer therapy as therapeutic agents, especially for acute lymphocytic leukaemia. The in vitro studies have been effective against various human cancer cell lines. L-glutaminase enhances the growth of probiotic bacteria. Apart from all these applications, it is suitably applicable in fermented foods as a flavour enhancer especially the umami flavour and content. Marine habitats have largely been exploited for their bio-catalytic potential but very scarcely for therapeutic enzymes. Some of the reports of such marine bacterial isolates from Bacillus sp., Pseudomonas sp. and Vibrio sp. are in the domain, but none highlights the therapeutic applications predominantly as anticancer and anti-proliferative agents. KEY POINTS: The exploration of marine habitats along the Gujarat coasts mainly for bacteria secreting L-glutaminase is scarcely reported, and even more scarce are the amidohydrolases from these marine niches as compared to their terrestrial counterparts. Microbial sourced amidohydrolase has wide bio-applicability that includes food, cosmetics and therapeutics especially as anticancer/anti-proliferative agent making it of immense biotechnological significance.

Marine microbial L-glutaminase: from pharmaceutical to food industry

Deamination of L-glutamine to glutamic acid with the concomitant release of ammonia by the activity of L-glutaminase (L-glutamine amidohydrolase EC 3.5.1.2) is a unique reaction that also finds potential applications in different sectors ranging from therapeutics to food industry. Owing to its cost-effectiveness, rapidity, and compatibility with downstream processes, microbial production of L-glutaminase is preferred over the production by other sources. Marine microorganisms including bacteria, yeasts, and moulds have manifested remarkable capacity to produce L-glutaminase and, therefore, are considered as prospective candidates for large-scale production of this enzyme. The main focus of this article is to provide an overview of L-glutaminase producing marine microorganisms, to discuss strategies used for the lab- and large-scale production of these enzyme and to review the application of L-glutaminase from marine sources so that the future prospects can be understood. KEY POINTS: • L-glutaminase has potential applications in different sectors ranging from therapeutics to food industry • Marine microorganisms are considered as prospective candidates for large-scale production of L-glutaminase • Marine microbial L-glutaminase have great potential in therapeutics and in the food industry.

Enhanced Recombinant Protein Production Under Special Environmental Stress

Regardless of bacteria or eukaryotic microorganism hosts, improving their ability to express heterologous proteins is always a goal worthy of elaborate study. In addition to traditional methods including intracellular synthesis process regulation and extracellular environment optimization, some special or extreme conditions can also be employed to create an enhancing effect on heterologous protein production. In this review, we summarize some extreme environmental factors used for the improvement of heterologous protein expression, including low temperature, hypoxia, microgravity and high osmolality. The applications of these strategies are elaborated with examples of well-documented studies. We also demonstrated the confirmed or hypothetical mechanisms of environment stress affecting the host behaviors. In addition, multi-omics techniques driving the stress-responsive research for construction of efficient microbial cell factories are also prospected at the end.

Adaptation of central metabolite pools to variations in growth rate and cultivation conditions in Saccharomyces cerevisiae

Background

Saccharomyces cerevisiae is a well-known popular model system for basic biological studies and serves as a host organism for the heterologous production of commercially interesting small molecules and proteins. The central metabolism is at the core to provide building blocks and energy to support growth and survival in normal situations as well as during exogenous stresses and forced heterologous protein production. Here, we present a comprehensive study of intracellular central metabolite pool profiling when growing S. cerevisiae on different carbon sources in batch cultivations and at different growth rates in nutrient-limited glucose chemostats. The latest versions of absolute quantitative mass spectrometry-based metabolite profiling methodology were applied to cover glycolytic and pentose phosphate pathway metabolites, tricarboxylic acid cycle (TCA), complete amino acid, and deoxy-/nucleoside phosphate pools.

Results

Glutamate, glutamine, alanine, and citrate were the four most abundant metabolites for most conditions tested. The amino acid is the dominant metabolite class even though a marked relative reduction compared to the other metabolite classes was observed for nitrogen and phosphate limited chemostats. Interestingly, glycolytic and pentose phosphate pathway (PPP) metabolites display the largest variation among the cultivation conditions while the nucleoside phosphate pools are more stable and vary within a closer concentration window. The overall trends for glucose and nitrogen-limited chemostats were increased metabolite pools with the increasing growth rate. Next, comparing the chosen chemostat reference growth rate (0.12 h⁻¹, approximate one-fourth of maximal unlimited growth rate) illuminates an interesting pattern: almost all pools are lower in nitrogen and phosphate limited conditions compared to glucose limitation, except for the TCA metabolites citrate, isocitrate and α-ketoglutarate.

Conclusions

This study provides new knowledge-how the central metabolism is adapting to various cultivations conditions and growth rates which is essential for expanding our understanding of cellular metabolism and the development of improved phenotypes in metabolic engineering.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12934-021-01557-8.

Unlocking Nature's Biosynthetic Power-Metabolic Engineering for the Fermentative Production of Chemicals

Fermentation as a production method for chemicals is especially attractive, as it is based on cheap renewable raw materials and often exhibits advantages in terms of costs and sustainability. The tremendous development of technology in bioscience has resulted in an exponentially increasing knowledge about biological systems and has become the main driver for innovations in the field of metabolic engineering. Progress in recombinant DNA technology, genomics, and computational methods open new, cheaper, and faster ways to metabolically engineer microorganisms. Existing biosynthetic pathways for natural products, such as vitamins, organic acids, amino acids, or secondary metabolites, can be discovered and optimized efficiently, thereby enabling competitive commercial production processes. Novel biosynthetic routes can now be designed by the rearrangement of nature's unlimited number of enzymes and metabolic pathways in microbial strains. This expands the range of chemicals accessible by biotechnology and has yielded the first commercial products, while new fermentation technologies targeting novel active ingredients, commodity chemicals, and CO₂ -fixation methods are on the horizon.

Dietary Change Enables Robust Growth-Coupling of Heterologous Methyltransferase Activity in Yeast

Genetic modifications of living organisms and proteins are made possible by a catalogue of molecular and synthetic biology tools, yet proper screening assays for genetic variants of interest continue to lag behind. Synthetic growth-coupling (GC) of enzyme activities offers a simple, inexpensive way to track such improvements. In this follow-up study we present the optimization of a recently established GC design for screening of heterologous methyltransferases (MTases) and related pathways in the yeast Saccharomyces cerevisiae. Specifically, upon testing different media compositions and genetic backgrounds, improved GC of different heterologous MTase activities is obtained. Furthermore, we demonstrate the strength of the system by screening a library of catechol O-MTase variants converting protocatechuic acid into vanillic acid. We demonstrated high correlation (R² = 0.775) between vanillic acid and cell density as a proxy for MTase activity. We envision that the improved MTase GC can aid evolution-guided optimization of biobased production processes for methylated compounds with yeast in the future.

A common approach for absolute quantification of short chain CoA thioesters in prokaryotic and eukaryotic microbes

BACKGROUND

Thioesters of coenzyme A participate in 5% of all enzymatic reactions. In microbial cell factories, they function as building blocks for products of recognized commercial value, including natural products such as polyketides, polyunsaturated fatty acids, biofuels, and biopolymers. A core spectrum of approximately 5-10 short chain thioesters is present in many microbes, as inferred from their genomic repertoire. The relevance of these metabolites explains the high interest to trace and quantify them in microbial cells.

RESULTS

Here, we describe a common workflow for extraction and absolute quantification of short chain CoA thioesters in different gram-positive and gram-negative bacteria and eukaryotic yeast, i.e. Corynebacterium glutamicum, Streptomyces albus, Pseudomonas putida, and Yarrowia lipolytica. The approach assessed intracellular CoA thioesters down to the picomolar level and exhibited high precision and reproducibility for all microbes, as shown by principal component analysis. Furthermore, it provided interesting insights into microbial CoA metabolism. A succinyl-CoA synthase defective mutant of C. glutamicum exhibited an unaffected level of succinyl-CoA that indicated a complete compensation by the L-lysine pathway to bypass the disrupted TCA cycle. Methylmalonyl-CoA, an important building block of high-value polyketides, was identified as dominant CoA thioester in the actinomycete S. albus. The microbe revealed a more than 10,000-fold difference in the abundance of intracellular CoA thioesters. A recombinant strain of S. albus, which produced different derivatives of the antituberculosis polyketide pamamycin, revealed a significant depletion of CoA thioesters of the ethylmalonyl CoA pathway, influencing product level and spectrum.

CONCLUSIONS

The high relevance of short chain CoA thioesters to synthetize industrial products and the interesting insights gained from the examples shown in this work, suggest analyzing these metabolites in microbial cell factories more routinely than done so far. Due to its broad application range, the developed approach appears useful to be applied this purpose. Hereby, the possibility to use one single protocol promises to facilitate automatized efforts, which rely on standardized workflows.

Absolute Quantification of the Central Carbon Metabolome in Eight Commonly Applied Prokaryotic and Eukaryotic Model Systems

Absolute quantification of intracellular metabolite pools is a prerequisite for modeling and in-depth biological interpretation of metabolomics data. It is the final step of an elaborate metabolomics workflow, with challenges associated with all steps—from sampling to quantifying the physicochemically diverse metabolite pool. Chromatographic separation combined with mass spectrometric (MS) detection is the superior platform for high coverage, selective, and sensitive detection of metabolites. Herein, we apply our quantitative MS-metabolomics workflow to measure and present the central carbon metabolome of a panel of commonly applied biological model systems. The workflow includes three chromatographic methods combined with isotope dilution tandem mass spectrometry to allow for absolute quantification of 68 metabolites of glycolysis, the pentose phosphate pathway, the tricarboxylic acid cycle, and the amino acid and (deoxy) nucleoside pools. The biological model systems; Bacillus subtilis, Saccharomyces cerevisiae, two microalgal species, and four human cell lines were all cultured in commonly applied culture media and sampled in exponential growth phase. Both literature and databases are scarce with comprehensive metabolite datasets, and existing entries range over several orders of magnitude. The workflow and metabolite panel presented herein can be employed to expand the list of reference metabolomes, as encouraged by the metabolomics community, in a continued effort to develop and refine high-quality quantitative metabolomics workflows.

Coupled metabolic-hydrodynamic modeling enabling rational scale-up of industrial bioprocesses

Metabolomics aims to address what and how regulatory mechanisms are coordinated to achieve flux optimality, different metabolic objectives as well as appropriate adaptations to dynamic nutrient availability. Recent decades have witnessed that the integration of metabolomics and fluxomics within the goal of synthetic biology has arrived at generating the desired bioproducts with improved bioconversion efficiency. Absolute metabolite quantification by isotope dilution mass spectrometry represents a functional readout of cellular biochemistry and contributes to the establishment of metabolic (structured) models required in systems metabolic engineering. In industrial practices, population heterogeneity arising from fluctuating nutrient availability frequently leads to performance losses, that is reduced commercial metrics (titer, rate, and yield). Hence, the development of more stable producers and more predictable bioprocesses can benefit from a quantitative understanding of spatial and temporal cell-to-cell heterogeneity within industrial bioprocesses. Quantitative metabolomics analysis and metabolic modeling applied in computational fluid dynamics (CFD)-assisted scale-down simulators that mimic industrial heterogeneity such as fluctuations in nutrients, dissolved gases, and other stresses can procure informative clues for coping with issues during bioprocessing scale-up. In previous studies, only limited insights into the hydrodynamic conditions inside the industrial-scale bioreactor have been obtained, which makes case-by-case scale-up far from straightforward. Tracking the flow paths of cells circulating in large-scale bioreactors is a highly valuable tool for evaluating cellular performance in production tanks. The "lifelines" or "trajectories" of cells in industrial-scale bioreactors can be captured using Euler-Lagrange CFD simulation. This novel methodology can be further coupled with metabolic (structured) models to provide not only a statistical analysis of cell lifelines triggered by the environmental fluctuations but also a global assessment of the metabolic response to heterogeneity inside an industrial bioreactor. For the future, the industrial design should be dependent on the computational framework, and this integration work will allow bioprocess scale-up to the industrial scale with an end in mind.

Heterologous production of small molecules in the optimized Streptomyces hosts

Time span of literature covered: 2010-2018The genome mining of streptomycetes has revealed their great biosynthetic potential to produce novel natural products. One of the most promising exploitation routes of this biosynthetic potential is the refactoring and heterologous expression of corresponding biosynthetic gene clusters in a panel of specifically selected and optimized chassis strains. This article will review selected recent reports on heterologous production of natural products in streptomycetes. In the first part, the importance of heterologous production for drug discovery will be discussed. In the second part, the review will discuss recently developed genetic control elements (such as promoters, ribosome binding sites, terminators) and their application to achieve successful heterologous expression of biosynthetic gene clusters. Finally, the most widely used Streptomyces hosts for heterologous expression of biosynthetic gene clusters will be compared in detail. The article will be of interest to natural product chemists, molecular biologists, pharmacists and all individuals working in the natural products drug discovery field.

Recent advances in plasmid-based tools for establishing novel microbial chassis

A key challenge for domesticating alternative cultivable microorganisms with biotechnological potential lies in the development of innovative technologies. Within this framework, a myriad of genetic tools has flourished, allowing the design and manipulation of complex synthetic circuits and genomes to become the general rule in many laboratories rather than the exception. More recently, with the development of novel technologies such as DNA automated synthesis/sequencing and powerful computational tools, molecular biology has entered the synthetic biology era. In the beginning, most of these technologies were established in traditional microbial models (known as chassis in the synthetic biology framework) such as Escherichia coli and Saccharomyces cerevisiae, enabling fast advances in the field and the validation of fundamental proofs of concept. However, it soon became clear that these organisms, although extremely useful for prototyping many genetic tools, were not ideal for a wide range of biotechnological tasks due to intrinsic limitations in their molecular/physiological properties. Over the last decade, researchers have been facing the great challenge of shifting from these model systems to non-conventional chassis with endogenous capacities for dealing with specific tasks. The key to address these issues includes the generation of narrow and broad host plasmid-based molecular tools and the development of novel methods for engineering genomes through homologous recombination systems, CRISPR/Cas9 and other alternative methods. Here, we address the most recent advances in plasmid-based tools for the construction of novel cell factories, including a guide for helping with "build-your-own" microbial host.

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.

Recent advances in microbial glutaminase production and applications-a concise review

This article focuses on significant advances in the production and applications of microbial glutaminases and provides insight into the structures of different glutaminases. Glutaminases catalyze the deamidation of glutamine to glutamic acid, and this unique ability forms the basis of their applications in various industries such as pharmaceutical and food organizations. Microbial glutaminases from bacteria, actinomycetes, yeast, and fungi are of greater significance than animal glutaminases because of their stability, affordability, and ease of production. Owing to these notable benefits, they are considered to possess considerable potential in anticancer and antiviral therapy, flavor enhancers in oriental foods, biosensors and in the production of a nutraceutical theanine. This review also aims to fully explore the potential of microbial glutaminases and to set the pace for future prospects.

Reconstruction of metabolic pathway for isobutanol production in Escherichia coli

Background

The microbial production of useful fuels and chemicals has been widely studied. In several cases, glucose is used as the raw material, and almost all microbes adopt the Embden–Meyerhof (EM) pathway to degrade glucose into compounds of interest. Recently, the Entner–Doudoroff (ED) pathway has been gaining attention as an alternative strategy for microbial production.

Results

In the present study, we attempted to apply the ED pathway for isobutanol production in Escherichia coli because of the complete redox balance involved. First, we generated ED pathway-dependent isobutanol-producing E. coli. Thereafter, the inactivation of the genes concerning organic acids as the byproducts was performed to improve the carbon flux to isobutanol from glucose. Finally, the expression of the genes concerning the ED pathway was modified.

Conclusions

The optimized isobutanol-producing E. coli produced 15.0 g/L of isobutanol as the final titer, and the yield from glucose was 0.37 g/g (g-glucose/g-isobutanol).

Electronic supplementary material

The online version of this article (10.1186/s12934-019-1171-4) contains supplementary material, which is available to authorized users.

Approaches to Computational Strain Design in the Multiomics Era

Modern omics analyses are able to effectively characterize the genetic, regulatory, and metabolic phenotypes of engineered microbes, yet designing genetic interventions to achieve a desired phenotype remains challenging. With recent developments in genetic engineering techniques, timelines associated with building and testing strain designs have been greatly reduced, allowing for the first time an efficient closed loop iteration between experiment and analysis. However, the scale and complexity associated with multi-omics datasets complicates manual biological reasoning about the mechanisms driving phenotypic changes. Computational techniques therefore form a critical part of the Design-Build-Test-Learn (DBTL) cycle in metabolic engineering. Traditional statistical approaches can reduce the dimensionality of these datasets and identify common motifs among high-performing strains. While successful in many studies, these methods do not take full advantage of known connections between genes, proteins, and metabolic networks. There is therefore a growing interest in model-aided design, in which modeling frameworks from systems biology are used to integrate experimental data and generate effective and non-intuitive design predictions. In this mini-review, we discuss recent progress and challenges in this field. In particular, we compare methods augmenting flux balance analysis with additional constraints from fluxomic, genomic, and metabolomic datasets and methods employing kinetic representations of individual metabolic reactions, and machine learning. We conclude with a discussion of potential future directions for improving strain design predictions in the omics era and remaining experimental and computational hurdles.

Biochemistry, genetics and biotechnology of glycerol utilization in Pseudomonas species

The use of renewable waste feedstocks is an environment‐friendly choice contributing to the reduction of waste treatment costs and increasing the economic value of industrial by‐products. Glycerol (1,2,3‐propanetriol), a simple polyol compound widely distributed in biological systems, constitutes a prime example of a relatively cheap and readily available substrate to be used in bioprocesses. Extensively exploited as an ingredient in the food and pharmaceutical industries, glycerol is also the main by‐product of biodiesel production, which has resulted in a progressive drop in substrate price over the years. Consequently, glycerol has become an attractive substrate in biotechnology, and several chemical commodities currently produced from petroleum have been shown to be obtained from this polyol using whole‐cell biocatalysts with both wild‐type and engineered bacterial strains. Pseudomonas species, endowed with a versatile and rich metabolism, have been adopted for the conversion of glycerol into value‐added products (ranging from simple molecules to structurally complex biopolymers, e.g. polyhydroxyalkanoates), and a number of metabolic engineering strategies have been deployed to increase the number of applications of glycerol as a cost‐effective substrate. The unique genetic and metabolic features of glycerol‐grown Pseudomonas are presented in this review, along with relevant examples of bioprocesses based on this substrate – and the synthetic biology and metabolic engineering strategies implemented in bacteria of this genus aimed at glycerol valorization.