Systems Metabolic Engineering Approaches Research Articles

Identification of key genes involved in secondary metabolite biosynthesis in Digitalis purpurea.

The medicinal plant Digitalis purpurea produces cardiac glycosides that are useful in the pharmaceutical industry. These bioactive compounds are in high demand due to ethnobotany's application to therapeutic procedures. Recent studies have investigated the role of integrative analysis of multi-omics data in understanding cellular metabolic status through systems metabolic engineering approach, as well as its application to genetically engineering metabolic pathways. In spite of numerous omics experiments, most molecular mechanisms involved in metabolic pathways biosynthesis in D. purpurea remain unclear. Using R Package Weighted Gene Co-expression Network Analysis, co-expression analysis was performed on the transcriptome and metabolome data. As a result of our study, we identified transcription factors, transcriptional regulators, protein kinases, transporters, non-coding RNAs, and hub genes that are involved in the production of secondary metabolites. Since jasmonates are involved in the biosynthesis of cardiac glycosides, the candidate genes for Scarecrow-Like Protein 14 (SCL14), Delta24-sterol reductase (DWF1), HYDRA1 (HYD1), and Jasmonate-ZIM domain3 (JAZ3) were validated under methyl jasmonate treatment (MeJA, 100 μM). Despite early induction of JAZ3, which affected downstream genes, it was dramatically suppressed after 48 hours. SCL14, which targets DWF1, and HYD1, which induces cholesterol and cardiac glycoside biosynthesis, were both promoted. The correlation between key genes and main metabolites and validation of expression patterns provide a unique insight into the biosynthesis mechanisms of cardiac glycosides in D. purpurea.

Genome-scale metabolic model of oleaginous yeast Papiliotrema laurentii

Oleaginous yeasts are promising candidates as single cell oil (SCO) platforms to meet energy demand due to their high growth rate, easy scaling and the possibility of being cultivated in culture media based on lignocellulosic biomass. The oleaginous yeast Papiliotrema laurentii UFV-1 is able to reach high lipid contents in short periods, besides its composition of fatty acids is suitable in terms of quality standards required for biodiesel production. However, little is known about the regulation of its metabolism. We present here the first genome-scale metabolic reconstruction of P. laurentii, papla-GEM. The reconstruction was based on homology to another oleaginous yeast and the model was subjected to intensive manual curation throughout the reconstruction stages to find out the metabolic specificities of this yeast. The final model includes 796 genes, 2465 reactions and 2127 metabolites, and its biomass equation is based on direct measurements of all major biomass components. The validation step was performed using experimental data obtained in this work, and simulation results evaluated the growth and lipid accumulation physiology of P. laurentii. Therefore, the papla-GEM will lead to a better understanding of the metabolic capabilities of P. laurentii and thus will be useful in systems metabolic engineering approaches.

Systems metabolic engineering of Corynebacterium glutamicum for high-level production of 1,3-propanediol from glucose and xylose

Corynebacterium glutamicum is a versatile chassis which has been widely used to produce various amino acids and organic acids. In this study, we report the development of an efficient C. glutamicum strain to produce 1,3-propanediol (1,3-PDO) from glucose and xylose by systems metabolic engineering approaches, including (1) construction and optimization of two different glycerol synthesis modules; (2) combining glycerol and 1,3-PDO synthesis modules; (3) reducing 3-hydroxypropionate accumulation by clarifying a mechanism involving 1,3-PDO re-consumption; (4) reducing the accumulation of toxic 3-hydroxypropionaldehyde by pathway engineering; (5) engineering NADPH generation pathway and anaplerotic pathway. The final engineered strain can efficiently produce 1,3-PDO from glucose with a titer of 110.4 g/L, a yield of 0.42 g/g glucose, and a productivity of 2.30 g/L/h in fed-batch fermentation. By further introducing an optimized xylose metabolism module, the engineered strain can simultaneously utilize glucose and xylose to produce 1,3-PDO with a titer of 98.2 g/L and a yield of 0.38 g/g sugars. This result demonstrates that C. glutamicum is a potential chassis for the industrial production of 1,3-PDO from abundant lignocellulosic feedstocks.

Protein Abundance Prediction Through Machine Learning Methods

Proteins are responsible for most physiological processes, and their abundance provides crucial information for systems biology research. However, absolute protein quantification, as determined by mass spectrometry, still has limitations in capturing the protein pool. Protein abundance is impacted by translation kinetics, which rely on features of codons. In this study, we evaluated the effect of codon usage bias of genes on protein abundance. Notably, we observed differences regarding codon usage patterns between genes coding for highly abundant proteins and genes coding for less abundant proteins. Analysis of synonymous codon usage and evolutionary selection showed a clear split between the two groups. Our machine learning models predicted protein abundances from codon usage metrics with remarkable accuracy, achieving strong correlation with experimental data. Upon integration of the predicted protein abundance in enzyme-constrained genome-scale metabolic models, the simulated phenotypes closely matched experimental data, which demonstrates that our predictive models are valuable tools for systems metabolic engineering approaches.

Systems Metabolic Engineering Approaches for Rewiring Cells

Systems Metabolic Engineering Approaches for Rewiring Cells

Metabolomics for industrial fermentation.

Metabolomics is essential to understand the metabolism and identify engineering targets to improve the performances of strains and bioprocesses. Although numerous metabolomics techniques have been developed and applied to various organisms, the metabolome of Saccharopolyspora erythraea, a native producer of erythromycin, had never been studied. The 2017 best paper of Bioprocess and Biosystems Engineering reports examination of three methods for quenching and extraction to analyze the intracellular metabolome of S. erythraea, and identified the most reliable methods for studying different groups of the metabolites. Subsequent studies on the dynamics of the intracellular metabolome of S. erythraea during the fed-batch fermentation identified a positive correlation between the specific erythromycin production rate and the pool size of intracellular propionyl-CoA and other precursors of erythromycin. A series of follow-up studies, such as demonstrating the applicability of the quenching/extraction methods in other related antibiotic producers, demonstrating the generality of the best matches between the quenching/extraction methods and the metabolite groups, and combining metabolomics approaches with the fluxomics and systems metabolic engineering approaches, will facilitate the metabolomics studies on important antibiotic producers, enable standardization of the quenching/extraction protocols, and improve the performance of the antibiotic production with deeper insight into their metabolism.

Engineering a short, aldolase-based pathway for (R)-1,3-butanediol production in Escherichia coli

Microbial processes can produce a wide range of compounds; however, producing complex and long chain hydrocarbons remains a challenge. Aldol condensation offers a direct route to synthesize these challenging chemistries and can be catalyzed by microbes using aldolases. Deoxyribose-5-phosphate aldolase (DERA) condenses aldehydes and/or ketones to β-hydroxyaldehydes, which can be further converted to value-added chemicals such as a precursor to cholesterol-lowering drugs. Here, we implement a short, aldolase-based pathway in Escherichia coli to produce (R)-1,3-BDO from glucose, an essential component of pharmaceutical products and cosmetics. First, we expressed a three step heterologous pathway from pyruvate to produce 0.3 g/L of (R)-1,3-BDO with a yield of 11.2 mg/g of glucose in wild-type E. coli K12 MG1655. We used a systems metabolic engineering approach to improve (R)-1,3-BDO titer and yield by: 1) identifying and reducing major by-products: ethanol, acetoin, and 2,3-butanediol; 2) increasing pathway flux through DERA to reduce accumulation of toxic acetaldehyde. We then implemented a two-stage fermentation process to improve (R)-1,3-BDO titer by 8-fold to 2.4 g/L and yield by 5-fold to 56 mg/g of glucose (11% of maximum theoretical yield) in strain BD24, by controlling pH to 7 and higher dissolved oxygen level. Furthermore, this study highlights the potential of the aldolase chemistry to synthesize diverse products directly from renewable resources in microbes.

Metabolic engineering of Escherichia coli for L-tryptophan production

The review summarizes the main approaches applied during the creation of L-tryptophan producing strains based on Escherichia coli for the industrial production of this amino acid. In addition, some prospects for the further improvement of tryptophan producers to increase their productivity and improve their technological characteristics based on systems metabolic engineering approaches are outlined in the review. These approaches can be used to obtain the producers of other aromatic amino acids and tryptophan precursors or derivatives.

Cyanobacterial Biofuels: Strategies and Developments on Network and Modeling.

Cyanobacteria, the phototrophic microorganisms, have attracted much attention recently as a promising source for environmentally sustainable biofuels production. However, barriers for commercial markets of cyanobacteria-based biofuels concern the economic feasibility. Miscellaneous strategies for improving the production performance of cyanobacteria have thus been developed. Among these, the simple ad hoc strategies resulting in failure to optimize fully cell growth coupled with desired product yield are explored. With the advancement of genomics and systems biology, a new paradigm toward systems metabolic engineering has been recognized. In particular, a genome-scale metabolic network reconstruction and modeling is a crucial systems-based tool for whole-cell-wide investigation and prediction. In this review, the cyanobacterial genome-scale metabolic models, which offer a system-level understanding of cyanobacterial metabolism, are described. The main process of metabolic network reconstruction and modeling of cyanobacteria are summarized. Strategies and developments on genome-scale network and modeling through the systems metabolic engineering approach are advanced and employed for efficient cyanobacterial-based biofuels production.

Systems metabolic engineering for the production of bio‐nylon precursor

Systematic approaches for in silico design of metabolic pathways and experimental evaluation of cellular performance are important for the development of industrially useful organisms. In this issue of Biotechnology Journal, Buschke et al. [1] report the production of 1,5-diaminopentane using xylose produced by Corynebacterium glutamicum by employing integration methodologies of rational design for genetic improvement, experimental analysis of metabolic fluxes, and comprehensive gene expression. Recent progress in 'omics sciences has facilitated the analysis of microorganisms for molecular breeding. There has been increasing interest for the integration of in silico and experimental approaches for the development of microbial cells for industrial applications. In silico simulations aid the rational design of metabolic pathways for the production of target compounds. On the basis of the in silico simulation data, the host organism is genetically manipulated to improve target metabolite production [2, 3]. The 13C-metabolic flux analysis method is useful for determining the flux distribution; this method requires experimental data procured from genetically manipulated strains [4, 5]. Identification of the genes that confer useful phenotypes for cells on the basis of DNA microarray analysis is also important [6]. The integration method, which combines in silico and experimental approaches for the development of cell factories is shown in Fig. 1. Many applications of the integration method for the bioproduction of chemicals and fuels have been reported [7, 8]. Concept of systems metabolic engineering. Production of 1,5-diaminopentane, a bio-nylon precursor, is reported by Buschke et al. [1], in this Special Issue “Systems Metabolic Engineering” of Biotechnology Journal. Buschke et al.'s study [1] is a good example of the successful application of bioengineering that contributes to the recent progress in systems metabolic engineering. Diaminopentane is produced by a one-step reaction from lysine by C. glutamicum, which is a well-known amino acid-producing bacterium and has recently used for chemical production as well [9, 10]. The authors have previously developed a high-producing strain that converts glucose to diaminopentane [11]. In the current study [1], a novel strain which produces diaminopentane from xylose was developed. Xylose utilization is particularly useful because xylose is a main component of lignocellulose waste, which is widely available. The previously developed diaminopentane-producing strain, DAP-Xyl1, produce diaminopentane less efficiently from xylose than from glucose. Thus, Buschke et al. [1] apply a systematic approach to improve diaminopentane production. In silico elementary flux mode analysis predicts an ideal metabolic state for diaminopentane production. The theoretical maximum yield from xylose is predicted, and the analysis reveal that the high oxidative pentose phosphate pathway (PPP) flux and the zero flux of the tricarboxylic acid (TCA) cycle are important for diaminopentane production; however, the metabolic flux of these pathways in the strain DAP-Xyl1 does not show good agreement with ideal metabolic flux for diaminopentane production. The small flux of PPP and the large flux of the TCA cycle cause low production of diaminopentane by the strain DAP-Xyl1. Additionally, gene selection is performed on the basis of the transcriptome analysis results. The novel, rationally designed strain DAP-Xyl2 successfully produce more than 100 g/L of diaminopentane after 75 h of cultivation. This study demonstrates the development process of a high performance strain of C. glutamicum and the importance of systems metabolic engineering approach for developing an industrially useful microorganism [7, 12]. The author declares no conflict of interest.

Toward systems metabolic engineering of Aspergillus and Pichia species for the production of chemicals and biofuels

Recently genome sequence data have become available for Aspergillus and Pichia species of industrial interest. This has stimulated the use of systems biology approaches for large-scale analysis of the molecular and metabolic responses of Aspergillus and Pichia under defined conditions, which has resulted in much new biological information. Case-specific contextualization of this information has been performed using comparative and functional genomic tools. Genomics data are also the basis for constructing genome-scale metabolic models, and these models have helped in the contextualization of knowledge on the fundamental biology of Aspergillus and Pichia species. Furthermore, with the availability of these models, the engineering of Aspergillus and Pichia is moving from traditional approaches, such as random mutagenesis, to a systems metabolic engineering approach. Here we review the recent trends in systems biology of Aspergillus and Pichia species, highlighting the relevance of these developments for systems metabolic engineering of these organisms for the production of hydrolytic enzymes, biofuels and chemicals from biomass.

Industrial biotechnology of Pseudomonas putida and related species

Since their discovery many decades ago, Pseudomonas putida and related subspecies have been intensively studied with regard to their potential application in industrial biotechnology. Today, these Gram-negative soil bacteria, traditionally known as well-performing xenobiotic degraders, are becoming efficient cell factories for various products of industrial relevance including a full range of unnatural chemicals. This development is strongly driven by systems biotechnology, integrating systems metabolic engineering approaches with novel concepts from bioprocess engineering, including novel reactor designs and renewable feedstocks.

Bio-based production of the platform chemical 1,5-diaminopentane

In the rising era of bio-economy, the five carbon compound 1,5-diaminopentane receives increasing interest as platform chemical, especially as innovative building block for bio-based polymers. The vital interest in bio-based supply of 1,5-diaminopentane has strongly stimulated research on the development of engineered producer strains. Based on the state-of-art knowledge on the pathways and reactions linked to microbial 1,5-diaminopentane metabolism, the review covers novel systems metabolic engineering approaches towards hyper-producing cell factories of Corynebacterium glutamicum or Escherichia coli. This is integrated into the whole value chain from renewable feedstocks via 1,5-diaminopentane to innovative biopolymers involving bioprocess engineering considerations for economic supply.

Systems metabolic engineering: genome-scale models and beyond.

The advent of high throughput genome-scale bioinformatics has led to an exponential increase in available cellular system data. Systems metabolic engineering attempts to use data-driven approaches--based on the data collected with high throughput technologies--to identify gene targets and optimize phenotypical properties on a systems level. Current systems metabolic engineering tools are limited for predicting and defining complex phenotypes such as chemical tolerances and other global, multigenic traits. The most pragmatic systems-based tool for metabolic engineering to arise is the in silico genome-scale metabolic reconstruction. This tool has seen wide adoption for modeling cell growth and predicting beneficial gene knockouts, and we examine here how this approach can be expanded for novel organisms. This review will highlight advances of the systems metabolic engineering approach with a focus on de novo development and use of genome-scale metabolic reconstructions for metabolic engineering applications. We will then discuss the challenges and prospects for this emerging field to enable model-based metabolic engineering. Specifically, we argue that current state-of-the-art systems metabolic engineering techniques represent a viable first step for improving product yield that still must be followed by combinatorial techniques or random strain mutagenesis to achieve optimal cellular systems.