Genome-scale metabolic model of Rhodococcus jostii RHA1 (iMT1174) to study the accumulation of storage compounds during nitrogen-limited condition

A High-Quality Genome-Scale Model for Rhodococcus opacus Metabolism

Rhodococcus opacus is a bacterium that has a high tolerance to aromatic compounds and can produce significant amounts of triacylglycerol (TAG). Here, we present iGR1773, the first genome-scale model (GSM) of R. opacus PD630 metabolism based on its genomic sequence and associated data. The model includes 1773 genes, 3025 reactions, and 1956 metabolites, was developed in a reproducible manner using CarveMe, and was evaluated through Metabolic Model tests (MEMOTE). We combine the model with two Constraint-Based Reconstruction and Analysis (COBRA) methods that use transcriptomics data to predict growth rates and fluxes: E-Flux2 and SPOT (Simplified Pearson Correlation with Transcriptomic data). Growth rates are best predicted by E-Flux2. Flux profiles are more accurately predicted by E-Flux2 than flux balance analysis (FBA) and parsimonious FBA (pFBA), when compared to 44 central carbon fluxes measured by 13C-Metabolic Flux Analysis (13C-MFA). Under glucose-fed conditions, E-Flux2 presents an R2 value of 0.54, while predictions based on pFBA had an inferior R2 of 0.28. We attribute this improved performance to the extra activity information provided by the transcriptomics data. For phenol-fed metabolism, in which the substrate first enters the TCA cycle, E-Flux2's flux predictions display a high R2 of 0.96 while pFBA showed an R2 of 0.93. We also show that glucose metabolism and phenol metabolism function with similar relative ATP maintenance costs. These findings demonstrate that iGR1773 can help the metabolic engineering community predict aromatic substrate utilization patterns and perform computational strain design.

Systems biology and metabolic engineering of Rhodococcus for bioconversion and biosynthesis processes

Rhodococcus spp. strains are widespread in diverse natural and anthropized environments thanks to their high metabolic versatility, biodegradation activities, and unique adaptation capacities to several stress conditions such as the presence of toxic compounds and environmental fluctuations. Additionally, the capability of Rhodococcus spp. strains to produce high value-added products has received considerable attention, mostly in relation to lipid accumulation. In relation with this, several works carried out omic studies and genome comparative analyses to investigate the genetic and genomic basis of these anabolic capacities, frequently in association with the bioconversion of renewable resources and low-cost substrates into triacylglycerols. This review is focused on these omic analyses and the genetic and metabolic approaches used to improve the biosynthetic and bioconversion performance of Rhodococcus. In particular, this review summarizes the works that applied heterologous expression of specific genes and adaptive laboratory evolution approaches to manipulate anabolic performance. Furthermore, recent molecular toolkits for targeted genome editing as well as genome-based metabolic models are described here as novel and promising strategies for genome-scaled rational design of Rhodococcus cells for efficient biosynthetic processes application.

Genetic toolkits for engineering Rhodococcus species with versatile applications

Rhodococcus spp. are a group of non-model gram-positive bacteria with diverse catabolic activities and strong adaptive capabilities, which enable their wide application in whole-cell biocatalysis, environmental bioremediation, and lignocellulosic biomass conversion. Compared with model microorganisms, the engineering of Rhodococcus is challenging because of the lack of universal molecular tools, high genome GC content (61% ~ 71%), and low transformation and recombination efficiencies. Nevertheless, because of the high interest in Rhodococcus species for bioproduction, various genetic elements and engineering tools have been recently developed for Rhodococcus spp., including R. opacus, R. jostii, R. ruber, and R. erythropolis, leading to the expansion of the genetic toolkits for Rhodococcus engineering. In this article, we provide a comprehensive review of the important developed genetic elements for Rhodococcus, including shuttle vectors, promoters, antibiotic markers, ribosome binding sites, and reporter genes. In addition, we also summarize gene transfer techniques and strategies to improve transformation efficiency, as well as random and precise genome editing tools available for Rhodococcus, including transposition, homologous recombination, recombineering, and CRISPR/Cas9. We conclude by discussing future trends in Rhodococcus engineering. We expect that more synthetic and systems biology tools (such as multiplex genome editing, dynamic regulation, and genome-scale metabolic models) will be adapted and optimized for Rhodococcus.

Biotechnology of Rhodococcus for the production of valuable compounds

Bacteria belonging to Rhodococcus genus represent ideal candidates for microbial biotechnology applications because of their metabolic versatility, ability to degrade a wide range of organic compounds, and resistance to various stress conditions, such as metal toxicity, desiccation, and high concentration of organic solvents. Rhodococcus spp. strains have also peculiar biosynthetic activities that contribute to their strong persistence in harsh and contaminated environments and provide them a competitive advantage over other microorganisms. This review is focused on the metabolic features of Rhodococcus genus and their potential use in biotechnology strategies for the production of compounds with environmental, industrial, and medical relevance such as biosurfactants, bioflocculants, carotenoids, triacylglycerols, polyhydroxyalkanoate, siderophores, antimicrobials, and metal-based nanostructures. These biosynthetic capacities can also be exploited to obtain high value-added products from low-cost substrates (industrial wastes and contaminants), offering the possibility to efficiently recover valuable resources and providing possible waste disposal solutions. Rhodococcus spp. strains have also recently been pointed out as a source of novel bioactive molecules highlighting the need to extend the knowledge on biosynthetic capacities of members of this genus and their potential utilization in the framework of bioeconomy. KEY POINTS: • Rhodococcus possesses promising biosynthetic and bioconversion capacities. • Rhodococcus bioconversion capacities can provide waste disposal solutions. • Rhodococcus bioproducts have environmental, industrial, and medical relevance. Graphical abstract.

Dynamic Metabolic Analysis of Cupriavidus necator DSM545 Producing Poly(3-hydroxybutyric acid) from Glycerol

Cupriavidus necator DSM 545 can utilise glycerol to synthesise poly(3-hydroxybutyric acid) under unbalanced growth conditions, i.e., nitrogen limitation. To improve poly(3-hydroxybutyric acid) (PHB) batch production by C. necator through model-guided bioprocessing or genetic engineering, insights into the dynamic effect of the fermentation conditions on cell metabolism are crucial. In this work, we have used dynamic flux balance analysis (DFBA), a constrained-based stoichiometric modelling approach, to study the metabolic change associated with PHB synthesis during batch cultivation. The model employs the ‘minimisation of all fluxes’ as cellular objectives and measured extracellular fluxes as additional constraints. The mass balance constraints are further adjusted based on thermodynamic considerations. The resultant flux distribution profiles characterise the evolution of metabolic states due to adaptation to dynamic extracellular conditions and provide further insights towards improvements that can be implemented to enhance PHB productivity.

Basics of genome-scale metabolic modeling and applications on C1-utilization

It is fundamental to understand the relationship between genotype and phenotype in biology. This requires comprehensive knowledge of metabolic pathways, genetic information and well-defined mathematic modeling. Integration of knowledge on metabolism with mathematical modeling results in genome-scale metabolic models which have proven useful to investigate bacterial metabolism and to engineer bacterial strains capable of producing value-added biochemical. Single carbon substrates such as methane and carbon monoxide have drawn interests and they assumed one of next-generation feedstocks because of their high abundance and low price. The methylotroph and acetogen-based biorefineries hold promises for bioconversion of C1 substrates into biofuels and high value compounds. As an effort on expanding our knowledge on C1 utilization approaches, in silico computational framework of C1-metabolism in methylotrophic and acetogenic bacteria has been developed. In this review, genome-scale metabolic models for C1-utilizing bacteria and well-established analysis tools are presented for potential uses for study of C1 metabolism at the genome scale and its application in metabolic engineering.

In silico identification of metabolic engineering strategies for improved lipid production in Yarrowia lipolytica by genome-scale metabolic modeling

BACKGROUND

Yarrowia lipolytica, an oleaginous yeast, is a promising platform strain for production of biofuels and oleochemicals as it can accumulate a high level of lipids in response to nitrogen limitation. Accordingly, many metabolic engineering efforts have been made to develop engineered strains of Y. lipolytica with higher lipid yields. Genome-scale model of metabolism (GEM) is a powerful tool for identifying novel genetic designs for metabolic engineering. Several GEMs for Y. lipolytica have recently been developed; however, not many applications of the GEMs have been reported for actual metabolic engineering of Y. lipolytica. The major obstacle impeding the application of Y. lipolytica GEMs is the lack of proper methods for predicting phenotypes of the cells in the nitrogen-limited condition, or more specifically in the stationary phase of a batch culture.

RESULTS

In this study, we showed that environmental version of minimization of metabolic adjustment (eMOMA) can be used for predicting metabolic flux distribution of Y. lipolytica under the nitrogen-limited condition and identifying metabolic engineering strategies to improve lipid production in Y. lipolytica. Several well-characterized overexpression targets, such as diglyceride acyltransferase, acetyl-CoA carboxylase, and stearoyl-CoA desaturase, were successfully rediscovered by our eMOMA-based design method, showing the relevance of prediction results. Interestingly, the eMOMA-based design method also suggested non-intuitive knockout targets, and we experimentally validated the prediction with a mutant lacking YALI0F30745g, one of the predicted targets involved in one-carbon/methionine metabolism. The mutant accumulated 45% more lipids compared to the wild-type.

CONCLUSION

This study demonstrated that eMOMA is a powerful computational method for understanding and engineering the metabolism of Y. lipolytica and potentially other oleaginous microorganisms.

Predicting the accumulation of storage compounds by Rhodococcus jostii RHA1 in the feast-famine growth cycles using genome-scale flux balance analysis

Feast-famine cycles in biological wastewater resource recovery systems select for bacterial species that accumulate intracellular storage compounds such as poly-β-hydroxybutyrate (PHB), glycogen, and triacylglycerols (TAG). These species survive better the famine phase and resume rapid substrate uptake at the beginning of the feast phase faster than microorganisms unable to accumulate storage. However, ecophysiological conditions favouring the accumulation of either storage compounds remain to be clarified, and predictive capabilities need to be developed to eventually rationally design reactors producing these compounds. Using a genome-scale metabolic modelling approach, the storage metabolism of Rhodococcus jostii RHA1 was investigated for steady-state feast-famine cycles on glucose and acetate as the sole carbon sources. R. jostii RHA1 is capable of accumulating the three storage compounds (PHB, TAG, and glycogen) simultaneously. According to the experimental observations, when glucose was the substrate, feast phase chemical oxygen demand (COD) accumulation was similar for the three storage compounds; when acetate was the substrate, however, PHB accumulation was 3 times higher than TAG accumulation and essentially no glycogen was accumulated. These results were simulated using the genome-scale metabolic model of R. jostii RHA1 (iMT1174) by means of flux balance analysis (FBA) to determine the objective functions capable of predicting these behaviours. Maximization of the growth rate was set as the main objective function, while minimization of total reaction fluxes and minimization of metabolic adjustment (environmental MOMA) were considered as the sub-objective functions. The environmental MOMA sub-objective performed better than the minimization of total reaction fluxes sub-objective function at predicting the mixture of storage compounds accumulated. Additional experiments with ¹³C-labelled bicarbonate (HCO₃⁻) found that the fluxes through the central metabolism reactions during the feast phases were similar to the ones during the famine phases on acetate due to similarity in the carbon sources in the feast and famine phases (i.e., acetate and poly-β-hydroxybutyrate, respectively); this suggests that the environmental MOMA sub-objective function could be used to analyze successive environmental conditions such as the feast and famine cycles while the metabolically similar carbon sources are taken up by microorganisms.

Engineering levoglucosan metabolic pathway in Rhodococcus jostii RHA1 for lipid production

Oleaginous strains of Rhodococcus including R. jostii RHA1 have attracted considerable attention due to their ability to accumulate triacylglycerols (TAGs), robust growth properties and genetic tractability. In this study, a novel metabolic pathway was introduced into R. jostii by heterogenous expression of the well-characterized gene, lgk encoding levoglucosan kinase from Lipomyces starkeyi YZ-215. This enables the recombinant R. jostii RHA1 to produce TAGs from the anhydrous sugar, levoglucosan, which can be generated efficiently as the major molecule from the pyrolysis of cellulose. The recombinant R. jostii RHA1 could grow on levoglucosan as the sole carbon source, and the consumption rate of levoglucosan was determined. Furthermore, expression of one more copy of lgk increased the enzymatic activity of LGK in the recombinant. However, the growth performance of the recombinant bearing two copies of lgk on levoglucosan was not improved. Although expression of lgk in the recombinants was not repressed by the glucose present in the media, glucose in the sugar mixture still affected consumption of levoglucosan. Under nitrogen limiting conditions, lipid produced from levoglucosan by the recombinant bearing lgk was up to 43.54 % of the cell dry weight, which was comparable to the content of lipid accumulated from glucose. This work demonstrated the technical feasibility of producing lipid from levoglucosan, an anhydrosugar derived from the pyrolysis of lignocellulosic materials, by the genetically modified rhodococci strains.

Flux Balance Analysis Inspired Bioprocess Upgrading for Lycopene Production by a Metabolically Engineered Strain of Yarrowia lipolytica

Genome-scale metabolic models embody a significant advantage of systems biology since their applications as metabolic flux simulation models enable predictions for the production of industrially-interesting metabolites. The biotechnological production of lycopene from Yarrowia lipolytica is an emerging scope that has not been fully scrutinized, especially for what concerns cultivation conditions of newly generated engineered strains. In this study, by combining flux balance analysis (FBA) and Plackett-Burman design, we screened chemicals for lycopene production from a metabolically engineered strain of Y. lipolytica. Lycopene concentrations of 126 and 242 mg/L were achieved correspondingly from the FBA-independent and the FBA-assisted designed media in fed-batch cultivation mode. Transcriptional studies revealed upregulations of heterologous genes in media designed according to FBA, thus implying the efficiency of model predictions. Our study will potentially support upgraded lycopene and other terpenoids production from existing or prospect bioengineered strains of Y. lipolytica and/or closely related yeast species.