Analysis of metabolic networks of Streptomyces leeuwenhoekii C34 by means of a genome scale model: Prediction of modifications that enhance the production of specialized metabolites

Promoting Butenyl-spinosyn Production Based on Omics Research and Metabolic Network Construction in Saccharopolyspora pogona

Understanding the metabolism of Saccharopolyspora pogona on a global scale is essential for manipulating its metabolic capabilities to improve butenyl-spinosyn biosynthesis. Here, we combined multiomics analysis to parse S. pogona genomic information, construct a metabolic network, and mine important functional genes that affect the butenyl-spinosyn biosynthesis. This research not only elucidated the relationship between butenyl-spinosyn biosynthesis and the primary metabolic pathway but also showed that the low expression level and continuous downregulation of the bus cluster and the competitive utilization of acetyl-CoA were the main reasons for reduced butenyl-spinosyn production. Our framework identified 148 genes related to butenyl-spinosyn biosynthesis that were significantly differentially expressed, confirming that butenyl-spinosyn polyketide synthase (PKS) and succinic semialdehyde dehydrogenase (GabD) play an important role in regulating butenyl-spinosyn biosynthesis. Combined modification of these genes increased overall butenyl-spinosyn production by 6.38-fold to 154.1 ± 10.98 mg/L. Our results provide an important strategy for further promoting the butenyl-spinosyn titer.

Inspecting the Solution Space of Genome-Scale Metabolic Models

Genome-scale metabolic models are frequently used in computational biology. They offer an integrative view on the metabolic network of an organism without the need to know kinetic information in detail. However, the huge solution space which comes with the analysis of genome-scale models by using, e.g., Flux Balance Analysis (FBA) poses a problem, since it is hard to thoroughly investigate and often only an arbitrarily selected individual flux distribution is discussed as an outcome of FBA. Here, we introduce a new approach to inspect the solution space and we compare it with other approaches, namely Flux Variability Analysis (FVA) and CoPE-FBA, using several different genome-scale models of lactic acid bacteria. We examine the extent to which different types of experimental data limit the solution space and how the robustness of the system increases as a result. We find that our new approach to inspect the solution space is a good complementary method that offers additional insights into the variance of biological phenotypes and can help to prevent wrong conclusions in the analysis of FBA results.

Using computer tools for the evaluation of biodegradability, toxicity, and activity on the AT1 receptor of degradation products identified in the removal of valsartan by using photo-electro-Fenton process

This work deals with the theoretical approach of biodegradability, lipophilicity, and physiological activity of VAL and four degradation products (DPs) detected after 20 min of the photo-electro-Fenton (PEF) process. The biodegradability calculation, taking into account the change in the theoretical oxygen demand, showed that the four DPs had a more negative value than VAL, indicating that they are more susceptible to oxidation. However, these results do not imply more accessible biotransformation pathways than VAL, as observed using the EAWAG-BBD program, through which neutral biotransformation pathway prediction for VAL and DPs was made. Subsequently, by calculating the theoretical lipophilicity of the molecules (log P), the theoretical toxicity of the DPs was proposed, where the DPs had log P values between 1 and 3, lower values than those of VAL (log P = 4), indicating that DPs could be less toxic than the original compound (VAL). Both results suggest that VAL degradation (by photo-electro-Fenton process proposed) yields a positive effect on the environment. Finally, when molecular dynamic simulations were carried out, it was observed that DP1, DP2, and DP3 maintained similar interactions to those of VAL with the binding site of the AT1R. DP4 did not show any interaction. These results indicated that, despite the presence of DPs, generated after 20 min of the treatment, they could not exert a physiological activity in any organism the same way that does VAL.

Clavulanic Acid Production by Streptomyces clavuligerus: Insights from Systems Biology, Strain Engineering, and Downstream Processing

Clavulanic acid (CA) is an irreversible β-lactamase enzyme inhibitor with a weak antibacterial activity produced by Streptomyces clavuligerus (S. clavuligerus). CA is typically co-formulated with broad-spectrum β‑lactam antibiotics such as amoxicillin, conferring them high potential to treat diseases caused by bacteria that possess β‑lactam resistance. The clinical importance of CA and the complexity of the production process motivate improvements from an interdisciplinary standpoint by integrating metabolic engineering strategies and knowledge on metabolic and regulatory events through systems biology and multi-omics approaches. In the large-scale bioprocessing, optimization of culture conditions, bioreactor design, agitation regime, as well as advances in CA separation and purification are required to improve the cost structure associated to CA production. This review presents the recent insights in CA production by S. clavuligerus, emphasizing on systems biology approaches, strain engineering, and downstream processing.

Metabolic modelling and simulation of the light and dark metabolism of Chlamydomonas reinhardtii

A metabolic network model of the green microalga Chlamydomonas reinhardtii was used to characterize photoautotrophic and heterotrophic (i.e. growth on stored compounds) growth under light and dark, respectively. The metabolic network comprised 2514 reactions distributed among nine intracellular compartments and the extracellular space. The metabolic network included all the key biochemical pathways for synthesis and metabolism of starch and triacylglycerols (TAGs). Under light and nitrogen limitation, the model simulated the accumulation of the energy-rich compounds (TAGs and starch) in the cell. In the dark, the model could simulate cell growth and maintenance on stored compounds. The model-predicted consumption rates of storage compounds (starch or TAGs) to enable growth in the dark, were found to be greater than the rates of synthesis under light. This implied utilization of the storage compounds for cell maintenance in the dark. Under constant illumination, the simulations of cell growth and intracellular starch content agreed closely with independent experimental data. In other simulations, compared with the case without photorespiration, light uptake rate increased 1.04-fold when the ratio of the rates of oxygenation and carboxylation (Rubisco) was 0.1. Although extensive experimental work exists on culture and physiology of microalgae, it does not allow quantitative predictions of the influence of dark metabolism on the productivity of metabolites to be made. This limitation is overcome using the present model. A metabolic network model of Chlamydomonas reinhardtii is shown to simulate growth and synthesis of energy-rich compounds (triacylglycerols and starch) under light. The same model also simulates dark growth and maintenance through consumption of the stored energy-rich compounds.

Interaction and Regulation of Carbon, Nitrogen, and Phosphorus Metabolisms in Root Nodules of Legumes

Members of the plant family Leguminosae (Fabaceae) are unique in that they have evolved a symbiotic relationship with rhizobia (a group of soil bacteria that can fix atmospheric nitrogen). Rhizobia infect and form root nodules on their specific host plants before differentiating into bacteroids, the symbiotic form of rhizobia. This complex relationship involves the supply of C₄-dicarboxylate and phosphate by the host plants to the microsymbionts that utilize them in the energy-intensive process of fixing atmospheric nitrogen into ammonium, which is in turn made available to the host plants as a source of nitrogen, a macronutrient for growth. Although nitrogen-fixing bacteroids are no longer growing, they are metabolically active. The symbiotic process is complex and tightly regulated by both the host plants and the bacteroids. The metabolic pathways of carbon, nitrogen, and phosphate are heavily regulated in the host plants, as they need to strike a fine balance between satisfying their own needs as well as those of the microsymbionts. A network of transporters for the various metabolites are responsible for the trafficking of these essential molecules between the two partners through the symbiosome membrane (plant-derived membrane surrounding the bacteroid), and these are in turn regulated by various transcription factors that control their expressions under different environmental conditions. Understanding this complex process of symbiotic nitrogen fixation is vital in promoting sustainable agriculture and enhancing soil fertility.