Integrative Computational Framework for Understanding Metabolic Modulation in Leishmania

Abstract

The integration of computational and mathematical approaches is used to provide a key insight into the biological systems. Here, we seek to find detailed and more robust information on Leishmanial metabolic network by performing mathematical characterization in terms of Forman/Forman-Ricci curvature measures combined with flux balance analysis (FBA). The model prototype developed largely depends on its structure and topological components. The correlation of curvature measures with various network statistical properties revealed the structural-functional framework. The analyses helped us to identify the importance of several nodes and detect sub-networks. Our results revealed several key high curvature nodes (metabolites) belonging to common yet crucial metabolic, thus, maintaining the integrity of the network which signifies its robustness. Further analysis revealed the presence of some of these metabolites in redox metabolism of the parasite. MGO, an important node, has highly cytotoxic and mutagenic nature that can irreversibly modify DNA, proteins and enzymes, making them nonfunctional, leading to the formation of AGEs and MGO •-. Being a component in the glyoxalase pathway, we further attempted to study the outcome of the deletion of the key enzyme (GLOI) mainly involved in the neutralization of MGO by utilizing FBA. The model and the objective function both kept as simple as possible, demonstrated an interesting emergent behavior. The nonfunctional GLOI in the model contributed to 'zero' flux which signifies the key role of GLOI as a rate limiting enzyme. This has led to several fold increase production of MGO, thereby, causing an increased level of MGO •generation. Hence, the integrated computational approaches has deciphered GLOI as a potential target both from curvature measures as well as FBA which could further be explored for kinetic modeling by implying various redox-dependent constraints on the model. Designing various in vitro experimental perspectives could churn the therapeutic importance of GLOI.Leishmaniasis, one of the most neglected tropical diseases in the world, is of primary concern due to the increased risk of emerging drug resistance. To design novel drugs and search effective molecular drug targets with therapeutic importance, it is important to decipher the relation among the components responsible for leishmanial parasite survival inside the host cell at the metabolic level. Here, we have attempted to get an insight in the leishmanial metabolic network and predict the importance of key metabolites by applying mathematical characterization in terms of curvature measures and flux balance analysis (FBA). Our results identified several metabolites playing significant role in parasite's redox homeostasis. Among these MGO (methylglyoxal) caught our interest due to its highly toxic and reactive nature of irreversibly modifying DNA and proteins. FBA results helped us to look into the important role of GLOI (Glyoxalase I), the enzyme that catalyses the detoxification of MGO, in the pathway tha...

Integrative Computational Framework for Understanding Metabolic Modulation in Leishmania

“…Nodes having high betweenness centrality are known to act as bridge between nodes for transmission of information in the network. In our M model several of these metabolites (HTA, MG, Pyr, T[SH] 2 ) with high betweenness centrality were part of M7 model (Table S3) suggesting the importance of M7 model (Chauhan and Singh, 2019).…”

“…Interestingly, peaks appearing far from “zero,” those with higher Forman curvature, consisted of edges and nodes related to glycolysis, MG metabolism and T[SH] 2 metabolism pathways. Furthermore, these metabolites were also spotted as important vertices from Forman curvature plot of nodes in “M” model (Figure 5) (Chauhan and Singh, 2019) (Table S4).…”

“…In our master model we found more than 25 nodes with high curvature values (Table S3). We noted that most of the nodes from these were related to “M7” model that consists of glycolysis, T[SH] 2 synthesis, and methylglyoxal metabolism pathways, signifying the importance of “M7” model (Chauhan and Singh, 2019).…”

“…We considered, for our model, the end products of both the pathways, glycolysis (pyruvate) and glyoxalase pathway (D-lactate), contributing to the total biomass production. The system was investigated under two scenarios, first, functional GLO I, and second, nonfunctional (absent from the system) GLO I (Chauhan and Singh, 2019).…”

Uncovering oomycete metabolism using systems biology

“…the bacterium Haemophilus influenzae that causes disease in humans (Edwards and Palsson, 1999). Since then, GEMs have been reconstructed for many more pathogens, such as the tuberculosis bacterium Mycobacterium tuberculosis (Kavvas et al, 2018;Rienksma et al, 2018) and the human and animal parasites of the genera Plasmodium (Plata et al, 2010;Stanway et al, 2019) and Leishmania (Chauhan and Singh, 2019;Sharma et al, 2017;Subramanian et al, 2015). Some GEMs integrated pathogen and host, thereby providing insight into the metabolic fluxes throughout infection (Bazzani et al, 2012;Bordbar et al, 2010;Huthmacher et al, 2010).…”