Evolutionary growth of certain metabolic pathways involved in the functioning of GAD and INS genes in Type 1 Diabetes Mellitus: Their architecture and stability

Background: Studying biochemical pathway evolution for diseases is a flourishing area of Systems Biology. Here, we study Type 1 Diabetes Mellitus (T1D), focusing on growth of glutamate, β-alanine, taurine and hypotaurine, and butanoate metabolisms involved in onset of GAD and INS genes in Homo sapiens with comparative analysis in non-obese diabetic Mus musculus, biobreeding Diabetes-prone Rattus norvegicus, Pan troglodytes, Oryctolagus cuniculus, Danio rerio and Drosophila melanogaster respectively. Methods: We propose an algorithm for growth analysis for four metabolic pathways involved in T1D. It has three modules, pattern finding, interaction identification and growth detection. The first module identifies patterns using Community structures using Hamming distances and the Tanimoto coefficient. We have performed functional analysis by representing patterns using ODEs, and identified Stoichiometric, Gradient and Jacobian matrices. The second module identifies interactions among patterns using cut-sets and network-partitioning by 'Divide-and-conquer'. The third module identifies functions of patterns using interactions, thereby highlighting their nature of growth.Results: We observed that metabolites that are genetically robust and resist alterations against stable state during evolution, account for emergence of a scale-free network.Discussion: New modules get acquired to the fundamental cluster in a preferential manner, an instance of micro-evolution theory. For instance, (S)-3-hydroxy butanoyl-CoA, acetoacetyl-CoA, acetoacetate, acetyl-CoA, (S)-3-hydroxy-3-methyl glutaryl-CoA acts as a fundamental cluster in butanoate metabolism. Moreover, the interactions among metabolites are divergent in nature.