A Quantitative Approach to Analyzing Genome Reductive Evolution Using Protein–Protein Interaction Networks: A Case Study of Mycobacterium leprae

Abstract

The advance in high-throughput sequencing technologies has yielded complete genome sequences of several organisms, including complete bacterial genomes. The growing number of these available sequenced genomes has enabled analyses of their dynamics, as well as the molecular and evolutionary processes which these organisms are under. Comparative genomics of different bacterial genomes have highlighted their genome size and gene content in association with lifestyles and adaptation to various environments and have contributed to enhancing our understanding of the mechanisms of their evolution. Protein–protein functional interactions mediate many essential processes for maintaining the stability of the biological systems under changing environmental conditions. Thus, these interactions play crucial roles in the evolutionary processes of different organisms, especially for obligate intracellular bacteria, proven to generally have reduced genome sizes compared to their nearest free-living relatives. In this study, we used the approach based on the Renormalization Group (RG) analysis technique and the Maximum-Excluded-Mass-Burning (MEMB) model to investigate the evolutionary process of genome reduction in relation to the organization of functional networks of two organisms. Using a Mycobacterium leprae (MLP) network in comparison with a Mycobacterium tuberculosis (MTB) network as a case study, we show that reductive evolution in MLP was as a result of removal of important proteins from neighbors of corresponding orthologous MTB proteins. While each orthologous MTB protein had an increase in number of interacting partners in most instances, the corresponding MLP protein had lost some of them. This work provides a quantitative model for mapping reductive evolution and protein–protein functional interaction network organization in terms of roles played by different proteins in the network structure.

Identifying genetic variants and pathways associated with extreme levels of fetal hemoglobin in Sickle Cell Disease in Tanzania.

“…CHD4 is a chromatin organization modifier which confers the chromatin remodeling function of the NuRD complex. CHD4 has been reported to repress γ-globin gene expression in mouse [63,64]. Similarly, MBD3 operates as a NuRD complex and is associated with the transcription factors GATA-1 and FOG-1 to directly regulate genes within the β-globin locus.…”

Identifying genetic variants and pathways associated with extreme levels of fetal hemoglobin in Sickle Cell Disease in Tanzania.

“…The human protein-protein interaction (PPI) ( Figure 3A) for CHD4 and MBD3 proteins indicates that they are essential to system survival and hence their biological functions tend to be evolutionary conserved [63]. Thus, in presence of non-synonymous mutations, it is expected that individual components (proteins and interactions) in the system must adapt to a changing environment while maintaining the system's primary function.…”

Identifying genetic variants and pathways associated with extreme levels of fetal hemoglobin in Sickle Cell Disease in Tanzania.

“…CHD4 is a chromatin organization modi er which confers the chromatin remodeling function of the NuRD complex. CHD4 has been reported to repress γ-globin gene expression in mice [63,64]. Similarly, MBD3 operates as a NuRD complex and is associated with the transcription factors GATA-1 and FOG-1, which directly regulate genes within the β-globin locus.…”