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Evolutionary Perspectives of Genotype–Phenotype Factors in Leishmania Metabolism

  • Abhishek Subramanian
  • Ram Rup Sarkar
Original Article

Abstract

The sandfly midgut and the human macrophage phagolysosome provide antagonistic metabolic niches for the endoparasite Leishmania to survive and populate. Although these environments fluctuate across developmental stages, the relative changes in both these environments across parasite generations might remain gradual. Such environmental restrictions might endow parasite metabolism with a choice of specific genotypic and phenotypic factors that can constrain enzyme evolution for successful adaptation to the host. With respect to the available cellular information for Leishmania species, for the first time, we measure the relative contribution of eight inter-correlated predictors related to codon usage, GC content, gene expression, gene length, multi-functionality, and flux-coupling potential of an enzyme on the evolutionary rates of singleton metabolic genes and further compare their effects across three Leishmania species. Our analysis reveals that codon adaptation, multi-functionality, and flux-coupling potential of an enzyme are independent contributors of enzyme evolutionary rates, which can together explain a large variation in enzyme evolutionary rates across species. We also hypothesize that a species-specific occurrence of duplicated genes in novel subcellular locations can create new flux routes through certain singleton flux-coupled enzymes, thereby constraining their evolution. A cross-species comparison revealed both common and species-specific genes whose evolutionary divergence was constrained by multiple independent factors. Out of these, previously known pharmacological targets and virulence factors in Leishmania were identified, suggesting their evolutionary reasons for being important survival factors to the parasite. All these results provide a fundamental understanding of the factors underlying adaptive strategies of the parasite, which can be further targeted.

Keywords

Leishmania metabolism Evolutionary rate variation Codon usage Multi-functionality Physiological flux-coupling Principal component regression (PCR) 

Notes

Acknowledgements

This work was supported by a Grant from the Department of Biotechnology, Government of India [BT/PR14958/BID/7/537/2015] provided to RRS. AS also acknowledges the Senior Research Fellowship from DBT-BINC. The authors are thankful to the anonymous reviewers for their critical comments and suggestion to improve the quality of the paper.

Supplementary material

239_2018_9857_MOESM1_ESM.doc (1024 kb)
Supplementary Text S1: This file contains results supporting the reported observations and further details of methodology provided in the main article (DOC 1023 KB)
239_2018_9857_MOESM2_ESM.xls (228 kb)
Supplementary File S1: The final shortlisted set of singleton orthologous genes and their features considered for the regression analyses for the three Leishmania species provided in separate sheets within the file (XLS 228 KB)
239_2018_9857_MOESM3_ESM.xls (309 kb)
Supplementary File S2: The principal components for the response dN and dS rates in the three Leishmania species (provided in separate sheets) identified after performing principal component regression (XLS 309 KB)
239_2018_9857_MOESM4_ESM.xls (79 kb)
Supplementary File S3: Orthologous groups of singleton and duplicated genes that occur in different subcellular locations across species and average number of flux-couplings associated with them. The singleton and duplicated genes are provided in separate sheets (XLS 79 KB)
239_2018_9857_MOESM5_ESM.xls (239 kb)
Supplementary File S4: File containing gene clusters as identified by K-means performed with respect to the coordinates of the genes in the selected principal component space for the dN and dS rates and the centroid of each cluster within the n-dimensional feature space. The gene clusters and the centroids for the three species are provided in separate sheets (XLS 239 KB)

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Copyright information

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Authors and Affiliations

  1. 1.Chemical Engineering and Process DevelopmentCSIR-National Chemical LaboratoryPuneIndia
  2. 2.Academy of Scientific & Innovative Research (AcSIR)PuneIndia

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