<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Subramanian, Abhishek</style></author><author><style face="normal" font="default" size="100%">Sarkar, Ram Rup</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Comparison of codon usage bias across leishmania and trypanosomatids to understand mRNA secondary structure, relative protein abundance and pathway functions</style></title><secondary-title><style face="normal" font="default" size="100%">Genomics</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Amino acid bias</style></keyword><keyword><style  face="normal" font="default" size="100%">Base composition</style></keyword><keyword><style  face="normal" font="default" size="100%">Codon usage bias</style></keyword><keyword><style  face="normal" font="default" size="100%">Leishmania</style></keyword><keyword><style  face="normal" font="default" size="100%">Mutation</style></keyword><keyword><style  face="normal" font="default" size="100%">Selection bias</style></keyword><keyword><style  face="normal" font="default" size="100%">Species specificity</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2015</style></year><pub-dates><date><style  face="normal" font="default" size="100%">OCT</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">4</style></number><publisher><style face="normal" font="default" size="100%">ACADEMIC PRESS INC ELSEVIER SCIENCE</style></publisher><pub-location><style face="normal" font="default" size="100%">525 B ST, STE 1900, SAN DIEGO, CA 92101-4495 USA</style></pub-location><volume><style face="normal" font="default" size="100%">106</style></volume><pages><style face="normal" font="default" size="100%">232-241</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Understanding the variations in gene organization and its effect on the phenotype across different Leishmania species, and to study differential clinical manifestations of parasite within the host, we performed large scale analysis of codon usage patterns between Leishmania and other known Trypanosomatid species. We present; the causes and consequences of codon usage bias in Leishmania genomes with respect to mutational pressure, translational selection and amino acid composition bias. We establish GC bias at wobble position that governs codon usage bias across Leishmania species, rather than amino acid composition bias. We found that, within Leishmania, homogenous codon context coding for less frequent amino acid pairs and codons avoiding formation of folding structures in mRNA are essentially chosen. We predicted putative differences in global expression between genes belonging to specific pathways across Leishmania. This explains the role of evolution in shaping the otherwise conserved genome to demonstrate species-specific function-level differences for efficient survival. (C) 2015 Elsevier Inc. All rights reserved.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">4</style></issue><custom3><style face="normal" font="default" size="100%">&lt;p&gt;Foreign&lt;/p&gt;</style></custom3><custom4><style face="normal" font="default" size="100%">2.386</style></custom4></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Subramanian, Abhishek</style></author><author><style face="normal" font="default" size="100%">Sarkar, Ram Rup</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Data in support of large scale comparative codon usage analysis in leishmania and trypanosomatids</style></title><secondary-title><style face="normal" font="default" size="100%">Data Brief</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year><pub-dates><date><style  face="normal" font="default" size="100%">JUN</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">4</style></volume><pages><style face="normal" font="default" size="100%">269-272</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;This data article contains data related to the article “Comparison of codon usage bias across Leishmania and Trypanosomatids to understand mRNA secondary structure, relative protein abundance and pathway functions” by Subramanian and Sarkar [1]. The data comprises of sequence-based measures that quantify the effect of codon usage across genomes. The data thus generated represents computed values of codon usage indices like relative synonymous codon usage (RSCU), effective number of codons (ENC), and codon adaptation index (CAI), a set of single copy orthologous genes common to the 13 Trypanosomatids, and comparisons of CAI between genes of different functions. This forms a basis of comparison to infer the causes and consequences of codon usage bias in Leishmania and other Trypanosomatids.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">C</style></issue><work-type><style face="normal" font="default" size="100%">Article</style></work-type><custom3><style face="normal" font="default" size="100%">&lt;p&gt;Foreign&lt;/p&gt;</style></custom3><custom4><style face="normal" font="default" size="100%">&lt;p&gt;1.43&lt;/p&gt;</style></custom4></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Subramanian, Abhishek</style></author><author><style face="normal" font="default" size="100%">Jhawar, Jitesh</style></author><author><style face="normal" font="default" size="100%">Sarkar, Ram Rup</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Dissecting leishmania infantum energy metabolism - a systems perspective</style></title><secondary-title><style face="normal" font="default" size="100%">Plos One</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year><pub-dates><date><style  face="normal" font="default" size="100%">SEP</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">9</style></number><publisher><style face="normal" font="default" size="100%">PUBLIC LIBRARY SCIENCE</style></publisher><pub-location><style face="normal" font="default" size="100%">1160 BATTERY STREET, STE 100, SAN FRANCISCO, CA 94111 USA</style></pub-location><volume><style face="normal" font="default" size="100%">10</style></volume><pages><style face="normal" font="default" size="100%">Article Number: e0137976</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Leishmania infantum, causative agent of visceral leishmaniasis in humans, illustrates a complex lifecycle pertaining to two extreme environments, namely, the gut of the sandfly vector and human macrophages. Leishmania is capable of dynamically adapting and tactically switching between these critically hostile situations. The possible metabolic routes ventured by the parasite to achieve this exceptional adaptation to its varying environments are still poorly understood. In this study, we present an extensively reconstructed energy metabolism network of Leishmania infantum as an attempt to identify certain strategic metabolic routes preferred by the parasite to optimize its survival in such dynamic environments. The reconstructed network consists of 142 genes encoding for enzymes performing 237 reactions distributed across five distinct model compartments. We annotated the subcellular locations of different enzymes and their reactions on the basis of strong literature evidence and sequence-based detection of cellular localization signal within a protein sequence. To explore the diverse features of parasite metabolism the metabolic network was implemented and analyzed as a constraint-based model. Using a systems-based approach, we also put forth an extensive set of lethal reaction knockouts; some of which were validated using published data on Leishmania species. Performing a robustness analysis, the model was rigorously validated and tested for the secretion of overflow metabolites specific to Leishmania under varying extracellular oxygen uptake rate. Further, the fate of important non-essential amino acids in L. infantum metabolism was investigated. Stage-specific scenarios of L. infantum energy metabolism were incorporated in the model and key metabolic differences were outlined. Analysis of the model revealed the essentiality of glucose uptake, succinate fermentation, glutamate biosynthesis and an active TCA cycle as driving forces for parasite energy metabolism and its optimal growth. Finally, through our in silico knockout analysis, we could identify possible therapeutic targets that provide experimentally testable hypotheses.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">9</style></issue><custom3><style face="normal" font="default" size="100%">&lt;p&gt;Foreign&lt;/p&gt;</style></custom3><custom4><style face="normal" font="default" size="100%">3.057</style></custom4></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Subramanian, Abhishek</style></author><author><style face="normal" font="default" size="100%">Sarkar, Ram Rup</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Dynamics of gli regulation and a strategy to control cancerous situation: hedgehog signaling pathway revisited</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Biological Systems</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">GLI Dynamics</style></keyword><keyword><style  face="normal" font="default" size="100%">Graded Response</style></keyword><keyword><style  face="normal" font="default" size="100%">Hedgehog Signaling Pathway</style></keyword><keyword><style  face="normal" font="default" size="100%">Ligand-Dependent and -Independent Pathway Activation</style></keyword><keyword><style  face="normal" font="default" size="100%">Ultrasensitive and Irreversible Switch</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2015</style></year><pub-dates><date><style  face="normal" font="default" size="100%">DEC</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">4</style></number><publisher><style face="normal" font="default" size="100%">WORLD SCIENTIFIC PUBL CO PTE LTD</style></publisher><pub-location><style face="normal" font="default" size="100%">5 TOH TUCK LINK, SINGAPORE 596224, SINGAPORE</style></pub-location><volume><style face="normal" font="default" size="100%">23</style></volume><pages><style face="normal" font="default" size="100%">681-719</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The hedgehog signaling cascade generates highly diverse, fine-tuned responses in response to the external stimulus by the sonic hedgehog (SHH) protein. This is required for the flawless functioning of the cell, its development, survival and proliferation; maintained through production of Glioma protein (GLI) and transcriptional activation of its target genes. Any change in the behavior of GLI response by ectopic expression of SHH or mutations in the core pathway components may cause serious consequences in the cell fate through rapid, uncontrolled and elevated production of GLI. Here, we present a simple but extensive computational model that considers the detailed reaction mechanisms involved in the hedgehog signal transduction and provides a detailed insight into regulation of GLI. For the first time, by explicit involvement of suppressor of fused (SUFU) and Hedgehog interacting protein (HHIP) reaction kinetics in the model, we try to demonstrate the vital importance of HHIP and SUFU in maintaining the graded response of GLI in response to SHH. By performing parameter variations, we capture the conversion of a graded response of GLI to an ultrasensitive switch under SUFU-deficient conditions that might predispose abnormal embryonic development and the irreversible switching response of GLI that corresponds to signal-independent pathway activation observed in cancers.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">4</style></issue><custom3><style face="normal" font="default" size="100%">&lt;p&gt;Foreign&lt;/p&gt;</style></custom3><custom4><style face="normal" font="default" size="100%">0.479</style></custom4></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Bhowmick, Rupa</style></author><author><style face="normal" font="default" size="100%">Subramanian, Abhishek</style></author><author><style face="normal" font="default" size="100%">Sarkar, Ram Rup</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Exploring the differences in metabolic behavior of astrocyte and glioblastoma: a flux balance analysis approach</style></title><secondary-title><style face="normal" font="default" size="100%">Systems and Synthetic Biology</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year><pub-dates><date><style  face="normal" font="default" size="100%">DEC</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">9</style></volume><pages><style face="normal" font="default" size="100%">159-177</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><issue><style face="normal" font="default" size="100%">4</style></issue><custom3><style face="normal" font="default" size="100%">&lt;p&gt;Foreign&lt;/p&gt;</style></custom3><custom4><style face="normal" font="default" size="100%">1.00</style></custom4></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Subramanian, Abhishek</style></author><author><style face="normal" font="default" size="100%">Singh, Vidhi</style></author><author><style face="normal" font="default" size="100%">Sarkar, Ram Rup</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Understanding visceral leishmaniasis disease transmission and its control - a study based on mathematical modelling</style></title><secondary-title><style face="normal" font="default" size="100%">Mathematics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year><pub-dates><date><style  face="normal" font="default" size="100%">SEP</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">3</style></volume><pages><style face="normal" font="default" size="100%">913-344</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><issue><style face="normal" font="default" size="100%">3</style></issue><custom3><style face="normal" font="default" size="100%">&lt;p&gt;Foreign&lt;/p&gt;</style></custom3><custom4><style face="normal" font="default" size="100%">0.446</style></custom4></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Subramanian, Abhishek</style></author><author><style face="normal" font="default" size="100%">Sarkar, Ram Rup</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Network structure and enzymatic evolution in Leishmania metabolism: a computational study</style></title><secondary-title><style face="normal" font="default" size="100%">Proceedings of the International Symposium on Mathematical and Computational Biology-BIOMAT 2015</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2016</style></year><pub-dates><date><style  face="normal" font="default" size="100%">JUN</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">World Scientific </style></publisher><pub-location><style face="normal" font="default" size="100%">Roorkee, Uttarakhand, India</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Banerjee, Swarnendu</style></author><author><style face="normal" font="default" size="100%">Subramanian, Abhishek</style></author><author><style face="normal" font="default" size="100%">Chattopadhyay, Joydev</style></author><author><style face="normal" font="default" size="100%">Sarkar, Ram Rup</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Exploring the role of GS-GOGAT cycle in microcystin synthesis and regulation - a model based analysis</style></title><secondary-title><style face="normal" font="default" size="100%">Molecular Biosystems</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2017</style></year><pub-dates><date><style  face="normal" font="default" size="100%">DEC</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">13</style></volume><pages><style face="normal" font="default" size="100%">2603-2614</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Toxic cyanobacteria blooms populate water bodies by consuming external nutrients and releasing cyanotoxins that are detrimental for other aquatic species, producing a significant impact on the plankton ecosystem and food web. To exercise population-level control of toxin production, understanding the biochemical mechanisms that explain cyanotoxin regulation within a bacterial cell is of utmost importance. In this study, we explore the mechanistic events to investigate the dependence of toxin microcystin on external nitrogen, a known regulator of the toxin, and for the first time, propose a kinetic model that analyzes the intracellular conditions required to ensure nitrogen dependence on microcystin. We hypothesize that the GS-GOGAT cycle is manipulated by variable influx of different intracellular metabolites that can either disturb or promote the balance between the enzyme microcystin synthetase and substrate glutamate to produce variable microcystin levels. As opposed to the popular notion that nitrogen starvation increases microcystin synthesis, our analyses suggest that under certain intracellular metabolite regimes, this relationship can either be completely lost or reversed. External nitrogen can only complement the conditions fixed by intracellular glutamate, glutamine and 2-oxoglutarate. This mechanistic understanding can provide an experimentally testable hypothesis for exploring the less-known biology of microcystin synthesis and designing specific interventions.</style></abstract><issue><style face="normal" font="default" size="100%">12</style></issue><work-type><style face="normal" font="default" size="100%">Article</style></work-type><custom3><style face="normal" font="default" size="100%">Foreign</style></custom3><custom4><style face="normal" font="default" size="100%">2.781</style></custom4></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Nandi, Sutanu</style></author><author><style face="normal" font="default" size="100%">Subramanian, Abhishek</style></author><author><style face="normal" font="default" size="100%">Sarkar, Ram Rup</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Integrative machine learning strategy for improved prediction of essential genes in Escherichia coli metabolism using flux-coupled features</style></title><secondary-title><style face="normal" font="default" size="100%">Molecular Biosystems</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2017</style></year><pub-dates><date><style  face="normal" font="default" size="100%">AUG</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">13</style></volume><pages><style face="normal" font="default" size="100%">1584-1596</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Prediction of essential genes helps to identify a minimal set of genes that are absolutely required for the appropriate functioning and survival of a cell. The available machine learning techniques for essential gene prediction have inherent problems, like imbalanced provision of training datasets, biased choice of the best model for a given balanced dataset, choice of a complex machine learning algorithm, and data-based automated selection of biologically relevant features for classification. Here, we propose a simple support vector machine-based learning strategy for the prediction of essential genes in Escherichia coli K-12 MG1655 metabolism that integrates a non-conventional combination of an appropriate sample balanced training set, a unique organism-specific genotype, phenotype attributes that characterize essential genes, and optimal parameters of the learning algorithm to generate the best machine learning model (the model with the highest accuracy among all the models trained for different sample training sets). For the first time, we also introduce flux-coupled metabolic subnetwork-based features for enhancing the classification performance. Our strategy proves to be superior as compared to previous SVM-based strategies in obtaining a biologically relevant classification of genes with high sensitivity and specificity. This methodology was also trained with datasets of other recent supervised classification techniques for essential gene classification and tested using reported test datasets. The testing accuracy was always high as compared to the known techniques, proving that our method outperforms known methods. Observations from our study indicate that essential genes are conserved among homologous bacterial species, demonstrate high codon usage bias, GC content and gene expression, and predominantly possess a tendency to form physiological flux modules in metabolism.</style></abstract><issue><style face="normal" font="default" size="100%">8</style></issue><work-type><style face="normal" font="default" size="100%">Article</style></work-type><custom3><style face="normal" font="default" size="100%">Foreign</style></custom3><custom4><style face="normal" font="default" size="100%">2.829</style></custom4></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Biswas, Santanu</style></author><author><style face="normal" font="default" size="100%">Subramanian, Abhishek</style></author><author><style face="normal" font="default" size="100%">Elmojtaba, Ibrahim M.</style></author><author><style face="normal" font="default" size="100%">Chattopadhyay, Joydev</style></author><author><style face="normal" font="default" size="100%">Sarkar, Ram Rup</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Optimal combinations of control strategies and cost-effective analysis for visceral leishmaniasis disease transmission</style></title><secondary-title><style face="normal" font="default" size="100%">PLoS ONE</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2017</style></year><pub-dates><date><style  face="normal" font="default" size="100%">MAR</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">12</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Visceral leishmaniasis (VL) is a deadly neglected tropical disease that poses a serious problem in various countries all over the world. Implementation of various intervention strategies fail in controlling the spread of this disease due to issues of parasite drug resistance and resistance of sandfly vectors to insecticide sprays. Due to this, policy makers need to develop novel strategies or resort to a combination of multiple intervention strategies to control the spread of the disease. To address this issue, we propose an extensive SIR-type model for anthroponotic visceral leishmaniasis transmission with seasonal fluctuations mod-eled in the form of periodic sandfly biting rate. Fitting the model for real data reported in South Sudan, we estimate the model parameters and compare the model predictions with known VL cases. Using optimal control theory, we study the effects of popular control strategies namely, drug-based treatment of symptomatic and PKDL-infected individuals, insecticide treated bednets and spray of insecticides on the dynamics of infected human and vector populations. We propose that the strategies remain ineffective in curbing the disease individually, as opposed to the use of optimal combinations of the mentioned strategies. Testing the model for different optimal combinations while considering periodic seasonal fluctuations, we find that the optimal combination of treatment of individuals and insecticide sprays perform well in controlling the disease for the time period of intervention introduced. Performing a cost-effective analysis we identify that the same strategy also proves to be effi-cacious and cost-effective. Finally, we suggest that our model would be helpful for policy makers to predict the best intervention strategies for specific time periods and their appropriate implementation for elimination of visceral leishmaniasis.</style></abstract><issue><style face="normal" font="default" size="100%">2</style></issue><custom3><style face="normal" font="default" size="100%">Foreign</style></custom3><custom4><style face="normal" font="default" size="100%">3.057</style></custom4></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Subramanian, Abhishek</style></author><author><style face="normal" font="default" size="100%">Sarkar, Ram Rup</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Revealing the mystery of metabolic adaptations using a genome scale model of Leishmania infantum</style></title><secondary-title><style face="normal" font="default" size="100%">Scientific Reports</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2017</style></year><pub-dates><date><style  face="normal" font="default" size="100%">AUG</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">7</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Human macrophage phagolysosome and sandfly midgut provide antagonistic ecological niches for Leishmania parasites to survive and proliferate. Parasites optimize their metabolism to utilize the available inadequate resources by adapting to those environments. Lately, a number of metabolomics studies have revived the interest to understand metabolic strategies utilized by the Leishmania parasite for optimal survival within its hosts. For the first time, we propose a reconstructed genome-scale metabolic model for Leishmania infantum JPCM5, the analyses of which not only captures observations reported by metabolomics studies in other Leishmania species but also divulges novel features of the L. infantum metabolome. Our results indicate that Leishmania metabolism is organized in such a way that the parasite can select appropriate alternatives to compensate for limited external substrates. A dynamic non-essential amino acid motif exists within the network that promotes a restricted redistribution of resources to yield required essential metabolites. Further, subcellular compartments regulate this metabolic re-routing by reinforcing the physiological coupling of specific reactions. This unique metabolic organization is robust against accidental errors and provides a wide array of choices for the parasite to achieve optimal survival.</style></abstract><issue><style face="normal" font="default" size="100%">Article Number: 10262</style></issue><work-type><style face="normal" font="default" size="100%">Article</style></work-type><custom3><style face="normal" font="default" size="100%">Foreign</style></custom3><custom4><style face="normal" font="default" size="100%">5.228</style></custom4></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Subramanian, Abhishek</style></author><author><style face="normal" font="default" size="100%">Sarkar, Ram Rup</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Evolutionary perspectives of genotype-phenotype factors in leishmania metabolism</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Molecular Evolution</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Codon usage</style></keyword><keyword><style  face="normal" font="default" size="100%">Evolutionary rate variation</style></keyword><keyword><style  face="normal" font="default" size="100%">Leishmania metabolism</style></keyword><keyword><style  face="normal" font="default" size="100%">Multi-functionality</style></keyword><keyword><style  face="normal" font="default" size="100%">Physiological fluxcoupling</style></keyword><keyword><style  face="normal" font="default" size="100%">Principal component regression (PCR)</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2018</style></year><pub-dates><date><style  face="normal" font="default" size="100%">AUG</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">86</style></volume><pages><style face="normal" font="default" size="100%">443-456</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;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.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">7</style></issue><work-type><style face="normal" font="default" size="100%">Article</style></work-type><custom3><style face="normal" font="default" size="100%">Foreign</style></custom3><custom4><style face="normal" font="default" size="100%">1.957</style></custom4></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Subramanian, Abhishek</style></author><author><style face="normal" font="default" size="100%">Sarkar, Ram Rup</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Perspectives on leishmania species and stage-specific adaptive mechanisms</style></title><secondary-title><style face="normal" font="default" size="100%">Trends In Parasitology</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2018</style></year><pub-dates><date><style  face="normal" font="default" size="100%">DEC</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">34</style></volume><pages><style face="normal" font="default" size="100%">10.1016/j.pt.2018.09.004</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The hurdles in drug and vaccine development pipelines for leishmaniasis, a complex, multifaceted disease, are largely due to the digenetic lifecycle, differential clinical manifestations of the parasite, and the incomplete understanding of its adaptations within its hosts. Here, we discuss the distinct computational and experimental techniques employed to identify the species and stage-specific adaptive mechanisms at different levels of biological organization, the progress made so far, and limitations in comprehending leishmaniasis as a systems biology disease. Based on the available perspectives, we also provide suggestions and requirements to tackle the growing challenges for bridging the genotype with the phenotype. A systems perspective can be instrumental in understanding the complexities of the disease and can provide insights for targeted control.</style></abstract><issue><style face="normal" font="default" size="100%">12</style></issue><work-type><style face="normal" font="default" size="100%">Article</style></work-type><custom3><style face="normal" font="default" size="100%">Foreign</style></custom3><custom4><style face="normal" font="default" size="100%">7.929</style></custom4></record></records></xml>