02095nas a2200241   4500008004100000022001400041245016200055210006900217260009500286300001200381490000800393520114900401653002001550653002101570653002101591653001501612653001301627653001901640653002401659100002601683700002101709856012301730       2015                        eng d  a0888-754300aComparison of codon usage bias across leishmania and trypanosomatids to understand mRNA secondary structure, relative protein abundance and pathway functions0 aComparison of codon usage bias across leishmania and trypanosoma  a525 B ST, STE 1900, SAN DIEGO, CA 92101-4495 USAbACADEMIC PRESS INC ELSEVIER SCIENCEcOCT  a232-2410 v1063 a<p>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.</p>10aAmino acid bias10aBase composition10aCodon usage bias10aLeishmania10aMutation10aSelection bias10aSpecies specificity1 aSubramanian, Abhishek1 aSarkar, Ram, Rup  uhttps://library.ncl.res.in/content/comparison-codon-usage-bias-across-leishmania-and-trypanosomatids-understand-mrna-001374nas a2200145   4500008004100000245010200041210006900143260000800212300001200220490000600232520081500238100002601053700002101079856012801100       2015                        eng d00aData in support of large scale comparative codon usage analysis in leishmania and trypanosomatids0 aData in support of large scale comparative codon usage analysis   cJUN  a269-2720 v43 a<p>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.</p>1 aSubramanian, Abhishek1 aSarkar, Ram, Rup  uhttps://library.ncl.res.in/content/data-support-large-scale-comparative-codon-usage-analysis-leishmania-and-trypanosomatids02853nas a2200169   4500008004100000022001400041245007700055210006900132260009100201300002900292490000700321520217900328100002602507700001902533700002102552856011002573       2015                        eng d  a1932-620300aDissecting leishmania infantum energy metabolism - a systems perspective0 aDissecting leishmania infantum energy metabolism a systems persp  a1160 BATTERY STREET, STE 100, SAN FRANCISCO, CA 94111 USAbPUBLIC LIBRARY SCIENCEcSEP  aArticle Number: e01379760 v103 a<p>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.</p>1 aSubramanian, Abhishek1 aJhawar, Jitesh1 aSarkar, Ram, Rup  uhttps://library.ncl.res.in/content/dissecting-leishmania-infantum-energy-metabolism-systems-perspective-102307nas a2200217   4500008004100000022001400041245011500055210006900170260008800239300001200327490000700339520140300346653001701749653002001766653003101786653005701817653004301874100002601917700002101943856012501964       2015                        eng d  a0218-339000aDynamics of gli regulation and a strategy to control cancerous situation: hedgehog signaling pathway revisited0 aDynamics of gli regulation and a strategy to control cancerous s  a5 TOH TUCK LINK, SINGAPORE 596224, SINGAPOREbWORLD SCIENTIFIC PUBL CO PTE LTDcDEC  a681-7190 v233 a<p>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.</p>10aGLI Dynamics10aGraded Response10aHedgehog Signaling Pathway10aLigand-Dependent and -Independent Pathway Activation10aUltrasensitive and Irreversible Switch1 aSubramanian, Abhishek1 aSarkar, Ram, Rup  uhttps://library.ncl.res.in/content/dynamics-gli-regulation-and-strategy-control-cancerous-situation-hedgehog-signaling-000593nas a2200145   4500008004100000245011600041210006900157260000800226300001200234490000600246100001900252700002600271700002100297856012900318       2015                        eng d00aExploring the differences in metabolic behavior of astrocyte and glioblastoma: a flux balance analysis approach0 aExploring the differences in metabolic behavior of astrocyte and  cDEC  a159-1770 v91 aBhowmick, Rupa1 aSubramanian, Abhishek1 aSarkar, Ram, Rup  uhttps://library.ncl.res.in/content/exploring-differences-metabolic-behavior-astrocyte-and-glioblastoma-flux-balance-analysis00591nas a2200145   4500008004100000245012000041210006900161260000800230300001200238490000600250100002600256700001700282700002100299856012500320       2015                        eng d00aUnderstanding visceral leishmaniasis disease transmission and its control - a study based on mathematical modelling0 aUnderstanding visceral leishmaniasis disease transmission and it  cSEP  a913-3440 v31 aSubramanian, Abhishek1 aSingh, Vidhi1 aSarkar, Ram, Rup  uhttps://library.ncl.res.in/content/understanding-visceral-leishmaniasis-disease-transmission-and-its-control-study-based00540nas a2200109   4500008004100000245009400041210006900135260005600204100002600260700002100286856012300307       2016                        eng d00aNetwork structure and enzymatic evolution in Leishmania metabolism: a computational study0 aNetwork structure and enzymatic evolution in Leishmania metaboli  aRoorkee, Uttarakhand, IndiabWorld Scientific cJUN1 aSubramanian, Abhishek1 aSarkar, Ram, Rup  uhttps://library.ncl.res.in/content/network-structure-and-enzymatic-evolution-leishmania-metabolism-computational-study02141nas a2200169   4500008004100000245010600041210006900147260000800216300001400224490000700238520150200245100002401747700002601771700002601797700002101823856012701844       2017                        eng d00aExploring the role of GS-GOGAT cycle in microcystin synthesis and regulation - a model based analysis0 aExploring the role of GSGOGAT cycle in microcystin synthesis and  cDEC  a2603-26140 v133 aToxic 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.1 aBanerjee, Swarnendu1 aSubramanian, Abhishek1 aChattopadhyay, Joydev1 aSarkar, Ram, Rup  uhttps://library.ncl.res.in/content/exploring-role-gs-gogat-cycle-microcystin-synthesis-and-regulation-model-based-analysis02553nas a2200157   4500008004100000245014400041210006900185260000800254300001400262490000700276520191700283100001802200700002602218700002102244856013002265       2017                        eng d00aIntegrative machine learning strategy for improved prediction of essential genes in Escherichia coli metabolism using flux-coupled features0 aIntegrative machine learning strategy for improved prediction of  cAUG  a1584-15960 v133 aPrediction 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.1 aNandi, Sutanu1 aSubramanian, Abhishek1 aSarkar, Ram, Rup  uhttps://library.ncl.res.in/content/integrative-machine-learning-strategy-improved-prediction-essential-genes-escherichia-coli02560nas a2200169   4500008004100000245012300041210006900164260000800233490000700241520189200248100002002140700002602160700002702186700002602213700002102239856013002260       2017                        eng d00aOptimal combinations of control strategies and cost-effective analysis for visceral leishmaniasis disease transmission0 aOptimal combinations of control strategies and costeffective ana  cMAR0 v123 aVisceral 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.1 aBiswas, Santanu1 aSubramanian, Abhishek1 aElmojtaba, Ibrahim, M.1 aChattopadhyay, Joydev1 aSarkar, Ram, Rup  uhttps://library.ncl.res.in/content/optimal-combinations-control-strategies-and-cost-effective-analysis-visceral-leishmaniasis01882nas a2200133   4500008004100000245010100041210006900142260000800211490000600219520135200225100002601577700002101603856012401624       2017                        eng d00aRevealing the mystery of metabolic adaptations using a genome scale model of Leishmania infantum0 aRevealing the mystery of metabolic adaptations using a genome sc  cAUG0 v73 aHuman 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.1 aSubramanian, Abhishek1 aSarkar, Ram, Rup  uhttps://library.ncl.res.in/content/revealing-mystery-metabolic-adaptations-using-genome-scale-model-leishmania-infantum02719nas a2200229   4500008004100000022001400041245008500055210006900140260000800209300001200217490000700229520192200236653001602158653003202174653002602206653002402232653003102256653004102287100002602328700002102354856011402375       2018                        eng d  a0022-284400aEvolutionary perspectives of genotype-phenotype factors in leishmania metabolism0 aEvolutionary perspectives of genotypephenotype factors in leishm  cAUG  a443-4560 v863 a<p>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.</p>10aCodon usage10aEvolutionary rate variation10aLeishmania metabolism10aMulti-functionality10aPhysiological fluxcoupling10aPrincipal component regression (PCR)1 aSubramanian, Abhishek1 aSarkar, Ram, Rup  uhttps://library.ncl.res.in/content/evolutionary-perspectives-genotype-phenotype-factors-leishmania-metabolism01435nas a2200157   4500008004100000022001600041245007800057210006900135260000800204300002900212490000700241520087200248100002601120700002101146856011001167       2018                        eng d  a 1471-4922 00aPerspectives on leishmania species and stage-specific adaptive mechanisms0 aPerspectives on leishmania species and stagespecific adaptive me  cDEC  a10.1016/j.pt.2018.09.0040 v343 aThe 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.1 aSubramanian, Abhishek1 aSarkar, Ram, Rup  uhttps://library.ncl.res.in/content/perspectives-leishmania-species-and-stage-specific-adaptive-mechanisms