Identification and validation of putative biomarkers by in silico analysis, mRNA expression and oxidative stress indicators for negative energy balance in buffaloes during transition period.

OBJECTIVE: Transition period is considered from 3 weeks prepartum to 3 weeks postpartum, characterized with dramatic events (endocrine, metabolic, and physiological) leading to occurrence of production diseases (negative energy balance/ketosis, milk fever etc). The objectives of our study were to analyze the periodic concentration of serum beta-hydroxy butyric acid (BHBA), glucose and oxidative markers along with identification, and validation of the putative markers of negative energy balance in buffaloes using in-silico and quantitative real time-polymerase chain reaction (qRT-PCR) assay. METHODS: Out of 20 potential markers of ketosis identified by in-silico analysis, two were selected and analyzed by qRT-PCR technique (upregulated; acetyl serotonin o-methyl transferase like and down regulated; guanylate cyclase activator 1B). Additional two sets of genes (carnitine palmotyl transferase A; upregulated and Insulin growth factor; downregulated) that have a role of hepatic fatty acid oxidation to maintain energy demands via gluconeogenesis were also validated. Extracted cDNA (complementary deoxyribonucleic acid) from the blood of the buffaloes were used for validation of selected genes via qRTPCR. Concentrations of BHBA, glucose and oxidative stress markers were identified with their respective optimized protocols. RESULTS: The analysis of qRT-PCR gave similar trends as shown by in-silico analysis throughout the transition period. Significant changes (p<0.05) in the levels of BHBA, glucose and oxidative stress markers throughout this period were observed. This study provides validation from in-silico and qRT-PCR assays for potential markers to be used for earliest diagnosis of negative energy balance in buffaloes. CONCLUSION: Apart from conventional diagnostic methods, this study improves the understanding of putative biomarkers at the molecular level which helps to unfold their role in normal immune function, fat synthesis/metabolism and oxidative stress pathways. Therefore, provides an opportunity to discover more accurate and sensitive diagnostic aids.

Unveiling the anticancer mechanism of 1,2,3-triazole-incorporated thiazole-pyrimidine-isoxazoles: insights from docking and molecular dynamics simulations.

Cancer is a major global health concern, and the constant search for novel, selective anticancer compounds with low toxicity is never ending. Nitrogen heterocyclic compounds such as pyrimidine and triazole have been identified as potential candidates for cancer treatment. A novel series of 1,2,3-triazole incorporated thiazole-pyrimidine-isoxazole derivatives 10 (a-j) were designed, synthesized and evaluated for antitumorigenic activities against human breast cancer (MCF-7), human lung cancer (A549) and human prostate (PC3 & DU-145) various cell-lines by employing MTT assay using etoposide as the positive control. The synthesized hybrids yielded decent efficacy, which was further compared with the standard drug. Among all the molecules, 10h revealed the more potent anticancerous activities, having IC50 values ranging from 0.011 ± 0.0017 µM; 0.063 ± 0.0012 µM; 0.017 ± 0.0094 µM and 0.66 ± 0.072 µM with DU145, PC3, A549, and MCF7 cell-lines, respectively. Tubulin, being a major protein involved with diverse biological actions, also serves, as a crucial target for several clinically practiced anticancer drugs, was utilized for docking analyses to evaluate the binding affinity of ligands. Docking results demonstrates that the selected hybrids 10 (g-j) exhibited good binding affinities with protein. Subsequently, drug likeness studies were carried out on the synthesized compounds to evaluate and analyze their drug like properties such as absorption, distribution, metabolism, excretion, and toxicity (ADMET) for toxicity prediction. Based on these analyses, the selected complexes were further employed for molecular dynamic simulations to analyze stability via an exhaustive cumulative 200 nanoseconds simulation. These results suggest that the selected compounds are stable and might serve as potential inhibitors to tubulin complex. In conclusion, we propose these synthesized compounds 10 (g-j) might provide new insights into cancer treatment and have potential for future development.Communicated by Ramaswamy H. Sarma.

Multimodal Imaging of Pancreatic Cancer Microenvironment in Response to an Antiglycolytic Drug.

Lipid metabolism and glycolysis play crucial roles in the progression and metastasis of cancer, and the use of 3-bromopyruvate (3-BP) as an antiglycolytic agent has shown promise in killing pancreatic cancer cells. However, developing an effective strategy to avoid chemoresistance requires the ability to probe the interaction of cancer drugs with complex tumor-associated microenvironments (TAMs). Unfortunately, no robust and multiplexed molecular imaging technology is currently available to analyze TAMs. In this study, the simultaneous profiling of three protein biomarkers using SERS nanotags and antibody-functionalized nanoparticles in a syngeneic mouse model of pancreatic cancer (PC) is demonstrated. This allows for comprehensive information about biomarkers and TAM alterations before and after treatment. These multimodal imaging techniques include surface-enhanced Raman spectroscopy (SERS), immunohistochemistry (IHC), polarized light microscopy, second harmonic generation (SHG) microscopy, fluorescence lifetime imaging microscopy (FLIM), and untargeted liquid chromatography and mass spectrometry (LC-MS) analysis. The study reveals the efficacy of 3-BP in treating pancreatic cancer and identifies drug treatment-induced lipid species remodeling and associated pathways through bioinformatics analysis.

Analyzing the effect of heparin on in vitro capacitation and spermatozoal RNA population in goats.

Heparin is a glycosaminoglycan polymer that is commonly used as an anticoagulant. Heparin also induces in vitro capacitation in spermatozoa, although its molecular mechanism is elusive. This study investigated the effect of heparin on in vitro capacitation and spermatozoal RNA (spRNA) population in goats. Goat spermatozoa were treated with 20 µM heparin for 0-6 h and evaluated for motility, capacitation, acrosome reaction, and spRNA population by RNA sequencing (RNA-seq). It was observed that heparin enhanced sperm motility up to 6 h of incubation (p < 0.05). Heparin also induced capacitation and acrosome reaction within 4 h. RNA-seq identified 1254 differentially expressed genes (DEGs) between heparin-treated and control spermatozoa. Most DEGs (1251 nos.) were upregulated and included 1090 protein-coding genes. A few genes (PRND, ITPR1, LLCFC1, and CHRM2) showed >5-fold increased expression in heparin-treated spermatozoa compared to the control. The upregulated genes were found to be involved in cAMP-PKA, PI3-Akt, calcium, MAPK signaling, and oxidative stress pathways. DCFDA staining confirmed the increased oxidative stress in heparin-treated spermatozoa compared to the control (p < 0.05). In conclusion, the results of the present study suggest that heparin enhances sperm motility and induces capacitation by upregulation of the spRNA population and oxidative stress pathway.

Restoration of Altered Oncogenic and Tumor Suppressor microRNA Expression in Breast Cancer and Colorectal Cancer Cell using Epicatechin.

BACKGROUND: MicroRNAs (miRNA) are small non-coding RNAs that regulate the function of mRNA post-transcriptionally in a tissue-specific manner. miRNA expressions are heavily dysregulated in human cancer cells through various mechanisms, including epigenetic changes, karyotype abnormalities, and miRNA biogenesis defects. miRNAs may act as either oncogenes or tumor suppressors under different conditions. Epicatechin is a natural compound found in green tea which possesses antioxidant and antitumor properties. OBJECTIVE: The objective of this study is to investigate the effect of epicatechin treatment on the expression level of several oncogenic and tumor suppressor miRNAs in breast and colorectal cancer cell lines (MCF7 and HT-29) and identify its mechanism of action. METHODS: The MCF-7 and HT29 cells were treated with epicatechin for 24 hours and untreated cells were considered control cultures. miRNA was isolated and qRT-PCR was used to measure the expression profile changes of different oncogenic and tumor suppressor miRNAs. Furthermore, the mRNA expression profile was also screened at different concentrations of epicatechin. RESULTS: Our results showed several-fold changes in miRNAs expression level, which is cell line specific. Also, epicatechin at different concentrations induces biphasic changes in mRNA expression levels in both cell lines. CONCLUSION: Our findings first time demonstrated that epicatechin can reverse the expression of these miRNAs and may trigger the cytostatic effect at a lower concentration.

Prediction of potential molecular markers of bovine mastitis by meta-analysis of differentially expressed genes using combined p value and robust rank aggregation.

Bovine mastitis causes significant economic loss to the dairy industry by affecting milk quality and quantity. Escherichia coli and Staphylococcus aureus are the two common mastitis-causing bacteria among the consortia of mastitis pathogens, wherein E. coli is an opportunistic environmental pathogen, and S. aureus is a contagious pathogen. This study was designed to predict molecular markers of bovine mastitis by meta-analysis of differentially expressed genes (DEG) in E. coli- or S. aureus-infected mammary epithelial cells (MECs) using p value combination and robust rank aggregation (RRA) methods. High-throughput transcriptome of bovine MECs, infected with E. coli or S. aureus, were analyzed, and correlation of z-scores were computed for the expression datasets to identify the lineage profile and functional ontology of DEGs. Key pathways enriched in infected MECs were deciphered by Gene Set Enrichment Analysis (GSEA), following which combined p value and RRA were used to perform DEG meta-analysis to limit type I error in the analysis. The miRNA-gene networks were then built to uncover potential molecular markers of mastitis. Lineage profiling of MECs showed that the gene expression levels were associated with mammary tissue lineage. The up-regulated genes were enriched in immune-related pathways, whereas down-regulated genes influenced the cellular processes. GSEA analysis of DEGs deciphered the involvement of Toll-like receptor (TLR), and NF-kappa B signaling pathway during infection. Comparison after meta-analysis yielded with genes ZC3H12A, RND1, and MAP3K8 having significant expression levels in both E. coli and S. aureus dataset, and on evaluating miRNA-gene network, 7 pairs were common to both sets identifying them as potential molecular markers.

Molecular modeling, docking and dynamic simulations of growth hormone receptor (GHR) of Labeo rohita.

Growth hormones (GH) have diverse functions like growth promotion, metabolism, appetite, reproduction and social behavior in vertebrates, which is mediated through the growth hormone receptor (GHR). This work was aimed to analyze structural features, homology modeling and molecular docking of Labeo rohita GHR protein. A physicochemical characteristic, like molecular weight was 67.2 kDa and hydropathicity was 0.336. Protein modeling and structure confirmation of L. rohita GHR protein showed 92.7% residues are in the favored region. Selection of ligands and molecular docking shown Melengestrol and Riboflavin ligand showed uppermost binding energy values -7.8 and -7.3 kcal/mol. Molecular interactions describe conventional hydrogen bonding of Melengestrol was observed with VAL94, GLU97, GLU95, TRP57, PHE33, THR34, PRO35, ASP36, PRO37, ARG49, GLY292, LYS291, ILE290, ALA287, LYS289 residues. Riboflavin hydrogen bonds interaction was at PRO37, ASP36, PRO35, THR34, ARG49, SER144, VAL443, GLN442, PRO284, ASP294, ILE285, PRO286, SER408, ALA287, GLY292, LYS291, ILE290, PRO288, LYS287. Molecular dynamics simulation outcomes revealed that complex 2 (Riboflavin and GHR protein) is better than complex1 (Melengestrol and GHR protein). Overall, the results of the present work lead identification of novel molecules that may be agonistic of growth hormone receptor protein and can be used to surge growth in fish. Communicated by Ramaswamy H. Sarma.

Analysis of Overexpressed miRNA in Circulation and Cancer Tissue to Develop a Potential microRNA Panel for the Diagnosis of Colorectal Cancer.

BACKGROUND: Colorectal cancer (CRC) represents the world's fourth deadly cancer, but its early diagnosis can be curative with considerable success rates. This study was aimed to identify CRC-specific microRNAs (miRNAs) in tissue and serum samples to develop a miRNA-based diagnostics panel for the minimal invasive detection of CRC in early conditions. METHODS: By integrating four microarrays in tissue and serum samples of CRC from the Gene Expression Omnibus (GEO) database, we screened out the highly expressed miRNAs in each dataset using the limma R package. Two important upregulated miRNAs, namely hsa-miR-1246 and hsamiR- 1825, were overlapped in both tissue and serum samples of CRC and were investigated to target identification, followed by functional annotation and protein-protein interaction (PPI) study for the target genes through DAVID and STRING, respectively. Finally, hub target genes were retrieved by Cytoscape analysis. RESULTS: It was shown that target genes of hsa-miR-1246 and hsa-miR-1825 were involved with core KEGG pathways (such as cAMP, PI3K-Akt, and calcium signaling pathway). In addition, biological processes (such as cell adhesion and cell proliferation), cellular components (such as plasma membrane and cytosol), molecular functions (such as protein binding and metal ion binding) were mostly associated with the target genes. Their top 5 target genes were retrieved, and their biological function towards tumor progression was shown using Cancer Hallmarks Analytics Tool. CONCLUSION: This study suggested that hsa-miR-1246 and hsa-miR-1825, as overlapped upregulated tissue and circulating miRNAs, might have a vital role in the development of CRC, and their five hub target genes were identified.

Prediction and Boolean logical modelling of synergistic microRNA regulatory networks during reprogramming of male germline pluripotent stem cells.

Unipotent male germline stem (GS) cells can undergo spontaneous reprogramming to germline pluripotent stem (GPS) cells during in vitro culture. In our previous study, we proposed a Boolean logical model of gene regulatory network (GRN) during reprogramming of GS cells to GPS cells. This study was designed to predict and model synergistic microRNA (miRNA) regulatory network during reprogramming of GS cells into GPS cells. The miRNAs targeting differentially expressed genes (DEGs) among GS and GPS cells were predicted by a novel Gene Ontology (GO) enrichment analysis to construct miRNA synergistic networks (MSN) and identify regulatory miRNA modules. Qualitative Boolean logical model of synergistic miRNAs and its regulated genes was then constructed by considering discrete, asynchronous, multivalued logical formalism using the GINsim modeling and simulation tools. Topology, functional and community overlap studies revealed that mmu-miR-200b-3p, mmu-miR-429-3p and mmu-miR-141-3p, mmu-miR-200a-3p and mmu-miR-200c-3p in MSN belongs to the family of miR-200/429/141 and conjectured to control the pluripotency and reprogramming by promoting Mesenchymal to Epithelial Transition (MET). Synergistic network involving mmu-miR-20b-5p, mmu-miR-20a-5p, mmu-miR-106a-5p, mmu-miR-106b-5p, and mmu-miR-17-5p were found to be essential for the maintenance of GS cells. Logical miRNA regulatory network modelling showed that synergistic miRNAs regulates the gene dynamics of MET during GS-GPS reprogramming, as confirmed by perturbation analysis. Taken together, our study predicted novel synergistic miRNAs involved in the regulation of reprogramming and pluripotency in GPS cells. The Boolean logical model of synergistic miRNAs regulatory network further confirms our previous study that gene dynamics of MET regulates GS-GPS reprogramming.

Molecular modeling and co-expression analysis of human stem cell factor as fusion partner to granulocyte colony stimulating factor for improving their bioactivity.

Human granulocyte colony stimulating factor (hG-CSF) is an expensive hematopoietic growth factor that is clinically used in human for the treatment of neutropenia in diseases such as AIDS, aplastic anemia, myelodysplastic syndrome and congenital or chemotherapy-induced neutropenia. Here, through a computational biology approach, we show that human stem cell factor (hSCF) could be a better fusion partner than human thyroid peroxidase (hTPO), human erythropoietin (hEPO) and human interleukin-3 (hIL3) for co-expression with hG-CSF. Molecular modeling of hG-CSF-hSCF fusion protein with hG-CSF and hSCF receptors showed that binding of fusion protein with human granulocyte colony stimulating factor receptor (hG-CSFR) did not inhibit its binding to human stem cell factor receptor (hSCFR) and vice versa. To validate the results, coding sequences of hG-CSF and hSCF were cloned and co-expressed as fusion protein and their bioactivity was evaluated on hG-CSF responsive 3T3 cell line. The fused expression vector expressed recombinant hG-CSF-hSCF upon IPTG-induction, as revealed by real-time polymerase chain reaction (RT-PCR), sodium dodecyl sulphate-polyacrylamide gel electrophoresis (SDS-PAGE) and Western blot analysis. Bioactivity analysis confirmed that rhG-CSF-hSCF protein had higher bioactivity than hG-CSF. Thus, hSCF could be a good fusion partner for hG-CSF and its co-expression as hG-CSF-hSCF may offer an alternative to individual use of two hematopoietic factors in clinics. Future studies should determine the purification strategies, folding status and mechanism of action of the recombinant proteins. Communicated by Ramaswamy H. Sarma.

Comparison of spermatozoal RNA extraction methods in goats.

RNA sequencing (RNAseq) has divulged newer role of spermatozoal RNA in male fertility. This study aimed to evaluate different sperm purification and RNA extraction methods for long-read RNA sequencing of poly(A) transcriptome in goat spermatozoa. Sperm samples were purified by swim-up separation using different purification medium. Spermatozoal RNA was extracted by seven different methods with additional supplementation of reducing agents in lysis buffer. poly(A) selected RNA was used for cDNA library preparation and long-read RNAseq in Nanopore sequencer. Sperm purification by 1 h swim-up resulted in higher recovery (89.20 ± 1.15%), motility (82.33 ± 1.53%), viability (88.10 ± 5.03%) and plasma membrane integrity (71.33 ± 4.51%) in sperm TALP (sp-TL) medium. A monophasic solution of GITC with phenol and DTT resulted in the highest yield of large sized RNAs (3.89 ± 0.46 ng/million cells) suitable for long-read RNAseq of poly(A) transcripts. RNAseq resulted in reads of length, ranging from 500bp to 2 Kb. A total of 123 transcripts were identified in goat spermatozoa by de novo assembly and included sperm-specific transcripts such as CATSPERG, PRM2, CYLC2, SPATA6, PLCZ1 etc. This study is the first report of long-read RNAseq of poly(A) transcriptome in goat spermatozoa.

A Boolean Logical model for Reprogramming of Testes-derived male Germline Stem Cells into Germline pluripotent stem cells.

BACKGROUND AND OBJECTIVE: Male germline stem (GS) cells are responsible for the maintenance of spermatogenesis throughout the adult life of males. Upon appropriate in vitro culture conditions, these GS cells can undergo reprogramming to become germline pluripotent stem (GPS) cells with the loss of spermatogenic potential. In recent years, voluminous data of gene transcripts in GS and GPS cells have become available. However, the mechanism of reprogramming of GS cells into GPS cells remains elusive. This study was designed to develop a Boolean logical model of gene regulatory network (GRN) that might be involved in the reprogramming of GS cells into GPS cells. METHODS: The gene expression profile of GS and GPS cells (GSE ID: GSE11274 and GSE74151) were analyzed using R Bioconductor to identify differentially expressed genes (DEGs) and were functionally annotated with DAVID server. Potential pluripotent genes among the DEGs were then predicted using a combination of machine learning [Support Vector Machine (SVM)] and BLAST search. Protein isoforms were identified by pattern matching with UniProt database with in-house scripts written in C++. Both linear and non-linear interaction maps were generated using the STRING server. CellNet is used to study the relationship of GRNs between the GS and GPS cells. Finally, the GRNs involving all the genes from integrated methods and literature was constructed and qualitative modelling for reprogramming of GS to GPS cells were done by considering the discrete, asynchronous, multivalued logical formalism using the GINsim modeling and simulation tool. RESULTS: Through the use of machine learning and logical modeling, the present study identified 3585 DEGs and 221 novel pluripotent genes including Tet1, Cdh1, Tfap2c, Etv4, Etv5, Prdm14, and Prdm10 in GPS cells. Pathway analysis revealed that important signaling pathways such as core pluripotency network, PI3K-Akt, WNT, GDNF and BMP4 signalling pathways were important for the reprogramming of GS cells to GPS cells. On the other hand, CellNet analysis of GRNs of GS and GPS cells revealed that GS cells were similar to gonads whereas GPS cells were similar to ESCs in gene expression profile. A logical regulatory model was developed, which showed that TGFß negatively regulated the reprogramming of the GS to GPS cells, as confirmed by perturbations studies. CONCLUSION: The study identified novel pluripotent genes involved in the reprogramming of GS cells into GPS cells. A multivalued logical model of cellular reprogramming is proposed, which suggests that reprogramming of GS cells to GPS cells involves signalling pathways namely LIF, GDNF, BMP4, and TGFß along with some novel pluripotency genes.

Examining the co-expression, transcriptome clustering and variation using fuzzy cluster network of testicular stem cells and pluripotent stem cells compared with other cell types.

Stem cells are crucial in the field of tissue regeneration and developmental biology. Embryonic stem cells (ESCs) which are pluripotent in nature are derived from the inner cell mass of blastocyst. The gene expression profiles of ESCs and Induced pluripotent stem cells (iPSCs) were compared to identify the differences. Spermatogonial stem cells (SSCs) are also known as Germ-line stem cells (GSCs) present in testis is having the capability of producing the sperm in their whole lifetime. Therefore can be reprogrammed into pluripotent cells called male germline pluripotent cells (gPSCs). It is very difficult to interpret the larger genomic data sets which are available in public databases without high computational facilities. In order to identify the similar groups We studied the co-expression, clustering of the transcriptome and variation of the transcriptome of the GSCs, gPSCs, ESCs and other cell types using fuzzy clustering using AutoSOME. The series matrix file with GSE ID GSE11274 was retrieved and subjected to the various normalization methods, corresponding rows and columns were clustered using p values, ensemble runs, and different running modes. Transcriptome analysis using the proposed approach intuitively and consistently characterized the variation in cell-cell significantly. Collectively, our results suggest that the GSCs and the ESCs displayed differential gene expression profiles, and the GSCs possessed the potential to acquire pluripotency based on the high expression of epigenetic factors and transcription factors. These data may provide novel insights into the reprogramming mechanism of GSCs.

Structural analysis, molecular docking and molecular dynamics simulations of G-protein-coupled receptor (kisspeptin) in fish.

Kisspeptins are neuropeptide that has emerged as an essential gatekeeper for reproduction and onset of puberty in higher vertebrates including fish. In present study, structural analysis, molecular docking and molecular dynamics simulations of kisspeptin receptor (kiss2r) were carried out, which is a G-protein-coupled receptor. An open reading frame of kiss2r is 1101 bp encoding a putative protein of 366 amino acids. Secondary structure protein consists of alpha helix 69.70%, beta-turn 2%, disordered 18% and 43% transmembrane helix. Sub-cellular localization and gene ontology revealed kiss2r protein is maximum localized in the plasma membrane (99.1%) with score of 4.958 and gene ontology analysis showed molecular function of 89.8%, biological process 30.6% and cellular component 41.2%. Homology modeling and structure validation of kiss2r confirm 97.5% residues are in the favored region and 2.5% residues are in the allowed region. Virtual screening of ligands and molecular docking revealed 2-(4-(2-Carboxyethyl) phenethylamino) 5'-N-ethylcarboxamidoadenosine and N-ethyl-5'-carboxamido adenosine ligand exhibited highest binding energy values 9.437 and 7.476 kcal/mol. Molecular interactions depict conventional hydrogen bonding with GLU197 THR198 GLN288 HIS297 LYS303 and TYR313 residues. Molecular dynamic simulation results revealed that complex 2 (N-ethyl-5'-carboxamido adenosine and kiss2r protein) is better than complex 1 (2-(4-(2-Carboxyethyl) phenethylamino)-5'-N-ethylcarboxamidoadenosine and kiss2r protein) and its connotation in drug designing. The outcome of this work sheds light on the protein modeling, molecular docking and virtual screening of agonist ligands against kiss2 and thus may significantly contribute in designing and optimizing therapeutic strategies to cure various reproductive dysfunctions in fish. Abbreviations3-Dthree-dimensionala.aAmino acidBLASTBasic local alignment search toolAMBERAssisted Model Building with Energy RefinementCDScoding sequenceCIDCompound identification numberDOPEDiscrete optimized protein energyGnRHGonadotropin-releasing hormoneGPR54G protein-coupled receptor 54GROMACSGroningen Machine for Chemicals SimulationsGUIGraphical user interfaceHPGHypothalamic-pituitary-gonadalKiss1rkisspeptin1 receptorkiss2rkisspeptin2 receptorMEGAMolecular Evolutionary Genetics Analysis.MDMolecular dynamicsNCBINational Center for Biotechnology InformationORFOpen reading framePDBProtein Data BankRMSDRoot-mean-square deviationSBDDStructure-based drug designingTMDsTransmembrane domainsYASARAYet Another Scientific Artificial Reality ApplicationCommunicated by Ramaswamy H. Sarma.

Pharmacophore modeling coupled with scaffold hopping to identify novel and potent ribosomal S6 kinase (RSK2) protein antagonists as anti-cancer agents.

Communicated by Ramaswamy H. Sarma.

Screening and insilico analysis of deleterious nsSNPs (missense) in human CSF3 for their effects on protein structure, stability and function.

Human granulocyte colony stimulating factor (hG-CSF), known as CSF3, plays an important role in the growth, differentiation, proliferation, survival, and activation of the granulocyte cell lineage such as neutrophils and their precursors. Functional reduction in native CSF3 protein results in reduced proliferation and activation of neutrophils and leads to neutropenia. Single nucleotide polymorphisms (SNPs) in the CSF3 gene may have deleterious effects on the CSF3 protein function. This study was undertaken to find the functional SNPs in the human CSF3 gene. Results suggest that 18.9% of all the SNPs in the dbSNP database for CSF3 gene were present in the coding region. Out of 59 non-synonymous SNPs (nsSNPs), 26 nsSNPs were predicted to be non-tolerable by SIFT whereas 18 and 7 nsSNPs were predicted as probably damaging and possibly damaging, respectively by PolyPhen. Among this 31 nsSNPs, 16 nsSNPs were identified to be potentially deleterious by PANTHER server, and 4 nsSNPs were found to be neutral by PROVEAN. SNPAnalyzer predicted 7 nsSNPs to be neutral phenotype and the remaining 24 nsSNPs to be associated with diseases. Among the predicted nsSNPs, rs144408123, rs144408123, rs145136406, rs145311241, rs373191696, rs762945096, rs763688260, rs767572172, rs775326370, rs777777864, rs777983866, rs781596455, rs139072004, rs757612684, rs772911210, rs139072004, rs746634544, rs749993200, rs763426127, rs772466210 were identified as deleterious and potentially damaging. I-Mutant analysis revealed that th 20 nsSNPs were important for protein stability of CSF3. Therefore, th 20 nsSNPs may be used for the wider population-based genetic studies and also should be taken into account while engineering the recombinant CSF3 protein for clinical use.

Elucidating the Role of Val-Asn 95 and Arg-Gly 52 Mutations on Structure and Stability of Fibroblast Growth Factor Homologous Factor 2.

BACKGROUND: Fibroblast growth Factor Homologous Factors (FHFs) belong to a subclass of Fibroblast Growth Factor (FGF) family owing to their high sequence and structural similarities with FGFs. However, despite these similarities, there are properties which set them apart from FGFs. FHFs lack the secretion signal sequence unlike other FGF members, except FGF1 and 2. Unlike FGFs, FHFs are not able to bind to FGF Receptors (FGFRs) and instead have been implicated in binding to Voltage-Gated Sodium Channels (VGSCs), neuronal MAP kinase scaffold protein and islet-brain-2 (IB2). The two amino acids Arg-52 and Val95 are conserved in all FHFs and mutation of these residues lead to its inability to bind with VGSC/IB2. However, it is not clear whether the loss of binding is due to destabilization of the protein on mutation or due to involvement of Arg52 and Val95 in conferring functionality to FHFs. OBJECTIVE: In the present study, we have mutated these two conserved residues of FHF2 with its corresponding FGF counterpart amino acids and studied the effects of the mutations on the structure and stability of the protein. METHODS: Several biophysical methods like isothermal equilibrium denaturation study, ANS fluorescence, intrinsic fluorescence, acrylamide quenching, circular dichroism studies as well as using computational approaches were employed. RESULTS: The single mutations were found to affect the overall stability, conformation and functionality of the protein. CONCLUSION: Thus, the studies throw light on the role of specific amino acids in deciding the stability, structure and functionality of proteins and will be useful for development of therapeutically engineered proteins.

Prediction of novel pluripotent proteins involved in reprogramming of male Germline stem cells (GSCs) into multipotent adult Germline stem cells (maGSCs) by network analysis.

Germline stem cells (GSCs) are known to transmit genetic information from parents to offspring. These GSCs can undergo reprogramming to transform themselves into pluripotent stem cells, called as Multipotent adult Germline stem cells (maGSCs). The mechanism of the reprogramming of GSCs to maGSCs is elusive. To investigate novel factors that may govern the process of reprogramming, the RNA-seq data of both GSCs and maGSCs were retrieved and subjected to Tuxedo protocol using Galaxy server. Total 1558 differentially expressed genes were identified from the analysis. Protein sequence in the FASTA format of all 1558 differentially expressed genes was retrieved and submitted to Pluripred web server to predict whether the proteins were pluripotent or not. A total of 232 proteins were predicted as pluripotent, and to identify the novel proteins, these were submitted to STRING database to obtain an interaction map. The obtained interaction map was submitted to Cytoscape, and various apps such as MCODE and Centiscape were used to identify the clusters and centrality measures between the nodes of the generated network. Five clusters were identified and ranked according to their score. Novel pluripotent proteins like cadherin related cdh5, cdh10 were predicted. Phox2b, Nrp2, Dll1, Shh, Gbx2, Nodal, Lefty1, Wnt7b, Pitx2, fgf4, Pou5f1, Nanog, Tet1, trim8, alx2, Dppa2, Prdm14,Sox11, Esrrb were predicted to be involved in the stem cell development. Dppa2, Sox11, Sox2, Bmp4, Shh, and Otp were predicted to be involved in positive regulation of the stem cell proliferation. Pathway analysis further revealed that signaling pathways such as Wnt, Jak-Stat and PI3K may play important role in the pluripotency of the maGSCs. Novel proteins involved in pluripotency, which were predicted by our findings, can be experimentally researched in future.

Structure based annotation of Helicobacter pylori strain 26695 proteome.

The availability of complete genome sequences of H. pylori 26695 has provided a wealth of information enabling us to carry out in silico studies to identify new molecular targets for pharmaceutical treatment. In order to construe the structural and functional information of complete proteome, use of computational methods are more relevant since these methods are reliable and provide a solution to the time consuming and expensive experimental methods. Out of 1590 predicted protein coding genes in H. pylori, experimentally determined structures are available for only 145 proteins in the PDB. In the absence of experimental structures, computational studies on the three dimensional (3D) structural organization would help in deciphering the protein fold, structure and active site. Functional annotation of each protein was carried out based on structural fold and binding site based ligand association. Most of these proteins are uncharacterized in this proteome and through our annotation pipeline we were able to annotate most of them. We could assign structural folds to 464 uncharacterized proteins from an initial list of 557 sequences. Of the 1195 known structural folds present in the SCOP database, 411 (34% of all known folds) are observed in the whole H. pylori 26695 proteome, with greater inclination for domains belonging to α/ß class (36.63%). Top folds include P-loop containing nucleoside triphosphate hydrolases (22.6%), TIM barrel (16.7%), transmembrane helix hairpin (16.05%), alpha-alpha superhelix (11.1%) and S-adenosyl-L-methionine-dependent methyltransferases (10.7%).