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The associated publication reports proteogenomic analysis of human pancreatic ductal adenocarcinoma (PDAC), where we provided significantly mutated genes (SMGs)/biomarkers, cellular pathways, and cell types as potential therapeutic targets to improve stratification of patients with PDAC. This protocol describes the detailed methods for whole exome sequencing (WES) and RNA sequencing analyses of PDAC samples, including tissue processing for proteogenomic analysis, DNA and RNA extraction, experimental procedures for WES and RNA sequencing, and WES and RNA sequencing data analyses.

The associated publication reports proteogenomic analysis of human pancreatic ductal adenocarcinoma (PDAC), where we provided significantly mutated genes (SMGs)/biomarkers, cellular pathways, and cell types as potential therapeutic targets to improve stratification of patients with PDAC. This protocol describes the detailed methods for mass spectrometry-based proteomic analysis of PDAC samples, including sample preparation, liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis, and data analyses (peptide/protein identification and quantitation).

The associated publication reports proteogenomic analysis of human pancreatic ductal adenocarcinoma (PDAC), where we provided significantly mutated genes (SMGs)/biomarkers, cellular pathways, and cell types as potential therapeutic targets to improve stratification of patients with PDAC. This protocol describes the detailed methods for cell-based assays for potential prognostic biomarkers in PDAC, including cell culture, viral transduction, and cell-based assays.

The associated publication reports proteogenomic analysis of human pancreatic ductal adenocarcinoma (PDAC), where we provided significantly mutated genes (SMGs)/biomarkers, cellular pathways, and cell types as potential therapeutic targets to improve stratification of patients with PDAC. This protocol describes the detailed methods for assays for orthotopic PDAC mouse models, including mouse tumour tissue processing, ultrasound imaging, Masson-trichrome staining, and IHC analysis for immune cell markers.

The associated publication reports proteogenomic analysis of human pancreatic ductal adenocarcinoma (PDAC), where we provided significantly mutated genes (SMGs)/biomarkers, cellular pathways, and cell types as potential therapeutic targets to improve stratification of patients with PDAC. This protocol describes the detailed methods for bioinformatics analysis of PDAC subtypes, including tumour purity estimation, subtype prediction for tumour samples in previous cohorts, pathway enrichment analysis, kinase activity analysis, and pan-omics analysis.

Alzheimer's Disease (AD) is one of the most common causes of dementia, mostly affecting the elderly population. Currently, there is no proper diagnostic tool or method available for the detection of AD. The present study used two distinct data sets of AD genes, which could be potential biomarkers in the diagnosis. The differentially expressed genes (DEGs) curated from both datasets were used for machine learning classification, tissue expression annotation and co-expression analysis. Further, CNPY3, GPR84, HIST1H2AB, HIST1H2AE, IFNAR1, LMO3, MYO18A, N4BP2L1, PML, SLC4A4, ST8SIA4, TLE1 and N4BP2L1 were identified as highly significant DEGs and exhibited co-expression with other query genes. Moreover, a tissue expression study found that these genes are also expressed in the brain tissue. In addition to the earlier studies for marker gene identification, we have considered a different set of machine learning classifiers to improve the accuracy rate from the analysis. Amongst all the six classification algorithms, J48 emerged as the best classifier, which could be used for differentiating healthy and diseased samples. SMO/SVM and Logit Boost further followed J48 to achieve the classification accuracy.

There is currently a transformed interest toward understanding the impact of fermentation on functional food development due to growing consumer interest on modified health benefits of sustainable foods. In this review, we attempt to summarize recent findings regarding the impact of Next-generation sequencing and other bioinformatics methods in the food microbiome and use prediction software to understand the critical role of microbes in producing fermented foods. Traditionally, fermentation methods and starter culture development were considered conventional methods needing optimization to eliminate errors in technique and were influenced by technical knowledge of fermentation. Recent advances in high-output omics innovations permit the implementation of additional logical tactics for developing fermentation methods. Further, the review describes the multiple functions of the predictions based on docking studies and the correlation of genomic and metabolomic analysis to develop trends to understand the potential food microbiome interactions and associated products to become a part of a healthy diet.

Thyroid cancer is a predominant form of endocrine malignancy, which destabilizes the metabolic rate of the body. The rapid increase in the incidence rate of thyroid cancer in recent years has aroused great concern to be investigated and diagnosed at an early stage. This study aimed to analyze the pathogenic mutations in thyroid cancer to identify their potential inhibitors for therapeutic targets. RAS genes are the most common oncogenes, which encode proteins that play an essential role in cell signaling and have been frequently mutated in different cancer types. The mutation in these genes causes abnormal cell growth and fails to respond to death signals. In this study, we identified the most significant mutations in the RAS genes; thus, the highly pathogenic mutations were curated from thyroid cancer patients and analyzed for their pathogenicity effect. The physicochemical analysis predicted mutation in wild-type KRAS protein had adapted negative charge on single base substitution of G12D that may easily cause loss of interactions and result in critical differences in the structure and function of the protein. Furthermore, the native KRAS protein was mutated and screened against a library of druggable compounds from the ZINC drug repository. The molecular docking analysis revealed that G12D mutant KRAS protein form best-docked complex with Naldemedine with the highest binding affinity. The dynamic simulation results further justified the stability of Naldemedine as a potential inhibitor with high efficiency in MMPBSA value of -45.4867 kcal/mol of being treated as a potential drug for papillary thyroid carcinoma. Further in vivo and in vitro validation of Naldemedine and its efficiency as a drug for the targeted pathogenic KRAS mutation is required.

Oxidative stress is known to cause cell apoptosis, tissue damage, and pathological changes in the body, but antioxidant peptides are renowned radical scavengers. This study investigated the antioxidative and protective effect of six novel peptides obtained after microbial fermentation of brown rice. The selected peptides (MW ≤ 8 KDa), namely AVPYPQ (P1), ILTAV (P2), LGDVIGVP (P3), NPIFDYVLLP (P4), VAPFPEV (P5), and VLPVPK (P6) exhibited strong antioxidant potential against in vitro radicals with IC

We report a proteogenomic analysis of pancreatic ductal adenocarcinoma (PDAC). Mutation-phosphorylation correlations identified signaling pathways associated with somatic mutations in significantly mutated genes. Messenger RNA-protein abundance correlations revealed potential prognostic biomarkers correlated with patient survival. Integrated clustering of mRNA, protein and phosphorylation data identified six PDAC subtypes. Cellular pathways represented by mRNA and protein signatures, defining the subtypes and compositions of cell types in the subtypes, characterized them as classical progenitor (TS1), squamous (TS2-4), immunogenic progenitor (IS1) and exocrine-like (IS2) subtypes. Compared with the mRNA data, protein and phosphorylation data further classified the squamous subtypes into activated stroma-enriched (TS2), invasive (TS3) and invasive-proliferative (TS4) squamous subtypes. Orthotopic mouse PDAC models revealed a higher number of pro-tumorigenic immune cells in TS4, inhibiting T cell proliferation. Our proteogenomic analysis provides significantly mutated genes/biomarkers, cellular pathways and cell types as potential therapeutic targets to improve stratification of patients with PDAC.

Bioactive peptides are present in most soy products and eggs and have essential protective functions. Infection is a core feature of innate immunity that affects blood pressure and the glucose level, and ageing can be delayed by killing senescent cells. Food also encrypts bioactive peptides and protein sequences produced through proteolysis or food processing. Unique food protein fragments can improve human health and avoid metabolic diseases, inflammation, hypertension, obesity, and diabetes mellitus. This review focuses on drug targets and fundamental mechanisms of bioactive peptides on metabolic syndromes, namely obesity and type 2 diabetes, to provide new ideas and knowledge on the ability of bioactive peptide to control metabolic syndromes.

Breast Cancer is the most predominant form of cancer among women worldwide. It has been rigorously studied for biomarker identifications and therapeutic targets. However, various potential genes and their clinical relevance to breast cancer remain unexplored. The heterogeneity of breast cancer is one of the major challenges in early detection. Several studies have reported the significant role of alkaline phosphate (ALP) in the regulation of tumor growth and overall free survival in the pathogenesis of different cancer, including breast cancer which may offer unique therapeutic targets. Therefore, these findings demand a comprehensive study for the biogenesis of ALP genes. This study aims to expression profiling of alkaline phosphate genes in breast cancer and to identify the key pathways and molecular mechanisms underlying breast cancer proliferation and progression. In this study, the transcriptome profiling of invasive breast carcinoma samples was performed and analyzed. We identified that all the ALP genes were downregulated in both Invasive Lobular and Invasive Ductal Carcinoma patients. To understand the underlying molecular mechanism and the clinical significance for these genes in breast cancer, the expression values of genes were measured in adjacent normal and tumor tissues of patients followed by network analysis and functional enrichment analysis. The overall analysis revealed the highly aberrant expression of

The study aimed to investigate the antibacterial activity of Mustard (Brassica juncea) and Moringa (Moringa oleifera) leaf extracts and coagulant protein for their potential application in water treatment. Bacterial cell aggregation and growth kinetics studies were employed for thirteen bacterial strains with different concentrations of leaf extracts and coagulant protein. Moringa oleifera leaf extract (MOS) and coagulant protein showed cell aggregation against ten bacterial strains, whereas leaf extract alone showed growth inhibition of five bacterial strains for up to 6 h and five bacterial strains for up to 3 h. Brassica juncea leaf extract (BJS) showed growth inhibition for up to 6 h, and three bacterial strains showed inhibition for up to 3 h. The highest inhibition concentration with 2.5 mg/mL was 19 mm, and furthermore, the minimum inhibitory concentration (MIC) (0.5 mg/mL) and MBC (1.5 mg/mL) were determined to have a higher antibacterial effect for &lt, 3 KDa peptides. Based on LCMS analysis, napin was identified in both MOS and BJS, furthermore, the mode of action of napin peptide was determined on lipoprotein X complex (LpxC) and four-chained structured binding protein of bacterial type II topoisomerase (4PLB). The docking analysis has exhibited moderate to potent inhibition with a range of dock score −912.9 Kcal/mol. Thus, it possesses antibacterial-coagulant potential bioactive peptides present in the Moringa oleifera purified protein (MOP) and Brassica juncea purified protein (BJP) that could act as an effective antimicrobial agent to replace currently available antibiotics. The result implies that MOP and Brassica juncea purified coagulant (BJP) proteins may perform a wide degree of antibacterial functions against different pathogens.

A novel corona virus, Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused about 100 million infections and is responsible for more than 2 million deaths worldwide. The new disease caused by this SARS-CoV-2 is named Coronavirus Disease 2019 (COVID-19) by World Health Organization (WHO). There is no specific drug approved to combat the COVID-19 to date. In the current study, anIn-silicoscreening of Indian natural compounds database approach was deployed to find potential inhibitors of SARS-CoV-2 targeting 3-chymotrypsin like protein (3CLpro). The protease 3CLpro is a potential drug target due to its critically important role in processing the polyproteins that are involved in viral replication. The Indian natural compounds library Indian Medicinal Plants, Phytochemistry And Therapeutics (IMPPAT) database, containing over 9500 manually curated compounds, were filtered and 1158 compounds were screened against the 3CLprotarget protein. A combination of virtual screening, molecular docking and molecular dynamic simulations were employed for this screening purpose. Out of the 1158 compounds screened, Gmelanone and Litseferine are the two compounds which have shown to be having best binding capabilities along with preferable absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties. Both Gmelanone and Litseferine have shown significant interactions with active site residues of 3CLprotarget protein. Our present finding are deemed further in-vitro and in-vivo studies towards developing novel anti-SARS-CoV-2 drugs based on the structure and properties of the compounds identified in this study.

Alzheimer's Disease (AD) is one of the most common causes of dementia, mostly affecting the elderly population. Currently, there is no proper diagnostic tool or method available for the detection of AD. The present study used two distinct data sets of AD genes, which could be potential biomarkers in the diagnosis. The differentially expressed genes (DEGs) curated from both datasets were used for machine learning classification, tissue expression annotation and co-expression analysis. Further, CNPY3, GPR84, HIST1H2AB, HIST1H2AE, IFNAR1, LMO3, MYO18A, N4BP2L1, PML, SLC4A4, ST8SIA4, TLE1 and N4BP2L1 were identified as highly significant DEGs and exhibited co-expression with other query genes. Moreover, a tissue expression study found that these genes are also expressed in the brain tissue. In addition to the earlier studies for marker gene identification, we have considered a different set of machine learning classifiers to improve the accuracy rate from the analysis. Amongst all the six classification algorithms, J48 emerged as the best classifier, which could be used for differentiating healthy and diseased samples. SMO/SVM and Logit Boost further followed J48 to achieve the classification accuracy.

Most of the probiotics Bacterial cells, express native antibacterial genes, resulting in the production of, antimicrobial peptides, which have various applications in biotechnology and drug development. But the identification of antibacterial peptide, structural characterization of antimicrobial peptide and prediction on mode of action. Regardless of the significance of protein manufacturing, three individual factors are required for the production method: gene expression, stabilization and specific peptide purification. Our protocol describes a straightforward technique of detecting and characterizing particular extracellular peptides and enhancing the antimicrobial peptide expression we optimized using low molecular weight peptides. This protocol can be used to improve peptide detection and expression. The following are the benefits of this method, (DOI – https://doi.org/10.1016/j.ijbiomac.2019.10.196 [1]).The data briefly describe a simple method in detection identification, characterization of antimicrobial extracellular peptide, predicating the mode of action of peptide in targeting pathogens (In-silico method), brief method on profiling of antimicrobial peptide and its mode of action [1]. Further the protocol can be used to enhance the specific peptide expressions, detection of peptides. The advantages of this technique are presented below: • Characterization protocol of specific antimicrobial peptide • The folded antimicrobial peptide expression were less expressed or non-expressed peptides. • Besides being low cost, less time-consuming, easy to handle, universal and fast to execute, the suggested technique can be used for multiple proteins expressed in probiotics (Lactobacillus species) expression system.

Pancreatic ductal adenocarcinoma (PDAC) is a devastating disease with poor prognosis, and the situation has not improved despite extensive clinical and scientific research. Here, we report proteogenomic analysis of PDAC. Mutation-phosphorylation correlations identified signaling pathways associated with somatic mutations in significantly mutated genes. mRNA-protein abundance correlations revealed oncogene and tumor suppressor candidates correlating with patient survival. Integrated clustering of mRNA, protein, and phosphorylation data identified six PDAC subtypes (Sub1-6), which were indistinguishable using mRNA data alone. mRNA and protein signatures defining Sub1-6 revealed that Sub1, Sub2-4, and Sub5-6 were precursor, invasive, and immunogenic tumors, respectively. In the Sub2-4 group, proliferation was highest for Sub4; Sub6 in the Sub5-6 group had an increased pancreatic secretion capacity. Orthotopic mouse PDAC models revealed higher numbers of pro-tumorigenic immune cells in Sub4 tumors, inhibiting T cell proliferation. Our proteogenomic analysis provides therapeutic targets and improves understanding of cancer biology and patient stratification in PDAC.

Proteogenomics provide opportunities for proteomic validation of gene structures, genomic alterations and functional relevance of novel findings obtained from genomic data analysis. However, for effective proteogenomic data integration, an extensive proteome profiling, approaching the gene coverage of genomics data, is critical. Here we developed a multi-stage database search method for comprehensive proteomics data analysis to complement whole transcriptome sequencing data. The method utilizes two complementary database search engines, MS-GF+ and MODa/MODi, in tandem. The MS/MS data were first subjected to MS-GF+ database search (1st stage search) and the unidentified MS/MS data from the 1st stage search were subsequently analyzed with the combined use of MODa and MODi (2nd stage search), tools for blind and unrestrictive modification search, respectively. When combined with m PE-MMR, a tool for accurate and extensive precursor masses assignments to MS/MS data, the multi-stage method exhibited a significant increase in identified peptides, modified peptides, mutated peptides, identified proteins and coding genes, compared to a conventional single-stage method. With the increased coverage of proteome profile, the genomics and proteomics data obtained from the same gastric tumor tissue were effectively integrated as evidenced by proBAMsuite analysis results, which showed abundant examples of peptides uniquely mapped to genomic locations as well as increased coverages of exon-exon junctions and coding regions with the multi-stage search method.

// Hussain Al Ssadh 1 , Patrick S. Spencer 1 , Waleed Alabdulmenaim 1, 2 , Rana Alghamdi 1, 3 , Inamul Hasan Madar 4 , Jose M. Miranda-Sayago 1 and Nelson Fernandez 1 1 School of Biological Sciences, University of Essex, Wivenhoe Park, Colchester, Essex CO4 3SQ, United Kingdom 2 Pathology Department, College of Medicine, Qassim University, Qassim, Saudi Arabia 3 King Abdulaziz University, Rabigh Campus, Rabigh, Saudi Arabia 4 Department of Biotechnology and Genetic Engineering, Bharathidasan University, Tiruchirappalli, 620024, Tamil Nadu, India Correspondence to: Nelson Fernandez, email: nelson@essex.ac.uk Keywords: CD74, CD44s, CD44v, co-localization Received: May 23, 2017 Accepted: August 17, 2017 Published: September 14, 2017 ABSTRACT Interactions between pairs of membrane-bound receptors can enhance tumour development with implications for targeted therapies for cancer. Here we demonstrate clear heterotypic interaction between CD74 and CD44, which might act in synergy and hence contribute to breast cancer progression. CD74, a type II transmembrane glycoprotein, is a chaperone for MHC class II biosynthesis and a receptor for the MIF. CD44 is the receptor for hyaluronic acid and is a Type I transmembrane protein. Interactions between CD74, MIF and the intra-cytoplasmic domain of CD44 result in activation of ERK1/2 pathway, leading to increased cell proliferation and decreased apoptosis. The level of CD44 in the breast tumor cell lines CAMA-1, MDA-MB-231, MDA-MB-435 and the immortalized normal luminal cell line 226LDM was higher than that of CD74. It was also observed that CD74 and CD44 exhibit significant variation in expression levels across the cells. CD74 and CD44 were observed to accumulate in cytoplasmic compartments, suggesting they associate with each other to facilitate tumour growth and metastasis. Use of a novel and validated colocalisation and image processing approach, coupled with co-immunoprecipitation, confirmed that CD74 and CD44 physically interact, suggesting a possible role in breast tumour growth. This is the first time that CD74 and CD44 colocalization has been quantified in breast cancer cells using a non-invasive and validated bioimaging procedure. Measuring the co-expression levels of CD74 and CD44 could potentially be used as a ‘biomarker signature’ to monitor different stages of breast cancer.

Breast cancer is a leading cause of morbidity and mortality among women comprising about 12% females worldwide. The underlying alteration in the gene expression, molecular mechanism and metabolic pathways responsible for incidence and progression of breast tumorigenesis are yet not completely understood. In the present study, potential biomarker genes involved in the early progression for early diagnosis of breast cancer has been detailed. Regulation and Gene profiling of Ductal Carcinoma In-situ (DCIS), Invasive Ductal Carcinoma (IDC) and healthy samples have been analyzed to follow their expression pattern employing normalization, statistical calculation, DEGs annotation and Protein-Protein Interaction (PPI) network. We have performed a comparative study on differentially expressed genes among Healthy vs DCIS, Healthy vsIDC and DCIS vs IDC. We found MCM102 and SLC12A8as consistently over-expressed and LEP, SORBS1, SFRP1, PLIN1, FABP4, RBP4, CD300LG, ID4, CRYAB, ECRG4, G0S2, FMO2, ADAMTS5, CAV1, CAV2, ABCA8, MAMDC2, IGFBP6, CLDN11, TGFBR3as under-expressed genes in all the 3 conditions categorized for pre-invasive and invasive ductal breast carcinoma. These genes were further studied for the active pathways where PPAR(γ) signaling pathway was found to be significantly involved. The gene expression profile database can be a potential tool in the early diagnosis of breast cancer.

BACKGROUND: The cluster of differentiation (CD) 74 is known for its immunological functions and its elevated level was reported in various cancer cells. AIM: The aim of the present study was to investigate the expression and potential roles of CD74 in the proliferative and apoptotic activity of breast cancer. METHODS: Expression of CD74, macrophage migration inhibitory factor (MIF) and CD44 was assayed in CAMA-1 and MDA-MB-231 cell lines using flow cytometry. CD74 was knocked down using CD74 siRNA-transfection in CAMA-1, and MDA-MB-231 cells and proliferation and apoptosis were determined in the transfected breast cancer cells. RESULTS: The data showed that CD74, MIF and CD44 were expressed in breast cancer cell lines and were associated with cell proliferation and apoptosis. Correlation analysis revealed that CD74 was positively correlated and colocalised with MIF on the cell-surface of CAMA-1 and MDA-MB-231. The knockdown of CD74 significantly reduced CAMA-1 and MDA-MB-231 cell proliferation and increased the level of apoptotic cells. CONCLUSION: We concluded that the interactions of CD74 with MIF and CD74 with CD44 could be a potential tumour marker for breast cancer cells. Moreover, the level of co-expression of MIF and CD74 or CD44 could be a surrogate marker for the efficacy of anti-angiogenic drugs, particularly in breast cancer tumours. In short, the study revealed the potential roles of CD74 in the proliferation and apoptosis of breast cancer which may serve as a potential therapeutic target for breast cancer.

Human-milk-based probiotics play a major role in the early colonization and protection of infants against gastrointestinal infection. We investigated potential probiotics in human milk. Among 41 Lactic acid bacteria (LAB) strains, four strains showed high antimicrobial activity against Escherichia coli 0157:H7, Listeria monocytogenes ATCC 15313, Bacillus cereus ATCC 14576, Staphylococcus aureus ATCC 19095, and Helicobacter pylori. The selected LAB strains were tested in simulated gastrointestinal conditions for their survival. Four LAB strains showed high resistance to pepsin (82%-99%), bile with pancreatine stability (96%-100%), and low pH (80%-94%). They showed moderate cell surface hydrophobicity (22%-46%), auto-aggregation abilities (12%-34%), and 70%-80% co-aggregation abilities against L. monocytogenes ATCC 15313, S. aureus ATCC 19095, B. cereus ATCC 14576, and E. coli 0157:H7. All four selected isolates were resistant to gentamicin, imipenem, novobiocin, tetracycline, clindamycin, meropenem, ampicillin, and penicillin. The results show that Pediococcus acidilatici is likely an efficient probiotic strain to produce 3 Kda pediocin-based antimicrobial peptides, confirmed by applying amino acid sequences), using liquid chromatography mass spectrometry and HPLC with the corresponding sequences from class 2 bacteriocin, and based on the molecular docking, the mode of action of pediocin was determined on LipoX complex, further the

In this study, the probiotic properties of nine lactic acid bacteria (LAB) were evaluated by using an in silico analysis comprising principal component, heat map, and network analyses. Acid and bile resistances, bile salt hydrolase (BSH) activity, antimicrobial activity, auto- and co-aggregation, and hydrophobicity were analyzed in the strains. All tested LAB exhibited >60% of survival percentage in acid and bile resistances. Five strains of LAB exhibited positive BSH activities and all LAB demonstrated antimicrobial activities against at least one pathogen except L. acidophilus IDCC3302. Following a time-dependent manner, L. acidophilus IDCC3302 and L. plantarum LP-K1791 exhibited the greatest auto- and co-aggregation percentages, respectively. The hydrophobicity of all LAB was satisfied with the minimum requirement of hydrophobicity (40%) as potential probiotics. Based on the in silico analysis, L. casei IDCC3451, L. plantarum LP-K1791, and L. rhamnosus IDCC3201 were selected as the most promising probiotics. This in silico analysis will be useful for the precise selection of probiotics for the development of functional foods and healthy dietary supplements in the food and pharmaceutical industries.

In this manuscript we have presented the results of binding efficacy of a range of chemical compounds that were generated from a modeled pharmacophore based upon structure clustering using donezaphil as a lead molecule On analyzing the structure cluster result we found that benzylcyclohexyl methyl dihydro H indene diol is present common in all the active drug potential lead molecules Furthermore we have established a structure activity relationship and studied the efficacy of the ligands generated Our results indicate that the compounds generated based on the pharmacophore model preferentially binds to the allosteric site of AChE The binding energy calculation of all compounds that were generated from the modeled pharmacophore reveals favorable interaction with moderate to low binding energy relative to donezaphil Among the compounds generated F was found to be the most effective compound based upon in silico binding prediction total energy and toxicity considerations Hence we propose to synthesis and further evaluate F that may show interesting biological activity In addition we have validated a hypothesis with evidence that the ligand targeted for AChE must possess a polar side group preferentially NH The pharmacphore generated and presented in this may serve a backbone structure for future ligands targeting AChE

Aims: To investigate the susceptibility profile of bacterial isolates from hand dug wells and borehole waters within the Amai Kingdom, in Ukwuani Local Government Area of Delta State. Place and Duration of Study: Department of Microbiology, Novena University, between April 2016 and November 2016. Methodology: A total of 30 boreholes and 30 well water samples were randomly sourced using sterile tightly locked plastic containers and transported to the laboratory within 2 hours. The water samples were cultured using spread plate method and the pure bacterial isolates tested for susceptibility to some commercial antibiotic discs using the Kirby-Bauer method. Results: Bacteria were isolated respectively from 50% and 100% of the borehole and well water samples collected. A total of 45 bacterial isolates, distributed among the genera Staphylococcus (6.7%), Bacillus (10.0%), Escherichia (16.7%), Pseudomonas (11.7%) Enterobacter (8.3%), Proteus (10.0%), and Klebsiella (11.7%), was encountered. Majority of the isolates were sensitive to Amoxicillin-clavulanic acid, Ciprofloxacin, Ceftriaxone, Gentamicin, Ofloxacin, and resistant to Ampicillin, Cotrimoxazole and Tetracycline. Bacillus sp (56%) was more resistant (p=.05) than S. aureus (33%), while the most resistant Gram-negative bacteria was Pseudomonas sp. (54%), followed by both E. coli (44%) and Klebsiella sp (44%), and both Proteus sp., (33%) and Enterobacter sp. (33%). Drug resistance was observed in at least three of the tested antibiotic disks. Conclusion: Findings from this study suggest that the drinking water sources in the Amai Kingdom are bacteriologically poor, with multiple-drug resistant bacteria, and thus of public health importance. Public education on dangers associated with indiscriminate dumping of waste and drug abuse is strongly recommended.

Polycystic ovary syndrome (PCOS) is endocrine system disease which affect women ages 18 to 44 where the women's hormones are imbalance. Recently it has been reported to occur in early age. Alteration of normal gene expression in PCOS has shown negative effects on long-term health issues. PCOS has been the responsible factor for the infertility in women of reproductive age group. Early diagnosis and treatment can improve the women's health suffering from PCOS. Earlier Studies shows correlation of PCOS upon insulin resistance with significant outcome, Current study shows the linkage between PCOS with obesity and non-obese patients. Gene expression datasets has been downloaded from GEO (control and PCOS affected patients). Normalization of the datasets were performed using R based on RMA and differentially expressed gene (DEG) were selected on the basis of p-value 0.05 followed by functional annotation of selected gene using Enrich R and DAVID. The DEGs were significantly related to PCOS with obesity and other risk factors involved in disease. The Gene Enrichment Analysis suggests alteration of genes and associated pathway in case of obesity. Current study provides a productive groundwork for specific biomarkers identification for the accurate diagnosis and efficient target for the treatment of PCOS.