Exploring Morin as an anti-quorum sensing agent (anti-QSA) against resistant strains of Staphylococcus aureus.

Staphylococcus aureus an opportunistic pathogen, causes biofilm-associated infections like nosocomial and chronic disease, where quorum sensing plays vital role. Biofilm-associated infections are provocative due to antibiotic resistance and become major public health threat to human. Accordingly, there is an urgent need to identify novel compounds and groundbreaking methods to pervade and clear biofilm-associated infections. It has been suggested that naturally occurring small molecules especially flavonoids could be used as a new source of anti-biofilm drugs. Thus, an attempt to evaluate the effectiveness of Morin against Staphylococcus aureus resistant strains, through in-vitro (antibacterial, anti-biofilm, microscopic analysis, anti-motility, anti-spreading, cell viability and EPS production assay) and in-silico studies (Docking and Molecular dynamic simulation). Interestingly, in vitro and microscopic analysis revealed Morin to have very less or negligible antibiotic activity against methicillin resistant and vancomycin resistant Staphylococcus aureus, however, Morin exhibited significant biofilm inhibition, reduced motility and spreading, and EPS production of both the resistant strains. Further, studies on the molecular interaction of Morin with global regulatory protein (SarA) of Staphylococcus aureus, suggested the effective role of Morin as an anti-quorum sensing agent and interpolating the further studies to suit it as drug candidate against the pathogenic bacteria.

Secretome analysis of diarrhea-inducing strains of Escherichia coli.

Secreted proteins constitute a major part of virulence factors that are responsible for pathogenesis caused by Gram-negative bacteria. Enterohemorrhagic Escherichia coli, O157:H7, is the major pathogen often causing outbreaks. However, studies have reported that the significant outbreaks caused by non-O157:H7 E. coli strains, also known as "Big-Six" serogroup strains, are increasing. There is no systematic study describing differential secreted proteins from these non-O157:H7 E. coli strains. In this study, we carried out MS-based differential secretome analysis using tandem mass tags labeling strategy of non-O157:H7 E. coli strains, O103, O111, O121, O145, O26, and O45. We identified 1241 proteins, of which 565 proteins were predicted to be secreted. We also found that 68 proteins were enriched in type III secretion system and several of them were differentially expressed across the strains. Additionally, we identified several strain-specific secreted proteins that could be used for developing potential markers for the identification and strain-level differentiation. To our knowledge, this study is the first comparative proteomic study on secretome of E. coli Big-Six serogroup and the several of these strain-specific secreted proteins can be further studied to develop potential markers for identification and strain-level differentiation. Moreover, the results of this study can be utilized in several applications, including food safety, diagnostics of E. coli outbreaks, and detection and identification of bio threats in biodefense.

APSLAP: an adaptive boosting technique for predicting subcellular localization of apoptosis protein.

Apoptotic proteins play key roles in understanding the mechanism of programmed cell death. Knowledge about the subcellular localization of apoptotic protein is constructive in understanding the mechanism of programmed cell death, determining the functional characterization of the protein, screening candidates in drug design, and selecting protein for relevant studies. It is also proclaimed that the information required for determining the subcellular localization of protein resides in their corresponding amino acid sequence. In this work, a new biological feature, class pattern frequency of physiochemical descriptor, was effectively used in accordance with the amino acid composition, protein similarity measure, CTD (composition, translation, and distribution) of physiochemical descriptors, and sequence similarity to predict the subcellular localization of apoptosis protein. AdaBoost with the weak learner as Random-Forest was designed for the five modules and prediction is made based on the weighted voting system. Bench mark dataset of 317 apoptosis proteins were subjected to prediction by our system and the accuracy was found to be 100.0 and 92.4 %, and 90.1 % for self-consistency test, jack-knife test, and tenfold cross validation test respectively, which is 0.9 % higher than that of other existing methods. Beside this, the independent data (N151 and ZW98) set prediction resulted in the accuracy of 90.7 and 87.7 %, respectively. These results show that the protein feature represented by a combined feature vector along with AdaBoost algorithm holds well in effective prediction of subcellular localization of apoptosis proteins. The user friendly web interface "APSLAP" has been constructed, which is freely available at http://apslap.bicpu.edu.in and it is anticipated that this tool will play a significant role in determining the specific role of apoptosis proteins with reliability.

Computational identification and characterization of vascular wilt pathogen (Fusarium oxysporum f. sp. lycopersici) CAZymes in tomato xylem sap.

Fusarium oxysporum f. sp. lycopersici is a devastating plant pathogenic fungi known for wilt disease in the tomato plant and secrete cell wall degrading enzymes. These enzymes are collectively known as carbohydrate-active enzymes (CAZymes), crucial for growth, colonization and pathogenesis. Therefore, the present study was aimed to identify and annotate pathogen CAZymes in the xylem sap of a susceptible tomato variety using downstream proteomics and meta servers. Further, structural elucidation and conformational stability analysis of the selected CAZyme families were done through homology modeling and molecular dynamics simulation. Among all the fungal proteins identified, the carbohydrate metabolic process was found to be enriched. Most of the annotated CAZymes belonged to the hydrolase and oxidoreductase families, and 90% were soluble and extracellular. Moreover, using a publically available interactome database, interactions were observed between the families acting on chitin, hemicellulose and pectin. Subsequently, important catalytic residues were identified in the candidate CAZymes belonging to carbohydrate esterase (CE8) and glycosyl hydrolase (GH18 and GH28). Further, essential dynamics after molecular simulation of 100 ns revealed the overall behavior of these CAZymes with distinct global minima and transition states in CE8. Thus, our study identified some of the CAZyme families that assist in pathogenesis and growth through host cell wall deconstruction with further structural insight into the selected CAZyme families.Communicated by Ramaswamy H. Sarma.

Comparative transcriptome profiling and weighted gene co-expression network analysis to identify core genes in maize (Zea mays L.) silks infected by multiple fungi.

Maize (Zea mays L.) is the third most popular Poaceae crop after wheat and rice and used in feed and pharmaceutical sectors. The maize silk contains bioactive components explored by traditional Chinese herbal medicine for various pharmacological activities. However, Fusarium graminearum, Fusarium verticillioides, Trichoderma atroviride, and Ustilago maydis can infect the maize, produce mycotoxins, hamper the quantity and quality of silk production, and further harm the primary consumer's health. However, the defense mechanism is not fully understood in multiple fungal infections in the silk of Z. mays. In this study, we applied bioinformatics approaches to use the publicly available transcriptome data of Z. mays silk affected by multiple fungal flora to identify core genes involved in combatting disease response. Differentially expressed genes (DEGs) were identified among intra- and inter-transcriptome data sets of control versus infected Z. mays silks. Upon further comparison between up- and downregulated genes within the control of datasets, 4,519 upregulated and 5,125 downregulated genes were found. The DEGs have been compared with genes in the modules of weighted gene co-expression network analysis to relevant specific traits towards identifying core genes. The expression pattern of transcription factors, carbohydrate-active enzymes (CAZyme), and resistance genes was analyzed. The present investigation is supportive of our findings that the gene ontology, immunity stimulus, and resistance genes are upregulated, but physical and metabolic processes such as cell wall organizations and pectin synthesis were downregulated respectively. Our results are indicative that terpene synthase TPS6 and TPS11 are involved in the defense mechanism against fungal infections in maize silk.

Computational investigation of FDA approved drugs as selective PARP-1 inhibitors by targeting BRCT domain for cancer therapy.

Poly(ADP-ribose) polymerase-1 is a promising target for the treatment of cancer due to its involvement in base excision repair pathways for repairing DNA single-strand breaks. However, available PARP-1 inhibitors target a highly conserved PARPs catalytic domain, which causes toxicity due to the off-target activity. Therefore, the present study was hypothesized to identify selective inhibitors by targeting specific protein-protein interacting (PPI) PARP-1 BRCT domain. Moreover, PPI hotspot residues (Gly399, Lys400, Leu401, Lys441 & Lys442) and a druggable pocket was detected to screen small molecule inhibitors. Hence, two FDA approved drug molecules (levoleucovorin and balsalazide) were recognized to fit in the druggable pocket. Since they are already under investigation for anti-cancer activity, thus could be further explored in PARP-1 sensitive cancer cells to expand their selectivity and develop as effective anti-cancer agents. Besides, the study also provides detailed structural insight of PARP-1 and XRCC1 complex through their BRCT domains.

Molecular inhibition of telomerase recruitment using designer peptides: an in silico approach.

Telomere holds special mechanism for solving end repair problems and maintaining genomic stability. Protection of telomeres 1 (POT1) which belongs to shelterin family is identified as a key protein that recruits telomerase by interacting with telomere repeat binding factors (TRB1-3). Since, deciphering the mechanism through which POT assembles telomerase is of great interest, computational approaches have been undertaken to understand the mechanism in a well- developed model system - Arabidopsis thaliana. As a first step, an untraditional approach was mediated to locate the active site residues on modeled AtPOT1b protein by interaction studies using molecular docking. To keep in trend with the recent developments, peptide construction and validation was promoted as the next step via molecular dynamics simulation studies. Finally, the validated peptides based on propensity score was evaluated for its efficacy as a potent inhibitor for POT and TRB1-3 interactions. The best peptide, namely, (1-2-d) out of 30 designed peptides, was proved to be vital inhibitor by weakening the interacting complexes.

Reduction of Silver Ions by Cell Free Extracts of Westiellopsis sp.

Biosynthesis of silver nanoparticles using Westiellopsis sp. (A15), a filamentous cyanobacterium belonging to the family Fischerellaceae, has been demonstrated. Aqueous silver ions (Ag(+)) when exposed to the culture filtrate of Westiellopsis were reduced in the solution, which were characterized by biophysical measures utilizing the UV-Vis spectroscopy, scanning electron microscopy (SEM), and FTIR. The nanoparticles exhibited the maximum absorbance at 420 nm in UV-Vis spectroscopy, while the SEM micrograph revealed that the aggregated nanoparticles vary in size between 20 nm and 5 µm. However, the FTIR analysis provided evidence for presence of proteins in the filtrate to be involved in the reduction of silver ions.

Fuzzy logic for personalized healthcare and diagnostics: FuzzyApp--a fuzzy logic based allergen-protein predictor.

The path to personalized medicine demands the use of new and customized biopharmaceutical products containing modified proteins. Hence, assessment of these products for allergenicity becomes mandatory before they are introduced as therapeutics. Despite the availability of different tools to predict the allergenicity of proteins, it remains challenging to predict the allergens and nonallergens, when they share significant sequence similarity with known nonallergens and allergens, respectively. Hence, we propose "FuzzyApp," a novel fuzzy rule based system to evaluate the quality of the query protein to be an allergen. It measures the allergenicity of the protein based on the fuzzy IF-THEN rules derived from five different modules. On various datasets, FuzzyApp outperformed other existing methods and retained balance between sensitivity and specificity, with positive Mathew's correlation coefficient. The high specificity of allergen-like putative nonallergens (APN) revealed the FuzzyApp's capability in distinguishing the APN from allergens. In addition, the error analysis and whole proteome dataset analysis suggest the efficiency and consistency of the proposed method. Further, FuzzyApp predicted the Tropomyosin from various allergenic and nonallergenic sources accurately. The web service created allows batch sequence submission, and outputs the result as readable sentences rather than values alone, which assists the user in understanding why and what features are responsible for the prediction. FuzzyApp is implemented using PERL CGI and is freely accessible at http://fuzzyapp.bicpu.edu.in/predict.php . We suggest the use of Fuzzy logic has much potential in biomarker and personalized medicine research to enhance predictive capabilities of post-genomics diagnostics.

NF-κB activation and proinflammatory cytokines mediated protective effect of Indigofera caerulea Roxb. on CCl4 induced liver damage in rats.

Indigofera caerulea Roxb. is a well known shrub among native medical practitioners in folk medicine used for the treatment of jaundice, epilepsy, night blindness and snake bites. It is also reported to have antioxidant and antimicrobial properties. However its actual efficacy and hepatoprotective mechanism in particular is uncertain. Thus the present study investigates the hepatoprotective effect of the methanolic extract of I. caerulea Roxb. leaves (MIL) and elucidation of its mode of action against carbon tetrachloride (CCl4) induced liver injury in rats. HPLC analysis of MIL when carried out showed peaks close to standard ferulic acid and quercetin. Intragastric administration of MIL up to 2000 mg/kg bw, didn't show any toxicity and mortality in acute toxicity studies. During "in-vivo" study, hepatic injury was established by intraperitoneal administration of CCl4 3 ml/kg bw (30% CCl4 in olive oil; v/v) twice a week for 4 weeks in Sprague-Dawley rats. Further, hepatoprotective activity of MIL assessed using two different doses (100 and 200mg/kg bw) showed that intra-gastric administration of MIL (200mg/kg bw) significantly attenuates liver injury. Investigation of the underlying mechanism revealed that MIL treatment was capable of reducing inflammation by an antioxidant defense mechanism that blocks the activation of NF-κB as well as inhibits the release of proinflammatory cytokine TNF-α and IL-1ß. The results suggest that MIL has a significant hepatoprotective activity which might be due to the presence of phytochemicals namely analogues of ferulic acid and other phytochemicals which together may suppress the inflammatory signaling pathways and promote hepatoprotective activity against CCl4 intoxicated liver damage.

SCLAP: an adaptive boosting method for predicting subchloroplast localization of plant proteins.

Chloroplasts are organelles found in plant system and other photosynthetic eukaryotes. Since a large number of essential pathways take place in this organelle, proteins in the chloroplast are considered vital. Therefore, knowledge about the subchloroplast localization of the chloroplast proteins will provide precise information in understanding its interaction within the chloroplast. To address this, an AdaBoost-based prediction system to predict the subchloroplast localization of chloroplast proteins (SCLAP) was developed. It integrates three different sequence-based features for prediction, beside the addition of similarity-based module for significant improvement in prediction performance. SCLAP achieved an overall accuracy of 89.3% in jackknife cross-validation test against the benchmark dataset, which was considered highest among existing tools and equals the SubIdent, and 85.9% accuracy in new error-free dataset. Evaluation of SCLAP with the independent dataset, five-fold cross-validation, and their corresponding receiver operator characteristic curve analysis demonstrated the SCLAP's efficient performance. SCLAP is the webserver implementation of our algorithm written in PERL. The server can be used to predict the subchloroplast localization of chloroplast proteins ( http://sclap.bicpu.edu.in/predict.php ).

Green synthesis, characterization and antimicrobial activity of Au NPs using Euphorbia hirta L. leaf extract.

The activity of a nano sized particle is said to be greater when compared to that of its parent materials combined. Thus, an attempt was made to produce gold nanostructures having unusual physicochemical properties. In this study, eco-friendly, non-toxic gold nanoparticles (Au NPs) were biologically synthesized using the leaf extract of Euphorbia hirta L. The synthesis of Au NPs was confirmed by a change in extract color from pale yellow to purple and surface plasmon resonance spectra obtained in a range of approximately 530nm. Nanoparticles whose sizes ranged from 6nm to 71nm, were synthesized. Different instrumental techniques were used to characterize the synthesized AuNPs, such TEM, XRD, EDAX, AFM, particle size analyzer, FTIR and Raman spectra. Also the antibacterial activity of the green synthesized Au NPs against bacterial strains of Escherchia coli, Pseudomonas aeroginosa and Klebsiella pneumonia was studied using MIC method, and found to be highly effective.

The Arabidopsis stress responsive gene database.

Plants in nature may face a wide range of favorable or unfavorable biotic and abiotic factors during their life cycle. Any of these factors may cause stress in plants; therefore, they have to be more adaptable to stressful environments and must acquire greater response to different stresses. The objective of this study is to retrieve and arrange data from the literature in a standardized electronic format for the development of information resources on potential stress responsive genes in Arabidopsis thaliana. This provides a powerful mean for manipulation, comparison, search, and retrieval of records describing the nature of various stress responsive genes in Arabidopsis thaliana. The database is based exclusively on published stress tolerance genes associated with plants.

Mining of simple sequence repeats in the Genome of Gentianaceae.

Simple sequence repeats (SSRs) or short tandem repeats are short repeat motifs that show high level of length polymorphism due to insertion or deletion mutations of one or more repeat types. Here, we present the detection and abundance of microsatellites or SSRs in nucleotide sequences of Gentianaceae family. A total of 545 SSRs were mined in 4698 nucleotide sequences downloaded from the National Center for Biotechnology Information (NCBI). Among the SSR sequences, the frequency of repeat type was about 429 -mono repeats, 99 -di repeats, 15 -tri repeats, and 2 --hexa repeats. Mononucleotide repeats were found to be abundant repeat types, about 78%, followed by dinucleotide repeats (18.16%) among the SSR sequences. An attempt was made to design primer pairs for 545 identified SSRs but these were found only for 169 sequences.