Leukocyte-derived matrix metalloproteinase-9 mediates blood-brain barrier breakdown and is proinflammatory after transient focal cerebral ischemia

Results of recent studies reveal vascular and neuroprotective effects of matrix metalloproteinase-9 (MMP-9) inhibition and MMP-9 gene deletion in experimental stroke. However, the cellular source of MMP-9 produced in the ischemic brain and the mechanistic basis of MMP-9-mediated brain injury require elucidation. In the present study, we used MMP-9-/- mice and chimeric knockouts lacking either MMP-9 in leukocytes or in resident brain cells to test the hypothesis that MMP-9 released from leukocytes recruited to the brain during postischemic reperfusion contributes to this injury phenotype. We also tested the hypothesis that MMP-9 promotes leukocyte recruitment to the ischemic brain and thus is proinflammatory. The extent of blood-brain barrier (BBB) breakdown, the neurological deficit, and the volume of infarction resulting from transient focal stroke were abrogated to a similar extent in MMP-9-/- mice and in chimeras lacking leukocytic MMP-9 but not in chimeras with MMP-9-containing leukocytes. Zymography and Western blot analysis from these chimeras confirmed that the elevated MMP-9 expression in the brain at 24 h of reperfusion is derived largely from leukocytes. MMP-9-/- mice exhibited a reduction in leukocyte-endothelial adherence and a reduction in the number of neutrophils plugging capillaries and infiltrating the ischemic brain during reperfusion; microvessel immunopositivity for collagen IV was also preserved in these animals. These latter results document proinflammatory actions of MMP-9 in the ischemic brain. Overall, our findings implicate leukocytes, most likely neutrophils, as a key cellular source of MMP-9, which, in turn, promotes leukocyte recruitment, causes BBB breakdown secondary to microvascular basal lamina proteolysis, and ultimately contributes to neuronal injury after transient focal stroke.     

Support vector machine-based method for subcellular localization of human proteins using amino acid compositions, their order, and similarity search

Here we report a systematic approach for predicting subcellular localization (cytoplasm, mitochondrial, nuclear, and plasma membrane) of human proteins. First, support vector machine (SVM)-based modules for predicting subcellular localization using traditional amino acid and dipeptide (i + 1) composition achieved overall accuracy of 76.6 and 77.8%, respectively. PSI-BLAST, when carried out using a similarity-based search against a nonredundant data base of experimentally annotated proteins, yielded 73.3% accuracy. To gain further insight, a hybrid module (hybrid1) was developed based on amino acid composition, dipeptide composition, and similarity information and attained better accuracy of 84.9%. In addition, SVM modules based on a different higher order dipeptide i.e. i + 2, i + 3, and i + 4 were also constructed for the prediction of subcellular localization of human proteins, and overall accuracy of 79.7, 77.5, and 77.1% was accomplished, respectively. Furthermore, another SVM module hybrid2 was developed using traditional dipeptide (i + 1) and higher order dipeptide (i + 2, i + 3, and i + 4) compositions, which gave an overall accuracy of 81.3%. We also developed SVM module hybrid3 based on amino acid composition, traditional and higher order dipeptide compositions, and PSI-BLAST output and achieved an overall accuracy of 84.4%. A Web server HSLPred (www.imtech.res.in/raghava/hslpred/ or bioinformatics.uams.edu/raghava/hslpred/) has been designed to predict subcellular localization of human proteins using the above approaches.     

Photocurable hard and porous biomaterials from ROMP precursors cross-linked with diyl radicals

A combination of (ROMP) ring-opening metathesis polymerization and diradical (diyl) cross-linking provides a new access to hard biomaterials and potential artificial bone replacements. ROMP was used to construct soft and pliable linear polymers bearing photolabile diazene functions. After treatment with light, a nitrogen aerosol is released throughout the polymer to create desirable porosity, cross-linking, and hardening in a single step. Nonpolymeric mechanistic work supporting these studies was also examined.     

Real value prediction of solvent accessibility in proteins using multiple sequence alignment and secondary structure

The present study is an attempt to develop a neural network-based method for predicting the real value of solvent accessibility from the sequence using evolutionary information in the form of multiple sequence alignment. In this method, two feed-forward networks with a single hidden layer have been trained with standard back-propagation as a learning algorithm. The Pearson's correlation coefficient increases from 0.53 to 0.63, and mean absolute error decreases from 18.2 to 16% when multiple-sequence alignment obtained from PSI-BLAST is used as input instead of a single sequence. The performance of the method further improves from a correlation coefficient of 0.63 to 0.67 when secondary structure information predicted by PSIPRED is incorporated in the prediction. The final network yields a mean absolute error value of 15.2% between the experimental and predicted values, when tested on two different nonhomologous and nonredundant datasets of varying sizes. The method consists of two steps: (1) in the first step, a sequence-to-structure network is trained with the multiple alignment profiles in the form of PSI-BLAST-generated position-specific scoring matrices, and (2) in the second step, the output obtained from the first network and PSIPRED-predicted secondary structure information is used as an input to the second structure-to-structure network. Based on the present study, a server SARpred (http://www.imtech.res.in/raghava/sarpred/) has been developed that predicts the real value of solvent accessibility of residues for a given protein sequence. We have also evaluated the performance of SARpred on 47 proteins used in CASP6 and achieved a correlation coefficient of 0.68 and a MAE of 15.9% between predicted and observed values.     

Characterisation of the nuclear proteome of a dehydration‐sensitive cultivar of chickpea and comparative proteomic analysis with a tolerant cultivar

Water deficit or dehydration hampers plant growth and development, and shrinks harvest size of major crop species worldwide. Therefore, a better understanding of dehydration response is the key to decipher the regulatory mechanism of better adaptation. In recent years, nuclear proteomics has become an attractive area of research, particularly to study the role of nucleus in stress response. In this study, a proteome of dehydration‐sensitive chickpea cultivar (ICCV‐2) was generated from nuclei‐enriched fractions. The LC‐MS/MS analysis led to the identification of 75 differentially expressed proteins presumably associated with different metabolic and regulatory pathways. Nuclear localisation of three candidate proteins was validated by transient expression assay. The ICCV‐2 proteome was then compared with that of JG‐62, a tolerant cultivar. The differential proteomics and in silico analysis revealed cultivar‐specific differential expression of many proteins involved in various cellular functions. The differential tolerance could be attributed to altered expression of many structural proteins and the proteins involved in stress adaptation, notably the ROS catabolising enzymes. Further, a comprehensive comparison on the abiotic stress‐responsive nuclear proteome was performed using the datasets published thus far. These findings might expedite the functional determination of the dehydration‐responsive proteins and their prioritisation as potential molecular targets for better adaptation.     

Management of the late blight (Phytophthora infestans) disease of potato in the southern hills of India

Late blight of potato is considered to be the most devastating problem causing severe yield losses in potato worldwide. Among the different management strategies, the use of resistant cultivars is the most viable option, but the non‐availability of enough quantity of quality seed materials of resistant cultivars forces the farmers to grow susceptible cultivars with proper fungicide scheduling. Therefore, in the present study, chemical control using fungicide has been attempted with newer molecules in the susceptible cultivar along with a resistant cultivar as a positive control. All the tested fungicides were found safe, and no phytotoxicity was observed with any chemical at the applied rate. In resistant cultivar, no late blight was appeared in both the years, whereas maximum AUDPC was observed in the untreated control (276.3) and minimum (41.7) in mancozeb‐cymoxanil + mancozeb based scheduling which was found on par with chlorothalonil‐famoxadone + cymoxanil (51.3) and chlorothalonil‐ametoctradin + dimethomorph (53.5) based scheduling. Among the treatments, resistant cultivar, Kufri Girdhari followed by chlorothalonil‐ametoctradin + dimethomorph and mancozeb‐cymoxanil + mancozeb based fungicidal scheduling were proven as the best treatments for both the crop seasons resulting in the highest yield parameters. The disease severity showed a strong negative correlation with the tuber yield of potatoes in both the years. Based on overall observations including BC ratio, it can be concluded that, wherever seed material of resistant cultivar is available farmers should grow the same or else with susceptible cultivars the fungicidal scheduling based on mancozeb‐cymoxanil + mancozeb or chlorothalonil‐ametoctradin + dimethomorph can be followed to obtain the maximum returns with effective management of late blight at the southern hills of India.     

Radiosensitization in human breast carcinoma cells by thymoquinone: role of cell cycle and apoptosis

TQ (thymoquinone), the bioactive constituent of black seed (Nigella sativa), has been shown to inhibit the growth of various human cancers both in vitro and in vivo. This study reports the radiosensitizing effect of TQ on human breast carcinoma cells (MCF7 and T47D). TQ in combination with single dose of ionizing radiation (2.5 Gy) was found to exert supra-additive cytotoxic effects on both the carcinomas as measured by cell proliferation and colony-formation assays. Annexin V binding and FACS analysis revealed the role of enhanced apoptosis and cell cycle modulation in the mechanism of TQ-mediated radiosensitization, thus supporting TQ as an adjuvant for preclinical testing in cancer chemo-radiotherapy.     

Comprehensive Analysis of MicroRNA (miRNA) Targets in Breast Cancer Cells

MicroRNAs (miRNAs) regulate mRNA stability and translation through the action of the RNAi-induced silencing complex. In this study, we systematically identified endogenous miRNA target genes by using AGO2 immunoprecipitation (AGO2-IP) and microarray analyses in two breast cancer cell lines, MCF7 and MDA-MB-231, representing luminal and basal-like breast cancer, respectively. The expression levels of ∼70% of the AGO2-IP mRNAs were increased by DROSHA or DICER1 knockdown. In addition, integrated analysis of miRNA expression profiles, mRNA-AGO2 interaction, and the 3′-UTR of mRNAs revealed that >60% of the AGO2-IP mRNAs were putative targets of the 50 most abundantly expressed miRNAs. Together, these results suggested that the majority of the AGO2-associated mRNAs were bona fide miRNA targets. Functional enrichment analysis uncovered that the AGO2-IP mRNAs were involved in regulation of cell cycle, apoptosis, adhesion/migration/invasion, stress responses (e.g. DNA damage and endoplasmic reticulum stress and hypoxia), and cell-cell communication (e.g. Notch and Ephrin signaling pathways). A role of miRNAs in regulating cell migration/invasion and stress response was further defined by examining the impact of DROSHA knockdown on cell behaviors. We demonstrated that DROSHA knockdown enhanced cell migration and invasion, whereas it sensitized cells to cell death induced by suspension culture, glucose depletion, and unfolding protein stress. Data from an orthotopic xenograft model showed that DROSHA knockdown resulted in reduced growth of primary tumors but enhanced lung metastasis. Taken together, these results suggest that miRNAs collectively function to promote survival of tumor cells under stress but suppress cell migration/invasion in breast cancer cells.     

PEPstr: a de novo method for tertiary structure prediction of small bioactive peptides

Among secondary structure elements, beta-turns are ubiquitous and major feature of bioactive peptides. We analyzed 77 biologically active peptides with length varying from 9 to 20 residues. Out of 77 peptides, 58 peptides were found to contain at least one beta-turn. Further, at the residue level, 34.9% of total peptide residues were found to be in beta-turns, higher than the number of helical (32.3%) and beta-sheet residues (6.9%). So, we utilized the predicted beta-turns information to develop an improved method for predicting the three-dimensional (3D) structure of small peptides. In principle, we built four different structural models for each peptide. The first 'model I' was built by assigning all the peptide residues an extended conformation (phi = Psi = 180 degrees ). Second 'model II' was built using the information of regular secondary structures (helices, beta-strands and coil) predicted from PSIPRED. In third 'model III', secondary structure information including beta-turn types predicted from BetaTurns method was used. The fourth 'model IV' had main-chain phi, Psi angles of model III and side chain angles assigned using standard Dunbrack backbone dependent rotamer library. These models were further refined using AMBER package and the resultant C(alpha) rmsd values were calculated. It was found that adding the beta-turns to the regular secondary structures greatly reduces the rmsd values both before and after the energy minimization. Hence, the results indicate that regular and irregular secondary structures, particularly beta-turns information can provide valuable and vital information in the tertiary structure prediction of small bioactive peptides. Based on the above study, a web server PEPstr (http://www.imtech.res.in/raghava/pepstr/) was developed for predicting the tertiary structure of small bioactive peptides.