Three-dimensional quantitative structure-activity relationship (3D-QSAR) studies of tricyclic oxazolidinones as antibacterial agents

Oxazolidinones exemplified by eprezolid and linezolid are a new class of antibacterials that are active against Gram positive and anaerobic bacteria including methicillin-resistant Staphylococcus aureus (MRSA), methicillin-resistant Staphylococcus epidermidis (MRSE) and vancomycin resistant enterococci (VRE). In an effort to have a better antibacterial agent in the oxazolidinone class, we have performed three-dimensional quantitative structure-activity relationship (3D-QSAR) studies for a series of tricyclic oxazolidinones. 3D-QSAR studies were performed using the Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA) procedures. These studies were performed using 42 compounds; the QSAR model was developed using a training set of 33 compounds. The predictive ability of the QSAR model was assessed using a test set of 9 compounds. The predictive 3D-QSAR models have conventional r(2) values of 0.975 and 0.940 for CoMFA and CoMSIA respectively; similarly, cross-validated coefficient q(2) values of 0.523 and 0.557 for CoMFA and CoMSIA, respectively, were obtained. The CoMFA 3D-QSAR model performed better than the CoMSIA model.     

Isolation and molecular characterization of five entomopathogenic nematode species and their bacterial symbionts from eastern Australia

BioControl - Entomopathogenic nematodes (EPNs) are used in biological control of pest insects but their potential may be limited by strain availability from different bioregions and effectiveness...     

An ensemble framework for clustering protein-protein interaction networks

MOTIVATION: Protein-Protein Interaction (PPI) networks are believed to be important sources of information related to biological processes and complex metabolic functions of the cell. The presence of biologically relevant functional modules in these networks has been theorized by many researchers. However, the application of traditional clustering algorithms for extracting these modules has not been successful, largely due to the presence of noisy false positive interactions as well as specific topological challenges in the network. RESULTS: In this article, we propose an ensemble clustering framework to address this problem. For base clustering, we introduce two topology-based distance metrics to counteract the effects of noise. We develop a PCA-based consensus clustering technique, designed to reduce the dimensionality of the consensus problem and yield informative clusters. We also develop a soft consensus clustering variant to assign multifaceted proteins to multiple functional groups. We conduct an empirical evaluation of different consensus techniques using topology-based, information theoretic and domain-specific validation metrics and show that our approaches can provide significant benefits over other state-of-the-art approaches. Our analysis of the consensus clusters obtained demonstrates that ensemble clustering can (a) produce improved biologically significant functional groupings; and (b) facilitate soft clustering by discovering multiple functional associations for proteins. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.     

A synthetic 13-residue peptide corresponding to the hydrophobic region of bovine seminalplasmin has antibacterial activity and also causes lysis of red blood cells

Seminalplasmin (SPLN), a 47-residue peptide present in bovine seminal plasma, is one of the few proteins isolated from mammalian sources having potent antibacterial activity. SPLN also interacts with sperm acrosomal and plasma membranes. On the basis of analysis of the primary structure of SPLN with respect to its relative hydrophobicity and hydrophilicity, a region comprising of 13-amino acids, Pro-Lys-Leu-Leu-Glu-Thr-Phe-Leu-Ser-Lys-Trp-Ile-Gly, has been delineated. It is demonstrated that a synthetic peptide corresponding to this 13-residue region inhibits growth of Escherichia coli like SPLN and also has the ability to lyse red blood cells.     

Metabolites of purine nucleoside phosphorylase (NP) in serum have the potential to delineate pancreatic adenocarcinoma

Pancreatic Adenocarcinoma (PDAC), the fourth highest cause of cancer related deaths in the United States, has the most aggressive presentation resulting in a very short median survival time for the affected patients. Early detection of PDAC is confounded by lack of specific markers that has motivated the use of high throughput molecular approaches to delineate potential biomarkers. To pursue identification of a distinct marker, this study profiled the secretory proteome in 16 PDAC, 2 carcinoma in situ (CIS) and 7 benign patients using label-free mass spectrometry coupled to 1D-SDS-PAGE and Strong Cation-Exchange Chromatography (SCX). A total of 431 proteins were detected of which 56 were found to be significantly elevated in PDAC. Included in this differential set were Parkinson disease autosomal recessive, early onset 7 (PARK 7) and Alpha Synuclein (aSyn), both of which are known to be pathognomonic to Parkinson's disease as well as metabolic enzymes like Purine Nucleoside Phosphorylase (NP) which has been exploited as therapeutic target in cancers. Tissue Microarray analysis confirmed higher expression of aSyn and NP in ductal epithelia of pancreatic tumors compared to benign ducts. Furthermore, extent of both aSyn and NP staining positively correlated with tumor stage and perineural invasion while their intensity of staining correlated with the existence of metastatic lesions in the PDAC tissues. From the biomarker perspective, NP protein levels were higher in PDAC sera and furthermore serum levels of its downstream metabolites guanosine and adenosine were able to distinguish PDAC from benign in an unsupervised hierarchical classification model. Overall, this study for the first time describes elevated levels of aSyn in PDAC as well as highlights the potential of evaluating NP protein expression and levels of its downstream metabolites to develop a multiplex panel for non-invasive detection of PDAC.     

The GAP Activity of Type III Effector YopE Triggers Killing of Yersinia in Macrophages

The mammalian immune system has the ability to discriminate between pathogens and innocuous microbes by detecting conserved molecular patterns. In addition to conserved microbial patterns, the mammalian immune system may recognize distinct pathogen-induced processes through a mechanism which is poorly understood. Previous studies have shown that a type III secretion system (T3SS) in Yersinia pseudotuberculosis leads to decreased survival of this bacterium in primary murine macrophages by unknown mechanisms. Here, we use colony forming unit assays and fluorescence microscopy to investigate how the T3SS triggers killing of Yersinia in macrophages. We present evidence that Yersinia outer protein E (YopE) delivered by the T3SS triggers intracellular killing response against Yersinia. YopE mimics eukaryotic GTPase activating proteins (GAPs) and inactivates Rho GTPases in host cells. Unlike wild-type YopE, catalytically dead YopER144A is impaired in restricting Yersinia intracellular survival, highlighting that the GAP activity of YopE is detected as a danger signal. Additionally, a second translocated effector, YopT, counteracts the YopE triggered killing effect by decreasing the translocation level of YopE and possibly by competing for the same pool of Rho GTPase targets. Moreover, inactivation of Rho GTPases by Clostridium difficile Toxin B mimics the effect of YopE and promotes increased killing of Yersinia in macrophages. Using a Rac inhibitor NSC23766 and a Rho inhibitor TAT-C3, we show that macrophages restrict Yersinia intracellular survival in response to Rac1 inhibition, but not Rho inhibition. In summary, our findings reveal that primary macrophages sense manipulation of Rho GTPases by Yersinia YopE and actively counteract pathogenic infection by restricting intracellular bacterial survival. Our results uncover a new mode of innate immune recognition in response to pathogenic infection.     

A BLOC-1–AP-3 super-complex sorts a cis-SNARE complex into endosome-derived tubular transport carriers

Membrane transport carriers fuse with target membranes through engagement of cognate vSNAREs and tSNAREs on each membrane. How vSNAREs are sorted into transport carriers is incompletely understood. Here we show that VAMP7, the vSNARE for fusing endosome-derived tubular transport carriers with maturing melanosomes in melanocytes, is sorted into transport carriers in complex with the tSNARE component STX13. Sorting requires either recognition of VAMP7 by the AP-3δ subunit of AP-3 or of STX13 by the pallidin subunit of BLOC-1, but not both. Consequently, melanocytes expressing both AP-3δ and pallidin variants that cannot bind their respective SNARE proteins are hypopigmented and fail to sort BLOC-1–dependent cargo, STX13, or VAMP7 into transport carriers. However, SNARE binding does not influence BLOC-1 function in generating tubular transport carriers. These data reveal a novel mechanism of vSNARE sorting by recognition of redundant sorting determinants on a SNARE complex by an AP-3–BLOC-1 super-complex.