Quantitative proteomics in resected renal cancer tissue for biomarker discovery and profiling

<b>Background:</b>  Proteomics-based approaches for biomarker discovery are promising strategies used in cancer research. We present state-of-art label-free quantitative proteomics method to assess proteome of renal cell carcinoma (RCC) compared with noncancer renal tissues.<p></p> <b>Methods:</b>  Fresh frozen tissue samples from eight primary RCC lesions and autologous adjacent normal renal tissues were obtained from surgically resected tumour-bearing kidneys. Proteins were extracted by complete solubilisation of tissues using filter-aided sample preparation (FASP) method. Trypsin digested proteins were analysed using quantitative label-free proteomics approach followed by data interpretation and pathways analysis.<p></p> <b>Results:</b>  A total of 1761 proteins were identified and quantified with high confidence (MASCOT ion score threshold of 35 and P-value <0.05). Of these, 596 proteins were identified as differentially expressed between cancer and noncancer tissues. Two upregulated proteins in tumour samples (adipose differentiation-related protein and Coronin 1A) were further validated by immunohistochemistry. Pathway analysis using IPA, KOBAS 2.0, DAVID functional annotation and FLink tools showed enrichment of many cancer-related biological processes and pathways such as oxidative phosphorylation, glycolysis and amino acid synthetic pathways.<p></p> <b>Conclusions:<b>  Our study identified a number of differentially expressed proteins and pathways using label-free proteomics approach in RCC compared with normal tissue samples. Two proteins validated in this study are the focus of on-going research in a large cohort of patients.<p></p&gt

Identification and functional characterization of a highly divergent N-acetylglucosaminyltransferase I (TbGnTI) in <em>Trypanosoma brucei</em>

Trypanosoma brucei expresses a diverse repertoire of N-glycans, ranging from oligomannose and paucimannose structures to exceptionally large complex N-glycans. Despite the presence of the latter, no obvious homologues of known β1–4-galactosyltransferase or β1–2- or β1–6-N-acetylglucosaminyltransferase genes have been found in the parasite genome. However, we previously reported a family of putative UDP-sugar-dependent glycosyltransferases with similarity to the mammalian β1–3-glycosyltransferase family. Here we characterize one of these genes, TbGT11, and show that it encodes a Golgi apparatus resident UDP-GlcNAc:α3-d-mannoside β1–2-N-acetylglucosaminyltransferase I activity (TbGnTI). The bloodstream-form TbGT11 null mutant exhibited significantly modified protein N-glycans but normal growth in vitro and infectivity to rodents. In contrast to multicellular organisms, where the GnTI reaction is essential for biosynthesis of both complex and hybrid N-glycans, T. brucei TbGT11 null mutants expressed atypical “pseudohybrid” glycans, indicating that TbGnTII activity is not dependent on prior TbGnTI action. Using a functional in vitro assay, we showed that TbGnTI transfers UDP-GlcNAc to biantennary Man(3)GlcNAc(2), but not to triantennary Man(5)GlcNAc(2), which is the preferred substrate for metazoan GnTIs. Sequence alignment reveals that the T. brucei enzyme is far removed from the metazoan GnTI family and suggests that the parasite has adapted the β3-glycosyltransferase family to catalyze β1–2 linkages

Towards an automated analysis of bacterial peptidoglycan structure.

Peptidoglycan (PG) is an essential component of the bacterial cell envelope. This macromolecule consists of glycan chains alternating N-acetylglucosamine and N-acetylmuramic acid, cross-linked by short peptides containing nonstandard amino acids. Structural analysis of PG usually involves enzymatic digestion of glycan strands and separation of disaccharide peptides by reversed-phase HPLC followed by collection of individual peaks for MALDI-TOF and/or tandem mass spectrometry. Here, we report a novel strategy using shotgun proteomics techniques for a systematic and unbiased structural analysis of PG using high-resolution mass spectrometry and automated analysis of HCD and ETD fragmentation spectra with the Byonic software. Using the PG of the nosocomial pathogen Clostridium difficile as a proof of concept, we show that this high-throughput approach allows the identification of all PG monomers and dimers previously described, leaving only disambiguation of 3-3 and 4-3 cross-linking as a manual step. Our analysis confirms previous findings that C. difficile peptidoglycans include mainly deacetylated N-acetylglucosamine residues and 3-3 cross-links. The analysis also revealed a number of low abundance muropeptides with peptide sequences not previously reported. Graphical Abstract The bacterial cell envelope includes plasma membrane, peptidoglycan, and surface layer. Peptidoglycan is unique to bacteria and the target of the most important antibiotics; here it is analyzed by mass spectrometry

Characterization of Modular Bacteriophage Endolysins from Myoviridae Phages OBP, 201ϕ2-1 and PVP-SE1

Peptidoglycan lytic enzymes (endolysins) induce bacterial host cell lysis in the late phase of the lytic bacteriophage replication cycle. Endolysins OBPgp279 (from Pseudomonas fluorescens phage OBP), PVP-SE1gp146 (Salmonella enterica serovar Enteritidis phage PVP-SE1) and 201ϕ2-1gp229 (Pseudomonas chlororaphis phage 201ϕ2-1) all possess a modular structure with an N-terminal cell wall binding domain and a C-terminal catalytic domain, a unique property for endolysins with a Gram-negative background. All three modular endolysins showed strong muralytic activity on the peptidoglycan of a broad range of Gram-negative bacteria, partly due to the presence of the cell wall binding domain. In the case of PVP-SE1gp146, this domain shows a binding affinity for Salmonella peptidoglycan that falls within the range of typical cell adhesion molecules (Kaff = 1.26×106 M−1). Remarkably, PVP-SE1gp146 turns out to be thermoresistant up to temperatures of 90°C, making it a potential candidate as antibacterial component in hurdle technology for food preservation. OBPgp279, on the other hand, is suggested to intrinsically destabilize the outer membrane of Pseudomonas species, thereby gaining access to their peptidoglycan and exerts an antibacterial activity of 1 logarithmic unit reduction. Addition of 0.5 mM EDTA significantly increases the antibacterial activity of the three modular endolysins up to 2–3 logarithmic units reduction. This research work offers perspectives towards elucidation of the structural differences explaining the unique biochemical and antibacterial properties of OBPgp279, PVP-SE1gp146 and 201ϕ2-1gp229. Furthermore, these endolysins extensively enlarge the pool of potential antibacterial compounds used against multi-drug resistant Gram-negative bacterial infections

A genetic algorithm-Bayesian network approach for the analysis of metabolomics and spectroscopic data: application to the rapid detection of Bacillus spores and identification of Bacillus species

Background The rapid identification of Bacillus spores and bacterial identification are paramount because of their implications in food poisoning, pathogenesis and their use as potential biowarfare agents. Many automated analytical techniques such as Curie-point pyrolysis mass spectrometry (Py-MS) have been used to identify bacterial spores giving use to large amounts of analytical data. This high number of features makes interpretation of the data extremely difficult We analysed Py-MS data from 36 different strains of aerobic endospore-forming bacteria encompassing seven different species. These bacteria were grown axenically on nutrient agar and vegetative biomass and spores were analyzed by Curie-point Py-MS. Results We develop a novel genetic algorithm-Bayesian network algorithm that accurately identifies sand selects a small subset of key relevant mass spectra (biomarkers) to be further analysed. Once identified, this subset of relevant biomarkers was then used to identify Bacillus spores successfully and to identify Bacillus species via a Bayesian network model specifically built for this reduced set of features. Conclusions This final compact Bayesian network classification model is parsimonious, computationally fast to run and its graphical visualization allows easy interpretation of the probabilistic relationships among selected biomarkers. In addition, we compare the features selected by the genetic algorithm-Bayesian network approach with the features selected by partial least squares-discriminant analysis (PLS-DA). The classification accuracy results show that the set of features selected by the GA-BN is far superior to PLS-DA

Sterilization of hydrogen peroxide resistant bacterial spores with stabilized chlorine dioxide

Bacillus pumilus SAFR-032 spores isolated from a clean room environment are known to exhibit enhanced resistance to peroxide, desiccation, UV radiation and chemical disinfection than other spore-forming bacteria. The survival of B. pumilus SAFR-032 spores to standard clean room sterilization practices requires development of more stringent disinfection agents. Here, we report the effects of a stabilized chlorine dioxide-based biocidal agent against spores of B. pumilus SAFR-032 and Bacillus subtilis ATCC 6051. Viability was determined via CFU measurement after exposure. Chlorine dioxide demonstrated efficacy towards sterilization of spores of B. pumilus SAFR-032 equivalent or better than exposure to hydrogen peroxide. These results indicate efficacy of chlorine dioxide delivered through a stabilized chlorine dioxide product as a means of sterilization of peroxide- and UV-resistant spores.This work is supported by the National Institutes of Health (1R01GM090064-01), a NASA EPSCoR Research Infrastructure Development (RID) grant NN07AL49A, and the University of Oklahoma.Ye