Strategies for proteomic analysis of blood glycated proteins

Comunicaciones a congreso

Quantitative analysis of protein glycation in clinical samples

Comunicaciones a congreso

Electron Transfer Dissociation Mass Spectrometry of Hemoglobin on Clinical Samples

A mass spectrometry-based assay combining the specificity of selected reaction monitoring and the protein ion activation capabilities of electron transfer dissociation was developed and employed for the rapid identification of hemoglobin variants from whole blood without previous proteolytic cleavage. The analysis was performed in a robust ion trap mass spectrometer operating at nominal mass accuracy and resolution. Subtle differences in globin sequences, resulting with mass shifts of about one Da, can be unambiguously identified. These results suggest that mass spectrometry analysis of entire proteins using electron transfer dissociation can be employed on clinical samples in a workflow compatible with diagnostic application

Precursor Ion Independent Algorithm for Top-Down Shotgun Proteomics

We present a precursor ion independent top-down algorithm (PIITA) for use in automated assignment of protein identifications from tandem mass spectra of whole proteins. To acquire the data, we utilize data-dependent acquisition to select protein precursor ions eluting from a C4-based HPLC column for collision induced dissociation in the linear ion trap of an LTQ-Orbitrap mass spectrometer. Gas-phase fractionation is used to increase the number of acquired tandem mass spectra, all of which are recorded in the Orbitrap mass analyzer. To identify proteins, the PIITA algorithm compares deconvoluted, deisotoped, observed tandem mass spectra to all possible theoretical tandem mass spectra for each protein in a genomic sequence database without regard for measured parent ion mass. Only after a protein is identified, is any difference in measured and theoretical precursor mass used to identify and locate post-translation modifications. We demonstrate the application of PIITA to data generated via our wet-lab approach on a Salmonella typhimurium outer membrane extract and compare these results to bottom-up analysis. From these data, we identify 154 proteins by top-down analysis, 73 of which were not identified in a parallel bottom-up analysis. We also identify 201 unique isoforms of these 154 proteins at a false discovery rate (FDR) of <1%

Clustering and Filtering Tandem Mass Spectra Acquired in Data-Independent Mode

Data-independent mass spectrometry activates all ion species isolated within a given mass-to-charge window (m/z) regardless of their abundance. This acquisition strategy overcomes the traditional data-dependent ion selection boosting data reproducibility and sensitivity. However, several tandem mass (MS/MS) spectra of the same precursor ion are acquired during chromatographic elution resulting in large data redundancy. Also, the significant number of chimeric spectra and the absence of accurate precursor ion masses hamper peptide identification. Here, we describe an algorithm to preprocess data-independent MS/MS spectra by filtering out noise peaks and clustering the spectra according to both the chromatographic elution profiles and the spectral similarity. In addition, we developed an approach to estimate the m/z value of precursor ions from clustered MS/MS spectra in order to improve database search performance. Data acquired using a small 3 m/z units precursor mass window and multiple injections to cover a m/z range of 400-1400 was processed with our algorithm. It showed an improvement in the number of both peptide and protein identifications by 8% while reducing the number of submitted spectra by 18% and the number of peaks by 55%. We conclude that our clustering method is a valid approach for data analysis of these data-independent fragmentation spectra. The software including the source code is available for the scientific community. Figure

Quantitative Clinical Chemistry Proteomics (qCCP) using mass spectrometry: general characteristics and application

Proteomics studies typically aim to exhaustively detect peptides/proteins in a given biological sample. Over the past decade, the number of publications using proteomics methodologies has exploded. This was made possible due to the availability of high-quality genomic data and many technological advances in the fields of microfluidics and mass spectrometry. Proteomics in biomedical research was initially used in ‘functional' studies for the identification of proteins involved in pathophysiological processes, complexes and networks. Improved sensitivity of instrumentation facilitated the analysis of even more complex sample types, including human biological fluids. It is at that point the field of clinical proteomics was born, and its fundamental aim was the discovery and (ideally) validation of biomarkers for the diagnosis, prognosis, or therapeutic monitoring of disease. Eventually, it was recognized that the technologies used in clinical proteomics studies [particularly liquid chromatography-tandem mass spectrometry (LC-MS/MS)] could represent an alternative to classical immunochemical assays. Prior to deploying MS in the measurement of peptides/proteins in the clinical laboratory, it seems likely that traditional proteomics workflows and data management systems will need to adapt to the clinical environment and meet in vitro diagnostic (IVD) regulatory constraints. This defines a new field, as reviewed in this article, that we have termed quantitative Clinical Chemistry Proteomics (qCCP

Daptomycin resistance mechanisms in clinically derived Staphylococcus aureus strains assessed by a combined transcriptomics and proteomics approach

Objectives The development of daptomycin resistance in Staphylococcus aureus is associated with clinical treatment failures. The mechanism(s) of such resistance have not been clearly defined. Methods We studied an isogenic daptomycin-susceptible (DAPS) and daptomycin-resistant (DAPR) S. aureus strain pair (616; 701) from a patient with relapsing endocarditis during daptomycin treatment, using comparative transcriptomic and proteomic techniques. Results Minor differences in the genome content were found between strains by DNA hybridization. Transcriptomic analyses identified a number of genes differentially expressed in important functional categories: cell division; metabolism of bacterial envelopes; and global regulation. Of note, the DAPR isolate exhibited reduced expression of the major cell wall autolysis gene coincident with the up-regulation of genes involved in cell wall teichoic acid production. Using quantitative (q)RT-PCR on the gene cadre putatively involved in cationic peptide resistance, we formulated a putative regulatory network compatible with microarray data sets, mainly implicating bacterial envelopes. Of interest, qRT-PCR of this same gene cadre from two distinct isogenic DAPS/DAPR clinical strain pairs revealed evidence of other strain-dependent networks operative in the DAPR phenotype. Comparative proteomics of 616 versus 701 revealed a differential abundance of proteins in various functional categories, including cell wall-associated targets and biofilm formation proteins. Phenotypically, strains 616 and 701 showed major differences in their ability to develop bacterial biofilms in the presence of the antibacterial lipid, oleic acid. Conclusions Compatible with previous in vitro observations, in vivo-acquired DAPR in S. aureus is a complex, multistep phenomenon involving: (i) strain-dependent phenotypes; (ii) transcriptome adaptation; and (iii) modification of the lipid and protein contents of cellular envelope

Exploring glycopeptide-resistance in Staphylococcus aureus: a combined proteomics and transcriptomics approach for the identification of resistance-related markers

BACKGROUND: To unravel molecular targets involved in glycopeptide resistance, three isogenic strains of Staphylococcus aureus with different susceptibility levels to vancomycin or teicoplanin were subjected to whole-genome microarray-based transcription and quantitative proteomic profiling. Quantitative proteomics performed on membrane extracts showed exquisite inter-experimental reproducibility permitting the identification and relative quantification of >30% of the predicted S. aureus proteome. RESULTS: In the absence of antibiotic selection pressure, comparison of stable resistant and susceptible strains revealed 94 differentially expressed genes and 178 proteins. As expected, only partial correlation was obtained between transcriptomic and proteomic results during stationary-phase. Application of massively parallel methods identified one third of the complete proteome, a majority of which was only predicted based on genome sequencing, but never identified to date. Several over-expressed genes represent previously reported targets, while series of genes and proteins possibly involved in the glycopeptide resistance mechanism were discovered here, including regulators, global regulator attenuator, hyper-mutability factor or hypothetical proteins. Gene expression of these markers was confirmed in a collection of genetically unrelated strains showing altered susceptibility to glycopeptides. CONCLUSION: Our proteome and transcriptome analyses have been performed during stationary-phase of growth on isogenic strains showing susceptibility or intermediate level of resistance against glycopeptides. Altered susceptibility had emerged spontaneously after infection with a sensitive parental strain, thus not selected in vitro. This combined analysis allows the identification of hundreds of proteins considered, so far as hypothetical protein. In addition, this study provides not only a global picture of transcription and expression adaptations during a complex antibiotic resistance mechanism but also unravels potential drug targets or markers that are constitutively expressed by resistant strains regardless of their genetic background, amenable to be used as diagnostic targets

Role of complement and antibodies in controlling infection with pathogenic simian immunodeficiency virus (SIV) in macaques vaccinated with replication-deficient viral vectors

<p>Abstract</p> <p>Background</p> <p>We investigated the interplay between complement and antibodies upon priming with single-cycle replicating viral vectors (SCIV) encoding SIV antigens combined with Adeno5-SIV or SCIV pseudotyped with murine leukemia virus envelope boosting strategies. The vaccine was applied via spray-immunization to the tonsils of rhesus macaques and compared with systemic regimens.</p> <p>Results</p> <p>Independent of the application regimen or route, viral loads were significantly reduced after challenge with SIVmac239 (p < 0.03) compared to controls. Considerable amounts of neutralizing antibodies were induced in systemic immunized monkeys. Most of the sera harvested during peak viremia exhibited a trend with an inverse correlation between complement C3-deposition on viral particles and plasma viral load within the different vaccination groups. In contrast, the amount of the observed complement-mediated lysis did not correlate with the reduction of SIV titres.</p> <p>Conclusion</p> <p>The heterologous prime-boost strategy with replication-deficient viral vectors administered exclusively via the tonsils did not induce any neutralizing antibodies before challenge. However, after challenge, comparable SIV-specific humoral immune responses were observed in all vaccinated animals. Immunization with single cycle immunodeficiency viruses mounts humoral immune responses comparable to live-attenuated immunodeficiency virus vaccines.</p

A Distinct Urinary Biomarker Pattern Characteristic of Female Fabry Patients That Mirrors Response to Enzyme Replacement Therapy

Female patients affected by Fabry disease, an X-linked lysosomal storage disorder, exhibit a wide spectrum of symptoms, which renders diagnosis, and treatment decisions challenging. No diagnostic test, other than sequencing of the alpha-galactosidase A gene, is available and no biomarker has been proven useful to screen for the disease, predict disease course and monitor response to enzyme replacement therapy. Here, we used urine proteomic analysis based on capillary electrophoresis coupled to mass spectrometry and identified a biomarker profile in adult female Fabry patients. Urine samples were taken from 35 treatment-naive female Fabry patients and were compared to 89 age-matched healthy controls. We found a diagnostic biomarker pattern that exhibited 88.2% sensitivity and 97.8% specificity when tested in an independent validation cohort consisting of 17 treatment-naive Fabry patients and 45 controls. The model remained highly specific when applied to additional control patients with a variety of other renal, metabolic and cardiovascular diseases. Several of the 64 identified diagnostic biomarkers showed correlations with measures of disease severity. Notably, most biomarkers responded to enzyme replacement therapy, and 8 of 11 treated patients scored negative for Fabry disease in the diagnostic model. In conclusion, we defined a urinary biomarker model that seems to be of diagnostic use for Fabry disease in female patients and may be used to monitor response to enzyme replacement therapy