MALDI-TOF mass spectrometry as a tool for differentiation of invasive and noninvasive Streptococcus pyogenes isolates.

A novel mass spectral fingerprinting and proteomics approach using MALDI-TOF MS was applied to detect and identify protein biomarkers of group A Streptococcus (GAS) strains. Streptococcus pyogenes ATCC 700294 genome strain was compared with eight GAS clinical isolates to explore the ability of MALDI-TOF MS to differentiate isolates. Reference strains of other bacterial species were also analyzed and compared with the GAS isolates. MALDI preparations were optimized by varying solvents, matrices, plating techniques, and mass ranges for S. pyogenes ATCC 700294. Spectral variability was tested. A subset of common, characteristic, and reproducible biomarkers in the range of 2000-14 000 Da were detected, and they appeared to be independent of the culture media. Statistical analysis confirmed method reproducibility. Random Forest analysis of all selected GAS isolates revealed differences among most of them, and summed spectra were used for hierarchical cluster analysis. Specific biomarkers were found for each strain, and invasive GAS isolates could be differentiated. GAS isolates from cases of necrotizing fasciitis were clustered together and were distinct from isolates associated with noninvasive infections, despite their sharing the same emm type. Almost 30% of the biomarkers detected were tentatively identified as ribosomal proteins.

Altered Proteome of Extracellular Vesicles Derived from Bladder Cancer Patients Urine.

Proteomic analysis of extracellular vesicles (EVs) from biological fluid is a powerful approach to discover potential biomarkers for human diseases including cancers, as EV secreted to biological fluids are originated from the affected tissue. In order to investigate significant molecules related to the pathogenesis of bladder cancer, EVs were isolated from patient urine which was analyzed by mass spectrometry based proteomics. Comparison of the EV proteome to the whole urine proteome demonstrated an increased number of protein identification in EV. Comparative MS analyses of urinary EV from control subjects and bladder cancer patients identified a total of 1,222 proteins. Statistical analyses provided 56 proteins significantly increased in bladder cancer urine, including proteins for which expression levels varied by cancer stage (P-value < 0.05). While urine represents a valuable, noninvasive specimen for biomarker discovery in urologic cancers, there is a high degree of intra- and inter-individual variability in urine samples. The enrichment of urinary EV demonstrated its capability and applicability of providing a focused identification of biologically relevant proteins in urological diseases.

The determination of organophosphonate nerve agent metabolites in human urine by hydrophilic interaction liquid chromatography tandem mass spectrometry.

A sensitive, robust isotope dilution LC/MS/MS method is presented for the quantitative analysis of human urine for the alkyl methylphosphonic acid metabolites of five organophosphorus nerve agents (VX, rVX or VR, GB or Sarin, GD or Soman, and GF or Cyclosarin). The selective sample preparation method employs non-bonded silica solid-phase extraction and is partially automated. While working with a mobile phase composition that enhances the electrospray ionization process, the hydrophilic interaction chromatography method results in a 5-min injection-to-injection cycle time, excellent peak shapes and adequate retention (k'=3.1). These factors lead to limits of detection for these metabolites as low as 30 pg/mL in a 1-mL sample of human urine. The quality control data (15 and 75 ng/mL) demonstrate accurate (-0.5 to +3.4%) and precise (coefficients of variation of 2.1-3.6%) quantitative results over the clinically relevant urine concentration range of 1-200 ng/mL for a validation set of 20 standard and quality control sets prepared by five analysts over 54 days. The selectivity of the method is demonstrated for a 100-individual reference range study, as well as the analysis of relevant biological samples. The combined sample preparation and analysis portions of this method have a throughput of 288 samples per day.

Exosomal proteome analysis of cerebrospinal fluid detects biosignatures of neuromyelitis optica and multiple sclerosis.

Quantitative proteomic analysis of exosomes isolated from cerebrospinal fluid (CSF) of neuromyelitis optica (NMO) patients detected signature proteins differentiating NMO from multiple sclerosis (MS) and idiopathic longitudinally extensive transverse myelitis. Exosomes with good yields were obtained using ultracentrifugation from pooled CSF assisted by chemokine-based clustering strategy, which improved target molecule identification by providing amplified fold change values. 442 significant proteins generated a list of signature molecules of diseases validated primarily by the identification of known markers such as glial fibrillary acidic protein (GFAP) and fibronectin specific to NMO and MS respectively. MetaCore pathway analysis of significant proteins supported the involvement of these proteins in disease progression via neurological pathway. Expression levels of target molecules from orthogonal label-free quantification employing quadrupole-Orbitrap hybrid mass spectrometry were in good agreement with those from Western blotting. Additional investigation of GFAP and fibronectin as representative disease molecules revealed their presence in intact exosomes as detected by flow cytometry. This comprehensive study suggests that the exosomal proteomic analysis of CSF can be applied to the identification and characterization of inflammatory disorders of the central nervous system.

Identification of anti-metastatic drug and natural compound targets in isogenic colorectal cancer cells.

Therapeutic strategies for cancer treatment often remain challenging due to the cumulative risk derived from metastasis, which has been described as an aggressive state of cancer cell proliferation often resulting in failure of clinical therapy. In the current study, anti-metastatic properties of three chemotherapeutic drugs and three compounds from natural sources were investigated by comparative proteomic analysis. Proteomic profile comparison of the isogenic primary and metastatic colon cancer cell lines SW480 and SW620 identified two potential metastasis related molecular targets: fatty acid synthase and histone H4. To demonstrate their biological roles in cancer metastasis, the expression of these target genes was suppressed by siRNA transfection. Subsequent cell migration assays demonstrated reduced migratory effects. SW620 cells were treated with six anti-cancerous components. Through comprehensive proteomic analysis, three of the tested compounds, oxaliplatin, ginsenoside 20(S)-Rg3 and curcumin, were revealed to have a suppressive effect on FASN and histone H4 expression. SW620 cells treated with these drugs showed significantly reduced migratory activity, which suggests that drug-induced targeted suppression of these genes may affect cell migration. The validity of the proteomic datasets was verified by knowledgebase pathway analysis and immunoblotting assays. The anti-metastatic components revealed by the current proteomic analysis represent promising chemotherapeutic candidates for the treatment of colorectal adenocarcinoma. BIOLOGICAL SIGNIFICANCE: The current study demonstrates anti-metastatic activity of chemotherapeutics and natural components by the suppression of target molecules, fatty acid synthase and histone H4 identified by a comparative proteomic analysis employing the isogenic primary and metastatic colon cancer cell lines, SW480 and SW620. Three tested drugs, namely, oxaliplatin, ginsenoside 20(S)-Rg3 and curcumin were revealed to possess suppressive effects on fatty acid synthase and histone H4 and reduce metastasis as determined by cell migration assay. Data were confirmed by the correlation between spectral counts from proteomic data and Western blot analysis, which were in good agreement with immunohistochemistry.

A draft map of rhesus monkey tissue proteome for biomedical research.

Though the rhesus monkey is one of the most valuable non-human primate animal models for various human diseases because of its manageable size and genetic and proteomic similarities with humans, proteomic research using rhesus monkeys still remains challenging due to the lack of a complete protein sequence database and effective strategy. To investigate the most effective and high-throughput proteomic strategy, comparative data analysis was performed employing various protein databases and search engines. The UniProt databases of monkey, human, bovine, rat and mouse were used for the comparative analysis and also a universal database with all protein sequences from all available species was tested. At the same time, de novo sequencing was compared to the SEQUEST search algorithm to identify an optimal work flow for monkey proteomics. Employing the most effective strategy, proteomic profiling of monkey organs identified 3,481 proteins at 0.5% FDR from 9 male and 10 female tissues in an automated, high-throughput manner. Data are available via ProteomeXchange with identifier PXD001972. Based on the success of this alternative interpretation of MS data, the list of proteins identified from 12 organs of male and female subjects will benefit future rhesus monkey proteome research.

Data supporting the identification of anti-metastatic drug and natural compound targets in isogenic colorectal cancer cells.

To investigate molecular therapeutic targets in cancer metastasis, comparative proteomic analysis was performed using the isogenic colorectal cancer cell lines SW480 and SW620. Two potential metastasis related molecular targets were identified: fatty acid synthase and histone H4. Subsequently, metastatic SW620 cells were treated with six anti-cancerous components and suppressive effects were observed in target protein expression. Through comprehensive proteomic analysis, three of the tested compounds, oxaliplatin, ginsenoside 20(S)-Rg3 and curcumin, were determined to have a suppressive effect on fatty acid synthase and histone H4 expression [1]. The current article contains one table exhibiting a list of proteins differentially expressed in metastatic SW620 cell lines compared to the primary SW480 cell line (Supplementary Table 1). Additionally, six tables demonstrate proteome changes in SW620 resulting from the treatment of three chemotherapeutics and three natural components (Supplementary Tables 1-7). The anti-metastatic components revealed by the current proteomic analysis represent promising chemotherapeutic candidates for the treatment of colorectal adenocarcinoma.

From the mouse to the mass spectrometer: detection and differentiation of the endoproteinase activities of botulinum neurotoxins A-G by mass spectrometry.

We have developed an assay (Endopep-MS) that detects the specific endoproteinase activities of all seven BoNT types by mass spectrometry (MS). Each BoNT type cleaves a unique site on proteins involved in neuronal transmission. Target peptide substrates based on these proteins identify a BoNT type by its enzymatic action on the substrate and the production of two peptide products, which are then detected by matrix-assisted laser desorption/ionization time-of-flight MS or liquid chromatography electrospray ionization MS/MS. We showed the ability to detect all seven toxin types in a multiplexed assay format. The detection limits achieved range from 0.039 to 0.625 mouse LD(50)/mL for toxin types A, B, E, and F in a buffer system. The Endopep-MS assay is the first to differentiate all seven BoNT types, is sensitive, specific, and has the potential to quantify toxin activity.

Botulinum neurotoxin detection and differentiation by mass spectrometry.

Botulinum neurotoxins (BoNTs) are proteases that cleave specific cellular proteins essential for neurotransmitter release. Seven BoNT serotypes (A-G) exist; 4 usually cause human botulism (A, B, E, and F). We developed a rapid, mass spectrometry-based method (Endopep-MS) to detect and differentiate active BoNTs A, B, E, and F. This method uses the highly specific protease activity of the toxins with target peptides specific for each toxin serotype. The product peptides derived from the endopeptidase activities of BoNTs are detected by matrix-assisted laser-desorption ionization time-of-flight mass spectrometry. In buffer, this method can detect toxin equivalents of as little as 0.01 mouse lethal dose (MLD)50 and concentrations as low as 0.62 MLD50/mL. A high-performance liquid chromatography-tandem mass spectrometry method for quantifying active toxin, where the amount of toxin can be correlated to the amount of product peptides, is also described.

Standardization and denoising algorithms for mass spectra to classify whole-organism bacterial specimens.

MOTIVATION: Application of mass spectrometry in proteomics is a breakthrough in high-throughput analyses. Early applications have focused on protein expression profiles to differentiate among various types of tissue samples (e.g. normal versus tumor). Here our goal is to use mass spectra to differentiate bacterial species using whole-organism samples. The raw spectra are similar to spectra of tissue samples, raising some of the same statistical issues (e.g. non-uniform baselines and higher noise associated with higher baseline), but are substantially noisier. As a result, new preprocessing procedures are required before these spectra can be used for statistical classification. RESULTS: In this study, we introduce novel preprocessing steps that can be used with any mass spectra. These comprise a standardization step and a denoising step. The noise level for each spectrum is determined using only data from that spectrum. Only spectral features that exceed a threshold defined by the noise level are subsequently used for classification. Using this approach, we trained the Random Forest program to classify 240 mass spectra into four bacterial types. The method resulted in zero prediction errors in the training samples and in two test datasets having 240 and 300 spectra, respectively.