6 resultados para Nanoelectrospray


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Purpose. To quantify the molecular lipid composition of patient-matched tear and meibum samples and compare tear and meibum lipid molecular profiles. Methods. Lipids were extracted from tears and meibum by bi-phasic methods using 10:3 tertbutyl methyl ether:methanol, washed with aqueous ammonium acetate, and analyzed by chipbased nanoelectrospray ionization tandem mass spectrometry. Targeted precursor ion and neutral loss scans identified individual molecular lipids and quantification was obtained by comparison to internal standards in each lipid class. Results. Two hundred and thirty-six lipid species were identified and quantified from nine lipid classes comprised of cholesterol esters, wax esters, (O-acyl)-x-hydroxy fatty acids, triacylglycerols, phosphatidylcholine, lysophosphatidylcholine, phosphatidylethanolamine, sphingomyelin, and phosphatidylserine. With the exception of phospholipids, lipid molecular profiles were strikingly similar between tears and meibum. Conclusions. Comparisons between tears and meibum indicate that meibum is likely to supply the majority of lipids in the tear film lipid layer. However, the observed higher mole ratio of phospholipid in tears shows that analysis of meibum alone does not provide a complete understanding of the tear film lipid composition.

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Numerous laboratory experiments have been performed in an attempt to mimic atmospheric secondary organic aerosol (SOA) formation. However, it is still unclear how close the aerosol particles generated in laboratory experiments resemble atmospheric SOA with respect to their detailed chemical composition. In this study, we generated SOA in a simulation chamber from the ozonolysis of α-pinene and a biogenic volatile organic compound (BVOC) mixture containing α- and β-pinene, Δ3-carene, and isoprene. The detailed molecular composition of laboratory-generated SOA was compared with that of background ambient aerosol collected at a boreal forest site (Hyytiälä, Finland) and an urban location (Cork, Ireland) using direct infusion nanoelectrospray ultrahigh resolution mass spectrometry. Kendrick Mass Defect and Van Krevelen approaches were used to identify and compare compound classes and distributions of the detected species. The laboratory-generated SOA contained a distinguishable group of dimers that was not observed in the ambient samples. The presence of dimers was found to be less pronounced in the SOA from the VOC mixtures when compared to the one component precursor system. The elemental composition of the compounds identified in the monomeric region from the ozonolysis of both α-pinene and VOC mixtures represented the ambient organic composition of particles collected at the boreal forest site reasonably well, with about 70% of common molecular formulae. In contrast, large differences were found between the laboratory-generated BVOC samples and the ambient urban sample. To our knowledge this is the first direct comparison of molecular composition of laboratory-generated SOA from BVOC mixtures and ambient samples.

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Only a small fraction of spectra acquired in LC-MS/MS runs matches peptides from target proteins upon database searches. The remaining, operationally termed background, spectra originate from a variety of poorly controlled sources and affect the throughput and confidence of database searches. Here, we report an algorithm and its software implementation that rapidly removes background spectra, regardless of their precise origin. The method estimates the dissimilarity distance between screened MS/MS spectra and unannotated spectra from a partially redundant background library compiled from several control and blank runs. Filtering MS/MS queries enhanced the protein identification capacity when searches lacked spectrum to sequence matching specificity. In sequence-similarity searches it reduced by, on average, 30-fold the number of orphan hits, which were not explicitly related to background protein contaminants and required manual validation. Removing high quality background MS/MS spectra, while preserving in the data set the genuine spectra from target proteins, decreased the false positive rate of stringent database searches and improved the identification of low-abundance proteins.

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The function of many of the uncharacterized open reading frames discovered by genomic sequencing can be determined at the level of expressed gene products, the proteome. However, identifying the cognate gene from minute amounts of protein has been one of the major problems in molecular biology. Using yeast as an example, we demonstrate here that mass spectrometric protein identification is a general solution to this problem given a completely sequenced genome. As a first screen, our strategy uses automated laser desorption ionization mass spectrometry of the peptide mixtures produced by in-gel tryptic digestion of a protein. Up to 90% of proteins are identified by searching sequence data bases by lists of peptide masses obtained with high accuracy. The remaining proteins are identified by partially sequencing several peptides of the unseparated mixture by nanoelectrospray tandem mass spectrometry followed by data base searching with multiple peptide sequence tags. In blind trials, the method led to unambiguous identification in all cases. In the largest individual protein identification project to date, a total of 150 gel spots—many of them at subpicomole amounts—were successfully analyzed, greatly enlarging a yeast two-dimensional gel data base. More than 32 proteins were novel and matched to previously uncharacterized open reading frames in the yeast genome. This study establishes that mass spectrometry provides the required throughput, the certainty of identification, and the general applicability to serve as the method of choice to connect genome and proteome.

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Oligomerization of receptor protein tyrosine kinases such as the epidermal growth factor receptor (EGFR) by their cognate ligands leads to activation of the receptor. Transphosphorylation of the receptor subunits is followed by the recruitment of signaling molecules containing src homology 2 (SH2) or phosphotyrosine interaction domains (PID). Additionally, several cytoplasmic proteins that may or may not associate with the receptor undergo tyrosine phosphorylation. To identify several components of the EGFR signaling pathway in a single step, we have immunoprecipitated molecules that are tyrosine phosphorylated in response to EGF and analyzed them by one-dimensional gel electrophoresis followed by mass spectrometry. Combining matrix-assisted laser desorption/ionization (MALDI) and nanoelectrospray tandem mass spectrometry (MS/MS) led to the identification of nine signaling molecules, seven of which had previously been implicated in EGFR signaling. Several of these molecules were identified from low femtomole levels of protein loaded onto the gel. We identified Vav-2, a recently discovered guanosine nucleotide exchange factor that is expressed ubiquitously, as a substrate of the EGFR. We demonstrate that Vav-2 is phosphorylated on tyrosine residues in response to EGF and associates with the EGFR in vivo. Binding of Vav-2 to the EGFR is mediated by the SH2 domain of Vav-2. In keeping with its ubiquitous expression, Vav-2 seems to be a general signaling molecule, since it also associates with the platelet-derived growth factor (PDGF) receptor and undergoes tyrosine phosphorylation in fibroblasts upon PDGF stimulation. The strategy suggested here can be used for routine identification of downstream components of cell surface receptors in mammalian cells.

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The Amazon Basin plays key role in atmospheric chemistry, biodiversity and climate change. In this study we applied nanoelectrospray (nanoESI) ultra-high-resolution mass spectrometry (UHRMS) for the analysis of the organic fraction of PM2.5 aerosol samples collected during dry and wet seasons at a site in central Amazonia receiving background air masses, biomass burning and urban pollution. Comprehensive mass spectral data evaluation methods (e.g. Kendrick mass defect, Van Krevelen diagrams, carbon oxidation state and aromaticity equivalent) were used to identify compound classes and mass distributions of the detected species. Nitrogen- and/or sulfur-containing organic species contributed up to 60 % of the total identified number of formulae. A large number of molecular formulae in organic aerosol (OA) were attributed to later-generation nitrogen- and sulfur-containing oxidation products, suggesting that OA composition is affected by biomass burning and other, potentially anthropogenic, sources. Isoprene-derived organosulfate (IEPOX-OS) was found to be the most dominant ion in most of the analysed samples and strongly followed the concentration trends of the gas-phase anthropogenic tracers confirming its mixed anthropogenic–biogenic origin. The presence of oxidised aromatic and nitro-aromatic compounds in the samples suggested a strong influence from biomass burning especially during the dry period. Aerosol samples from the dry period and under enhanced biomass burning conditions contained a large number of molecules with high carbon oxidation state and an increased number of aromatic compounds compared to that from the wet period. The results of this work demonstrate that the studied site is influenced not only by biogenic emissions from the forest but also by biomass burning and potentially other anthropogenic emissions from the neighbouring urban environments.