Development of combined micro -preparation, separation, and mass spectrometry methods and application in the microdialysis study of neuropeptide metabolism

Two sets of mass spectrometry-based methods were developed specifically for the in vivo study of extracellular neuropeptide biochemistry. First, an integrated micro-concentration/desalting/matrix-addition device was constructed for matrix-assisted laser desorption ionization mass spectrometry (MALDI MS) to achieve attomole sensitivity for microdialysis samples. Second, capillary electrophoresis (CE) was incorporated into the above micro-liquid chromatography (LC) and MALDI MS system to provide two-dimensional separation and identification (i.e. electrophoretic mobility and molecular mass) for the analysis of complex mixtures. The latter technique includes two parts of instrumentation: (1) the coupling of a preconcentration LC column to the inlet of a CE capillary, and (2) the utilization of a matrix-precoated membrane target for continuous CE effluent deposition and for automatic MALDI MS analysis (imaging) of the CE track.^ Initial in vivo data reveals a carboxypeptidase A (CPA) activity in rat brain involved in extracellular neurotensin metabolism. Benzylsuccinic acid, a CPA inhibitor, inhibited neurotensin metabolite NT1-12 formation by 70%, while inhibitors of other major extracellular peptide metabolizing enzymes increased NT1-12 formation. CPA activity has not been observed in previous in vitro experiments. Next, the validity of the methodology was demonstrated in the detection and structural elucidation of an endogenous neuropeptide, (L)VV-hemorphin-7, in rat brain upon ATP stimulation. Finally, the combined micro-LC/CE/MALDI MS was used in the in vivo metabolic study of peptide E, a mu-selective opioid peptide with 25 amino acid residues. Profiles of 88 metabolites were obtained, their identity being determined by their mass-to-charge ratio and electrophoretic mobility. The results indicate that there are several primary cleavage sites in vivo for peptide E in the release of its enkephalin-containing fragments. ^

Extreme temperature events analyzed with Fast Fourier Transform

Extreme weather and climate events have received increased attention in the last few years, due to the often large loss of agriculture business and exponentially increasing costs associated with them and insurance planning. This increased attention raises the question as to whether extreme weather and climate events are truly increasing, whether this is only a perceived increase exacerbated by enhanced media coverage, or both. There are a number of ways extreme climate events can be defined, such as extreme daily temperatures, extreme daily rainfall amounts, and large areas experiencing unusually warm monthly temperatures, among others. In this study, we will focus our attention in frost and heatstroke events measuring it as the number of days under 0 ºC and number of days with daily maximum over 30ºC monthly respectively. We have studied the trends in these extreme events applying a Fast Fourier Transform to the series to clarify the tendency. Lack of long-term climate data suitable for analysis of extremes is the single biggest obstacle to quantifying whether extreme events have changed over the twentieth century, including high temporal and spatial resolution observations of temperatures. However, several series have been grouped in different ways: chosen the longest series independently, by provinces, by main watersheds and altitude. On the other hand, synthetic series generated by Luna and Balairón (AEMet) were also analyzed. The results obtained by different pooling data are discussed concluding the difficulties to assess the extreme events tendencies and high regional variation in the trends.

Comparison of metaheuristic strategies for peakbin selection in proteomic mass spectrometry data

Mass spectrometry (MS) data provide a promising strategy for biomarker discovery. For this purpose, the detection of relevant peakbins in MS data is currently under intense research. Data from mass spectrometry are challenging to analyze because of their high dimensionality and the generally low number of samples available. To tackle this problem, the scientific community is becoming increasingly interested in applying feature subset selection techniques based on specialized machine learning algorithms. In this paper, we present a performance comparison of some metaheuristics: best first (BF), genetic algorithm (GA), scatter search (SS) and variable neighborhood search (VNS). Up to now, all the algorithms, except for GA, have been first applied to detect relevant peakbins in MS data. All these metaheuristic searches are embedded in two different filter and wrapper schemes coupled with Naive Bayes and SVM classifiers.

Plasma dynamics studies by mass spectrometry techniques

We present temporal information obtained by mass spectrometry techniques about the evolution of plasmas generated by laser filamentation in air. The experimental setup used in this work allowed us to study not only the dynamics of the filament core but also of the energy reservoir that surrounds it. Furthermore, valuable insights about the chemistry of such systems like the photofragmentation and/or formation of molecules were obtained. The interpretation of the experimental results are supported by PIC simulations.

Multiresidue Analysis of Insecticides and Other Selected Environmental Contaminants in Poultry Manure by Gas Chromatography/Mass Spectrometry

An analytical method was developed for the simultaneous determination in poultry manure of 41 organic contaminants belonging to different chemical classes: pesticides, polycyclic aromatic hydrocarbons, polychlorinated biphenyls, and polybrominated diphenyl ethers. Poultry manure was extracted with a modified QuEChERS method, and the extracts were analyzed by isotope dilution GC/MS. Recovery of these contaminants from samples spiked at levels ranging from 25 to 100 ng/g was satisfactory for all the compounds. The developed procedure provided LODs from 0.8 to 9.6 ng/g. The analysis of poultry manure samples collected on different farms confirmed the presence of some of the studied contaminants. Pyrethroids and polycyclic aromatic hydrocarbons were the main contaminants detected.

Identification by mass spectrometry of the phosphorylated residue responsible for activation of the catalytic domain of myosin I heavy chain kinase, a member of the PAK/STE20 family

Myosin I heavy chain kinase from Acanthamoeba castellanii is activated in vitro by autophosphorylation (8–10 mol of P per mol). The catalytically active C-terminal domain produced by trypsin cleavage of the phosphorylated kinase contains 2–3 mol of P per mol. However, the catalytic domain expressed in a baculovirus–insect cell system is fully active as isolated without autophosphorylation in vitro. We now show that the expressed catalytic domain is inactivated by incubation with acid phosphatase and regains activity upon autophosphorylation. The state of phosphorylation of all of the hydroxyamino acids in the catalytic domain were determined by mass spectrometry of unfractionated protease digests. Ser-627 was phosphorylated in the active, expressed catalytic domain, lost its phosphate when the protein was incubated with phosphatase, and was rephosphorylated when the dephosphorylated protein was incubated with ATP. No other residue was significantly phosphorylated in any of the three samples. Thus, phosphorylation of Ser-627, which is in the same position as the Ser and Thr residues that are phosphorylated in many other kinases, is necessary and sufficient for full activity of the catalytic domain. Ser-627 is also phosphorylated when full-length, native kinase is activated by autophosphorylation.

Linking genome and proteome by mass spectrometry: Large-scale identification of yeast proteins from two dimensional gels

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.

Analysis of receptor signaling pathways by mass spectrometry: Identification of Vav-2 as a substrate of the epidermal and platelet-derived growth factor receptors

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.

Fourier transform infrared spectroscopy reveals a rigid α-helical assembly for the tetrameric Streptomyces lividans K+ channel

The structure of the tetrameric K+ channel from Streptomyces lividans in a lipid bilayer environment was studied by polarized attenuated total reflection Fourier transform infrared spectroscopy. The channel displays approximately 43% α-helical and 25% β-sheet content. In addition, H/D exchange experiments show that only 43% of the backbone amide protons are exchangeable with solvent. On average, the α-helices are tilted 33° normal to the membrane surface. The results are discussed in relationship to the lactose permease of Escherichia coli, a membrane transport protein.