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DaRue A Prieto

Publications and source records attributed to DaRue A Prieto.

6 recordsLinked to original sources

Identification of the SELDI ProteinChip human serum retentate by microcapillary liquid chromatography-tandem mass spectrometry.

Surface-enhanced laser desorption/ionization (SELDI) time-of-flight (TOF) mass spectrometry (MS) has been widely applied for conducting biomarker research with the goal of discovering patterns of proteins and/or peptides from biological samples that reflect disease status. Many diseases, ranging from cancers of the colon, breast, and prostate to Alzheimer's disease, have been studied through serum protein profiling using SELDI-based methods. Although the results from SELDI-based diagnostic studies have generated a great deal of excitement and skepticism alike, the basis of the molecular identities of the features that underpin the diagnostic potential of the mass spectra is still largely unexplored. A detailed investigation has been undertaken to identify the compliment of serum proteins that bind to the commonly used weak cation exchange (WCX-2) SELDI protein chip. Following incubation and washing of a standard serum sample on the WCX-2 sorbent, proteins were harvested, digested with trypsin, fractionated by strong cation exchange liquid chromatography (LC), and subsequently analyzed by microcapillary reversed-phase LC coupled online with an ion-trap mass spectrometer. This analysis resulted in the identification of 383 unique proteins in the WCX-2 serum retentate. Among the proteins identified, 50 (13%) are documented clinical biomarkers with 36 of these (72%) identified from multiple peptides.

Biomarkers↗

Liquid Tissue: proteomic profiling of formalin-fixed tissues.

Identification and quantitation of candidate biomarker proteins in large numbers of individual tissues is required to validate specific proteins, or panels of proteins, for clinical use as diagnostic, prognostic, toxicological, or therapeutic markers. Mass spectrometry (MS) provides an exciting analytical methodology for this purpose. Liquid Tissue MS protein preparation allows researchers to utilize the vast, already existing, collections offormalin-fixed paraffin-embedded (FFPE) tissues for the procurement of peptides and the analysis across a variety of MS platforms.

Chromatography, Liquid↗

Organic solvent extraction of proteins and peptides from serum as an effective sample preparation for detection and identification of biomarkers by mass spectrometry.

A method to extract peptides and low molecular weight proteins from serum under denaturing conditions using acetonitrile containing 0.1% trifluoroacetic acid has been developed. The extraction procedure precipitates large, abundant proteins to simplify subsequent mass spectral analysis. This sample preparation method provides an efficient way to extract serum peptides, enabling them to be compared and identified using different mass spectrometry approaches. Surface-enhanced laser desorption/ionization-time of flight mass spectrometry analysis of mouse blood serum samples prepared by this method allowed detection of two markers which were significantly reduced in mice with B cell lymphoma tumor. One of these markers has been identified as apolipoprotein A-II.

Acetonitriles↗

Characterization of the low molecular weight human serum proteome.

Serum potentially carries an archive of important histological information whose determination could serve to improve early disease detection. The analysis of serum, however, is analytically challenging due to the high dynamic concentration range of constituent protein/peptide species, necessitating extensive fractionation prior to mass spectrometric analyses. The low molecular weight (LMW) serum proteome is that protein/peptide fraction from which high molecular weight proteins, such as albumin, immunoglobulins, transferrin, and lipoproteins, have been removed. This LMW fraction is made up of several classes of physiologically important proteins such as cytokines, chemokines, peptide hormones, as well as proteolytic fragments of larger proteins. Centrifugal ultrafiltration of serum was used to remove the large constituent proteins resulting in the enrichment of the LMW proteins/peptides. Because albumin is known to bind and transport small molecules and peptides within the circulatory system, the centrifugal ultrafiltration was conducted under solvent conditions effecting the disruption of protein-protein interactions. The LMW serum proteome sample was digested with trypsin, fractionated by strong cation exchange chromatography, and analyzed by microcapillary reversed-phase liquid chromatography coupled on-line with electrospray ionization tandem mass spectrometry. Analysis of the tandem mass spectra resulted in the identification of over 340 human serum proteins; however, not a single peptide from serum albumin was observed. The large number of proteins identified demonstrates the efficacy of this method for the removal of large abundant proteins and the enrichment of the LMW serum proteome.

Blood Proteins↗

The use of urine proteomic and metabonomic patterns for the diagnosis of interstitial cystitis and bacterial cystitis.

The advent of systems biology approaches that have stemmed from the sequencing of the human genome has led to the search for new methods to diagnose diseases. While much effort has been focused on the identification of disease-specific biomarkers, recent efforts are underway toward the use of proteomic and metabonomic patterns to indicate disease. We have developed and contrasted the use of both proteomic and metabonomic patterns in urine for the detection of interstitial cystitis (IC). The methodology relies on advanced bioinformatics to scrutinize information contained within mass spectrometry (MS) and high-resolution proton nuclear magnetic resonance (1H-NMR) spectral patterns to distinguish IC-affected from non-affected individuals as well as those suffering from bacterial cystitis (BC). We have applied a novel pattern recognition tool that employs an unsupervised system (self-organizing-type cluster mapping) as a fitness test for a supervised system (a genetic algorithm). With this approach, a training set comprised of mass spectra and 1H-NMR spectra from urine derived from either unaffected individuals or patients with IC is employed so that the most fit combination of relative, normalized intensity features defined at precise m/z or chemical shift values plotted in n-space can reliably distinguish the cohorts used in training. Using this bioinformatic approach, we were able to discriminate spectral patterns associated with IC-affected, BC-affected, and unaffected patients with a success rate of approximately 84%.

Bacterial Infections↗