Biomedical subjects

Ronald J Moore

Publications and source records attributed to Ronald J Moore.

At least 19 recordsLinked to original sources

PubMed2026

Proteogenomic analysis of pediatric and AYA high-grade glioma reveals age-dependent biology, female-male differences, and kinase targets.

High-grade gliomas (HGGs) in children and adolescents and young adults (AYA) exhibit distinct biology across the neurodevelopmental spectrum. To dissect tumor-intrinsic molecular characteristics independent of developmental variation, we perform comprehensive proteogenomic analyses of tumors from 112 HGG patients aged 0-40 years. Our multi-omics analysis identifies two AYA subgroups-adolescents (aged 15-26 years) and young adults (aged 26-40 years)-with distinct molecular profiles and survival outcomes. Tumor-normal comparisons and survival modeling highlight roles of oxidative phosphorylation and neuronal system biology in glioma progression. Causal network analysis and cell line studies provide a rationale for personalized therapies targeting candidate kinases, such as CDK8. Survival modeling, clustering, and immune-landscape analyses identify proteins, post-translational modifications, and immune signatures linked to outcomes and reveal clinically relevant differences between male and female patients.

adolescent and young adult glioma↗

PubMed2024

Proteome-Scale Tissue Mapping Using Mass Spectrometry Based on Label-Free and Multiplexed Workflows.

Multiplexed bimolecular profiling of tissue microenvironment, or spatial omics, can provide deep insight into cellular compositions and interactions in healthy and diseased tissues. Proteome-scale tissue mapping, which aims to unbiasedly visualize all the proteins in a whole tissue section or region of interest, has attracted significant interest because it holds great potential to directly reveal diagnostic biomarkers and therapeutic targets. While many approaches are available, however, proteome mapping still exhibits significant technical challenges in both protein coverage and analytical throughput. Since many of these existing challenges are associated with mass spectrometry-based protein identification and quantification, we performed a detailed benchmarking study of three protein quantification methods for spatial proteome mapping, including label-free, TMT-MS2, and TMT-MS3. Our study indicates label-free method provided the deepest coverages of ∼3500 proteins at a spatial resolution of 50 μm and the highest quantification dynamic range, while TMT-MS2 method holds great benefit in mapping throughput at >125 pixels per day. The evaluation also indicates both label-free and TMT-MS2 provides robust protein quantifications in identifying differentially abundant proteins and spatially covariable clusters. In the study of pancreatic islet microenvironment, we demonstrated deep proteome mapping not only enables the identification of protein markers specific to different cell types, but more importantly, it also reveals unknown or hidden protein patterns by spatial coexpression analysis.

Proteome↗

PubMed2024

Proteome-scale tissue mapping using mass spectrometry based on label-free and multiplexed workflows.

Multiplexed bimolecular profiling of tissue microenvironment, or spatial omics, can provide deep insight into cellular compositions and interactions in healthy and diseased tissues. Proteome-scale tissue mapping, which aims to unbiasedly visualize all the proteins in a whole tissue section or region of interest, has attracted significant interest because it holds great potential to directly reveal diagnostic biomarkers and therapeutic targets. While many approaches are available, however, proteome mapping still exhibits significant technical challenges in both protein coverage and analytical throughput. Since many of these existing challenges are associated with mass spectrometry-based protein identification and quantification, we performed a detailed benchmarking study of three protein quantification methods for spatial proteome mapping, including label-free, TMT-MS2, and TMT-MS3. Our study indicates label-free method provided the deepest coverages of ~3500 proteins at a spatial resolution of 50 µm and the highest quantification dynamic range, while TMT-MS2 method holds great benefit in mapping throughput at >125 pixels per day. The evaluation also indicates both label-free and TMT-MS2 provide robust protein quantifications in identifying differentially abundant proteins and spatially co-variable clusters. In the study of pancreatic islet microenvironment, we demonstrated deep proteome mapping not only enables the identification of protein markers specific to different cell types, but more importantly, it also reveals unknown or hidden protein patterns by spatial co-expression analysis.

Journal Article↗

PubMed2013

The identification of novel potential injury mechanisms and candidate biomarkers in renal allograft rejection by quantitative proteomics.

Early transplant dysfunction and failure because of immunological and nonimmunological factors still presents a significant clinical problem for transplant recipients. A critical unmet need is the noninvasive detection and prediction of immune injury such that acute injury can be reversed by proactive immunosuppression titration. In this study, we used iTRAQ -based proteomic discovery and targeted ELISA validation to discover and validate candidate urine protein biomarkers from 262 renal allograft recipients with biopsy-confirmed allograft injury. Urine samples were randomly split into a training set of 108 patients and an independent validation set of 154 patients, which comprised the clinical biopsy-confirmed phenotypes of acute rejection (AR) (n = 74), stable graft (STA) (n = 74), chronic allograft injury (CAI) (n = 58), BK virus nephritis (BKVN) (n = 38), nephrotic syndrome (NS) (n = 8), and healthy, normal control (HC) (n = 10). A total of 389 proteins were measured that displayed differential abundances across urine specimens of the injury types (p < 0.05) with a significant finding that SUMO2 (small ubiquitin-related modifier 2) was identified as a "hub" protein for graft injury irrespective of causation. Sixty-nine urine proteins had differences in abundance (p < 0.01) in AR compared with stable graft, of which 12 proteins were up-regulated in AR with a mean fold increase of 2.8. Nine urine proteins were highly specific for AR because of their significant differences (p < 0.01; fold increase >1.5) from all other transplant categories (HLA class II protein HLA-DRB1, KRT14, HIST1H4B, FGG, ACTB, FGB, FGA, KRT7, DPP4). Increased levels of three of these proteins, fibrinogen beta (FGB; p = 0.04), fibrinogen gamma (FGG; p = 0.03), and HLA DRB1 (p = 0.003) were validated by ELISA in AR using an independent sample set. The fibrinogen proteins further segregated AR from BK virus nephritis (FGB p = 0.03, FGG p = 0.02), a finding that supports the utility of monitoring these urinary proteins for the specific and sensitive noninvasive diagnosis of acute renal allograft rejection.

Acute Kidney Injury↗

PubMed2006

Chemically etched open tubular and monolithic emitters for nanoelectrospray ionization mass spectrometry.

We have developed a new procedure for fabricating fused-silica emitters for electrospray ionization-mass spectrometry (ESI-MS) in which the end of a bare fused-silica capillary is immersed into aqueous hydrofluoric acid, and water is pumped through the capillary to prevent etching of the interior. Surface tension causes the etchant to climb the capillary exterior, and the etch rate in the resulting meniscus decreases as a function of distance from the bulk solution. Etching continues until the silica touching the hydrofluoric acid reservoir is completely removed, essentially stopping the etch process. The resulting emitters have no internal taper, making them much less prone to clogging compared to, e.g., pulled emitters. The high aspect ratios and extremely thin walls at the orifice facilitate very low flow rate operation; stable ESI-MS signals were obtained for model analytes from 5-microm-diameter emitters at a flow rate of 5 nL/min with a high degree of interemitter reproducibility. In extensive evaluation, the etched emitters were found to enable approximately four times as many LC-MS analyses of proteomic samples before failing compared with conventional pulled emitters. The fabrication procedure was also employed to taper the ends of polymer monolith-containing silica capillaries for use as ESI emitters. In contrast to previous work, the monolithic material protrudes beyond the fused-silica capillaries, improving the monolith-assisted electrospray process.

Hydrofluoric Acid↗

PubMed2006

Protein composition of the vaccinia virus mature virion.

The protein content of vaccinia virus mature virions, purified by rate zonal and isopycnic centrifugations and solubilized by SDS or a solution of urea and thiourea, was determined by the accurate mass and time tag technology which uses both tandem mass spectrometry and Fourier transform-ion cyclotron resonance mass spectrometry to detect tryptic peptides separated by high-resolution liquid chromatography. Eighty vaccinia virus-encoded proteins representing 37% of the 218 genes annotated in the complete genome sequence were detected in at least three analyses. Ten proteins accounted for approximately 80% of the virion mass. Thirteen identified proteins were not previously reported as components of virions. On the other hand, 8 previously described virion proteins were not detected here, presumably due to technical reasons including small size and hydrophobicity. In addition to vaccinia virus-encoded proteins, 24 host proteins omitting isoforms were detected. The most abundant of these were cytoskeletal proteins, heat shock proteins and proteins involved in translation.

Centrifugation, Isopycnic↗

PubMed2006

LC-MS/MS based proteomic analysis and functional inference of hypothetical proteins in Desulfovibrio vulgaris.

High efficiency capillary liquid chromatography-tandem mass spectrometry (LC-MS/MS) was used to examine the proteins extracted from Desulfovibrio vulgaris cells across six treatment conditions. While our previous study provided a proteomic overview of the cellular metabolism based on proteins with known functions [W. Zhang, M.A. Gritsenko, R.J. Moore, D.E. Culley, L. Nie, K. Petritis, E.F. Strittmatter, D.G. Camp II, R.D. Smith, F.J. Brockman, A proteomic view of the metabolism in Desulfovibrio vulgaris determined by liquid chromatography coupled with tandem mass spectrometry, Proteomics 6 (2006) 4286-4299], this study describes the global detection and functional inference for hypothetical D. vulgaris proteins. Using criteria that a given peptide of a protein is identified from at least two out of three independent LC-MS/MS measurements and that for any protein at least two different peptides are identified among the three measurements, 129 open reading frames (ORFs) originally annotated as hypothetical proteins were found to encode expressed proteins. Functional inference for the conserved hypothetical proteins was performed by a combination of several non-homology based methods: genomic context analysis, phylogenomic profiling, and analysis of a combination of experimental information, including peptide detection in cells grown under specific culture conditions and cellular location of the proteins. Using this approach we were able to assign possible functions to 20 conserved hypothetical proteins. This study demonstrated that a combination of proteomics and bioinformatics methodologies can provide verification of the expression of hypothetical proteins and improve genome annotation.

Amino Acid Sequence↗

PubMed2006

Evaluation of multiprotein immunoaffinity subtraction for plasma proteomics and candidate biomarker discovery using mass spectrometry.

Strategies for removal of high abundance proteins have been increasingly utilized in proteomic studies of serum/plasma and other body fluids to enhance the detection of low abundance proteins and achieve broader proteome coverage; however, both the reproducibility and specificity of the high abundance protein depletion process still represent common concerns. Here we report a detailed evaluation of immunoaffinity subtraction performed applying the ProteomeLab IgY-12 system that is commonly used in human serum/plasma proteome characterization in combination with high resolution LC-MS/MS. Plasma samples were repeatedly processed using this approach, and the resulting flow-through fractions and bound fractions were individually analyzed for comparison. The removal of target proteins by the immunoaffinity subtraction system and the overall process was highly reproducible. Non-target proteins, including one spiked protein standard (rabbit glyceraldehyde-3-phosphate dehydrogenase), were also observed to bind to the column at different levels but also in a reproducible manner. The results suggest that multiprotein immunoaffinity subtraction systems can be readily integrated into quantitative strategies to enhance detection of low abundance proteins in biomarker discovery studies.

Biomarkers↗

PubMed2006

Improved peptide elution time prediction for reversed-phase liquid chromatography-MS by incorporating peptide sequence information.

We describe an improved artificial neural network (ANN)-based method for predicting peptide retention times in reversed-phase liquid chromatography. In addition to the peptide amino acid composition, this study investigated several other peptide descriptors to improve the predictive capability, such as peptide length, sequence, hydrophobicity and hydrophobic moment, and nearest-neighbor amino acid, as well as peptide predicted structural configurations (i.e., helix, sheet, coil). An ANN architecture that consisted of 1052 input nodes, 24 hidden nodes, and 1 output node was used to fully consider the amino acid residue sequence in each peptide. The network was trained using approximately 345,000 nonredundant peptides identified from a total of 12,059 LC-MS/MS analyses of more than 20 different organisms, and the predictive capability of the model was tested using 1303 confidently identified peptides that were not included in the training set. The model demonstrated an average elution time precision of approximately 1.5% and was able to distinguish among isomeric peptides based upon the inclusion of peptide sequence information. The prediction power represents a significant improvement over our earlier report (Petritis, K.; Kangas, L. J.; Ferguson, P. L.; Anderson, G. A.; Pasa-Tolic, L.; Lipton, M. S.; Auberry, K. J.; Strittmatter, E. F.; Shen, Y.; Zhao, R.; Smith, R. D. Anal. Chem. 2003, 75, 1039-1048) and other previously reported models.

Amino Acid Sequence↗

PubMed2006

High dynamic range characterization of the trauma patient plasma proteome.

Although human plasma represents an attractive sample for disease biomarker discovery, the extreme complexity and large dynamic range in protein concentrations present significant challenges for characterization, candidate biomarker discovery, and validation. Herein we describe a strategy that combines immunoaffinity subtraction and subsequent chemical fractionation based on cysteinyl peptide and N-glycopeptide captures with two-dimensional LC-MS/MS to increase the dynamic range of analysis for plasma. Application of this "divide-and-conquer" strategy to trauma patient plasma significantly improved the overall dynamic range of detection and resulted in confident identification of 22,267 unique peptides from four different peptide populations (cysteinyl peptides, non-cysteinyl peptides, N-glycopeptides, and non-glycopeptides) that covered 3,654 different proteins with 1,494 proteins identified by multiple peptides. Numerous low abundance proteins were identified, exemplified by 78 "classic" cytokines and cytokine receptors and by 136 human cell differentiation molecules. Additionally a total of 2,910 different N-glycopeptides that correspond to 662 N-glycoproteins and 1,553 N-glycosylation sites were identified. A panel of the proteins identified in this study is known to be involved in inflammation and immune responses. This study established an extensive reference protein database for trauma patients that provides a foundation for future high throughput quantitative plasma proteomic studies designed to elucidate the mechanisms that underlie systemic inflammatory responses.

Blood Proteins↗

PubMed2006

Differential label-free quantitative proteomic analysis of Shewanella oneidensis cultured under aerobic and suboxic conditions by accurate mass and time tag approach.

We describe the application of LC-MS without the use of stable isotope labeling for differential quantitative proteomic analysis of whole cell lysates of Shewanella oneidensis MR-1 cultured under aerobic and suboxic conditions. LC-MS/MS was used to initially identify peptide sequences, and LC-FTICR was used to confirm these identifications as well as measure relative peptide abundances. 2343 peptides covering 668 proteins were identified with high confidence and quantified. Among these proteins, a subset of 56 changed significantly using statistical approaches such as statistical analysis of microarrays, whereas another subset of 56 that were annotated as performing housekeeping functions remained essentially unchanged in relative abundance. Numerous proteins involved in anaerobic energy metabolism exhibited up to a 10-fold increase in relative abundance when S. oneidensis was transitioned from aerobic to suboxic conditions.

Amino Acid Sequence↗

PubMed2006

A proteomic view of Desulfovibrio vulgaris metabolism as determined by liquid chromatography coupled with tandem mass spectrometry.

Direct LC-MS/MS was used to examine the proteins extracted from exponential or stationary phase Desulfovibrio vulgaris cells that had been grown on a minimal medium containing either lactate or formate as the primary carbon source. Across all four growth conditions, 976 gene products were identified with high confidence, which is equal to approximately 28% of all predicted proteins in the D. vulgaris genome. Bioinformatic analysis showed that the proteins identified were distributed among almost all functional classes, with the energy metabolism category containing the greatest number of identified proteins. At least 154 ORFs originally annotated as hypothetical proteins were found to encode the expressed proteins, which provided verification for the authenticity of these hypothetical proteins. Proteomic analysis showed that proteins potentially involved in ATP biosynthesis using the proton gradient across membrane, such as ATPase, alcohol dehydrogenases, heterodisulfide reductases, and [NiFe] hydrogenase (HynAB-1) of the hydrogen cycling were highly expressed in all four growth conditions, suggesting they may be the primary pathways for ATP synthesis in D. vulgaris. Most of the enzymes involved in substrate-level phosphorylation were also detected in all tested conditions. However, no enzyme involved in CO cycling or formate cycling was detected, suggesting that they are not the primary ATP-biosynthesis pathways under the tested conditions. This study provides the first proteomic overview of the cellular metabolism of D. vulgaris. The complete list of proteins identified in this study and their abundances (peptide hits) is provided in Supplementary Table 1.

Alcohol Dehydrogenase↗

PubMed2006

Characterization of the mouse brain proteome using global proteomic analysis complemented with cysteinyl-peptide enrichment.

We report a global proteomic approach for analyzing brain tissue and for the first time a comprehensive characterization of the whole mouse brain proteome. Preparation of the whole brain sample incorporated a highly efficient cysteinyl-peptide enrichment (CPE) technique to complement a global enzymatic digestion method. Both the global and the cysteinyl-enriched peptide samples were analyzed by SCX fractionation coupled with reversed phase LC-MS/MS analysis. A total of 48,328 different peptides were confidently identified (>98% confidence level), covering 7792 nonredundant proteins ( approximately 34% of the predicted mouse proteome). A total of 1564 and 1859 proteins were identified exclusively from the cysteinyl-peptide and the global peptide samples, respectively, corresponding to 25% and 31% improvements in proteome coverage compared to analysis of only the global peptide or cysteinyl-peptide samples. The identified proteins provide a broad representation of the mouse proteome with little bias evident due to protein pI, molecular weight, and/or cellular localization. Approximately 26% of the identified proteins with gene ontology (GO) annotations were membrane proteins, with 1447 proteins predicted to have transmembrane domains, and many of the membrane proteins were found to be involved in transport and cell signaling. The MS/MS spectrum count information for the identified proteins was used to provide a measure of relative protein abundances. The mouse brain peptide/protein database generated from this study represents the most comprehensive proteome coverage for the mammalian brain to date, and the basis for future quantitative brain proteomic studies using mouse models. The proteomic approach presented here may have broad applications for rapid proteomic analyses of various mouse models of human brain diseases.

Animals↗

PubMed2006

More sensitive and quantitative proteomic measurements using very low flow rate porous silica monolithic LC columns with electrospray ionization-mass spectrometry.

The sensitivity of proteomics measurements using liquid chromatography (LC) separations interfaced with electrospray ionization-mass spectrometry (ESI-MS) improves approximately inversely with liquid flow rate (for the columns having the same separation efficiency, linear velocity, and porosity), making attractive the use of smaller inner diameter LC columns. We report the development and initial application of 10 microm i.d. silica-based monolithic LC columns providing more sensitive proteomics measurements. A 50-microm-i.d. micro solid-phase extraction precolumn was used for ease of sample injection and cleanup prior to the reversed-phase LC separation, enabling the sample volume loading speed to be increased by approximately 50-fold. Greater than 10-fold improvement in sensitivity was obtained compared to analyses using more conventional capillary LC, enabling e.g. the identification of >5000 different peptides by MS/MS from 100-ng of a Shewanella oneidensis tryptic digest using an ion trap MS. The low nL/min LC flow rates provide more uniform responses for different peptides, and provided improved quantitative measurements compared to conventional separation systems without the use of internal standards or isotopic labeling. The improved sensitivity allowed LC-MS measurements of immunopurified protein phosphatase 5 that were in good agreement with quantitative Western blot analyses.

Amino Acid Sequence↗

PubMed2006

Biomarker candidate identification in Yersinia pestis using organism-wide semiquantitative proteomics.

The accurate mass and time tag mass spectrometry method and clustering analysis were used to compare the abundance change of 992 Yersinia pestis proteins under four contrasting growth conditions (26 and 37 degrees C, with or without Ca2+) that mimicked growth states in either a flea vector or mammalian host. Eighty-nine proteins were observed to have similar abundance change profiles to 29 known virulence associated proteins, providing identification of additional biomarker candidates. Eighty-seven hypothetical proteins, which clustered into 5 distinct clusters of like-protein abundance change, were identified as unique biomarkers related specifically to growth condition.

Bacterial Proteins↗

PubMed2005

Making broad proteome protein measurements in 1-5 min using high-speed RPLC separations and high-accuracy mass measurements.

The throughput of proteomics measurements that provide broad protein coverage is limited by the quality and speed of both the separations as well as the subsequent mass spectrometric analysis; at present, analysis times can range anywhere from hours (high throughput) to days or longer (low throughput). We have explored the basis for proteomics analyses conducted on the order of minutes using high-speed capillary RPLC combined through on-line electrospray ionization interface with high-accuracy mass spectrometry (MS) measurements. Short 0.8-microm porous C18 particle-packed 50-microm-i.d. capillaries were used to speed the RPLC separations while still providing high-quality separations. Both time-of-flight (TOF) and Fourier transform ion cyclotron resonance (FTICR) MS were applied for identifying peptides using the accurate mass and time (AMT) tag approach. Peptide RPLC relative retention (elution) times that were generated by solvent gradients that differed by at least 25-fold were found to provide relative elution times that agreed to within 5%, which provides the basis for using peptide AMT tags for higher throughput proteomics measurements. For fast MS acquisition speeds (e.g., 0.2 s for TOF and either approximately 0.3 or approximately 0.6 s for FTICR), peptide mass measurement accuracies of better than +/-15 ppm were obtained with the high-speed RPLC separations. The ability to identify peptides and the overall proteome coverage was determined by factors that include the separation peak capacity, the sensitivity of the MS (with fast scanning), and the accuracy of both the mass measurements and the relative RPLC peptide elution times. The experimental RPLC relative elution time accuracies of 5% (using high-speed capillary RPLC) and mass measurement accuracies of better than +/-15 ppm allowed for the confident identification of >2800 peptides and >760 proteins from >13,000 different putative peptides detected from a Shewanellaoneidensis tryptic digest. Initial results for both RPLC-ESI-TOF and RPLC-ESI-FTICR MS were similar, with approximately 2000 different peptides from approximately 600 different proteins identified within 2-3 min. For <120-s proteomic analysis, TOF MS analyses were more effective, while FTICR MS was more effective for the >150-s analysis due to the improved mass accuracies attained using longer spectrum acquisition times.

Animals↗

PubMed2005

Preparation of 20-microm-i.d. silica-based monolithic columns and their performance for proteomics analyses.

We describe the preparation and performance of high-efficiency 70 cm x 20 microm i.d. silica-based monolithic capillary LC columns. The monolithic columns at a mobile-phase pressure of 5000 psi provide flow rates of approximately 40 nL/min at a linear velocity of approximately 0.24 cm/s. The columns provide a separation peak capacity of approximately 420 in conjunction with both on-line coupling with microsolid-phase extraction and nanoelectrospray ionization-mass spectrometry. Performance was evaluated using a Shewanella oneidensis tryptic digest, and approximately 15-amol detection limits for peptides were obtained using a conventional ion trap and MS/MS for peptide identification. The sensitivity and separation efficiency enabled the identification of 2367 different peptides covering 855 distinct S. oneidensis proteins from a 2.5-microg tryptic digest sample in a single 10-h analysis. The number of identified peptides and proteins approximately doubled when the effective separation time was extended from 200 to 600 min. The number of identified peptides increased from 32 to 390 as the injection amount was increased from 0.5 to 100 ng. Both the run-to-run and column-to-column reproducibility for proteomic analyses were also evaluated.

Chromatography, Liquid↗

PubMed2005

Automated 20 kpsi RPLC-MS and MS/MS with chromatographic peak capacities of 1000-1500 and capabilities in proteomics and metabolomics.

Proteomics analysis based-on reversed-phase liquid chromatography (RPLC) is widely practiced; however, variations providing cutting-edge RPLC performance have generally not been adopted even though their benefits are well established. Here, we describe an automated format 20 kpsi RPLC system for proteomics and metabolomics that includes on-line coupling of micro-solid phase extraction for sample loading and allows electrospray ionization emitters to be readily replaced. The system uses 50 microm i.d. x 40-200 cm fused-silica capillaries packed with 1.4-3-microm porous C18-bonded silica particles to obtain chromatographic peak capacities of 1000-1500 for complex peptide and metabolite mixtures. This separation quality provided high-confidence identifications of >12 000 different tryptic peptides from >2000 distinct Shewanella oneidensis proteins (approximately 40% of the proteins predicted for the S. oneidensis proteome) in a single 12-h ion trap tandem mass spectrometry (MS/MS) analysis. The protein identification reproducibility approached 90% between replicate experiments. The average protein MS/MS identification rate exceeded 10 proteins/min, and 1207 proteins were identified in 120 min through assignment of 5944 different peptides. The proteomic analysis dynamic range of the 20 kpsi RPLC-ion trap MS/MS was approximately 10(6) based on analyses of a human blood plasma sample, for which 835 distinct proteins were identified with high confidence in a single 12-h run. A single run of the 20 kpsi RPLC-accurate mass MS detected >5000 different compounds from a metabolomics sample.

Automation↗