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David G Camp

Publications and source records attributed to David G Camp.

At least 19 recordsLinked to original sources

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↗

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↗

Advances and challenges in liquid chromatography-mass spectrometry-based proteomics profiling for clinical applications.

Recent advances in proteomics technologies provide tremendous opportunities for biomarker-related clinical applications; however, the distinctive characteristics of human biofluids such as the high dynamic range in protein abundances and extreme complexity of the proteomes present tremendous challenges. In this review we summarize recent advances in LC-MS-based proteomics profiling and its applications in clinical proteomics as well as discuss the major challenges associated with implementing these technologies for more effective candidate biomarker discovery. Developments in immunoaffinity depletion and various fractionation approaches in combination with substantial improvements in LC-MS platforms have enabled the plasma proteome to be profiled with considerably greater dynamic range of coverage, allowing many proteins at low ng/ml levels to be confidently identified. Despite these significant advances and efforts, major challenges associated with the dynamic range of measurements and extent of proteome coverage, confidence of peptide/protein identifications, quantitation accuracy, analysis throughput, and the robustness of present instrumentation must be addressed before a proteomics profiling platform suitable for efficient clinical applications can be routinely implemented.

Biomarkers↗

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↗

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↗

Endogenously nitrated proteins in mouse brain: links to neurodegenerative disease.

Increased abundance of nitrotyrosine modifications of proteins have been documented in multiple pathologies in a variety of tissue types and play a role in the redox regulation of normal metabolism. To identify proteins sensitive to nitrating conditions in vivo, a comprehensive proteomic data set identifying 7792 proteins from a whole mouse brain, generated by LC/LC-MS/MS analyses, was used to identify nitrated proteins. This analysis resulted in the identification of 31 unique nitrotyrosine sites within 29 different proteins. More than half of the nitrated proteins that have been identified are involved in Parkinson's disease, Alzheimer's disease, or other neurodegenerative disorders. Similarly, nitrotyrosine immunoblots of whole brain homogenates show that treatment of mice with 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP), an experimental model of Parkinson's disease, induces an increased level of nitration of the same protein bands observed to be nitrated in brains of untreated animals. Comparing sequences and available high-resolution structures around nitrated tyrosines with those of unmodified sites indicates a preference of nitration in vivo for surface accessible tyrosines in loops, a characteristic consistent with peroxynitrite-induced tyrosine modification. In addition, most sequences contain cysteines or methionines proximal to nitrotyrosines, contrary to suggestions that these amino acid side chains prevent tyrosine nitration. More striking is the presence of a positively charged moiety near the sites of nitration, which is not observed for non-nitrated tyrosines. Together, these observations suggest a predictive tool of functionally important sites of nitration and that cellular nitrating conditions play a role in neurodegenerative changes in the brain.

1-Methyl-4-phenyl-1,2,3,6-tetrahydropyridine↗

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↗

HepatoProteomics: applying proteomic technologies to the study of liver function and disease.

The wealth of human genome sequence information now available, coupled with technological advances in robotics, nanotechnology, mass spectrometry, and information systems, has given rise to a method of scientific inquiry known as functional genomics. By using these technologies to survey gene expression and protein production on a near global scale, the goal of functional genomics is to assign biological function to genes with currently unknown roles in physiology. This approach carries particular appeal in disease research, where it can uncover the function of previously unknown genes and molecular pathways that are directly involved in disease progression. With this knowledge may come improved diagnostic techniques, prognostic capabilities, and novel therapeutic approaches. In this regard, the continuing evolution of proteomic technologies has resulted in an increasingly greater impact of proteome studies in many areas of research and hepatology is no exception. Our laboratory has been extremely active in this area, applying both genomic and proteomic technologies to the analysis of virus-host interactions in several systems, including the study of hepatitis C virus (HCV) infection and HCV-associated liver disease. Since proteomic technologies are foreign to many hepatologists (and to almost everyone else), this article will provide an overview of proteomic methods and technologies and describe how they are being used to study liver function and disease.

Humans↗

Proteome analysis of mitochondrial outer membrane from Neurospora crassa.

The mitochondrial outer membrane mediates numerous interactions between the metabolic and genetic systems of mitochondria and the rest of the eukaryotic cell. We performed a proteomic study to discover novel functions of components of the mitochondrial outer membrane. Proteins of highly pure outer membrane vesicles (OMV) from Neurospora crassa were identified by a combination of LC-MS/MS of tryptic peptide digests and gel electrophoresis of solubilized OMV proteins, followed by their identification using MALDI-MS PMF. Among the 30 proteins found in at least three of four separate analyses were 23 proteins with known functions in the outer membrane. These included components of the import machinery (the TOM and TOB complexes), a pore-forming component (porin), and proteins that control fusion and fission of the organelle. In addition, proteins playing a role in various biosynthetic pathways, whose intracellular location had not been established previously, could be localized to the mitochondrial outer membrane. Thus, the proteome of the outer membrane can help in identifying new mitochondria-related functions.

DNA, Recombinant↗

Quantitative proteome analysis of breast cancer cell lines using 18O-labeling and an accurate mass and time tag strategy.

Proteome comparison of cell lines derived from cancer and normal breast epithelium provide opportunities to identify differentially expressed proteins and pathways associated with specific phenotypes. We employed 16O/18O peptide labeling, FT-ICR MS, and an accurate mass and time (AMT) tag strategy to simultaneously compare the relative abundance of hundreds of proteins in non-cancer and cancer cell lines derived from breast tissue. A cell line reference panel allowed relative protein abundance comparisons among multiple cell lines and across multiple experiments. A peptide database generated from multidimensional LC separations and MS/MS analysis was used for subsequent AMT tag-based peptide identifications. This peptide database represented a total of 2299 proteins, including 514 that were quantified in five cell lines using the AMT tag and 16O/18O strategies. Eighty-six proteins showed at least a threefold protein abundance change between cancer and non-cancer cell lines. Hierarchical clustering of protein abundance ratios revealed that several groups of proteins were differentially expressed between the cancer cell lines.

Breast Neoplasms↗

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↗

Phosphoproteome profiling of human skin fibroblast cells in response to low- and high-dose irradiation.

A hallmark of the response to high-dose radiation is the up-regulation and phosphorylation of proteins involved in cell cycle checkpoint control, DNA damage signaling, DNA repair, and apoptosis. Exposure of cells to low doses of radiation has well documented biological effects, but the underlying regulatory mechanisms are still poorly understood. The objective of this study is to provide an initial profile of the normal human skin fibroblast (HSF) phosphoproteome and explore potential differences between low- and high-dose irradiation responses at the protein phosphorylation level. Several techniques including Trizol extraction of proteins, methylation of tryptic peptides, enrichment of phosphopeptides with immobilized metal affinity chromatography (IMAC), nanoflow reversed-phase HPLC (nano-LC)/electrospray ionization, and tandem mass spectrometry were combined for analysis of the HSF cell phosphoproteome. Among 494 unique phosphopeptides, 232 were singly phosphorylated, while 262 peptides had multiple phosphorylation sites indicating the overall effectiveness of the IMAC technique to enrich both singly and multiply phosphorylated peptides. We observed approximately 1.9-fold and approximately 3.6-fold increases in the number of identified phosphopeptides in low-dose and high-dose samples respectively, suggesting both radiation levels stimulate cell signaling pathways. A 6-fold increase in the phosphorylation of cyclin dependent kinase (cdk) motifs was observed after low- dose irradiation, while high-dose irradiation stimulated phosphorylation of 3-phosphoinositide-dependent protein kinase-1 (PDK1) and AKT/RSK motifs 8.5- and 5.5-fold, respectively. High- dose radiation resulted in the increased phosphorylation of proteins involved in cell signaling pathways as well as apoptosis while low-dose and control phosphoproteins were broadly distributed among biological processes.

3-Phosphoinositide-Dependent Protein Kinases↗

Characterization of the human pancreatic islet proteome by two-dimensional LC/MS/MS.

The pancreatic beta-cell plays a central role in the maintenance of glucose homeostasis and in the pathogenesis of both type 1 and type 2 diabetes mellitus. Elucidation of the insulin secretory defects observed in diabetes first requires a better understanding of the complex mechanisms regulating insulin secretion, which are only partly understood. While there have been reports detailing proteomic analyses of islet cell lines or isolated rodent islets, the information gained is not always applicable to humans. Therefore, definition of the human islet proteome could contribute to a better understanding of islet biology and lead to more effective treatment strategies. We have applied a two-dimensional LC-MS/MS-based analysis to the characterization of the human islet proteome, resulting in the confident identification of 29,021 different tryptic peptides covering 3365 proteins (> or =2 unique peptide identifications per protein). As expected, the three major islet hormones (insulin, glucagon, and somatostatin) were detected, as well as various beta-cell enriched secretory products, ion channels, and transcription factors. In addition, significant proteome coverage of metabolic enzymes and cellular pathways was observed, including the integrin signaling cascade and the MAP kinase, NF-kappa beta, and JAK/STAT pathways. The resulting peptide reference library provides a resource for future higher throughput and quantitative studies of islet biology.

Chromatography, Liquid↗

Sites of proteolytic processing and noncovalent association of the distal C-terminal domain of CaV1.1 channels in skeletal muscle.

In skeletal muscle cells, voltage-dependent potentiation of Ca2+ channel activity requires phosphorylation by cAMP-dependent protein kinase (PKA) anchored via an A-kinase anchoring protein (AKAP15), and the most rapid sites of phosphorylation are located in the C-terminal domain. Surprisingly, the site of interaction of the complex of PKA and AKAP15 with the alpha1-subunit of Ca(V)1.1 channels lies in the distal C terminus, which is cleaved from the remainder of the channel by in vivo proteolytic processing. Here we report that the distal C terminus is noncovalently associated with the remainder of the channel via an interaction with a site in the proximal C-terminal domain when expressed as a separate protein in mammalian nonmuscle cells. Deletion mapping of the C terminus of the alpha1-subunit using the yeast two-hybrid assay revealed that a distal C-terminal peptide containing amino acids 1802-1841 specifically interacts with a region in the proximal C terminus containing amino acid residues 1556-1612. Analysis of the purified alpha1-subunit of Ca(V)1.1 channels from skeletal muscle by saturation sequencing of the intracellular peptides by tandem mass spectrometry identified the site of proteolytic processing as alanine 1664. Our results support the conclusion that a noncovalently associated complex of the alpha1-subunit truncated at A1664 with the proteolytically cleaved distal C-terminal domain, AKAP15, and PKA is the primary physiological form of Ca(V)1.1 channels in skeletal muscle cells.

Amino Acid Sequence↗

Quantitative proteome analysis of human plasma following in vivo lipopolysaccharide administration using 16O/18O labeling and the accurate mass and time tag approach.

Identification of novel diagnostic or therapeutic biomarkers from human blood plasma would benefit significantly from quantitative measurements of the proteome constituents over a range of physiological conditions. Herein we describe an initial demonstration of proteome-wide quantitative analysis of human plasma. The approach utilizes postdigestion trypsin-catalyzed 16O/18O peptide labeling, two-dimensional LC-FTICR mass spectrometry, and the accurate mass and time (AMT) tag strategy to identify and quantify peptides/proteins from complex samples. A peptide accurate mass and LC elution time AMT tag data base was initially generated using MS/MS following extensive multidimensional LC separations to provide the basis for subsequent peptide identifications. The AMT tag data base contains >8,000 putative identified peptides, providing 938 confident plasma protein identifications. The quantitative approach was applied without depletion of high abundance proteins for comparative analyses of plasma samples from an individual prior to and 9 h after lipopolysaccharide (LPS) administration. Accurate quantification of changes in protein abundance was demonstrated by both 1:1 labeling of control plasma and the comparison between the plasma samples following LPS administration. A total of 429 distinct plasma proteins were quantified from the comparative analyses, and the protein abundances for 25 proteins, including several known inflammatory response mediators, were observed to change significantly following LPS administration.

Blood Proteins↗

Targeted comparative proteomics by liquid chromatography-tandem Fourier ion cyclotron resonance mass spectrometry.

In proteomics, effective methods are needed for identifying the relatively limited subset of proteins displaying significant changes in abundance between two samples. One way to accomplish this task is to target for identification by MS/MS only the "interesting" proteins based on the abundance ratio of isotopically labeled pairs of peptides. We have developed the software and hardware tools for online LC-FTICR MS/MS studies in which a set of initially unidentified peptides from a proteome analysis can be selected for identification based on their distinctive changes in abundance following a "perturbation". We report here the validation of this method using a mixture of standard proteins combined in different ratios after isotopic labeling. We also demonstrate the application of this method to the identification of Shewanella oneidensis peptides/proteins exhibiting differential abundance in suboxic versus aerobic cell cultures.

Bacterial Proteins↗

Comparative proteome analyses of human plasma following in vivo lipopolysaccharide administration using multidimensional separations coupled with tandem mass spectrometry.

There is significant interest in characterization of the human plasma proteome due to its potential for providing biomarkers applicable to clinical diagnosis and treatment and for gaining a better understanding of human diseases. We describe here a strategy for comparative proteome analyses of human plasma, which is applicable to biomarker identifications for various disease states. Multidimensional liquid chromatography-mass spectrometry (LC-MS/MS) has been applied to make comparative proteome analyses of plasma samples from an individual prior to and 9 h after lipopolysaccharide (LPS) administration. Peptide peak areas and the number of peptide identifications for each protein were used to evaluate the reproducibility of LC-MS/MS and to compare relative changes in protein concentration between the samples following LPS treatment. A total of 804 distinct plasma proteins (not including immunoglobulins) were confidently identified with 32 proteins observed to be significantly increased in concentration following LPS administration, including several known inflammatory response or acute-phase mediators such as C-reactive protein, serum amyloid A and A2, LPS-binding protein, LPS-responsive and beige-like anchor protein, hepatocyte growth factor activator, and von Willebrand factor, and thus, constituting potential biomarkers for inflammatory response.

Blood Proteins↗

Proteomic analysis of Lyme disease: global protein comparison of three strains of Borrelia burgdorferi.

The Borrelia burgdorferi spirochete is the causative agent of Lyme disease, the most common tick-borne disease in the United States. It has been studied extensively to help understand its pathogenicity of infection and how it can persist in different mammalian hosts. We report the proteomic analysis of the archetype B. burgdorferi B31 strain and two other strains (ND40, and JD-1) having different Borrelia pathotypes using strong cation exchange fractionation of proteolytic peptides followed by high-resolution, reversed phase capillary liquid chromatography coupled with ion trap tandem mass spectrometric analysis. Protein identification was facilitated by the availability of the complete B31 genome sequence. A total of 665 Borrelia proteins were identified representing approximately 38% coverage of the theoretical B31 proteome. A significant overlap was observed between the identified proteins in direct comparisons between any two strains (>72%), but distinct differences were observed among identified hypothetical and outer membrane proteins of the three strains. Such a concurrent proteomic overview of three Borrelia strains based upon only the B31 genome sequence is shown to provide significant insights into the presence or absence of specific proteins and a broad overall comparison among strains.

Animals↗