Variable blood processing procedures contribute to plasma proteomic variability.

BACKGROUND: Plasma is a potentially rich source of protein biomarkers for disease progression and drug response. Large multi-center studies are often carried out to increase the number of samples analyzed in a given study. This may increase the chances of variation in blood processing and handling, leading to altered proteomic results. This study evaluates the impact of blood processing variation on LC-MS/MS proteomic analysis of plasma. METHODS: Initially two batches of patient plasma samples (120 and 204 samples, respectively) were analyzed using LC-MS/MS shotgun proteomics. Follow-up experiments were designed and carried out on healthy donor blood in order to examine the effects of different centrifugation conditions, length of delay until first centrifugation, storage temperature and anticoagulant type on results from shotgun proteomics. RESULTS: Variable levels of intracellular proteins were observed in subsets of patient plasma samples from the initial batches analyzed. This observation correlated strongly with the site of collection, implicating variability in blood processing procedures. Results from the healthy donor blood analysis did not demonstrate a significant impact of centrifugation conditions to plasma proteome variation. The time delay until first centrifugation had a major impact on variability, while storage temperature and anticoagulant showed less pronounced but still significant effects. The intracellular proteins associated with study site effect in patient plasma samples were significantly altered by delayed processing also. CONCLUSIONS: Variable blood processing procedures contribute significantly to plasma proteomic variation and may give rise to increased intracellular proteins in plasma. Accounting for these effects can be important both at study design and data analysis stages. This understanding will be valuable to incorporate in the planning of protein-based biomarker discovery efforts in the future.

Integrative omics analysis reveals the importance and scope of translational repression in microRNA-mediated regulation.

MicroRNAs (miRNAs) are key post-transcriptional regulators that inhibit gene expression by promoting mRNA decay and/or suppressing translation. However, the relative contributions of these two mechanisms to gene repression remain controversial. Early studies favor a translational repression-centric scenario, whereas recent large-scale studies suggest a dominant role of mRNA decay in miRNA regulation. Here we generated proteomics data for nine colorectal cancer cell lines and integrated them with matched miRNA and mRNA expression data to infer and characterize miRNA-mediated regulation. Consistent with previous reports, we found that 8mer site, site positioning within 3'UTR, local AU-rich context, and additional 3' pairing could all help boost miRNA-mediated mRNA decay. However, these sequence features were generally not correlated with increased translational repression, except for local AU-rich context. Thus the contribution of translational repression might be underestimated in recent studies in which the analyses were based primarily on the response of genes with canonical 7-8 mer sites in 3'UTRs. Indeed, we found that translational repression was involved in more than half, and played a major role in one-third of all predicted miRNA-target interactions. It was even the predominant contributor to miR-138 mediated regulation, which was further supported by the observation that differential expression of miR-138 in two genetically matched cell lines corresponded to altered protein but not mRNA abundance of most target genes. In addition, our study also provided interesting insights into colon cancer biology such as the possible contributions of miR-138 and miR-141/miR-200c in inducing specific phenotypes of SW480 and RKO cell lines, respectively.

Proteomic analysis of exosomes from mutant KRAS colon cancer cells identifies intercellular transfer of mutant KRAS.

Activating mutations in KRAS occur in 30% to 40% of colorectal cancers. How mutant KRAS alters cancer cell behavior has been studied intensively, but non-cell autonomous effects of mutant KRAS are less understood. We recently reported that exosomes isolated from mutant KRAS-expressing colon cancer cells enhanced the invasiveness of recipient cells relative to exosomes purified from wild-type KRAS-expressing cells, leading us to hypothesize mutant KRAS might affect neighboring and distant cells by regulating exosome composition and behavior. Herein, we show the results of a comprehensive proteomic analysis of exosomes from parental DLD-1 cells that contain both wild-type and G13D mutant KRAS alleles and isogenically matched derivative cell lines, DKO-1 (mutant KRAS allele only) and DKs-8 (wild-type KRAS allele only). Mutant KRAS status dramatically affects the composition of the exosome proteome. Exosomes from mutant KRAS cells contain many tumor-promoting proteins, including KRAS, EGFR, SRC family kinases, and integrins. DKs-8 cells internalize DKO-1 exosomes, and, notably, DKO-1 exosomes transfer mutant KRAS to DKs-8 cells, leading to enhanced three-dimensional growth of these wild-type KRAS-expressing non-transformed cells. These results have important implications for non-cell autonomous effects of mutant KRAS, such as field effect and tumor progression.

A bioinformatics workflow for variant peptide detection in shotgun proteomics.

Shotgun proteomics data analysis usually relies on database search. However, commonly used protein sequence databases do not contain information on protein variants and thus prevent variant peptides and proteins from been identified. Including known coding variations into protein sequence databases could help alleviate this problem. Based on our recently published human Cancer Proteome Variation Database, we have created a protein sequence database that comprehensively annotates thousands of cancer-related coding variants collected in the Cancer Proteome Variation Database as well as noncancer-specific ones from the Single Nucleotide Polymorphism Database (dbSNP). Using this database, we then developed a data analysis workflow for variant peptide identification in shotgun proteomics. The high risk of false positive variant identifications was addressed by a modified false discovery rate estimation method. Analysis of colorectal cancer cell lines SW480, RKO, and HCT-116 revealed a total of 81 peptides that contain either noncancer-specific or cancer-related variations. Twenty-three out of 26 variants randomly selected from the 81 were confirmed by genomic sequencing. We further applied the workflow on data sets from three individual colorectal tumor specimens. A total of 204 distinct variant peptides were detected, and five carried known cancer-related mutations. Each individual showed a specific pattern of cancer-related mutations, suggesting potential use of this type of information for personalized medicine. Compatibility of the workflow has been tested with four popular database search engines including Sequest, Mascot, X!Tandem, and MyriMatch. In summary, we have developed a workflow that effectively uses existing genomic data to enable variant peptide detection in proteomics.

GeLC-MRM quantitation of mutant KRAS oncoprotein in complex biological samples.

Tumor-derived mutant KRAS (v-Ki-ras-2 Kirsten rat sarcoma viral oncogene) oncoprotein is a critical driver of cancer phenotypes and a potential biomarker for many epithelial cancers. Targeted mass spectrometry analysis by multiple reaction monitoring (MRM) enables selective detection and quantitation of wild-type and mutant KRAS proteins in complex biological samples. A recently described immunoprecipitation approach (Proc. Nat. Acad. Sci.2011, 108, 2444-2449) can be used to enrich KRAS for MRM analysis, but requires large protein inputs (2-4 mg). Here, we describe sodium dodecyl sulfate-polyacrylamide gel electrophoresis-based enrichment of KRAS in a low molecular weight (20-25 kDa) protein fraction prior to MRM analysis (GeLC-MRM). This approach reduces background proteome complexity, thus, allowing mutant KRAS to be reliably quantified in low protein inputs (5-50 µg). GeLC-MRM detected KRAS mutant variants (G12D, G13D, G12V, G12S) in a panel of cancer cell lines. GeLC-MRM analysis of wild-type and mutant was linear with respect to protein input and showed low variability across process replicates (CV = 14%). Concomitant analysis of a peptide from the highly similar HRAS and NRAS proteins enabled correction of KRAS-targeted measurements for contributions from these other proteins. KRAS peptides were also quantified in fluid from benign pancreatic cysts and pancreatic cancers at concentrations from 0.08 to 1.1 fmol/µg protein. GeLC-MRM provides a robust, sensitive approach to quantitation of mutant proteins in complex biological samples.

Proteomic consequences of a single gene mutation in a colorectal cancer model.

The proteomic effects of specific cancer-related mutations have not been well characterized. In colorectal cancer (CRC), a relatively small number of mutations in key signaling pathways appear to drive tumorigenesis. Mutations in adenomatous polyposis coli (APC), a negative regulator of Wnt signaling, occur in up to 60% of CRC tumors. Here we examine the proteomic consequences of a single gene mutation by using an isogenic CRC cell culture model in which wildtype APC expression has been ectopically restored. Using LC-MS/MS label free shotgun proteomics, over 5000 proteins were identified in SW480Null (mutant APC) and SW480APC (APC restored). We observed 155 significantly differentially expressed proteins between the two cell lines, with 26 proteins showing opposite expression trends relative to gene expression measurements. Protein changes corresponded to previously characterized features of the APCNull phenotype: loss of cell adhesion proteins, increase in cell cycle regulators, alteration in Wnt signaling related proteins, and redistribution of ß-catenin. Increased expression of RNA processing and isoprenoid biosynthetic proteins occurred in SW480Null cells. Therefore, shotgun proteomics reveals proteomic differences associated with a single gene change, including many novel differences that fall outside known target pathways.

Protein identification using customized protein sequence databases derived from RNA-Seq data.

The standard shotgun proteomics data analysis strategy relies on searching MS/MS spectra against a context-independent protein sequence database derived from the complete genome sequence of an organism. Because transcriptome sequence analysis (RNA-Seq) promises an unbiased and comprehensive picture of the transcriptome, we reason that a sample-specific protein database derived from RNA-Seq data can better approximate the real protein pool in the sample and thus improve protein identification. In this study, we have developed a two-step strategy for building sample-specific protein databases from RNA-Seq data. First, the database size is reduced by eliminating unexpressed or lowly expressed genes according to transcript quantification. Second, high-quality nonsynonymous coding single nucleotide variations (SNVs) are identified based on RNA-Seq data, and corresponding protein variants are added to the database. Using RNA-Seq and shotgun proteomics data from two colorectal cancer cell lines SW480 and RKO, we demonstrated that customized protein sequence databases could significantly increase the sensitivity of peptide identification, reduce ambiguity in protein assembly, and enable the detection of known and novel peptide variants. Thus, sample-specific databases from RNA-Seq data can enable more sensitive and comprehensive protein discovery in shotgun proteomics studies.

Molecular profiling of rheumatoid arthritis patients reveals an association between innate and adaptive cell populations and response to anti-tumor necrosis factor.

BACKGROUND: The goal of this study is to use comprehensive molecular profiling to characterize clinical response to anti-TNF therapy in a real-world setting and identify reproducible markers differentiating good responders and non-responders in rheumatoid arthritis (RA). METHODS: Whole-blood mRNA, plasma proteins, and glycopeptides were measured in two cohorts of biologic-naïve RA patients (n = 40 and n = 36) from the Corrona CERTAIN (Comparative Effectiveness Registry to study Therapies for Arthritis and Inflammatory coNditions) registry at baseline and after 3 months of anti-TNF treatment. Response to treatment was categorized by EULAR criteria. A cell type-specific data analysis was conducted to evaluate the involvement of the most common immune cell sub-populations. Findings concordant between the two cohorts were further assessed for reproducibility using selected NCBI-GEO datasets and clinical laboratory measurements available in the CERTAIN database. RESULTS: A treatment-related signature suggesting a reduction in neutrophils, independent of the status of response, was indicated by a high level of correlation (ρ = 0.62; p < 0.01) between the two cohorts. A baseline, response signature of increased innate cell types in responders compared to increased adaptive cell types in non-responders was identified in both cohorts. This result was further assessed by applying the cell type-specific analysis to five other publicly available RA datasets. Evaluation of the neutrophil-to-lymphocyte ratio at baseline in the remaining patients (n = 1962) from the CERTAIN database confirmed the observation (odds ratio of good/moderate response = 1.20 [95% CI = 1.03-1.41, p = 0.02]). CONCLUSION: Differences in innate/adaptive immune cell type composition at baseline may be a major contributor to response to anti-TNF treatment within the first 3 months of therapy.

Selective oxidative stress in cell nuclei by nuclear-targeted D-amino acid oxidase.

The effects of nuclear-localized oxidative stress on both nuclear antioxidant systems, and the processes that they regulate, are not clearly understood. Here, we targeted a hydrogen peroxide (H(2)O(2))-producing enzyme, D-amino acid oxidase (DAAO), to the nucleus (NLS-DAAO) and used this to generate H(2)O(2) in the nuclei of cells. On addition of N-acetyl-D-alanine (NADA), a substrate of DAAO, to NLS-DAAO-transfected HeLa cells, a twofold increase in ROS production relative to untreated, transfected control was observed. Staining of cellular thiols confirmed that NLS-DAAO-induced ROS selectively modified the nuclear thiol pool, whereas the cytoplasmic pool remained unchanged. Furthermore, NLS-DAAO/NADA-induced ROS caused significant oxidation of the nuclear GSH pool, as measured by nuclear protein S-glutathionylation (Pr-SSG), but under the same conditions, nuclear Trx1 redox state was not altered significantly. NF-kappaB reporter activity was diminished by NLS-DAAO/NADA-stimulated nuclear oxidation. We conclude that nuclear GSH is more susceptible to localized oxidation than is nuclear Trx1. Furthermore, the attenuation of NF-kappaB reporter activity in the absence of nuclear Trx1 oxidation suggests that critical nuclear redox proteins are subject to control by S-glutathionylation during oxidative stress in the nucleus.

Compartmental oxidation of thiol-disulphide redox couples during epidermal growth factor signalling.

Exogenously added ROS (reactive oxygen species) cause generalized oxidation of cellular components, whereas endogenously generated ROS induced by physiological stimuli activate discrete signal transduction pathways. Compartmentation is an important aspect of such pathways, but little is known about its role in redox signalling. We measured the redox states of cytosolic and nuclear Trx1 (thioredoxin-1) and mitochondrial Trx2 (thioredoxin-2) using redox Western blot methodologies during endogenous ROS production induced by EGF (epidermal growth factor) signalling. The glutathione redox state was measured by HPLC. Results showed that only cytosolic Trx1 undergoes significant oxidation. Thus EGF signalling involves subcellular compartmental oxidation of Trx1 in the absence of a generalized cellular oxidation.

Proteogenomic analysis reveals unanticipated adaptations of colorectal tumor cells to deficiencies in DNA mismatch repair.

A growing body of genomic data on human cancers poses the critical question of how genomic variations translate to cancer phenotypes. We used standardized shotgun proteomics and targeted protein quantitation platforms to analyze a panel of 10 colon cancer cell lines differing by mutations in DNA mismatch repair (MMR) genes. In addition, we performed transcriptome sequencing (RNA-seq) to enable detection of protein sequence variants from the proteomic data. Biologic replicate cultures yielded highly consistent proteomic inventories with a cumulative total of 6,513 protein groups with a protein false discovery rate of 3.17% across all cell lines. Networks of coexpressed proteins with differential expression based on MMR status revealed impact on protein folding, turnover and transport, on cellular metabolism and on DNA and RNA synthesis and repair. Analysis of variant amino acid sequences suggested higher stability of proteins affected by naturally occurring germline polymorphisms than of proteins affected by somatic protein sequence changes. The data provide evidence for multisystem adaptation to MMR deficiency with a stress response that targets misfolded proteins for degradation through the ubiquitin-dependent proteasome pathway. Enrichment analysis suggested epithelial-to-mesenchymal transition in RKO cells, as evidenced by increased mobility and invasion properties compared with SW480. The observed proteomic profiles demonstrate previously unknown consequences of altered DNA repair and provide an expanded basis for mechanistic interpretation of MMR phenotypes.

A Reporter System for Translational Readthrough of Stop Codons in Human Cells.

Agents to induce readthrough of premature termination codons (PTCs) are useful research tools and potential therapeutics. Reporters used to detect PTC readthrough are gene-specific and thus are not suited to for general assessment of readthrough activity or in cases where PTC-inactivated genes are unknown. Here we describe a GFP-based reporter construct pMHG-W57* which is capable of detecting dose-dependent drug-induced PTC readthrough both by fluorescence microscopy and flow cytometry. pMHG-W57* may be used as a general indicator of PTC readthrough in living cells and obviates the need for gene-specific recoding sequences in reporter constructs.

IDPicker 2.0: Improved protein assembly with high discrimination peptide identification filtering.

Tandem mass spectrometry-based shotgun proteomics has become a widespread technology for analyzing complex protein mixtures. A number of database searching algorithms have been developed to assign peptide sequences to tandem mass spectra. Assembling the peptide identifications to proteins, however, is a challenging issue because many peptides are shared among multiple proteins. IDPicker is an open-source protein assembly tool that derives a minimum protein list from peptide identifications filtered to a specified False Discovery Rate. Here, we update IDPicker to increase confident peptide identifications by combining multiple scores produced by database search tools. By segregating peptide identifications for thresholding using both the precursor charge state and the number of tryptic termini, IDPicker retrieves more peptides for protein assembly. The new version is more robust against false positive proteins, especially in searches using multispecies databases, by requiring additional novel peptides in the parsimony process. IDPicker has been designed for incorporation in many identification workflows by the addition of a graphical user interface and the ability to read identifications from the pepXML format. These advances position IDPicker for high peptide discrimination and reliable protein assembly in large-scale proteomics studies. The source code and binaries for the latest version of IDPicker are available from http://fenchurch.mc.vanderbilt.edu/ .

Reactive aldehyde modification of thioredoxin-1 activates early steps of inflammation and cell adhesion.

Several lines of evidence suggest that an increase in aldehyde-modified proteins is associated with development of atherosclerosis. Acrolein and 4-hydroxynonenal (HNE) are reactive aldehydes generated during active inflammation as a consequence of lipid peroxidation; both react with protein thiols, including thioredoxin-1 (Trx1), a protein recently found to regulate antioxidant function in endothelial cells. The present study examined whether acrolein or HNE modification of Trx1 could potentiate monocyte adhesion to endothelial cells, an early event of atherosclerosis. We examined the function of acrolein and HNE-modified Trx1 in the regulation of the early events of atherosclerosis using cultured aortic endothelial cells as a vascular model system, for in vitro enzymatic assay, and in mass spectrometry analysis. Our data show that acrolein and HNE at 1:1 ratios with Trx1 modified Cys-73 and inhibited activity. In endothelial cells, adducts were detected at concentrations as low as 1 mumol/L including conditions in which there was no detectable change in glutathione. Acrolein and HNE modification of Trx1 was associated with increased production of reactive oxygen species. Microinjection of acrolein- and HNE-modified Trx1 into endothelial cells stimulated monocyte adhesion. Chemical modification of Trx1 by common environmental and endogenously generated reactive aldehydes can contribute to atherosclerosis development by interfering with antioxidant and redox signaling functions of Trx1.