Partially tryptic peptides are often identified in shotgun proteomics using trypsin as the proteolytic enzyme; however, their sources have been controversial. Herein we investigate the impact of in-source fragmentation on shotgun proteomics profiling of three biological samples: a standard protein mixture, a mouse brain tissue homogenate, and mouse plasma. Since the in-source fragments of peptide ions have the same LC elution time as its parental peptide, partially tryptic peptide ions from in-source fragmentation can be distinguished from the other partially tryptic peptides based on their elution time differences from those computationally predicted data. The percentage of partially tryptic peptide identifications resulting from in-source fragmentation in a standard protein digest was observed to be ~60 %. In more complex mouse brain or plasma samples, in-source fragmentation contributed to a less degree of 1–3 % of all identified peptides due to the limit dynamic range of LC-MS/MS measurements. The other major source of partially tryptic peptides in complex biological samples is presumably proteolytic cleavage by endogenous proteases in the samples. Our work also provides a method to identify such proteolytic-derived partially tryptic peptides due to endogenous proteases in the samples by removing in-source fragmentation artifacts from the identified peptides.
in-source fragmentation; partially tryptic; trypsin specificity; predicted elution time
Antibiotic resistance among highly pathogenic strains of bacteria and fungi is a growing concern in the face of the ability to sustain life during critical illness with advancing medical interventions. The longer patients remain critically ill, the more likely they are to become colonized by multidrug-resistant (MDR) pathogens. The human gastrointestinal tract is the primary site of colonization of many MDR pathogens and is a major source of life-threatening infections due to these microorganisms. Eradication measures to sterilize the gut are difficult if not impossible and carry the risk of further antibiotic resistance. Here, we present a strategy to contain rather than eliminate MDR pathogens by using an agent that interferes with the ability of colonizing pathogens to express virulence in response to host-derived and local environmental factors. The antivirulence agent is a phosphorylated triblock high-molecular-weight polymer (here termed Pi-PEG 15–20) that exploits the known properties of phosphate (Pi) and polyethylene glycol 15-20 (PEG 15-20) to suppress microbial virulence and protect the integrity of the intestinal epithelium. The compound is nonmicrobiocidal and appears to be highly effective when tested both in vitro and in vivo. Structure functional analyses suggest that the hydrophobic bis-aromatic moiety at the polymer center is of particular importance to the biological function of Pi-PEG 15-20, beyond its phosphate content. Animal studies demonstrate that Pi-PEG prevents mortality in mice inoculated with multiple highly virulent pathogenic organisms from hospitalized patients in association with preservation of the core microbiome.
During acute Lyme disease, bacteria can disseminate to the central nervous system (CNS) leading to the development of meningitis and other neurologic symptoms. Here we have analyzed pooled cerebrospinal fluid (CSF) allowing a deep view into the proteome for patients diagnosed with early-disseminated Lyme disease and CSF inflammation. Additionally, we analyzed individual patient samples and quantified differences in protein abundance employing label-free quantitative mass spectrometry based methods. We identified 108 proteins that differ significantly in abundance in patients with acute Lyme disease from controls. Comparison between infected patients and control subjects revealed differences in proteins in the CSF associated with cell death localized to brain synapses and others that likely originate from brain parenchyma.
Proteomics; mass spectrometry; Lyme disease; cerebrospinal fluid; Lyme neuroborreliosis
The cause of multiple sclerosis (MS), its driving pathogenesis at the earliest stages, and what factors allow the first clinical attack to manifest remain unknown. Some imaging studies suggest gray rather than white matter may be involved early, and some postulate this may be predictive of developing MS. Other imaging studies are in conflict. To determine if there was objective molecular evidence of gray matter involvement in early MS we used high-resolution mass spectrometry to identify proteins in the cerebrospinal fluid (CSF) of first-attack MS patients (two independent groups) compared to established relapsing remitting (RR) MS and controls. We found that the CSF proteins in first-attack patients were differentially enriched for gray matter components (axon, neuron, synapse). Myelin components did not distinguish these groups. The results support that gray matter dysfunction is involved early in MS, and also may be integral for the initial clinical presentation.
Reduced signaling through the C. elegans insulin/insulin-like growth factor-1-like tyrosine kinase receptor daf-2 and dietary restriction via bacterial dilution are two well-characterized lifespan-extending interventions that operate in parallel or through (partially) independent mechanisms. Using accurate mass and time tag LC-MS/MS quantitative proteomics, we detected that the abundance of a large number of ribosomal subunits is decreased in response to dietary restriction, as well as in the daf-2(e1370) insulin/insulin-like growth factor-1-receptor mutant. In addition, general protein synthesis levels in these long-lived worms are repressed. Surprisingly, ribosomal transcript levels were not correlated to actual protein abundance, suggesting that post-transcriptional regulation determines ribosome content. Proteomics also revealed the increased presence of many structural muscle cell components in long-lived worms, which appeared to result from the prioritized preservation of muscle cell volume in nutrient-poor conditions or low insulin-like signaling. Activation of DAF-16, but not diet restriction, stimulates mRNA expression of muscle-related genes to prevent muscle atrophy. Important daf-2-specific proteome changes include overexpression of aerobic metabolism enzymes and general activation of stress-responsive and immune defense systems, whereas the increased abundance of many protein subunits of the proteasome core complex is a dietary-restriction-specific characteristic.
To design a robust quantitative proteomics study, an understanding of both the inherent heterogeneity of the biological samples being studied as well as the technical variability of the proteomics methods and platform is needed. Additionally, accurately identifying the technical steps associated with the largest variability would provide valuable information for the improvement and design of future processing pipelines. We present an experimental strategy that allows for a detailed examination of the variability of the quantitative LC-MS proteomics measurements. By replicating analyses at different stages of processing, various technical components can be estimated and their individual contribution to technical variability can be dissected. This design can be easily adapted to other quantitative proteomics pipelines. Herein, we applied this methodology to our label-free workflow for the processing of human brain tissue. For this application, the pipeline was divided into four critical components: Tissue dissection and homogenization (extraction), protein denaturation followed by trypsin digestion and SPE clean-up (digestion), short-term run-to-run instrumental response fluctuation (instrumental variance), and long-term drift of the quantitative response of the LC-MS/MS platform over the 2 week period of continuous analysis (instrumental stability). From this analysis, we found the following contributions to variability: extraction (72%) >> instrumental variance (16%) > instrumental stability (8.4%) > digestion (3.1%). Furthermore, the stability of the platform and its' suitability for discovery proteomics studies is demonstrated.
Label-free quantification; technical variation; sample preparation; reproducibility; study design; tissue analysis
Our objective here was to perform a quantitative phosphoproteomic study on a reconstituted human skin tissue to identify low and high dose ionizing radiation dependent signaling in a complex 3-dimensional setting. Application of an isobaric labeling strategy using sham and 3 radiation doses (3, 10, 200 cGy) resulted in the identification of 1052 unique phosphopeptides. Statistical analyses identified 176 phosphopeptides showing significant changes in response to radiation and radiation dose. Proteins responsible for maintaining skin structural integrity including keratins and desmosomal proteins (desmoglein, desmoplakin, plakophilin 1, 2 and 3) had altered phosphorylation levels following exposure to both low and high doses of radiation. Altered phosphorylation of multiple sites in profilaggrin linker domains coincided with altered profilaggrin processing suggesting a role for linker phosphorylation in human profilaggrin regulation. These studies demonstrate that the reconstituted human skin system undergoes a coordinated response to both low and high doses of ionizing radiation involving multiple layers of the stratified epithelium that serve to maintain tissue integrity and mitigate effects of radiation exposure.
Ionizing Radiation; Skin; Phosphorylation
Selected reaction monitoring (SRM)—also known as multiple reaction monitoring (MRM)—has emerged as a promising high-throughput targeted protein quantification technology for candidate biomarker verification and systems biology applications. A major bottleneck for current SRM technology, however, is insufficient sensitivity for e.g., detecting low-abundance biomarkers likely present at the low ng/mL to pg/mL range in human blood plasma or serum, or extremely low-abundance signaling proteins in cells or tissues. Herein we review recent advances in methods and technologies, including front-end immunoaffinity depletion, fractionation, selective enrichment of target proteins/peptides including posttranslational modifications (PTMs), as well as advances in MS instrumentation which have significantly enhanced the overall sensitivity of SRM assays and enabled the detection of low-abundance proteins at low to sub- ng/mL level in human blood plasma or serum. General perspectives on the potential of achieving sufficient sensitivity for detection of pg/mL level proteins in plasma are also discussed.
SRM; sensitivity; fractionation; ion funnel; enrichment
Sodium dodecyl sulfate (SDS) is one of the most popular laboratory reagents used for biological sample extraction; however, the presence of this reagent in samples challenges LC-MS-based proteomics analyses because it can interfer with reversed-phase LC separations and electrospray ionization. This study reports a simple SDS-assisted proteomics sample preparation method facilitated by a novel peptide-level SDS removal step. In an initial demonstration, SDS was effectively (>99.9%) removed from peptide samples through ion substitution-mediated DS- precipitation using potassium chloride (KCl), and excellent peptide recovery (>95%) was observed for <20 μg peptides. Further experiments demonstrated the compatibility of this protocol with LC-MS/MS analyses. The resulting proteome coverage obtained for both mammalian tissues and bacterial samples was comparable to or better than that obtained for the same sample types prepared using standard proteomics preparation methods and analyzed using LC-MS/MS. These results suggest the SDS-assisted protocol is a practical, simple, and broadly applicable proteomics sample processing method, which can be particularly useful when dealing with samples difficult to solubilize by other methods.
SDS removal; KDS precipitation; proteomics; sample preparation; LC-MS
Cytomegaloviruses are highly host restricted, resulting in cospeciation with their hosts. As a natural pathogen of rhesus macaques (RM), rhesus cytomegalovirus (RhCMV) has therefore emerged as a highly relevant experimental model for pathogenesis and vaccine development due to its close evolutionary relationship to human CMV (HCMV). Most in vivo experiments performed with RhCMV employed strain 68-1 cloned as a bacterial artificial chromosome (BAC). However, the complete genome sequence of the 68-1 BAC has not been determined. Furthermore, the gene content of the RhCMV genome is unknown, and previous open reading frame (ORF) predictions relied solely on uninterrupted ORFs with an arbitrary cutoff of 300 bp. To obtain a more precise picture of the actual proteins encoded by the most commonly used molecular clone of RhCMV, we reevaluated the RhCMV 68-1 BAC genome by whole-genome shotgun sequencing and determined the protein content of the resulting RhCMV virions by proteomics. By comparing the RhCMV genome to those of several related Old World monkey (OWM) CMVs, we were able to filter out many unlikely ORFs and obtain a simplified map of the RhCMV genome. This comparative genomics analysis suggests a high degree of ORF conservation among OWM CMVs, thus decreasing the likelihood that ORFs found only in RhCMV comprise true genes. Moreover, virion proteomics independently validated the revised ORF predictions, since only proteins that were conserved across OWM CMVs could be detected. Taken together, these data suggest a much higher conservation of genome and virion structure between CMVs of humans, apes, and OWMs than previously assumed.
Interest in the application of advanced proteomics technologies to human blood plasma- or serum-based clinical samples for the purpose of discovering disease biomarkers continues to grow; however, the enormous dynamic range of protein concentrations in these types of samples (often >10 orders of magnitude) represents a significant analytical challenge, particularly for detecting low-abundance candidate biomarkers. In response, immunoaffinity separation methods for depleting multiple high- and moderate-abundance proteins have become key tools for enriching low-abundance proteins and enhancing detection of these proteins in plasma proteomics. Herein, we describe IgY14 and tandem IgY14-Supermix separation methods for removing 14 high-abundance and up to 60 moderate-abundance proteins, respectively, from human blood plasma and highlight their utility when combined with liquid chromatography-tandem mass spectrometry for interrogating the human plasma proteome.
SuperMix; IgY14; immunoaffinity; plasma proteomics; Biomarker discovery
Nanoparticle biological activity, biocompatibility and fate can be directly affected by layers of readily adsorbed host proteins in biofluids. Here, we report a study on the interactions between human blood plasma proteins and nanoparticles with a controlled systematic variation of properties using 18O-labeling and LC-MS-based quantitative proteomics. We developed a novel protocol to both simplify isolation of nanoparticle bound proteins and improve reproducibility. LC-MS analysis identified and quantified 88 human plasma proteins associated with polystyrene nanoparticles consisting of three different surface chemistries and two sizes, as well as, for four different exposure times (for a total of 24 different samples). Quantitative comparison of relative protein abundances was achieved by spiking an 18O-labeled “universal” reference into each individually processed unlabeled sample as an internal standard, enabling simultaneous application of both label-free and isotopic labeling quantification across the entire sample set. Clustering analysis of the quantitative proteomics data resulted in distinctive patterns that classified the nanoparticles based on their surface properties and size. In addition, temporal data indicated that the formation of the stable protein corona was at equilibrium within 5 min. The comprehensive quantitative proteomics results obtained in this study provide rich data for computational modeling and have potential implications towards predicting nanoparticle biocompatibility.
Corona; Human plasma; LC-MS; Nanoparticle; Quantitative proteomics
Recently, selected reaction monitoring mass spectrometry (SRM-MS) has been more frequently applied to measure low abundance biomarker candidates in tissues and biofluids, owing to its high sensitivity and specificity, simplicity of assay configuration, and exceptional multiplexing capability. In this study, we report for the first time the development of immunoaffinity depletion-based workflows and SRM-MS assays that enable sensitive and accurate quantification of total and free prostate-specific antigen (PSA) in serum without the requirement for specific PSA antibodies. Low ng/mL level detection of both total and free PSA was consistently achieved in both PSA-spiked female serum samples and actual patient serum samples. Moreover, comparison of the results obtained when SRM PSA assays and conventional immunoassays were applied to the same samples showed good correlation in several independent clinical serum sample sets. These results demonstrate that the workflows and SRM assays developed here provide an attractive alternative for reliably measuring candidate biomarkers in human blood, without the need to develop affinity reagents. Furthermore, the simultaneous measurement of multiple biomarkers, including the free and bound forms of PSA, can be performed in a single multiplexed analysis using high-resolution liquid chromatographic separation coupled with SRM-MS.
Selected reaction monitoring; immunoaffinity depletion; total PSA; free PSA; serum; immunoassay
In this study, we evaluated a concatenated low pH (pH 3) and high pH (pH 10) reversed-phase liquid chromatography strategy as a first dimension for two-dimensional liquid chromatography tandem mass spectrometry (“shotgun”) proteomic analysis of trypsin-digested human MCF10A cell sample. Compared with the more traditional strong cation exchange method, the use of concatenated high pH reversed-phase liquid chromatography as a first-dimension fractionation strategy resulted in 1.8- and 1.6-fold increases in the number of peptide and protein identifications (with two or more unique peptides), respectively. In addition to broader identifications, advantages of the concatenated high pH fractionation approach include improved protein sequence coverage, simplified sample processing, and reduced sample losses. The results demonstrate that the concatenated high pH reversed-phased strategy is an attractive alternative to strong cation exchange for two-dimensional shotgun proteomic analysis.
2-D chromatography; Concatenation; Fractionation; High pH RP; Low pH RP; Technology
Orthogonal high-resolution separations are critical for attaining improved analytical dynamic range and protein coverage in proteomic measurements. High pH reversed-phase liquid chromatography (RPLC) followed by fraction concatenation affords better peptide analysis than conventional strong-cation exchange (SCX) chromatography applied for the two-dimensional proteomic analysis. For example, concatenated high pH reversed-phase liquid chromatography increased identification for peptides (1.8-fold) and proteins (1.6-fold) in shotgun proteomics analyses of a digested human protein sample. Additional advantages of high pH RPLC with fraction concatenation include improved protein sequence coverage, simplified sample processing, and reduced sample losses, making this an attractive alternative to SCX chromatography in conjunction with the second dimension low pH RPLC for two-dimensional proteomics analyses.
Two dimensional chromatographic separation; shotgun proteomics analysis; SCX; Fraction concatenation; High pH RP
The molecular mechanisms underlying the changes in the nigrostriatal pathway in Parkinson’s disease (PD) are not completely understood. Here, we use mass spectrometry and microarrays to study the proteomic and transcriptomic changes in the striatum of two mouse models of PD, induced by the distinct neurotoxins 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) and methamphetamine (METH). Proteomic analyses resulted in the identification and relative quantification of 912 proteins with two or more unique peptides and 86 proteins with significant abundance changes following neurotoxin treatment. Similarly, microarray analyses revealed 181 genes with significant changes in mRNA, following neurotoxin treatment. The combined protein and gene list provides a clearer picture of the potential mechanisms underlying neurodegeneration observed in PD. Functional analysis of this combined list revealed a number of significant categories, including mitochondrial dysfunction, oxidative stress response, and apoptosis. These results constitute one of the largest descriptive data sets integrating protein and transcript changes for these neurotoxin models with many similar end point phenotypes but distinct mechanisms.
Parkinson’s disease; transcriptomics; proteomics; codon usage; miRNA; mouse model
We generated extensive transcriptional and proteomic profiles from a Her2-driven mouse model of breast cancer that closely recapitulates human breast cancer. This report makes these data publicly available in raw and processed forms, as a resource to the community. Importantly, we previously made biospecimens from this same mouse model freely available through a sample repository, so researchers can obtain samples to test biological hypotheses without the need of breeding animals and collecting biospecimens.
Twelve datasets are available, encompassing 841 LC-MS/MS experiments (plasma and tissues) and 255 microarray analyses of multiple tissues (thymus, spleen, liver, blood cells, and breast). Cases and controls were rigorously paired to avoid bias.
In total, 18,880 unique peptides were identified (PeptideProphet peptide error rate ≤1%), with 3884 and 1659 non-redundant protein groups identified in plasma and tissue datasets, respectively. Sixty-one of these protein groups overlapped between cancer plasma and cancer tissue.
Conclusions and clinical relevance
These data are of use for advancing our understanding of cancer biology, for software and quality control tool development, investigations of analytical variation in MS/MS data, and selection of proteotypic peptides for MRM-MS. The availability of these datasets will contribute positively to clinical proteomics.
Breast cancer; Her2; mouse; proteome; transcriptome
Quantitative proteomic measurements are of significant interest in studies aimed at discovering disease biomarkers and providing new insights into biological pathways. A quantitative cysteinyl-peptide enrichment technology (QCET) can be employed to achieve higher efficiency, greater dynamic range, and higher throughput in quantitative proteomic studies based upon the use of stable-isotope labeling techniques combined with high-resolution capillary or nano-scale liquid chromatography (LC)-mass spectrometry (MS) measurements. The QCET approach involves specific 16O/18O labeling of tryptic peptides, high-efficiency enrichment of cysteinyl-peptides, and confident protein identification and quantification using high mass accuracy LC-Fourier transform ion cyclotron resonance mass spectrometry (FTICR) measurements and a previously established database of accurate mass and LC elution time information for the labeled peptides. This methodology has been initially demonstrated by using proteome profiling of naïve and in vitro-differentiated human mammary epithelial cells (HMEC) as an example, which initially resulted in the identification and quantification of 603 proteins in a single LC-FTICR analysis. QCET provides not only highly efficient enrichment of cysteinyl-peptides for more extensive proteome coverage and improved labeling efficiency for better quantitative measurements, but more importantly, a high-throughput strategy suitable for quantitative proteome analysis where extensive or parallel proteomic measurements are required, such as in time course studies of specific pathways and clinical sample analyses for biomarker discovery.
Quantitative proteomics; QCET; 18O labeling; cysteinyl-peptide enrichment; FTICR; AMT
Kaposi's sarcoma-associated herpesvirus (KSHV) and Epstein-Barr virus (EBV) are related human tumor viruses that cause primary effusion lymphomas (PEL) and Burkitt's lymphomas (BL), respectively. Viral genes expressed in naturally-infected cancer cells contribute to disease pathogenesis; knowing which viral genes are expressed is critical in understanding how these viruses cause cancer. To evaluate the expression of viral genes, we used high-resolution separation and mass spectrometry coupled with custom tiling arrays to align the viral proteomes and transcriptomes of three PEL and two BL cell lines under latent and lytic culture conditions.
The majority of viral genes were efficiently detected at the transcript and/or protein level on manipulating the viral life cycle. Overall the correlation of expressed viral proteins and transcripts was highly complementary in both validating and providing orthogonal data with latent/lytic viral gene expression. Our approach also identified novel viral genes in both KSHV and EBV, and extends viral genome annotation. Several previously uncharacterized genes were validated at both transcript and protein levels.
This systems biology approach coupling proteome and transcriptome measurements provides a comprehensive view of viral gene expression that could not have been attained using each methodology independently. Detection of viral proteins in combination with viral transcripts is a potentially powerful method for establishing virus-disease relationships.
Spectral counting has become a popular method for LC-MS/MS based proteome quantification; however, this methodology is often not reliable when proteins are identified by a small number of spectra. Here we present a simple strategy to improve spectral counting based quantification for low abundance proteins by recovering low quality or low scoring spectra for confidently identified peptides. In this approach, stringent data filtering criteria were initially applied to achieve confident peptide identifications with low false discovery rate (e.g., < 1% at peptide level) after LC-MS/MS analysis and database search by SEQUEST. Then, all low scoring MS/MS spectra that match to this set of confidently identified peptides were recovered, leading to more than 20% increase of total identified spectra. The validity of these recovered spectra was assessed by the parent ion mass measurement error distribution, retention time distribution, and by comparing the individual low score and high score spectra that correspond to the same peptides. The results support that the recovered low scoring spectra have similar confidence levels in peptide identifications as the spectra passing the initial stringent filter. The application of this strategy of recovering low scoring spectra significantly improved the spectral count quantification statistics for low abundance proteins, as illustrated in the identification of mouse brain region specific proteins.
Spectral count; LC-MS/MS; false negative; quantification
Accurate assignment of monoisotopic precursor masses to tandem mass spectrometric (MS/MS) data is a fundamental and critically important step for successful peptide identifications in mass spectrometry based proteomics. Here we describe an integrated approach that combines three previously reported methods of treating MS/MS data for precursor mass refinement. This combined method, “integrated Post-Experiment Monoisotopic Mass Refinement” (iPE-MMR), integrates steps: 1) generation of refined MS/MS data by DeconMSn; 2) additional refinement of the resultant MS/MS data by a modified version of PE-MMR; 3) elimination of systematic errors of precursor masses using DtaRefinery. iPE-MMR is the first method that utilizes all MS information from multiple MS scans of a precursor ion including multiple charge states, in an MS scan, to determine precursor mass. By combining these methods, iPE-MMR increases sensitivity in peptide identification and provides increased accuracy when applied to complex high-throughput proteomics data.
Neutrophils play critical roles in modulating the immune response. We present a robust methodology for rapidly isolating neutrophils directly from whole blood and develop ‘on-chip’ processing for mRNA and protein isolation for genomics and proteomics. We validate this device with an ex vivo stimulation experiment and by comparison with standard bulk isolation methodologies. Lastly, we implement this tool as part of a near patient blood processing system within a multi-center clinical study of the immune response to severe trauma and burn injury. The preliminary results from a small cohort of patients in our study and healthy controls show a unique time-dependent gene expression pattern clearly demonstrating the ability of this tool to discriminate temporal transcriptional events of neutrophils within a clinical setting.
Herein we describe a platform for degradomic-peptidomic analyses. The human blood peptidome was isolated through application of AC/SEC, which enriched its components by >300-fold. The isolated peptidome components were separated by the long column HRLC providing a peak capacity of ~300 for species having MWs of up to 20 kDa. The separated species were identified by the FT MS/MS-UStags sequencing method. We identified >200 peptidome peptides that originated from 29 protein substrates from the blood plasma of a single healthy person. The peptidome peptides identified had MWs range of 0.5–14 kDa and identifications were achieved with extremely low (near zero) false discovery rates through searching the IPI human protein database (~70,000 entries). Some of the peptidome peptides identified have mutations and modifications such as acetylation, acetylhexosamine, amidation, cysteinylation, didehydro, oxidation, and pyro-glu. The capabilities described enable the global analysis of the peptidome peptides to identify degradome targets such as degradome proteases, proteases inhibitors, and other relevant substrates, the cleavage specificities for the degradation of individual substrates, as well as a potential basis for using the various extents of substrate degradation for diagnostic purposes.
The DNA damage response is a global phosphorylation signaling cascade process involved in sensing the damaged DNA condition and coordinating responses to cope with and repair the perturbed cellular state. We utilized a label-free liquid chromatography-mass spectrometry approach to evaluate changes in protein phosphorylation associated with PP5 activity during the DNA damage response. Biological replicate analyses of bleomycin-treated HeLa cells expressing either WT-PP5 or mutant inactive PP5 lead to the identification of six potential target proteins of PP5 action. Four of these putative targets are known to be involved in DNA damage responses. Using phospho-site specific antibodies, we confirmed that phosphorylation of one target, ribosomal protein S6, was selectively decreased in cells overexpressing catalytically inactive PP5. Our findings also suggest that PP5 may play a role in controlling translation and in regulating substrates for proline-directed kinases, such as MAP kinases and cyclin-dependent protein kinases that are involved in response to DNA damage.
Label-free quantitation; DNA damage; Comparative phosphoproteomics; Immobilized metal ion affinity chromatography (IMAC); Mass spectrometry (MS); nano reverse phase HPLC; Protein phosphatase 5; PP5; Ser/Thr protein phosphatase; Bleomycin
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 3,365 proteins (≥ 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-κβ, and JAK/STAT pathways. The resulting peptide reference library provides a resource for future higher throughput and quantitative studies of islet biology.
pancreatic islets; liquid chromatography; electrospray; mass spectrometry; proteomics; linear ion trap