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.
Respiratory infections stemming from influenza viruses and the Severe Acute Respiratory Syndrome corona virus (SARS-CoV) represent a serious public health threat as emerging pandemics. Despite efforts to identify the critical interactions of these viruses with host machinery, the key regulatory events that lead to disease pathology remain poorly targeted with therapeutics. Here we implement an integrated network interrogation approach, in which proteome and transcriptome datasets from infection of both viruses in human lung epithelial cells are utilized to predict regulatory genes involved in the host response. We take advantage of a novel “crowd-based” approach to identify and combine ranking metrics that isolate genes/proteins likely related to the pathogenicity of SARS-CoV and influenza virus. Subsequently, a multivariate regression model is used to compare predicted lung epithelial regulatory influences with data derived from other respiratory virus infection models. We predicted a small set of regulatory factors with conserved behavior for consideration as important components of viral pathogenesis that might also serve as therapeutic targets for intervention. Our results demonstrate the utility of integrating diverse ‘omic datasets to predict and prioritize regulatory features conserved across multiple pathogen infection models.
Proteomics analysis identifies human serum proteins involved with innate immune responses, complement activation, and blood coagulation that are diagnostic for type 1 diabetes.
Using global liquid chromatography-mass spectrometry (LC-MS)–based proteomics analyses, we identified 24 serum proteins that were significantly variant between those with type 1 diabetes (T1D) and healthy controls. Functionally, these proteins represent innate immune responses, the activation cascade of complement, inflammatory responses, and blood coagulation. Targeted verification analyses were performed on 52 surrogate peptides representing these proteins, with serum samples from an antibody standardization program cohort of 100 healthy control and 50 type 1 diabetic subjects. 16 peptides were verified as having very good discriminating power, with areas under the receiver operating characteristic curve ≥0.8. Further validation with blinded serum samples from an independent cohort (10 healthy control and 10 type 1 diabetics) demonstrated that peptides from platelet basic protein and C1 inhibitor achieved both 100% sensitivity and 100% specificity for classification of samples. The disease specificity of these proteins was assessed using sera from 50 age-matched type 2 diabetic individuals, and a subset of proteins, C1 inhibitor in particular, were exceptionally good discriminators between these two forms of diabetes. The panel of biomarkers distinguishing those with T1D from healthy controls and those with type 2 diabetes suggests that dysregulated innate immune responses may be associated with the development of this disorder.
We report on the effectiveness of CID, HCD, and ETD for LC-FT MS/MS analysis of peptides using a tandem linear ion trap-Orbitrap mass spectrometer. A range of software tools and analysis parameters were employed to explore the use of CID, HCD, and ETD to identify peptides isolated from human blood plasma without the use of specific “enzyme rules”. In the evaluation of an FDR-controlled SEQUEST scoring method, the use of accurate masses for fragments increased the numbers of identified peptides (by ~50%) compared to the use of conventional low accuracy fragment mass information, and CID provided the largest contribution to the identified peptide datasets compared to HCD and ETD. The FDR-controlled Mascot scoring method provided significantly fewer peptide identifications than with SEQUEST (by 1.3–2.3 fold) at the same confidence levels, and CID, HCD, and ETD provided similar contributions to identified peptides. Evaluation of de novo sequencing and the UStags method for more intense fragment ions revealed that HCD afforded more sequence consecutive residues (e.g., ≥7 amino acids) than either CID or ETD. Both the FDR-controlled SEQUEST and Mascot scoring methods provided peptide datasets that were affected by the decoy database and mass tolerances applied (e.g., the identical peptides between the datasets could be limited to ~70%), while the UStags method provided the most consistent peptide datasets (>90% overlap) with extremely low (near zero) numbers of false positive identifications. The m/z ranges in which CID, HCD, and ETD contributed the largest number of peptide identifications were substantially overlapping. This work suggests that the three peptide ion fragmentation methods are complementary, and that maximizing the number of peptide identifications benefits significantly from a careful match with the informatics tools and methods applied. These results also suggest that the decoy strategy may inaccurately estimate identification FDRs.
CID; HCD; ETD; FT MS/MS; FDR; protein UStags; de novo sequencing; peptides; peptidomic analysis; blood plasma
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
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
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
Non-enzymatic glycation of proteins sets the stage for formation of advanced glycation end-products and development of chronic complications of diabetes. In this report, we extended our previous methods on proteomics analysis of glycated proteins to comprehensively identify glycated proteins in control and diabetic human plasma and erythrocytes. Using immunodepletion, enrichment, and fractionation strategies, we identified 7749 unique glycated peptides, corresponding to 3742 unique glycated proteins. Semi-quantitative comparisons showed that glycation levels of a number of proteins were significantly increased in diabetes and that erythrocyte proteins were more extensively glycated than plasma proteins. A glycation motif analysis revealed that some amino acids were favored more than others in the protein primary structures in the vicinity of the glycation sites in both sample types. The glycated peptides and corresponding proteins reported here provide a foundation for potential identification of novel markers for diabetes, hyperglycemia, and diabetic complications in future studies.
nonenzymatic glycation; Amadori compound; boronate affinity chromatography; electron transfer dissociation; type 2 diabetes mellitus; plasma; erythrocyte; red blood cell; glycation motif
Salmonella enterica serovar Typhimurium is a leading cause of acute gastroenteritis throughout the world. This pathogen has two type III secretion systems (TTSS) encoded in Salmonella pathogenicity islands 1 and 2 (SPI-1 and SPI-2) that deliver virulence factors (effectors) to the host cell cytoplasm and are required for virulence. While many effectors have been identified and at least partially characterized, the full repertoire of effectors has not been catalogued. In this proteomic study, we identified effector proteins secreted into defined minimal medium designed to induce expression of the SPI-2 TTSS and its effectors. We compared the secretomes of the parent strain to those of strains missing essential (ssaK::cat) or regulatory (ΔssaL) components of the SPI-2 TTSS. We identified 20 known SPI-2 effectors. Excluding the translocon components SseBCD, all SPI-2 effectors were biased for identification in the ΔssaL mutant, substantiating the regulatory role of SsaL in TTS. To identify novel effector proteins, we coupled our secretome data with a machine learning algorithm (SIEVE, SVM-based identification and evaluation of virulence effectors) and selected 12 candidate proteins for further characterization. Using CyaA′ reporter fusions, we identified six novel type III effectors and two additional proteins that were secreted into J774 macrophages independently of a TTSS. To assess their roles in virulence, we constructed nonpolar deletions and performed a competitive index analysis from intraperitoneally infected 129/SvJ mice. Six mutants were significantly attenuated for spleen colonization. Our results also suggest that non-type III secretion mechanisms are required for full Salmonella virulence.
Neurologic Post Treatment Lyme disease (nPTLS) and Chronic Fatigue (CFS) are syndromes of unknown etiology. They share features of fatigue and cognitive dysfunction, making it difficult to differentiate them. Unresolved is whether nPTLS is a subset of CFS.
Methods and Principal Findings
Pooled cerebrospinal fluid (CSF) samples from nPTLS patients, CFS patients, and healthy volunteers were comprehensively analyzed using high-resolution mass spectrometry (MS), coupled with immunoaffinity depletion methods to reduce protein-masking by abundant proteins. Individual patient and healthy control CSF samples were analyzed directly employing a MS-based label-free quantitative proteomics approach. We found that both groups, and individuals within the groups, could be distinguished from each other and normals based on their specific CSF proteins (p<0.01). CFS (n = 43) had 2,783 non-redundant proteins, nPTLS (n = 25) contained 2,768 proteins, and healthy normals had 2,630 proteins. Preliminary pathway analysis demonstrated that the data could be useful for hypothesis generation on the pathogenetic mechanisms underlying these two related syndromes.
nPTLS and CFS have distinguishing CSF protein complements. Each condition has a number of CSF proteins that can be useful in providing candidates for future validation studies and insights on the respective mechanisms of pathogenesis. Distinguishing nPTLS and CFS permits more focused study of each condition, and can lead to novel diagnostics and therapeutic interventions.
A high-throughput approach and platform using 15 minute reversed-phase capillary liquid chromatography (RPLC) separations in conjunction with ion mobility spectrometry-mass spectrometry (IMS-MS) measurements was evaluated for the rapid analysis of complex proteomics samples. To test the separation quality of the short LC gradient, a sample was prepared by spiking twenty reference peptides at varying concentrations from 1 ng/mL to 10 µg/mL into a tryptic digest of mouse blood plasma and analyzed with both a LC-Linear Ion Trap Fourier Transform (FT) MS and LC-IMS-TOF MS. The LC-FT MS detected thirteen out of the twenty spiked peptides that had concentrations ≥100 ng/mL. In contrast, the drift time selected mass spectra from the LC-IMS-TOF MS analyses yielded identifications for nineteen of the twenty peptides with all spiking levels present. The greater dynamic range of the LC-IMS-TOF MS system could be attributed to two factors. First, the LC-IMS-TOF MS system enabled drift time separation of the low concentration spiked peptides from the high concentration mouse peptide matrix components, reducing signal interference and background, and allowing species to be resolved that would otherwise be obscured by other components. Second, the automatic gain control (AGC) in the linear ion trap of the hybrid FT MS instrument limits the number of ions that are accumulated to reduce space charge effects and achieve high measurement accuracy, but in turn limits the achievable dynamic range compared to the IMS-TOF instrument.
Ion mobility spectrometry; IMS-MS; LC-IMS-MS; high-throughput RPLC
A burn injury represents one of the most severe forms of human trauma and is responsible for significant mortality worldwide. Here, we present the first quantitative proteomics investigation of the blood plasma proteome response to severe burn injury by comparing the plasma protein concentrations of 10 healthy control subjects with those of 15 severe burn patients at two time-points following the injury. The overall analytical strategy for this work integrated immunoaffinity depletion of the 12 most abundant plasma proteins with cysteinyl-peptide enrichment-based fractionation prior to LC-MS analyses of individual patient samples. Incorporation of an 18O-labeled “universal” reference among the sample sets enabled precise relative quantification across samples. In total, 313 plasma proteins confidently identified with two or more unique peptides were quantified. Following statistical analysis, 110 proteins exhibited significant abundance changes in response to the burn injury. The observed changes in protein concentrations suggest significant inflammatory and hypermetabolic response to the injury, which is supported by the fact that many of the identified proteins are associated with acute phase response signaling, the complement system, and coagulation system pathways. The regulation of ~35 proteins observed in this study is in agreement with previous results reported for inflammatory or burn response, but approximately 50 potentially novel proteins previously not known to be associated with burn response or inflammation are also found. Elucidating proteins involved in the response to severe burn injury may reveal novel targets for therapeutic interventions, as well as potential predictive biomarkers for patient outcomes such as multiple organ failure.
human plasma; quantitative proteomics; 18O labeling; LC-MS; burn; inflammation; “universal” reference
Protein tyrosine phosphorylation represents a central regulatory mechanism in cell signaling. Here we present an extensive survey of tyrosine phosphorylation sites in a normal-derived human mammary epithelial cell line by applying anti-phosphotyrosine peptide immunoaffinity purification coupled with high sensitivity capillary liquid chromatography tandem mass spectrometry. A total of 481 tyrosine phosphorylation sites (covered by 716 unique peptides) from 285 proteins were confidently identified in HMEC following the analysis of both the basal condition and acute stimulation with epidermal growth factor (EGF). The estimated false discovery rate was 1.0% as determined by searching against a scrambled database. Comparison of these data with existing literature showed significant agreement for previously reported sites. However, we observed 281 sites that were not previously reported for HMEC cultures and 29 of which have not been reported for any human cell or tissue system. The analysis showed that the majority of highly phosphorylated proteins were relatively low-abundance. Large differences in phosphorylation stoichiometry for sites within the same protein were also observed, raising the possibility of more important functional roles for such highly phosphorylated pTyr sites. By mapping to major signaling networks, such as the EGF receptor and insulin growth factor-1 receptor signaling pathways, many known proteins involved in these pathways were revealed to be tyrosine phosphorylated, which provides interesting targets for future hypothesis-driven and targeted quantitative studies involving tyrosine phosphorylation in HMEC or other human systems.
LC-MS/MS; phosphotyrosine; phosphoproteomics; HMEC; phosphorylation; immunoprecipitation
Knowledge of the entire protein content, the proteome, of normal human cerebrospinal fluid (CSF) would enable insights into neurologic and psychiatric disorders. Until now technologic hurdles and access to true normal samples hindered attaining this goal.
Methods and Principal Findings
We applied immunoaffinity separation and high sensitivity and resolution liquid chromatography-mass spectrometry to examine CSF from healthy normal individuals. 2630 proteins in CSF from normal subjects were identified, of which 56% were CSF-specific, not found in the much larger set of 3654 proteins we have identified in plasma. We also examined CSF from groups of subjects previously examined by others as surrogates for normals where neurologic symptoms warranted a lumbar puncture but where clinical laboratory were reported as normal. We found statistically significant differences between their CSF proteins and our non-neurological normals. We also examined CSF from 10 volunteer subjects who had lumbar punctures at least 4 weeks apart and found that there was little variability in CSF proteins in an individual as compared to subject to subject.
Our results represent the most comprehensive characterization of true normal CSF to date. This normal CSF proteome establishes a comparative standard and basis for investigations into a variety of diseases with neurological and psychiatric features.
Parkinson’s disease (PD) is characterized by dopaminergic neurodegeneration in the nigrostriatal region of the brain; however, the neurodegeneration extends well beyond dopaminergic neurons. To gain a better understanding of the molecular changes relevant to PD, we applied two-dimensional LC-MS/MS to comparatively analyze the proteome changes in four brain regions (striatum, cerebellum, cortex, and the rest of brain) using a MPTP-induced PD mouse model with the objective to identify nigrostriatal-specific and other region-specific protein abundance changes. The combined analyses resulted in the identification of 4,895 non-redundant proteins with at least two unique peptides per protein. The relative abundance changes in each analyzed brain region were estimated based on the spectral count information. A total of 518 proteins were observed with significant MPTP-induced changes across different brain regions. 270 of these proteins were observed with specific changes occurring either only in the striatum and/or in the rest of the brain region that contains substantia nigra, suggesting that these proteins are associated with the underlying nigrostriatal pathways. Many of the proteins that exhibit significant abundance changes were associated with dopamine signaling, mitochondrial dysfunction, the ubiquitin system, calcium signaling, the oxidative stress response, and apoptosis. A set of proteins with either consistent change across all brain regions or with changes specific to the cortex and cerebellum regions were also detected. One of the interesting proteins is ubiquitin specific protease (USP9X), a deubiquination enzyme involved in the protection of proteins from degradation and promotion of the TGF-β pathway, which exhibited altered abundances in all brain regions. Western blot validation showed similar spatial changes, suggesting that USP9X is potentially associated with neurodegeneration. Together, this study for the first time presents an overall picture of proteome changes underlying both nigrostriatal pathways and other brain regions potentially involved in MPTP-induced neurodegeneration. The observed molecular changes provide a valuable reference resource for future hypothesis-driven functional studies of PD.
mass spectrometry; mouse brain proteome; Parkinson’s disease; MPTP; LC-MS/MS; mouse model
Proteolytic processing events are essential to physiological processes such as reproduction, development, and host responses, as well as regulating proteins in cancer; therefore, there is a significant need to develop robust approaches for characterizing such events. The current mass spectrometry (MS)-based proteomics techniques employs a “bottom-up” strategy, which does not allow for identification of different proteolytic proteins since the strategy measures all the small peptides from any given protein. The aim of this development is to enable the effective identification of specific proteolytic fragments. The protocol utilizes an acetylation reaction to block the N-termini of a protein, as well as any lysine residues. Following digestion, N-terminal peptides are enriched by removing peptides that contain free amines, using amine-reactive silica-bond succinic anhydride beads. The resulting enriched sample has one N-terminal peptide per protein, which reduces sample complexity and allows for increased analytical sensitivity compared to global proteomics.1 We initially compared the peptide identification and efficiency of blocking lysine using acetic anhydride (a 42 Da modification) or propionic anhydride (a 56 Da modification) in our protocol. Both chemical reactions resulted in comparable peptide identifications and ∼95 percent efficiency for blocking lysine residues. However, the use of propionic anhydride allowed us to distinguish in vivo acetylated peptides from chemically-tagged peptides.2 In an initial experiment using mouse plasma, we were able to identify >300 unique N-termini peptides, as well as many known cleavage sites. This protocol holds potential for uncovering new information related to proteolytic pathways, which will assist our understanding about cancer biology and efforts to identify potential biomarkers for various diseases.
Nonenzymatic glycation of tissue proteins has important implications in the development of complications of diabetes mellitus. Herein we report improved methods for the enrichment and analysis of glycated peptides using boronate affinity chromatography and electron-transfer dissociation mass spectrometry, respectively. The enrichment of glycated peptides was improved by replacing an off-line desalting step with an online wash of column-bound glycated peptides using 50 mM ammonium acetate, followed by elution with 100 mM acetic acid. The analysis of glycated peptides by MS/MS was improved by considering only higher charged (≥3) precursor ions during data-dependent acquisition, which increased the number of glycated peptide identifications. Similarly, the use of supplemental collisional activation after electron transfer (ETcaD) resulted in more glycated peptide identifications when the MS survey scan was acquired with enhanced resolution. Acquiring ETD-MS/MS data at a normal MS survey scan rate, in conjunction with the rejection of both 1+ and 2+ precursor ions, increased the number of identified glycated peptides relative to ETcaD or the enhanced MS survey scan rate. Finally, an evaluation of trypsin, Arg-C, and Lys-C showed that tryptic digestion of glycated proteins was comparable to digestion with Lys-C and that both were better than Arg-C in terms of the number of glycated peptides and corresponding glycated proteins identified by LC–MS/MS.
Nonenzymatic glycation of peptides and proteins by d-glucose has important implications in the pathogenesis of diabetes mellitus, particularly in the development of diabetic complications. In this work, we report the first proteomics-based characterization of nonenzymatically glycated proteins in human plasma and erythrocyte membranes from individuals with normal glucose tolerance, impaired glucose tolerance, and type 2 diabetes mellitus. Phenylboronate affinity chromatography was used to enrich glycated proteins and glycated tryptic peptides from both human plasma and erythrocyte membranes. The enriched peptides were subsequently analyzed by liquid chromatography coupled with electron transfer dissociation-tandem mass spectrometry, resulting in the confident identification of 76 and 31 proteins from human plasma and erythrocyte membranes, respectively. Although most of the glycated proteins could be identified in samples from individuals with normal glucose tolerance, slightly higher numbers of glycated proteins and more glycation sites were identified in samples from individuals with impaired glucose tolerance and type 2 diabetes mellitus.
protein nonenzymatic glycation; Amadori compound; boronate affinity enrichment; electron transfer dissociation tandem mass spectrometry; type 2 diabetes mellitus; human plasma; erythrocyte membrane; comparative proteomics
Non-enzymatic glycation of tissue proteins has important implications in the development of complications of diabetes mellitus. While electron transfer dissociation (ETD) has been shown to outperform collision-induced dissociation (CID) in sequencing glycated peptides by tandem mass spectrometry, ETD instrumentation is not yet widely available and often suffers from significantly lower sensitivity than CID. In this study, we evaluated different advanced CID techniques (i.e., neutral-loss-triggered MS3 and multi-stage activation) during liquid chromatography/multi-stage mass spectrometric (LC/MSn) analyses of Amadori-modified peptides enriched from human serum glycated in vitro. During neutral-loss-triggered MS3 experiments, MS3 scans triggered by neutral losses of 3 H2O or 3 H2O + HCHO produced similar results in terms of glycated peptide identifications. However, neutral losses of 3 H2O resulted in significantly more glycated peptide identifications during multi-stage activation experiments. Overall, the multi-stage activation approach produced more glycated peptide identifications, while the neutral-loss-triggered MS3 approach resulted in much higher specificity. Both techniques are viable alternatives to ETD for identifying glycated peptides.