Ion mobility spectrometry in conjunction with liquid chromatography separations and mass spectrometry offers a range of new possibilities for analyzing complex biological samples. To fully utilize the information obtained from these three measurement dimensions, informatics tools based on the accurate mass and time tag methodology were modified to incorporate ion mobility spectrometry drift times for peptides observed in human serum. In this work a reference human serum database was created for 12,139 peptides and populated with the monoisotopic mass, liquid chromatography normalized elution time, and ion mobility spectrometry drift time(s) for each. We demonstrate that the use of three dimensions for peak matching during the peptide identification process resulted in an increased numbers of identifications and a lower false discovery rate relative to only using the mass and normalized elution time dimensions.
ion mobility spectrometry; mass spectrometry; peptide identification; LC-MS; LC-IMS-MS; AMT tag; false discovery rate; drift time
Polymorphonuclear neutrophils (PMNs) play an important role in mediating the innate immune response after severe traumatic injury; however, the cellular proteome response to traumatic condition is still largely unknown.
We applied 2D-LC-MS/MS based shotgun proteomics to perform comparative proteome profiling of human PMNs from severe trauma patients and healthy controls.
A total of 197 out of ~2500 proteins (being identified with at least two peptides) were observed with significant abundance changes following the injury. The proteomics data were further compared with transcriptomics data for the same genes obtained from an independent patient cohort. The comparison showed that the protein abundance changes for the majority of proteins were consistent with the mRNA abundance changes in terms of directions of changes. Moreover, increased protein secretion was suggested as one of the mechanisms contributing to the observed discrepancy between protein and mRNA abundance changes. Functional analyses of the altered proteins showed that many of these proteins were involved in immune response, protein biosynthesis, protein transport, NRF2-mediated oxidative stress response, the ubiquitin-proteasome system, and apoptosis pathways.
CONCLUSIONS AND CLINICAL RELEVANCE
Our data suggest increased neutrophil activation and inhibited neutrophil apoptosis in response to trauma. The study not only reveals an overall picture of functional neutrophil response to trauma at the proteome level, but also provides a rich proteomics data resource of trauma-associated changes in the neutrophil that will be valuable for further studies of the functions of individual proteins in PMNs.
human neutrophil; LC-MS/MS; Proteomics; Trauma; Genomics
The broad range and diversity of interferon-stimulated genes (ISGs) function to induce an antiviral state within the host, impeding viral pathogenesis. While successful respiratory viruses overcome individual ISG effectors, analysis of the global ISG response and subsequent viral antagonism has yet to be examined. Employing models of the human airway, transcriptomics and proteomics datasets were used to compare ISG response patterns following highly pathogenic H5N1 avian influenza (HPAI) A virus, 2009 pandemic H1N1, severe acute respiratory syndrome coronavirus (SARS-CoV), and Middle East respiratory syndrome CoV (MERS-CoV) infection. The results illustrated distinct approaches utilized by each virus to antagonize the global ISG response. In addition, the data revealed that highly virulent HPAI virus and MERS-CoV induce repressive histone modifications, which downregulate expression of ISG subsets. Notably, influenza A virus NS1 appears to play a central role in this histone-mediated downregulation in highly pathogenic influenza strains. Together, the work demonstrates the existence of unique and common viral strategies for controlling the global ISG response and provides a novel avenue for viral antagonism via altered histone modifications.
This work combines systems biology and experimental validation to identify and confirm strategies used by viruses to control the immune response. Using a novel screening approach, specific comparison between highly pathogenic influenza viruses and coronaviruses revealed similarities and differences in strategies to control the interferon and innate immune response. These findings were subsequently confirmed and explored, revealing both a common pathway of antagonism via type I interferon (IFN) delay as well as a novel avenue for control by altered histone modification. Together, the data highlight how comparative systems biology analysis can be combined with experimental validation to derive novel insights into viral pathogenesis.
insulin/IGF-1 receptor is a major known determinant of dauer
formation, stress resistance, longevity, and metabolism in Caenorhabditis elegans. In the past, whole-genome
transcript profiling was used extensively to study differential gene
expression in response to reduced insulin/IGF-1 signaling, including
the expression levels of metabolism-associated genes. Taking advantage
of the recent developments in quantitative liquid chromatography mass
spectrometry (LC–MS)-based proteomics, we profiled the proteomic
changes that occur in response to activation of the DAF-16 transcription
factor in the germline-less glp-4(bn2);daf-2(e1370) receptor mutant. Strikingly, the daf-2 profile
suggests extensive reorganization of intermediary metabolism, characterized
by the upregulation of many core intermediary metabolic pathways.
These include glycolysis/gluconeogenesis, glycogenesis, pentose phosphate
cycle, citric acid cycle, glyoxylate shunt, fatty acid β-oxidation,
one-carbon metabolism, propionate and tyrosine catabolism, and complexes
I, II, III, and V of the electron transport chain. Interestingly,
we found simultaneous activation of reciprocally regulated metabolic
pathways, which is indicative of spatiotemporal coordination of energy
metabolism and/or extensive post-translational regulation of these
enzymes. This restructuring of daf-2 metabolism is
reminiscent to that of hypometabolic dauers, allowing the efficient
and economical utilization of internal nutrient reserves and possibly
also shunting metabolites through alternative energy-generating pathways
to sustain longevity.
Caenorhabditis elegans; gene expression; mass spectrometry; metabolism; physiology; aging
One can interpret fragmentation spectra stemming from peptides in mass spectrometry-based proteomics experiments using so called database search engines. Frequently, one also runs post-processors such as Percolator to assess the confidence, infer unique peptides and increase the number of identifications. A recent search engine, MS-GF+, has shown promising results, due to a new and efficient scoring algorithm. However, MS-GF+ provides few statistical estimates about the peptide-spectrum matches, hence limiting the biological interpretation. Here, we enabled Percolator-processing for MS-GF+ output, and observed an increased number of identified peptides for a wide variety of datasets. In addition, Percolator directly reports p values and false discovery rate estimates, such as q values and posterior error probabilities, for peptide-spectrum matches, peptides and proteins, functions that are useful for the whole proteomics community.
Anterior gradient 2 (AGR2) is a secreted, cancer-associated protein in many types of epithelial cancer cells. We developed a highly sensitive targeted mass spectrometric assay for quantification of AGR2 in urine and serum. Digested peptides from clinical samples were processed by PRISM (high pressure and high resolution separations coupled with intelligent selection and multiplexing), which incorporates high pH reversed-phase LC separations to fractionate and select target fractions for follow-on LC-SRM analyses. The PRISM-SRM assay for AGR2 showed a reproducibility of <10% CV and LOQ values of ~130 pg/mL in serum and ~10 pg per 100 μg total protein mass in urine, respectively. A good correlation (R2 = 0.91) was observed for the measurable AGR2 concentrations in urine between SRM and ELISA. Based on an initial cohort of 37 subjects, urinary AGR2/PSA concentration ratios showed a significant difference (P = 0.026) between non-cancer and cancer. Large clinical cohort studies are needed for the validation of AGR2 as a useful diagnostic biomarker for prostate cancer. Our work validated the approach of identifying candidate secreted protein biomarkers through genomics and measurement by targeted proteomics, especially for proteins where no immunoassays are available.
AGR2; PSA; prostate cancer; PRISM-SRM; human urine; human serum
Individual proteomes typically differ from the reference human proteome at ~10,000 single amino acid variants. When viewed at the population scale, this individual variation results in a wide variety of protein sequences. In targeted proteomics experiments, such variability can confound accurate protein quantification. To assist researchers in identifying target peptides with high variability within the human population we have created the Population Variation plug-in for Skyline, which provides easy access to the polymorphisms stored in dbSNP. Given a set of peptides, the tool reports minor allele frequency for common polymorphisms. We highlight the importance of considering genetic variation by applying the tool to public datasets.
MRM/SRM; genetic variation; bioinformatics; dbSNP
Electrospray ionization mass spectrometry (ESI-MS) at flow rates below ~10 nL/min has been only sporadically explored due to difficulty in reproducibly fabricating emitters that can operate at lower flow rates. Here we demonstrate narrow orifice chemically etched emitters for stable electrospray at flow rates as low as 400 pL/min. Depending on the analyte concentration, we observe two types of MS signal response as a function of flow rate. At low concentrations, an optimum flow rate is observed slightly above 1 nL/min, while the signal decreases monotonically with decreasing flow rates at higher concentrations. For example, consumption of 500 zmol of sample yielded signal-to-noise ratios ~10 for some peptides. In spite of lower MS signal, the ion utilization efficiency increases exponentially with decreasing flow rate in all cases. Significant variations in ionization efficiency were observed within this flow rate range for an equimolar mixture of peptides, indicating that ionization efficiency is an analyte-dependent characteristic for the present experimental conditions. Mass-limited samples benefit strongly from the use of low flow rates and avoiding unnecessary sample dilution. These findings have important implications for the analysis of trace biological samples.
Cyanothece sp. PCC 7822 is an excellent cyanobacterial model organism with great potential to be applied as a biocatalyst for the production of high value compounds. Like other unicellular diazotrophic cyanobacterial species, it has a tightly regulated metabolism synchronized to the light–dark cycle. Utilizing transcriptomic and proteomic methods, we quantified the relationships between transcription and translation underlying central and secondary metabolism in response to nitrogen free, 12 hour light and 12 hour dark conditions.
By combining mass-spectrometry based proteomics and RNA-sequencing transcriptomics, we quantitatively measured a total of 6766 mRNAs and 1322 proteins at four time points across a 24 hour light–dark cycle. Photosynthesis, nitrogen fixation, and carbon storage relevant genes were expressed during the preceding light or dark period, concurrent with measured nitrogenase activity in the late light period. We describe many instances of disparity in peak mRNA and protein abundances, and strong correlation of light dependent expression of both antisense and CRISPR-related gene expression. The proteins for nitrogenase and the pentose phosphate pathway were highest in the dark, whereas those for glycolysis and the TCA cycle were more prominent in the light. Interestingly, one copy of the psbA gene encoding the photosystem II (PSII) reaction center protein D1 (psbA4) was highly upregulated only in the dark. This protein likely cannot catalyze O2 evolution and so may be used by the cell to keep PSII intact during N2 fixation. The CRISPR elements were found exclusively at the ends of the large plasmid and we speculate that their presence is crucial to the maintenance of this plasmid.
This investigation of parallel transcriptional and translational activity within Cyanothece sp. PCC 7822 provided quantitative information on expression levels of metabolic pathways relevant to engineering efforts. The identification of expression patterns for both mRNA and protein affords a basis for improving biofuel production in this strain and for further genetic manipulations. Expression analysis of the genes encoded on the 6 plasmids provided insight into the possible acquisition and maintenance of some of these extra-chromosomal elements.
Electronic supplementary material
The online version of this article (doi:10.1186/1471-2164-15-1185) contains supplementary material, which is available to authorized users.
Cyanothece; Cyanobacteria; RNA-Seq; N2 fixation; Proteomics; Butanol; CRISPR
O -GlcNAcylation is a dynamic protein post-translational modification of serine or threonine residues by an O-linked monosaccharide N-acetylglucosamine (O-GlcNAc). O-GlcNAcylation was discovered three decades ago and its significance has been implicated in several disease states, such as metabolic diseases, cancer and neurological diseases. Yet it remains technically challenging to characterize comprehensively and quantitatively because of its low abundance, low stoichiometry and extremely labile nature under conventional collision-induced dissociation tandem MS conditions. Herein, we review the recent advances addressing these challenges in developing proteomic approaches for site-specific O-GlcNAcylation analysis, including specific enrichment of O-GlcNAc peptides/proteins, unambiguous site-determination of O-GlcNAc modification and quantitative analysis of O-GlcNAcylation.
The development of liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) has made it possible to measure phosphopeptides on an increasingly large-scale and high-throughput fashion. However, extracting confident phosphopeptide identifications from the resulting large dataset in a similar high-throughput fashion remains difficult, as does rigorously estimating the false discovery rate (FDR) of a set of phosphopeptide identifications. This article describes a data analysis pipeline designed to address these issues. The first step is to re-analyze phosphopeptide identifications that contain ambiguous assignments for the incorporated phosphate(s) to determine the most likely arrangement of the phosphate(s). The next step is to employ an expectation maximization algorithm to estimate the joint distribution of the SEQUEST scores. A linear discriminant analysis is then performed to determine how to optimally combine peptide scores (in this case, SEQUEST) into a discriminant score that possesses the maximum discriminating power. Based on this discriminant score, the p- and q-values for each phosphopeptide identification are calculated, and the phosphopeptide identification FDR is then estimated. This data analysis approach was applied to data from a study of irradiated human skin fibroblasts to provide a robust estimate of FDR for phosphopeptides, and has been coded into a software package that is freely available (http://ncrr.pnl.gov/downloads/data/Du2008_Supplementary_Data.zip).
False Discovery Rate; phosphoproteomics; expectation maximization; linear discriminant analysis; p-value; q-value; Bayesian analysis
Cancer is driven by the acquisition of somatic DNA lesions. Distinguishing the early driver mutations from subsequent passenger mutations is key to molecular sub-typing of cancers, understanding cancer progression, and the discovery of novel biomarkers. The advances of genomics technologies (whole-genome exome, and transcript sequencing, collectively referred to as NGS(Next Gengeration Sequencing)) have fueled recent studies on somatic mutation discovery. However, the vision is challenged by the complexity, redundancy, and errors in genomic data, and the difficulty of investigating the proteome translated portion of aberrant genes using only genomic approaches. Combination of proteomic and genomic technologies are increasingly being employed.
Various strategies have been employed to allow the usage of large scale NGS data for conventional MS/MS searches. This paper provides a discussion of applying different strategies relating to large database search, and FDR(False Discovery Rate) based error control, and their implication to cancer proteogenomics. Moreover, it extends and develops the idea of a unified genomic variant database that can be searched by any mass spectrometry sample. A total of 879 BAM files downloaded from TCGA repository were used to create a 4.34 GB unified FASTA database which contained 2, 787, 062 novel splice junctions, 38, 464 deletions, 1, 105 insertions, and 182, 302 substitutions. Proteomic data from a single ovarian carcinoma sample (439, 858 spectra) was searched against the database. By applying the most conservative FDR measure, we have identified 524 novel peptides and 65, 578 known peptides at 1% FDR threshold. The novel peptides include interesting examples of doubly mutated peptides, frame-shifts, and non-sample-recruited mutations, which emphasize the strength of our approach.
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
Arrays of chemically etched emitters with individualized sheath gas capillaries were developed to enhance electrospray ionization (ESI) efficiency at subambient pressures. By incorporating the new emitter array in a subambient pressure ionization with nanoelectrospray (SPIN) source, both ionization efficiency and ion transmission efficiency were significantly increased, providing enhanced sensitivity in mass spectrometric analyses. The SPIN source eliminates the major ion losses of conventional ESI-mass spectrometry (MS) interfaces by placing the emitter in the first reduced pressure region of the instrument. The new ESI emitter array design developed in this study allows individualized sheath gas around each emitter in the array making it possible to generate an array of uniform and stable electrosprays in the subambient pressure (10 to 30 Torr) environment for the first time. The utility of the new emitter arrays was demonstrated by coupling the emitter array/SPIN source with a time of flight (TOF) mass spectrometer. The instrument sensitivity was compared under different ESI source and interface configurations including a standard atmospheric pressure single ESI emitter/heated capillary, single emitter/SPIN and multi-emitter/SPIN configurations using an equimolar solution of 9 peptides. The highest instrument sensitivity was observed using the multi-emitter/SPIN configuration in which the sensitivity increased with the number of emitters in the array. Over an order of magnitude MS sensitivity improvement was achieved using multi-emitter/SPIN as compared to using the standard atmospheric pressure single ESI emitter/heated capillary interface.
Applying Hadamard transform multiplexing to ion mobility separations (IMS) can significantly improve the signal-to-noise ratio and throughput for IMS coupled mass spectrometry (MS) measurements by increasing the ion utilization efficiency. However, it has been determined that fluctuations in ion intensity as well as spatial shifts in the multiplexed data lower the signal-to-noise ratios and appear as noise in downstream processing of the data. To address this problem, we have developed a novel algorithm that discovers and eliminates data artifacts. The algorithm employs an analytical approach to identify and remove artifacts from the data, decreasing the likelihood of false identifications in subsequent data processing. Following application of the algorithm, IMS-MS measurement sensitivity is greatly increased and artifacts that previously limited the utility of applying the Hadamard transform to IMS are avoided.
Ion mobility; Computational proteomics; Hadamard transform; Bioinformatics; Sensitivity; Data analysis
Cell fusion in genetically identical Neurospora crassa germlings and in hyphae is a highly regulated process involving the activation of a conserved MAP kinase cascade that includes NRC-1, MEK-2 and MAK-2. During chemotrophic growth in germlings, the MAP kinase cascade members localize to conidial anastomosis tube (CAT) tips every ∼8 minutes, perfectly out of phase with another protein that is recruited to the tip: SOFT, a recently identified scaffold for the MAK-1 MAP kinase pathway in Sordaria macrospora. How the MAK-2 oscillation process is initiated, maintained and what proteins regulate the MAP kinase cascade is currently unclear. A global phosphoproteomics approach using an allele of mak-2 (mak-2Q100G) that can be specifically inhibited by the ATP analog 1NM-PP1 was utilized to identify MAK-2 kinase targets in germlings that were potentially involved in this process. One such putative target was HAM-5, a protein of unknown biochemical function. Previously, Δham-5 mutants were shown to be deficient for hyphal fusion. Here we show that HAM-5-GFP co-localized with NRC-1, MEK-2 and MAK-2 and oscillated with identical dynamics from the cytoplasm to CAT tips during chemotropic interactions. In the Δmak-2 strain, HAM-5-GFP localized to punctate complexes that did not oscillate, but still localized to the germling tip, suggesting that MAK-2 activity influences HAM-5 function/localization. However, MAK-2-GFP showed cytoplasmic and nuclear localization in a Δham-5 strain and did not localize to puncta. Via co-immunoprecipitation experiments, HAM-5 was shown to physically interact with NRC-1, MEK-2 and MAK-2, suggesting that it functions as a scaffold/transport hub for the MAP kinase cascade members for oscillation and chemotropic interactions during germling and hyphal fusion in N. crassa. The identification of HAM-5 as a scaffold-like protein will help to link the activation of MAK-2 cascade to upstream factors and proteins involved in this intriguing process of fungal communication.
Cell fusion between genetically identical cells of the fungus Neurospora crassa occurs when germinating asexual cells (conidia) sense each other's proximity and redirect their growth. Chemotropic growth is dependent upon the assembly of a MAPK cascade (NRC-1/MEK-2/MAK-2) at the cell cortex (conidial anastomosis tubes; CATs), followed by disassembly over an ∼8 min cycle. A second protein required for fusion, SO, also assembles and disassembles at CAT tips during chemotropic growth, but with perfectly opposite dynamics to the MAK-2 complex. This process of germling chemotropism, oscillation and cell fusion is regulated by many genes and is poorly understood. Via a phosphoproteomics approach, we identify HAM-5, which functions as a scaffold for the MAK-2 signal transduction complex. HAM-5 is required for assembly/disassembly and oscillation of the MAK-2 complex during chemotropic growth. Our data supports a model whereby regulated modification of HAM-5 controls the disassembly of the MAK-2 MAPK complex and is essential for modulating the tempo of oscillation during chemotropic interactions.
MS dissociation methods, including CID, HCD, and ETD, can each contribute distinct peptidome identifications using conventional peptide identification methods (Shen et al. J. Proteome Res. 2011), but such samples still pose significant informatics challenges. In this work, we explored utilization of high accuracy fragment ion mass measurements, in this case provided by FT MS/MS, to improve peptidome peptide dataset size and consistency relative to conventional descriptive and probabilistic scoring methods. For example, we identified 20–40% more peptides than SEQUEST, Mascot, and MS-GF scoring methods using high accuracy fragment ion information and the same FDR (e.g., <10 mass errors) from CID, HCD, and ETD spectra. Identified species covered >90% of the collective identifications obtained using various conventional peptide identification methods, which resolves the issue of different data analysis methods generating different peptide datasets. Choice of peptide dissociation and high-precision measurement-based identification methods presently available for degradomic-peptidomic analyses needs to be based on the coverage and confidence (or specificity) afforded by the method, as well as practical issues (e.g., throughput). By using accurate fragment information, >1000 peptidome peptides can be identified from a single human blood plasma sample with low peptide-level FDRs (e.g., 0.6%), providing an improved basis for investigating potential disease-related peptidome components.
FT MS/MS; CID; HCD; ETD; peptides; non-tryptic peptides; peptidome; degradome; merging of spectra; scoring of spectra
Motivation: The addition of ion mobility spectrometry to liquid chromatography-mass spectrometry experiments requires new, or updated, software tools to facilitate data processing.
Results: We introduce a command line software application LC-IMS-MS Feature Finder that searches for molecular ion signatures in multidimensional liquid chromatography-ion mobility spectrometry-mass spectrometry (LC-IMS-MS) data by clustering deisotoped peaks with similar monoisotopic mass, charge state, LC elution time and ion mobility drift time values. The software application includes an algorithm for detecting and quantifying co-eluting chemical species, including species that exist in multiple conformations that may have been separated in the IMS dimension.
Availability: LC-IMS-MS Feature Finder is available as a command-line tool for download at http://omics.pnl.gov/software/LC-IMS-MS_Feature_Finder.php. The Microsoft.NET Framework 4.0 is required to run the software. All other dependencies are included with the software package. Usage of this software is limited to non-profit research to use (see README).
Supplementary data are available at Bioinformatics online.
Removal of highly abundant proteins in plasma is often carried out using immunoaffinity depletion to extend the dynamic range of measurements to lower abundance species. While commercial depletion columns are available for this purpose, they generally are not applicable to limited sample quantities (<20 μL) due to low yields stemming from losses caused by nonspecific binding to the column matrix and concentration of large eluent volumes. Additionally, the cost of the depletion media can be prohibitive for larger-scale studies. Modern LC-MS instrumentation provides the sensitivity necessary to scale-down depletion methods with minimal sacrifice to proteome coverage, which makes smaller volume depletion columns desirable for maximizing sample recovery when samples are limited, as well as for reducing the expense of large-scale studies. We characterized the performance of a 346 μL column volume microscale depletion system, using four different flow rates to determine the most effective depletion conditions for ~6-μL injections of human plasma proteins and then evaluated depletion reproducibility at the optimum flow rate condition. Depletion of plasma using a commercial 10-mL depletion column served as the control. Results showed depletion efficiency of the microscale column increased as flow rate decreased, and that our microdepletion was reproducible. In an initial application, a 600-μL sample of human cerebrospinal fluid (CSF) pooled from multiple sclerosis patients was depleted and then analyzed using reversed phase liquid chromatography-mass spectrometry to demonstrate the utility of the system for this important biofluid where sample quantities are more commonly limited.
Microscale depletion; IgY-14 immunoaffinity resin; Human plasma; Cerebrospinal fluid; MS
Fusions between the transmembrane protease serine 2 (TMPRSS2) and ETS related gene (ERG) represent one of the most specific biomarkers that define a distinct molecular subtype of prostate cancer. Studies of TMPRSS2-ERG gene fusions have seldom been performed at the protein level, primarily due to the lack of high-quality antibodies suitable for quantitative studies. Herein, we applied a recently developed PRISM (high-pressure high-resolution separations with intelligent selection and multiplexing)-SRM (selected reaction monitoring) strategy for quantifying ERG protein in prostate cancer cell lines and tumors. The highly sensitive PRISM-SRM assays provided confident detection of 6 unique ERG peptides in both TMPRSS2-ERG positive cell lines and tissues, but not in cell lines or tissues lacking the TMPRSS2-ERG rearrangement, clearly indicating that ERG protein expression is significantly increased in the presence of the TMPRSS2-ERG gene fusion. Significantly, our results provide evidence that two distinct ERG protein isoforms are simultaneously expressed in TMPRSS2-ERG positive samples as evidenced by the concomitant detection of two mutually exclusive peptides in two patient tumors and in the VCaP prostate cancer cell line. Three peptides, shared across almost all fusion protein products, were determined to be the most abundant peptides, providing “signature” peptides for detection of ERG over-expression resulting from TMPRSS2-ERG gene fusion. The PRISM-SRM assays provide valuable tools for studying TMPRSS2-ERG gene fusion protein products in prostate cancer.
TMPRSS2-ERG gene fusion; ERG protein isoform; PRISM-SRM; Targeted quantification; Prostate cancer
We report on the performance of structures for lossless ion manipulation (SLIM) as a means for transmitting ions and performing ion mobility separations (IMS). Ions were successfully transferred from an electrospray ionization (ESI) source to the TOF MS analyzer by means of a linear SLIM, demonstrating lossless ion transmission and an alternative arrangement including a 90° turn. First, the linear geometry was optimized for radial confinement by tuning RF on the central “rung” electrodes and potentials on the DC-only guard electrodes. Selecting an appropriate DC guard bias (2–6 V) and RF amplitude (≥160 Vp-p at 750 kHz) resulted in the greatest ion intensities. Close to ideal IMS resolving power was maintained over a significant range of applied voltages. Second, the 90° turn was optimized for radial confinement by tuning RF on the rung electrodes and DC on the guard electrodes. However, both resolving power and ion transmission showed a dependence on these voltages, and the best conditions for both were >300 Vp-p RF (685 kHz) and 7–11 V guard DC bias. Both geometries provide IMS resolving powers at the theoretical limit (R ~ 58), showing that degraded resolution from a “racetrack” effect from turning around a corner can be successfully avoided, and the capability also was maintained for essentially lossless ion transmission.
We have identified candidate protein and microRNA (miRNA) biomarkers for dyspnea by studying serum, lavage fluid, and urine from military personnel who reported serious respiratory symptoms after they were deployed to Iraq or Afghanistan.
Forty-seven soldiers with the complaint of dyspnea who enrolled in the STudy of Active Duty Military Personnel for Environmental Dust Exposure (STAMPEDE) underwent comprehensive pulmonary evaluations at the San Antonio Military Medical Center. The evaluation included fiber-optic bronchoscopy with bronchoalveolar lavage. The clinical findings from the STAMPEDE subjects pointed to seven general underlying diagnoses or findings including airway hyperreactivity, asthma, low diffusivity of carbon monoxide, and abnormal cell counts. The largest category was undiagnosed. As an exploratory study, not a classification study, we profiled proteins or miRNAs in lavage fluid, serum, or urine in this group to look for any underlying molecular patterns that might lead to biomarkers. Proteins in lavage fluid and urine were identified by accurate mass tag (database-driven) proteomics methods while miRNAs were profiled by a hybridization assay applied to serum, urine, and lavage fluid.
Over seventy differentially expressed proteins were reliably identified both from lavage and from urine in forty-eight dyspnea subjects compared to fifteen controls with no known lung disorder. Six of these proteins were detected both in urine and lavage. One group of subjects was distinguished from controls by expressing a characteristic group of proteins. A related group of dyspnea subjects expressed a unique group of miRNAs that included one miRNA that was differentially overexpressed in all three fluids studied. The levels of several miRNAs also showed modest but direct associations with several standard clinical measures of lung health such as forced vital capacity or gas exchange efficiency.
Candidate proteins and miRNAs associated with the general diagnosis of dyspnea have been identified in subjects with differing medical diagnoses. Since these markers can be measured in readily obtained clinical samples, further studies are possible that test the value of these findings in more formal classification or case–control studies in much larger cohorts of subjects with specific lung diseases such as asthma, emphysema, or some other well-defined lung disease.
Dyspnea; Biomarkers; Lavage fluid; Serum; Urine; Proteomics; MicroRNAs
Due to their high sensitivity and specificity, selected reaction monitoring (SRM) based targeted proteomics has become increasingly popular for biological and translational applications. Selection of optimal transitions and optimization of collision energy (CE) are important assay development steps for achieving sensitive detection and accurate quantification; however, these steps can be labor-intensive, especially, for large-scale applications. Herein, we explored several options for accelerating SRM assay development evaluated in the context of a relatively large set of 215 synthetic peptide targets. We first showed that HCD fragmentation is very similar to CID in triple quadrupole (QQQ) instrumentation, and by selection of the top six y fragment ions from HCD spectra, >86% of the top transitions optimized from direct infusion on QQQ instrument are covered. We also demonstrated that the CE calculated by existing prediction tools was less accurate for 3+ precursors, and a significant increase in intensity for transitions could be obtained using a new CE prediction equation constructed from the present experimental data. Overall, our study illustrated the feasibility of expediting the development of larger numbers of high-sensitivity SRM assays through automation of transition selection and accurate prediction of optimal CE to improve both SRM throughput and measurement quality.
SRM; MRM; HCD; QQQ; transition selection; optimization; CE prediction; targeted quantification
The National Cancer Institute (NCI) Clinical Proteomic Tumor Analysis Consortium (CPTAC) is applying latest generation of proteomic technologies to genomically annotated tumors from The Cancer Genome Atlas (TCGA) program, a joint initiative of the NCI and National Human Genome Research Institute. By providing a fully integrated accounting of DNA, RNA and protein abnormalities in individual tumors, these datasets will illuminate the complex relationship between genomic abnormalities and cancer phenotypes, thus producing biological insights as well as a wave of novel candidate biomarkers and therapeutic targets amenable to verification using targeted mass spectrometry methods.
Gene Expression; Cancer Proteomics; Protein Phosphorylation; Mass Spectrometry; Cancer Genome Atlas
Long-gradient separations coupled to tandem MS were recently demonstrated to provide a deep proteome coverage for global proteomics; however, such long-gradient separations have not been explored for targeted proteomics. Herein, we investigate the potential performance of the long-gradient separations coupled with selected reaction monitoring (LG-SRM) for targeted protein quantification. Direct comparison of LG-SRM (5 h gradient) and conventional LC-SRM (45 min gradient) showed that the long-gradient separations significantly reduced background interference levels and provided an 8- to 100-fold improvement in LOQ for target proteins in human female serum. Based on at least one surrogate peptide per protein, an LOQ of 10 ng/mL was achieved for the two spiked proteins in non-depleted human serum. The LG-SRM detection of seven out of eight endogenous plasma proteins expressed at ng/mL or sub-ng/mL levels in clinical patient sera was also demonstrated. A correlation coefficient of >0.99 was observed for the results of LG-SRM and ELISA measurements for prostate-specific antigen (PSA) in selected patient sera. Further enhancement of LG-SRM sensitivity was achieved by applying front-end IgY14 immunoaffinity depletion. Besides improved sensitivity, LG-SRM potentially offers much higher multiplexing capacity than conventional LC-SRM due to an increase in average peak widths (~3-fold) for a 300-min gradient compared to a 45-min gradient. Therefore, LG-SRM holds great potential for bridging the gap between global and targeted proteomics due to its advantages in both sensitivity and multiplexing capacity.
long-gradient; targeted quantification; low-abundance protein; human serum; sensitivity; reproducibility