Unique Peptide Identifications Research Articles

A calibration routine for efficient ETD in large-scale proteomics.

Electron transfer dissociation (ETD) has been broadly adopted and is now available on a variety of commercial mass spectrometers. Unlike collisional activation techniques, optimal performance of ETD requires considerable user knowledge and input. ETD reaction duration is one key parameter that can greatly influence spectral quality and overall experiment outcome. We describe a calibration routine that determines the correct number of reagent anions necessary to reach a defined ETD reaction rate. Implementation of this automated calibration routine on two hybrid Orbitrap platforms illustrate considerable advantages, namely, increased product ion yield with concomitant reduction in scan rates netting up to 75% more unique peptide identifications in a shotgun experiment. Graphical Abstract ᅟ.

Comparison of fractionation strategies for offline two-dimensional liquid chromatography tandem mass spectrometry analysis of proteins from mouse adipose tissue

In the frame of protein identification from mouse adipose tissue, two strategies were compared for the offline elution of peptides from a strong cation exchange (SCX) column in two-dimensional liquid chromatography tandem mass spectrometry (2D–LC–MS/MS) analyses. First, the salt gradient (using K+ as displacing agent) was evaluated from 25 to 500mM KCl. Then, a less investigated elution mode using a pH gradient (using citric acid and ammonium hydroxide) was carried out from pH 2.5 to 9.0. Equal amounts of peptide digest derived from mouse adipose tissue were loaded onto the SCX column and fractionated according to the two approaches. A total of 15 fractions were collected in two independent experiments for each SCX elution strategy. Then, each fraction was analyzed on a nanoLC–MS/MS platform equipped with a column-switching unit for desalting and enrichment. No substantial differences in peptide quality characteristics (molecular weight, isoelectric point, or GRAVY [grand average of hydropathicity] index distributions) were observed between the two datasets. The pH gradient approach was found to be superior, with 27.5% more unique peptide identifications and 10% more distinct protein identifications compared with the salt-based elution method. In conclusion, our data imply that the pH gradient SCX fractionation is more desirable for proteomics analysis of entire adipose tissue.

Can "normal" protein expression ranges be estimated with high-throughput proteomics?

Although biological science discovery often involves comparing conditions to a normal state, in proteomics little is actually known about normal. Two Human Proteome studies featured in Nature offer new insights into protein expression and an opportunity to assess how high-throughput proteomics measures normal protein ranges. We use data from these studies to estimate technical and biological variability in protein expression and compare them to other expression data sets from normal tissue. Results show that measured protein expression across same-tissue replicates vary by ±4- to 10-fold for most proteins. Coefficients of variation (CV) for protein expression measurements range from 62% to 117% across different tissue experiments; however, adjusting for technical variation reduced this variability by as much as 50%. In addition, the CV could also be reduced by limiting comparisons to proteins with at least 3 or more unique peptide identifications as the CV was on average 33% lower than for proteins with 2 or fewer peptide identifications. We also selected 13 housekeeping proteins and genes that were expressed across all tissues with low variability to determine their utility as a reference set for normalization and comparative purposes. These results present the first step toward estimating normal protein ranges by determining the variability in expression measurements through combining publicly available data. They support an approach that combines standard protocols with replicates of normal tissues to estimate normal protein ranges for large numbers of proteins and tissues. This would be a tremendous resource for normal cellular physiology and comparisons of proteomics studies.

Fast photochemical oxidation of proteins coupled to multidimensional protein identification technology (MudPIT): expanding footprinting strategies to complex systems.

Peptides containing the oxidation products of hydroxyl radical-mediated protein footprinting experiments are typically much less abundant than their unoxidized counterparts. This is inherent to the design of the experiment as excessive oxidation may lead to undesired conformational changes or unfolding of the protein, skewing the results. Thus, as the complexity of the systems studied using this method expands, the detection and identification of these oxidized species can be increasingly difficult with the limitations of data-dependent acquisition (DDA) and one-dimensional chromatography. Here we report the application of multidimensional protein identification technology (MudPIT) in combination with hydroxyl radical footprinting as a method to increase the identification of quantifiable peptides in these experiments. Using this method led to a 37% increase in unique peptide identifications as well as a 70% increase in protein group identifications over one-dimensional data-dependent acquisition on the same samples. Furthermore, we demonstrate the combination of these methods as a means to investigate megadalton complexes.

Ultrasensitive proteome analysis using paramagnetic bead technology.

In order to obtain a systems-level understanding of a complex biological system, detailed proteome information is essential. Despite great progress in proteomics technologies, thorough interrogation of the proteome from quantity-limited biological samples is hampered by inefficiencies during processing. To address these challenges, here we introduce a novel protocol using paramagnetic beads, termed Single-Pot Solid-Phase-enhanced Sample Preparation (SP3). SP3 provides a rapid and unbiased means of proteomic sample preparation in a single tube that facilitates ultrasensitive analysis by outperforming existing protocols in terms of efficiency, scalability, speed, throughput, and flexibility. To illustrate these benefits, characterization of 1,000 HeLa cells and single Drosophila embryos is used to establish that SP3 provides an enhanced platform for profiling proteomes derived from sub-microgram amounts of material. These data present a first view of developmental stage-specific proteome dynamics in Drosophila at a single-embryo resolution, permitting characterization of inter-individual expression variation. Together, the findings of this work position SP3 as a superior protocol that facilitates exciting new directions in multiple areas of proteomics ranging from developmental biology to clinical applications.

Deep Proteomic Profiling Predicts Differential Chemosensitivity In Anaplastic Large Cell Lymphoma Cell Lines

BackgroundThe lymphoma proteome is the phenotypic representation of the underlying genetic and epigenetic makeup of each individual patient's tumor. The proteome is rich in druggable targets and offers a unique opportunity for the hematologist to personalize therapy. We developed a deep proteomic profiling method using ion exchange fractionation and tandem mass spectrometry. In this pilot study, we applied this method to detect differentially expressed proteins in anaplastic large cell lymphoma (ALCL) cell lines with previously known (ALK-positive) and unknown (ALK-negative) therapeutic targets. We then asked whether integrative informatic analysis of these data could be used to predict drug sensitivity in each of the cell lines. MethodsTo examine reproducibility of our method, proteins were extracted independently from 4 pellets each of FE-PD (ALK-negative) and Karpas 299 (ALK-positive) ALCL cells, reduced with dithiothreitol, alkylated with iodoacetamide, and digested with trypsin. Resulting peptides were separated into 6 fractions using strong anion exchange (SAX) chromatography. Peptides in each fraction were analyzed via shotgun proteomics on a QExactive mass spectrometer. Peptide mass spectra (MS/MS) were matched against a RefSeq human protein sequence database using MyriMatch software. Reversed sequences were added to the database to measure identification false discovery rates (FDRs). IDPicker filtered the peptide identifications at 2% FDR. Proteins with at least two unique peptide identifications and five MS/MS matches were considered to be present in the sample. Filtered protein identifications and corresponding spectral counts were used as input to QuasiTel software, which was configured to use proteins with at least one spectrum per biological replicate. Proteins that were significantly differentially expressed (quasi p-value < 0.05) with an absolute log2 fold-change of at least 0.5 fold were loaded into the Ingenuity Pathway Analysis (IPA) software, and a master list of drugs and corresponding gene targets was assembled using PharmGKB database and the Drug-Gene Interaction Database (DGID). The resulting drug-gene target list was merged with the differentially expressed protein identifications. Candidate targets were validated by Western blot and candidate drugs were assessed in viability assays. ResultsThe SAX-LC-MS/MS method identified 10,111 proteins from all replicate analyses of FE-PD and Karpas 299 samples, and 93% of the identified proteome was detected in all 4 replicate analyses. The detected proteome was well represented by key transcription factors, phophatases, kinases, translation regulators and transmembrane regulators. There were 1369 proteins differentially expressed between the 2 cell lines, 709 up regulated in Karpas 299 cell line and 673 up regulated in FE-PD. Differentially expressed proteins also showed consistent expression across the biological replicates (Figure 1). Our integrated approach to identify candidate targets and drugs “rediscovered” ALK in Karpas299 and unexpectedly identified relative overexpression of the IL2-IL2RA-STAT5A-STAT5B network in ALK-negative FE-PD cells. Western blot confirmed these findings. As expected, 50-100 nM crizotinib (ALK inhibitor) decreased Karpas 299 viability (p =0.016) but had no effect on FE-PD (Figure 2). In contrast, 50-100 nM of the experimental STAT5 inhibitor 573108 (EMD Millipore) decreased FE-PD viability (p=0.002) but had no effect on Karpas 299 (Figure 2). [Display omitted] [Display omitted] ConclusionThe lymphoma proteome is complex with 10,000 proteins and contains druggable targets that can be reproducibly identified using SAX-LC-MS/MS. These targets vary across samples and integrated informatic analysis can predict target-drug combinations that have efficacy in an experimental model. These data suggest that SAX-LC-MS/MS could be used to personalize treatment regimens in lymphoma patients. Figure 1: Spectral counts of 1369 differentially expressed proteins between Karpas299 and FE-PD cell lines were normalized and plotted in a heat map. Red color indicates down regulation and yellow color indicates up regulation. Disclosures:No relevant conflicts of interest to declare.

Mass Spectrometry-Based Proteomics Reveals Distinct Immunoglobulin Light Chain Variable Region Usage In Systemic Versus Localized AL Amyloidosis

BackgroundImmunoglobulin light chain-associated amyloidosis (AL) is caused by deposition of immunoglobulin light chain molecules with unique, clonotypic variable (V) regions. Detection and identification of the V region, however, has been challenging due heterogeneity inherent in V regions. We developed a new method for detecting IGKV and IGLV region fragments in AL deposits using protein mass spectrometry and novel bioinformatics approach. We report distinct IGKV and IGLV usage in localized versus systemic AL. MethodsShotgun protein mass spectrometry on amyloid plaques was performed as previously described (Blood. 2009; 114: 4957-9). Peptide tandem mass spectra (MS/MS) were searched against a composite sequence database containing SwissProt's human complete proteome augmented with 1764 IG V region sequences obtained from ImMunoGeneTics database and a Mayo Clinic internal database. Reversed sequences were appended to the database for estimating identification false discovery rates (FDRs). Peptide identifications were processed with Scaffold software. Confident protein identifications (probability > 0.9) with at least one unique peptide identifications and five MS/MS matches were considered. Detected variable gene family (if any) with most number of peptide and spectral matches is considered to be present in the deposit. The method was first validated in 8 cases of AL amyloidosis with known IGKV and IGLV region sequences and then applied on 1238 systemic and 393 localized AL cases. Differences between groups were measured by generating hypergeometric p-values. ResultsIn all 8 AL cases with known IGKV and IGLV region usage, gene family identified in the AL deposit via proteomics matched the gene family inferred from bone marrow plasma cells by Sanger sequencing of IGLC genes.Armed with this method, we analyzed the amyloid proteomics data from 1238 patients with systemic AL amyloidosis and 393 patients with localized AL amyloidosis. The anatomical site distribution in systemic cohort was 296 GI tract, 364 heart, 225 kidney, 81 liver and 272 fat aspirate; Localized cohort has 78 bladder, 158 lung and 157 skin cases. Figure 1 shows the normalized frequency of the variable gene families detected between the systemic and localized AL amyloidosis. For AL-kappa, KV1 was more prevalent in systemic cases when compared to localized cases (p=7.2E-12) suggesting KV1 clones as a hallmark for systemic AL-kappa amyloidosis. KV3 was more frequently seen in localized AL-kappa cases when compared to systemic AL-kappa cases (p =2.8E-11). For AL-lambda, LV1 and LV2 gene families were more prevalent in localized cases when compared to systemic cases (p= 0.039 and 2.7E-05). LV6 was more prevalent in systemic AL-lambda cases (p=1.4E-07). We also detected a higher incidence of mixed AL/AH type in localized AL (18%) when compared to systemic AL (5%; Odds Ratio=4.2673, p<0.0001). [Display omitted] We next turned to the organ specific IGKV and IGLV gene family usage patterns in patients with localized amyloidosis. For 147 localized AL-kappa cases, KV3 was most dominant in lung (64%) and KV1 was dominant in skin (38%). For 246 localized AL-lambda cases, LV2 was most prevalent in lung (34%) and LV3 was most prevalent in skin (36%). For bladder, both LV1 and LV2 had comparable prevalence (42% and 32%).For 361 systemic AL-kappa cases, KV1 consistently ranked at the top of gene families used in GI tract (55%), heart (71%), kidney (59%), liver (75%) and fat aspirate (50%). For 877 systemic AL-lambda cases, LV2 was predominant in GI tract (30%), LV3 in heart (35%) and LV6 in kidney (33%). The prevalence of LV1, LV2 and LV3 in liver is comparable (36%, 22% and 31%). LV6 and LV3 had comparable prevalence (22% and 24%) in AL-lambda fat aspirates. ConclusionThe novel proteomics method detects IGLC V family usage in large cohorts of AL patients. It identifies unique profiles in systemic and localized cases, and in different organ sites. This information will be helpful in determining systemic versus localized nature of AL amyloidosis at diagnosis and to assess risk of specific end organ involvement. We found also a strong association between IGKV and IGLV gene usage and organ involvement. Disclosures:No relevant conflicts of interest to declare.

The One Hour Yeast Proteome

We describe the comprehensive analysis of the yeast proteome in just over one hour of optimized analysis. We achieve this expedited proteome characterization with improved sample preparation, chromatographic separations, and by using a new Orbitrap hybrid mass spectrometer equipped with a mass filter, a collision cell, a high-field Orbitrap analyzer, and, finally, a dual cell linear ion trap analyzer (Q-OT-qIT, Orbitrap Fusion). This system offers high MS2 acquisition speed of 20 Hz and detects up to 19 peptide sequences within a single second of operation. Over a 1.3 h chromatographic method, the Q-OT-qIT hybrid collected an average of 13,447 MS1 and 80,460 MS2 scans (per run) to produce 43,400 (x̄) peptide spectral matches and 34,255 (x̄) peptides with unique amino acid sequences (1% false discovery rate (FDR)). On average, each one hour analysis achieved detection of 3,977 proteins (1% FDR). We conclude that further improvements in mass spectrometer scan rate could render comprehensive analysis of the human proteome within a few hours.

PPARα Activation Induces Nε‐Lys‐Acetylation of Rat Liver Peroxisomal Multifunctional Enzyme Type 1

Peroxisomes are ubiquitous subcellular organelles that participate in metabolic and disease processes, with few of its proteins undergoing posttranslational modifications. As the role of lysine-acetylation has expanded into the cellular intermediary metabolism, we used a combination of differential centrifugation, organelle isolation by linear density gradient centrifugation, western blot analysis, and peptide fingerprinting and amino acid sequencing by mass spectrometry to investigate protein acetylation in control and ciprofibrate-treated rat liver peroxisomes. Organelle protein samples isolated by density gradient centrifugation from PPARα-agonist treated rat liver screened with an anti-N(ε)-acetyl lysine antibody revealed a single protein band of 75 kDa. Immunoprecipitation with this antibody resulted in the precipitation of a protein from the protein pool of ciprofibrate-induced peroxisomes, but not from the protein pool of non-induced peroxisomes. Peptide mass fingerprinting analysis identified the protein as the peroxisomal multifunctional enzyme type 1. In addition, mass spectrometry-based amino acid sequencing resulted in the identification of unique peptides containing 4 acetylated-Lys residues (K¹⁵⁵, K¹⁷³, K¹⁹⁰, and K⁵⁸³). This is the first report that demonstrates posttranslational acetylation of a peroxisomal enzyme in PPARα-dependent proliferation of peroxisomes in rat liver.

High-throughput Database Search and Large-scale Negative Polarity Liquid Chromatography–Tandem Mass Spectrometry with Ultraviolet Photodissociation for Complex Proteomic Samples

The use of ultraviolet photodissociation (UVPD) for the activation and dissociation of peptide anions is evaluated for broader coverage of the proteome. To facilitate interpretation and assignment of the resulting UVPD mass spectra of peptide anions, the MassMatrix database search algorithm was modified to allow automated analysis of negative polarity MS/MS spectra. The new UVPD algorithms were developed based on the MassMatrix database search engine by adding specific fragmentation pathways for UVPD. The new UVPD fragmentation pathways in MassMatrix were rigorously and statistically optimized using two large data sets with high mass accuracy and high mass resolution for both MS(1) and MS(2) data acquired on an Orbitrap mass spectrometer for complex Halobacterium and HeLa proteome samples. Negative mode UVPD led to the identification of 3663 and 2350 peptides for the Halo and HeLa tryptic digests, respectively, corresponding to 655 and 645 peptides that were unique when compared with electron transfer dissociation (ETD), higher energy collision-induced dissociation, and collision-induced dissociation results for the same digests analyzed in the positive mode. In sum, 805 and 619 proteins were identified via UVPD for the Halobacterium and HeLa samples, respectively, with 49 and 50 unique proteins identified in contrast to the more conventional MS/MS methods. The algorithm also features automated charge determination for low mass accuracy data, precursor filtering (including intact charge-reduced peaks), and the ability to combine both positive and negative MS/MS spectra into a single search, and it is freely open to the public. The accuracy and specificity of the MassMatrix UVPD search algorithm was also assessed for low resolution, low mass accuracy data on a linear ion trap. Analysis of a known mixture of three mitogen-activated kinases yielded similar sequence coverage percentages for UVPD of peptide anions versus conventional collision-induced dissociation of peptide cations, and when these methods were combined into a single search, an increase of up to 13% sequence coverage was observed for the kinases. The ability to sequence peptide anions and cations in alternating scans in the same chromatographic run was also demonstrated. Because ETD has a significant bias toward identifying highly basic peptides, negative UVPD was used to improve the identification of the more acidic peptides in conjunction with positive ETD for the more basic species. In this case, tryptic peptides from the cytosolic section of HeLa cells were analyzed by polarity switching nanoLC-MS/MS utilizing ETD for cation sequencing and UVPD for anion sequencing. Relative to searching using ETD alone, positive/negative polarity switching significantly improved sequence coverages across identified proteins, resulting in a 33% increase in unique peptide identifications and more than twice the number of peptide spectral matches.

Proteomic Analysis of Sarcoplasmic Peptides of Two Related Fish Species for Food Authentication

Detection of species-specific sarcoplasmic peptides can be used as proteomic markers for fish food authentication and identification of species of origin in processed products. In the present study, proteomics technology was employed for differential characterization of sarcoplasmic peptides of two closely related fish species, Sperata seenghala and Sperata aor. Species-specific peptides were searched in white muscle extracts of the two species for identification of unique peptides that might aid in differentiation of the species, under two-dimensional gel electrophoresis platform. A total of 19 proteins were identified by combined matrix-assisted laser desorption ionization time-of-flight mass spectrometry and liquid chromatography-tandem mass spectrometry, of which nine and two proteins were found to be unique to S. seenghala and S. aor, respectively. One of the proteins, triosephosphate isomerase (TPI) was found to have three isoforms, out of which two were specific to S. aor, and one was specific to S. seenghala. All the three isoforms of TPI were present in the mixed samples of raw protein extracts of S. seenghala and S. aor, an observation that can be exploited to differentiate between the species and detection of deceptive practices of fraudulent substitution of commercially valuable fish species with inferior ones and differential characterization between closely related fish species.

Synthetic Molecular Evolution of Pore-Forming Peptides by Iterative Combinatorial Library Screening

We previously reported the de novo design of a combinatorial peptide library that was subjected to high-throughput screening to identify membrane-permeabilizing antimicrobial peptides that have β-sheet-like secondary structure. Those peptides do not form discrete pores in membranes but instead partition into membrane interfaces and cause transient permeabilization by membrane disruption, but only when present at high concentration. In this work, we used a consensus sequence from that initial screen as a template to design an iterative, second generation library. In the 24-26-residue, 16,200-member second generation library we varied six residues. Two diad repeat motifs of alternating polar and nonpolar amino acids were preserved to maintain a propensity for non-helical secondary structure. We used a new high-throughput assay to identify members that self-assemble into equilibrium pores in synthetic lipid bilayers. This screen was done at a very stringent peptide to lipid ratio of 1:1000 where most known membrane-permeabilizing peptides, including the template peptide, are not active. In a screen of 10,000 library members we identified 16 (~0.2%) that are equilibrium pore-formers at this high stringency. These rare and highly active peptides, which share a common sequence motif, are as potent as the most active pore-forming peptides known. Furthermore, they are not α-helical, which makes them unusual, as most of the highly potent pore-forming peptides are amphipathic α-helices. Here we demonstrate that this synthetic molecular evolution-based approach, taken together with the new high-throughput tools we have developed, enables the identification, refinement, and optimization of unique membrane active peptides.

Size-Selective Fractionation and Visual Mapping of Allergen Protein Chemistry in Arachis hypogaea

Peanuts (Arachis hypogaea) in addition to milk, eggs, fish, crustaceans, wheat, tree nuts, and soybean are commonly referred to as the "big eight" foods that contribute to the majority of food allergies worldwide. Despite the severity of allergic reactions and growing prevalence in children and adults, there is no cure for peanut allergy, leaving avoidance as the primary mode of treatment. To improve analytical methods for peanut allergen detection, researchers must overcome obstacles involved in handling complex food matrices while attempting to decipher the chemistry that underlies allergen protein interactions. To address such challenges, we conducted a global proteome characterization of raw peanuts using a sophisticated GELFrEE-PAGE-LC-MS/MS platform consisting of gel-based protein fractionation followed by mass spectrometric identification. The in-solution mass-selective protein fractionation: (1) enhances the number of unique peptide identifications, (2) provides a visual map of protein isoforms, and (3) aids in the identification of disulfide-linked protein complexes. GELFrEE-PAGE-LC-MS/MS not only overcomes many of the challenges involved in the study of plant proteomics, but enriches the understanding of peanut protein chemistry, which is typically unattainable in a traditional bottom-up proteomic analysis. A global understanding of protein chemistry in Arachis hypogaea ultimately will aid the development of improved methods for allergen detection in food.

Systematic Comparison of Ultraviolet Photodissociation and Electron Transfer Dissociation for Peptide Anion Characterization

Ultraviolet photodissociation at 193 nm (UVPD) and negative electron transfer dissociation (NETD) were compared to establish their utility for characterizing acidic proteomes with respect to sequence coverage distributions (a measure of product ion signals across the peptide backbone), sequence coverage percentages, backbone cleavage preferences, and fragmentation differences relative to precursor charge state. UVPD yielded significantly more diagnostic information compared with NETD for lower charge states (n ≤ 2), but both methods were comparable for higher charged species. While UVPD often generated a more heterogeneous array of sequence-specific products (b-, y-, c-, z-, Y-, d-, and w-type ions in addition to a- and x- type ions), NETD usually created simpler sets of a/x-type ions. LC-MS/UVPD and LC-MS/NETD analysis of protein digests utilizing high pH mobile phases coupled with automated database searching via modified versions of the MassMatrix algorithm was undertaken. UVPD generally outperformed NETD in stand-alone searches due to its ability to efficiently sequence both lower and higher charge states with rapid activation times. However, when combined with traditional positive mode CID, both methods yielded complementary information with significantly increased sequence coverage percentages and unique peptide identifications over that of just CID alone.

Enhanced Peptide Identification by Electron Transfer Dissociation Using an Improved Mascot Percolator

Peptide identification using tandem mass spectrometry is a core technology in proteomics. Latest generations of mass spectrometry instruments enable the use of electron transfer dissociation (ETD) to complement collision induced dissociation (CID) for peptide fragmentation. However, a critical limitation to the use of ETD has been optimal database search software. Percolator is a post-search algorithm, which uses semi-supervised machine learning to improve the rate of peptide spectrum identifications (PSMs) together with providing reliable significance measures. We have previously interfaced the Mascot search engine with Percolator and demonstrated sensitivity and specificity benefits with CID data. Here, we report recent developments in the Mascot Percolator V2.0 software including an improved feature calculator and support for a wider range of ion series. The updated software is applied to the analysis of several CID and ETD fragmented peptide data sets. This version of Mascot Percolator increases the number of CID PSMs by up to 80% and ETD PSMs by up to 60% at a 0.01 q-value (1% false discovery rate) threshold over a standard Mascot search, notably recovering PSMs from high charge state precursor ions. The greatly increased number of PSMs and peptide coverage afforded by Mascot Percolator has enabled a fuller assessment of CID/ETD complementarity to be performed. Using a data set of CID and ETcaD spectral pairs, we find that at a 1% false discovery rate, the overlap in peptide identifications by CID and ETD is 83%, which is significantly higher than that obtained using either stand-alone Mascot (69%) or OMSSA (39%). We conclude that Mascot Percolator is a highly sensitive and accurate post-search algorithm for peptide identification and allows direct comparison of peptide identifications using multiple alternative fragmentation techniques.

Evaluation of Front-End Higher Energy Collision-Induced Dissociation on a Benchtop Dual-Pressure Linear Ion Trap Mass Spectrometer for Shotgun Proteomics

We report the implementation of front-end higher energy collision-induced dissociation (fHCD) on a benchtop dual-pressure linear ion trap. Software and hardware modifications were employed, described in detail vide-infra, to allow isolated ions to undergo collisions with ambient gas molecules in an intermediate multipole (q00) of the instrument. Results comparing the performance of fHCD and resonance excitation collision-induced dissociation (RE-CID) in terms of injection time, total number of scans, efficiency, mass measurement accuracy (MMA), unique peptide identifications, and spectral quality of labile modified peptides are presented. fHCD is approximately 23% as efficient as RE-CID, and depending on the search algorithm, it identifies 6.6% more or 15% less peptides (q < 0.01) from a soluble whole-cell lysate ( Caenorhabditis elegans ) than RE-CID using Mascot or Sequest search algorithms, respectively. fHCD offers a clear advantage for the analysis of phosphorylated and glycosylated (O-GlcNAc) peptides as the average cross-correlation score (XCorr) for spectra using fHCD was statistically greater (p < 0.05) than for spectra collected using RE-CID.

Reliable Detection of Milk Allergens in Food Using a High-Resolution, Stand-Alone Mass Spectrometer

Reliable methods are needed for detection of allergenic milk proteins in complex food matrixes. The feasibility of an LC/high-resolution MS method for the analysis of milk proteins in a thermally processed model food (incurred cookies) and in white wine spiked, respectively, with milk powder and caseinate is described. Detection of milk proteins was based on the identification of unique peptides in the tryptic digests of cookie/wine extracts using an RP-HPLC separation coupled to an Exactive nonhybrid mass spectrometer using Orbitrap technology. The extremely high mass accuracy and resolution provided by the Orbitrap analyzer allowed a fast preliminary identification of four previously proposed peptide markers of caseins using only accurate values of the m/z of their ions. No interference was observed, despite the complexity of the analyzed matrixes. Moreover, the availability of a high- energy, collisionally activated dissociation cell integrated in the mass spectrometer enabled acquisition of peptide MS/MS-like spectra through post-source fragmentation. Confirmation of peptide marker identity could then be achieved by a comparison between experimental and predicted product ions. The described method shows the great potential of Orbitrap MS as a reliable technique in the field of protein allergen detection once the peptide markers are identified.

Electrophoretic mapping of highly homologous keratins: A novel marker peptide approach

Identification of the intermediate filament proteins (IFPs) in the wool proteome has formerly been hampered by limited sequence information, the high degree of IFP homology and their close proximity on 2-DE maps. This has been partially rectified by the recent acquisition of four new Type I and two Type II wool IFP sequences. Among closely migrating proteins, such as IFP clusters in a 2-DE map, proteins with higher sequence coverage will be assigned higher scores, but the identification of unique peptides in such tight clusters may distinguish these closely migrating proteins. Two approaches were adopted for the study of wool IFPs. In the first, searches were conducted for peptides known to be unique to each member of the family in each spot. In the second, MALDI imaging was employed to examine peptides bound to a PVDF membrane from a poorly resolved part of the Type I IFP region of the 2-DE map. As a result, a distinct picture has emerged of the distribution of the six Type I and four Type II IFPs across the 2-DE wool protein map.

Identification and Characterization of Unique Proline-rich Peptides Binding to the Mitochondrial Fission Protein hFis1

Mammalian mitochondrial fission requires at least two proteins, hFis1 and the dynamin-like GTPase DLP1/Drp1. The mitochondrial protein hFis1 is anchored at the outer membrane by a C-terminal transmembrane domain. The cytosolic domain of hFis1 contains six alpha helices [alpha1-alpha6] out of which [alpha2-alpha5] form tetratricopeptide repeat (TPR)-like motifs. DLP1 and possibly other proteins are thought to interact with the hFis1 TPR region during the fission process. It has also been suggested that the alpha1-helix regulates protein-protein interactions at the TPR. We performed random peptide phage display screening using the hFis1[alpha2-alpha6] as the target and identified ten different peptide sequences. Phage ELISA using mutant hFis1 indicates that the peptide binding requires the alpha2 and alpha3 helices and the intact TPR structure. Competition experiments and surface plasmon resonance analyses confirmed that a subset of free peptides enriched with proline residues directly bind to the target. Two of these peptides bind to the alpha1-containing intact cytosolic domain of hFis1 with decreased affinity. Peptide microinjection into cells abolished the mitochondrial swelling induced by overexpression of alpha1-deleted hFis1, and significantly decreased cytochrome c release from mitochondria upon apoptotic induction. Our data demonstrate that hFis1 can bind to multiple amino acid sequences selectively, and that the TPR constitutes the main binding region of hFis1, providing a first insight into the hFis1 TPR as a potential therapeutic target.

The effect of interfering ions on search algorithm performance for electron‐transfer dissociation data

Collision-activated dissociation and electron-transfer dissociation (ETD) each produce spectra containing unique features. Though several database search algorithms (e.g. SEQUEST, MASCOT, and Open Mass Spectrometry Search Algorithm) have been modified to search ETD data, this consists chiefly of the ability to search for c- and z(*)-ions; additional ETD-specific features are often unaccounted for and may hinder identification. Removal of these features via spectral processing increased total search sensitivity by approximately 20% for both human and yeast data sets; unique peptide identifications increased by approximately 17% for the yeast data sets and approximately 16% for the human data set.