A framework for quality control in quantitative proteomics

A thorough evaluation of the quality, reproducibility, and variability of bottom-up proteomics data is necessary at every stage of a workflow from planning to analysis. We share real-world case studies applying adaptable quality control (QC) measures to assess sample preparation, system function, and quantitative analysis. System suitability samples are repeatedly measured longitudinally with targeted methods, and we share examples where they are used on three instrument platforms to identify severe system failures and track function over months to years. Internal QCs incorporated at protein and peptide-level allow our team to assess sample preparation issues and to differentiate system failures from sample-specific issues. External QC samples prepared alongside our experimental samples are used to verify the consistency and quantitative potential of our results during batch correction and normalization before assessing biological phenotypes. We combine these controls with rapid analysis using Skyline, longitudinal QC metrics using AutoQC, and server-based data deposition using PanoramaWeb. We propose that this integrated approach to QC be used as a starting point for groups to facilitate rapid quality control assessment to ensure that valuable instrument time is used to collect the best quality data possible.

Filtered Cerebrospinal Fluid From Patients With Amyotrophic Lateral Sclerosis Displays an Altered Proteome and Affects Motor Phenotype in a Mouse Model

INTRODUCTION

Cerebrospinal fluid (CSF) has been implicated in amyotrophic lateral sclerosis (ALS) due to its ability to spread inflammatory proteins throughout the nervous system. We hypothesized that filtration of the CSF could remove pathogenic proteins and prevent them from altering motor phenotypes in a mouse model.

METHODS

We filtered the CSF from 11 ALS patients via 100 kilodaltons (kD) molecular weight cut-off filters. We used mass spectrometry-based discovery proteomics workflows to compare protein abundances before and after filtration. To test the effects of CSF filtration on motor function, we injected groups of mice with saline, filtered ALS-CSF, or unfiltered ALS-CSF (n=12 per group) and assessed motor function via pole descent and open field tests.

RESULTS

We identified proteins implicated in ALS pathogenesis and showed that these were removed in significant amounts in our workflow. Key filtered proteins included complement proteins, chitinases, serine protease inhibitors, and neuro-inflammatory proteins such as amyloid precursor protein, chromogranin A, and glial fibrillary acidic protein. Compared to the filtered ALS-CSF mice, unfiltered ALS-CSF mice took longer to descend a pole (10 days post-injection, 11.14 seconds vs 14.25 seconds, p = 0.02) and explored less on an open field (one day post-injection, 21.81 m vs 16.83 m, p = 0.0004).

CONCLUSIONS

We demonstrated the ability to filter proteins from the CSF of ALS patients and identified potentially pathologic proteins that were reduced in quantity. Additionally, we demonstrated the ability of unfiltered ALS-CSF to induce motor deficits in mice on the pole descent and open field tests and showed that filtration could prevent this deficit. Given the lack of effective treatments for ALS, this could be a novel solution for patients suffering from this deadly and irreversible condition.

The Cyanotoxin 2,4-DAB Reduces Viability and Causes Behavioral and Molecular Dysfunctions Associated with Neurodegeneration in Larval Zebrafish

Exposure to cyanotoxins has been linked to neurodegenerative diseases, including amyotrophic lateral sclerosis, Alzheimer's, and Parkinson's disease. While the cyanotoxin β-methylamino-L-alanine (BMAA) has received much attention, cyanobacteria produce many cyanotoxic compounds, several of which have been detected in nature alongside BMAA, including 2,4-diaminobutyric acid (2,4-DAB) and N-(2-aminoethyl)glycine (AEG). Thus, the question of whether 2,4-DAB and AEG also cause neurotoxic effects in vivo is of great interest, as is the question of whether they interact to enhance toxicity. Here, we evaluate the toxic and neurotoxic effects of these cyanotoxins alone or in combination by measuring zebrafish larval viability and behavior after exposure. 2,4-DAB was the most potent cyanotoxin as it decreased larval viability by approximately 50% at 6 days post fertilization, while BMAA and AEG decreased viability by just 16% and 8%, respectively. Although we only observed minor neurotoxic effects on spontaneous locomotion, BMAA and AEG enhanced acoustic startle sensitivity, and they interacted in an additive manner to exert their effects. 2,4-DAB; however, only modulated startle kinematics, an indication of motor dysfunction. To investigate the mechanisms of 2,4-DAB's effects, we analyzed the protein profile of larval zebrafish exposed to 500 µM 2,4-DAB at two time points and identified molecular signatures consistent with neurodegeneration, including disruption of metabolic pathways and downregulation of the ALS-associated genes SOD1 and UBQLN4. Together, our data demonstrate that BMAA and its isomers AEG and 2,4-DAB cause neurotoxic effects in vivo, with 2,4-DAB as the most potent of the three in the zebrafish model.

BMAA and MCLR interact to modulate behavior and exacerbate molecular changes related to neurodegeneration in larval zebrafish

Exposure to toxins produced by cyanobacteria (i.e., cyanotoxins) is an emerging health concern due to their increasing prevalence and previous associations with neurodegenerative diseases including amyotrophic lateral sclerosis (ALS). The objective of this study was to evaluate the neurotoxic effects of a mixture of two co-occurring cyanotoxins, β-methylamino-L-alanine (BMAA) and microcystin leucine and arginine (MCLR), using the larval zebrafish model. We combined high-throughput behavior-based toxicity assays with discovery proteomic techniques to identify behavioral and molecular changes following 6 days of exposure. While neither toxin caused mortality, morphological defects, or altered general locomotor behavior in zebrafish larvae, both toxins increased acoustic startle sensitivity in a dose-dependent manner by at least 40% (p < 0.0001). Furthermore, startle sensitivity was enhanced by an additional 40% in larvae exposed to the BMAA/MCLR mixture relative to those exposed to the individual toxins. Supporting these behavioral results, our proteomic analysis revealed a 4-fold increase in the number of differentially expressed proteins (DEPs) in the mixture-exposed group. Additionally, prediction analysis reveals activation and/or inhibition of 8 enriched canonical pathways (enrichment p-value < 0.01; z-score ≥|2|), including ILK, Rho Family GTPase, RhoGDI, and calcium signaling pathways, which have been implicated in neurodegeneration. We also found that expression of TDP-43, of which cytoplasmic aggregates are a hallmark of ALS pathology, was significantly upregulated by 5.7-fold following BMAA/MCLR mixture exposure. Together, our results emphasize the importance of including mixtures of cyanotoxins when investigating the link between environmental cyanotoxins and neurodegeneration as we reveal that BMAA and MCLR interact in vivo to enhance neurotoxicity.

Peptide variability and signatures associated with disease progression in CSF collected longitudinally from ALS patients

We employ shotgun proteomics and data-independent acquisition (DIA) mass spectrometry to analyze cerebrospinal fluid longitudinally collected from 14 amyotrophic lateral sclerosis (ALS) patients (8 males and 6 females). We perform three main analyses of these data: (1) examine the intra- and inter-patient protein variability in CSF; (2) explore the association of inflammation with rate of disease progression; and (3) develop a mixed-effects model to best explain the decrease in ALS-Functional Rating Scale (ALS-FRS) score. Overall, the CSF protein abundances are tightly regulated with the intra-individual variability contributing just 4% to the overall variance. In four patients, a moderately significant correlation (p < 0.1) was observed between inflammation and rate of disease progression. Using a least absolute shrinkage and selection operator (LASSO) variable selection, we selected 55 viable peptides for mathematical modeling via a linear mixed-effects regression. We then employed forward selection to generate a final model by minimizing Akaike's information criterion (AIC). The final model utilized changes in abundance from 28 peptides as fixed effects to model progression of the disease in these patients. These peptides were from proteins involved in stress response and innate immunity. Graphical abstract.

Metabolite Profiling Reveals Predictive Biomarkers and the Absence of β-Methyl Amino-l-alanine in Plasma from Individuals Diagnosed with Amyotrophic Lateral Sclerosis

By employing chip-based capillary zone electrophoresis coupled to high-resolution mass spectrometry, we profiled the plasma metabolome of 134 patients diagnosed with sporadic amyotrophic lateral sclerosis (ALS) (81 males and 53 females) and 118 individuals deemed healthy (49 males and 69 females). The most significant markers (p < 0.01) were creatine, which was 49% elevated, and creatinine and methylhistidine, which were decreased by 20 and 24%, respectively, in ALS patients. The ratio of creatine versus creatinine increased 370 and 200% for male and female ALS patients, respectively. In addition, male ALS patients on an average had 5-13% lower amounts of seven essential amino acids, whereas females did not significantly differ from healthy controls. We developed two models using the metabolite abundances: (1) a classification model for the separation of ALS and healthy samples and (2) a classification model for the prediction of disease progression based on the ALS functional rating score. Utilizing a Monte Carlo cross-validation approach, a linear discriminant analysis model achieved a mean area under the receiver operating characteristic curve (AUC) of 0.85 (0.06) with a mean sensitivity of 80% (9%) and specificity of 78% (10%) for the separation of ALS and controls, respectively. A support vector machine classifier predicted progression categories with an AUC of 0.90 (0.06) with a mean sensitivity of 73% (10%) and a specificity of 86% (5%). Lastly, using a previously reported assay with a stable isotope-labeled (¹³C₃¹⁵N₂) spike-in standard, we were unable to detect the exogenous neurotoxic metabolite, β-methylamino-l-alanine, in the free or protein-bound fraction of any of the 252 plasma samples.

Mixture designs to investigate adverse effects upon co-exposure to environmental cyanotoxins

The goal of this study was to implement powerful mixture design techniques, commonly used in process optimization, to investigate enhanced adverse effects upon co-exposure to environmental cyanotoxins. Exposure to cyanobacteria, which are found ubiquitously in environmental water reservoirs, have been linked to several neurodegenerative diseases. Despite the known co-occurrence of various cyanotoxins, the majority of studies investigating this link have focused on the investigation of a single cyanotoxin, a noncanonical amino acid called β-methylamino-L-alanine (BMAA), which poorly recapitulates an actual environmental exposure. Interactions amongst cyanotoxic compounds is an area of great concern and remains poorly understood. To this end, we describe the use of a simplex axial mixture design to screen for interactive adverse effects of cyanotoxic mixtures. Using a combination of basic toxicity assays coupled with contemporary proteomic techniques, our results show the existence of a significant (p ≤ 0.01) interaction between BMAA and its isomers aminoethyl glycine (AEG) and 2,4-diaminobutyric acid (2,4DAB). Cyanotoxic mixtures significantly decreased cell viability by an average of 19% and increased caspases 3/7 activities by an average of 110% when compared to individual cyanotoxins (p ≤ 0.05). Cyanotoxic mixtures perturbed various biological pathways associated with neurodegeneration, including inhibition of protective autophagy and activation of mitochondrial dysfunction (z-score >|2|). Additionally, exposure to mixtures perturbed important upstream regulators involved in cellular dysfunction, morbidity, and development. Taken together, our results highlight: (1) the need to study combinations of cyanotoxins when investigating the link between cyanobacteria and neurodegenerative pathologies and (2) the application of design of experiment (DoE) as an efficient methodology to study mixtures of relevant environmental toxins.

Machine Learning Reveals Protein Signatures in CSF and Plasma Fluids of Clinical Value for ALS

We use shotgun proteomics to identify biomarkers of diagnostic and prognostic value in individuals diagnosed with amyotrophic lateral sclerosis. Matched cerebrospinal and plasma fluids were subjected to abundant protein depletion and analyzed by nano-flow liquid chromatography high resolution tandem mass spectrometry. Label free quantitation was used to identify differential proteins between individuals with ALS (n = 33) and healthy controls (n = 30) in both fluids. In CSF, 118 (p-value < 0.05) and 27 proteins (q-value < 0.05) were identified as significantly altered between ALS and controls. In plasma, 20 (p-value < 0.05) and 0 (q-value < 0.05) proteins were identified as significantly altered between ALS and controls. Proteins involved in complement activation, acute phase response and retinoid signaling pathways were significantly enriched in the CSF from ALS patients. Subsequently various machine learning methods were evaluated for disease classification using a repeated Monte Carlo cross-validation approach. A linear discriminant analysis model achieved a median area under the receiver operating characteristic curve of 0.94 with an interquartile range of 0.88–1.0. Three proteins composed a prognostic model (p = 5e-4) that explained 49% of the variation in the ALS-FRS scores. Finally we investigated the specificity of two promising proteins from our discovery data set, chitinase-3 like 1 protein and alpha-1-antichymotrypsin, using targeted proteomics in a separate set of CSF samples derived from individuals diagnosed with ALS (n = 11) and other neurological diseases (n = 15). These results demonstrate the potential of a panel of targeted proteins for objective measurements of clinical value in ALS.

A novel integrated strategy for the detection and quantification of the neurotoxin β-N-methylamino-L-alanine in environmental samples

We describe a set of new tools for the detection and quantification of β-N-methylamino-L-alanine (BMAA) which includes a novel stable isotope-labeled BMAA standard (13C3,15N2) and a chip-based capillary electrophoresis mass spectrometry platform for separation and detection. Baseline resolution of BMAA from its potentially confounding structural isomers N-2-aminoethylglycine (AEG) and 2,4-diaminobutyric acid (2,4-DAB) is achieved using the chip-based CE-MS system in less than 1 min. Detection and linearity of response are demonstrated across > 3.5 orders of dynamic range using parallel reaction monitoring (PRM). The lower limit of detection and quantification were calculated for BMAA detection at 40 nM (4.8 ng/mL) and 400 nM (48 ng/mL), respectively. Finally, the strategy was applied to detect BMAA in seafood samples purchased at a local market in Raleigh, NC where their harvest location was known. BMAA was detected in a sea scallop sample. Because the BMAA/stable isotope-labeled 13C3,15N2-BMAA (SIL-BMAA) ratio in the scallop sample was below the limit of quantification, a semiquantitative analysis of BMAA content was carried out, and BMAA content was estimated to be approximately 820 ng BMAA/1 g of wet scallop tissue. Identification was verified by high mass measurement accuracy of precursor (< 5 ppm) and product ions (< 10 ppm), comigration with SIL-BMAA spike-in standard, and conservation of ion abundance ratios for product ions between BMAA and SIL-BMAA. Interestingly, BMAA was not identified in the free protein fraction but only detected after protein hydrolysis which suggests that BMAA is tightly bound by and/or incorporated into proteins. Graphical abstract Utilization of novel 13C3,15N2-BMAA and chip-based CE-MS/MS for detection and quantification of BMAA in environmental samples.

Exposure to BMAA mirrors molecular processes linked to neurodegenerative disease

The goal of this study is to investigate the molecular pathways perturbed by in vitro exposure of beta-methylamino-L-alanine (BMAA) to NSC-34 cells via contemporary proteomics. Our analysis of differentially regulated proteins reveals significant enrichment (p < 0.01) of pathways related to ER stress, protein ubiquitination, the unfolded protein response, and mitochondrial dysfunction. Upstream regulator analysis indicates that exposure to BMAA induces activation of transcription factors (X-box binding protein 1; nuclear factor 2 erythroid like 2; promyelocytic leukemia) involved in regulation of the UPR, oxidative stress, and cellular senescence. Furthermore, the authors examine the hypothesis that BMAA causes protein damage via misincorporation in place of L-Serine. The authors are unable to detect misincorporation of BMAA into protein via analysis of cellular protein, secreted protein, targeted detection of BMAA after protein hydrolysis, or through the use of in vitro protein translation kits.

Evaluation of a Bead-Free Coimmunoprecipitation Technique for Identification of Virus-Host Protein Interactions Using High-Resolution Mass Spectrometry

Protein interactions between virus and host are essential for viral propagation and movement, as viruses lack most of the proteins required to thrive on their own. Precision methods aimed at disrupting virus-host interactions represent new approaches to disease management but require in-depth knowledge of the identity and binding specificity of host proteins within these interaction networks. Protein coimmunoprecipitation (co-IP) coupled with mass spectrometry (MS) provides a high-throughput way to characterize virus-host interactomes in a single experiment. Common co-IP methods use antibodies immobilized on agarose or magnetic beads to isolate virus-host complexes in solutions of host tissue homogenate. Although these workflows are well established, they can be fairly laborious and expensive. Therefore, we evaluated the feasibility of using antibody-coated microtiter plates coupled with MS analysis as an easy, less expensive way to identify host proteins that interact with Potato leafroll virus (PLRV), an insect-borne RNA virus that infects potatoes. With the use of the bead-free platform, we were able to detect 36 plant and 1 nonstructural viral protein significantly coimmunoprecipitating with PLRV. Two of these proteins, a 14-3-3 signal transduction protein and malate dehydrogenase 2 (mMDH2), were detected as having a weakened or lost association with a structural mutant of the virus, demonstrating that the bead-free method is sensitive enough to detect quantitative differences that can be used to pin-point domains of interaction. Collectively, our analysis shows that the bead-free platform is a low-cost alternative that can be used by core facilities and other investigators to identify plant and viral proteins interacting with virions and/or the viral structural proteins.

Acetylation-induced TDP-43 pathology is suppressed by an HSF1-dependent chaperone program

TDP-43 pathology marks a spectrum of multisystem proteinopathies including amyotrophic lateral sclerosis, frontotemporal lobar degeneration, and sporadic inclusion body myositis. Surprisingly, it has been challenging to recapitulate this pathology, highlighting an incomplete understanding of TDP-43 regulatory mechanisms. Here we provide evidence supporting TDP-43 acetylation as a trigger for disease pathology. Using cultured cells and mouse skeletal muscle, we show that TDP-43 acetylation-mimics promote TDP-43 phosphorylation and ubiquitination, perturb mitochondria, and initiate degenerative inflammatory responses that resemble sporadic inclusion body myositis pathology. Analysis of functionally linked amyotrophic lateral sclerosis proteins revealed recruitment of p62, ubiquilin-2, and optineurin to TDP-43 aggregates. We demonstrate that TDP-43 acetylation-mimic pathology is potently suppressed by an HSF1-dependent mechanism that disaggregates TDP-43. Our study illustrates bidirectional TDP-43 processing in which TDP-43 aggregation is targeted by a coordinated chaperone response. Thus, activation or restoration of refolding mechanisms may alleviate TDP-43 aggregation in tissues that are uniquely susceptible to TDP-43 proteinopathies.

TDP-43 aggregation is linked to various diseases including amyotrophic lateral sclerosis. Here the authors show that acetylation of the protein triggers TDP-43 pathology in cultured cells and mouse skeletal muscle, which can be cleared through an HSF1-dependent chaperone mechanism that disaggregates the protein.

MSstatsQC: Longitudinal System Suitability Monitoring and Quality Control for Targeted Proteomic Experiments

Selected Reaction Monitoring (SRM) is a powerful tool for targeted detection and quantification of peptides in complex matrices. An important objective of SRM is to obtain peptide quantifications that are (1) suitable for the investigation, and (2) reproducible across laboratories and runs. The first objective is achieved by system suitability tests (SST), which verify that mass spectrometric instrumentation performs as specified. The second objective is achieved by quality control (QC), which provides in-process quality assurance of the sample profile. A common aspect of SST and QC is the longitudinal nature of the data. Although SST and QC have received a lot of attention in the proteomic community, the currently used statistical methods are limited. This manuscript improves upon the statistical methodology for SST and QC that is currently used in proteomics. It adapts the modern methods of longitudinal statistical process control, such as simultaneous and time weighted control charts and change point analysis, to SST and QC of SRM experiments, discusses their advantages, and provides practical guidelines. Evaluations on simulated data sets, and on data sets from the Clinical Proteomics Technology Assessment for Cancer (CPTAC) consortium, demonstrated that these methods substantially improve our ability of real time monitoring, early detection and prevention of chromatographic and instrumental problems. We implemented the methods in an open-source R-based software package MSstatsQC and its web-based graphical user interface. They are available for use stand-alone, or for integration with automated pipelines. Although the examples focus on targeted proteomics, the statistical methods in this manuscript apply more generally to quantitative proteomics.

Mapping differential cellular protein response of mouse alveolar epithelial cells to multi-walled carbon nanotubes as a function of atomic layer deposition coating

Carbon nanotubes (CNTs), a prototypical engineered nanomaterial, have been increasingly manufactured for a variety of novel applications over the past two decades. However, since CNTs possess fiber-like shape and cause pulmonary fibrosis in rodents, there is concern that mass production of CNTs will lead to occupational exposure and associated pulmonary diseases. The aim of this study was to use contemporary proteomics to investigate the mechanisms of cellular response in E10 mouse alveolar epithelial cells in vitro after exposure to multi-walled CNTs (MWCNTs) that were functionalized by atomic layer deposition (ALD). ALD is a method used to generate highly uniform and conformal nanoscale thin-film coatings of metals to enhance novel conductive properties of CNTs. We hypothesized that specific types of metal oxide coatings applied to the surface of MWCNTs by ALD would determine distinct proteomic profiles in mouse alveolar epithelial cells in vitro that could be used to predict oxidative stress and pulmonary inflammation. Uncoated (U)-MWCNTs were functionalized by ALD with zinc oxide (ZnO) to yield Z-MWCNTs or aluminum oxide (Al₂O₃) to yield A-MWCNTs. Significant differential protein expression was found in the following critical pathways: mTOR/eIF4/p70S6K signaling and Nrf-2 mediated oxidative stress response increased following exposure to Z-MWCNTs, interleukin-1 signaling increased following U-MWCNT exposure, and inhibition of angiogenesis by thrombospondin-1, oxidative phosphorylation, and mitochondrial dysfunction increased following A-MWCNT exposure. This study demonstrates that specific types of metal oxide thin film coatings applied by ALD produce distinct cellular and biochemical responses related to lung inflammation and fibrosis compared to uncoated MWCNT exposure in vitro.

An Automated Pipeline to Monitor System Performance in Liquid Chromatography-Tandem Mass Spectrometry Proteomic Experiments

We report the development of a completely automated pipeline to monitor system suitability in bottom-up proteomic experiments. LC-MS/MS runs are automatically imported into Skyline and multiple identification-free metrics are extracted from targeted peptides. These data are then uploaded to the Panorama Skyline document repository where metrics can be viewed in a web-based interface using powerful process control techniques, including Levey-Jennings and Pareto plots. The interface is versatile and takes user input, which allows the user significant control over the visualization of the data. The pipeline is vendor and instrument-type neutral, supports multiple acquisition techniques (e.g., MS 1 filtering, data-independent acquisition, parallel reaction monitoring, and selected reaction monitoring), can track performance of multiple instruments, and requires no manual intervention aside from initial setup. Data can be viewed from any computer with Internet access and a web browser, facilitating sharing of QC data between researchers. Herein, we describe the use of this pipeline, termed Panorama AutoQC, to evaluate LC-MS/MS performance in a range of scenarios including identification of suboptimal instrument performance, evaluation of ultrahigh pressure chromatography, and identification of the major sources of variation throughout years of peptide data collection.

Improving the analytical performance and versatility of paper spray mass spectrometry via paper microfluidics

Paper-based microfluidic techniques were explored to increase paper spray mass spectrometry's performance and versatility.

C/EBPα regulates CRL4(Cdt2)-mediated degradation of p21 in response to UVB-induced DNA damage to control the G1/S checkpoint

The bZIP transcription factor, C/EBPα is highly inducible by UVB and other DNA damaging agents in keratinocytes. C/EBPα-deficient keratinocytes fail to undergo cell cycle arrest in G1 in response to UVB-induced DNA damage and mice lacking epidermal C/EBPα are highly susceptible to UVB-induced skin cancer. The mechanism through which C/EBPα regulates the cell cycle checkpoint in response to DNA damage is unknown. Here we report untreated C/EBPα-deficient keratinocytes have normal levels of the cyclin-dependent kinase inhibitor, p21, however, UVB-treated C/EBPα-deficient keratinocytes fail to up-regulate nuclear p21 protein levels despite normal up-regulation of Cdkn1a mRNA levels. UVB-treated C/EBPα-deficient keratinocytes displayed a 4-fold decrease in nuclear p21 protein half-life due to the increased proteasomal degradation of p21 via the E3 ubiquitin ligase CRL4(Cdt2). Cdt2 is the substrate recognition subunit of CRL4(Cdt2) and Cdt2 mRNA and protein levels were up-regulated in UVB-treated C/EBPα-deficient keratinocytes. Knockdown of Cdt2 restored p21 protein levels in UVB-treated C/EBPα-deficient keratinocytes. Lastly, the failure to accumulate p21 in response to UVB in C/EBPα-deficient keratinocytes resulted in decreased p21 interactions with critical cell cycle regulatory proteins, increased CDK2 activity, and inappropriate entry into S-phase. These findings reveal C/EBPα regulates G1/S cell cycle arrest in response to DNA damage via the control of CRL4(Cdt2) mediated degradation of p21.

Data-independent-acquisition mass spectrometry for identification of targeted-peptide site-specific modifications

We present a novel strategy based on data-independent acquisition coupled to targeted data extraction for the detection and identification of site-specific modifications of targeted peptides in a completely unbiased manner. This method requires prior knowledge of the site of the modification along the peptide backbone from the protein of interest, but not the mass of the modification. The procedure, named multiplex adduct peptide profiling (MAPP), consists of three steps: 1) A fragment-ion tag is extracted from the data, consisting of the b-type and y-type ion series from the N and C-terminus, respectively, up to the amino-acid position that is believed to be modified; 2) MS1 features are matched to the fragment-ion tag in retention-time space, using the isolation window as a pre-filter to enable calculation of the mass of the modification; and 3) modified fragment ions are overlaid with the unmodified fragment ions to verify the mass calculated in step 2. We discuss the development, applications, and limitations of this new method for detection of unknown peptide modifications. We present an application of the method in profiling adducted peptides derived from abundant proteins in biological fluids with the ultimate objective of detecting biomarkers of exposure to reactive species.

Toxicoproteomic analysis of pulmonary carbon nanotube exposure using LC-MS/MS

Toxicoproteomics is a developing field that utilizes global proteomic methodologies to investigate the physiological response as a result of adverse toxicant exposure. The aim of this study was to compare the protein secretion profile in lung bronchoalveolar lavage fluid (BALF) from mice exposed to non-functionalized multi-walled carbon nanotubes (U-MWCNTs) or MWCNTs functionalized by nanoscale Al2O3 coatings (A-MWCNT) formed using atomic layer deposition (ALD). Proteins were identified using liquid chromatography tandem mass spectrometry (LC-MS/MS), and quantified using a combination of two label-free proteomic methods: spectral counting and MS1 peak area analysis. On average 465 protein groups were identified per sample and proteins were first screened using spectral counting and the Fisher's exact test to determine differentially regulated species. Significant proteins by Fisher's exact test (p<0.05) were then verified by integrating the intensity under the extracted ion chromatogram from a single unique peptide for each protein across all runs. A two sample t-test based on integrated peak intensities discovered differences in 27 proteins for control versus U-MWCNT, 13 proteins for control versus A-MWCNT, and 2 proteins for U-MWCNT versus A-MWCNT. Finally, an in-vitro binding experiment was performed yielding 4 common proteins statistically different (p<0.05) for both the in-vitro and in-vivo study. Several of the proteins found to be significantly different between exposed and control groups are known to play a key role in inflammatory and immune response. A comparison between the in-vitro and in-vivo CNT exposure emphasized a true biological response to CNT exposure.

Implementation of statistical process control for proteomic experiments via LC MS/MS

Statistical process control (SPC) is a robust set of tools that aids in the visualization, detection, and identification of assignable causes of variation in any process that creates products, services, or information. A tool has been developed termed Statistical Process Control in Proteomics (SProCoP) which implements aspects of SPC (e.g., control charts and Pareto analysis) into the Skyline proteomics software. It monitors five quality control metrics in a shotgun or targeted proteomic workflow. None of these metrics require peptide identification. The source code, written in the R statistical language, runs directly from the Skyline interface, which supports the use of raw data files from several of the mass spectrometry vendors. It provides real time evaluation of the chromatographic performance (e.g., retention time reproducibility, peak asymmetry, and resolution), and mass spectrometric performance (targeted peptide ion intensity and mass measurement accuracy for high resolving power instruments) via control charts. Thresholds are experiment- and instrument-specific and are determined empirically from user-defined quality control standards that enable the separation of random noise and systematic error. Finally, Pareto analysis provides a summary of performance metrics and guides the user to metrics with high variance. The utility of these charts to evaluate proteomic experiments is illustrated in two case studies.

Evidence of the biochemical basis of host virulence in the greenbug aphid, Schizaphis graminum (Homoptera: Aphididae)

Biotypes of aphids and many other insect pests are defined based on the phenotypic response of host plants to the insect pest without considering their intrinsic characteristics and genotypes. Plant breeders have spent considerable effort developing aphid-resistant, small-grain varieties to limit insecticide control of the greenbug, Schizaphis graminum. However, new S. graminum biotypes frequently emerge that break resistance. Mechanisms of virulence on the aphid side of the plant-insect interaction are not well understood. S. graminum biotype H is highly virulent on most small grain varieties. This characteristic makes biotype H ideal for comparative proteomics to investigate the basis of biotype virulence in aphids. In this study, we used comparative proteomics to identify protein expression differences associated with virulence. Aphid proteins involved in the tricarboxylic acid cycle, immune system, cell division, and antiapoptosis pathways were found to be up-regulated in biotype H relative to other biotypes. Proteins from the bacterial endosymbiont of aphids were also differentially expressed in biotype H. Guided by the proteome results, we tested whether biotype H had a fitness advantage compared with other S. graminum biotypes and found that biotype H had a higher reproductive fitness as compared with two other biotypes on a range of different wheat germplasms. Finally, we tested whether aphid genetics can be used to further dissect the genetic mechanisms of biotype virulence in aphids. The genetic data showed that sexual reproduction is a source of biotypic variation observed in S. graminum.

Genomic and proteomic analysis of Schizaphis graminum reveals cyclophilin proteins are involved in the transmission of cereal yellow dwarf virus

Yellow dwarf viruses cause the most economically important virus diseases of cereal crops worldwide and are transmitted by aphid vectors. The identification of aphid genes and proteins mediating virus transmission is critical to develop agriculturally sustainable virus management practices and to understand viral strategies for circulative movement in all insect vectors. Two cyclophilin B proteins, S28 and S29, were identified previously in populations of Schizaphisgraminum that differed in their ability to transmit the RPV strain of Cereal yellow dwarf virus (CYDV-RPV). The presence of S29 was correlated with F2 genotypes that were efficient virus transmitters. The present study revealed the two proteins were isoforms, and a single amino acid change distinguished S28 and S29. The distribution of the two alleles was determined in 12 F2 genotypes segregating for CYDV-RPV transmission capacity and in 11 genetically independent, field-collected S. graminum biotypes. Transmission efficiency for CYDV-RPV was determined in all genotypes and biotypes. The S29 isoform was present in all genotypes or biotypes that efficiently transmit CYDV-RPV and more specifically in genotypes that efficiently transport virus across the hindgut. We confirmed a direct interaction between CYDV-RPV and both S28 and S29 using purified virus and bacterially expressed, his-tagged S28 and S29 proteins. Importantly, S29 failed to interact with a closely related virus that is transported across the aphid midgut. We tested for in vivo interactions using an aphid-virus co-immunoprecipitation strategy coupled with a bottom-up LC-MS/MS analysis using a Q Exactive mass spectrometer. This analysis enabled us to identify a third cyclophilin protein, cyclophilin A, interacting directly or in complex with purified CYDV-RPV. Taken together, these data provide evidence that both cyclophilin A and B interact with CYDV-RPV, and these interactions may be important but not sufficient to mediate virus transport from the hindgut lumen into the hemocoel.

Development and characterization of a novel plug and play liquid chromatography-mass spectrometry (LC-MS) source that automates connections between the capillary trap, column, and emitter

We report the development and characterization of a novel, vendor-neutral ultra-high pressure-compatible (~10,000 p.s.i.) LC-MS source. This device is the first to make automated connections with user-packed capillary traps, columns, and capillary emitters. The source uses plastic rectangular inserts (referred to here as cartridges) where individual components (i.e. trap, column, or emitter) can be exchanged independent of one another in a plug and play manner. Automated robotic connections are made between the three cartridges using linear translation powered by stepper motors to axially compress each cartridge by applying a well controlled constant compression force to each commercial LC fitting. The user has the versatility to tailor the separation (e.g. the length of the column, type of stationary phase, and mode of separation) to the experimental design of interest in a cost-effective manner. The source is described in detail, and several experiments are performed to evaluate the robustness of both the system and the exchange of the individual trap and emitter cartridges. The standard deviation in the retention time of four targeted peptides from a standard digest interlaced with a soluble Caenorhabditis elegans lysate ranged between 3.1 and 5.3 s over 3 days of analyses. Exchange of the emitter cartridge was found to have an insignificant effect on the abundance of various peptides. In addition, the trap cartridge can be replaced with minimal effects on retention time (<20 s).

Effects of column and gradient lengths on peak capacity and peptide identification in nanoflow LC-MS/MS of complex proteomic samples

Reversed-phase liquid chromatography is the most commonly used separation method for shotgun proteomics. Nanoflow chromatography has emerged as the preferred chromatography method for its increased sensitivity and separation. Despite its common use, there are a wide range of parameters and conditions used across research groups. These parameters have an effect on the quality of the chromatographic separation, which is critical to maximizing the number of peptide identifications and minimizing ion suppression. Here we examined the relationship between column lengths, gradient lengths, peptide identifications, and peptide peak capacity. We found that while longer column and gradient lengths generally increase peptide identifications, the degree of improvement is dependent on both parameters and is diminished at longer column and gradients. Peak capacity, in comparison, showed a more linear increase with column and gradient lengths. We discuss the discrepancy between these two results and some of the considerations that should be taken into account when deciding on the chromatographic conditions for a proteomics experiment.

De novo correction of mass measurement error in low resolution tandem MS spectra for shotgun proteomics

We report an algorithm designed for the calibration of low resolution peptide mass spectra. Our algorithm is implemented in a program called FineTune, which corrects systematic mass measurement error in 1 min, with no input required besides the mass spectra themselves. The mass measurement accuracy for a set of spectra collected on an LTQ-Velos improved 20-fold from -0.1776 ± 0.0010 m/z to 0.0078 ± 0.0006 m/z after calibration (avg ± 95 % confidence interval). The precision in mass measurement was improved due to the correction of non-linear variation in mass measurement accuracy across the m/z range.

Estimating relative abundances of proteins from shotgun proteomics data

Background

Spectral counting methods provide an easy means of identifying proteins with differing abundances between complex mixtures using shotgun proteomics data. The crux spectral-counts command, implemented as part of the Crux software toolkit, implements four previously reported spectral counting methods, the spectral index (SI_N), the exponentially modified protein abundance index (emPAI), the normalized spectral abundance factor (NSAF), and the distributed normalized spectral abundance factor (dNSAF).

Results

We compared the reproducibility and the linearity relative to each protein’s abundance of the four spectral counting metrics. Our analysis suggests that NSAF yields the most reproducible counts across technical and biological replicates, and both SI_N and NSAF achieve the best linearity.

Conclusions

With the crux spectral-counts command, Crux provides open-source modular methods to analyze mass spectrometry data for identifying and now quantifying peptides and proteins. The C++ source code, compiled binaries, spectra and sequence databases are available at http://noble.gs.washington.edu/proj/crux-spectral-counts.

Discovery and targeted LC-MS/MS of purified polerovirus reveals differences in the virus-host interactome associated with altered aphid transmission

Circulative transmission of viruses in the Luteoviridae, such as cereal yellow dwarf virus (CYDV), requires a series of precisely orchestrated interactions between virus, plant, and aphid proteins. Natural selection has favored these viruses to be retained in the phloem to facilitate acquisition and transmission by aphids. We show that treatment of infected oat tissue homogenate with sodium sulfite reduces transmission of the purified virus by aphids. Transmission electron microscopy data indicated no gross change in virion morphology due to treatments. However, treated virions were not acquired by aphids through the hindgut epithelial cells and were not transmitted when injected directly into the hemocoel. Analysis of virus preparations using nanoflow liquid chromatography coupled to tandem mass spectrometry revealed a number of host plant proteins co-purifying with viruses, some of which were lost following sodium sulfite treatment. Using targeted mass spectrometry, we show data suggesting that several of the virus-associated host plant proteins accumulated to higher levels in aphids that were fed on CYDV-infected plants compared to healthy plants. We propose two hypotheses to explain these observations, and these are not mutually exclusive: (a) that sodium sulfite treatment disrupts critical virion-host protein interactions required for aphid transmission, or (b) that host infection with CYDV modulates phloem protein expression in a way that is favorable for virus uptake by aphids. Importantly, the genes coding for the plant proteins associated with virus may be examined as targets in breeding cereal crops for new modes of virus resistance that disrupt phloem-virus or aphid-virus interactions.

The development of selected reaction monitoring methods for targeted proteomics via empirical refinement

Software advancements in the last several years have had a significant impact on proteomics from method development to data analysis. Herein, we detail a method, which uses our in-house developed software tool termed Skyline, for empirical refinement of candidate peptides from targeted proteins. The method consists of four main steps from generation of a testable hypothesis, method development, peptide refinement, to peptide validation. The ultimate goal is to identify the best performing peptide in terms of ionization efficiency, reproducibility, specificity, and chromatographic characteristics to monitor as a proxy for protein abundance. It is important to emphasize that this method allows the user to perform this refinement procedure in the sample matrix and organism of interest with the instrumentation available. Finally, the method is demonstrated in a case study to determine the best peptide to monitor the abundance of surfactant protein B in lung aspirates.

Learning score function parameters for improved spectrum identification in tandem mass spectrometry experiments

The identification of proteins from spectra derived from a tandem mass spectrometry experiment involves several challenges: matching each observed spectrum to a peptide sequence, ranking the resulting collection of peptide-spectrum matches, assigning statistical confidence estimates to the matches, and identifying the proteins. The present work addresses algorithms to rank peptide-spectrum matches. Many of these algorithms, such as PeptideProphet, IDPicker, or Q-ranker, follow a similar methodology that includes representing peptide-spectrum matches as feature vectors and using optimization techniques to rank them. We propose a richer and more flexible feature set representation that is based on the parametrization of the SEQUEST XCorr score and that can be used by all of these algorithms. This extended feature set allows a more effective ranking of the peptide-spectrum matches based on the target-decoy strategy, in comparison to a baseline feature set devoid of these XCorr-based features. Ranking using the extended feature set gives 10-40% improvement in the number of distinct peptide identifications relative to a range of q-value thresholds. While this work is inspired by the model of the theoretical spectrum and the similarity measure between spectra used specifically by SEQUEST, the method itself can be applied to the output of any database search. Further, our approach can be trivially extended beyond XCorr to any linear operator that can serve as similarity score between experimental spectra and peptide sequences.

A method to determine the kinetics of multiple proteins in human infants with respiratory distress syndrome

We report a method to measure in vivo turnover of four proteins from sequential tracheal aspirates obtained from human newborn infants with respiratory distress syndrome using targeted proteomics. We detected enrichment for all targeted proteins approximately 3 h from the start of infusion of [5,5,5-(2)H(3)] leucine, secretion times that varied from 1.2 to 2.5 h, and half lives that ranged between 10 and 21 h. Complement factor B, a component of the alternative pathway of complement activation, had an approximately twofold-longer half-life than the other three proteins. In addition, the kinetics of mature and carboxy-terminal tryptic peptides from the same protein (surfactant protein B) were not statistically different (p = 0.49).

Platform-independent and label-free quantitation of proteomic data using MS1 extracted ion chromatograms in skyline: application to protein acetylation and phosphorylation

Despite advances in metabolic and postmetabolic labeling methods for quantitative proteomics, there remains a need for improved label-free approaches. This need is particularly pressing for workflows that incorporate affinity enrichment at the peptide level, where isobaric chemical labels such as isobaric tags for relative and absolute quantitation and tandem mass tags may prove problematic or where stable isotope labeling with amino acids in cell culture labeling cannot be readily applied. Skyline is a freely available, open source software tool for quantitative data processing and proteomic analysis. We expanded the capabilities of Skyline to process ion intensity chromatograms of peptide analytes from full scan mass spectral data (MS1) acquired during HPLC MS/MS proteomic experiments. Moreover, unlike existing programs, Skyline MS1 filtering can be used with mass spectrometers from four major vendors, which allows results to be compared directly across laboratories. The new quantitative and graphical tools now available in Skyline specifically support interrogation of multiple acquisitions for MS1 filtering, including visual inspection of peak picking and both automated and manual integration, key features often lacking in existing software. In addition, Skyline MS1 filtering displays retention time indicators from underlying MS/MS data contained within the spectral library to ensure proper peak selection. The modular structure of Skyline also provides well defined, customizable data reports and thus allows users to directly connect to existing statistical programs for post hoc data analysis. To demonstrate the utility of the MS1 filtering approach, we have carried out experiments on several MS platforms and have specifically examined the performance of this method to quantify two important post-translational modifications: acetylation and phosphorylation, in peptide-centric affinity workflows of increasing complexity using mouse and human models.

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.

One-Year Plasma N-linked Glycome Intra-individual and Inter-individual Variability in the Chicken Model of Spontaneous Ovarian Adenocarcinoma

Spontaneous epithelial ovarian cancer (EOC) in the chicken presents a similar pathogenesis compared with humans including CA-125 expression and genetic mutational frequencies (e.g., p53). The high prevalence of spontaneous EOC chickens also provides a unique experimental model for biomarker discovery at the genomic, proteomic, glycomic, and metabolomic level. In an effort to exploit this unique model for biomarker discovery, longitudinal plasma samples were collected from chickens at three month intervals for one year. The study described herein involved cleaving the N-glycans from these longitudinal chicken plasma samples and analyzing them via nanoLC-FTMS/MS. Glycans identified in this study were previously found in human plasma and this work provides a promising methodology to enable longitudinal studies of the N-linked plasma glycome profile during EOC progression. The structure, abundance, and intra-variability and inter-variability for 35 N-linked glycans identified in this study are reported. The full potential of the chicken model for biomarker discovery has yet to be realized, but the initial interrogation of longitudinally-procured samples provides evidence that supports the value of this strategy in the search for glycomic biomarkers.

Comparison between procedures using SDS for shotgun proteomic analyses of complex samples

Filter-aided sample preparation (FASP) and a new sample preparation method using a modified commercial SDS removal spin column are quantitatively compared in terms of their performance for shotgun proteomic experiments in three complex proteomic samples: a Saccharomyces cerevisiae lysate (insoluble fraction), a Caenorhabditis elegans lysate (soluble fraction), and a human embryonic kidney cell line (HEK293T). The characteristics and total number of peptides and proteins identified are compared between the two procedures. The SDS spin column procedure affords a conservative fourfold improvement in throughput, is more reproducible, less expensive (i.e. requires less materials), and identifies between 30 and 107% more peptides at q≤0.01, than the FASP procedure. The peptides identified by SDS spin column are more hydrophobic than species identified by the FASP procedure as indicated by the distribution of GRAVY scores. Ultimately, these improvements correlate to as great as a 50% increase in protein identifications with two or more peptides.

N-linked global glycan profiling by nanoLC mass spectrometry

A method is detailed for the global profiling of underivatized N-linked glycans that are derived from complex protein mixtures. The method consists of five main steps that include the following: (1) protein denaturation; (2) enzymatic digestion; (3) solid phase extraction; (4) nanoLC MS analysis; and (5) data interpretation. Materials, methods, and algorithms for the identification of both glycan composition and structure are summarized. In addition, potential problems and their resolutions are addressed.

The effects of abundant plasma protein depletion on global glycan profiling using nanoLC FT-ICR mass spectrometry

We report the results of abundant plasma protein depletion on the analysis of underivatized N-linked glycans derived from plasma proteins by nanoLC Fourier-transform ion cyclotron resonance mass spectrometry. N-linked glycan profiles were compared between plasma samples where the six most abundant plasma proteins were depleted (n = 3) through a solid-phase immunoaffinity column and undepleted plasma samples (n = 3). Three exogenous glycan standards were spiked into all samples which allowed for normalization of the N-glycan abundances. The abundances of 20 glycans varying in type, structure, composition, and molecular weight (1,200-3,700 Da) were compared between the two sets of samples. Small fucosylated non-sialylated complex glycans were found to decrease in abundance in the depleted samples (greater than or equal to tenfold) relative to the undepleted samples. Protein depletion was found to marginally effect (less than threefold) the abundance of high mannose, hybrid, and large highly sialylated complex species. The significance of these findings in terms of future biomarker discovery experiments via global glycan profiling is discussed.

Development of a robust and high throughput method for profiling N-linked glycans derived from plasma glycoproteins by NanoLC-FTICR mass spectrometry

Recent investigations continue to emphasize the importance of glycosylation in various diseases including cancer. In this work, we present a step-by-step protocol describing a method for N-linked glycan profiling of plasma glycoproteins by nanoflow liquid chromatography Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS). A large experimental space was initially explored and is described herein. Three internal standards were spiked into the sample and provided normalization of plasma glycan abundance across different experimental conditions. Incubation methods and times and the effect of NP40 detergent on glycan abundance were explored. It was found that an 18-h incubation with no detergent led to the greatest ion abundance; however, data could be obtained in less than one day from raw plasma samples utilizing microwave irradiation or shorter incubation periods. The intersample precision of three different glycans was less than 5.5% (RSD) when the internal standards were added prior to the initial processing step. The high mass measurement accuracy (<3 ppm) afforded by the FTICR mass spectrometer provided confident identifications of several glycan species.

Development of a nanoLC LTQ orbitrap mass spectrometric method for profiling glycans derived from plasma from healthy, benign tumor control, and epithelial ovarian cancer patients

We report the development of split-less nano-flow liquid chromatography mass spectrometric analysis of glycans chemically cleaved from glycoproteins in plasma. Porous graphitized carbon operating under reverse-phase conditions and an amide-based stationary phase operating under hydrophilic interaction conditions are quantitatively compared for glycan separation. Both stationary phases demonstrated similar column efficiencies and excellent retention time reproducibility without an internal standard to correct for retention time shift. The 95% confidence intervals of the mean retention times were +/-4 s across 5 days of analysis for both stationary phases; however, the amide stationary phase was observed to be more robust. The high mass measurement accuracy of less than 2 ppm and fragmentation spectra provided highly confident identifications along with structural information. In addition, data are compared among samples derived from 10 healthy controls, 10 controls with a differential diagnosis of benign gynecologic tumors, and 10 diseased epithelial ovarian cancer patients (EOC). Two fucosylated glycans were found to be up-regulated in healthy controls and provided an accurate diagnostic value with an area under the receiver operator characteristic curve of 0.87. However, these same glycans provided a significantly less diagnostic value when used to differentiate EOC from benign tumor control samples with an area under the curve of 0.73.

Mass measurement accuracy comparisons between a double-focusing magnetic sector and a time-of-flight mass analyzer

We report a direct comparison of the mass measurement accuracies (MMAs) obtained on different mass spectrometry instrument types; a magnetic sector as the 'gold standard' and an electrospray ionization time-of-flight (ESI-TOF) instrument. Sixty samples, obtained from the Department of Chemistry at North Carolina State University, were analyzed on each instrument. Data are presented and compared between the different instruments. The average absolute MMAs achieved for the magnetic sector and Agilent ESI-TOF mass spectrometers were 3.0 and 1.1 ppm, respectively.

Carbohydrate analysis by desorption electrospray ionization fourier transform ion cyclotron resonance mass spectrometry

We report the use of desorption electrospray ionization hybrid Fourier transform ion cyclotron resonance mass spectrometry (DESI-FT-ICR-MS) for the analysis of carbohydrates. Spectra of neat carbohydrates are presented along with their mass measurement accuracies and limits of detection. Furthermore, a comparison is made between the analyses of O-linked glycans from mucin by DESI-FT-ICR-MS and matrix-assisted laser desorption/ionization Fourier transform ion cyclotron resonance mass spectrometry. Finally, glycans from mucin are identified by using the high mass measurement accuracy and tandem MS capabilities afforded by the hybrid FT-ICR-MS platform.

Remote mass spectrometric sampling of electrospray- and desorption electrospray-generated ions using an air ejector

A commercial air ejector was coupled to an electrospray ionization linear ion trap mass spectrometer (LTQ) to transport remotely generated ions from both electrospray (ESI) and desorption electrospray ionization (DESI) sources. We demonstrate the remote analysis of a series of analyte ions that range from small molecules and polymers to polypeptides using the AE-LTQ interface. The details of the ESI-AE-LTQ and DESI-AE-LTQ experimental configurations are described and preliminary mass spectrometric data are presented.

Detection of attomole amounts of analyte by desorption electrospray ionization mass spectrometry (DESI-MS) determined using fluorescence spectroscopy

We report the use of fluorescence spectroscopy to investigate the amount of material removed from a PTFE surface and detected during desorption electrospray ionization (DESI) mass spectrometry measurements. The fluorescence intensity before and after DESI analysis of rhodamine 6G is used to determine the amount of material removed from the surface per mass spectrum. Calculations indicate low attomole amounts are removed per linear ion trap mass spectrum.

Direct high-resolution peptide and protein analysis by desorption electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry

We report the first coupling of a desorption electrospray ionization (DESI) ion source to Fourier transform ion cyclotron resonance mass spectrometry (ESI-FT-ICR-MS) for high-resolution protein analysis. The DESI FT-ICR-MS source design is described in detail along with preliminary data obtained on peptides and proteins ranging from 1 to 5.7 kDa.