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.

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 ß-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.

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.

BMAA and MCLR Interact to Modulate Behavior and Exacerbate Molecular Changes Related to Neurodegeneration in Larval Zebrafish.

Exposure to toxins produced by cyanobacteria (ie, cyanotoxins) is an emerging health concern due to their increasing prevalence and previous associations with neurodegenerative diseases including amyotrophic lateral sclerosis. The objective of this study was to evaluate the neurotoxic effects of a mixture of two co-occurring cyanotoxins, ß-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. Although neither toxin caused mortality, morphological defects, nor altered general locomotor behavior in zebrafish larvae, both toxins increased acoustic startle sensitivity in a dose-dependent manner by at least 40% (p < .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 in the mixture-exposed group. Additionally, prediction analysis reveals activation and/or inhibition of 8 enriched canonical pathways (enrichment p-value < .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 amyotrophic lateral sclerosis 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 ß-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, ß-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 ß-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 ß-N-methylamino-L-alanine in environmental samples.

We describe a set of new tools for the detection and quantification of ß-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.

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.

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.

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.

Two paper-based microfluidic techniques, photolithography and wax patterning, were investigated for their potential to improve upon the sensitivity, reproducibility, and versatility of paper spray mass spectrometry. The main limitation of photolithography was the significant signal (approximately three orders of magnitude) above background which was attributed to the chemicals used in the photoresist process. Hydrophobic barriers created via wax patterning were discovered to have approximately 2 orders of magnitude less background signal compared to analogous barriers created using photolithography. A minimum printed wax barrier thickness of approximately 0.3 mm was necessary to consistently retain commonly used paper spray solvents (1 : 1 water : acetonitrile/methanol) and avoid leakage. Constricting capillary flow via wax-printed channels yielded both a significant increase in signal and detection time for detection of model analytes. This signal increase, which was attributed to restricting the radial flow of analyte/solvent on paper (i.e., a concentrating effect), afforded a significant increase in sensitivity (p ≪ 0.05) for the detection of pesticides spiked into residential tap water using a five-point calibration curve. Finally, unique mixing designs using wax patterning can be envisioned to perform on-paper analyte derivatization.

Reagent for Evaluating Liquid Chromatography-Tandem Mass Spectrometry (LC-MS/MS) Performance in Bottom-Up Proteomic Experiments.

We present a novel proteomic standard for assessing liquid chromatography-tandem mass spectrometry (LC-MS/MS) instrument performance, in terms of chromatographic reproducibility and dynamic range within a single LC-MS/MS injection. The peptide mixture standard consists of six peptides that were specifically synthesized to cover a wide range of hydrophobicities (grand average hydropathy (GRAVY) scores of -0.6 to 1.9). A combination of stable isotope labeled amino acids ((13)C and (15)N) were inserted to create five isotopologues. By combining these isotopologues at different ratios, they span four orders of magnitude within each distinct peptide sequence. Each peptide, from lightest to heaviest, increases in abundance by a factor of 10. We evaluate several metrics on our quadrupole orbitrap instrument using the 6 × 5 LC-MS/MS reference mixture spiked into a complex lysate background as a function of dynamic range, including mass measurement accuracy (MMA) and the linear range of quantitation of MS1 and parallel reaction monitoring experiments. Detection and linearity of the instrument routinely spanned three orders of magnitude across the gradient (500 fmol to 0.5 fmol on column) and no systematic trend was observed for MMA of targeted peptides as a function of abundance by analysis of variance analysis (p = 0.17). Detection and linearity of the fifth isotopologue (i.e., 0.05 fmol on column) was dependent on the peptide and instrument scan type (MS1 vs PRM). We foresee that this standard will serve as a powerful method to conduct both intra-instrument performance monitoring/evaluation, technology development, and inter-instrument comparisons.

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.

Tools for monitoring system suitability in LC MS/MS centric proteomic experiments.

With advances in liquid chromatography coupled to tandem mass spectrometry technologies combined with the continued goals of biomarker discovery, clinical applications of established biomarkers, and integrating large multiomic datasets (i.e. "big data"), there remains an urgent need for robust tools to assess instrument performance (i.e. system suitability) in proteomic workflows. To this end, several freely available tools have been introduced that monitor a number of peptide identification (ID) and/or peptide ID free metrics. Peptide ID metrics include numbers of proteins, peptides, or peptide spectral matches identified from a complex mixture. Peptide ID free metrics include retention time reproducibility, full width half maximum, ion injection times, and integrated peptide intensities. The main driving force in the development of these tools is to monitor both intra- and interexperiment performance variability and to identify sources of variation. The purpose of this review is to summarize and evaluate these tools based on versatility, automation, vendor neutrality, metrics monitored, and visualization capabilities. In addition, the implementation of a robust system suitability workflow is discussed in terms of metrics, type of standard, and frequency of evaluation along with the obstacles to overcome prior to incorporating a more proactive approach to overall quality control in liquid chromatography coupled to tandem mass spectrometry based proteomic workflows.