Rapid optimization of MRM-MS instrument parameters by subtle alteration of precursor and product m/z targets

Absolute quantification of viral proteins from pseudotyped VSV-GP using UPLC-MRM

The rapidly developing field of oncolytic virus (OV) therapy necessitates the development of new and improved analytical approaches for the characterization of the virus during production and development. Accurate monitoring and absolute quantification of viral proteins are crucial for OV product characterization and can facilitate the understanding of infection, immunogenicity, and development stages of viral replication. Targeted mass spectrometry methods like multiple reaction monitoring (MRM) offer a robust way to directly detect and quantify specific targeted proteins represented by surrogate peptides. We have leveraged the power of MRM by combining ultra-high performance liquid chromatography (UPLC) with a Sciex 6500 triple-stage quadrupole mass spectrometer to develop an assay that accurately and absolutely quantifies the structural proteins of a pseudotyped vesicular stomatitis virus (VSV) intended for use as a new biotherapeutic (designated hereafter as VSV-GP to differentiate it from native VSV). The new UPLC-MRM method provides absolute quantification with the use of heavy-labeled reference standard surrogate peptides. When added in known exact amounts to standards and samples, the reference standards normalize and account for any small perturbations during sample preparation and/or instrument performance, resulting in accurate and precise quantification. Because of the multiplexed nature of MRM, all targeted proteins are quantified at the same time. The optimized assay has been enhanced to quantify the ratios of the processed GP1 and GP2 proteins while simultaneously measuring any remaining or unprocessed form of the envelope protein GP complex (GPC; full-length GPC).

IMPORTANCE

The development of oncolytic viral therapy has gained considerable momentum in recent years. Vesicular stomatitis virus glycoprotein (VSV-GP) is a new biotherapeutic emerging in the oncolytic viral therapy platform. Novel analytical assays that can accurately and precisely quantify the viral proteins are a necessity for the successful development of viral vector as a biotherapeutic. We developed an ultra-high performance liquid chromatography multiple reaction monitoring-based assay to quantify the absolute concentrations of the different structural proteins of VSV-GP. The complete processing of GP complex (GPC) is a prerequisite for the infectivity of the virus. The assay extends the potential for quantifying full-length GPC, which provides an understanding of the processing of GPC (along with the quantification of GP1 and GP2 separately). We used this assay in tracking GPC processing in HEK-293-F production cell lines infected with VSV-GP.

Collision energies: Optimization strategies for bottom-up proteomics

Mass-spectrometry coupled to liquid chromatography is an indispensable tool in the field of proteomics. In the last decades, more and more complex and diverse biochemical and biomedical questions have arisen. Problems to be solved involve protein identification, quantitative analysis, screening of low abundance modifications, handling matrix effect, and concentrations differing by orders of magnitude. This led the development of more tailored protocols and problem centered proteomics workflows, including advanced choice of experimental parameters. In the most widespread bottom-up approach, the choice of collision energy in tandem mass spectrometric experiments has outstanding role. This review presents the collision energy optimization strategies in the field of proteomics which can help fully exploit the potential of MS based proteomics techniques. A systematic collection of use case studies is then presented to serve as a starting point for related further scientific work. Finally, this article discusses the issue of comparing results from different studies or obtained on different instruments, and it gives some hints on methodology transfer between laboratories based on measurement of reference species.

Quantifiable peptide library bridges the gap for proteomics based biomarker discovery and validation on breast cancer

Mass spectrometry (MS) based proteomics is widely used for biomarker discovery. However, often, most biomarker candidates from discovery are discarded during the validation processes. Such discrepancies between biomarker discovery and validation are caused by several factors, mainly due to the differences in analytical methodology and experimental conditions. Here, we generated a peptide library which allows discovery of biomarkers in the equal settings as the validation process, thereby making the transition from discovery to validation more robust and efficient. The peptide library initiated with a list of 3393 proteins detectable in the blood from public databases. For each protein, surrogate peptides favorable for detection in mass spectrometry was selected and synthesized. A total of 4683 synthesized peptides were spiked into neat serum and plasma samples to check their quantifiability in a 10 min liquid chromatography-MS/MS run time. This led to the PepQuant library, which is composed of 852 quantifiable peptides that cover 452 human blood proteins. Using the PepQuant library, we discovered 30 candidate biomarkers for breast cancer. Among the 30 candidates, nine biomarkers, FN1, VWF, PRG4, MMP9, CLU, PRDX6, PPBP, APOC1, and CHL1 were validated. By combining the quantification values of these markers, we generated a machine learning model predicting breast cancer, showing an average area under the curve of 0.9105 for the receiver operating characteristic curve.

A validated LC-MS/MS method for clinical pharmacokinetics and presumptive phase II metabolic pathways following oral administration of Andrographis paniculata extract

Andrographis paniculata, a medicinal plant in Thailand national list of essential medicines, has been proposed for treatment of patients with mild to moderate coronavirus disease 2019. This study aims to develop a highly selective and sensitive liquid chromatography triple quadrupole tandem mass spectrometry method for quantitative determination of major diterpenoids in plasma and urine with application in pharmacokinetics. Chromatographic separation was performed on C18 column using a gradient mobile phase of water and acetonitrile. Mass spectrometry was analyzed using multiple reaction monitoring with negative ionization mode. This validated analytical method was very sensitive, less time consuming in analysis, and allowed the reliability and reproducibility on its application. The clinical pharmacokinetics was evaluated after single oral administration of A. paniculata extract (calculated as 60 mg of andrographolide). The disposition kinetics demonstrated that major diterpenoids could enter into systemic circulation, but they are mostly biotransformed (phase II) into conjugated glucuronide and sulfate metabolites. These metabolites are predominantly found in plasma and then extremely eliminated, in part through urinary excretion. The successful application of this analytical method supports its suitable uses in further clinical benefits after oral administration of A. paniculata.

Advancements in Oncoproteomics Technologies: Treading toward Translation into Clinical Practice

Proteomics continues to forge significant strides in the discovery of essential biological processes, uncovering valuable information on the identity, global protein abundance, protein modifications, proteoform levels, and signal transduction pathways. Cancer is a complicated and heterogeneous disease, and the onset and progression involve multiple dysregulated proteoforms and their downstream signaling pathways. These are modulated by various factors such as molecular, genetic, tissue, cellular, ethnic/racial, socioeconomic status, environmental, and demographic differences that vary with time. The knowledge of cancer has improved the treatment and clinical management; however, the survival rates have not increased significantly, and cancer remains a major cause of mortality. Oncoproteomics studies help to develop and validate proteomics technologies for routine application in clinical laboratories for (1) diagnostic and prognostic categorization of cancer, (2) real-time monitoring of treatment, (3) assessing drug efficacy and toxicity, (4) therapeutic modulations based on the changes with prognosis and drug resistance, and (5) personalized medication. Investigation of tumor-specific proteomic profiles in conjunction with healthy controls provides crucial information in mechanistic studies on tumorigenesis, metastasis, and drug resistance. This review provides an overview of proteomics technologies that assist the discovery of novel drug targets, biomarkers for early detection, surveillance, prognosis, drug monitoring, and tailoring therapy to the cancer patient. The information gained from such technologies has drastically improved cancer research. We further provide exemplars from recent oncoproteomics applications in the discovery of biomarkers in various cancers, drug discovery, and clinical treatment. Overall, the future of oncoproteomics holds enormous potential for translating technologies from the bench to the bedside.

The Parallel Reaction Monitoring-Parallel Accumulation-Serial Fragmentation (prm-PASEF) Approach for Multiplexed Absolute Quantitation of Proteins in Human Plasma

Mass spectrometry (MS)-based quantitative proteomic methods have become some of the major tools for protein biomarker discovery and validation. The recently developed parallel reaction monitoring-parallel accumulation-serial fragmentation (prm-PASEF) approach on a Bruker timsTOF Pro mass spectrometer allows the addition of ion mobility as a new dimension to LC-MS-based proteomics and increases proteome coverage at a reduced analysis time. In this study, a prm-PASEF approach was used for the multiplexed absolute quantitation of proteins in human plasma using isotope-labeled peptide standards for 125 plasma proteins, over a broad (10⁴-10⁶) dynamic range. Optimization of LC and MS parameters, such as accumulation time and collision energy, resulted in improved sensitivity for more than half of the targets (73 out of 125 peptides) by increasing the signal-to-noise ratio by a factor of up to 10. Overall, 41 peptides showed up to a 2-fold increase in sensitivity, 25 peptides showed up to a 5-fold increase in sensitivity, and 7 peptides showed up to a 10-fold increase in sensitivity. Implementation of the prm-PASEF method allowed absolute protein quantitation (down to 1.13 fmol) in human plasma samples. A comparison of the concentration values of plasma proteins determined by MRM on a QTRAP instrument and by prm-PASEF on a timsTOF Pro revealed an excellent correlation (R² = 0.97) with a slope of close to 1 (0.99), demonstrating that prm-PASEF is well suited for "absolute" quantitative proteomics.

A rapid and sensitive UPLC–MS/MS method for quantification of erdosteine as bulk drug and in capsules as dosage forms

A rapid, sensitive, specific ultra-performance liquid chromatography-tandem mass spectrometric (UPLC-MS-MS) method was developed for the determination of erdosteine (ERD) in pharmaceutical preparations. The chromatographic separation was achieved with 0.1% formic acid in combination with acetonitrile (25:75 v/v) using C18 UPLC column, 95Å, 2.1 x 50 mm, 1.8 µm. The flow rate was 0.15 mL/min and the total run time was 2.0 min. The column temperature was kept constant at 40 °C and the injection volume was 5 μL. Ibuprofen was used as internal standard (IS). The mass transitions of ERD and IS were m/z 249.9 → 231.8 and 205.1 → 161.0. Also, another product ion of ERD (m/z 249.80 → 231.80) was monitored as predictive ion during the analysis. The standard calibration curve shows determination coefficient (R2) greater than 0.996 with a range of 1-5000 ng/mL using the linear regression model. Within-run precision and between-run repeatability were expressed as relative standard deviation and were lower than 5%. The developed method was successfully applied in the analysis of ERD-containing capsule formulation indicating that the method could be used for routine quality control analyses. Keywords: erdosteine, UPLC-MS/MS, multiple reaction monitoring, pharmaceutical analysis, method validation

Antibiotic standards stored as a mixture in water: methanol are unstable at various temperatures irrespective of pH and glass container silanization

It is well-established that antibiotics stored individually at their optimal pH and in appropriate solvents are stable over time. However, limited information exists on the stability of antibiotics from multiple classes when prepared and stored as a mixture prior to multiresidue analysis by mass spectrometry. This study tested the stability of antibiotic standard mixtures from eight classes [amphenicols, tetracyclines, sulfonamides, quinolones, macrolides, β-lactams, lincosamides and miscellaneous (i.e., trimethoprim)] in relation to the water:methanol ratio, presence of sodium hydroxide base (to solubilise quinolones), storage temperature, and container type including plain and silanized glass vials. Antibiotics were analysed by ultra-high-performance liquid chromatography coupled to tandem mass spectrometry. Several antibiotics, mainly quinolones, tetracyclines and macrolides, were unstable when stored as mixtures for one week regardless of the water:methanol ratio, storage temperature (4, -20 or -80 °C) and presence/absence of sodium hydroxide. Silanization of glassware improved the storage stability of quinolones and macrolides but reduced the stability of tetracyclines and other antibiotics including florfenicol amine, penicillin G, erythromycin and sulfadiazine. Our results show that several antibiotics in water:methanol are unstable when stored as a mixture and suggest a limited advantage of using base or silanized glass vials for the preparation and storage of antibiotic standards mixed together. Freshly prepared antibiotic standard mixtures are recommended for multi-residue quantitation of antibiotics.Abbreviations AMOX: amoxicillin; AMP: ampicillin; AZ: azithromycin; CAP: chloramphenicol; CE: collision energy; CTC: chlortetracycline; CIP: ciprofloxacin; DOX: doxycycline; ENO: enoxacin; ENRO: enrofloxacin; ERYTH: erythromycin; FF: florfenicol; FFA: florfenicol amine; FLU: flumequine; HDPE: high-density polyethylene; LC-MS/MS: liquid chromatography-tandem mass spectrometry; LIN: lincomycin; MRM: multiple reaction monitoring; NOR: norfloxacin; OFL-D3: ofloxacin-D3; OXO: oxolinic acid; OTC: oxytetracycline; PEN-G: penicillin G; PEN-V: penicillin V; ROX: roxithromycin; SDM: sulfadimethoxine; SDZ: sulfadiazine; SMX: sulfamethoxazole; SMZ-D4: sulfamethazine-D4; SSZ: sulfasalazine; TC: tetracycline; TAP: thiamphenicol; TILM: tilmicosin; TRIM: trimethoprim; TL: tolerance limit; VIRG: virginiamycin; UPLC-MS/MS: ultra-high pressure liquid chromatography-tandem mass spectrometry.

Multiple reaction monitoring for identification and quantification of oligosaccharides in legumes using a triple quadrupole mass spectrometer

Raffinose family oligosaccharides are non-digestible compounds considered as dietary prebiotics with health-related properties. Hence, it is important to develop highly specific methods for their determination. An analytical method is developed in this study for oligosaccharide identification and quantification using liquid chromatography-tandem mass spectrometry equipped with a triple quadrupole analyser operating in Multiple Reaction Monitoring mode. Raffinose, stachyose and verbascose are separated in a 10-minute run and the method is validated over a broad concentration range, showing good linearity, accuracy, precision and high sensitivity. A low-cost, short eco-friendly procedure for oligosaccharide extraction from legumes, with a high recovery rate extraction, good repeatability and reproducibility is also proposed. No plant-matrix effects were demonstrated. The method applied to the screening of 28 different legumes revealed species-related traits for oligosaccharide distribution, highlighting Pisum sativum (9.22 g/100 g) as the richest source of these prebiotics and its suitability as a functional food ingredient.

Sweat metabolome and proteome: Recent trends in analytical advances and potential biological functions

Metabolome and proteome profiling of biofluids, e.g., urine, plasma, has generated vast and ever-increasing amounts of knowledge over the last few decades. Paradoxically, omics analyses of sweat, one of the most readily available human biofluids, have lagged behind. This review capitalizes on the current knowledge and state of the art analytical advances of sweat metabolomics and proteomics. Moreover, current applications of sweat omics such as the discovery of disease biomarkers and monitoring athletic performance are also presented in this review. Another area of emerging knowledge that has been highlighted herein lies in the role of skin host-microbiome interactions in shaping the sweat metabolite-protein profiles. Discussion of future research directions describes the need to have a better grasp of sweat chemicals and to better understand how they function as aided by advances in omics tools. Overall, the role of sweat as an information-rich biofluid that could complement the exploration of the skin metabolome/proteome is emphasized.

Simultaneous determination of eight tryptic peptides in musk using high-performance liquid chromatography coupled with tandem mass spectrometry

In comparison of herbal medicines, less attention has been paid onto animal medicines, partially attributing to the protein-enriched property. Particularly, it is still challenging to conduct quality evaluation for the animal medicines because of the lack of a fit-for-purpose analytical tool. Herein, an attempt was made to propose a workflow allowing the quality assessment of animal medicines by LC-MS/MS, and musk that is one of the most precious traditional Chinese medicines was employed as a representative case for utility illustration. After the extraction of protein from musk with a well-defined protocol, tryptic digestion was conducted to hydrolyze proteins into peptides, and the peptide-enriched sample was subjected to nanoLC-Orbitrap MS measurement. The tandem mass spectral dataset was retrieved in Human Swiss-Prot FASTA database, and the sequences together with the sources of 733 tryptic peptides, in total, were annotated. Because of the abundant distributions, eight peptides were chosen as the analytes for quantitative measurements, and their quantitative MS parameters, such as ion transitions and collision energies, were rapid optimized in an authentic compound-free manner using online energy-resolved MS (ER-MS). On the other side, the annotated peptides were structurally consolidated via synthesizing reference peptides. When the synthetic peptides were applied for parameter optimization with the authentic compound-dependent manner, the values were almost identical with those from online ER-MS measurements. After being validated with diverse assays, the developed method was applied for the simultaneous determination of eight peptides in 28 batches of musk samples, including captive (C1-C18) and wild ones (W1-W10). Significant differences took place for the content patterns of concerned tryptic peptides between the captive and wild musk samples. Trace distributions occurred for DVDAAYMNK in most batches. Captive samples were rich of QSLEASLAETEGR, TLLDIDNTR, and EVATNSELVQSGK, whereas wild samples were able to accumulate YLGYLEQLLR. Together, the present study provided a meaningful approach for the quality evaluation of musk, as well as other peptide-enriched animal medicines, even if the absences of authentic peptides.

Tailoring to Search Engines: Bottom-Up Proteomics with Collision Energies Optimized for Identification Confidence

Bottom-up proteomics relies on identification of peptides from tandem mass spectra, usually via matching against sequence databases. Confidence in a peptide–spectrum match can be characterized by a score value given by the database search engines, and it depends on the information content and the quality of the spectrum. The latter are influenced by experimental parameters, of which the collision energy is the most important one in the case of collision-induced dissociation. We examined how the identification score of the Byonic and Andromeda (MaxQuant) engines varies with collision energy for more than a thousand individual peptides from a HeLa tryptic digest on a QTof instrument. We thereby extended our earlier study on Mascot scores and corroborated its findings on the potential bimodal nature of this energy dependence. Optimal energies as a function of m/z show comparable linear trends for the three engines. On the basis of peptide-level results, we designed methods with one or two liquid chromatography–tandem mass spectrometry (LC-MS/MS) runs and various collision energy settings and assessed their practical performance in peptide and protein identification from the HeLa standard sample. A 10–40% gain in various measures, such as the number of identified proteins or sequence coverage, was obtained over the factory default settings. Best performing methods differ for the three engines, suggesting that the experimental parameters should be fine-tuned to the choice of the engine. We also recommend a simple approach and provide reference data to ease the transfer of the optimized methods to other mass spectrometers relevant for proteomics. We demonstrate the utility of this approach on an Orbitrap instrument. Data sets can be accessed via the MassIVE repository (MSV000086379).

Functional Characterization of POFUT1 Variants Associated with Colorectal Cancer

BACKGROUND

Protein O-fucosyltransferase 1 (POFUT1) overexpression, which is observed in many cancers such as colorectal cancer (CRC), leads to a NOTCH signaling dysregulation associated with the tumoral process. In rare CRC cases, with no POFUT1 overexpression, seven missense mutations were found in human POFUT1.

METHODS

Recombinant secreted forms of human WT POFUT1 and its seven mutated counterparts were produced and purified. Their O-fucosyltransferase activities were assayed in vitro using a chemo-enzymatic approach with azido-labeled GDP-fucose as a donor substrate and NOTCH1 EGF-LD26, produced in E. coli periplasm, as a relevant acceptor substrate. Targeted mass spectrometry (MS) was carried out to quantify the O-fucosyltransferase ability of all POFUT1 proteins.

FINDINGS

MS analyses showed a significantly higher O-fucosyltransferase activity of six POFUT1 variants (R43H, Y73C, T115A, I343V, D348N, and R364W) compared to WT POFUT1.

INTERPRETATION

This study provides insights on the possible involvement of these seven missense mutations in colorectal tumors. The hyperactive forms could lead to an increased O-fucosylation of POFUT1 protein targets such as NOTCH receptors in CRC patients, thereby leading to a NOTCH signaling dysregulation. It is the first demonstration of gain-of-function mutations for this crucial glycosyltransferase, modulating NOTCH activity, as well as that of other potential glycoproteins.

The Skyline ecosystem: Informatics for quantitative mass spectrometry proteomics

Skyline is a freely available, open-source Windows client application for accelerating targeted proteomics experimentation, with an emphasis on the proteomics and mass spectrometry community as users and as contributors. This review covers the informatics encompassed by the Skyline ecosystem, from computationally assisted targeted mass spectrometry method development, to raw acquisition file data processing, and quantitative analysis and results sharing.

Improving Peptide Fragmentation for Hydrogen-Deuterium Exchange Mass Spectrometry Using a Time-Dependent Collision Energy Calculator

Hydrogen-deuterium exchange mass spectrometry (HDX-MS) is becoming a popular technique for interrogating biological systems. In recent years, advancements have been made to increase peptide coverage for proteins that resist digestion such as antibodies and membrane proteins. These methods commonly include using alternative digestion enzymes or longer chromatographic gradients, which may be expensive or time-consuming to implement. Here, we recommend an efficient proteomics-based approach to increase peptide confidence and coverage. A major filtering parameter for peptides in HDX is the number of product ions detected; this is a result of the collision energy (CE) applied within the MS. A traditional linear ramp achieves optimal CE for only short periods of time. More product ions will be created and detected if optimal CE can be achieved for a longer period of time. As a result, the coverage, redundancy, and data confidence are all increased. We achieved this by implementing a mobility-dependent CE look up table (LUT) which increases the CE as a function of mobility. We developed a program to calculate the optimal CE for a set of peptides and MS settings based on initial reference samples. We demonstrated the utility of the CE LUT on three protein samples including the soluble phosphorylase B, IgG2, and the membrane-stabilized AcrB. We showed that applying a CE LUT provided 8.5-50% more peptides compared to a linear CE ramp. The results demonstrate that a time-dependent CE LUT is a quick and inexpensive method to increase data confidence and peptide abundance for HDX-MS experiments.

Affinity-Bead Assisted Mass Spectrometry (Affi-BAMS): A Multiplexed Microarray Platform for Targeted Proteomics

The ability to quantitatively probe diverse panels of proteins and their post-translational modifications (PTMs) across multiple samples would aid a broad spectrum of biological, biochemical and pharmacological studies. We report a novel, microarray analytical technology that combines immuno-affinity capture with Matrix Assisted Laser Desorption Ionization Mass Spectrometry (MALDI MS), which is capable of supporting highly multiplexed, targeted proteomic assays. Termed "Affinity-Bead Assisted Mass Spectrometry" (Affi-BAMS), this LC-free technology enables development of highly specific and customizable assay panels for simultaneous profiling of multiple proteins and PTMs. While affinity beads have been used previously in combination with MS, the Affi-BAMS workflow uses enrichment on a single bead that contains one type of antibody, generally capturing a single analyte (protein or PTM) while having enough binding capacity to enable quantification within approximately 3 orders of magnitude. The multiplexing capability is achieved by combining Affi-BAMS beads with different protein specificities. To enable screening of bead-captured analytes by MS, we further developed a novel method of performing spatially localized elution of targets from individual beads arrayed on a microscope slide. The resulting arrays of micro spots contain highly concentrated analytes localized within 0.5 mm diameter spots that can be directly measured using MALDI MS. While both intact proteins and protein fragments can be monitored by Affi-BAMS, we initially focused on applying this technology for bottom-up proteomics to enable screening of hundreds of samples per day by combining the robust magnetic bead-based workflow with the high throughput nature of MALDI MS acquisition. To demonstrate the variety of applications and robustness of Affi-BAMS, several studies are presented that focus on the response of 4EBP1, RPS6, ERK1/ERK2, mTOR, Histone H3 and C-MET to stimuli including rapamycin, H2O2, EPO, SU11274, Staurosporine and Vorinostat.

Proteomic profiling of HIV-infected T-cells by SWATH mass spectrometry

Viral pathogenesis results from changes in host cells due to virus usurpation of the host cell and the innate cellular responses to thwart infection. We measured global changes in protein expression and localization in HIV-1 infected T-cells using subcellular fractionation and the Sequential Window Acquisition of all Theoretical Mass Spectra (SWATH-MS) proteomic platform. Eight biological replicates were performed in two independent experimental series. In silico merging of both experiments identified 287 proteins with altered expression (p < .05) between control and infected cells- 172 in the cytoplasm, 84 in the membrane, and 31 in nuclei. 170 of the proteins are components of the NIH HIV interaction database. Multiple Reaction Monitoring and traditional immunoblotting validated the altered expression of several factors during infection. Numerous factors were found to affect HIV infection in gain- and loss-of-expression infection assays, including the intermediate filament vimentin which was found to be required for efficient infection.

Selection of Collision Energies in Proteomics Mass Spectrometry Experiments for Best Peptide Identification: Study of Mascot Score Energy Dependence Reveals Double Optimum

Collision energy is a key parameter determining the information content of beam-type collision induced dissociation tandem mass spectrometry (MS/MS) spectra, and its optimal choice largely affects successful peptide and protein identification in MS-based proteomics. For an MS/MS spectrum, quality of peptide match based on sequence database search, often characterized in terms of a single score, is a complex function of spectrum characteristics, and its collision energy dependence has remained largely unexplored. We carried out electrospray ionization-quadrupole-time of flight (ESI-Q-TOF)-MS/MS measurements on 2807 peptides from tryptic digests of HeLa and E. coli at 21 different collision energies. Agglomerative clustering of the resulting Mascot score versus energy curves revealed that only few of them display a single, well-defined maximum; rather, they feature either a broad plateau or two clear peaks. Nonlinear least-squares fitting of one or two Gaussian functions allowed the characteristic energies to be determined. We found that the double peaks and the plateaus in Mascot score can be associated with the different energy dependence of b- and y-type fragment ion intensities. We determined that the energies for optimum Mascot scores follow separate linear trends for the unimodal and bimodal cases with rather large residual variance even after differences in proton mobility are taken into account. This leaves room for experiment optimization and points to the possible influence of further factors beyond m/ z.

Evaluation of bioactive compounds potential and antioxidant activity of brown, green and red propolis from Brazilian northeast region

The aim of the present study was to determine the contents of bioactive compounds present in brown, green and red species of propolis cultivated in the Brazilian northeast states of Alagoas and Sergipe. The contents of phenolic compounds, flavonoids and antioxidant activity (DPPH, ABTS⁺, FRAP, ORAC) were determined. Identification and quantification of phenolic and flavonoid compounds were performed by using UHPLC-QqQ-MS/MS system. The results revealed high contents of total phenolics and flavonoids. Among the three species, the antioxidant potential had higher capacity in the red propolis. The presence of some of bioactive compounds viz. acacetin, artepellin C, eriodictyol, gallic acid, isorhamnetin, protocatechuic acid, vanillin and vanillic acid in Brazilian red propolis is reported for the first time in this work. Positive correlation between total phenolics versus the FRAP and ORAC methods was established which led to conclusion that antioxidant activity of propolis is mainly due to its phenolic compounds.

New approaches for extraction and determination of betaine from Beta vulgaris samples by hydrophilic interaction liquid chromatography-tandem mass spectrometry

Betaine is one of most studied biologically active compounds, due its role in the main biological processes. Although it may be found in several plants and roots, such as the Beta vulgaris family, present in typical diets, just a few analytical methods have been developed for its extraction from roots. A new, quick and effective procedure for the isolation and determination of betaine from two different varieties of B. vulgaris (red and gold) is presented. For betaine extraction, an accelerated solvent extraction (ASE) was coupled with solid-phase extraction. For betaine determination, a separation method based on hydrophilic interaction chromatography coupled with tandem mass spectrometry was optimized for a sensible detection of betaine by means of experimental design. Recoveries were about 93%, with RSD <5%, for both the matrices, without evidence of interfering species. The total content of betaine in extracts of various parts of plants (juice, peel, root) have been determined, obtaining concentrations in the range 3000–4000 mg/L for the juice and in the range 2–5 mg/g for the pulp and for the peel. The B. vulgaris gold species exhibited a higher concentration of betaine, compared to the red variety. Additionally, a micro extraction by packed sorbent technique and a modified quick, easy, cheap, rugged and safe (QuEChERS) procedure, were also tested and compared. Despite the lower recoveries of the latter, with respect to the ASE/SPE procedure (75–89%, RSD <1.5%), the ease of the method, which can be applied without the SPE purification procedure, can represent a positive improvement.

Graphical abstract

Analysis of Major Histocompatibility Complex (MHC) Immunopeptidomes Using Mass Spectrometry

The myriad of peptides presented at the cell surface by class I and class II major histocompatibility complex (MHC) molecules are referred to as the immunopeptidome and are of great importance for basic and translational science. For basic science, the immunopeptidome is a critical component for understanding the immune system; for translational science, exact knowledge of the immunopeptidome can directly fuel and guide the development of next-generation vaccines and immunotherapies against autoimmunity, infectious diseases, and cancers. In this mini-review, we summarize established isolation techniques as well as emerging mass spectrometry-based platforms (i.e. SWATH-MS) to identify and quantify MHC-associated peptides. We also highlight selected biological applications and discuss important current technical limitations that need to be solved to accelerate the development of this field.

Multiple stage MS in analysis of plasma, serum, urine and in vitro samples relevant to clinical and forensic toxicology

This paper reviews MS approaches applied to metabolism studies, structure elucidation and qualitative or quantitative screening of drugs (of abuse) and/or their metabolites. Applications in clinical and forensic toxicology were included using blood plasma or serum, urine, in vitro samples, liquids, solids or plant material. Techniques covered are liquid chromatography coupled to low-resolution and high-resolution multiple stage mass analyzers. Only PubMed listed studies published in English between January 2008 and January 2015 were considered. Approaches are discussed focusing on sample preparation and mass spectral settings. Comments on advantages and limitations of these techniques complete the review.

Stepped MS(All) Relied Transition (SMART): An approach to rapidly determine optimal multiple reaction monitoring mass spectrometry parameters for small molecules

Multiple reaction monitoring (MRM) is a universal approach for quantitative analysis because of its high specificity and sensitivity. Nevertheless, optimization of MRM parameters remains as a time and labor-intensive task particularly in multiplexed quantitative analysis of small molecules in complex mixtures. In this study, we have developed an approach named Stepped MS(All) Relied Transition (SMART) to predict the optimal MRM parameters of small molecules. SMART requires firstly a rapid and high-throughput analysis of samples using a Stepped MS(All) technique (sMS(All)) on a Q-TOF, which consists of serial MS(All) events acquired from low CE to gradually stepped-up CE values in a cycle. The optimal CE values can then be determined by comparing the extracted ion chromatograms for the ion pairs of interest among serial scans. The SMART-predicted parameters were found to agree well with the parameters optimized on a triple quadrupole from the same vendor using a mixture of standards. The parameters optimized on a triple quadrupole from a different vendor was also employed for comparison, and found to be linearly correlated with the SMART-predicted parameters, suggesting the potential applications of the SMART approach among different instrumental platforms. This approach was further validated by applying to simultaneous quantification of 31 herbal components in the plasma of rats treated with a herbal prescription. Because the sMS(All) acquisition can be accomplished in a single run for multiple components independent of standards, the SMART approach are expected to find its wide application in the multiplexed quantitative analysis of complex mixtures.

Adaptation of Skyline for Targeted Lipidomics

In response to the urgent need for analysis software that is capable of handling data from targeted high-throughput lipidomics experiments, we here present a systematic workflow for the straightforward method design and analysis of selected reaction monitoring data in lipidomics based on lipid building blocks. Skyline is a powerful software primarily designed for proteomics applications where it is widely used. We adapted this tool to a "Plug and Play" system for lipid research. This extension offers the unique capability to assemble targeted mass spectrometry methods for complex lipids easily by making use of building blocks. With simple yet tailored modifications, targeted methods to analyze main lipid classes such as glycerophospholipids, sphingolipids, glycerolipids, cholesteryl-esters, and cholesterol can be quickly introduced into Skyline for easy application by end users without distinct bioinformatics skills. To illustrate the benefits of our novel strategy, we used Skyline to quantify sphingolipids in mesenchymal stem cells. We demonstrate a simple method building procedure for sphingolipids screening, collision energy optimization, and absolute quantification of sphingolipids. In total, 72 sphingolipids were identified and absolutely quantified at the fatty acid scan species level by utilizing Skyline for data interpretation and visualization.

Recent developments in proteomic methods and disease biomarkers

Proteomic methodologies for identification and analysis of biomarkers have gained more attention during recent years and have evolved rapidly. Identification and detection of disease biomarkers are important to foresee outbreaks of certain diseases thereby avoiding surgery and other invasive and expensive medical treatments for patients. Thus, more research into discovering new biomarkers and new methods for faster and more accurate detection is needed. It is often difficult to detect and measure biomarkers because of their low concentrations and the complexity of their respective matrices. Therefore it is hard to find and validate methods for accurate screening methods suitable for clinical use. The most recent developments during the last three years and also some historical considerations of proteomic methodologies for identification and validation of disease biomarkers are presented in this review.

The role of quantitative mass spectrometry in the discovery of pancreatic cancer biomarkers for translational science

In the post-genomic era, it has become evident that genetic changes alone are not sufficient to understand most disease processes including pancreatic cancer. Genome sequencing has revealed a complex set of genetic alterations in pancreatic cancer such as point mutations, chromosomal losses, gene amplifications and telomere shortening that drive cancerous growth through specific signaling pathways. Proteome-based approaches are important complements to genomic data and provide crucial information of the target driver molecules and their post-translational modifications. By applying quantitative mass spectrometry, this is an alternative way to identify biomarkers for early diagnosis and personalized medicine. We review the current quantitative mass spectrometric technologies and analyses that have been developed and applied in the last decade in the context of pancreatic cancer. Examples of candidate biomarkers that have been identified from these pancreas studies include among others, asporin, CD9, CXC chemokine ligand 7, fibronectin 1, galectin-1, gelsolin, intercellular adhesion molecule 1, insulin-like growth factor binding protein 2, metalloproteinase inhibitor 1, stromal cell derived factor 4, and transforming growth factor beta-induced protein. Many of these proteins are involved in various steps in pancreatic tumor progression including cell proliferation, adhesion, migration, invasion, metastasis, immune response and angiogenesis. These new protein candidates may provide essential information for the development of protein diagnostics and targeted therapies. We further argue that new strategies must be advanced and established for the integration of proteomic, transcriptomic and genomic data, in order to enhance biomarker translation. Large scale studies with meta data processing will pave the way for novel and unexpected correlations within pancreatic cancer, that will benefit the patient, with targeted treatment.

Proteomic approaches and identification of novel therapeutic targets for alcoholism

Recent studies have shown that gene regulation is far more complex than previously believed and does not completely explain changes at the protein level. Therefore, the direct study of the proteome, considerably different in both complexity and dynamicity to the genome/transcriptome, has provided unique insights to an increasing number of researchers. During the past decade, extraordinary advances in proteomic techniques have changed the way we can analyze the composition, regulation, and function of protein complexes and pathways underlying altered neurobiological conditions. When combined with complementary approaches, these advances provide the contextual information for decoding large data sets into meaningful biologically adaptive processes. Neuroproteomics offers potential breakthroughs in the field of alcohol research by leading to a deeper understanding of how alcohol globally affects protein structure, function, interactions, and networks. The wealth of information gained from these advances can help pinpoint relevant biomarkers for early diagnosis and improved prognosis of alcoholism and identify future pharmacological targets for the treatment of this addiction.

Targeted quantitation of proteins by mass spectrometry

Quantitative measurement of proteins is one of the most fundamental analytical tasks in a biochemistry laboratory, but widely used immunochemical methods often have limited specificity and high measurement variation. In this review, we discuss applications of multiple-reaction monitoring (MRM) mass spectrometry, which allows sensitive, precise quantitative analyses of peptides and the proteins from which they are derived. Systematic development of MRM assays is permitted by databases of peptide mass spectra and sequences, software tools for analysis design and data analysis, and rapid evolution of tandem mass spectrometer technology. Key advantages of MRM assays are the ability to target specific peptide sequences, including variants and modified forms, and the capacity for multiplexing that allows analysis of dozens to hundreds of peptides. Different quantitative standardization methods provide options that balance precision, sensitivity, and assay cost. Targeted protein quantitation by MRM and related mass spectrometry methods can advance biochemistry by transforming approaches to protein measurement.

Extensive mass spectrometry-based analysis of the fission yeast proteome: the Schizosaccharomyces pombe PeptideAtlas

We report a high quality and system-wide proteome catalogue covering 71% (3,542 proteins) of the predicted genes of fission yeast, Schizosaccharomyces pombe, presenting the largest protein dataset to date for this important model organism. We obtained this high proteome and peptide (11.4 peptides/protein) coverage by a combination of extensive sample fractionation, high resolution Orbitrap mass spectrometry, and combined database searching using the iProphet software as part of the Trans-Proteomics Pipeline. All raw and processed data are made accessible in the S. pombe PeptideAtlas. The identified proteins showed no biases in functional properties and allowed global estimation of protein abundances. The high coverage of the PeptideAtlas allowed correlation with transcriptomic data in a system-wide manner indicating that post-transcriptional processes control the levels of at least half of all identified proteins. Interestingly, the correlation was not equally tight for all functional categories ranging from r(s) >0.80 for proteins involved in translation to r(s) <0.45 for signal transduction proteins. Moreover, many proteins involved in DNA damage repair could not be detected in the PeptideAtlas despite their high mRNA levels, strengthening the translation-on-demand hypothesis for members of this protein class. In summary, the extensive and publicly available S. pombe PeptideAtlas together with the generated proteotypic peptide spectral library will be a useful resource for future targeted, in-depth, and quantitative proteomic studies on this microorganism.

Kinetics of antigen expression and epitope presentation during virus infection

Current knowledge about the dynamics of antigen presentation to T cells during viral infection is very poor despite being of fundamental importance to our understanding of anti-viral immunity. Here we use an advanced mass spectrometry method to simultaneously quantify the presentation of eight vaccinia virus peptide-MHC complexes (epitopes) on infected cells and the amounts of their source antigens at multiple times after infection. The results show a startling 1000-fold range in abundance as well as strikingly different kinetics across the epitopes monitored. The tight correlation between onset of protein expression and epitope display for most antigens provides the strongest support to date that antigen presentation is largely linked to translation and not later degradation of antigens. Finally, we show a complete disconnect between the epitope abundance and immunodominance hierarchy of these eight epitopes. This study highlights the complexity of viral antigen presentation by the host and demonstrates the weakness of simple models that assume total protein levels are directly linked to epitope presentation and immunogenicity.

A major mechanism for the detection of virus infection is the recognition by T cells of short peptide fragments (epitopes) derived from the degradation of intracellular proteins presented at the cell surface in a complex with class I MHC. Whilst the mechanics of antigen degradation and the loading of peptides onto MHC are now well understood, the kinetics of epitope presentation have only been studied for individual model antigens. We addressed this issue by studying vaccinia virus, best known as the smallpox vaccine, using advanced mass spectrometry. Precise and simultaneous quantification of multiple peptide-MHC complexes showed that the surface of infected cells provides a surprisingly dynamic landscape from the point of view of anti-viral T cells. Further, concurrent measurement of virus protein levels demonstrated that in most cases, peak presentation of epitopes occurs at the same time or precedes the time of maximum protein build up. Finally, we found a complete disconnect between the abundance of epitopes on infected cells and the size of the responding T cell populations. These data provide new insights into how virus infected cells are seen by T cells, which is crucial to our understanding of anti-viral immunity and development of vaccines.

Proteomics for understanding miRNA biology

MicroRNAs (miRNAs) are small noncoding RNAs that play important roles in posttranscriptional regulation of gene expression. Mature miRNAs associate with the RNA interference silencing complex to repress mRNA translation and/or degrade mRNA transcripts. Mass spectrometry-based proteomics has enabled identification of several core components of the canonical miRNA processing pathway and their posttranslational modifications which are pivotal in miRNA regulatory mechanisms. The use of quantitative proteomic strategies has also emerged as a key technique for experimental identification of miRNA targets by allowing direct determination of proteins whose levels are altered because of translational suppression. This review focuses on the role of proteomics and labeling strategies to understand miRNA biology.

The use of selected reaction monitoring in quantitative proteomics

Selected reaction monitoring (SRM) has a long history of use in the area of quantitative MS. In recent years, the approach has seen increased application to quantitative proteomics, facilitating multiplexed relative and absolute quantification studies in a variety of organisms. This article discusses SRM, after introducing the context of quantitative proteomics (specifically primarily absolute quantification) where it finds most application, and considers topics such as the theory and advantages of SRM, the selection of peptide surrogates for protein quantification, the design of optimal SRM co-ordinates and the handling of SRM data. A number of published studies are also discussed to demonstrate the impact that SRM has had on the field of quantitative proteomics.

Interlaboratory reproducibility of selective reaction monitoring assays using multiple upfront analyte enrichment strategies

Over the past few years, mass spectrometry has emerged as a technology to complement and potentially replace standard immunoassays in routine clinical core laboratories. Application of mass spectrometry to protein and peptide measurement can provide advantages including high sensitivity, the ability to multiplex analytes, and high specificity at the amino acid sequence level. In our previous study, we demonstrated excellent reproducibility of mass spectrometry-selective reaction monitoring (MS-SRM) assays when applying standardized standard operating procedures (SOPs) to measure synthetic peptides in a complex sample, as lack of reproducibility has been a frequent criticism leveled at the use of mass spectrometers in the clinical laboratory compared to immunoassays. Furthermore, an important caveat of SRM-based assays for proteins is that many low-abundance analytes require some type of enrichment before detection with MS. This adds a level of complexity to the procedure and the potential for irreproducibility increases, especially across different laboratories with different operators. The purpose of this study was to test the interlaboratory reproducibility of SRM assays with various upfront enrichment strategies and different types of clinical samples (representing real-world body fluids commonly encountered in routine clinical laboratories). Three different, previously published enrichment strategies for low-abundance analytes and a no-enrichment strategy for high-abundance analytes were tested across four different laboratories using different liquid chromatography-SRM (LC-SRM) platforms and previously developed SOPs. The results demonstrated that these assays were indeed reproducible with coefficients of variation of less than 30% for the measurement of important clinical proteins across all four laboratories in real world samples.

Selected reaction monitoring-based proteomics: workflows, potential, pitfalls and future directions

Selected reaction monitoring (SRM) is a targeted mass spectrometry technique that is emerging in the field of proteomics as a complement to untargeted shotgun methods. SRM is particularly useful when predetermined sets of proteins, such as those constituting cellular networks or sets of candidate biomarkers, need to be measured across multiple samples in a consistent, reproducible and quantitatively precise manner. Here we describe how SRM is applied in proteomics, review recent advances, present selected applications and provide a perspective on the future of this powerful technology.

Current challenges in detecting food allergens by shotgun and targeted proteomic approaches: a case study on traces of peanut allergens in baked cookies

There is a need for selective and sensitive methods to detect the presence of food allergens at trace levels in highly processed food products. In this work, a combination of non-targeted and targeted proteomics approaches are used to illustrate the difficulties encountered in the detection of the major peanut allergens Ara h 1, Ara h 2 and Ara h 3 from a representative processed food matrix. Shotgun proteomics was employed for selection of the proteotypic peptides for targeted approaches via selective reaction monitoring. Peanut presence through detection of the proteotypic Ara h 3/4 peptides AHVQVVDSNGNR (m/z 432.5, 3+) and SPDIYNPQAGSLK (m/z 695.4, 2+) was confirmed and the developed method was able to detect peanut presence at trace levels (≥10 μg peanut g(-1) matrix) in baked cookies.

Multiplexed quantification of 63 proteins in human urine by multiple reaction monitoring-based mass spectrometry for discovery of potential bladder cancer biomarkers

Three common urological diseases are bladder cancer, urinary tract infection, and hematuria. Seventeen bladder cancer biomarkers were previously discovered using iTRAQ - these findings were verified by MRM-MS in this current study. Urine samples from 156 patients with hernia (n=57, control), bladder cancer (n=76), or urinary tract infection/hematuria (n=23) were collected and subjected to multiplexed LC-MRM/MS to determine the concentrations of 63 proteins that are normally considered to be plasma proteins, but which include proteins found in our earlier iTRAQ study. Sixty-five stable isotope-labeled standard proteotypic peptides were used as internal standards for 63 targeted proteins. Twelve proteins showed higher concentrations in the bladder cancer group than in the hernia and the urinary tract infection/hematuria groups, and thus represent potential urinary biomarkers for detection of bladder cancer. Prothrombin had the highest AUC (0.796), with 71.1% sensitivity and 75.0% specificity for differentiating bladder cancer (n=76) from non-cancerous (n=80) patients. The multiplexed MRM-MS data was used to generate a six-peptide marker panel. This six-peptide panel (afamin, adiponectin, complement C4 gamma chain, apolipoprotein A-II precursor, ceruloplasmin, and prothrombin) can discriminate bladder cancer subjects from non-cancerous subjects with an AUC of 0.814, with a 76.3% positive predictive value, and a 77.5% negative predictive value. This article is part of a Special Section entitled: Understanding genome regulation and genetic diversity by mass spectrometry.

Biomarker validation in blood specimens by selected reaction monitoring mass spectrometry of N-glycosites

Targeted mass spectrometry using selected reaction monitoring (SRM) has emerged as the method of choice for the validation in blood serum, plasma, or other clinically relevant specimens of biomarker candidates arising from comparative proteomics or other discovery strategies. Here, we describe a method in which N-glycosites are selectively enriched from biological specimens by solid phase capture and PNGase F release, and then analyzed by SRM. Focusing the highly sensitive targeted mass spectrometry method on a subproteome enriched for secreted and shed proteins reproducibly identifies and quantifies such proteins in serum and plasma at the low nanogram per milliliter (ng/mL) concentration range. This protocol is intended to give an introduction to SRM-based targeted mass spectrometry with a special focus on the validation of biomarker candidates.

Effect of collision energy optimization on the measurement of peptides by selected reaction monitoring (SRM) mass spectrometry

Proteomics experiments based on Selected Reaction Monitoring (SRM, also referred to as Multiple Reaction Monitoring or MRM) are being used to target large numbers of protein candidates in complex mixtures. At present, instrument parameters are often optimized for each peptide, a time and resource intensive process. Large SRM experiments are greatly facilitated by having the ability to predict MS instrument parameters that work well with the broad diversity of peptides they target. For this reason, we investigated the impact of using simple linear equations to predict the collision energy (CE) on peptide signal intensity and compared it with the empirical optimization of the CE for each peptide and transition individually. Using optimized linear equations, the difference between predicted and empirically derived CE values was found to be an average gain of only 7.8% of total peak area. We also found that existing commonly used linear equations fall short of their potential, and should be recalculated for each charge state and when introducing new instrument platforms. We provide a fully automated pipeline for calculating these equations and individually optimizing CE of each transition on SRM instruments from Agilent, Applied Biosystems, Thermo-Scientific and Waters in the open source Skyline software tool ( http://proteome.gs.washington.edu/software/skyline ).