Technical considerations for large-scale parallel reaction monitoring analysis

Applicability of selected reaction monitoring for precise screening tests

INTRODUCTION

The proactive identification of diseases through screening tests has long been endorsed as a means to preempt symptomatic onset. However, such screening endeavors are fraught with complications, such as diagnostic inaccuracies, procedural risks, and patient unease during examinations. These challenges are amplified when screenings for multiple diseases are administered concurrently. Selected Reaction Monitoring (SRM) offers a unique advantage, allowing for the high-throughput quantification of hundreds of analytes with minimal interferences.

AREAS COVERED

Our research posits that SRM-based assays, traditionally tailored for single-disease biomarker profiling, can be repurposed for multi-disease screening. This innovative approach has the potential to substantially alleviate time, labor, and cost demands on healthcare systems and patients alike. Nonetheless, there are formidable methodological hurdles to overcome. These include difficulties in detecting low-abundance proteins and the risk of model overfitting due to the multiple functionalities of single proteins across different disease spectrums - issues especially pertinent in blood-based assays where detection sensitivity is constrained. As we move forward, technological strides in sample preparation, online extraction, throughput, and automation are expected to ameliorate these limitations.

EXPERT OPINION

The maturation of mass spectrometry's integration into clinical laboratories appears imminent, positioning it as an invaluable asset for delivering highly sensitive, reproducible, and precise diagnostic results.

Differential expression of N-glycopeptides derived from serum glycoproteins in mild cognitive impairment (MCI) patients

Mild cognitive impairment (MCI) is an early stage of memory loss that affects cognitive abilities with the aging of individuals, such as language or visual/spatial comprehension. MCI is considered a prodromal phase of more complicated neurodegenerative diseases such as Alzheimer's. Therefore, accurate diagnosis and better understanding of the disease prognosis will facilitate prevention of neurodegeneration. However, the existing diagnostic methods fail to provide precise and well-timed diagnoses, and the pathophysiology of MCI is not fully understood. Alterations of the serum N-glycoproteome expression could represent an essential contributor to the overall pathophysiology of neurodegenerative diseases and be used as a potential marker to assess MCI diagnosis using less invasive procedures. In this approach, we identified N-glycopeptides with different expressions between healthy and MCI patients from serum glycoproteins. Seven of the N-glycopeptides showed outstanding AUC values, among them the antithrombin-III Asn224 + 4-5-0-2 with an AUC value of 1.00 and a p value of 0.0004. According to proteomics and ingenuity pathway analysis (IPA), our data is in line with recent publications, and the glycoproteins carrying the identified N-sites play an important role in neurodegeneration.

Phosphoproteomics changes due to allograft-induced stress responses of Pinctada fucata martensii

Protein phosphorylation modifications are post-translational modifications (PTMs) that play important roles in signal transduction and immune regulation. Implanting a spherical nucleus into a recipient shellfish is critical in marine pearl aquaculture. Protein phosphorylation may be important in the immune responses of Pinctada fucata martensii after nucleus implantation, but their involvement in regulation remains unclear. Here, phosphoproteomics of P. f. martensii gill tissues was conducted 12 h after nuclear implantation using label-free data-independent acquisition (DIA) with LC-MS/MS. Among the 4024 phosphorylated peptides with quantitative information, 181 were up-regulated and 148 were down-regulated. Functional enrichment analysis of these differentially expressed phosphorylated proteins (DEPPs) revealed significant enrichment in functions related to membrane trafficking, exosomes, cytoskeleton, and signal transduction mechanisms. Further, 16 conserved motifs were identified among the DEPPs, including the RSphP, SphP, RSphA, RSphE, PTphP, and ATphP motifs that were significantly conserved, and which may be related to specific kinase recognition. Parallel response monitoring (PRM) analysis validated the abundances of 12 DEPPs from the proteomics, indicating that the phosphoproteomics analyses were robust. 12 DEPPs were selected from the proteomics results through Quantitative real-time PCR (qPCR) technology, and verification analysis was conducted at the gene level. The study suggests that kinases such as MAPKs, Akt, and CK2 may regulate the phosphorylation of related proteins following nuclear implantation. Furthermore, the important signaling pathways of Rap 1, IL-17A, and NF-κB, which are influenced by phosphorylated or dephosphorylated proteins, are found to be involved in this response. Overall, this study revealed the protein phosphorylation responses after nucleus implantation in P. f. martensii, helping to elucidate the characteristics and mechanisms of immune regulation responses in P. f. martensii, in addition to promoting a further understanding of protein phosphorylation modification functions in P. f. martensii.

Quantification of putative ovarian cancer serum protein biomarkers using a multiplexed targeted mass spectrometry assay

BACKGROUND

Ovarian cancer is the most lethal gynecologic malignancy in women, and high-grade serous ovarian cancer (HGSOC) is the most common subtype. Currently, no clinical test has been approved by the FDA to screen the general population for ovarian cancer. This underscores the critical need for the development of a robust methodology combined with novel technology to detect diagnostic biomarkers for HGSOC in the sera of women. Targeted mass spectrometry (MS) can be used to identify and quantify specific peptides/proteins in complex biological samples with high accuracy, sensitivity, and reproducibility. In this study, we sought to develop and conduct analytical validation of a multiplexed Tier 2 targeted MS parallel reaction monitoring (PRM) assay for the relative quantification of 23 putative ovarian cancer protein biomarkers in sera.

METHODS

To develop a PRM method for our target peptides in sera, we followed nationally recognized consensus guidelines for validating fit-for-purpose Tier 2 targeted MS assays. The endogenous target peptide concentrations were calculated using the calibration curves in serum for each target peptide. Receiver operating characteristic (ROC) curves were analyzed to evaluate the diagnostic performance of the biomarker candidates.

RESULTS

We describe an effort to develop and analytically validate a multiplexed Tier 2 targeted PRM MS assay to quantify candidate ovarian cancer protein biomarkers in sera. Among the 64 peptides corresponding to 23 proteins in our PRM assay, 24 peptides corresponding to 16 proteins passed the assay validation acceptability criteria. A total of 6 of these peptides from insulin-like growth factor-binding protein 2 (IBP2), sex hormone-binding globulin (SHBG), and TIMP metalloproteinase inhibitor 1 (TIMP1) were quantified in sera from a cohort of 69 patients with early-stage HGSOC, late-stage HGSOC, benign ovarian conditions, and healthy (non-cancer) controls. Confirming the results from previously published studies using orthogonal analytical approaches, IBP2 was identified as a diagnostic biomarker candidate based on its significantly increased abundance in the late-stage HGSOC patient sera compared to the healthy controls and patients with benign ovarian conditions.

CONCLUSIONS

A multiplexed targeted PRM MS assay was applied to detect candidate diagnostic biomarkers in HGSOC sera. To evaluate the clinical utility of the IBP2 PRM assay for HGSOC detection, further studies need to be performed using a larger patient cohort.

Targeted Proteomic Quantitation of NRF2 Signaling and Predictive Biomarkers in HNSCC

The NFE2L2 (NRF2) oncogene and transcription factor drives a gene expression program that promotes cancer progression, metabolic reprogramming, immune evasion, and chemoradiation resistance. Patient stratification by NRF2 activity may guide treatment decisions to improve outcome. Here, we developed a mass spectrometry-based targeted proteomics assay based on internal standard-triggered parallel reaction monitoring to quantify 69 NRF2 pathway components and targets, as well as 21 proteins of broad clinical significance in head and neck squamous cell carcinoma (HNSCC). We improved an existing internal standard-triggered parallel reaction monitoring acquisition algorithm, called SureQuant, to increase throughput, sensitivity, and precision. Testing the optimized platform on 27 lung and upper aerodigestive cancer cell models revealed 35 NRF2 responsive proteins. In formalin-fixed paraffin-embedded HNSCCs, NRF2 signaling intensity positively correlated with NRF2-activating mutations and with SOX2 protein expression. Protein markers of T-cell infiltration correlated positively with one another and with human papilloma virus infection status. CDKN2A (p16) protein expression positively correlated with the human papilloma virus oncogenic E7 protein and confirmed the presence of translationally active virus. This work establishes a clinically actionable HNSCC protein biomarker assay capable of quantifying over 600 peptides from frozen or formalin-fixed paraffin-embedded archived tissues in under 90 min.

Mass spectrometry-based retina proteomics

A subfield of neuroproteomics, retina proteomics has experienced a transformative growth since its inception due to methodological advances in enabling chemical, biochemical, and molecular biology techniques. This review focuses on mass spectrometry's contributions to facilitate mammalian and avian retina proteomics to catalog and quantify retinal protein expressions, determine their posttranslational modifications, as well as its applications to study the proteome of the retina in the context of biology, health and diseases, and therapy developments.

Sample Preparation Methods for Targeted Single-Cell Proteomics

We compared three cell isolation and two proteomic sample preparation methods for single-cell and near-single-cell analysis. Whole blood was used to quantify hemoglobin (Hb) and glycated-Hb (gly-Hb) in erythrocytes using targeted mass spectrometry and stable isotope-labeled standard peptides. Each method differed in cell isolation and sample preparation as follows: 1) FACS and automated preparation in one-pot for trace samples (autoPOTS); 2) limited dilution via microscopy and a novel rapid one-pot sample preparation method that circumvented the need for the solid-phase extraction, low-volume liquid handling instrumentation and humidified incubation chamber; and 3) CellenONE-based cell isolation and the same one-pot sample preparation method used for limited dilution. Only the CellenONE device routinely isolated single-cells from which Hb was measured to be 540-660 amol per red blood cell (RBC), which was comparable to the calculated SI reference range for mean corpuscular hemoglobin (390-540 amol/RBC). FACSAria sorter and limited dilution could routinely isolate single-digit cell numbers, to reliably quantify CMV-Hb heterogeneity. Finally, we observed that repeated measures, using 5-25 RBCs obtained from N = 10 blood donors, could be used as an alternative and more efficient strategy than single RBC analysis to measure protein heterogeneity, which revealed multimodal distribution, unique for each individual.

Analysis of Golgi Protein Acetylation Using In Vitro Assays and Parallel Reaction Monitoring Mass Spectrometry

Acetylation is one of the most abundant post-translational protein modifications that regulates all cellular compartments ranging from chromatin to cytoskeleton and Golgi. The dynamic acetylation of the Golgi stacking protein GRASP55 was shown to regulate Golgi reassembly after mitosis. Here we provide a detailed protocol for the analysis of Golgi acetylation including in vitro assays to detect protein acetylation and mass spectrometry analysis to identify specific acetylation sites and their relative abundance.

Quantitative proteomics identified circulating biomarkers in lung adenocarcinoma diagnosis

BACKGROUND

Lung cancer (LC) is a common malignant tumor with a high incidence and poor prognosis. Early LC could be cured, but the 5-year-survival rate for patients advanced is extremely low. Early screening of tumor biomarkers through plasma could allow more LC to be detected at an early stage, leading to a earlier treatment and a better prognosis.

METHODS

This study was based on total proteomic analysis and parallel reaction monitoring validation of peripheral blood from 20 lung adenocarcinoma patients and 20 healthy individuals. Furthermore, differentially expressed proteins closely related to prognosis were analysed using Kaplan-Meier Plotter and receiver operating characteristic curve (ROC) curve analysis.

RESULTS

The candidate proteins GAPDH and RAC1 showed the highest connectivity with other differentially expressed proteins between the lung adenocarcinoma group and the healthy group using STRING. Kaplan-Meier Plotter analysis showed that lung adenocarcinoma patients with positive ATCR2, FHL1, RAB27B, and RAP1B expression had observably longer overall survival than patients with negative expression (P < 0.05). The high expression of ARPC2, PFKP, PNP, RAC1 was observably negatively correlated with prognosis (P < 0.05). 17 out of 27 proteins showed a high area under the curve (> 0.80) between the lung adenocarcinoma and healthy plasma groups. Among those proteins, UQCRC1 had an area under the curve of 0.960, and 5 proteins had an area under the curve from 0.90 to 0.95, suggesting that these hub proteins might have discriminatory potential in lung adenocarcinoma, P < 0.05.

CONCLUSIONS

These findings provide UQCRC1, GAPDH, RAC1, PFKP have potential as novel biomarkers for the early screening of lung adenocarcinoma.

The addition of FAIMS increases targeted proteomics sensitivity from FFPE tumor biopsies

Mass spectrometry-based targeted proteomics allows objective protein quantitation of clinical biomarkers from a single section of formalin-fixed, paraffin-embedded (FFPE) tumor tissue biopsies. We combined high-field asymmetric waveform ion mobility spectrometry (FAIMS) and parallel reaction monitoring (PRM) to increase assay sensitivity. The modular nature of the FAIMS source allowed direct comparison of the performance of FAIMS-PRM to PRM. Limits of quantitation were determined by spiking synthetic peptides into a human spleen matrix. In addition, 20 clinical samples were analyzed using FAIMS-PRM and the quantitation of HER2 was compared with that obtained with the Ventana immunohistochemistry assay. FAIMS-PRM improved the overall signal-to-noise ratio over that from PRM and increased assay sensitivity in FFPE tissue analysis for four (HER2, EGFR, cMET, and KRAS) of five proteins of clinical interest. FAIMS-PRM enabled sensitive quantitation of basal HER2 expression in breast cancer samples classified as HER2 negative by immunohistochemistry. Furthermore, we determined the degree of FAIMS-dependent background reduction and showed that this correlated with an improved lower limit of quantitation with FAIMS. FAIMS-PRM is anticipated to benefit clinical trials in which multiple biomarker questions must be addressed and the availability of tumor biopsy samples is limited.

Internal Standard Triggered-Parallel Reaction Monitoring Mass Spectrometry Enables Multiplexed Quantification of Candidate Biomarkers in Plasma

Despite advances in proteomic technologies, clinical translation of plasma biomarkers remains low, partly due to a major bottleneck between the discovery of candidate biomarkers and costly clinical validation studies. Due to a dearth of multiplexable assays, generally only a few candidate biomarkers are tested, and the validation success rate is accordingly low. Previously, mass spectrometry-based approaches have been used to fill this gap but feature poor quantitative performance and were generally limited to hundreds of proteins. Here, we demonstrate the capability of an internal standard triggered-parallel reaction monitoring (IS-PRM) assay to greatly expand the numbers of candidates that can be tested with improved quantitative performance. The assay couples immunodepletion and fractionation with IS-PRM and was developed and implemented in human plasma to quantify 5176 peptides representing 1314 breast cancer biomarker candidates. Characterization of the IS-PRM assay demonstrated the precision (median % CV of 7.7%), linearity (median R² > 0.999 over 4 orders of magnitude), and sensitivity (median LLOQ < 1 fmol, approximately) to enable rank-ordering of candidate biomarkers for validation studies. Using three plasma pools from breast cancer patients and three control pools, 893 proteins were quantified, of which 162 candidate biomarkers were verified in at least one of the cancer pools and 22 were verified in all three cancer pools. The assay greatly expands capabilities for quantification of large numbers of proteins and is well suited for prioritization of viable candidate biomarkers.

Application of Parallel Reaction Monitoring in 15N Labeled Samples for Quantification

Accurate relative quantification is critical in proteomic studies. The incorporation of stable isotope ¹⁵N to plant-expressed proteins in vivo is a powerful tool for accurate quantification with a major advantage of reducing preparative and analytical variabilities. However, ¹⁵N labeling quantification has several challenges. Less identifications are often observed in the heavy-labeled samples because of incomplete labeling, resulting in missing values in reciprocal labeling experiments. Inaccurate quantification can happen when there is contamination from co-eluting peptides or chemical noise in the MS¹ survey scan. These drawbacks in quantification can be more pronounced in less abundant but biologically interesting proteins, which often have very few identified peptides. Here, we demonstrate the application of parallel reaction monitoring (PRM) to ¹⁵N labeled samples on a high resolution, high mass accuracy Orbitrap mass spectrometer to achieve reliable quantification even of low abundance proteins in samples.

Proteomics in thrombosis research

A State of the Art lecture titled “Proteomics in Thrombosis Research” was presented at the ISTH Congress in 2021. In clinical practice, there is a need for improved plasma biomarker‐based tools for diagnosis and risk prediction of venous thromboembolism (VTE). Analysis of blood, to identify plasma proteins with potential utility for such tools, could enable an individualized approach to treatment and prevention. Technological advances to study the plasma proteome on a large scale allows broad screening for the identification of novel plasma biomarkers, both by targeted and nontargeted proteomics methods. However, assay limitations need to be considered when interpreting results, with orthogonal validation required before conclusions are drawn. Here, we review and provide perspectives on the application of affinity‐ and mass spectrometry‐based methods for the identification and analysis of plasma protein biomarkers, with potential application in the field of VTE. We also provide a future perspective on discovery strategies and emerging technologies for targeted proteomics in thrombosis research. Finally, we summarize relevant new data on this topic, presented during the 2021 ISTH Congress.

Modern Data Acquisition Approaches in Proteomics Based on Dynamic Instrument Control

Traditionally, data acquisition in mass spectrometry-based proteomics is directed by user-defined parameters and relatively simple decision making, such as selection of the highest MS1 peaks for fragmentation. In recent years, access to two-way-communication with instrument codebases has led to a surge in algorithms instructing more complex decision processes on-the-fly. A closer matching between the time windows for monitoring peptides in targeted proteomics and their actual chromatographic elution peaks has been addressed through dynamic retention time scheduling and through triggered acquisition. Strategies based on real-time database searching and spectral matching have, among others, been used to adjust acquisition parameters for selected peptides for improved quantitative accuracy. While initial studies were mainly performed on a proof-of-concept level, dynamic acquisition approaches recently became more broadly available through software and increasing integration into standard instrument control and are likely to transform the field of proteomics in the coming years.

Multiplex Detection of 24 Staphylococcal Enterotoxins in Culture Supernatant Using Liquid Chromatography Coupled to High-Resolution Mass Spectrometry

Staphylococcal food poisoning outbreaks are caused by the ingestion of food contaminated with staphylococcal enterotoxins (SEs). Among the 27 SEs described in the literature to date, only a few can be detected using immuno-enzymatic-based methods that are strongly dependent on the availability of antibodies. Liquid chromatography, coupled to high-resolution mass spectrometry (LC-HRMS), has, therefore, been put forward as a relevant complementary method, but only for the detection of a limited number of enterotoxins. In this work, LC-HRMS was developed for the detection and quantification of 24 SEs. A database of 93 specific signature peptides and LC-HRMS parameters was optimized using sequences from 24 SEs, including their 162 variants. A label-free quantification protocol was established to overcome the absence of calibration standards. The LC-HRMS method showed high performance in terms of specificity, sensitivity, and accuracy when applied to 49 enterotoxin-producing strains. SE concentrations measured depended on both SE type and the coagulase-positive staphylococci (CPS) strain. This study indicates that LC-MS is a relevant alternative and complementary tool to ELISA methods. The advantages of LC-MS clearly lie in both the multiplex analysis of a large number of SEs, and the automated analysis of a high number of samples.

Global Quantification of Glutathione S-Transferases in Human Serum Using LC-MS/MS Coupled with Affinity Enrichment

The members of the glutathione S-transferase (GST) superfamily often exhibit functional overlap and can compensate for each other. Their concentrations in serum are considered as disease biomarkers. A global and quantitative evaluation of serum GSTs is therefore urgent, but there is a lack of efficient approaches due to technological limitations. GSH magnetic beads were examined for their affinity to enrich GSTs in serum, and the enriched GSTs were quantitatively targeted using a Q Exactive HF-X mass spectrometer in parallel reaction monitoring (PRM) mode. To optimize the quantification of GST peptides, sample types, trypsin digestion, and serum loading were carefully assessed; a biosynthetic method was employed to generate isotope-labeled GST peptides, and instrumental parameters were systematically optimized. A total of 134 clinical sera were collected for GST quantification from healthy donors and patients with four liver diseases. Using the new approach, GSTs in healthy sera were profiled: 14 GST peptides were quantified, and the abundance of five GST families was ranked GSTM > GSTP > GSTA > MGST1 > GSTT1, ranging from 0.1 to 4 pmol/L. Furthermore, combining the abundance of multiple GST peptides could effectively distinguish different types of liver diseases. Quantification of serum GSTs through targeted proteomics, therefore, has apparent clinical potential for disease diagnosis.

Kynurenine Pathway Metabolites as Potential Clinical Biomarkers in Coronary Artery Disease

Coronary artery disease (CAD) is one of the leading cause of mortality worldwide. Several risk factors including unhealthy lifestyle, genetic background, obesity, diabetes, hypercholesterolemia, hypertension, smoking, age, etc. contribute to the development of coronary atherosclerosis and subsequent coronary artery disease. Inflammation plays an important role in coronary artery disease development and progression. Pro-inflammatory signals promote the degradation of tryptophan via the kynurenine pathway resulting in the formation of several immunomodulatory metabolites. An unbalanced kynurenic pathway has been implicated in the pathomechanisms of various diseases including CAD. Significant improvements in detection methods in the last decades may allow simultaneous measurement of multiple metabolites of the kynurenine pathway and such a thorough analysis of the kynurenine pathway may be a valuable tool for risk stratification and determination of CAD prognosis. Nevertheless, imbalance in the activities of different branches of the kynurenine pathway may require careful interpretation. In this review, we aim to summarize clinical evidence supporting a possible use of kynurenine pathway metabolites as clinical biomarkers in various manifestations of CAD.

Pan-cancer quantitation of epithelial-mesenchymal transition dynamics using parallel reaction monitoring-based targeted proteomics approach

Epithelial–mesenchymal transition (EMT) is a dynamic and complex cellular process that is known to be hijacked by cancer cells to facilitate invasion, metastasis and therapeutic resistance. Several quantitative measures to assess the interplay between EMT and cancer progression are available, based on large scale genome and transcriptome data. However, these large scale multi-omics studies have repeatedly illustrated a lack of correlation in mRNA and protein abundances that may be influenced by diverse post-translational regulation. Hence, it is imperative to understand how changes in the EMT proteome are associated with the process of oncogenic transformation. To this effect, we developed a parallel reaction monitoring-based targeted proteomics method for quantifying abundances of EMT-associated proteins across cancer cell lines. Our study revealed that quantitative measurement of EMT proteome which enabled a more accurate assessment than transcriptomics data and revealed specific discrepancies against a backdrop of generally strong concordance between proteomic and transcriptomic data. We further demonstrated that changes in our EMT proteome panel might play a role in tumor transformation across cancer types. In future, this EMT panel assay has the potential to be used for clinical samples to guide treatment choices and to congregate functional information for the development and advancing novel therapeutics.

Dynamic diel proteome and daytime nitrogenase activity supports buoyancy in the cyanobacterium Trichodesmium

Cyanobacteria of the genus Trichodesmium provide about 80 Tg of fixed nitrogen to the surface ocean per year and contribute to marine biogeochemistry, including the sequestration of carbon dioxide. Trichodesmium fixes nitrogen in the daylight, despite the incompatibility of the nitrogenase enzyme with oxygen produced during photosynthesis. While the mechanisms protecting nitrogenase remain unclear, all proposed strategies require considerable resource investment. Here we identify a crucial benefit of daytime nitrogen fixation in Trichodesmium spp. that may counteract these costs. We analysed diel proteomes of cultured and field populations of Trichodesmium in comparison with the marine diazotroph Crocosphaera watsonii WH8501, which fixes nitrogen at night. Trichodesmium's proteome is extraordinarily dynamic and demonstrates simultaneous photosynthesis and nitrogen fixation, resulting in balanced particulate organic carbon and particulate organic nitrogen production. Unlike Crocosphaera, which produces large quantities of glycogen as an energy store for nitrogenase, proteomic evidence is consistent with the idea that Trichodesmium reduces the need to produce glycogen by supplying energy directly to nitrogenase via soluble ferredoxin charged by the photosynthesis protein PsaC. This minimizes ballast associated with glycogen, reducing cell density and decreasing sinking velocity, thus supporting Trichodesmium's niche as a buoyant, high-light-adapted colony forming cyanobacterium. To occupy its niche of simultaneous nitrogen fixation and photosynthesis, Trichodesmium appears to be a conspicuous consumer of iron, and has therefore developed unique iron-acquisition strategies, including the use of iron-rich dust. Particle capture by buoyant Trichodesmium colonies may increase the residence time and degradation of mineral iron in the euphotic zone. These findings describe how cellular biochemistry defines and reinforces the ecological and biogeochemical function of these keystone marine diazotrophs.

BATL: Bayesian annotations for targeted lipidomics

MOTIVATION

Bioinformatic tools capable of annotating, rapidly and reproducibly, large, targeted lipidomic datasets are limited. Specifically, few programs enable high-throughput peak assessment of liquid chromatography-electrospray ionization tandem mass spectrometry data acquired in either selected or multiple reaction monitoring modes.

RESULTS

We present here Bayesian Annotations for Targeted Lipidomics, a Gaussian naïve Bayes classifier for targeted lipidomics that annotates peak identities according to eight features related to retention time, intensity, and peak shape. Lipid identification is achieved by modeling distributions of these eight input features across biological conditions and maximizing the joint posterior probabilities of all peak identities at a given transition. When applied to sphingolipid and glycerophosphocholine selected reaction monitoring datasets, we demonstrate over 95% of all peaks are rapidly and correctly identified.

AVAILABILITY AND IMPLEMENTATION

BATL software is freely accessible online at https://complimet.ca/batl/ and is compatible with Safari, Firefox, Chrome and Edge.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

An Introduction to Advanced Targeted Acquisition Methods

Targeted proteomics via selected reaction monitoring (SRM) or parallel reaction monitoring (PRM) enables fast and sensitive detection of a preselected set of target peptides. However, the number of peptides that can be monitored in conventional targeting methods is usually rather small. Recently, a series of methods has been described that employ intelligent acquisition strategies to increase the efficiency of mass spectrometers to detect target peptides. These methods are based on one of two strategies. First, retention time adjustment-based methods enable intelligent scheduling of target peptide retention times. These include Picky, iRT, as well as spike-in free real-time adjustment methods such as MaxQuant.Live. Second, in spike-in triggered acquisition methods such as SureQuant, Pseudo-PRM, TOMAHAQ, and Scout-MRM, targeted scans are initiated by abundant labeled synthetic peptides added to samples before the run. Both strategies enable the mass spectrometer to better focus data acquisition time on target peptides. This either enables more sensitive detection or a higher number of targets per run. Here, we provide an overview of available advanced targeting methods and highlight their intrinsic strengths and weaknesses and compatibility with specific experimental setups. Our goal is to provide a basic introduction to advanced targeting methods for people starting to work in this field.

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Advanced acquisition methods improve focus of mass spectrometers on target peptides.

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This review discusses existing methods based on two strategies.

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Retention time adjustment-based methods enable intelligent scheduling of peptide RTs.

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In spike-in triggered acquisition methods targeted scans are initiated by spike-ins.

Global Extraction from Parallel Reaction Monitoring to Quantify Background Peptides for Improved Normalization and Quality Control in Targeted Proteomics

Mass spectrometry-based targeted proteomics employs heavy isotope-labeled proteins or peptides as standards to improve accuracy and precision. The input sample amount is often determined by the total quantity of endogenous proteins or peptides, as defined by spectrophotometric assays, before the heavy-isotope standards are spiked into the samples. Errors in spectrophotometric measurements, which may be due to low sensitivity or chemical or biological interference, have a direct impact on the quantitative mass spectrometry results. Currently used targeted proteomics workflows cannot identify or correct deviations that arise from differences in the input sample amount. We have developed a workflow, global extraction from parallel reaction monitoring (PRM), to identify and quantify thousands of background peptides that are inherently acquired by PRM experiments. These background peptides were used to identify differences in the input sample amount and to reduce this variance by intensity-based, post-acquisition normalization. This approach was then applied to a xenograft study to improve the quantification of human proteins in the presence of mouse tissue contamination. In addition, these background peptides also provided a direct source of quality control metrics related to sample handling and preparation.

Building Personalized Cancer Therapeutics through Multi-Omics Assays and Bacteriophage-Eukaryotic Cell Interactions

Bacteriophage-eukaryotic cell interaction provides the biological foundation of Phage Display technology, which has been widely adopted in studies involving protein-protein and protein-peptide interactions, and it provides a direct link between the proteins and the DNA encoding them. Phage display has also facilitated the development of new therapeutic agents targeting personalized cancer mutations. Proteins encoded by mutant genes in cancers can be processed and presented on the tumor cell surface by human leukocyte antigen (HLA) molecules, and such mutant peptides are called Neoantigens. Neoantigens are naturally existing tumor markers presented on the cell surface. In clinical settings, the T-cell recognition of neoantigens is the foundation of cancer immunotherapeutics. This year, we utilized phage display to successfully develop the 1st antibody-based neoantigen targeting approach for next-generation personalized cancer therapeutics. In this article, we discussed the strategies for identifying neoantigens, followed by using phage display to create personalized cancer therapeutics-a complete pipeline for personalized cancer treatment.

Comparison of Unit Resolution Versus High-Resolution Accurate Mass for Parallel Reaction Monitoring

Parallel reaction monitoring (PRM) is an increasingly popular alternative to selected reaction monitoring (SRM) for targeted proteomics. PRM's strengths over SRM are that it monitors all product ions in a single spectrum, thus eliminating the need to select interference-free product ions prior to data acquisition, and that it is most frequently performed on high-resolution instruments, such as quadrupole-orbitrap and quadrupole-time-of-flight instruments. Here, we show that the primary advantage of PRM is the ability to monitor all transitions in parallel and that high-resolution data are not necessary to obtain high-quality quantitative data. We run the same scheduled PRM assay, measuring 432 peptides from 126 plasma proteins, multiple times on an Orbitrap Eclipse Tribrid mass spectrometer, alternating separate liquid chromatography-tandem mass spectrometry runs between the high-resolution Orbitrap and the unit resolution linear ion trap for PRM. We find that both mass analyzers have similar technical precision and that the linear ion trap's superior sensitivity gives it better lower limits of quantitation for over 62% of peptides in the assay.

Applying Log-Normal Peak Fitting to Parallel Reaction Monitoring Data Analysis

Chromatographic separation is often an important part of mass-spectrometry-based proteomic analysis. It reduces the complexity of the initial samples before they are introduced to mass-spectrometric detection and chromatographic characteristics (such as retention time) add analytical features to the analyte. The acquisition and analysis of chromatographic data are thus of great importance, and specialized software is used for the extraction of quantitative information in an efficient and optimized manner. However, occasionally, automatic peak picking and correct peak boundary setting is challenged by, for instance, aberration of peak shape, peak truncation, and peak tailing, and a manual review of a large number of peaks is frequently required. To support this part of the analysis, we present here a software tool, Peakfit, that fits acquired chromatographic data to the log-normal peak equation and reports the calculated peak parameters. The program is written in R and can easily be integrated into Skyline, a popular software packages that is frequently used for proteomic parallel reaction monitoring applications. The program is capable of processing large data sets (>10 000 peaks) and detecting sporadic outliers in peak boundary selection performed, for instance, in Skyline. In an example data set, available via ProteomeXchange with identifier PXD026875, we demonstrated the capability of the program to characterize chromatographic peaks and showed an example of its ability to objectively and reproducibly detect and solve problematic peak-picking situations.

Mesh Fragmentation Improves Dissociation Efficiency in Top-down Proteomics

Top-down proteomics is a key mass spectrometry-based technology for comprehensive analysis of proteoforms. Proteoforms exhibit multiple high charge states and isotopic forms in full MS scans. The dissociation behavior of proteoforms in different charge states and subjected to different collision energies is highly variable. The current widely employed data-dependent acquisition (DDA) method selects a narrow m/z range (corresponding to a single proteoform charge state) for dissociation from the most abundant precursors. We describe here Mesh, a novel dissociation strategy, to dissociate multiple charge states of one proteoform with multiple collision energies. We show that the Mesh strategy has the potential to generate fragment ions with improved sequence coverage and improve identification ratios in top-down proteomic analyses of complex samples. The strategy is implemented within an open-source instrument control software program named MetaDrive to perform real time deconvolution and precursor selection.

Proteomics, Personalized Medicine and Cancer

As of 2020 the human genome and proteome are both at >90% completion based on high stringency analyses. This has been largely achieved by major technological advances over the last 20 years and has enlarged our understanding of human health and disease, including cancer, and is supporting the current trend towards personalized/precision medicine. This is due to improved screening, novel therapeutic approaches and an increased understanding of underlying cancer biology. However, cancer is a complex, heterogeneous disease modulated by genetic, molecular, cellular, tissue, population, environmental and socioeconomic factors, which evolve with time. In spite of recent advances in treatment that have resulted in improved patient outcomes, prognosis is still poor for many patients with certain cancers (e.g., mesothelioma, pancreatic and brain cancer) with a high death rate associated with late diagnosis. In this review we overview key hallmarks of cancer (e.g., autophagy, the role of redox signaling), current unmet clinical needs, the requirement for sensitive and specific biomarkers for early detection, surveillance, prognosis and drug monitoring, the role of the microbiome and the goals of personalized/precision medicine, discussing how emerging omics technologies can further inform on these areas. Exemplars from recent onco-proteogenomic-related publications will be given. Finally, we will address future perspectives, not only from the standpoint of perceived advances in treatment, but also from the hurdles that have to be overcome.

Are There Indeed Spliced Peptides in the Immunopeptidome?

The claims that a large fraction of the immunopeptidome is composed of spliced major histocompatibility complex (MHC) peptides have stirred significant excitement and raised controversy. Here, I suggest that there are likely no spliced peptides in the immunopeptidome, and if they exist at all, they are extremely rare. I base this claim on both biochemical and bioinformatics considerations. First, as a reactant in normal proteolytic reactions, water will compete with transpeptidation, which has been suggested as the mechanism of peptide splicing. The high mobility and abundance of water in aqueous solutions renders transpeptidation very inefficient and therefore unlikely to occur. Second, new studies have refuted the bioinformatics assignments to spliced peptides of most of the immunopeptidome MS data, suggesting that the correct assignments are likely other canonical, noncanonical, and post-translationally modified peptides. Therefore, I call for rigorous experimental methodology using heavy stable isotope peptides spiking into the immunoaffinity-purified mixtures of natural MHC peptides and analysis by the highly reliable targeted MS, to claim that MHC peptides are indeed spliced.

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Peptide splicing was suggested to contribute to the immunopeptidome.

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I suggest that this idea should be reconsidered based on new evidences.

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Both biochemical and bioinformatics considerations argue against peptide splicing.

Measuring fucosylated alpha-fetoprotein in hepatocellular carcinoma: A comparison of μTAS and parallel reaction monitoring

PURPOSE

Fucosylation of alpha-fetoprotein (AFP) is closely correlated with the diagnosis of patients with hepatocellular carcinoma (HCC). In current, a micro-total analysis system (μTAS) using immunoassay has been developed for determining fucosylated AFP EXPERIMENTAL DESIGN: We compared two analytical methods, μTAS and liquid chromatography-parallel reaction monitoring mass spectrometry (LC-PRM MS), for the measurement of fucosylated AFP in serum to evaluate the usefulness of the results. For this purpose, serum samples were used (cirrhosis, n = 105; HCC, n = 105), and we have discussed the analytical performance of these two methods RESULTS: We observed a correlation (R²  = 0.84) between LC-PRM MS and μTAS using samples where fucosylated levels were measured by both methods. The fucosylated level of AFP by LC-PRM MS better differentiated between cirrhosis and HCC patients than those by μTAS (AUC = 0.910 vs. 0.861), particularly in subgroups with a level of total AFP < 20 ng/mL (0.973 vs. 0.874) and in early stage (I and II) patients (0.922 vs. 0.835) CONCLUSIONS AND CLINICAL RELEVANCE: From this comparative study we can suggest that the LC-PRM MS is applicable in the measurement of fucosylated AFP from human serum and is more useful for early diagnosis of HCC.

CLINICAL RELEVANCE

Fucosylation of AFP is used for the detection of HCC. A micro-total analysis system (μTAS) has been only developed for measuring fucosylation of AFP in clinical research. This study reports the fucosylation of AFP in human serum samples from cirrhosis and HCC patients using the μTAS and a LC-PRM MS to evaluate fucosylation of AFP from each method. As a result, LC-PRM MS is complementary to the conventional μTAS method. Furthermore, LC-PRM MS provides a higher diagnostic accuracy than the μTAS in patients with low AFP levels and an early stage.

Quantitative Determination of Staphylococcus aureus Enterotoxins Types A to I and Variants in Dairy Food Products by Multiplex Immuno-LC-MS/MS

Staphylococcal enterotoxins (SEs) are responsible for frequent food poisoning outbreaks worldwide. Specific identification of SEs is crucial for confirmation of food poisoning, tracking of the incriminated foods or food ingredients, and removal from the food chain. Here, we report on a new food testing protocol addressing the challenge of low abundance of SEs in contaminated food and high sequence heterogeneity. Multiplex ability of targeted high-resolution mass spectrometry was succesfully applied to the simultaneous and quantitative determination of the eight most frequent SEs including sequence variants. In this aim, between three and eight proteotypic peptides of each SE were selected by carefully considering amino acid variations within each type, and sequence homology between types. Quantification of trace levels of SEs directly in food samples was reached by immunoaffinity enrichment and optimized analytical conditions. The assay was validated in dairy food products with a lower limit of quantification down to 0.1 ng/g (in milk), and quantification of SEs was successfully demonstrated in real-life samples collected during staphylococcal food poisoning outbreaks. Importantly, the ability of the method to detect diverse sequence variants was also illustrated. By enabling for the first time the simultaneous quantification of the eight most frequent SEs, the new mass spectrometry-based assay would facilitate the laboratory confirmation of positive samples in situation of food poisoning outbreaks.

Identification of potential salivary biomarker panels for oral squamous cell carcinoma

Oral squamous cell carcinoma (OSCC) is one of the most prevalent cancers worldwide with the maximum number of incidences and deaths reported from India. One of the major causes of poor survival rate associated with OSCC has been attributed to late presentation due to non-availability of a biomarker. Identification of early diagnostic biomarker will help in reducing the disease morbidity and mortality. We validated 12 salivary proteins using targeted proteomics, identified initially by relative quantification of salivary proteins on LC-MS, in OSCC patients and controls. Salivary AHSG (p = 0.0041**) and KRT6C (p = 0.002**) were upregulated in OSCC cases and AZGP1 (p ≤ 0.0001***), KLK1 (p = 0.006**) and BPIFB2 (p = 0.0061**) were downregulated. Regression modelling resulted in a significant risk prediction model (p < 0.0001***) consisting of AZGP1, AHSG and KRT6C for which ROC curve had AUC, sensitivity and specificity of 82.4%, 78% and 73.5% respectively for all OSCC cases and 87.9%, 87.5% and 73.5% respectively for late stage (T3/T4) OSCC. AZGP1, AHSG, KRT6C and BPIFB2 together resulted in ROC curve (p < 0.0001***) with AUC, sensitivity and specificity of 94%, 100% and 77.6% respectively for N0 cases while KRT6C and AZGP1 for N+ cases with ROC curve (p < 0.0001***) having AUC sensitivity and specificity of 76.8%, 73% and 69.4%. Our data aids in the identification of biomarker panels for the diagnosis of OSCC cases with a differential diagnosis between early and late-stage cases.

Interrogation of Dystrophin and Dystroglycan Complex Protein Turnover After Exon Skipping Therapy

Recently, the Food and Drug Administration granted accelerated approvals for four exon skipping therapies -Eteplirsen, Golodirsen, Viltolarsen, and Casimersen -for Duchenne Muscular Dystrophy (DMD). However, these treatments have only demonstrated variable and largely sub-therapeutic levels of restored dystrophin protein in DMD patients, limiting their clinical impact. To better understand variable protein expression and the behavior of truncated dystrophin protein in vivo, we assessed turnover dynamics of restored dystrophin and dystrophin glycoprotein complex (DGC) proteins in mdx mice after exon skipping therapy, compared to those dynamics in wild type mice, using a targeted, highly-reproducible and sensitive, in vivo stable isotope labeling mass spectrometry approach in multiple muscle tissues. Through statistical modeling, we found that restored dystrophin protein exhibited altered stability and slower turnover in treated mdx muscle compared with that in wild type muscle (∼44 d vs. ∼24 d, respectively). Assessment of mRNA transcript stability (quantitative real-time PCR, droplet digital PCR) and dystrophin protein expression (capillary gel electrophoresis, immunofluorescence) support our dystrophin protein turnover measurements and modeling. Further, we assessed pathology-induced muscle fiber turnover through bromodeoxyuridine (BrdU) labeling to model dystrophin and DGC protein turnover in the context of persistent fiber degeneration. Our findings reveal sequestration of restored dystrophin protein after exon skipping therapy in mdx muscle leading to a significant extension of its half-life compared to the dynamics of full-length dystrophin in normal muscle. In contrast, DGC proteins show constant turnover attributable to myofiber degeneration and dysregulation of the extracellular matrix (ECM) in dystrophic muscle. Based on our results, we demonstrate the use of targeted mass spectrometry to evaluate the suitability and functionality of restored dystrophin isoforms in the context of disease and propose its use to optimize alternative gene correction strategies in development for DMD.

Recent advances in analytical strategies for mass spectrometry-based lipidomics

Lipids are vital biological molecules and play multiple roles in cellular function of mammalian organisms such as cellular membrane anchoring, signal transduction, material trafficking and energy storage. Driven by the biological significance of lipids, lipidomics has become an emerging science in the field of omics. Lipidome in biological systems consists of hundreds of thousands of individual lipid molecules that possess complex structures, multiple categories, and diverse physicochemical properties assembled by different combinations of polar headgroups and hydrophobic fatty acyl chains. Such structural complexity poses a huge challenge for comprehensive lipidome analysis. Thanks to the great innovations in chromatographic separation techniques and the continuous advances in mass spectrometric detection tools, analytical strategies for lipidomics have been highly diversified so that the depth and breadth of lipidomics have been greatly enhanced. This review will present the current state of mass spectrometry-based analytical strategies including untargeted, targeted and pseudotargeted lipidomics. Recent typical applications of lipidomics in biomarker discovery, pathogenic mechanism and therapeutic strategy are summarized, and the challenges facing to the field of lipidomics are also discussed.

Parallel reaction monitoring revealed tolerance to drought proteins in weedy rice (Oryza sativa f. spontanea)

Drought is a complicated abiotic stress factor with severe effects on rice growth and production. Weedy rice is a valuable genetic resource that possesses a strong capacity for drought tolerance, cold tolerance, and salt tolerance, and is an excellent material for studying rice tolerance. Here, according to comprehensive tolerance to drought index D, accession WR16 was selected based on strong drought tolerance among 133 studied weedy red rice germplasms. WR16 was compared with Oryza sativa ssp. Japonica. cv. IAPAR-9, a reference genotype originating from Brazil. In addition, accession WR24 was classified as moderately tolerant to drought accessions. Transcriptomic and proteomic analyses were combined to identify 38 co-upregulated proteins related to drought tolerance, and targeted parallel reaction monitoring (PRM) was used to precisely quantify and verify nine proteins in the complex backgrounds. Result showed that six proteins were significantly (Fisher's exact P value < 0.05) related to drought tolerance in accessions WR16 and WR24. Among them, OS09T0478300-01, OS09T0530300-01, and OS01T0800500-01 formed a combined defense system to respond to drought stress in weedy rice. Results of these studies provide comprehensive information for precisely identifying and verifying tolerance to drought proteins and lay a solid theoretical foundation for research on drought tolerance mechanisms.

The Mitochondrial Proteomic Signatures of Human Skeletal Muscle Linked to Insulin Resistance

Introduction: Mitochondria are essential in energy metabolism and cellular survival, and there is growing evidence that insulin resistance in chronic metabolic disorders, such as obesity, type 2 diabetes (T2D), and aging, is linked to mitochondrial dysfunction in skeletal muscle. Protein profiling by proteomics is a powerful tool to investigate mechanisms underlying complex disorders. However, despite significant advances in proteomics within the past two decades, the technologies have not yet been fully exploited in the field of skeletal muscle proteome. Area covered: Here, we review the currently available studies characterizing the mitochondrial proteome in human skeletal muscle in insulin-resistant conditions, such as obesity, T2D, and aging, as well as exercise-mediated changes in the mitochondrial proteome. Furthermore, we outline technical challenges and limitations and methodological aspects that should be considered when planning future large-scale proteomics studies of mitochondria from human skeletal muscle. Authors’ view: At present, most proteomic studies of skeletal muscle or isolated muscle mitochondria have demonstrated a reduced abundance of proteins in several mitochondrial biological processes in obesity, T2D, and aging, whereas the beneficial effects of exercise involve an increased content of muscle proteins involved in mitochondrial metabolism. Powerful mass-spectrometry-based proteomics now provides unprecedented opportunities to perform in-depth proteomics of muscle mitochondria, which in the near future is expected to increase our understanding of the complex molecular mechanisms underlying the link between mitochondrial dysfunction and insulin resistance in chronic metabolic disorders.

MealTime-MS: A Machine Learning-Guided Real-Time Mass Spectrometry Analysis for Protein Identification and Efficient Dynamic Exclusion

Mass spectrometry-based proteomics technologies are prime methods for the high-throughput identification of proteins in complex biological samples. Nevertheless, there are still technical limitations that hinder the ability of mass spectrometry to identify low abundance proteins in complex samples. Characterizing such proteins is essential to provide a comprehensive understanding of the biological processes taking place in cells and tissues. Still today, most mass spectrometry-based proteomics approaches use a data-dependent acquisition strategy, which favors the collection of mass spectra from proteins of higher abundance. Since the computational identification of proteins from proteomics data is typically performed after mass spectrometry analysis, large numbers of mass spectra are typically redundantly acquired from the same abundant proteins, and little to no mass spectra are acquired for proteins of lower abundance. We therefore propose a novel supervised learning algorithm, MealTime-MS, that identifies proteins in real-time as mass spectrometry data are acquired and prevents further data collection from confidently identified proteins to ultimately free mass spectrometry resources to improve the identification sensitivity of low abundance proteins. We use real-time simulations of a previously performed mass spectrometry analysis of a HEK293 cell lysate to show that our approach can identify 92.1% of the proteins detected in the experiment using 66.2% of the MS2 spectra. We also demonstrate that our approach outperforms a previously proposed method, is sufficiently fast for real-time mass spectrometry analysis, and is flexible. Finally, MealTime-MS' efficient usage of mass spectrometry resources will provide a more comprehensive characterization of proteomes in complex samples.

Parallel Reaction Monitoring Mass Spectrometry Method for Detection of Both Casein and Whey Milk Allergens from a Baked Food Matrix

Milk allergy is among the most common food allergies present in early childhood, which in some cases may persist into adulthood as well. Proteins belonging to both casein and whey fractions of milk can trigger an allergic response in susceptible individuals. Milk is present as an ingredient in many foods, and it can also be present as casein- or whey-enriched milk-derived ingredients. As whey proteins are more susceptible to thermal processing than caseins, conventional methods often posed a challenge in accurate detection of whey allergens, particularly from a processed complex food matrix. In this study, a targeted mass spectrometry method has been developed to detect the presence of both casein and whey allergens from thermally processed foods. A pool of 19 candidate peptides representing four casein proteins and two whey proteins was identified using a discovery-driven target selection approach from various milk-derived ingredients. These target peptides were evaluated by parallel reaction monitoring of baked cookie samples containing known amounts of nonfat dry milk (NFDM). The presence of milk could be detected from baked cookies incurred with NFDM at levels as low as 1 ppm using seven peptides representing α-, β-, and κ-casein proteins and three peptides representing a whey protein, β-lactoglobulin, by this consensus PRM method.

Evaluation and minimization of nonspecific tryptic cleavages in proteomic sample preparation

High specificity of trypsin is a prerequisite for accurate identification and quantification of proteins in shotgun proteomics. It is important to minimize nonspecific enzymatic cleavages during proteomic sample preparation.

METHODS

In this study, protein extraction and trypsin digestion conditions were extensively evaluated using the less-complex Escherichia coli lysates to improve the sensitivity of detecting low-abundance nonspecific peptides by liquid chromatography/tandem mass spectrometry.

RESULTS

Trypsin digestion buffers and digestion times were proved to have a significant effect on nonspecific cleavages. The triethylammonium bicarbonate buffer induces significantly lower nonspecific cleavages than the other two buffers, but a freshly prepared urea solution does not induce more than sodium dodecyl sulfate. Because prolonged trypsin digestion resulted in a considerable number of nonspecific cleavages, an optimized 2-h protocol was developed with 45.2% less semispecific tryptic peptides but 18.5% more unmodified peptides identified than the commonly used 16-h protocol.

CONCLUSIONS

The significant decrease in nonspecific cleavages and artificial modifications improves the accuracy of protein quantification and the identification of low-abundance proteins, and it is especially useful for studying protein posttranslational modifications. For trypsin digestion, the proposed 2-h protocol can potentially be a replacement for the traditional 16-h protocol.

Identification of Isopeptides Between Human Tissue Transglutaminase and Wheat, Rye, and Barley Gluten Peptides

Celiac disease (CD) is a chronic immune-mediated enteropathy of the small intestine, which is triggered by the ingestion of storage proteins (gluten) from wheat, rye, and barley in genetically predisposed individuals. Human tissue transglutaminase (TG2) plays a central role in the pathogenesis of CD, because it is responsible for specific gluten peptide deamidation and covalent crosslinking, resulting in the formation of N^ε-(γ-glutamyl)-lysine isopeptide bonds. The resulting TG2-gluten peptide complexes are assumed to cause the secretion of anti-TG2 autoantibodies, but the underlying mechanisms are only partly known. To gain more insight into the structures of these complexes, the aim of our study was to identify TG2-gluten isopeptides. With the use of discovery-driven as well as targeted nanoscale liquid chromatography tandem mass spectrometry, we detected 29 TG2-gluten isopeptides in total, involving seven selected TG2 lysine residues (K205, K265, K429, K468, K590, K600, K677). Several gluten peptides carried known B-cell epitopes and/or T-cell epitopes, either intact 9-mer core regions or partial sequences, as well as sequences bearing striking similarities to already known epitopes. These novel insights into the molecular structures of TG2-gluten peptide complexes may help clarify their physiological relevance in the initiation of CD autoimmunity and the role of anti-TG2 autoantibodies.

Enhancing Data Reliability in TOMAHAQ for Large-Scale Protein Quantification

The analytical scale of most mass-spectrometry-based targeted proteomics assays is usually limited by assay performance and instrument utilization. A recently introduced method, called triggered by offset, multiplexed, accurate mass, high resolution, and absolute quantitation (TOMAHAQ), combines both peptide and sample multiplexing to simultaneously improve analytical scale and quantitative performance. In the present work, critical technical requirements and data analysis considerations for successful implementation of the TOMAHAQ technique based on the study of a total of 185 target peptides across over 200 clinical plasma samples are discussed. Importantly, it is observed that significant interference originate from the TMTzero reporter ion used for the synthetic trigger peptides. This interference is not expected because only TMT10plex reporter ions from the target peptides should be observed under typical TOMAHAQ conditions. In order to unlock the great promise of the technique for high throughput quantification, here a post-acquisition data correction strategy to deconvolute the reporter ion superposition and recover reliable data is proposed.

Proteomic analyses of sheep (ovis aries) embryonic skeletal muscle

The growth and development of embryonic skeletal muscle plays a crucial role in sheep muscle mass. But proteomic analyses for embryonic skeletal development in sheep had been little involved in the past research. In this study, we explored differential abundance proteins during embryonic skeletal muscle development by the tandem mass tags (TMT) and performed a protein profile analyses in the longissimus dorsi of Chinese merino sheep at embryonic ages Day85 (D85N), Day105 (D105N) and Day135 (D135N). 5,520 proteins in sheep embryonic skeletal muscle were identified, and 1,316 of them were differential abundance (fold change ≥1.5 and p-value < 0.05). After the KEGG enrichment analyses, these differential abundance proteins were significant enriched in the protein binding, muscle contraction and energy metabolism pathways. After validation of the protein quantification with the parallel reaction monitoring (PRM), 41% (16/39) significant abundance proteins were validated, which was similar to the results of protein quantification with TMT. All results indicated that D85N to D105N was the stage of embryonic muscle fibers proliferation, while D105N to D135N was the stage of their hypertrophy. These findings provided a deeper understanding of the function and rules of proteins in different phases of sheep embryonic skeletal muscle growth and development.

Absolute quantification of dystrophin protein in human muscle biopsies using parallel reaction monitoring (PRM)

The need for a reliable and accurate method to quantify dystrophin proteins in human skeletal muscle biopsies has become crucial in order to assess the efficacy of dystrophin replacement therapies in Duchenne muscular dystrophy as well as to gain insight into the relationship between dystrophin levels and disease severity in Becker's muscular dystrophy. Current methods to measure dystrophin such as western blot and immunofluorescence, while straightforward and simple, lack precision and sometimes specificity. Here, we standardized a targeted mass spectrometry method to determine the absolute amount of dystrophin in ng/mg of muscle using full-length ¹³ C6-Arg- and ¹³ C6,¹⁵ N2-Lys-labeled dystrophin and parallel reaction monitoring (PRM). The method was found to be reproducible with a limit of quantification as low as 30 pg of dystrophin protein per mg of total muscle proteins. The method was then tested to measure levels of dystrophin in muscle biopsies from a healthy donor and from Duchenne and Becker's muscular dystrophy patients.

Current developments in LC-MS for pharmaceutical analysis

Liquid chromatography (LC) based techniques in combination with mass spectrometry (MS) detection have had a large impact on the development of new pharmaceuticals in the past decades.

Methods for characterizing protein acetylation during viral infection

Lysine acetylation is a prevalent posttranslational modification that acts as a regulator of protein function, subcellular localization, and interactions. A growing body of work has highlighted the importance of temporal alterations in protein acetylation during infection with a range of human viruses. It has become clear that both cellular and viral proteins are decorated by lysine acetylations, and that these modifications contribute to core host defense and virus replication processes. Further defining the extent and dynamics of protein acetylation events during the progression of an infection can provide an important new perspective on the intricate mechanisms underlying the biology and pathogenesis of virus infections. Here, we provide protocols for identifying, quantifying, and probing the regulation of lysine acetylations during viral infection. We describe the use of acetyl-lysine immunoaffinity purification and quantitative mass spectrometry for assessing the cellular acetylome at different stages of an infection. As an alternative to traditional antibody-mediated western blotting, we discuss the benefits of targeted mass spectrometry approaches for detecting and quantifying site-specific acetylations on proteins of interest. Specifically, we provide a protocol using parallel reaction monitoring (PRM). We further discuss experimental considerations that are specific to studying viral infections. Finally, we provide a brief overview of the types of assays that can be employed to characterize the function of an acetylation event in the context of infection. As a method to interrogate the regulation of acetylation, we describe the Fluor de Lys assay for monitoring the enzymatic activities of deacetylases.