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.

Use of Nonhuman Sera as a Highly Cost-Effective Internal Standard for Quantitation of Multiple Human Proteins Using Species-Specific Tryptic Peptides: Applicability in Clinical LC-MS Analyses

Quantitation of proteins using liquid chromatography-tandem mass spectrometry (LC-MS/MS) is complex, with a multiplicity of options ranging from label-free techniques to chemically and metabolically labeling proteins. Increasingly, for clinically relevant analyses, stable isotope-labeled (SIL) internal standards (ISs) represent the "gold standard" for quantitation due to their similar physiochemical properties to the analyte, wide availability, and ability to multiplex to several peptides. However, the purchase of SIL-ISs is a resource-intensive step in terms of cost and time, particularly for screening putative biomarker panels of hundreds of proteins. We demonstrate an alternative strategy utilizing nonhuman sera as the IS for quantitation of multiple human proteins. We demonstrate the effectiveness of this strategy using two high abundance clinically relevant analytes, vitamin D binding protein [Gc globulin] (DBP) and albumin (ALB). We extend this to three putative risk markers for cardiovascular disease: plasma protease C1 inhibitor (SERPING1), annexin A1 (ANXA1), and protein kinase, DNA-activated catalytic subunit (PRKDC). The results show highly specific, reproducible, and linear measurement of the proteins of interest with comparable precision and accuracy to the gold standard SIL-IS technique. This approach may not be applicable to every protein, but for many proteins it can offer a cost-effective solution to LC-MS/MS protein quantitation.

Use of quantitative mass spectrometry-based proteomics and ELISA to compare the alpha 2 macroglobulin concentration in equine blood-based products processed by three different orthobiologic devices

Introduction

Alpha 2 macroglobulin (A2M), a multi-functional protein in the plasma protease inhibitor class, regulates proinflammatory cytokines and the clearance of chondrodestructive enzymes in cases of joint injury and osteoarthritis (OA). The purpose of this study was to compare A2M concentrations in equine plasma samples processed by three commercial devices developed for stall-side regenerative joint therapy.

Methods

Plasma samples were obtained from healthy adult horses (N = 13). Mass spectrometry analysis was used to determine the concentration of protein analytes in each sample. Selected reaction monitoring measured a specific A2M peptide as a surrogate of the whole A2M protein. A2M concentrations produced by each test device were compared for two sample types: a pre-concentrate or platelet-poor (PP) component and a final component for use in the horse.

Results

There was no significant difference (p > 0.05) in the geometric mean (GM) concentration of A2M in the final concentration samples produced by the Alpha2EQ® device (N horses = 13) and the single-centrifugation PP samples produced by the Pro-Stride® APS (autologous protein solution) device (N = 13) and the Restigen® PRP (platelet-rich plasma) device (N = 11). When A2M content in final concentration samples produced by each device was compared, the Pro-Stride APS and Restigen PRP samples had significantly greater GM A2M content (p < 0.0001) compared to the Alpha2EQ samples, and the Pro-Stride APS final concentration samples had significantly greater GM A2M concentration (p < 0.0001) versus that for the Restigen PRP final samples.

Discussion

This comparison demonstrated that the volume and A2M concentration of an Alpha2EQ final concentrate are no different than the volume and concentration of A2M in the PP from Pro-Stride or Restigen devices.

Targeted proteomics data interpretation with DeepMRM

Targeted proteomics is widely utilized in clinical proteomics; however, researchers often devote substantial time to manual data interpretation, which hinders the transferability, reproducibility, and scalability of this approach. We introduce DeepMRM, a software package based on deep learning algorithms for object detection developed to minimize manual intervention in targeted proteomics data analysis. DeepMRM was evaluated on internal and public datasets, demonstrating superior accuracy compared with the community standard tool Skyline. To promote widespread adoption, we have incorporated a stand-alone graphical user interface for DeepMRM and integrated its algorithm into the Skyline software package as an external tool.

Malondialdehyde-Induced Post-translational Modifications in Hemoglobin of Smokers by NanoLC-NSI/MS/MS Analysis

Malondialdehyde (MDA) is the most abundant α,β-unsaturated aldehyde generated from endogenous peroxidation of polyunsaturated fatty acids and is present in cigarette smoke. Post-translational modifications of blood hemoglobin can serve as biomarkers for exposure to chemicals. In this study, two types of MDA-induced modifications, the N-propenal and the dihydropyridine (DHP), were identified at multiple sites in human hemoglobin digest by the high-resolution mass spectrometry. The N-propenal and the DHP types of modification led to the increase of 54.0106 and 134.0368 amu, respectively, at the N-terminal and lysine residues. Among the 21 MDA-modified peptides, 14 with dose-response to MDA concentrations were simultaneously quantified in study subjects by the nanoflow liquid chromatography nanoelectrospray ionization tandem mass spectrometry under selected reaction monitoring (nanoLC-NSI-MS/MS-SRM) without prior enrichment. The results showed that the modifications of the N-propenal-type at α-Lys-11, α-Lys-16, α-Lys-61, β-Lys-8, and β-Lys-17, as well as the DHP-type at the α-N-terminal valine, are significantly higher in hemoglobin isolated from the blood of smokers than in nonsmoking individuals. This is the first report to identify and quantify multiple sites of MDA-induced modifications in human hemoglobin from peripheral blood. Our results suggest that the MDA-derived modifications on hemoglobin might represent valuable biomarkers for MDA-induced protein damage.

Extending the Proteomic Characterization of Candida albicans Exposed to Stress and Apoptotic Inducers through Data-Independent Acquisition Mass Spectrometry

Candida albicans is a commensal fungus that causes systemic infections in immunosuppressed patients. In order to deal with the changing environment during commensalism or infection, C. albicans must reprogram its proteome. Characterizing the stress-induced changes in the proteome that C. albicans uses to survive should be very useful in the development of new antifungal drugs. We studied the C. albicans global proteome after exposure to hydrogen peroxide (H₂O₂) and acetic acid (AA), using a data-independent acquisition mass spectrometry (DIA-MS) strategy. More than 2,000 C. albicans proteins were quantified using an ion library previously constructed using data-dependent acquisition mass spectrometry (DDA-MS). C. albicans responded to treatment with H₂O₂ with an increase in the abundance of many proteins involved in the oxidative stress response, protein folding, and proteasome-dependent catabolism, which led to increased proteasome activity. The data revealed a previously unknown key role for Prn1, a protein similar to pirins, in the oxidative stress response. Treatment with AA resulted in a general decrease in the abundance of proteins involved in amino acid biosynthesis, protein folding, and rRNA processing. Almost all proteasome proteins declined, as did proteasome activity. Apoptosis was observed after treatment with H₂O₂ but not AA. A targeted proteomic study of 32 proteins related to apoptosis in yeast supported the results obtained by DIA-MS and allowed the creation of an efficient method to quantify relevant proteins after treatment with stressors (H₂O₂, AA, and amphotericin B). This approach also uncovered a main role for Oye32, an oxidoreductase, suggesting this protein as a possible apoptotic marker common to many stressors.

IMPORTANCE Fungal infections are a worldwide health problem, especially in immunocompromised patients and patients with chronic disorders. Invasive candidiasis, caused mainly by C. albicans, is among the most common fungal diseases. Despite the existence of treatments to combat candidiasis, the spectrum of drugs available is limited. For the discovery of new drug targets, it is essential to know the pathogen response to different stress conditions. Our study provides a global vision of proteomic remodeling in C. albicans after exposure to different agents, such as hydrogen peroxide, acetic acid, and amphotericin B, that can cause apoptotic cell death. These results revealed the significance of many proteins related to oxidative stress response and proteasome activity, among others. Of note, the discovery of Prn1 as a key protein in the defense against oxidative stress as well the increase in the abundance of Oye32 protein when apoptotic process occurred point them out as possible drug targets.

Quantitative Multiplexed Proteomics Could Assist Therapeutic Decision Making in Non-Small Cell Lung Cancer Patients with Ambiguous ALK Test Results

Therapeutic guidance in non-small cell lung cancer (NSCLC) tumors that are positive for anaplastic lymphoma kinase (ALK) fluorescent in situ hybridization (FISH), but negative for ALK immunohistochemistry, is still challenging. Parallel routine screening of 4588 NSCLC cases identified 22 discordant cases. We rechecked these samples using ALK antibodies and selected reaction monitoring (SRM) quantitative multiplexed proteomics screening multiple protein targets, including ALK and MET for the ALK tyrosine kinase inhibitor (TKI), and FR-alpha, hENT1, RRM1, TUBB3, ERCC1, and XRCC1 for chemotherapy. The presence of ALK (31.8%), MET (36.4%), FR-alpha (72.7%), hENT1 (18.2%), RRM1 (31.8%), TUBB3 (72.9%), ERCC1 (4.5%), and a low level of XRCC1 (54.4%) correlated with clinical outcomes. SRM was more sensitive than the ALK D5F3 assay. Among the eight cases receiving ALK TKI, four cases with ALK or MET detected by SRM had complete or partial responses, whereas four cases without ALK or MET showed progression. Twenty-seven treatment outcomes from 20 cases were assessed and cases expressing more than half of the specific predictive proteins were sensitive to matching therapeutic agents and showed longer progression-free survival than the other cases (p < 0.001). SRM showed a potential role in therapeutic decision making in NSCLC patients with ambiguous ALK test results.

Mapping Isoform Abundance and Interactome of the Endogenous TMPRSS2-ERG Fusion Protein by Orthogonal Immunoprecipitation-Mass Spectrometry Assays

TMPRSS2-ERG gene fusion, a molecular alteration found in nearly half of primary prostate cancer cases, has been intensively characterized at the transcript level. However limited studies have explored the molecular identity and function of the endogenous fusion at the protein level. Here, we developed immunoprecipitation-mass spectrometry assays for the measurement of a low-abundance T1E4 TMPRSS2-ERG fusion protein, its isoforms, and its interactome in VCaP prostate cancer cells. Our assays quantified total ERG (∼27,000 copies/cell) and its four unique isoforms and revealed that the T1E4-ERG isoform accounted for 52 ± 3% of the total ERG protein in VCaP cells, and 50 ± 11% in formalin-fixed paraffin-embedded prostate cancer tissues. For the first time, the N-terminal peptide (methionine-truncated and N-acetylated TASSSSDYGQTSK) unique for the T1/E4 fusion was identified. ERG interactome profiling with the C-terminal, but not the N-terminal, antibodies identified 29 proteins, including mutually exclusive BRG1- and BRM-associated canonical SWI/SNF chromatin remodeling complexes. Our sensitive and selective IP-SRM assays present alternative tools to quantify ERG and its isoforms in clinical samples, thus paving the way for development of more accurate diagnostics of prostate cancer.

Bioanalysis of therapeutic monoclonal antibody by peptide adsorption-controlled LC-MS

Aim: We aimed to develop an easy, low-cost and versatile mass spectrometric method for the bioanalysis of a therapeutic monoclonal antibody (mAb) in human serum that employs peptide adsorption-controlled (PAC)-LC/MS using selected reaction monitoring mode (LC-MS/MS-SRM). Materials & methods: Rituximab was used as a model mAb. To apply the method to human serum samples, a peptide of the complementarity-determining region was selected as the surrogate peptide. The usefulness of PAC-LC-MS/MS-SRM was evaluated by a collaborative study. Results: The calibration curve ranged from 0.5 (or 1.0) to 1000.0 μg/ml. The selectivity, linearity, accuracy and precision met the predefined acceptance criteria. Conclusion: Our method could be a useful bioanalytical method for the quantification of mAbs in clinical samples.

Changes in Feed Proanthocyanidin Profiles during Silage Production and Digestion by Lamb

Proanthocyanidins are plant specialized metabolites which are beneficial to animal nutrition and health. This study determined how proanthocyanidin profiles of sainfoin (Onobrychis viciifolia) and birdsfoot trefoil (Lotus corniculatus) change during the forage conservation process and along the digestive tract of lamb. We determined soluble, protein- and fiber-bound proanthocyanidins by spectrophotometric methods and soluble proanthocyanidin profiles by UPLC-MS/MS. During the conservation process, the total proanthocyanidin contents reduced in both forages and the relative proportion of insoluble proanthocyanidins increased, especially in sainfoin. The soluble proanthocyanidins, their mean degree of polymerization and the relative prodelphinidin share declined in both feed species. In the abomasum of lambs fed sainfoin silage, most of the proanthocyanidins were in insoluble form bound to proteins and fibers, but in the small and large intestines, the proportion of soluble proanthocyanidins increased again. For lambs fed birdsfoot trefoil, the trend was not so clear as proanthocyanidins were already mainly soluble in the abomasum. Nevertheless, a large part of soluble proanthocyanidins was recovered in the digestive tract but could not be detected by the UPLC-MS/MS method used. This study suggests that proanthocyanidins have probably been metabolized in the digestive tract by the resident microbiota.

High-Throughput Large-Scale Targeted Proteomics Assays for Quantifying Pathway Proteins in Pseudomonas putida KT2440

Targeted proteomics is a mass spectrometry-based protein quantification technique with high sensitivity, accuracy, and reproducibility. As a key component in the multi-omics toolbox of systems biology, targeted liquid chromatography-selected reaction monitoring (LC-SRM) measurements are critical for enzyme and pathway identification and design in metabolic engineering. To fulfill the increasing need for analyzing large sample sets with faster turnaround time in systems biology, high-throughput LC-SRM is greatly needed. Even though nanoflow LC-SRM has better sensitivity, it lacks the speed offered by microflow LC-SRM. Recent advancements in mass spectrometry instrumentation significantly enhance the scan speed and sensitivity of LC-SRM, thereby creating opportunities for applying the high speed of microflow LC-SRM without losing peptide multiplexing power or sacrificing sensitivity. Here, we studied the performance of microflow LC-SRM relative to nanoflow LC-SRM by monitoring 339 peptides representing 132 enzymes in Pseudomonas putida KT2440 grown on various carbon sources. The results from the two LC-SRM platforms are highly correlated. In addition, the response curve study of 248 peptides demonstrates that microflow LC-SRM has comparable sensitivity for the majority of detected peptides and better mass spectrometry signal and chromatography stability than nanoflow LC-SRM.

Proteomic Analysis of Chr 18 Proteins Using 2D Fractionation

One of the main goals of the Chromosome-Centric Human Proteome Project (C-HPP) is detection of "missing proteins" (PE2-PE4). Using the UPS2 (Universal proteomics standard 2) set as a model to simulate the range of protein concentrations in the cell, we have previously shown that 2D fractionation enables the detection of more than 95% of UPS2 proteins in a complex biological mixture. In this study, we propose a novel experimental workflow for protein detection during the analysis of biological samples. This approach is extremely important in the context of the C-HPP and the neXt-MP50 Challenge, which can be solved by increasing the sensitivity and the coverage of the proteome encoded by a particular human chromosome. In this study, we used 2D fractionation for in-depth analysis of the proteins encoded by human chromosome 18 (Chr 18) in the HepG2 cell line. Use of 2D fractionation increased the sensitivity of the SRM SIS method by 1.3-fold (68 and 88 proteins were identified by 1D fractionation and 2D fractionation, respectively) and the shotgun MS/MS method by 2.5-fold (21 and 53 proteins encoded by Chr 18 were detected by 1D fractionation and 2D fractionation, respectively). The results of all experiments indicate that 111 proteins encoded by human Chr 18 have been identified; this list includes 42% of the Chr 18 protein-coding genes and 67% of the Chr 18 transcriptome species (Illumina RNaseq) in the HepG2 cell line obtained using a single sample. Corresponding mRNAs were not registered for 13 of the detected proteins. The combination of 2D fractionation technology with SRM SIS and shotgun mass spectrometric analysis did not achieve full coverage, i.e., identification of at least one protein product for each of the 265 protein-coding genes of the selected chromosome. To further increase the sensitivity of the method, we plan to use 5-10 crude synthetic peptides for each protein to identify the proteins and select one of the peptides based on the obtained mass spectra for the synthesis of an isotopically labeled standard for subsequent quantitative analysis. Data are available via ProteomeXchange with the identifier PXD019263.

Selection of Features with Consistent Profiles Improves Relative Protein Quantification in Mass Spectrometry Experiments

In bottom-up mass spectrometry-based proteomics, relative protein quantification is often achieved with data-dependent acquisition (DDA), data-independent acquisition (DIA), or selected reaction monitoring (SRM). These workflows quantify proteins by summarizing the abundances of all the spectral features of the protein (e.g. precursor ions, transitions or fragments) in a single value per protein per run. When abundances of some features are inconsistent with the overall protein profile (for technological reasons such as interferences, or for biological reasons such as post-translational modifications), the protein-level summaries and the downstream conclusions are undermined. We propose a statistical approach that automatically detects spectral features with such inconsistent patterns. The detected features can be separately investigated, and if necessary, removed from the data set. We evaluated the proposed approach on a series of benchmark-controlled mixtures and biological investigations with DDA, DIA and SRM data acquisitions. The results demonstrated that it could facilitate and complement manual curation of the data. Moreover, it can improve the estimation accuracy, sensitivity and specificity of detecting differentially abundant proteins, and reproducibility of conclusions across different data processing tools. The approach is implemented as an option in the open-source R-based software MSstats.

Evaluation of Aptamers as Affinity Reagents for an Enhancement of SRM-Based Detection of Low-Abundance Proteins in Blood Plasma

Selected reaction monitoring (SRM) is a mass spectrometric technique characterized by the exceptionally high selectivity and sensitivity of protein detection. However, even with this technique, the quantitative detection of low- and ultralow-abundance proteins in blood plasma, which is of great importance for the search and verification of novel protein disease markers, is a challenging task due to the immense dynamic range of protein abundance levels. One approach used to overcome this problem is the immunoaffinity enrichment of target proteins for SRM analysis, employing monoclonal antibodies. Aptamers appear as a promising alternative to antibodies for affinity enrichment. Here, using recombinant protein SMAD4 as a model target added at known concentrations to human blood plasma and SRM as a detection method, we investigated a relationship between the initial amount of the target protein and its amount in the fraction enriched with SMAD4 by an anti-SMAD4 DNA-aptamer immobilized on magnetic beads. It was found that the aptamer-based enrichment provided a 30-fold increase in the sensitivity of SRM detection of SMAD4. These results indicate that the aptamer-based affinity enrichment of target proteins can be successfully employed to improve quantitative detection of low-abundance proteins by SRM in undepleted human blood plasma.

Nitrogen-containing cyclic compounds as iminium ion sources for selected reaction monitoring detection of derivatized analytes

Liquid chromatography-tandem mass spectrometry is one of the most sensitive tools for determination of trace amounts of analytes in metabolomics and proteomics. The highest sensitivity is achieved in selected reaction monitoring detection, which involves fragmentation of the molecular ion between two levels of mass selection. However, fragmentation of some compounds is complicated. Detection sensitivity of such analytes may be increased by derivatizing them with a specific moiety fragmentation of which results in product ion of high abundance. In this work, we reveal the influence of iminium ions' structures on their stability by comparing six nitrogen-containing cyclic compounds as derivatization reagents for tandem mass spectrometric analysis of amino group-containing analyte. Commercially available starting materials (piperidine, 2,6-dimethylpiperidine, 1-methylpiperazine, morpholine, pyrrolidine and 1-cyanomethyl-3-methylimidazolium ionic liquid) were used for the synthesis of corresponding carboxylic acids which were further used for derivatization of the model analyte tryptamine. Liquid chromatographic-mass spectrometric analysis of differently derivatized tryptamine was performed for the evaluation of release and stability of corresponding iminium ions under collision-induced dissociation conditions. As a result, morpholine moiety was shown being the most promising iminium ion source among tested compounds. Possible sub-fragmentation pathways of investigated iminium ions were discussed, and the structures of secondary product ions were proposed.

Absolute Quantification of Apolipoproteins Following Treatment with Omega-3 Carboxylic Acids and Fenofibrate Using a High Precision Stable Isotope-labeled Recombinant Protein Fragments Based SRM Assay

Stable isotope-labeled standard (SIS) peptides are used as internal standards in targeted proteomics to provide robust protein quantification, which is required in clinical settings. However, SIS peptides are typically added post trypsin digestion and, as the digestion efficiency can vary significantly between peptides within a protein, the accuracy and precision of the assay may be compromised. These drawbacks can be remedied by a new class of internal standards introduced by the Human Protein Atlas project, which are based on SIS recombinant protein fragments called SIS PrESTs. SIS PrESTs are added initially to the sample and SIS peptides are released on trypsin digestion. The SIS PrEST technology is promising for absolute quantification of protein biomarkers but has not previously been evaluated in a clinical setting. An automated and scalable solid phase extraction workflow for desalting and enrichment of plasma digests was established enabling simultaneous preparation of up to 96 samples. Robust high-precision quantification of 13 apolipoproteins was achieved using a novel multiplex SIS PrEST-based LC-SRM/MS Tier 2 assay in non-depleted human plasma. The assay exhibited inter-day coefficients of variation between 1.5% and 14.5% (median = 3.5%) and was subsequently used to investigate the effects of omega-3 carboxylic acids (OM3-CA) and fenofibrate on these 13 apolipoproteins in human plasma samples from a randomized placebo-controlled trial, EFFECT I (NCT02354976). No significant changes were observed in the OM3-CA arm, whereas treatment with fenofibrate significantly increased apoAII and reduced apoB, apoCI, apoE and apoCIV levels. The reduction in apoCIV following fenofibrate treatment is a novel finding. The study demonstrates that SIS PrESTs can facilitate the generation of robust multiplexed biomarker Tier 2 assays for absolute quantification of proteins in clinical studies.

A Targeted Mass Spectrometry Strategy for Developing Proteomic Biomarkers: A Case Study of Epithelial Ovarian Cancer

Protein biomarkers for epithelial ovarian cancer are critical for the early detection of the cancer to improve patient prognosis and for the clinical management of the disease to monitor treatment response and to detect recurrences. Unfortunately, the discovery of protein biomarkers is hampered by the limited availability of reliable and sensitive assays needed for the reproducible quantification of proteins in complex biological matrices such as blood plasma. In recent years, targeted mass spectrometry, exemplified by selected reaction monitoring (SRM) has emerged as a method, capable of overcoming this limitation. Here, we present a comprehensive SRM-based strategy for developing plasma-based protein biomarkers for epithelial ovarian cancer and illustrate how the SRM platform, when combined with rigorous experimental design and statistical analysis, can result in detection of predictive analytes.Our biomarker development strategy first involved a discovery-driven proteomic effort to derive potential N-glycoprotein biomarker candidates for plasma-based detection of human ovarian cancer from a genetically engineered mouse model of endometrioid ovarian cancer, which accurately recapitulates the human disease. Next, 65 candidate markers selected from proteins of different abundance in the discovery dataset were reproducibly quantified with SRM assays across a large cohort of over 200 plasma samples from ovarian cancer patients and healthy controls. Finally, these measurements were used to derive a 5-protein signature for distinguishing individuals with epithelial ovarian cancer from healthy controls. The sensitivity of the candidate biomarker signature in combination with CA125 ELISA-based measurements currently used in clinic, exceeded that of CA125 ELISA-based measurements alone. The SRM-based strategy in this study is broadly applicable. It can be used in any study that requires accurate and reproducible quantification of selected proteins in a high-throughput and multiplexed fashion.

Multi-omics Biomarker Pipeline Reveals Elevated Levels of Protein-glutamine Gamma-glutamyltransferase 4 in Seminal Plasma of Prostate Cancer Patients

Seminal plasma, because of its proximity to prostate, is a promising fluid for biomarker discovery and noninvasive diagnostics. In this study, we investigated if seminal plasma proteins could increase diagnostic specificity of detecting primary prostate cancer and discriminate between high- and low-grade cancers. To select 147 most promising biomarker candidates, we combined proteins identified through five independent experimental or data mining approaches: tissue transcriptomics, seminal plasma proteomics, cell line secretomics, tissue specificity, and androgen regulation. A rigorous biomarker development pipeline based on selected reaction monitoring assays was designed to evaluate the most promising candidates. As a result, we qualified 76, and verified 19 proteins in seminal plasma of 67 negative biopsy and 152 prostate cancer patients. Verification revealed a prostate-specific, secreted and androgen-regulated protein-glutamine gamma-glutamyltransferase 4 (TGM4), which predicted prostate cancer on biopsy and outperformed age and serum Prostate-Specific Antigen (PSA). A machine-learning approach for data analysis provided improved multi-marker combinations for diagnosis and prognosis. In the independent verification set measured by an in-house immunoassay, TGM4 protein was upregulated 3.7-fold (p = 0.006) and revealed AUC = 0.66 for detecting prostate cancer on biopsy for patients with serum PSA ≥4 ng/ml and age ≥50. Very low levels of TGM4 (120 pg/ml) were detected in blood serum. Collectively, our study demonstrated rigorous evaluation of one of the remaining and not well-explored prostate-specific proteins within the medium-abundance proteome of seminal plasma. Performance of TGM4 warrants its further investigation within the distinct genomic subtypes and evaluation for the inclusion into emerging multi-biomarker panels.

[Use of DNA-aptamers for enrichment of low abundant proteins in cellular extracts for quntitative detection by selected reaction monitoring]

The relationship between the amount of a target protein in a complex biological sample and its amount measured by selected reaction monitoring (SRM) mass spectrometry upon the affinity enrichment of target protein with aptamers immobilized on a solid phase was studied. Human thrombin added in known concentrations to cellular extracts derived from bacterial cells was used as model target protein. It has been demonstrated that the affinity enrichment of thrombin in cellular extracts by means of the thrombin-binding aptamer immobilized on the surface of magnetic microbeads results in an approximately 10-fold increase of the concentration of target protein and a 100-fold decrease of the low limit of a target protein concentration range where its quantitative detection by SRM is possible without an interference from other peptides present in a tryptic digest.

Mass spectrometry: A platform for biomarker discovery and validation for Alzheimer's and Parkinson's diseases

Accurate, reliable, and objective biomarkers for Alzheimer's disease (AD), Parkinson's disease (PD), and related age-associated neurodegenerative disorders are urgently needed to assist in both diagnosis, particularly at early stages, and monitoring of disease progression. Technological advancements in protein detection platforms over the last few decades have resulted in a plethora of reported molecular biomarker candidates for both AD and PD; however, very few of these candidates are developed beyond the discovery phase of the biomarker development pipeline, a reflection of the current bottleneck within the field. In this review, the expanded use of selected reaction monitoring (SRM) targeted mass spectrometry will be discussed in detail as a platform for systematic verification of large panels of protein biomarker candidates prior to costly validation testing. We also advocate for the coupling of discovery-based proteomics with modern targeted MS-based approaches (e.g., SRM) within a single study in future workflows to expedite biomarker development and validation for AD and PD. It is our hope that improving the efficiency within the biomarker development process by use of an SRM pipeline may ultimately hasten the development of biomarkers that both decrease misdiagnosis of AD and PD and ultimately lead to detection at early stages of disease and objective assessment of disease progression. This article is part of the special issue "Proteomics".

Multiplex Assay for Quantification of Acute Phase Proteins and Immunoglobulin A in Dried Blood Spots

Inflammation is the first line defense mechanism against infection, tissue damage, or cancer development. However, inappropriate inflammatory response may also trigger diseases. The quantification of inflammatory proteins is essential to distinguish between harmful and beneficial immune response. Currently used immunoanalytical assays may suffer specificity issues due to antigen-antibody interaction and possible cross-reactivity of antibody with other protein species. In addition, immunoanalytical assays typically require invasive blood sampling and additional logistics; they are relatively costly and highly challenging to multiplex. We present a multiplex assay based on selected reaction monitoring (SRM) for quantification of seven acute-phase proteins (i.e., SAA1, SAA2-isoform1, SAA4, CRP, A1AT-isoform1, A1AG1, A1AG2) and the adaptive immunity effector IGHA1 in dried blood spots. This type of sample is readily available from all human subjects including newborns. The study utilizes proteotypic isotopically labeled peptides with trypsin-cleavable tag and presents optimized and reproducible workflow and several important practical remarks regarding quantitative SRM assays development. The panel of inflammatory proteins was quantified with sequence specificity capable to differentiate protein isoforms with intra- and interday precision (<16.4% coefficient of variation (CV) and <14.3% CV, respectively). Quantitative results were correlated with immuno-nephelometric assay (typically greater than 0.9 Pearson's R).

Increased Sensitivity of Mass Spectrometry by Alkaline Two-Dimensional Liquid Chromatography: Deep Cover of the Human Proteome in Gene-Centric Mode

Currently, great interest is paid to the identification of "missing" proteins that have not been detected in any biological material at the protein level (PE1). In this paper, using the Universal Proteomic Standard sets 1 and 2 (UPS1 and UPS2, respectively) as an example, we characterized mass spectrometric approaches from the point of view of sensitivity (Sn), specificity (Sp), and accuracy (Ac). The aim of the paper was to show the utility of a mass spectra approach for protein detection. This sets consists of 48 high-purity human proteins without single aminoacid polymorphism (SAP) or post translational modification (PTM). The UPS1 set consists of the same 48 proteins at 5 pmols each, and in UPS2, proteins were grouped into 5 groups in accordance with their molar concentration, ranging from 10^-11 to 10^-6 M. Single peptides from the 92% and 96% of all sets of proteins could be detected in a pure solution of UPS2 and UPS1, respectively, by selected reaction monitoring with stable isotope-labeled standards (SRM-SIS). We also found that, in the presence of a biological matrix such as Escherichia coli extract or human blood plasma (HBP), SRM-SIS makes it possible to detect from 63% to 79% of proteins in the UPS2 set (sensitivity) with the highest specificity (∼100%) and an accuracy of 80% by increasing the sensitivity of shotgun and selected reaction monitoring combined with a stable-isotope-labeled peptide standard (SRM-SIS technology) by fractionating samples using reverse-phase liquid chromatography under alkaline conditions (2D-LC_alk). It is shown that this technique of sample fractionation allows the SRM-SIS to detect 98% of the single peptides from the proteins present in the pure solution of UPS2 (47 out of 48 proteins). When the extracts of E. coli or Pichia pastoris are added as biological matrixes to the UPS2, 46, and 45 out of 48 proteins (∼95%) can be detected, respectively, using the SRM-SIS combined with 2D-LC_alk. The combination of the 2D-LC_alk SRM-SIS and shotgun technologies allows us to increase the sensitivity up to 100% in the case of the proteins of the UPS2 set. The usage of that technology can be a solution for identifying the so-called "missing" proteins and, eventually, creating the deep proteome of a particular chromosome of tissue or organs. Experimental data have been deposited in the PeptideAtlas SRM Experiment Library with the dataset identifier PASS01192 and the PRIDE repository with the dataset identifier PXD007643.

[Quantitative targeted screening of proteins associated with lung adenocarcinoma cancer by the method of selected reaction monitoring]

In the present study, we applied selected reaction monitoring (SRM) to a group of proteins that were previously reported to be associated with lung cancer (Novikova S.E. et al. (2017) Biomeditsinskaya khimiya, 63, 181-210. [1]). Measurements were performed on 59 plasma samples. These samples included: 23 samples of plasma of patients diagnosed with lung adenocarcinoma (LAC), 11 samples of plasma of patients diagnosed with squamous cell lung carcinoma (SqCC), 25 samples of donors with no previous history of oncological diseases, and one pooled sample from each of the above group. As a result of the SRM measurements 52 proteins were detected at least in one individual plasma sample. Statistical analysis showed that there were two groups confidently differentiated by the concentration value of 8 proteins wherein 5 proteins displayed increased level (P00738, P26639, P21926, P08603, P51149) in LAC group and 3 proteins (P51884, O15162, Q8N2K0) indicated diminishing the concentration level towards the control level. Data on protein concentrations obtained for LAC and SqCC did not distinguish the samples by statistical clustering analysis. These potential biomarkers can be used for further development of methods for early diagnostics of lung cancer.

Neuronal pentraxin receptor-1 is a new cerebrospinal fluid biomarker of Alzheimer's disease progression

Background: Alzheimer's disease (AD) is the most common type of dementia, with progressive onset of clinical symptoms. The main pathological hallmarks are brain deposits of extracellular amyloid beta plaques and intracellular neurofibrillary tangles (NFT). Cerebrospinal fluid reflects pathological changes in the brain; amyloid beta 1-42 is a marker of amyloid plaques, while total and phosphorylated tau are markers of NFT formation. Additional biomarkers associated with disease pathogenesis are needed, for better prognosis, more specific diagnosis, prediction of disease severity and progression and for improved patient classification in clinical trials. The aim of the present study was to evaluate brain-specific proteins as potential biomarkers of progression of AD. Methods: Overall, 30 candidate proteins were quantified in cerebrospinal fluid (CSF) samples from patients with mild cognitive impairment (MCI) and mild, moderate and severe AD dementia (n=101) using mass spectrometry-based selected reaction monitoring assays. ELISA was used for neuronal pentraxin receptor-1 (NPTXR) confirmation. Results: The best discrimination between MCI and more advanced AD stages (moderate and severe dementia) was observed for protein NPTXR (area under the curve, AUC=0.799). A statistically different abundance of this protein was observed between the two groups, with severe AD patients having progressively lower levels (p<0.05). ELISA confirmed lower levels in AD, in a separate cohort that included controls, MCI and AD patients. Conclusions: We conclude that NPTXR protein in CSF is a novel potential biomarker of AD progression and could have important utility in assessing treatment success in clinical trials.

Targeted Mass Spectrometry-Based Assays for Relative Quantification of 30 Brain-Related Proteins and Their Clinical Applications

Cerebrospinal fluid (CSF) is a promising clinical sample for identification of novel biomarkers for various neurological disorders. Considering its direct contact with brain tissue, CSF represents a valuable source of brain-related and brain-specific proteins. Multiple sclerosis is an inflammatory, demyelinating neurological disease affecting the central nervous system, and so far there are no diagnostic or prognostic disease specific biomarkers available in the clinic. The primary aim of the present study was to develop a targeted mass spectrometry assay for simultaneous quantification of 30 brain-related proteins in CSF and subsequently to demonstrate assay feasibility in neurological samples derived from multiple sclerosis patients. Our multiplex selected reaction monitoring assay had wide dynamic range (median fold range across peptides = 8.16 × 10³) and high assay reproducibility (median across peptides CV = 4%). Candidate biomarkers were quantified in CSF samples from neurologically healthy individuals (n = 9) and patients diagnosed with clinically isolated syndrome (n = 29) or early multiple sclerosis (n = 15).

Selected reaction monitoring mass spectrometry of mastitis milk reveals pathogen-specific regulation of bovine host response proteins

Mastitis is a major challenge to bovine health. The detection of sensitive markers for mastitis in dairy herds is of great demand. Suitable biomarkers should be measurable in milk and should report pathogen-specific changes at an early stage to support earlier diagnosis and more efficient treatment. However, the identification of sensitive biomarkers in milk has remained a challenge, in part due to their relatively low concentration in milk. In the present study, we used a selected reaction monitoring (SRM) mass spectrometry approach, which allowed the absolute quantitation of 13 host response proteins in milk for the first time. These proteins were measured over a 54-h period upon an in vivo challenge with cell wall components from either gram-negative (lipopolysaccharide from Escherichia coli; LPS) or gram-positive bacteria (peptidoglycan from Staphylococcus aureus; PGN). Whereas our data clearly demonstrate that all challenged animals have consistent upregulation of innate immune response proteins after both LPS and PGN challenge, the data also reveal clearly that LPS challenge unleashes faster and shows a more intense host response compared with PGN challenge. Biomarker candidates that may distinguish between gram-negative and gram-positive bacteria include α-2 macroglobulin, α-1 antitrypsin, haptoglobin, serum amyloid A3, cluster of differentiation 14, calgranulin B, cathepsin C, vanin-1, galectin 1, galectin 3, and IL-8. Our approach can support further studies of large cohorts of animals with natural occurring mastitis, to validate the relevance of these suggested biomarkers in dairy production.

Endosomal trafficking regulates receptor-mediated transcytosis of antibodies across the blood brain barrier

Current methods for examining antibody trafficking are either non-quantitative such as immunocytochemistry or require antibody labeling with tracers. We have developed a multiplexed quantitative method for antibody 'tracking' in endosomal compartments of brain endothelial cells. Rat brain endothelial cells were co-incubated with blood-brain barrier (BBB)-crossing FC5, monovalent FC5Fc or bivalent FC5Fc fusion antibodies and control antibodies. Endosomes were separated using sucrose-density gradient ultracentrifugation and analyzed using multiplexed mass spectrometry to simultaneously quantify endosomal markers, receptor-mediated transcytosis (RMT) receptors and the co-incubated antibodies in each fraction. The quantitation showed that markers of early endosomes were enriched in high-density fractions (HDF), whereas markers of late endosomes and lysosomes were enriched in low-density fractions (LDF). RMT receptors, including transferrin receptor, showed a profile similar to that of early endosome markers. The in vitro BBB transcytosis rates of antibodies were directly proportional to their partition into early endosome fractions of brain endothelial cells. Addition of the Fc domain resulted in facilitated antibody 'redistribution' from LDF into HDF and additionally into multivesicular bodies (MVB). Sorting of various FC5 antibody formats away from late endosomes and lysosomes and into early endosomes and a subset of MVB results in increased antibody transcytosis at the abluminal side of the BBB.

A 14-Protein Signature for Rapid Identification of Poor Prognosis Stage III Metastatic Melanoma

PURPOSE

To validate differences in protein levels between good and poor prognosis American Joint Committee on Cancer (AJCC) stage III melanoma patients and compile a protein panel to stratify patient risk.

EXPERIMENTAL DESIGN

Protein extracts from melanoma metastases within lymph nodes in patients with stage III disease with good (n = 16, >4 years survival) and poor survival (n = 14, <2 years survival) were analyzed by selected reaction monitoring (SRM). Diagonal Linear Discriminant Analysis (DLDA) was performed to generate a protein biomarker panel.

RESULTS

SRM analysis identified ten proteins that were differentially abundant between good and poor prognosis stage III melanoma patients. The ten differential proteins were combined with 22 proteins identified in our previous work. A panel of 14 proteins was selected by DLDA that was able to accurately classify patients into prognostic groups based on levels of these proteins.

CONCLUSIONS AND CLINICAL RELEVANCE

The ten differential proteins identified by SRM have biological significance in cancer progression. The final signature of 14 proteins identified by SRM could be used to identify AJCC stage III melanoma patients likely to have poor outcomes who may benefit from adjuvant systemic therapy.

Targeted degradomics in protein terminomics and protease substrate discovery

Targeted degradomics integrates positional information into mass spectrometry (MS)-based targeted proteomics workflows and thereby enables analysis of proteolytic cleavage events with unprecedented specificity and sensitivity. Rapid progress in the establishment of protease-substrate relations provides extensive degradomics target lists that now can be tested with help of selected and parallel reaction monitoring (S/PRM) in complex biological systems, where proteases act in physiological environments. In this minireview, we describe the general principles of targeted degradomics, outline the generic experimental workflow of the methodology and highlight recent and future applications in protease research.

Selected reaction monitoring approach for validating peptide biomarkers

We here describe a selected reaction monitoring (SRM)-based approach for the discovery and validation of peptide biomarkers for cancer. The first stage of this approach is the direct identification of candidate peptides through comparison of proteolytic peptides derived from the plasma of cancer patients or healthy individuals. Several hundred candidate peptides were identified through this method, providing challenges for choosing and validating the small number of peptides that might prove diagnostically useful. To accomplish this validation, we used 2D chromatography coupled with SRM of candidate peptides. We applied this approach, called sequential analysis of fractionated eluates by SRM (SAFE-SRM), to plasma from cancer patients and discovered two peptides encoded by the peptidyl-prolyl cis-trans isomerase A (PPIA) gene whose abundance was increased in the plasma of ovarian cancer patients. At optimal thresholds, elevated levels of at least one of these two peptides was detected in 43 (68.3%) of 63 women with ovarian cancer but in none of 50 healthy controls. In addition to providing a potential biomarker for ovarian cancer, this approach is generally applicable to the discovery of peptides characteristic of various disease states.

Multiple marker abundance profiling: combining selected reaction monitoring and data-dependent acquisition for rapid estimation of organelle abundance in subcellular samples

Measuring changes in protein or organelle abundance in the cell is an essential, but challenging aspect of cell biology. Frequently-used methods for determining organelle abundance typically rely on detection of a very few marker proteins, so are unsatisfactory. In silico estimates of protein abundances from publicly available protein spectra can provide useful standard abundance values but contain only data from tissue proteomes, and are not coupled to organelle localization data. A new protein abundance score, the normalized protein abundance scale (NPAS), expands on the number of scored proteins and the scoring accuracy of lower-abundance proteins in Arabidopsis. NPAS was combined with subcellular protein localization data, facilitating quantitative estimations of organelle abundance during routine experimental procedures. A suite of targeted proteomics markers for subcellular compartment markers was developed, enabling independent verification of in silico estimates for relative organelle abundance. Estimation of relative organelle abundance was found to be reproducible and consistent over a range of tissues and growth conditions. In silico abundance estimations and localization data have been combined into an online tool, multiple marker abundance profiling, available in the SUBA4 toolbox (http://suba.live).

Quantifying HDL proteins by mass spectrometry: how many proteins are there and what are their functions?

INTRODUCTION

Many lines of evidence indicate that low levels of HDL cholesterol increase the risk of cardiovascular disease (CVD). However, recent clinical studies of statin-treated subjects with established atherosclerosis cast doubt on the hypothesis that elevating HDL cholesterol levels reduces CVD risk. Areas covered: It is critical to identify new HDL metrics that capture HDL's proposed cardioprotective effects. One promising approach is quantitative MS/MS-based HDL proteomics. This article focuses on recent studies of the feasibility and challenges of using this strategy in translational studies. It also discusses how lipid-lowering therapy and renal disease alter HDL's functions and proteome, and how HDL might serve as a platform for binding proteins with specific functional properties. Expert commentary: It is clear that HDL has a diverse protein cargo and that its functions extend well beyond its classic role in lipid transport and reverse cholesterol transport. MS/MS analysis has demonstrated that HDL might contain >80 different proteins. Key challenges are demonstrating that these proteins truly associate with HDL, are functionally important, and that MS-based HDL proteomics can reproducibly detect biomarkers in translational studies of disease risk.

Why Are the Correlations between mRNA and Protein Levels so Low among the 275 Predicted Protein-Coding Genes on Human Chromosome 18?

In this work targeted (selected reaction monitoring, SRM, PASSEL: PASS00697) and panoramic (shotgun LC-MS/MS, PRIDE: PXD00244) mass-spectrometric methods as well as transcriptomic analysis of the same samples using RNA-Seq and PCR methods (SRA experiment IDs: SRX341198, SRX267708, SRX395473, SRX390071) were applied for quantification of chromosome 18 encoded transcripts and proteins in human liver and HepG2 cells. The obtained data was used for the estimation of quantitative mRNA-protein ratios for the 275 genes of the selected chromosome in the selected tissues. The impact of methodological limitations of existing analytical proteomic methods on gene-specific mRNA-protein ratios and possible ways of overcoming these limitations for detection of missing proteins are also discussed.

Multiplexed targeted mass spectrometry assays for prostate cancer-associated urinary proteins

Biomarkers for effective early diagnosis and prognosis of prostate cancer are still lacking. Multiplexed assays for cancer-associated proteins could be useful for identifying biomarkers for cancer detection and stratification. Herein, we report the development of sensitive targeted mass spectrometry assays for simultaneous quantification of 10 prostate cancer-associated proteins in urine. The diagnostic utility of these markers was evaluated with an initial cohort of 20 clinical urine samples. Individual marker concentration was normalized against the measured urinary prostate-specific antigen level as a reference of prostate-specific secretion. The areas under the receiver-operating characteristic curves for the 10 proteins ranged from 0.75 for CXL14 to 0.87 for CEAM5. Furthermore, MMP9 level was found to be significantly higher in patients with high Gleason scores, suggesting a potential of MMP9 as a marker for risk level assessment. Taken together, our work illustrated the feasibility of accurate multiplexed measurements of low-abundance cancer-associated proteins in urine and provided a viable path forward for preclinical verification of candidate biomarkers for prostate cancer.

Current state of the art for enhancing urine biomarker discovery

INTRODUCTION

Urine is a highly desirable biospecimen for biomarker analysis because it can be collected recurrently by non-invasive techniques, in relatively large volumes. Urine contains cellular elements, biochemicals, and proteins derived from glomerular filtration of plasma, renal tubule excretion, and urogenital tract secretions that reflect, at a given time point, an individual's metabolic and pathophysiologic state.

AREAS COVERED

High-resolution mass spectrometry, coupled with state of the art fractionation systems are revealing the plethora of diagnostic/prognostic proteomic information existing within urinary exosomes, glycoproteins, and proteins. Affinity capture pre-processing techniques such as combinatorial peptide ligand libraries and biomarker harvesting hydrogel nanoparticles are enabling measurement/identification of previously undetectable urinary proteins. Expert commentary: Future challenges in the urinary proteomics field include a) defining either single or multiple, universally applicable data normalization methods for comparing results within and between individual patients/data sets, and b) defining expected urinary protein levels in healthy individuals.

Sirtuin Lipoamidase Activity Is Conserved in Bacteria as a Regulator of Metabolic Enzyme Complexes

Lipoic acid is an essential metabolic cofactor added as a posttranslational modification on several multimeric enzyme complexes. These protein complexes, evolutionarily conserved from bacteria to humans, are core regulators of cellular metabolism. While the multistep enzymatic process of adding lipoyl modifications has been well characterized in Escherichia coli, the enzyme required for the removal of these lipoyl moieties (i.e., a lipoamidase or delipoylase) has not yet been identified. Here, we describe our discovery of sirtuins as lipoamidases in bacteria and establish their conserved substrates. Specifically, by using a series of knockout, overexpression, biochemical, in vitro, proteomic, and functional assays, we determined the substrates of sirtuin CobB in E. coli as components of the pyruvate dehydrogenase (PDH), α-ketoglutarate dehydrogenase (KDH), and glycine cleavage (GCV) complexes. In vitro assays provided direct evidence for this specific CobB activity and its NAD⁺ dependence, a signature of all sirtuins. By designing a targeted quantitative mass spectrometry method, we further measured sirtuin-dependent, site-specific lipoylation on these substrates. The biological significance of CobB-modulated lipoylation was next established by its inhibition of both PDH and KDH activities. By restricting the carbon sources available to E. coli, we demonstrated that CobB regulates PDH and KDH under several growth conditions. Additionally, we found that SrtN, the sirtuin homolog in Gram-positive Bacillus subtilis, can also act as a lipoamidase. By demonstrating the evolutionary conservation of lipoamidase activity across sirtuin homologs, along with the conservation of common substrates, this work emphasizes the significance of protein lipoylation in regulating central metabolic processes.IMPORTANCE Here, we demonstrate that sirtuin lipoamidase activity exists in both Gram-positive and Gram-negative bacteria and establishing its conservation from bacteria to humans. Specifically, we discovered that CobB and SrtN act as lipoamidases in E. coli and B. subtilis, respectively. Intriguingly, not only is this sirtuin enzymatic activity conserved, but also the lipoylated substrates and functions are conserved, as bacterial sirtuins negatively regulate the lipoylation levels and activities of PDH and KDH. Considering that PDH and KDH regulate two carbon entry points into the tricarboxylic acid cycle, our finding highlights lipoylation as a conserved molecular toggle that regulates central metabolic pathways. Indeed, our findings from tests in which we limited nutrient availability support this. Furthermore, this study illustrates how the integration of technologies from different disciplines provides avenues to uncover enzymatic activities at the core of cellular metabolism regulation.

Quantitative Assessment of the Effects of Trypsin Digestion Methods on Affinity Purification-Mass Spectrometry-based Protein-Protein Interaction Analysis

Affinity purification-mass spectrometry (AP-MS) has become the method of choice for discovering protein-protein interactions (PPIs) under native conditions. The success of AP-MS depends on the efficiency of trypsin digestion and the recovery of the tryptic peptides for MS analysis. Several different protocols have been used for trypsin digestion of protein complexes in AP-MS studies, but no systematic studies have been conducted on the impact of trypsin digestion conditions on the identification of PPIs. Here, we used NFκB/RelA and Bromodomain-containing protein 4 (BRD4) as baits and test five distinct trypsin digestion methods (two using "on-beads," three using "elution-digestion" protocols). Although the performance of the trypsin digestion protocols change slightly depending on the different baits, antibodies and cell lines used, we found that elution-digestion methods consistently outperformed on-beads digestion methods. The high-abundance interactors can be identified universally by all five methods, but the identification of low-abundance RelA interactors is significantly affected by the choice of trypsin digestion method. We also found that different digestion protocols influence the selected reaction monitoring (SRM)-MS quantification of PPIs, suggesting that optimization of trypsin digestion conditions may be required for robust targeted analysis of PPIs.

Heterogeneous Ribosomes Preferentially Translate Distinct Subpools of mRNAs Genome-wide

Emerging studies have linked the ribosome to more selective control of gene regulation. However, an outstanding question is whether ribosome heterogeneity at the level of core ribosomal proteins (RPs) exists and enables ribosomes to preferentially translate specific mRNAs genome-wide. Here, we measured the absolute abundance of RPs in translating ribosomes and profiled transcripts that are enriched or depleted from select subsets of ribosomes within embryonic stem cells. We find that heterogeneity in RP composition endows ribosomes with differential selectivity for translating subpools of transcripts, including those controlling metabolism, cell cycle, and development. As an example, mRNAs enriched in binding to RPL10A/uL1-containing ribosomes are shown to require RPL10A/uL1 for their efficient translation. Within several of these transcripts, this level of regulation is mediated, at least in part, by internal ribosome entry sites. Together, these results reveal a critical functional link between ribosome heterogeneity and the post-transcriptional circuitry of gene expression.

Prediction of Hopeless Peptides Unlikely to be Selected for Targeted Proteome Analysis

In targeted proteomics using liquid chromatography-tandem triple quadrupole mass spectrometry (LC/MS/MS) in the selected reaction monitoring (SRM) mode, selecting the best observable or visible peptides is a key step in the development of SRM assay methods of target proteins. A direct comparison of signal intensities among all candidate peptides by brute-force LC/MS/MS analysis is a concrete approach for peptide selection. However, the analysis requires an SRM method with hundreds of transitions. This study reports on the development of a method for predicting and identifying hopeless peptides to reduce the number of candidate peptides needed for brute-force experiments. Hopeless peptides are proteotypic peptides that are unlikely to be selected for targets in SRM analysis owing to their poor ionization characteristics. Targeted proteomics data from Escherichia coli demonstrated that the relative ionization efficiency between two peptides could be predicted from sequences of two peptides, when a multivariate regression model is used. Validation of the method showed that >20% of the candidate peptides could be successfully eliminated as hopeless peptides with a false positive rate of less than 2%.

How may targeted proteomics complement genomic data in breast cancer?

INTRODUCTION

Breast cancer (BC) is the most common female cancer in the world and was recently deconstructed in different molecular entities. Although most of the recent assays to characterize tumors at the molecular level are genomic-based, proteins are the actual executors of cellular functions and represent the vast majority of targets for anticancer drugs. Accumulated data has demonstrated an important level of quantitative and qualitative discrepancies between genomic/transcriptomic alterations and their protein counterparts, mostly related to the large number of post-translational modifications. Areas covered: This review will present novel proteomics technologies such as Reverse Phase Protein Array (RPPA) or mass-spectrometry (MS) based approaches that have emerged and that could progressively replace old-fashioned methods (e.g. immunohistochemistry, ELISA, etc.) to validate proteins as diagnostic, prognostic or predictive biomarkers, and eventually monitor them in the routine practice. Expert commentary: These different targeted proteomic approaches, able to complement genomic data in BC and characterize tumors more precisely, will permit to go through a more personalized treatment for each patient and tumor.

Aroma Constituents in Shanxi Aged Vinegar before and after Aging

Shanxi aged vinegar is one of the most famous Chinese traditional cereal vinegars produced by spontaneous solid-state fermentation. However, the aroma composition of Shanxi aged vinegar is still ambiguous. The Shanxi vinegars before and after aging were both analyzed by solvent-assisted flavor evaporation combined with gas chromatography-mass spectrometry (GC-MS) as well as gas chromatography-olfactometry (GC-O) in aroma extract dilution analysis. A total of 87 odor-active regions were found by GC-O, and 80 odor-active compounds were identified. By GC-MS/MS, in selected reaction monitoring mode, 30 important identifications were quantitated using authentic standards. In comparison, the aroma molecules for the vinegars before and after aging were almost the same; only their levels were altered, with mostly the esters and some compounds that produce pungent smells being lost and the levels of those from the Maillard reaction, especially the pyrazines (e.g., tetramethylpyrazine), being greatly increased. As for the aged vinegar, the compounds found to have high flavor dilution factors (>128) were 3-(methylthio)propanal, vanillin, 2,3-butanedione, tetramethylpyrazine, 3-methylbutanoic acid, γ-nonalactone, guaiacol, 3-(methylthio)propyl acetate, dimethyl trisulfide, phenylacetaldehyde, 2-ethyl-6-methylpyrazine, 2-acetylpyrazine, 2,3-dimethylpyrazine, furfural, and 3-hydroxy-2-butanone. However, the aroma compounds found at high concentrations (>25 μg/L) in the aged vinegar were acetic acid, followed by 2,3-butanedione, furfural, 3-hydroxy-2-butanone, tetramethylpyrazine, furfuryl alcohol, and 3-methylbutanoic acid.

Identification of Organ-Enriched Protein Biomarkers of Acute Liver Injury by Targeted Quantitative Proteomics of Blood in Acetaminophen- and Carbon-Tetrachloride-Treated Mouse Models and Acetaminophen Overdose Patients

Organ-enriched blood proteins, those produced primarily in one organ and secreted or exported to the blood, potentially afford a powerful and specific approach to assessing diseases in their cognate organs. We demonstrate that quantification of organ-enriched proteins in the blood offers a new strategy to find biomarkers for diagnosis and assessment of drug-induced liver injury (and presumably the assessment of other liver diseases). We used selected reaction monitoring (SRM) mass spectrometry to quantify 81 liver-enriched proteins plus three aminotransferases (ALT1, AST1, and AST2) in plasma of C57BL/6J and NOD/ShiLtJ mice exposed to acetaminophen or carbon tetrachloride. Plasma concentrations of 49 liver-enriched proteins were perturbed significantly in response to liver injury induced by one or both toxins. We validated four of these toxin-responsive proteins (ALDOB, ASS1, BHMT, and GLUD1) by Western blotting. By both assays, these four proteins constitute liver injury markers superior to currently employed markers such as ALT and AST. A similar approach was also successful in human serum where we had analyzed 66 liver-enriched proteins in acetaminophen overdose patients. Of these, 23 proteins were elevated in patients; 15 of 23 overlapped with the concentration-increased proteins in the mouse study. A combination of 5 human proteins, AGXT, ALDOB, CRP, FBP1, and MMP9, provides the best diagnostic performance to distinguish acetaminophen overdose patients from controls (sensitivity: 0.85, specificity: 0.84, accuracy: 85%). These five blood proteins are candidates for detecting acetaminophen-induced liver injury using next-generation diagnostic devices (e.g, microfluidic ELISA assays).

Serine and threonine residues of plant STN7 kinase are differentially phosphorylated upon changing light conditions and specifically influence the activity and stability of the kinase

STN7 kinase catalyzes the phosphorylation of the globally most common membrane proteins, the light-harvesting complex II (LHCII) in plant chloroplasts. STN7 itself possesses one serine (Ser) and two threonine (Thr) phosphosites. We show that phosphorylation of the Thr residues protects STN7 against degradation in darkness, low light and red light, whereas increasing light intensity and far red illumination decrease phosphorylation and induce STN7 degradation. Ser phosphorylation, in turn, occurs under red and low intensity white light, coinciding with the client protein (LHCII) phosphorylation. Through analysis of the counteracting LHCII phosphatase mutant tap38/pph1, we show that Ser phosphorylation and activation of the STN7 kinase for subsequent LHCII phosphorylation are heavily affected by pre-illumination conditions. Transitions between the three activity states of the STN7 kinase (deactivated in darkness and far red light, activated in low and red light, inhibited in high light) are shown to modulate the phosphorylation of the STN7 Ser and Thr residues independently of each other. Such dynamic regulation of STN7 kinase phosphorylation is crucial for plant growth and environmental acclimation.

State of the Art of Chromosome 18-Centric HPP in 2016: Transcriptome and Proteome Profiling of Liver Tissue and HepG2 Cells

A gene-centric approach was applied for a large-scale study of expression products of a single chromosome. Transcriptome profiling of liver tissue and HepG2 cell line was independently performed using two RNA-Seq platforms (SOLiD and Illumina) and also by Droplet Digital PCR (ddPCR) and quantitative RT-PCR. Proteome profiling was performed using shotgun LC-MS/MS as well as selected reaction monitoring with stable isotope-labeled standards (SRM/SIS) for liver tissue and HepG2 cells. On the basis of SRM/SIS measurements, protein copy numbers were estimated for the Chromosome 18 (Chr 18) encoded proteins in the selected types of biological material. These values were compared with expression levels of corresponding mRNA. As a result, we obtained information about 158 and 142 transcripts for HepG2 cell line and liver tissue, respectively. SRM/SIS measurements and shotgun LC-MS/MS allowed us to detect 91 Chr 18-encoded proteins in total, while an intersection between the HepG2 cell line and liver tissue proteomes was ∼66%. In total, there were 16 proteins specifically observed in HepG2 cell line, while 15 proteins were found solely in the liver tissue. Comparison between proteome and transcriptome revealed a poor correlation (R² ≈ 0.1) between corresponding mRNA and protein expression levels. The SRM and shotgun data sets (obtained during 2015-2016) are available in PASSEL (PASS00697) and ProteomeExchange/PRIDE (PXD004407). All measurements were also uploaded into the in-house Chr 18 Knowledgebase at http://kb18.ru/protein/matrix/416126 .

Quantitative analysis of human centrosome architecture by targeted proteomics and fluorescence imaging

Centrioles are essential for the formation of centrosomes and cilia. While numerical and/or structural centrosomes aberrations are implicated in cancer, mutations in centriolar and centrosomal proteins are genetically linked to ciliopathies, microcephaly, and dwarfism. The evolutionarily conserved mechanisms underlying centrosome biogenesis are centered on a set of key proteins, including Plk4, Sas-6, and STIL, whose exact levels are critical to ensure accurate reproduction of centrioles during cell cycle progression. However, neither the intracellular levels of centrosomal proteins nor their stoichiometry within centrosomes is presently known. Here, we have used two complementary approaches, targeted proteomics and EGFP-tagging of centrosomal proteins at endogenous loci, to measure protein abundance in cultured human cells and purified centrosomes. Our results provide a first assessment of the absolute and relative amounts of major components of the human centrosome. Specifically, they predict that human centriolar cartwheels comprise up to 16 stacked hubs and 1 molecule of STIL for every dimer of Sas-6. This type of quantitative information will help guide future studies of the molecular basis of centrosome assembly and function.

Targeted Proteomics Approach for Precision Plant Breeding

Selected reaction monitoring (SRM) is a targeted mass spectrometry technique that enables precise quantitation of hundreds of peptides in a single run. This technique provides new opportunities for multiplexed protein biomarker measurements. For precision plant breeding, DNA-based markers have been used extensively, but the potential of protein biomarkers has not been exploited. In this work, we developed an SRM marker panel with assays for 104 potato (Solanum tuberosum) peptides selected using univariate and multivariate statistics. Thereafter, using random forest classification, the prediction markers were identified for Phytopthora infestans resistance in leaves, P. infestans resistance in tubers, and plant yield in potato leaf secretome samples. The results suggest that the marker panel has the predictive potential for three traits, two of which have no commercial DNA markers so far. Furthermore, the marker panel was also tested and found to be applicable to potato clones not used during the marker development. The proposed workflow is thus a proof-of-concept for targeted proteomics as an efficient readout in accelerated breeding for complex and agronomically important traits.

The clinical impact of recent advances in LC-MS for cancer biomarker discovery and verification

Mass spectrometry (MS) -based proteomics has become an indispensable tool with broad applications in systems biology and biomedical research. With recent advances in liquid chromatography (LC) and MS instrumentation, LC-MS is making increasingly significant contributions to clinical applications, especially in the area of cancer biomarker discovery and verification. To overcome challenges associated with analyses of clinical samples (for example, a wide dynamic range of protein concentrations in bodily fluids and the need to perform high throughput and accurate quantification of candidate biomarker proteins), significant efforts have been devoted to improve the overall performance of LC-MS-based clinical proteomics platforms. Reviewed here are the recent advances in LC-MS and its applications in cancer biomarker discovery and quantification, along with the potentials, limitations and future perspectives.

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.

Parallel Reaction Monitoring: A Targeted Experiment Performed Using High Resolution and High Mass Accuracy Mass Spectrometry

The parallel reaction monitoring (PRM) assay has emerged as an alternative method of targeted quantification. The PRM assay is performed in a high resolution and high mass accuracy mode on a mass spectrometer. This review presents the features that make PRM a highly specific and selective method for targeted quantification using quadrupole-Orbitrap hybrid instruments. In addition, this review discusses the label-based and label-free methods of quantification that can be performed with the targeted approach.