PeptidePicker: A scientific workflow with web interface for selecting appropriate peptides for targeted proteomics experiments

Determination of A1 and A2 β-casein in cow milk by high-performance liquid chromatography tandem mass spectrometry

A2 β-CN milk has gained widespread acceptance due to its nutritional benefits. To verify the authenticity and detect adulteration and contamination in A2 milk, we developed an HPLC-MS/MS method for determining the characteristic peptides of A1 and A2 β-CN in cow milk. The method demonstrated good specificity, sensitivity, and linearity for both A1 and A2 characteristic peptides, with limit of detection of 0.01 and 0.03 mg/L, limit of quantitation of 0.03 and 0.1 mg/L, and determination coefficients of 0.9994 and 0.9992, respectively. Whereas accuracy and precision were reasonable, the recoveries varied (69.4%-151%) across concentration levels (0.04, 0.2, and 1.0 g/kg), with higher recoveries for both peptides at low concentrations and lower recoveries for A2 peptide at medium and high concentrations, influenced by factors such as adsorption and ionization efficiency. We optimized the tryptic hydrolysis conditions, selecting a trypsin-to-casein ratio of 1:25 and a hydrolysis time of 6 h at 37°C. However, the hydrolysis of A1 and A2 β-CN was incomplete and asynchronous, exhibiting parabolic relationships with their respective concentrations, with hydrolysis degrees of 12.3% for A1 β-CN and 9.6% for A2 β-CN in pure powders. We finally established a regression model to calculate the actual proportion of A1 and A2 β-CN, with the detection limits of 5% for both β-CN. In the quantitation range of this model, A1 β-CN accounting for 10% to 80% or A2 β-CN accounting for 20% to 90%, the measured value of A1/A2 or A2/A1 was a power function relationship with the theoretical value. This method effectively verifies the authenticity of A1 and A2 milk, providing a reliable tool for detecting adulteration and contamination.

A reference database enabling in-depth proteome and PTM analysis of mouse immune cells

Spectral libraries fulfill multiple functions in biological and analytical applications. For biologists, these libraries provide a valuable resource to verify the presence and abundance of proteins or pathways within a selected cell type thus determine the feasibility of further experiments. Despite advances, existing libraries are incomplete and provide researchers only a limited amount of information. To address this, we introduce the reference database - Spectral Library of Immune Cells (SpLICe), a resource covering B-cells, CD4 and CD8 T-cells, macrophages and dendritic cells containing nearly 9,000 protein groups and 110,346 proteotypic peptides. Additionally, the database provides data on > 20,000 post-translationally modified proteotypic peptides (oxidation, phosphorylation, methylation, acetylation, deamidation and N-glycosylation) across the selected immune cell populations. SpLICe supports the quantification of more than half of total murine proteins annotated by UniProtKB/Swiss-Prot, enabling monitoring of selected proteins or pathways from Reactome pathways and Gene Ontology databases. The platform provides relative protein abundances and supports the generation of targeted mass spectrometry assays by identifying and scoring proteotypic peptides.

Strategies to verify equimolar peptide release in mass spectrometry-based protein quantification exemplified for apolipoprotein(a)

OBJECTIVES

Quantitative protein mass spectrometry (MS) is ideally suited for precision diagnostics and for reference standardization of protein analytes. At the Leiden Apolipoprotein Reference Laboratory we apply MS strategies to obtain detailed insight into the protein-to-peptide conversion in order to verify that quantifier peptides are not partly concealed in miscleaved protein backbone.

METHODS

Apolipoprotein(a) (apo(a)) was digested in a non-optimal manner to enhance the number of miscleaved peptides that were identified by high resolution liquid chromatography tandem-MS measurements. The protein-to-peptide conversion was carefully mapped with specific attention for miscleaved peptides that contain an apo(a) quantifier peptide. Four different isotopologues of each apo(a)-quantifier peptide were applied to evaluate linearity of internal peptide standards during measurement of specific real-life samples.

RESULTS

Two apo(a) quantifier peptides that were concealed in two different miscleaved peptides were included into a multiple reaction monitoring list in our targeted MS-based apo(a) quantifications to alert for potential protein digestion discrepancies. The presence of miscleaved peptides could be ruled out when applying our candidate reference measurement procedure (RMP) for apo(a) quantification.

CONCLUSIONS

These data further corroborate the validity of our apo(a) candidate RMP as higher order method for certification of commercial Lp(a) tests that is endorsed by the International Federation of Clinical Chemistry and Laboratory Medicine. MS-based molecular detection and quantification of heterogeneous apo(a) proteoforms will allow manufacturers' transitioning from confounded lipoprotein(a) [Lp(a)] mass levels into accurate molar apo(a) levels.

Characterization of 53 Multiplexed Targeted Proteomics Assays for Verification Studies in Cancer Cell Lines

The National Cancer Institute's Clinical Proteomics Tumor Analysis Consortium (CPTAC) was established to address the need for improved design, standardization, and validation of proteomics assays to enable better translation of biomarkers from the analytical lab to the clinic. Here, we applied CPTAC guidelines to characterize quantitative mass spectrometry (MS) assays in a new multiple reaction monitoring (MRM) proteomics panel. The panel of 50 proteins was developed in response to a previous study that identified a proteomic profile of altered translational control associated with response to a new cancer drug. MRM-MS assays for 53 peptides of interest were developed, optimized, and characterized on a UPLC system coupled to a triple-quadrupole mass spectrometer (QQQ-MS) using synthetic proteotypic peptides and corresponding stable-isotope labeled internal standard (SIS) peptides. Most of the assays were found to be fit-for-purpose for biomarker verification in that they precisely and reproducibly quantify the peptides at levels corresponding to the endogenous concentration in the desired cancer cell lines. Of these, 28 peptide assays represent to proteins that previously had no associated assays published in the CPTAC database. The targeted proteins in this publicly deposited validated multiplexed panel may be of use for research applications in cancer, cellular stress, neurology, cardiology, and metabolism.

Quantitative Proteomics on Immune Cells of ME/CFS Patients Using SWATH-MS

Proteomics is one of the "omics" disciplines that has provided molecular insights into the pathophysiology of myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). Here we describe a complete SWATH-MS workflow for the quantitative profiling of proteins extracted from peripheral mononuclear blood cells to investigate proteomic alterations in ME/CFS. This workflow covers all steps of sample preparation, data acquisition, and data analysis. We describe the process of generating a comprehensive spectral library from a pre-fractionated peptide reference sample followed by the acquisition of DIA data sets of individual samples using a 5600+ TripleTOF mass spectrometer. Examples of both library-based and library-free data analysis pipelines are presented based on the PeakView/MarkerView software package (commercial) and DIA-NN (free) software respectively.

Quantitative protein mass spectrometry for multiplex measurement of coagulation and fibrinolytic proteins towards clinical application: What, why and how?

Plasma proteins involved in coagulation and fibrinolysis are essential to hemostasis. Consequently, their circulating levels and functionality are critical in bleeding and thrombosis development. Well-established laboratory tests to assess these are available; however, said tests do not allow high multiplicity, require large volumes of plasma and are often costly. A novel technology to quantify plasma proteins is quantitative protein mass spectrometry (QPMS). Aided by stable isotope-labeled internal standards a large number of proteins can be quantified in one single analytical run requiring <30 μL of plasma. This provides an opportunity to improve insight in the etiology and prognosis of bleeding and thrombotic disorders, in which the balance between different proteins plays a crucial role. This manuscript aims to give an overview of the QPMS potential applications in thrombosis and hemostasis research (quantifying the 38 proteins assigned to coagulation and fibrinolysis by the KEGG database), but also to explore the potential and hurdles if designed for clinical practice. Advantages and limitations of QPMS are described and strategies for improved analysis are proposed, using as an example the test requirements for antithrombin. Application of this technology in the future could represent a step towards individualized patient care.

Delineating protein biomarkers for gastric cancers: A catalogue of mass spectrometry-based markers and assessment of their suitability for targeted proteomics applications

Gastric cancer (GC) is a global health concern. To facilitate improved management of GCs, protein biomarkers have been identified through mass spectrometry-based proteomics platforms. In order to exhibit clinical utility of such data, we congregated over 6800 differentially regulated proteins in GCs from proteomics studies and recorded the mass spectrometry platforms, association of the protein with infectious agents, protein identifiers, sample size and clinical characters of samples used with details on validation. Development of targeted proteomics methods is the cornerstone for pursuing these markers into clinical utility. Therefore, we developed Protein Biomarker Matrix for Gastric Cancer (PBMGC), a simple catalogue of robustness of each protein. This analysis yielded the identification of robust tissue, serum, and urine diagnostic and prognostic protein biomarker panels which can be further tested for their clinical utility. We also ascertained proteotypic tryptic peptides of 5631 proteins suitable for developing multiple reaction monitoring (MRM) assays. Extensive characterization of these peptides was carried out to record peptide ions, mass/charge and enhanced specific peptide features. With the vision of catering to proteomics researchers, the data generated through this analysis has been catalogued at Gastric Cancer Proteomics DataBase (GCPDB) (https://ciods.in/gcpdb/). Users can browse and download the data and improve GCPDB by submitting recently published data. SIGNIFICANCE: Mass spectrometry-based proteomics platforms have accumulated substantial data on proteins differentially regulated in gastric cancer (GC) clinical samples. The utility of such data in clinical applications is limited by search for suitable biomarker panels for assessment of GCs. We assembled over 6800 differentially regulated proteins in GCs from proteomics studies and recorded the corresponding details including mass spectrometry platforms, status on the association of the protein with infectious agents, protein identifiers from different databases, sample size and clinical characters of samples used in test and control conditions along with details on their validation. Towards the vision of utilizing these markers in clinical assays, Protein Biomarker Matrix for Gastric Cancer (PBMGC) was developed and clinically relevant multi-protein panels were identified. We also demonstrated identification and characterization of tryptic proteotypic tryptic peptides of 5631 proteins biomarkers of GCs which are suitable for development of MRM assays in a SCIEX QTRAP instrument. Aimed to caterproteomics researchers, the data generated through this analysis has been catalogued at Gastric Cancer Proteomics DataBase (GCPDB) (https://ciods.in/gcpdb/). The users can browse and download details on different markers and improve GCPDB by submitting recently published data. Such an analysis could lay a cornerstone for building more such resources or conduct such analysis in different clinical conditions to uptake and develop targeted proteomics as the method of choice for clinical applications.

Establishment of a targeted proteomics method for the quantification of collagen chain: Revealing the chain stoichiometry of heterotypic collagen fibrils in sea cucumber

Collagen is the most abundant and important structural biomacromolecule in sea cucumbers. The sea cucumber collagen fibrils were previously confirmed to be heterotypic, nevertheless, the stoichiometry of collagen α-chains governing the complexity of collagen fibrils is still poorly understood. Herein, four representative collagen α-chains in sea cucumber including two clade A fibrillar collagens, one clade B fibrillar collagen, and one fibril-associated collagen with interrupted triple helices were selected. After the screening of signature peptides and optimization of multiple reaction monitoring (MRM) acquisition parameters including fragmentation, collision energy, and ion transition, a feasible MRM-based method was established. Consequently, the stoichiometry of the four collagen chains was determined to be approximately 100:54:3:4 based on the method. The assembly forms of sea cucumber collagen fibrils were further hypothesized according to the chain stoichiometry. This study facilitated the quantification of collagen and understanding of the collagen constituents in sea cucumber.

Proteomic Evolution from Acute to Post-COVID-19 Conditions

Many COVID-19 survivors have post-COVID-19 conditions, and females are at a higher risk. We sought to determine (1) how protein levels change from acute to post-COVID-19 conditions, (2) whether females have a plasma protein signature different from that of males, and (3) which biological pathways are associated with COVID-19 when compared to restrictive lung disease. We measured protein levels in 74 patients on the day of admission and at 3 and 6 months after diagnosis. We determined protein concentrations by multiple reaction monitoring (MRM) using a panel of 269 heavy-labeled peptides. The predicted forced vital capacity (FVC) and diffusing capacity of the lungs for carbon monoxide (DLCO) were measured by routine pulmonary function testing. Proteins associated with six key lipid-related pathways increased from admission to 3 and 6 months; conversely, proteins related to innate immune responses and vasoconstriction-related proteins decreased. Multiple biological functions were regulated differentially between females and males. Concentrations of eight proteins were associated with FVC, %, and they together had c-statistics of 0.751 (CI:0.732-0.779); similarly, concentrations of five proteins had c-statistics of 0.707 (CI:0.676-0.737) for DLCO, %. Lipid biology may drive evolution from acute to post-COVID-19 conditions, while activation of innate immunity and vascular regulation pathways decreased over that period. (ProteomeXchange identifiers: PXD041762, PXD029437).

Multiple reaction monitoring assays for large-scale quantitation of proteins from 20 mouse organs and tissues

Mouse is the mammalian model of choice to study human health and disease due to its size, ease of breeding and the natural occurrence of conditions mimicking human pathology. Here we design and validate multiple reaction monitoring mass spectrometry (MRM-MS) assays for quantitation of 2118 unique proteins in 20 murine tissues and organs. We provide open access to technical aspects of these assays to enable their implementation in other laboratories, and demonstrate their suitability for proteomic profiling in mice by measuring normal protein abundances in tissues from three mouse strains: C57BL/6NCrl, NOD/SCID, and BALB/cAnNCrl. Sex- and strain-specific differences in protein abundances are identified and described, and the measured values are freely accessible via our MouseQuaPro database: http://mousequapro.proteincentre.com . Together, this large library of quantitative MRM-MS assays established in mice and the measured baseline protein abundances represent an important resource for research involving mouse models.

Simultaneous detection of glycinin and β-conglycinin in processed soybean products by high-performance liquid chromatography-tandem mass spectrometry with stable isotope-labeled standard peptides

Glycinin and β-conglycinin are the two main allergic proteins in soybean. Due to their complex structures and lack of protein standards, it is difficult to achieve quantitative determination of these proteins in soybeans. In this study, an HPLC-MS/MS method was developed for the simultaneous determination of five subunits of glycinin (G1, G2, G3, G4, and G5) and three subunits of β-conglycinin (α, α', and β) in processed soybean products based on 8 specific peptides and their stable isotope-labeled peptides. Here, each specific peptide was derived from one of the above 8 subunits. When soy protein was extracted and digested with trypsin, 8 specific peptides, and corresponding stable isotope-labeled peptides were analyzed by HPLC-MS/MS. The linear range for the specific peptides was between 3.2 and 1000 ng/mL (R2 > 0.9955). The recoveries of added peptides ranged from 83.4% to 117.8%, and the intra-day precisions (% CV) were below 17.4%. The limit of quantification of each subunit of glycinin and β-conglycinin in processed soybean products (in terms of protein amount) was between 15.1 and 156.1 g/g. This method was successfully applied to the analysis of 8 subunits of glycinin and β-conglycinin in 68 different processed soybean products, which provides technical support for processed product quality evaluation and monitoring soybean processing technology.

Assessment and Prediction of Human Proteotypic Peptide Stability for Proteomics Quantification

Mass spectrometry coupled to liquid chromatography is one of the most powerful technologies for proteome quantification in biomedical samples. In peptide-centric workflows, protein mixtures are enzymatically digested to peptides prior their analysis. However, proteome-wide quantification studies rarely identify all potential peptides for any given protein, and targeted proteomics experiments focus on a set of peptides for the proteins of interest. Consequently, proteomics relies on the use of a limited subset of all possible peptides as proxies for protein quantitation. In this work, we evaluated the stability of the human proteotypic peptides during 21 days and trained a deep learning model to predict peptide stability directly from tryptic sequences, which together constitute a resource of broad interest to prioritize and select peptides in proteome quantification experiments.

A single protein to multiple peptides: Investigation of protein-peptide correlations using targeted alpha-2-macroglobulin analysis

Recent advances in proteomics technologies have enabled the analysis of thousands of proteins in a high-throughput manner. Mass spectrometry (MS) based proteomics uses a peptide-centric approach where biological samples undergo specific proteolytic digestion and then only unique peptides are used for protein identification and quantification. Considering the fact that a single protein may have multiple unique peptides and a number of different forms, it becomes essential to understand dynamic protein-peptide relationships to ensure robust and reliable peptide-centric protein analysis. In this study, we investigated the correlation between protein concentration and corresponding unique peptide responses under a conventional proteolytic digestion condition. Protein-peptide correlation, digestion efficiency, matrix-effect, and concentration-effect were evaluated. Twelve unique peptides of alpha-2-macroglobulin (A2MG) were monitored using a targeted MS approach to acquire insights into protein-peptide dynamics. Although the peptide responses were reproducible between replicates, protein-peptide correlation was moderate in protein standards and low in complex matrices. The results suggest that reproducible peptide signal could be misleading in clinical studies and a peptide selection could dramatically change the outcome at protein level. This is the first study investigating quantitative protein-peptide correlations in biological samples using all unique peptides representing the same protein and opens a discussion on peptide-based proteomics.

Absolute Quantitative Targeted Proteomics Assays for Plasma Proteins

Preclinical and clinical trials require rapid, precise, and multiplexed analytical methods to characterize the complex samples and to allow high-throughput biomarker monitoring with low consumption of sample material. Targeted proteomics has been used to address these challenges when quantifying protein abundances in complex biological matrices. In many of these studies, blood plasma is collected either as the main research or diagnostic sample or in combination with other specimens. Mass spectrometry (MS)-based targeted proteomics using multiple reaction monitoring (MRM) or parallel reaction monitoring (PRM) with stable isotope-labeled internal standard (SIS) peptides allows robust characterization of blood plasma protein via absolute quantification. Compared to other commonly used technologies like enzyme-linked immunosorbent assay (ELISA), targeted proteomics is faster, more sensitive, and more cost-effective. Here we describe a protocol for the quantification of proteins in blood plasma using targeted MRM proteomics with heavy-labeled internal standards. The 270-protein panel allows rapid and robust absolute quantitative proteomic characterization of blood plasma in a 1 h gradient. The method we describe here works for non-depleted plasma, which makes it simple and easy to implement. Moreover, the protocol works with the two most commonly used blood plasma collection methods used in practice, namely, either K₂EDTA or sodium citrate as anticoagulants.

Bioinformatics Tools and Knowledgebases to Assist Generating Targeted Assays for Plasma Proteomics

In targeted proteomics experiments, selecting the appropriate proteotypic peptides as surrogate for the target protein is a crucial pre-acquisition step. This step is largely a bioinformatics exercise that involves integrating information on the peptides and proteins and using various software tools and knowledgebases. We present here a few resources that automate and simplify the selection process to a great degree. These tools and knowledgebases were developed primarily to streamline targeted proteomics assay development and include PeptidePicker, PeptidePickerDB, MRMAssayDB, MouseQuaPro, and PeptideTracker. We have used these tools to develop and document thousands of targeted proteomics assays, many of them for plasma proteins with focus on human and mouse. An important aspect in all these resources is the integrative approach on which they are based. Using these tools in the first steps of designing a singleplexed or multiplexed targeted proteomic experiment can reduce the necessary experimental steps tremendously. All the tools and knowledgebases we describe here are Web-based and freely accessible so scientists can query the information conveniently from the browser. This chapter provides an overview of these software tools and knowledgebases, their content, and how to use them for targeted plasma proteomics. We further demonstrate how to use them with the results of the HUPO Human Plasma Proteome Project to produce a new database of 3.8 k targeted assays for known human plasma proteins. Upon experimental validation, these assays should help in the further quantitative characterizing of the plasma proteome.

Typic: A Practical and Robust Tool to Rank Proteotypic Peptides for Targeted Proteomics

The selection of a suitable proteotypic peptide remains a challenge for designing a targeted quantitative proteomics assay. Although the criteria are well-established in the literature, the selection of these peptides is often performed in a subjective and time-consuming manner. Here, we have developed a practical and semiautomated workflow implemented in an open-source program named Typic. Typic is designed to run in a command line and a graphical interface to help selecting a list of proteotypic peptides for targeted quantitation. The tool combines the input data and downloads additional data from public repositories to produce a file per protein as output. Each output file includes relevant information to the selection of proteotypic peptides organized in a table, a colored ranking of peptides according to their potential value as targets for quantitation and auxiliary plots to assist users in the task of proteotypic peptides selection. Taken together, Typic leads to a practical and straightforward data extraction from multiple data sets, allowing the identification of most suitable proteotypic peptides based on established criteria, in an unbiased and standardized manner, ultimately leading to a more robust targeted proteomics assay.

Development of Tier 2 LC-MRM-MS protein quantification methods for liquid biopsies

In the pursuit of personalized diagnostics and tailored treatments, quantitative protein tests contribute to a more precise definition of health and disease. The development of new quantitative protein tests should be driven by an unmet clinical need and performed in a collaborative effort that involves all stakeholders. With regard to the analytical part, mass spectrometry (MS)-based platforms are an excellent tool for quantification of specific proteins in body fluids, for example focused on cancer. The obtained readouts have great potential in determining tumor aggressiveness to facilitate treatment decisions, and can furthermore be used to monitor patient response. Internationally standardized TNM classifications of malignant tumors are beneficial for diagnosis, however treatment outcome and survival of cancer patients is poorly predicted. To this end, the importance of the tumor microenvironment has endorsed the introduction of the tumor-stroma ratio as a prognostic parameter in solid primary tumor types. Currently, the stromal content of tumor tissues is determined via routine diagnostic pathology slides. With the development of liquid chromatography (LC)-MS methods we aim at quantification of tumor-stroma specific proteins in body fluids. In this mini-review the analytical aspect of this developmental trajectory is further detailed.

Early Prediction of COVID-19 Patient Survival by Targeted Plasma Multi-Omics and Machine Learning

The recent surge of coronavirus disease 2019 (COVID-19) hospitalizations severely challenges healthcare systems around the globe and has increased the demand for reliable tests predictive of disease severity and mortality. Using multiplexed targeted mass spectrometry assays on a robust triple quadrupole MS setup which is available in many clinical laboratories, we determined the precise concentrations of hundreds of proteins and metabolites in plasma from hospitalized COVID-19 patients. We observed a clear distinction between COVID-19 patients and controls and, strikingly, a significant difference between survivors and nonsurvivors. With increasing length of hospitalization, the survivors' samples showed a trend toward normal concentrations, indicating a potential sensitive readout of treatment success. Building a machine learning multi-omic model that considers the concentrations of 10 proteins and five metabolites, we could predict patient survival with 92% accuracy (area under the receiver operating characteristic curve: 0.97) on the day of hospitalization. Hence, our standardized assays represent a unique opportunity for the early stratification of hospitalized COVID-19 patients.

Absolute protein quantitation of the mouse macrophage Toll-like receptor and chemotaxis pathways

The Toll-like receptor (TLR) and chemotaxis pathways are key components of the innate immune system. Subtle variation in the concentration, timing, and molecular structure of the ligands are known to affect downstream signaling and the resulting immune response. Computational modeling and simulation at the molecular interaction level can be used to study complex biological pathways, but such simulations require protein concentration values as model parameters. Here we report the development and application of targeted mass spectrometry assays to measure the absolute abundance of proteins of the mouse macrophage Toll-like receptor 4 (TLR4) and chemotaxis pathways. Two peptides per protein were quantified, if possible. The protein abundance values ranged from 1,332 to 227,000,000 copies per cell. They moderately correlated with transcript abundance values from a previously published mouse macrophage RNA-seq dataset, and these two datasets were combined to make proteome-wide abundance estimates. The datasets produced during this investigation can be used for pathway modeling and simulation, as well as for other studies of the TLR and chemotaxis pathways.

Measurement(s)	molecules per cell
Technology Type(s)	nanoflow high-performance liquid chromatography-electrospray ionisation tandem mass spectrometry
Sample Characteristic - Organism	Mus musculus

Longitudinal Plasma Proteomics Analysis Reveals Novel Candidate Biomarkers in Acute COVID-19

The host response to COVID-19 pathophysiology over the first few days of infection remains largely unclear, especially the mechanisms in the blood compartment. We report on a longitudinal proteomic analysis of acute-phase COVID-19 patients, for which we used blood plasma, multiple reaction monitoring with internal standards, and data-independent acquisition. We measured samples on admission for 49 patients, of which 21 had additional samples on days 2, 4, 7, and 14 after admission. We also measured 30 externally obtained samples from healthy individuals for comparison at baseline. The 31 proteins differentiated in abundance between acute COVID-19 patients and healthy controls belonged to acute inflammatory response, complement activation, regulation of inflammatory response, and regulation of protein activation cascade. The longitudinal analysis showed distinct profiles revealing increased levels of multiple lipid-associated functions, a rapid decrease followed by recovery for complement activation, humoral immune response, and acute inflammatory response-related proteins, and level fluctuation in the regulation of smooth muscle cell proliferation, secretory mechanisms, and platelet degranulation. Three proteins were differentiated between survivors and nonsurvivors. Finally, increased levels of fructose-bisphosphate aldolase B were determined in patients with exposure to angiotensin receptor blockers versus decreased levels in those exposed to angiotensin-converting enzyme inhibitors. Data are available via ProteomeXchange PXD029437.

Targeted proteomics for evaluating risk of venous thrombosis following traumatic lower-leg injury or knee arthroscopy

INTRODUCTION

Patients with lower-leg cast immobilization and patients undergoing knee arthroscopy have an increased risk of venous thrombosis (VT). Guidelines are ambiguous about thromboprophylaxis use, and individual risk factors for developing VT are often ignored. To assist in VT risk stratification and guide thromboprophylaxis use, various prediction models have been developed. These models depend largely on clinical factors and provide reasonably good C-statistics of around 70%. We explored using protein levels in blood plasma measured by multiplexed quantitative targeted proteomics to predict VT. Our aim was to assess whether a VT risk prediction model based on absolute plasma protein quantification is possible.

METHODS

We used internal standards to quantify proteins in less than 10 μl plasma. We measured 270 proteins in samples from patients scheduled for knee arthroscopy or with lower-leg cast immobilization. The two prospective POT-(K)CAST trails allow complementary views of VT signature in blood, namely pre and post trauma, respectively. From approximately 3000 patients, 31 patients developed VT who were included and matched with double the number of controls.

RESULTS

Top discriminating proteins between cases and controls included APOC3, APOC4, APOC2, ATRN, F13B, and F2 in knee arthroscopy patients and APOE, SERPINF2, B2M, F13B, AFM, and C1QC in patients with lower-leg cast. A logistic regression model with cross-validation resulted in C-statistics of 88.1% (95% CI: 85.7-90.6%) and 79.6% (95% CI: 77.2-82.0%) for knee arthroscopy and cast immobilization groups respectively.

CONCLUSIONS

Promising C-statistics merit further exploration of the value of proteomic tests for predicting VT risk upon additional validation.

Diagnosing pleural effusions using mass spectrometry-based multiplexed targeted proteomics quantitating mid- to high-abundance markers of cancer, infection/inflammation and tuberculosis

Pleural effusion (PE) is excess fluid in the pleural cavity that stems from lung cancer, other diseases like extra-pulmonary tuberculosis (TB) and pneumonia, or from a variety of benign conditions. Diagnosing its cause is often a clinical challenge and we have applied targeted proteomic methods with the aim of aiding the determination of PE etiology. We developed a mass spectrometry (MS)-based multiple reaction monitoring (MRM)-protein-panel assay to precisely quantitate 53 established cancer-markers, TB-markers, and infection/inflammation-markers currently assessed individually in the clinic, as well as potential biomarkers suggested in the literature for PE classification. Since MS-based proteomic assays are on the cusp of entering clinical use, we assessed the merits of such an approach and this marker panel based on a single-center 209 patient cohort with established etiology. We observed groups of infection/inflammation markers (ADA2, WARS, CXCL10, S100A9, VIM, APCS, LGALS1, CRP, MMP9, and LDHA) that specifically discriminate TB-PEs and other-infectious-PEs, and a number of cancer markers (CDH1, MUC1/CA-15-3, THBS4, MSLN, HPX, SVEP1, SPINT1, CK-18, and CK-8) that discriminate cancerous-PEs. Some previously suggested potential biomarkers did not show any significant difference. Using a Decision Tree/Multiclass classification method, we show a very good discrimination ability for classifying PEs into one of four types: cancerous-PEs (AUC: 0.863), tuberculous-PEs (AUC of 0.859), other-infectious-PEs (AUC of 0.863), and benign-PEs (AUC: 0.842). This type of approach and the indicated markers have the potential to assist in clinical diagnosis in the future, and help with the difficult decision on therapy guidance.

Multiple reaction monitoring-mass spectrometry enables robust quantitation of plasma proteins regardless of whole blood processing delays that may occur in the clinic

Plasma is an important biofluid for clinical research and diagnostics. In the clinic, unpredictable delays—from minutes to hours—between blood collection and plasma generation are often unavoidable. These delays can potentially lead to protein degradation and modification and might considerably affect intact protein measurement methods such as sandwich enzyme-linked immunosorbent assays that bind proteins on two epitopes to increase specificity, thus requiring largely intact protein structures. Here, we investigated, using multiple reaction monitoring mass spectrometry (MRM-MS), how delays in plasma processing affect peptide-centric “bottom-up” proteomics. We used validated assays for proteotypic peptide surrogates of 270 human proteins to analyze plasma generated after whole blood had been kept at room temperature from 0 to 40 h to mimic delays that occur in the clinic. Moreover, we evaluated the impact of different plasma-thawing conditions on MRM-based plasma protein quantitation. We demonstrate that >90% of protein concentration measurements were unaffected by the thawing procedure and by up to 40-h delayed plasma generation, reflected by relative standard deviations (RSDs) of <30%. Of the 159 MRM assays that yielded quantitative results in 60% of the measured time points, 139 enabled a stable protein quantitation (RSD <20%), 14 showed a slight variation (RSD 20–30%), and 6 appeared unstable/irreproducible (RSD > 30%). These results demonstrate the high robustness and thus the potential for MRM-based plasma-protein quantitation to be used in a clinical setting. In contrast to enzyme-linked immunosorbent assay, peptide-based MRM assays do not require intact three-dimensional protein structures for an accurate and precise quantitation of protein concentrations in the original sample.

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Delays in whole blood processing often cannot be avoided in the clinic.

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These delays might affect measurements by intact protein assays such as ELISA.

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The impact on LC/MRM was evaluated using validated assays to quantify 270 proteins.

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>95% of the measured concentrations had RSDs <30% between delays of 0 to 40 h.

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Protein quantitation by LC/MRM-MS is robust against pitfalls in the clinical setting.

Immuno-MALDI-MS for Accurate Quantitation of Targeted Peptides from Volume-Restricted Samples

The immuno-MALDI-MS method can be used to quantify low-abundance proteins from clinical samples that offer only a limited amount of material for analysis. An internal standard, in the form of a stable isotope-labeled peptide, is used to ensure reproducible and absolute quantitation. The protocol described here was optimized for the quantitation of AKT1 and AKT2, but we offer instructions on how to adapt the method to target other proteins. The described workflow is compatible with automation via a liquid handling robot for high-throughput applications.

Peptide Charge Derivatization as a Tool for Early Detection of Preeclampsia by Mass Spectrometry-A Comparison with the ELISA Test

Early detection of any preeclampsia biomarkers may lower the risk of mortality, both for a mother and a child. Our study focuses on techniques for preeclampsia biomarker identification by comparing the results of a method using liquid chromatography mass spectrometry in multiple reaction monitoring mode (LC-MS/MS) with those by the enzyme-linked immunosorbent assay (ELISA) test, as well as by comparing the obtained results with clinical data. In the proposed LC-MS/MS method a tryptic digest peptide charge derivatization strategy was used as a tool for sensitive detection of podocin, i.e., a previously discovered preeclampsia biomarker present in urine samples from pregnant women. Urine samples from pregnant women with diagnosed preeclampsia were collected at different stages of pregnancy and from healthy subjects, and then were analyzed by ELISA test and the proposed method with LC-MS/MS. Charge derivatization of the ε amino group of C-terminal lysine residues in tryptic digests by 2,4,6-triphenylpyrylium salt was performed to increase the ionization efficiency in the LC-MS/MS mode. Podocin was identified at the early stage of pregnancy, while its detection using an ELISA test was not possible. The protocol for urine sample preparation was optimized. Our results show that the proposed method by LC-MS/MS in combination with peptide charge derivatization, provides an ultrasensitive tool for diagnosis of preeclampsia, and provides earlier detection than a clinical diagnosis or ELISA test. The proposed solution may revolutionize medical diagnostics.

Versatile and multiplexed mass spectrometry-based absolute quantification with cell-free-synthesized internal standard peptides

Preparation of stable isotope-labeled internal standard peptides is crucial for mass spectrometry (MS)-based targeted proteomics. Herein, we developed versatile and multiplexed absolute protein quantification method using MS. A previously developed method based on the cell-free peptide synthesis system, termed MS-based quantification by isotope-labeled cell-free products (MS-QBiC), was improved for multiple peptide synthesis in one-pot reaction. We pluralized the quantification tags used for the quantification of synthesized peptides and thus, made it possible to use cell-free synthesized isotope-labeled peptides as mixtures for the absolute quantification. The improved multiplexed MS-QBiC method was proved to be applied to clarify ribosomal proteins stoichiometry in the ribosomal subunit, one of the largest cellular complexes. The study demonstrates that the developed method enables the preparation of several dozens and even several hundreds of internal standard peptides within a few days for quantification of multiple proteins with only a single-run of MS analysis. SIGNIFICANCE: The developed method can be applied for the preparation of internal standard peptides without limiting the number of peptides to be synthesized, which may result in more practical screening of quantitatively reliable peptides, one of the fundamental steps in the reliable absolute quantification using MS. Furthermore, the method is highly versatile for proteome analysis of any organisms or species without any cDNA or SIL peptide libraries. The quantification can be finished in a few days including design and preparation of appropriate SIL peptides using small-scale batch cell-free reactions, which has a potential to be a part of the standard methodology in a field of quantitative proteomics.

Precise Quantitation of PTEN by Immuno-MRM: A Tool To Resolve the Breast Cancer Biomarker Controversy

The tumor suppressor PTEN is the main negative regulator of PI3K/AKT/mTOR signaling and is commonly found downregulated in breast cancer (BC). Conflicting data from conventional immunoassays such as immunohistochemistry (IHC) has sparked controversy about PTEN's role as a prognostic and predictive biomarker in BC, which can be largely attributed to the lack of specificity, sensitivity, and interlaboratory standardization. Here, we present a fully standardized, highly sensitive, robust microflow immuno-MRM (iMRM) assay that enables precise quantitation of PTEN concentrations in cells and fresh frozen (FF) and formalin-fixed paraffin-embedded (FFPE) tissues, down to 0.1 fmol/10 μg of extracted protein, with high interday and intraday precision (CV 6.3%). PTEN protein levels in BC PDX samples that were determined by iMRM correlate well with semiquantitative IHC and WB data. iMRM, however, allowed the precise quantitation of PTEN-even in samples that were deemed to be PTEN negative by IHC or western blot (WB)-while requiring substantially less tumor tissue than WB. This is particularly relevant because the extent of PTEN downregulation in tumors has been shown to correlate with severity. Our standardized and robust workflow includes an 11 min microflow LC-MRM analysis on a triple-quadrupole MS and thus provides a much needed tool for the study of PTEN as a potential biomarker for BC.

Proteomic Portraits Reveal Evolutionarily Conserved and Divergent Responses to Spinal Cord Injury

Despite the emergence of promising therapeutic approaches in preclinical studies, the failure of large-scale clinical trials leaves clinicians without effective treatments for acute spinal cord injury (SCI). These trials are hindered by their reliance on detailed neurological examinations to establish outcomes, which inflate the time and resources required for completion. Moreover, therapeutic development takes place in animal models whose relevance to human injury remains unclear. Here, we address these challenges through targeted proteomic analyses of cerebrospinal fluid and serum samples from 111 patients with acute SCI and, in parallel, a large animal (porcine) model of SCI. We develop protein biomarkers of injury severity and recovery, including a prognostic model of neurological improvement at 6 months with an area under the receiver operating characteristic curve of 0.91, and validate these in an independent cohort. Through cross-species proteomic analyses, we dissect evolutionarily conserved and divergent aspects of the SCI response and establish the cerebrospinal fluid abundance of glial fibrillary acidic protein as a biochemical outcome measure in both humans and pigs. Our work opens up new avenues to catalyze translation by facilitating the evaluation of novel SCI therapies, while also providing a resource from which to direct future preclinical efforts.

• Targeted proteomic analysis of CSF and serum samples from 111 acute SCI patients.

• Single- and multiprotein biomarkers of injury severity and recovery.

• Parallel proteomic analysis in a large animal model identifies conserved biomarkers.

• Evolutionary conservation and divergence of the proteomic response to SCI.

Analysis and comparison of key proteins in Maiwa yak and bovine milk using high-performance liquid chromatography mass spectrometry

Yak milk is an essential and predominant food resource for Tibetan people for subsistence purposes and to combat altitude-induced challenges. Due to its unique qualities, yak milk has recently been gaining broader attention from consumers across China as well in other parts of the world. One of the key characteristics of yak milk is the protein content, which is about 40 to 60% higher than that of native bovine milk. In this work, a sensitive and reproducible high-throughput analytical method was developed employing both ultra high-performance liquid chromatography Orbitrap (Thermo Fisher Scientific) high-resolution accurate mass spectroscopy (UHPLC-HRAM-MS) and UHPLC coupled with triple quadrupole tandem MS (UHPLC-QqQ-MS) to simultaneously analyze 8 milk proteins. A total of 15 Maiwa yak milk samples and 15 bovine milk samples were qualitatively and quantitatively analyzed using targeted proteomics and compared for α-lactalbumin, β-lactoglobulin, α_S1-casein, α_S2-casein, β-casein, κ-casein, lactoferrin, and osteopontin. Peptides of β-lactoglobulin were used to specifically distinguish yak and bovine milk. The results showed that this novel detection method could quantitatively detect these major and minor milk proteins with >0.99 linear correlation coefficient and a recovery rate between 90 and 120%, with relative standard deviations typically less than 10%. The data revealed that yak milk not only had higher overall milk protein content than bovine milk but higher lactoferrin and osteopontin contents as well. The lactoferrin content of yak milk was about 30% higher than that of bovine milk, and the osteopontin content of yak milk was nearly twice that of bovine milk. The application of this method demonstrates that UHPLC-HRAM-MS and UHPLC-QqQ-MS are suitable for high-throughput qualitative and quantitative analysis of major and minor proteins of yak and bovine milk.

Proteotyping of knockout mouse strains reveals sex- and strain-specific signatures in blood plasma

We proteotyped blood plasma from 30 mouse knockout strains and corresponding wild-type mice from the International Mouse Phenotyping Consortium. We used targeted proteomics with internal standards to quantify 375 proteins in 218 samples. Our results provide insights into the manifested effects of each gene knockout at the plasma proteome level. We first investigated possible contamination by erythrocytes during sample preparation and labeled, in one case, up to 11 differential proteins as erythrocyte originated. Second, we showed that differences in baseline protein abundance between female and male mice were evident in all mice, emphasizing the necessity to include both sexes in basic research, target discovery, and preclinical effect and safety studies. Next, we identified the protein signature of each gene knockout and performed functional analyses for all knockout strains. Further, to demonstrate how proteome analysis identifies the effect of gene deficiency beyond traditional phenotyping tests, we provide in-depth analysis of two strains, C8a-/- and Npc2+/-. The proteins encoded by these genes are well-characterized providing good validation of our method in homozygous and heterozygous knockout mice. Ig alpha chain C region, a poorly characterized protein, was among the differentiating proteins in C8a-/-. In Npc2+/- mice, where histopathology and traditional tests failed to differentiate heterozygous from wild-type mice, our data showed significant difference in various lysosomal storage disease-related proteins. Our results demonstrate how to combine absolute quantitative proteomics with mouse gene knockout strategies to systematically study the effect of protein absence. The approach used here for blood plasma is applicable to all tissue protein extracts.

Detailed Method for Performing the ExSTA Approach in Quantitative Bottom-Up Plasma Proteomics

The use of stable isotope-labeled standards (SIS) is an analytically valid means of quantifying proteins in biological samples. The nature of the labeled standards and their point of insertion in a bottom-up proteomic workflow can vary, with quantification methods utilizing curves in analytically sound practices. A promising quantification strategy for low sample amounts is external standard addition (ExSTA). In ExSTA, multipoint calibration curves are generated in buffer using serially diluted natural (NAT) peptides and a fixed concentration of SIS peptides. Equal concentrations of SIS peptides are spiked into experimental sample digests, with all digests (control and experimental) subjected to solid-phase extraction prior to liquid chromatography tandem mass spectrometry (LC-MS/MS) analysis. Endogenous peptide concentrations are then determined using the regression equation of the standard curves. Given the benefits of ExSTA in large-scale analysis, a detailed protocol is provided herein for quantifying a multiplexed panel of 125 high-to-moderate abundance proteins in undepleted and non-enriched human plasma samples. The procedural details and recommendations for successfully executing all phases of this quantification approach are described. As the proteins have been putatively correlated with various noncommunicable diseases, quantifying these by ExSTA in large-scale studies should help rapidly and precisely assess their true biomarker efficacy.

An Update on MRMAssayDB: A Comprehensive Resource for Targeted Proteomics Assays in the Community

Precise multiplexed quantification of proteins in biological samples can be achieved by targeted proteomics using multiple or parallel reaction monitoring (MRM/PRM). Combined with internal standards, the method achieves very good repeatability and reproducibility enabling excellent protein quantification and allowing longitudinal and cohort studies. A laborious part of performing such experiments lies in the preparation steps dedicated to the development and validation of individual protein assays. Several public repositories host information on targeted proteomics assays, including NCI’s Clinical Proteomic Tumor Analysis Consortium assay portals, PeptideAtlas SRM Experiment Library, SRMAtlas, PanoramaWeb, and PeptideTracker, with all offering varying levels of details. We introduced MRMAssayDB in 2018 as an integrated resource for targeted proteomics assays. The Web-based application maps and links the assays from the repositories, includes comprehensive up-to-date protein and sequence annotations, and provides multiple visualization options on the peptide and protein level. We have extended MRMAssayDB with more assays and extensive annotations. Currently it contains >828 000 assays covering >51 000 proteins from 94 organisms, of which >17 000 proteins are present in >2400 biological pathways, and >48 000 mapping to >21 000 Gene Ontology terms. This is an increase of about four times the number of assays since introduction. We have expanded annotations of interaction, biological pathways, and disease associations. A newly added visualization module for coupled molecular structural annotation browsing allows the user to interactively examine peptide sequence and any known PTMs and disease mutations, and map all to available protein 3D structures. Because of its integrative approach, MRMAssayDB enables a holistic view of suitable proteotypic peptides and commonly used transitions in empirical data. Availability: http://mrmassaydb.proteincentre.com.

Mouse Quantitative Proteomics Knowledgebase: reference protein concentration ranges in 20 mouse tissues using 5000 quantitative proteomics assays

Laboratory mouse is the most used animal model in biological research, largely due to its high conserved synteny with human. Researchers use mice to answer various questions ranging from determining a pathological effect of knocked out/in gene to understanding drug metabolism. Our group developed >5000 quantitative targeted proteomics assays for 20 mouse tissues and determined the concentration ranges of a total of more than 1600 proteins using heavy labelled internal standards. We describe here MouseQuaPro; a knowledgebase that hosts this collection of carefully curated experimental data. The Web-based application includes protein concentrations from >700 mouse tissue samples from three common research strains, corresponding to more than 200k experimentally determined concentrations. The knowledgebase integrates the assay and protein concentration information with their human orthologs, functional and molecular annotations, biological pathways, related human diseases, and known gene expressions. At its core are the protein concentration ranges, which provide insights into (dis)similarities between tissues, strains, and sexes. MouseQuaPro implements advanced search as well as filtering functionalities with a simple interface and interactive visualization. This information-rich resource provides an initial map of protein absolute concentration in mouse tissues and allows guided design of proteomics phenotyping experiments. The knowledgebase is available at mousequapro.proteincentre.com. (Reviewer access username and password: mousequapro_reviewer1234567).

Perspective on Proteomics for Virus Detection in Clinical Samples

One of the most widely used methods to detect an acute viral infection in clinical specimens is diagnostic real-time polymerase chain reaction. However, because of the COVID-19 pandemic, mass-spectrometry-based proteomics is currently being discussed as a potential diagnostic method for viral infections. Because proteomics is not yet applied in routine virus diagnostics, here we discuss its potential to detect viral infections. Apart from theoretical considerations, the current status and technical limitations are considered. Finally, the challenges that have to be overcome to establish proteomics in routine virus diagnostics are highlighted.

Quantitative determination of osteopontin in bovine, buffalo, yak, sheep and goat milk by Ultra-high performance liquid chromatography-tandem mass spectrometry and stable isotope dimethyl labeling

Osteopontin (OPN) is a multifunctional protein present in different tissues, body fluids and milk. Different milk has different level of OPN content. To determine the amount of osteopontin in bovine, buffalo, yak, sheep and goat milk, we developed an ultra-high performance liquid chromatography tandem mass spectrometry (UHPLC-MS/MS) method to detect an osteopontin signature peptide. The signature peptides selected by searching Uniprot database for trypsin digested osteopontin. The sample preparation procedure includes trypsin digestion, dimethyl labeling of tryptic peptides, purification and concentration of labeled tryptic peptide with solid phase extraction. The limit of detection and limit of quantification are 0.5 mg L^-1 and 2.0 mg L^-1, respectively. The method has satisfactory analytical performance with a linearity of R² ≥ 0.998, recoveries of 103.7-111.0%, and precision of 1.8-6.2%. It is also validated and successfully applied to quantifying osteopontin content in bovine, buffalo, yak, sheep and goat milk.

Evaluation of podocin in urine in horses using qualitative and quantitative methods

No sensitive method for diagnosing early kidney dysfunction in horses has been identified so far. Many studies carried out in humans and small animals show that podocin can be useful to diagnose various kidney diseases, mainly affecting the glomeruli. The aim of this study was to perform a qualitative and quantitative analysis of podocin in urine samples obtained from healthy horses, horses with clinical kidney dysfunction and horses at risk of acute kidney injury. The study objectives aimed to assess: (1) whether the selected podocin tryptic peptide for LC-MS-MRM allows for podocin detection in horse; and (2) whether the species-specific ELISA test makes this detection possible as well;, (3) whether the chosen methods are sensitive enough to detect kidney dysfunction and glomerular injury, (4) whether the results of the tests applying both methods correspond with one another, (5) whether the results correlate with the hematological and biochemical data. The signals that may indicate the presence of trypsin fragments of podocin were found in three healthy horses, all the horses diagnosed with kidney dysfunction and half of the animals at risk for acute kidney injury. The concentration of podocin, diagnosed with the ELISA test was as follows: from 0.19 to 1.2 ng/ml in healthy animals, from 0.19 to 20.0 ng/ml in AKI horses, from 0.29 to 5.71 ng/ml in horses at risk for acute kidney injury. The results of both methods corresponded significantly. Podocin may be a potential biomarker of clinical kidney disease in horses and may be used in the detection of glomerular injury. However, its use is limited by the possibility of physiological podocyturia. LC-MS-MRM seems to be a more sensitive method to evaluate the presence of podocin than the ELISA test, whilst selected tryptic peptides of podocin appear to apply to horses. The ELISA test showed greater effectiveness in excluding the disease than in confirming it.

Mass Spectrometry Techniques: Principles and Practices for Quantitative Proteomics

In the current omics-age of research, major developments have been made in technologies that attempt to survey the entire repertoire of genes, transcripts, proteins, and metabolites present within a cell. While genomics has led to a dramatic increase in our understanding of such things as disease morphology and how organisms respond to medications, it is critical to obtain information at the proteome level since proteins carry out most of the functions within the cell. The primary tool for obtaining proteome-wide information on proteins within the cell is mass spectrometry (MS). While it has historically been associated with the protein identification, developments over the past couple of decades have made MS a robust technology for protein quantitation as well. Identifying quantitative changes in proteomes is complicated by its dynamic nature and the inability of any technique to guarantee complete coverage of every protein within a proteome sample. Fortunately, the combined development of sample preparation and MS methods have made it capable of quantitatively comparing many thousands of proteins obtained from cells and organisms.

Systematic Optimization of the iMALDI Workflow for the Robust and Straightforward Quantification of Signaling Proteins in Cancer Cells

PURPOSE

Immuno-MALDI (iMALDI) combines immuno-enrichment of biomarkers with MALDI-MS for fast, precise, and specific quantitation, making it a valuable tool for developing clinical assays. iMALDI assays are optimized for the PI3-kinase signaling pathway members phosphatase and tensin homolog (PTEN) and PI3-kinase catalytic subunit alpha (p110α), with regard to sensitivity, robustness, and throughput. A standardized template for developing future iMALDI assays, including automation protocols to streamline assay development and translation, is provided.

EXPERIMENTAL DESIGN

Conditions for tryptic digestion and immuno-enrichment (beads, bead:antibody ratios, incubation times, direct vs. indirect immuno-enrichment) are rigorously tested. Different strategies for calibration and data readout are compared.

RESULTS

Digestion using 1:2 protein:trypsin (wt:wt) for 1 h yielded high and consistent peptide recoveries. Direct immuno-enrichment (antibody-bead coupling prior to antigen-enrichment) yielded 30% higher peptide recovery with a 1 h shorter incubation time than indirect enrichment. Immuno-enrichment incubation overnight yielded 1.5-fold higher sensitivities than 1 h incubation. Quantitation of the endogenous target proteins is not affected by the complexity of the calibration matrix, further simplifying the workflow.

CONCLUSIONS AND CLINICAL RELEVANCE

This optimized and automated workflow will facilitate the clinical translation of high-throughput sensitive iMALDI assays for quantifying cell-signaling proteins in individual tumor samples, thereby improving patient stratification for targeted treatment.

Detection of Podocin in Human Urine Sediment Samples by Charge Derivatization and LC-MS-MRM Method

Detection of podocytes in urine might serve as a useful diagnostic tool in both primary and secondary glomerular diseases. The utility of podocyturia has been confirmed for both pre-eclampsia and glomerulonephritis. Here, we present a new and sensitive method for qualitative LC-MS-multiple-reaction-monitoring (MRM) analysis of podocin, serving as a podocyturia biomarker in urine sediments. The following podocin tryptic peptides with the ¹⁶⁹LQTLEIPFHEIVTK¹⁸², ²¹³AVQFLVQTTMK²²³, ²⁴⁰SIAQDAK²⁴⁶, and ²⁹²MIAAEAEK²⁹⁹ sequences were applied as a model. The selective chemical derivatization of the ε amino group of C-terminal lysine residue in tryptic peptides, by 2,4,6-triphenylpyrylium salt (TPP) as a fixed charge tag, was employed to increase the ionization efficiency, in routine ESI-MS analysis. Additionally, the generation of a reporter ion, in the form of a protonated 2,4,6-triphenylpyridinium cation, makes the derivatized peptide analysis in the MRM mode unambiguous. Identification of derivatized and non-derivatized peptides were performed, and the obtained results suggest that the peptide with the ²⁹²MIAAEAEK²⁹⁹ sequence may serve as a marker of podocyturia.

Multiplexed MRM-based protein quantification of putative prognostic biomarkers for chronic kidney disease progression in plasma

Current diagnostic measures for Chronic Kidney Disease (CKD) include detection of reduced estimated glomerular filtration rate (eGFR) and albuminuria, which have suboptimal accuracies in predicting disease progression. The disease complexity and heterogeneity underscore the need for multiplex quantification of different markers. The goal of this study was to determine the association of six previously reported CKD-associated plasma proteins [B2M (Beta-2-microglobulin), SERPINF1 (Pigment epithelium-derived factor), AMBP (Protein AMBP), LYZ (Lysozyme C), HBB (Hemoglobin subunit beta) and IGHA1 (Immunoglobulin heavy constant alpha 1)], as measured in a multiplex format, with kidney function, and outcome. Antibody-free, multiple reaction monitoring mass spectrometry (MRM) assays were developed, characterized for their analytical performance, and used for the analysis of 72 plasma samples from a patient cohort with longitudinal follow-up. The MRM significantly correlated (Rho = 0.5–0.9) with results from respective ELISA. Five proteins [AMBP, B2M, LYZ, HBB and SERPINF1] were significantly associated with eGFR, with the three former also associated with unfavorable outcome. The combination of these markers provided stronger associations with outcome (p < 0.0001) compared to individual markers. Collectively, our study describes a multiplex assay for absolute quantification and verification analysis of previously described putative CKD prognostic markers, laying the groundwork for further use in prospective validation studies.

Peptide Selection for Accurate Targeted Protein Quantification via a Dimethylation High-Resolution Mass Spectrum Strategy with a Peptide Release Kinetic Model

A crucial step in accurate targeted protein quantification using targeted proteomics is to determine optimal proteotypic peptides representing targeted proteins. In this study, a workflow of peptide selection to determine proteotypic peptides using a dimethylation high-resolution mass spectrum strategy with a peptide release kinetic model was investigated and applied in peptide selection of bovine serum albumin. After specificity, digestibility, recovery, and stability evaluation of tryptic peptides in bovine serum albumin, the optimal proteotypic peptide was selected as LVNELTEFAK. The quantification method using LVNELTEFAK gave a linear range of 1-100 ppm with the coefficient greater than 0.9990, and the detection limit of bovine serum albumin in milk was 0.78 mg/kg. Compared with the proteotypic peptides selected by Skyline, the method showed a better performance in method validation. The workflow exhibited high comprehensiveness and efficiency in peptide selection, facilitating accurate targeted protein quantification in the food matrix, which lack protein standards.

The intestinal microbiome potentially affects thrombin generation in human subjects

BACKGROUND

The intestinal microbiome plays a versatile role in the etiology of arterial thrombosis. In venous thrombosis, driven chiefly by plasma coagulation, no such role has yet been established. We hypothesized that the intestinal microbiome composition affects coagulation in humans.

METHODS

We used healthy donor fecal microbiota transplant (FMT) to experimentally change the microbiome composition in metabolic syndrome patients. Thirty-five subjects were randomized in a blinded fashion to healthy donor FMT or autologous FMT as a control in a 2:1 ratio. We measured thrombin generation at baseline and after 6 weeks using automated calibrated thrombinography, and we determined plasma abundance of 32 coagulation related proteins using a targeted mass spectrometry-based quantitative proteomics assay with heavy labeled internal standards.

RESULTS

Healthy donor FMT prolonged the thrombinography lag time (median delta 0.0 versus 0.25 minutes, P = .039). The other thrombinography parameters showed no significant difference. Unsupervised cluster analysis suggested overall downregulation of coagulation related plasma proteins in subject clusters containing predominantly subjects that had a metabolic response to healthy donor FMT. FMT treatment status itself showed no clear clustering pattern with up- or downregulation, however, and proteins did not cluster according to an apparent biological grouping.

DISCUSSION

A single healthy donor FMT tends to modestly suppress the onset thrombin generation in metabolic syndrome patients, representing initial proof-of-principle that the intestinal microbiota composition might affect the coagulation system in humans. The findings merit external validation as a role for intestinal microbiota in coagulation can have clinically important implications.

Determination of the concentration range for 267 proteins from 21 lots of commercial human plasma using highly multiplexed multiple reaction monitoring mass spectrometry

Multiple reaction monitoring (MRM) is a key tool for biomarker validation and the translation of potential biomarkers into the clinic.

Evaluation of Tryptic Podocin Peptide in Urine Sediment Using LC-MS-MRM Method as a Potential Biomarker of Glomerular Injury in Dogs with Clinical Signs of Renal and Cardiac Disorders

The early asymptomatic stage of glomerular injury is a diagnostic challenge in the course of renal and extra-renal disease, e.g., heart insufficiency. It was found that podocin, a podocyte-specific protein present in the urine, may serve as a biomarker in the diagnosis of glomerular disease in humans and animals including glomerulonephritis, glomerulosclerosis, amyloidosis, or nephropathy. Therefore, there is a need of development of the sensitive and straightforward method of urinary podocin identification. In this work, we report our extended research under the glomerular injury investigation in dogs by application of clinical examination and LC-MS-MRM method in the identification of canine podocin in urine samples. The LC-MS-MRM method is based on the identification of podocin tryptic peptide with the ²¹⁸H-AAEILAATPAAVQLR-OH²³² sequence. The model peptide was characterized by the highest ionization efficiency of all the proposed model podocin tryptic peptides in a canine urine sediment according to the LC-MS/MS analysis. The obtained results revealed the presence of the model peptide in 40.9% of dogs with MMVD (active glomerular injury secondary to heart disease = cardiorenal syndrome-CRS) and 33.3% dogs with chronic kidney disease. The potential applicability of the developed methodology in the analysis of podocin in canine urine sediments was confirmed.

Purple: A Computational Workflow for Strategic Selection of Peptides for Viral Diagnostics Using MS-Based Targeted Proteomics

Emerging virus diseases present a global threat to public health. To detect viral pathogens in time-critical scenarios, accurate and fast diagnostic assays are required. Such assays can now be established using mass spectrometry-based targeted proteomics, by which viral proteins can be rapidly detected from complex samples down to the strain-level with high sensitivity and reproducibility. Developing such targeted assays involves tedious steps of peptide candidate selection, peptide synthesis, and assay optimization. Peptide selection requires extensive preprocessing by comparing candidate peptides against a large search space of background proteins. Here we present Purple (Picking unique relevant peptides for viral experiments), a software tool for selecting target-specific peptide candidates directly from given proteome sequence data. It comes with an intuitive graphical user interface, various parameter options and a threshold-based filtering strategy for homologous sequences. Purple enables peptide candidate selection across various taxonomic levels and filtering against backgrounds of varying complexity. Its functionality is demonstrated using data from different virus species and strains. Our software enables to build taxon-specific targeted assays and paves the way to time-efficient and robust viral diagnostics using targeted proteomics.

Clinical potential of mass spectrometry-based proteogenomics

Cancer genomics research aims to advance personalized oncology by finding and targeting specific genetic alterations associated with cancers. In genome-driven oncology, treatments are selected for individual patients on the basis of the findings of tumour genome sequencing. This personalized approach has prolonged the survival of subsets of patients with cancer. However, many patients do not respond to the predicted therapies based on the genomic profiles of their tumours. Furthermore, studies pairing genomic and proteomic analyses of samples from the same tumours have shown that the proteome contains novel information that cannot be discerned through genomic analysis alone. This observation has led to the concept of proteogenomics, in which both types of data are leveraged for a more complete view of tumour biology that might enable patients to be more successfully matched to effective treatments than they would using genomics alone. In this Perspective, we discuss the added value of proteogenomics over the current genome-driven approach to the clinical characterization of cancers and summarize current efforts to incorporate targeted proteomic measurements based on selected/multiple reaction monitoring (SRM/MRM) mass spectrometry into the clinical laboratory to facilitate clinical proteogenomics.