Establishing Personalized Blood Protein Reference Ranges Using Noninvasive Microsampling and Targeted Proteomics: Implications for Antidoping Strategies.

To prevent doping practices in sports, the World Anti-Doping Agency implemented the Athlete Biological Passport (ABP) program, monitoring biological variables over time to indirectly reveal the effects of doping rather than detect the doping substance or the method itself. In the context of this program, a highly multiplexed mass spectrometry-based proteomics assay for 319 peptides corresponding to 250 proteins was developed, including proteins associated with blood-doping practices. "Baseline" expression profiles of these potential biomarkers in capillary blood (dried blood spots (DBS)) were established using multiple reaction monitoring (MRM). Combining DBS microsampling with highly multiplexed MRM assays is the best-suited technology to enhance the effectiveness of the ABP program, as it represents a cost-effective and robust alternative analytical method with high specificity and selectivity of targets in the attomole range. DBS data were collected from 10 healthy athlete volunteers over a period of 140 days (28 time points per participant). These comprehensive findings provide a personalized targeted blood proteome "fingerprint" showcasing that the targeted proteome is unique to an individual and likely comparable to a DNA fingerprint. The results can serve as a baseline for future studies investigating doping-related perturbations.

Spatially and temporally resolved metabolome of the human oral cavity.

Saliva is a complex bodily fluid composed of secretions by major and minor salivary glands. Salivary glands and their secretions are known to be unevenly distributed in the human oral cavity. Moreover, saliva flow rate and composition vary across locations and time of the day. This remarkable heterogeneity of salivary secretions suggests that different subtypes of saliva fulfill different functions. By coupling a non-invasive and facile collection method with comprehensive metabolomic profiling, we investigated the spatial and temporal distributions of salivary components. We identified location-specific metabolite profiles, novel oscillating metabolites, and location-specific diurnal patterns. In summary, our study paves the way for a deeper and more comprehensive understanding of the complex dynamics and functionalities of the salivary metabolome and its integration in multi-omics studies related to oral and systemic (patho-)physiology.

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.

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).

Fatty acid desaturation and lipoxygenase pathways support trained immunity.

Infections and vaccines can induce enhanced long-term responses in innate immune cells, establishing an innate immunological memory termed trained immunity. Here, we show that monocytes with a trained immunity phenotype, due to exposure to the Bacillus Calmette-Guérin (BCG) vaccine, are characterized by an increased biosynthesis of different lipid mediators (LM) derived from long-chain polyunsaturated fatty acids (PUFA). Pharmacological and genetic approaches show that long-chain PUFA synthesis and lipoxygenase-derived LM are essential for the BCG-induced trained immunity responses of human monocytes. Furthermore, products of 12-lipoxygenase activity increase in monocytes of healthy individuals after BCG vaccination. Grasping the underscoring lipid metabolic pathways contributes to our understanding of trained immunity and may help to identify therapeutic tools and targets for the modulation of innate immune responses.

Cellular Validation of a Chemically Improved Inhibitor Identifies Monoubiquitination on OTUB2.

Ubiquitin thioesterase OTUB2, a cysteine protease from the ovarian tumor (OTU) deubiquitinase superfamily, is often overexpressed during tumor progression and metastasis. Development of OTUB2 inhibitors is therefore believed to be therapeutically important, yet potent and selective small-molecule inhibitors targeting OTUB2 are scarce. Here, we describe the development of an improved OTUB2 inhibitor, LN5P45, comprising a chloroacethydrazide moiety that covalently reacts to the active-site cysteine residue. LN5P45 shows outstanding target engagement and proteome-wide selectivity in living cells. Importantly, LN5P45 as well as other OTUB2 inhibitors strongly induce monoubiquitination of OTUB2 on lysine 31. We present a route to future OTUB2-related therapeutics and have shown that the OTUB2 inhibitor developed in this study can help to uncover new aspects of the related biology and open new questions regarding the understanding of OTUB2 regulation at the post-translational modification level.

Inhibition of DHCR24 activates LXRα to ameliorate hepatic steatosis and inflammation.

Liver X receptor (LXR) agonism has theoretical potential for treating NAFLD/NASH, but synthetic agonists induce hyperlipidemia in preclinical models. Desmosterol, which is converted by Δ24-dehydrocholesterol reductase (DHCR24) into cholesterol, is a potent endogenous LXR agonist with anti-inflammatory properties. We aimed to investigate the effects of DHCR24 inhibition on NAFLD/NASH development. Here, by using APOE*3-Leiden. CETP mice, a well-established translational model that develops diet-induced human-like NAFLD/NASH characteristics, we report that SH42, a published DHCR24 inhibitor, markedly increases desmosterol levels in liver and plasma, reduces hepatic lipid content and the steatosis score, and decreases plasma fatty acid and cholesteryl ester concentrations. Flow cytometry showed that SH42 decreases liver inflammation by preventing Kupffer cell activation and monocyte infiltration. LXRα deficiency completely abolishes these beneficial effects of SH42. Together, the inhibition of DHCR24 by SH42 prevents diet-induced hepatic steatosis and inflammation in a strictly LXRα-dependent manner without causing hyperlipidemia. Finally, we also showed that SH42 treatment decreased liver collagen content and plasma alanine transaminase levels in an established NAFLD model. In conclusion, we anticipate that pharmacological DHCR24 inhibition may represent a novel therapeutic strategy for treatment of NAFLD/NASH.

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.

Congruence and Complementarity of Differential Mobility Spectrometry and NMR Spectroscopy for Plasma Lipidomics.

The lipid composition of lipoprotein particles is determinative of their respective formation and function. In turn, the combination and correlation of nuclear magnetic resonance (NMR)-based lipoprotein measurements with mass spectrometry (MS)-based lipidomics is an appealing technological combination for a better understanding of lipid metabolism in health and disease. Here, we developed a combined workflow for subsequent NMR- and MS-based analysis on single sample aliquots of human plasma. We evaluated the quantitative agreement of the two platforms for lipid quantification and benchmarked our combined workflow. We investigated the congruence and complementarity between the platforms in order to facilitate a better understanding of patho-physiological lipoprotein and lipid alterations. We evaluated the correlation and agreement between the platforms. Next, we compared lipid class concentrations between healthy controls and rheumatoid arthritis patient samples to investigate the consensus among the platforms on differentiating the two groups. Finally, we performed correlation analysis between all measured lipoprotein particles and lipid species. We found excellent agreement and correlation (r > 0.8) between the platforms and their respective diagnostic performance. Additionally, we generated correlation maps detailing lipoprotein/lipid interactions and describe disease-relevant correlations.

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.

Renin-Angiotensin System Pathway Therapeutics Associated With Improved Outcomes in Males Hospitalized With COVID-19.

OBJECTIVES: To determine whether angiotensin receptor blockers (ARBs) or angiotensin-converting enzyme (ACE) inhibitors are associated with improved outcomes in hospitalized patients with COVID-19 according to sex and to report sex-related differences in renin-angiotensin system (RAS) components. DESIGN: Prospective observational cohort study comparing the effects of ARB or ACE inhibitors versus no ARBs or ACE inhibitors in males versus females. Severe acute respiratory syndrome coronavirus 2 downregulates ACE-2, potentially increasing angiotensin II (a pro-inflammatory vasoconstrictor). Sex-based differences in RAS dysregulation may explain sex-based differences in responses to ARBs because the ACE2 gene is on the X chromosome. We recorded baseline characteristics, comorbidities, prehospital ARBs or ACE inhibitor treatment, use of organ support and mortality, and measured RAS components at admission and days 2, 4, 7, and 14 in a subgroup ( n = 46), recorded d -dimer ( n = 967), comparing males with females. SETTING: ARBs CORONA I is a multicenter Canadian observational cohort of patients hospitalized with acute COVID-19. This analysis includes patients admitted to 10 large urban hospitals across the four most populated provinces. PATIENTS: One-thousand six-hundred eighty-six patients with polymerase chain reaction-confirmed COVID-19 (February 2020 to March 2021) for acute COVID-19 illness were included. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Males on ARBs before admission had decreased use of ventilation (adjusted odds ratio [aOR] = 0.52; p = 0.007) and vasopressors (aOR = 0.55; p = 0.011) compared with males not on ARBs or ACE inhibitors. No significant effects were observed in females for these outcomes. The test for interaction was significant for use of ventilation ( p = 0.006) and vasopressors ( p = 0.044) indicating significantly different responses to ARBs according to sex. Males had significantly higher plasma ACE-1 at baseline and angiotensin II at day 7 and 14 than females. CONCLUSIONS: ARBs use was associated with less ventilation and vasopressors in males but not females. Sex-based differences in RAS dysregulation may contribute to sex-based differences in outcomes and responses to ARBs in COVID-19.

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.

Evaluation of Fast and Sensitive Proteome Profiling of FF and FFPE Kidney Patient Tissues.

The application of proteomics to fresh frozen (FF) and formalin-fixed paraffin-embedded (FFPE) human tissues is an important development spurred on by requests from stakeholder groups in clinical fields. One objective is to complement current diagnostic methods with new specific molecular information. An important goal is to achieve adequate and consistent protein recovery across and within large-scale studies. Here, we describe development of several protocols incorporating mass spectrometry compatible detergents, including Rapigest, PPS, and ProteaseMax. Methods were applied on 4 and 15 µm thick FF tissues, and 4 µm thick FFPE tissues. We evaluated sensitivity and repeatability of the methods and found that the protocol containing Rapigest enabled detection of 630 proteins from FF tissue of 1 mm2 and 15 µm thick, whereas 498 and 297 proteins were detected with the protocols containing ProteaseMax and PPS, respectively. Surprisingly, PPS-containing buffer showed good extraction of the proteins from 4 µm thick FFPE tissue with the average of 270 protein identifications (1 mm2), similar to the results on 4 µm thick FF. Moreover, we found that temperature increases during incubation with urea on 4 µm thick FF tissue revealed a decrease in the number of identified proteins and increase in the number of the carbamylated peptides.

Clostridioides difficile Phosphoproteomics Shows an Expansion of Phosphorylated Proteins in Stationary Growth Phase.

Phosphorylation is a posttranslational modification that can affect both housekeeping functions and virulence characteristics in bacterial pathogens. In the Gram-positive enteropathogen Clostridioides difficile, the extent and nature of phosphorylation events are poorly characterized, though a protein kinase mutant strain demonstrates pleiotropic phenotypes. Here, we used an immobilized metal affinity chromatography strategy to characterize serine, threonine, and tyrosine phosphorylation in C. difficile. We find limited protein phosphorylation in the exponential growth phase but a sharp increase in the number of phosphopeptides after the onset of the stationary growth phase. Our approach identifies expected targets and phosphorylation sites among the more than 1,500 phosphosites, including the protein kinase PrkC, the anti-sigma-F factor antagonist (SpoIIAA), the anti-sigma-B factor antagonist (RsbV), and HPr kinase/phosphorylase (HprK). Analysis of high-confidence phosphosites shows that phosphorylation on serine residues is most common, followed by threonine and tyrosine phosphorylation. This work forms the basis for a further investigation into the contributions of individual kinases to the overall phosphoproteome of C. difficile and the role of phosphorylation in C. difficile physiology and pathogenesis. IMPORTANCE In this paper, we present a comprehensive analysis of protein phosphorylation in the Gram-positive enteropathogen Clostridioides difficile. To date, only limited evidence on the role of phosphorylation in the regulation of this organism has been published; the current study is expected to form the basis for research on this posttranslational modification in C. difficile. .

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.

Cross-Laboratory Standardization of Preclinical Lipidomics Using Differential Mobility Spectrometry and Multiple Reaction Monitoring.

Modern biomarker and translational research as well as personalized health care studies rely heavily on powerful omics' technologies, including metabolomics and lipidomics. However, to translate metabolomics and lipidomics discoveries into a high-throughput clinical setting, standardization is of utmost importance. Here, we compared and benchmarked a quantitative lipidomics platform. The employed Lipidyzer platform is based on lipid class separation by means of differential mobility spectrometry with subsequent multiple reaction monitoring. Quantitation is achieved by the use of 54 deuterated internal standards and an automated informatics approach. We investigated the platform performance across nine laboratories using NIST SRM 1950-Metabolites in Frozen Human Plasma, and three NIST Candidate Reference Materials 8231-Frozen Human Plasma Suite for Metabolomics (high triglyceride, diabetic, and African-American plasma). In addition, we comparatively analyzed 59 plasma samples from individuals with familial hypercholesterolemia from a clinical cohort study. We provide evidence that the more practical methyl-tert-butyl ether extraction outperforms the classic Bligh and Dyer approach and compare our results with two previously published ring trials. In summary, we present standardized lipidomics protocols, allowing for the highly reproducible analysis of several hundred human plasma lipids, and present detailed molecular information for potentially disease relevant and ethnicity-related materials.

Reinspection of a Clinical Proteomics Tumor Analysis Consortium (CPTAC) Dataset with Cloud Computing Reveals Abundant Post-Translational Modifications and Protein Sequence Variants.

The Clinical Proteomic Tumor Analysis Consortium (CPTAC) has provided some of the most in-depth analyses of the phenotypes of human tumors ever constructed. Today, the majority of proteomic data analysis is still performed using software housed on desktop computers which limits the number of sequence variants and post-translational modifications that can be considered. The original CPTAC studies limited the search for PTMs to only samples that were chemically enriched for those modified peptides. Similarly, the only sequence variants considered were those with strong evidence at the exon or transcript level. In this multi-institutional collaborative reanalysis, we utilized unbiased protein databases containing millions of human sequence variants in conjunction with hundreds of common post-translational modifications. Using these tools, we identified tens of thousands of high-confidence PTMs and sequence variants. We identified 4132 phosphorylated peptides in nonenriched samples, 93% of which were confirmed in the samples which were chemically enriched for phosphopeptides. In addition, our results also cover 90% of the high-confidence variants reported by the original proteogenomics study, without the need for sample specific next-generation sequencing. Finally, we report fivefold more somatic and germline variants that have an independent evidence at the peptide level, including mutations in ERRB2 and BCAS1. In this reanalysis of CPTAC proteomic data with cloud computing, we present an openly available and searchable web resource of the highest-coverage proteomic profiling of human tumors described to date.

A multiplexed, automated immuno-matrix assisted laser desorption/ionization mass spectrometry assay for simultaneous and precise quantitation of PTEN and p110α in cell lines and tumor tissues.

The PI3-kinase/AKT/mTOR pathway plays a central role in cancer signaling. While p110α is the catalytic α-subunit of PI3-kinase and a major drug target, PTEN is the main negative regulator of the PI3-kinase/AKT/mTOR pathway. PTEN is often down-regulated in cancer, and there are conflicting data on PTEN's role as breast cancer biomarker. PTEN and p110α protein expression in tumors is commonly analyzed by immunohistochemistry, which suffers from poor multiplexing capacity, poor standardization, and antibody crossreactivity, and which provides only semi-quantitative data. Here, we present an automated, and standardized immuno-matrix-assisted laser desorption/ionization mass spectrometry (iMALDI) assay that allows precise and multiplexed quantitation of PTEN and p110α concentrations, without the limitations of immunohistochemistry. Our iMALDI assay only requires a low-cost benchtop MALDI-TOF mass spectrometer, which simplifies clinical translation. We validated our assay's precision and accuracy, with simultaneous enrichment of both target proteins not significantly affecting the precision and accuracy of the quantitation when compared to the PTEN- and p110α-singleplex iMALDI assays (<15% difference). The multiplexed assay's linear range is from 0.6-20 fmol with accuracies of 90-112% for both target proteins, and the assay is free of matrix-related interferences. The inter-day reproducibility over 5-days was high, with an overall CV of 9%. PTEN and p110α protein concentrations can be quantified down to 1.4 fmol and 0.6 fmol per 10 µg of total tumor protein, respectively, in various tumor tissue samples, including fresh-frozen breast tumors and colorectal cancer liver metastases, and patient-derived xenograft (PDX) tumors.

Performance Assessment of a 125 Human Plasma Peptide Mixture Stored at Room Temperature for Multiple Reaction Monitoring-Mass Spectrometry.

Synthetic peptides are a critical requirement for the development and application of targeted mass spectrometry (MS)-based assays for the quantitation of proteins from biological matrices. Transporting synthetic peptides on dry ice from one laboratory to another is costly and often difficult because of country-specific import and export regulations. Therefore, in this study, we assessed the impact of leaving a lyophilized mixture consisting of 125 peptides at room temperature for up to 20 days, and we assessed the effect on the quantitative performance of multiple reaction monitoring-MS (MRM-MS) assays. The findings suggest that there are no significant differences in the MRM-MS results for the time points assessed in this study (up to 20 days). All the calibration curves and quality control (QC) samples met the acceptance criteria for precision and accuracy (raw data are available via the public MS data repository PanoramaWeb, identifier: /MRM Proteomics/2020_BAK125_RT). The number of endogenous proteins quantifiable across five plasma samples was consistently between 87 and 99 out of 125 for all time points. Moreover, the coefficients of variation (CVs) calculated for the majority of peptide concentrations across all samples and time points were <5%. In addition, a lyophilized peptide mixture was transported from Canada to Iceland without dry ice. The results showed that there was no significant difference in the quantitative performance, with the determined concentrations of most proteins in the samples falling within 30% between the analyses performed on the same three plasma samples in Iceland and those in Canada. Overall, a comparison of the results obtained in Canada and in Iceland indicated that the peptides were stable under the conditions tested and also indicated that shipping lyophilized peptide mixtures without dry ice, but in the presence of sufficient desiccant material, could be a feasible option in cases where transport difficulties may arise or dry-ice sublimation may occur.