Blood-Based Multiomics-Guided Detection of a Precancerous Pancreatic Tumor.

Over a decade ago, longitudinal multiomics analysis was pioneered for early disease detection and individually tailored precision health interventions. However, high sample processing costs, expansive multiomics measurements along with complex data analysis have made this approach to precision/personalized medicine impractical. Here we describe in a case report, a more practical approach that uses fewer measurements, annual sampling, and faster decision making. We also show how this approach offers promise to detect an exceedingly rare and potentially fatal condition before it fully manifests. Specifically, we describe in the present case report how longitudinal multiomics monitoring (LMOM) helped detect a precancerous pancreatic tumor and led to a successful surgical intervention. The patient, enrolled in an annual blood-based LMOM since 2018, had dramatic changes in the June 2021 and 2022 annual metabolomics and proteomics results that prompted further clinical diagnostic testing for pancreatic cancer. Using abdominal magnetic resonance imaging, a 2.6 cm lesion in the tail of the patient's pancreas was detected. The tumor fluid from an aspiration biopsy had 10,000 times that of normal carcinoembryonic antigen levels. After the tumor was surgically resected, histopathological findings confirmed it was a precancerous pancreatic tumor. Postoperative omics testing indicated that most metabolite and protein levels returned to patient's 2018 levels. This case report illustrates the potentials of blood LMOM for precision/personalized medicine, and new ways of thinking medical innovation for a potentially life-saving early diagnosis of pancreatic cancer. Blood LMOM warrants future programmatic translational research with the goals of precision medicine, and individually tailored cancer diagnoses and treatments.

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.

A Simplified Proteomics LC-MRM-MS Assay for Determination of apoE Genotypes in Plasma Samples.

Apolipoprotein E (apoE), a polymorphic plasma protein, plays a pivotal role in lipid transportation. The human apoE gene possesses three major alleles (ε2, ε3, and ε4), which differ by single amino acid (cysteine to arginine) substitutions. The ε4 allele represents the primary genetic risk factor for Alzheimer's disease (AD), whereas the ε2 allele protects against the disease. Knowledge of a patient's apoE genotype has high diagnostic value. A recent study has introduced an LC-MRM-MS-based proteomic approach for apoE isoform genotyping using stable isotope-labeled peptide internal standards (SIS). Here, our goal was to develop a simplified LC-MRM-MS assay for identifying apoE genotypes in plasma samples, eliminating the need for the use of SIS peptides. To determine the apoE genotypes, we monitored the chromatographic peak area ratios of isoform-specific peptides relative to a peptide that is common to all apoE isoforms. The assay results correlated well with the standard TaqMan allelic discrimination assay, and we observed a concordance between the two methods for all but three out of 172 samples. DNA sequencing of these three samples has confirmed that the results of the LC-MRM-MS method were correct. Thus, our simplified UPLC-MRM-MS assay is a feasible and reliable method for identifying apoE genotypes without using SIS internal standard peptides. The approach can be seamlessly incorporated into existing quantitative proteomics assays and kits, providing additional valuable apoE genotype information. The principle of using signal ratios of the protein isoform-specific peptides to the peptide common for all of the protein isoforms has the potential to be used for protein isoform determination in general.

Measurement of CYP1A2 and CYP3A4 activity by a simplified Geneva cocktail approach in a cohort of free-living individuals: a pilot study.

Introduction: The cytochrome P450 enzyme subfamilies, including CYP3A4 and CYP1A2, have a major role in metabolism of a range of drugs including several anti-cancer treatments. Many factors including environmental exposures, diet, diseaserelated systemic inflammation and certain genetic polymorphisms can impact the activity level of these enzymes. As a result, the net activity of each enzyme subfamily can vary widely between individuals and in the same individual over time. This variability has potential major implications for treatment efficacy and risk of drug toxicity, but currently no assays are available for routine use to guide clinical decision-making. Methods: To address this, a mass spectrometry-based method to measure activities of CYP3A4, CYP1A2 was adapted and tested in free-living participants. The assay results were compared with the predicted activity of each enzyme, based on a self-report tool capturing diet, medication, chronic disease state, and tobacco usage. In addition, a feasibility test was performed using a low-volume dried blood spots (DBS) on two different filter-paper supports, to determine if the same assay could be deployed without the need for repeated standard blood tests. Results: The results confirmed the methodology is safe and feasible to perform in free-living participants using midazolam and caffeine as test substrates for CYP3A4 and CYP1A2 respectively. Furthermore, though similar methods were previously shown to be compatible with the DBS format, the assay can also be performed successfully while incorporating glucuronidase treatment into the DBS approach. The measured CYP3A4 activity score varied 2.6-fold across participants and correlated with predicted activity score obtained with the self-report tool. The measured CYP1A2 activity varied 3.5-fold between participants but no correlation with predicted activity from the self-report tool was found. Discussion: The results confirm the wide variation in CYP activity between individuals and the important role of diet and other exposures in determining CYP3A4 activity. This methodology shows great potential and future cross-sectional and longitudinal studies using DBS are warranted to determine how best to use the assay results to guide drug treatments.

The Deubiquitylase Otub1 Regulates the Chemotactic Response of Splenic B Cells by Modulating the Stability of the γ-Subunit Gng2.

The ubiquitin proteasome system performs the covalent attachment of lysine 48-linked polyubiquitin chains to substrate proteins, thereby targeting them for degradation, while deubiquitylating enzymes (DUBs) reverse this process. This posttranslational modification regulates key features both of innate and adaptative immunity, including antigen presentation, protein homeostasis and signal transduction. Here we show that loss of one of the most highly expressed DUBs, Otub1, results in changes in murine splenic B cell subsets, leading to a significant increase in marginal zone and transitional B cells and a concomitant decrease in follicular B cells. We demonstrate that Otub1 interacts with the γ-subunit of the heterotrimeric G protein, Gng2, and modulates its ubiquitylation status, thereby controlling Gng2 stability. Proximal mapping of Gng2 revealed an enrichment in partners associated with chemokine signaling, actin cytoskeleton and cell migration. In line with these findings, we show that Otub1-deficient B cells exhibit greater Ca2+ mobilization, F-actin polymerization and chemotactic responsiveness to Cxcl12, Cxcl13 and S1P in vitro, which manifests in vivo as altered localization of B cells within the spleen. Together, our data establishes Otub1 as a novel regulator of G-protein coupled receptor signaling in B cells, regulating their differentiation and positioning in the spleen.

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).

Hyperinsulinemia acts via acinar insulin receptors to initiate pancreatic cancer by increasing digestive enzyme production and inflammation.

The rising pancreatic cancer incidence due to obesity and type 2 diabetes is closely tied to hyperinsulinemia, an independent cancer risk factor. Previous studies demonstrated reducing insulin production suppressed pancreatic intraepithelial neoplasia (PanIN) pre-cancerous lesions in Kras-mutant mice. However, the pathophysiological and molecular mechanisms remained unknown, and in particular it was unclear whether hyperinsulinemia affected PanIN precursor cells directly or indirectly. Here, we demonstrate that insulin receptors (Insr) in KrasG12D-expressing pancreatic acinar cells are dispensable for glucose homeostasis but necessary for hyperinsulinemia-driven PanIN formation in the context of diet-induced hyperinsulinemia and obesity. Mechanistically, this was attributed to amplified digestive enzyme protein translation, triggering of local inflammation, and PanIN metaplasia in vivo. In vitro, insulin dose-dependently increased acinar-to-ductal metaplasia formation in a trypsin- and Insr-dependent manner. Collectively, our data shed light on the mechanisms connecting obesity-driven hyperinsulinemia and pancreatic cancer development.

A Metabolomics Analysis of a Novel Phenotype of Older Adults at Higher Risk of Dementia.

BACKGROUND: Older adults presenting with dual-decline in cognition and walking speed face a 6-fold higher risk for dementia compared with those showing no decline. We hypothesized that the metabolomics profile of dual-decliners would be unique even before they show signs of decline in cognition and gait speed. OBJECTIVE: The objective of this study was to determine if plasma metabolomics signatures can discriminate dual-decliners from no decliners, purely cognitive decliners, and purely motor decliners prior to decline. METHODS: A retrospective cross-sectional study using baseline plasma for untargeted metabolomics analyses to investigate early signals of later dual-decline status in study participants (n = 76) with convenient sampling. Dual-decline was operationalized as decline in gait speed (>10 cm/s) and cognition (>2 points decline in Montreal Cognitive Assessment score) on at least two consecutive 6-monthly assessments. The participants' decliner status was evaluated 3 years after the blood sample was collected. Pair-wise comparison of detected compounds was completed using principal components and hierarchical clustering analyses. RESULTS: Analyses did not detect any cluster separation in untargeted metabolomes across baseline groups. However, follow-up analyses of specific molecules detected 4 compounds (17-Hydroxy-12-(hydroxymethyl)-10-oxo-8 oxapentacyclomethyl hexopyranoside, Fleroxacin, Oleic acid, and 5xi-11,12-Dihydroxyabieta-8(14),9(11),12-trien-20-oic acid) were at significantly higher concentration among the dual-decliners compared to non-decliners. The pure cognitive decliner group had significantly lower concentration of six compounds (1,3-nonanediol acetate, 4-(2-carboxyethyl)-2-methoxyphenyl beta-D-glucopyranosiduronic acid, oleic acid, 2E-3-[4-(sulfo-oxy)phenyl] acrylic acid, palmitelaidic acid, and myristoleic acid) compared to the non-decliner group. CONCLUSIONS: The unique metabolomics profile of dual-decliners warrants follow-up metabolomics analysis. Results may point to modifiable pathways.

Sequential multi-omics analysis identifies clinical phenotypes and predictive biomarkers for long COVID.

The post-acute sequelae of COVID-19 (PASC), also known as long COVID, is often associated with debilitating symptoms and adverse multisystem consequences. We obtain plasma samples from 117 individuals during and 6 months following their acute phase of infection to comprehensively profile and assess changes in cytokines, proteome, and metabolome. Network analysis reveals sustained inflammatory response, platelet degranulation, and cellular activation during convalescence accompanied by dysregulation in arginine biosynthesis, methionine metabolism, taurine metabolism, and tricarboxylic acid (TCA) cycle processes. Furthermore, we develop a prognostic model composed of 20 molecules involved in regulating T cell exhaustion and energy metabolism that can reliably predict adverse clinical outcomes following discharge from acute infection with 83% accuracy and an area under the curve (AUC) of 0.96. Our study reveals pertinent biological processes during convalescence that differ from acute infection, and it supports the development of specific therapies and biomarkers for patients suffering from long COVID.

Determination of Protein Monoclonal-Antibody Epitopes by a Combination of Structural Proteomics Methods.

Structural proteomics techniques are useful for the determination of protein interaction interfaces. Each technique provides orthogonal structural information on the structure and the location of protein interaction sites. Here, we have characterized a monoclonal antibody epitope for a protein antigen by a combination of differential photoreactive surface modification (SM), cross-linking (CL), differential hydrogen-deuterium exchange (HDX), and epitope extraction/excision. We found that experimental data from different approaches agree with each other in determining the epitope of the monoclonal antibody on the protein antigens using the HIV-1 p24-mAb E complex as an illustrative example. A combination of these multiple structural proteomics approaches results in a detailed picture of the interaction of the proteins and increases confidence in the determination of the final structure of the protein interaction interface. Data are available via ProteomeXchange with identifier PXD040902.

FGF1 supports glycolytic metabolism through the estrogen receptor in endocrine-resistant and obesity-associated breast cancer.

BACKGROUND: Obesity increases breast cancer risk and breast cancer-specific mortality, particularly for people with estrogen receptor (ER)-positive tumors. Body mass index (BMI) is used to define obesity, but it may not be the best predictor of breast cancer risk or prognosis on an individual level. Adult weight gain is an independent indicator of breast cancer risk. Our previous work described a murine model of obesity, ER-positive breast cancer, and weight gain and identified fibroblast growth factor receptor (FGFR) as a potential driver of tumor progression. During adipose tissue expansion, the FGF1 ligand is produced by hypertrophic adipocytes as a stimulus to stromal preadipocytes that proliferate and differentiate to provide additional lipid storage capacity. In breast adipose tissue, FGF1 production may stimulate cancer cell proliferation and tumor progression. METHODS: We explored the effects of FGF1 on ER-positive endocrine-sensitive and resistant breast cancer and compared that to the effects of the canonical ER ligand, estradiol. We used untargeted proteomics, specific immunoblot assays, gene expression profiling, and functional metabolic assessments of breast cancer cells. The results were validated in tumors from obese mice and breast cancer datasets from women with obesity. RESULTS: FGF1 stimulated ER phosphorylation independently of estradiol in cells that grow in obese female mice after estrogen deprivation treatment. Phospho- and total proteomic, genomic, and functional analyses of endocrine-sensitive and resistant breast cancer cells show that FGF1 promoted a cellular phenotype characterized by glycolytic metabolism. In endocrine-sensitive but not endocrine-resistant breast cancer cells, mitochondrial metabolism was also regulated by FGF1. Comparison of gene expression profiles indicated that tumors from women with obesity shared hallmarks with endocrine-resistant breast cancer cells. CONCLUSIONS: Collectively, our data suggest that one mechanism by which obesity and weight gain promote breast cancer progression is through estrogen-independent ER activation and cancer cell metabolic reprogramming, partly driven by FGF/FGFR. The first-line treatment for many patients with ER-positive breast cancer is inhibition of estrogen synthesis using aromatase inhibitors. In women with obesity who are experiencing weight gain, locally produced FGF1 may activate ER to promote cancer cell metabolic reprogramming and tumor progression independently of estrogen.

Amino acid analysis for peptide quantitation using reversed-phase liquid chromatography combined with multiple reaction monitoring mass spectrometry.

Amino acid analysis (AAA) can be used for absolute quantitation of standard peptides after acid hydrolysis using 6 M HCl. Obtained individual amino acids can then be quantified by liquid chromatography-mass spectrometry (LC-MS). Achieving baseline separation of non-derivatized amino acids is challenging when reversed-phase (RP) chromatography is used. Several derivatization methods are commonly utilized to address this issue; however, derivatization has several drawbacks, such as derivative instability and lack of reproducibility. Currently, separation of non-derivatized amino acids is typically done using HILIC, but HILIC has problems of poor reproducibility and long column equilibration times. We developed a method to quantify non-derivatized amino acids, including methionine and cysteine, from peptide hydrolysates by RP-LC-MS without special pre-treatment of the samples. Samples were spiked with certified isotopically labeled (13C- and/or 15N-) amino acids as internal standards. The amino acids released from acid hydrolysis were then analyzed by RP-UPLC-MRM-MS and quantified using the analyte/internal standard chromatographic peak area ratios. Peptide quantitation was based on the sum of the individual amino acid concentrations from the known peptide sequences. The resulting method did not require derivatization, used standard C18-based reversed-phase liquid chromatography, did not require external calibration, was robust, and was able to quantify all 17 amino acids for which we had internal standards, including the sulfur-containing amino acids, cysteine and methionine, in their respective oxidized forms. This simple and robust method enabled the absolute quantitation of standard peptides using only acid hydrolysis and a standard RP-UPLC-MRM-MS setup.

Evaluation of a 'plug and play' nanoflow liquid chromatography system for MS-based proteomic characterization of clinical FFPE specimens.

INTRODUCTION: Proteomic analysis of formalin-fixed paraffin-embedded (FFPE) tumor tissue specimens has gained interest in the last 5 years due to technological advances and improved sample collection, as well as biobanking for clinical trials. The real-world implementation of clinical proteomics to these specimens, however, is hampered by tedious sample preparation steps and long instrument acquisition times. AREAS COVERED: To advance the translation of quantitative proteomics into the clinic, we are comparing the performance of the leading commercial nanoflow liquid chromatography (nLC) system (based on literature reviews), the Easy-nLC 1200 (Thermo Fisher Scientific, Waltham, MA, U.S.A.), to the Evosep One HPLC (Evosep Biosystems, Odense, Denmark). We measured FFPE-tissue digests from 21 biological replicates with a similar gradient on both of the LC systems while keeping the on-column amount (1 µg total protein) and the single-shot data-dependent acquisition-based MS/MS method constant. EXPERT OPINION: Overall, the Evosep One facilitates robust and sensitive high-throughput sample acquisition, making it suitable for clinical MS. We found the Evosep One to be a useful platform for positioning mass spectrometry-based proteomics in the clinical setting. The clinical application of nLC/MS will inform clinical decision-making in oncology and other diseases.

Genome mining of Pseudomonas spp. hints towards the production of under-pitched secondary metabolites.

The recent advances in omics and computational analysis have enabled the capacity to identify the exclusive strain-specific metabolites and novel biosynthetic gene clusters. This study analyzed eight strains of P. aurantiaca including GS1, GS3, GS4, GS6, GS7, FS2, ARS38, PBSt2, one strain of P. chlororaphis RP4, one strain of P. aeruginosa (At1RP4), and one strain of P. fluorescens (RS1) for the production of rhamnolipids, quorum-sensing signals, and osmolytes. Seven rhamnolipid derivatives were variably detected in fluorescent pseudomonads. These rhamnolipids included Rha-C10-C8, Rha-Rha-C10-C10, Rha-C10-C12db, Rha-C10-C10, Rha-Rha-C10-C12, Rha-C10-C12, and Rha-Rha-C10-C12db. Pseudomonas spp. also showed the variable production of osmoprotectants including N-acetyl glutaminyl glutamine amide (NAGGN), betaine, ectoine, and trehalose. Betaine and ectoine were produced by all pseudomonads, however, NAGGN and trehalose were observed by five and three strains, respectively. Four strains including P. chlororaphis (RP4), P. aeruginosa (At1RP4), P. fluorescens (RS1), and P. aurantiaca (PBSt2) were exposed to 1- 4% NaCl concentrations and evaluated for the changes in phenazine production profile which were negligible. AntiSMASH 5.0 platform showed 50 biosynthetic gene clusters in PB-St2, of which 23 (45%) were classified as putative gene clusters with ClusterFinder algorithm, five (10%) were classified as non-ribosomal peptides synthetases (NRPS), five (10%) as saccharides, and four (8%) were classified as putative fatty acids. The genomic attributes and comprehensive insights into the metabolomic profile of these Pseudomonas spp. strains showcase their phytostimulatory, phyto-protective, and osmoprotective effects of diverse crops grown in normal and saline soils. Supplementary Information: The online version contains supplementary material available at 10.1007/s13205-023-03607-x.

Pressure overload induces ISG15 to facilitate adverse ventricular remodeling and promote heart failure.

Inflammation promotes adverse ventricular remodeling, a common antecedent of heart failure. Here, we set out to determine how inflammatory cells affect cardiomyocytes in the remodeling heart. Pathogenic cardiac macrophages induced an IFN response in cardiomyocytes, characterized by upregulation of the ubiquitin-like protein IFN-stimulated gene 15 (ISG15), which posttranslationally modifies its targets through a process termed ISGylation. Cardiac ISG15 is controlled by type I IFN signaling, and ISG15 or ISGylation is upregulated in mice with transverse aortic constriction or infused with angiotensin II; rats with uninephrectomy and DOCA-salt, or pulmonary artery banding; cardiomyocytes exposed to IFNs or CD4+ T cell-conditioned medium; and ventricular tissue of humans with nonischemic cardiomyopathy. By nanoscale liquid chromatography-tandem mass spectrometry, we identified the myofibrillar protein filamin-C as an ISGylation target. ISG15 deficiency preserved cardiac function in mice with transverse aortic constriction and led to improved recovery of mouse hearts ex vivo. Metabolomics revealed that ISG15 regulates cardiac amino acid metabolism, whereas ISG15 deficiency prevented misfolded filamin-C accumulation and induced cardiomyocyte autophagy. In sum, ISG15 upregulation is a feature of pathological ventricular remodeling, and protein ISGylation is an inflammation-induced posttranslational modification that may contribute to heart failure development by altering cardiomyocyte protein turnover.

Discovery-Based Proteomics Identify Skeletal Muscle Mitochondrial Alterations as an Early Metabolic Defect in a Mouse Model of ß-Thalassemia.

Although metabolic complications are common in thalassemia patients, there is still an unmet need to better understand underlying mechanisms. We used unbiased global proteomics to reveal molecular differences between the th3/+ mouse model of thalassemia and wild-type control animals focusing on skeletal muscles at 8 weeks of age. Our data point toward a significantly impaired mitochondrial oxidative phosphorylation. Furthermore, we observed a shift from oxidative fibre types toward more glycolytic fibre types in these animals, which was further supported by larger fibre-type cross-sectional areas in the more oxidative type fibres (type I/type IIa/type IIax hybrid). We also observed an increase in capillary density in th3/+ mice, indicative of a compensatory response. Western blotting for mitochondrial oxidative phosphorylation complex proteins and PCR analysis of mitochondrial genes indicated reduced mitochondrial content in the skeletal muscle but not the hearts of th3/+ mice. The phenotypic manifestation of these alterations was a small but significant reduction in glucose handling capacity. Overall, this study identified many important alterations in the proteome of th3/+ mice, amongst which mitochondrial defects leading to skeletal muscle remodelling and metabolic dysfunction were paramount.

Offline Peptide Fractionation and Parallel Reaction Monitoring MS for the Quantitation of Low-Abundance Plasma Proteins.

Mass spectrometry (MS)-based protein quantitation is an attractive means for research and diagnostics due to its high specificity, precision, sensitivity, versatility, and the ability to develop multiplexed assays for the "absolute" quantitation of virtually any protein target. However, due to the large dynamic range of protein concentrations in blood, high abundance proteins in blood plasma hinder the detectability and quantification of lower-abundance proteins which are often relevant in the context of different diseases. Here we outline a streamlined method involving offline high-pH reversed-phase fractionation of human plasma samples followed by the quantitative analysis of specific fractions using nanoLC-parallel reaction monitoring (PRM) on a Q Exactive Plus mass spectrometer for peptide detection and quantitation with increased sensitivity. Because we use a set of synthetic peptide standards, we can more efficiently determine the precise retention times of the target peptides in the first-dimensional separation and specifically collect eluting fractions of interest for the subsequent targeted MS quantitation, making the analysis faster and easier. An eight-point standard curve was generated by serial dilution of a mixture of previously validated unlabeled ("light") synthetic peptides of interest at known concentrations. The corresponding heavy stable-isotope-labeled standard (SIS) analogues were used as normalizers to account for losses during sample processing and analysis. Using this method, we were able to improve the sensitivity of plasma protein quantitation by up to 50-fold compared to using nanoLC-PRM alone.

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.