Next generation plasma proteome profiling of COVID-19 patients with mild to moderate symptoms.

BACKGROUND: COVID-19 has caused millions of deaths globally, yet the cellular mechanisms underlying the various effects of the disease remain poorly understood. Recently, a new analytical platform for comprehensive analysis of plasma protein profiles using proximity extension assays combined with next generation sequencing has been developed, which allows for multiple proteins to be analyzed simultaneously without sacrifice on accuracy or sensitivity. METHODS: We analyzed the plasma protein profiles of COVID-19 patients (n = 50) with mild and moderate symptoms by comparing the protein levels in newly diagnosed patients with the protein levels in the same individuals after 14 days. FINDINGS: The study has identified more than 200 proteins that are significantly elevated during infection and many of these are related to cytokine response and other immune-related functions. In addition, several other proteins are shown to be elevated, including SCARB2, a host cell receptor protein involved in virus entry. A comparison with the plasma protein response in patients with severe symptoms shows a highly similar pattern, but with some interesting differences. INTERPRETATION: The study presented here demonstrates the usefulness of "next generation plasma protein profiling" to identify molecular signatures of importance for disease progression and to allow monitoring of disease during recovery from the infection. The results will facilitate further studies to understand the molecular mechanism of the immune-related response of the SARS-CoV-2 virus. FUNDING: This work was financially supported by Knut and Alice Wallenberg Foundation.

Multiplex Protein Biomarker Profiling in Patients with Familial Hypercholesterolemia.

Familial hypercholesterolemia (FH), is an autosomal dominant disorder caused by mutations in the LDLR, APOB, PCSK9, and APOE genes and is characterized by high plasma levels of total and low-density lipoprotein (LDL) cholesterol. Our study aimed to analyze the influences of two different therapies on a wide spectrum of plasma protein biomarkers of cardiovascular diseases. Plasma from FH patients under hypolipidemic therapy (N = 18; men = 8, age 55.4 ± 13.1 years) and patients under combined long-term LDL apheresis/hypolipidemic therapy (N = 14; men = 7; age 58.0 ± 13.6 years) were analyzed in our study. We measured a profile of 184 cardiovascular disease (CVD) associated proteins using a proximity extension assay (PEA). Hypolipidemic therapy significantly (all p < 0.01) influenced 10 plasma proteins (TM, DKK1, CCL3, CD4, PDGF subunit B, AGRP, IL18, THPO, and LOX1 decreased; ST2 increased). Under combined apheresis/hypolipidemic treatment, 18 plasma proteins (LDLR, PCSK9, MMP-3, GDF2, CTRC, SORT1, VEGFD, IL27, CCL24, and KIM1 decreased; OPN, COL1A1, KLK6, IL4RA, PLC, TNFR1, GLO1, and PTX3 increased) were significantly affected (all p < 0.006). Hypolipidemic treatment mainly affected biomarkers involved in vascular endothelial maintenance. Combined therapy influenced proteins that participate in cholesterol metabolism and inflammation.

Quantitative Proteomic Analysis of Plasma after Remote Ischemic Conditioning in a Rhesus Monkey Ischemic Stroke Model.

BACKGROUND: Animal and clinical studies have shown that remote ischemic conditioning (RIC) has protective effects for cerebral vascular diseases, with induced humoral factor changes in the peripheral blood. However, many findings are heterogeneous, perhaps due to differences in the RIC intervention schemes, enrolled populations, and sample times. This study aimed to examine the RIC-induced changes in the plasma proteome using rhesus monkey models of strokes. METHODS: Two adult rhesus monkeys with autologous blood clot-induced middle cerebral artery (MCA) occlusion underwent RIC interventions twice a week for five consecutive weeks. Each RIC treatment included five cycles of five minutes of ischemia alternating with five minutes of reperfusion of the forearm. The blood samples were taken from the median cubital vein of the monkeys at baseline and immediately after each week's RIC stimulus. The plasma samples were isolated for a proteomic analysis using mass spectrometry (MS). RESULTS: Several proteins related to lipid metabolism (Apolipoprotein A-II and Apolipoprotein C-II), coagulation (Fibrinogen alpha chain and serpin), immunoinflammatory responses (complement C3 and C1), and endovascular hemostasis (basement membrane-specific heparan sulfate proteoglycan) were significantly modulated after the RIC intervention. Many of these induced changes, such as in the lipid metabolism regulation and anticoagulation responses, starting as early as two weeks following the RIC intervention. The complementary activation and protection of the endovascular cells occurred more than three weeks postintervention. CONCLUSIONS: Multiple protective effects were induced by RIC and involved lipid metabolism regulation (anti-atherogenesis), anticoagulation (antithrombosis), complement activation, and endovascular homeostasis (anti-inflammation). In conclusion, this study indicates that RIC results in significant modulations of the plasma proteome. It also provides ideas for future research and screening targets.

Crowdsourcing assessment of maternal blood multi-omics for predicting gestational age and preterm birth.

Identification of pregnancies at risk of preterm birth (PTB), the leading cause of newborn deaths, remains challenging given the syndromic nature of the disease. We report a longitudinal multi-omics study coupled with a DREAM challenge to develop predictive models of PTB. The findings indicate that whole-blood gene expression predicts ultrasound-based gestational ages in normal and complicated pregnancies (r = 0.83) and, using data collected before 37 weeks of gestation, also predicts the delivery date in both normal pregnancies (r = 0.86) and those with spontaneous preterm birth (r = 0.75). Based on samples collected before 33 weeks in asymptomatic women, our analysis suggests that expression changes preceding preterm prelabor rupture of the membranes are consistent across time points and cohorts and involve leukocyte-mediated immunity. Models built from plasma proteomic data predict spontaneous preterm delivery with intact membranes with higher accuracy and earlier in pregnancy than transcriptomic models (AUROC = 0.76 versus AUROC = 0.6 at 27-33 weeks of gestation).

Exploration of Serum Marker Proteins in Mice Induced by Babesia microti Infection Using a Quantitative Proteomic Approach.

Babesia microti is a protozoan that mainly parasitizes rodent and human erythrocytes. B. microti infection can result in changes in the expression levels of various proteins in the host serum. To explore the mechanism underlying the regulation of serum proteins by the host during B. microti infection, this study used a data-independent acquisition (DIA) quantitative proteomic approach to perform comprehensive quantitative proteomic analysis on the serum of B. microti-infected mice. We identified and analysed 333 serum proteins during the infectious stage and recovery stage within 30 days of infection by B. microti in mice. Through quantitative analysis, we found 57 proteins differentially expressed in the infection stage and 69 proteins differentially expressed in the recovery stage. Bioinformatics analysis revealed that these differentially expressed proteins were mainly concentrated in organelles, cell parts, and extracellular regions that are mainly involved in immune system, metabolic, and cellular processes. Additionally, the differentially expressed proteins mainly had catalytic activity. Kyoto Encyclopedia of Genes and Genome (KEGG) pathway analysis showed that many of the differentially expressed proteins participate in the complement and coagulation cascade reaction, including complement C3, complement FP, and coagulation factor XII. The results of this study can provide more information for the selection of biomarkers for the early clinical monitoring of babesiosis and help in the treatment of babesiosis.

Plasma Proteome Responses in Salmonid Fish Following Immunization.

Vaccination plays a critical role in the protection of humans and other animals from infectious diseases. However, the same vaccine often confers different protection levels among individuals due to variation in genetics and/or immunological histories. While this represents a well-recognized issue in humans, it has received little attention in fish. Here we address this knowledge gap in a proteomic study of rainbow trout (Oncorhynchus mykiss, Walbaum), using non-lethal repeated blood sampling to establish the plasma protein response of individual fish following immunization. Six trout were immunized with adjuvanted hen egg-white lysozyme (HEL) and peripheral blood sampled at ten time points from day 0 to day 84 post-injection. We confirm that an antigen-specific antibody response to HEL was raised, showing differences in timing and magnitude among individuals. Using label-free liquid chromatography-mass spectrometry, we quantified the abundance of 278 plasma proteins across the timecourse. As part of the analysis, we show that this approach can distinguish many (but not all) duplicated plasma proteins encoded by paralogous genes retained from the salmonid-specific whole genome duplication event. Global variation in the plasma proteome was predominantly explained by individual differences among fish. However, sampling day explained a major component of variation in abundance for a statistically defined subset of 41 proteins, representing 15% of those detected. These proteins clustered into five groups showing distinct temporal responses to HEL immunization at the population level, and include classical immune (e.g. complement system members) and acute phase molecules (e.g. apolipoproteins, haptoglobins), several enzymes and other proteins supporting the immune response, in addition to evolutionarily conserved molecules that are as yet uncharacterized. Overall, this study improves our understanding of the fish plasma proteome, provides valuable marker proteins for different phases of the immune response, and has implications for vaccine development and the design of immune challenge experiments.

Identification of Differentially Expressed Proteins in Serum of Obese Patients by Isobaric Tags for Relative and Absolute Quantification (iTRAQ)-Coupled 2D LC-MS.

BACKGROUND The aim of this study was to identify the differentially expressed proteins of obese patients compared with normal participants and to provide a potential target for future investigation of obesity. MATERIAL AND METHODS We enrolled 10 obese male adults and 10 matched normal subjects. Serum samples were collected to get total protein extraction, denaturation, deoxidation, and enzymatic hydrolysis. Differentially expressed proteins were distinguished with mass spectrometry after samples were labeled with iTRAQ. RESULTS A total of 9622 differentially expressed peptides were identified, corresponding to 733 proteins; 118 proteins of these showed significant differential expression, with 15 upregulated and 103 downregulated. CONCLUSIONS iTRAQ is an effective technique to identify differentially expressed proteins in obese patients. The development of obesity is correlated with a series of complex elements and mutual effects. The proteins identified in this study may provide novel directions and targets for future pathological studies of obesity.

A Serum Protein Classifier Identifying Patients with Advanced Non-Small Cell Lung Cancer Who Derive Clinical Benefit from Treatment with Immune Checkpoint Inhibitors.

PURPOSE: Pretreatment selection of patients with non-small cell lung cancer (NSCLC) who would derive clinical benefit from treatment with immune checkpoint inhibitors (CPIs) would fulfill an unmet clinical need by reducing unnecessary toxicities from treatment and result in substantial health care savings. EXPERIMENTAL DESIGN: In a retrospective study, mass spectrometry (MS)-based proteomic analysis was performed on pretreatment sera derived from patients with advanced NSCLC treated with nivolumab as part of routine clinical care (n = 289). Machine learning combined spectral and clinical data to stratify patients into three groups with good ("sensitive"), intermediate, and poor ("resistant") outcomes following treatment in the second-line setting. The test was applied to three independent patient cohorts and its biology was investigated using protein set enrichment analyses (PSEA). RESULTS: A signature consisting of 274 MS features derived from a development set of 116 patients was associated with progression-free survival (PFS) and overall survival (OS) across two validation cohorts (N = 98 and N = 75). In pooled analysis, significantly better OS was demonstrated for "sensitive" relative to "not sensitive" patients treated with nivolumab; HR, 0.58 (95% confidence interval, 0.38-0-87; P = 0.009). There was no significant association with clinical factors including PD-L1 expression, available from 133 of 289 patients. The test demonstrated no significant association with PFS or OS in a historical cohort (n = 68) of second-line NSCLC patients treated with docetaxel. PSEA revealed proteomic classification to be significantly associated with complement and wound-healing cascades. CONCLUSIONS: This serum-derived protein signature successfully stratified outcomes in cohorts of patients with advanced NSCLC treated with second-line PD-1 CPIs and deserves further prospective study.

Profiling of hydroxyurea-treated ß-thalassemia/ serum proteome through nano-LC-ESI-MS/ MS in combination with microsol-isoelectric focusing.

Advancements in proteomic tools offer a comprehensive solution to studying the complexity of diseases at molecular level. This study focusses on the clinical proteomic profiling of pre- and post-hydroxyurea (HU)-treated ß-thalassemia patients in parallel with healthy individuals to better understand the role of HU in the treatment of ß-thalassemia. The strategy encompasses sequential high-resolution protein fractionation using MicroSol-isoelectric focusing (ZOOM- IEF) followed by one-dimensional SDS-PAGE before nano-RP-LC-MS/ MS analysis of tryptic peptides. Protein identification was performed through Mascot search using NCBInr and SwissProt databases. Several different proteins were observed in pool serum samples of each of the three study groups. Approximately, 1250 proteins exclusive to each group were identified, and after removing the redundant and low sequence coverage proteins, the number was reduced to 576 (201 in healthy, 187 in HU-untreated and 188 in HU-treated group). Uniquely identified proteins in the HU-treated group regulate the focal adhesion, ECM-receptor interaction, PI3K-Akt signaling, Rap1 signaling, cAMP signaling, platelet activation, and Ca2+ signaling pathways in the HU-treated group. The proteomic profile presented here will add to the current state of understanding of molecular mechanisms involved in hydroxyurea treatment of ß-thalassemia.

Molecular characterization and expression patterns of two LPS binding /bactericidal permeability-increasing proteins (LBP/BPIs) from the scallop Argopecten purpuratus.

Lipopolysaccharide-binding proteins (LBPs) and bactericidal permeability-increasing proteins (BPIs) are effectors of the innate immune response which act in a coordinated manner to bind and neutralize the LPS present in Gram negative bacteria. The structural organization that confers the function of LBPs and BPIs is very similar, however, they are antagonistic to each other. In this work, we characterized two LBP/BPIs from the scallop Argopecten purpuratus, namely ApLBP/BPI1 and ApLBP/BPI2. The molecular and phylogenetic analyses of ApLBP/BPIs indicated that both isoforms display classic characteristics of LBP/BPIs from other invertebrates. Additionally, ApLBP/BPIs are constitutively expressed in scallop tissues and their transcript expression is upregulated in hemocytes and gills in response to an immune challenge. However, some structural characteristics of functional importance for the biological activity of these molecules, such as the net charge differ substantially between ApLBP/BPI1 and ApLBP/BPI2. Furthermore, each isoform displays a specific profile of basal expression among different tissues, as well as specific patterns of expression during the activation of the immune response. Results suggest that functional specialization of ApLBP/BPIs might happen, with potential role as LBP or BPI in this species of scallop. Further research on the biological activities of ApLBP/BPIs are necessary to elucidate their participation in the scallop immune response.

In-depth serum proteomics reveals biomarkers of psoriasis severity and response to traditional Chinese medicine.

Serum and plasma contain abundant biological information that reflect the body's physiological and pathological conditions and are therefore a valuable sample type for disease biomarkers. However, comprehensive profiling of the serological proteome is challenging due to the wide range of protein concentrations in serum. Methods: To address this challenge, we developed a novel in-depth serum proteomics platform capable of analyzing the serum proteome across ~10 orders or magnitude by combining data obtained from Data Independent Acquisition Mass Spectrometry (DIA-MS) and customizable antibody microarrays. Results: Using psoriasis as a proof-of-concept disease model, we screened 50 serum proteomes from healthy controls and psoriasis patients before and after treatment with traditional Chinese medicine (YinXieLing) on our in-depth serum proteomics platform. We identified 106 differentially-expressed proteins in psoriasis patients involved in psoriasis-relevant biological processes, such as blood coagulation, inflammation, apoptosis and angiogenesis signaling pathways. In addition, unbiased clustering and principle component analysis revealed 58 proteins discriminating healthy volunteers from psoriasis patients and 12 proteins distinguishing responders from non-responders to YinXieLing. To further demonstrate the clinical utility of our platform, we performed correlation analyses between serum proteomes and psoriasis activity and found a positive association between the psoriasis area and severity index (PASI) score with three serum proteins (PI3, CCL22, IL-12B). Conclusion: Taken together, these results demonstrate the clinical utility of our in-depth serum proteomics platform to identify specific diagnostic and predictive biomarkers of psoriasis and other immune-mediated diseases.

Alterations of Human Plasma Proteome Profile on Adaptation to High-Altitude Hypobaric Hypoxia.

For individuals migrating to or residing permanently in high-altitude regions, environmental hypobaric hypoxia is a primary challenge that induces several physiological or pathological responses. It is well documented that human beings adapt to hypobaric hypoxia via some protective mechanisms, such as erythropoiesis and overproduction of hemoglobin; however, little is known on the alterations of plasma proteome profiles in accommodation to high-altitude hypobaric hypoxia. In the present study, we investigated differential plasma proteomes of high altitude natives and lowland normal controls by a TMT-based proteomic approach. A total of 818 proteins were identified, of which 137 were differentially altered. Bioinformatics (including GO, KEGG, protein-protein interactions, etc.) analysis showed that the differentially altered proteins were basically involved in complement and coagulation cascades, antioxidative stress, and glycolysis. Validation results demonstrated that CCL18, C9, PF4, MPO, and S100A9 were notably up-regulated, and HRG and F11 were down-regulated in high altitude natives, which were consistent with TMT-based proteomic results. Our findings highlight the contributions of complement and coagulation cascades, antioxidative stress, and glycolysis in acclimatization to hypobaric hypoxia and provide a foundation for developing potential diagnostic or/and therapeutic biomarkers for high altitude hypobaric hypoxia-induced diseases.

Differences in expression of serum protein in patients with psoriasis vulgaris and blood heat syndrome and healthy volunteers.

To explore the mechanism of psoriasis vulgaris (PV), serum protein expression profiles between PV patients with blood-heat syndrome and healthy volunteers were detected by isobaric tags for relative and absolute quantitation (iTRAQ). First, sera from 15 PV patients with blood-heat syndrome and 10 healthy volunteers were collected; then, serum proteins were separated and hydrolyzed by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and a specific iTRAQ marker enzyme respectively after further purification and protein abundance treatment. Compared with the control group, differentially expressed proteins in PV patients with blood-heat syndrome were identified and analyzed by tandem mass spectrometry. A total of 787 proteins were identified and 718 proteins had a functional annotation with gene ontology (GO) by iTRAQ in the current study. Significant differences (P <0.05) and great differences (P <0.01) were found in 681 proteins and 536 proteins respectively between the patient group and healthy group. ). Different protein expression profiles in serum existed between PV patients with blood-heat syndrome and healthy volunteers; the differences largely involved immune-related proteins and lipoproteins. The proteins specific for PV with blood-heat syndrome deserves further investigation.

Identification of Jak-STAT signaling involvement in sarcoidosis severity via a novel microRNA-regulated peripheral blood mononuclear cell gene signature.

Sarcoidosis is a granulomatous lung disorder of unknown cause. The majority of individuals with sarcoidosis spontaneously achieve full remission (uncomplicated sarcoidosis), however, ~20% of sarcoidosis-affected individuals experience progressive lung disease or cardiac and nervous system involvement (complicated sarcoidosis). We investigated peripheral blood mononuclear cell (PBMC) microRNA and protein-coding gene expression data from healthy controls and patients with uncomplicated or complicated sarcoidosis. We identified 46 microRNAs and 1,559 genes that were differentially expressed across a continuum of sarcoidosis severity (healthy control → uncomplicated sarcoidosis → complicated sarcoidosis). A total of 19 microRNA-mRNA regulatory pairs were identified within these deregulated microRNAs and mRNAs, which consisted of 17 unique protein-coding genes yielding a 17-gene signature. Pathway analysis of the 17-gene signature revealed Jak-STAT signaling pathway as the most significantly represented pathway. A severity score was assigned to each patient based on the expression of the 17-gene signature and a significant increasing trend in the severity score was observed from healthy control, to uncomplicated sarcoidosis, and finally to complicated sarcoidosis. In addition, this microRNA-regulated gene signature differentiates sarcoidosis patients from healthy controls in independent validation cohorts. Our study suggests that PBMC gene expression is useful in diagnosis of sarcoidosis.

Time- and radiation-dose dependent changes in the plasma proteome after total body irradiation of non-human primates: Implications for biomarker selection.

Acute radiation syndrome (ARS) is a complex multi-organ disease resulting from total body exposure to high doses of radiation. Individuals can be exposed to total body irradiation (TBI) in a number of ways, including terrorist radiological weapons or nuclear accidents. In order to determine whether an individual has been exposed to high doses of radiation and needs countermeasure treatment, robust biomarkers are needed to estimate radiation exposure from biospecimens such as blood or urine. In order to identity such candidate biomarkers of radiation exposure, high-resolution proteomics was used to analyze plasma from non-human primates following whole body irradiation (Co-60 at 6.7 Gy and 7.4 Gy) with a twelve day observation period. A total of 663 proteins were evaluated from the plasma proteome analysis. A panel of plasma proteins with characteristic time- and dose-dependent changes was identified. In addition to the plasma proteomics study reported here, we recently identified candidate biomarkers using urine from these same non-human primates. From the proteomic analysis of both plasma and urine, we identified ten overlapping proteins that significantly differentiate both time and dose variables. These shared plasma and urine proteins represent optimal candidate biomarkers of radiation exposure.

Differential expression and clinical significance of serum protein among patients with clear-cell renal cell carcinoma.

BACKGROUND AND OBJECTIVE: Looking for tumor markers by using protein chip technology is one of the hot topics, but many studies are still limited on short term detection of differential expressed proteins before and after surgery among patients with RCC. This study analyzed differential expressed serum protein and its clinical significance with clear-cell renal cell carcinoma to further measurement of the rule of variable expressing. METHODS: Eighty-nine patients with clear-cell renal cell carcinoma who underwent surgery from November 2013 to 2014 and postoperatively confirmed by pathology were entered in RCC group, 100 healthy volunteers and patients without RCC who underwent medical examination in the same period were entered in control group. The serum protein were analyzed in both group before surgery and every regular follow-up period in 1 year after surgery with RCC group. The surface-enhanced laser desorption ionization time of flight mass spectrometry (SELDI-TOF-MS) and weak cation exchange protein chip (CM10) technology systems were used for identifying differential expressed serum protein in RCC group and controls. The linear support vector machine (SVM) was applied to establish the diagnostic model of protein fingerprints and the leave-one-out cross validation was used for determining model discriminating effect. The differential expressed proteins were analyzed by ZUCI-PDAS protein spectral data analysis system. RESULTS: Five kinds of proteins were identified as potential biomarker, ultimately. The M/Z of these proteins was 15953, 7987, 9304, 8948, 5911, respectively. There were significant difference on expression level of these proteins with two groups preoperatively (P< 0.05). Comparison of all postoperative expression levels to preoperative one and each differential level mutually between a year in postoperative period also revealed statistical significance (P< 0.05). With taking identified proteins as biomarker, the sensitivity and specificity in predicting clear-cell renal cell carcinoma was 88.8% (79/89) and 91.0% (91/100), respectively. CONCLUSION: The corresponding specific protein was Bcl-2 family apoptosis regulatory proteins, WAP four-disulfide core protein, Krueppel-like factor 8, monocyte chemotactic protein-1, serum amyloid ß -protein-4, respectively, and will may serve as tumor markers of kidney cancer. These proteins manifests high predictive value for clear-cell renal cell carcinoma, and may contribute to therapeutic evaluation, prognosis and targeted therapy for clear-cell renal cell carcinoma.

A candidate plasma protein classifier to identify Alzheimer's disease.

Biomarkers currently used in the aid for the diagnosis of Alzheimer's disease (AD) are cerebrospinal fluid (CSF) protein markers and brain neuroimaging markers. These biomarkers, however, either involve semi-invasive procedures or are costly to measure. Thus, AD biomarkers from more easily accessible body fluids, such as plasma, are very enticing. Using an aptamer-based proteomic technology, we profiled 1,129 plasma proteins of AD patients and non-demented control individuals. A 5-protein classifier for AD identification was constructed in the discovery study with excellent 10-fold cross-validation performance (90.1% sensitivity, 84.2% specificity, 87.9% accuracy, and AUC as 0.94). In an independent validation study, the classifier was applied and correctly predicted AD with 100.0% sensitivity, 80.0% specificity, and 90.0% accuracy, matching or outperforming the CSF Aß42 and tau biomarkers whose performance were assessed in individual-matched CSF samples obtained at the same visit as plasma sample collection. Moreover, the classifier also correctly predicted mild cognitive impairment, an early pre-dementia state of the disease, with 96.7% sensitivity, 80.0% specificity, and 92.5% accuracy. These studies demonstrate that plasma proteins could be used effectively and accurately to contribute to the clinical diagnosis of AD. Although additional and more diverse cohorts are needed for further validation of the robustness, including the support of postmortem diagnosis, the 5-protein classifier appears to be a promising blood test to contribute diagnosis of AD.

Proteomic biomarkers of recovered heart function.

AIMS: Chronic heart failure is a costly epidemic that affects up to 2% of people in developed countries. The purpose of this study was to discover novel blood proteomic biomarker signatures of recovered heart function that could lead to more effective heart failure patient management by both primary care and specialty physicians. METHODS AND RESULTS: The discovery cohort included 41 heart transplant patients and 20 healthy individuals. Plasma levels of 138 proteins were detected in at least 75% of these subjects by iTRAQ mass spectrometry. Eighteen proteins were identified that had (i) differential levels between pre-transplant patients with end-stage heart failure and healthy individuals; and (ii) levels that returned to normal by 1 month post-transplant in patients with stable heart function after transplantation. Seventeen of the 18 markers were validated by multiple reaction monitoring mass spectrometry in a cohort of 39 heart failure patients treated with drug therapy, of which 30 had recovered heart function and 9 had not. This 17-protein biomarker panel had 93% sensitivity and 89% specificity, while the RAMP® NT-proBNP assay had the same specificity but 80% sensitivity. Performance further improved when the panel was combined with NT-proBNP, yielding a net reclassification index relative to NT-proBNP of 0.28. CONCLUSIONS: We have identified potential blood biomarkers of recovered heart function by harnessing data from transplant patients. These biomarkers can lead to the development of an inexpensive protein-based blood test that could be used by physicians to monitor response to therapy in heart failure, resulting in more personalized, front-line heart failure patient management.

Annotating N termini for the human proteome project: N termini and Nα-acetylation status differentiate stable cleaved protein species from degradation remnants in the human erythrocyte proteome.

A goal of the Chromosome-centric Human Proteome Project is to identify all human protein species. With 3844 proteins annotated as "missing", this is challenging. Moreover, proteolytic processing generates new protein species with characteristic neo-N termini that are frequently accompanied by altered half-lives, function, interactions, and location. Enucleated and largely void of internal membranes and organelles, erythrocytes are simple yet proteomically challenging cells due to the high hemoglobin content and wide dynamic range of protein concentrations that impedes protein identification. Using the N-terminomics procedure TAILS, we identified 1369 human erythrocyte natural and neo-N-termini and 1234 proteins. Multiple semitryptic N-terminal peptides exhibited improved mass spectrometric identification properties versus the intact tryptic peptide enabling identification of 281 novel erythrocyte proteins and six missing proteins identified for the first time in the human proteome. With an improved bioinformatics workflow, we developed a new classification system and the Terminus Cluster Score. Thereby we described a new stabilizing N-end rule for processed protein termini, which discriminates novel protein species from degradation remnants, and identified protein domain hot spots susceptible to cleavage. Strikingly, 68% of the N-termini were within genome-encoded protein sequences, revealing alternative translation initiation sites, pervasive endoproteolytic processing, and stabilization of protein fragments in vivo. The mass spectrometry proteomics data have been deposited to ProteomeXchange with the data set identifier .

Plasma proteomics, the Human Proteome Project, and cancer-associated alternative splice variant proteins.

This article addresses three inter-related subjects: the development of the Human Plasma Proteome Peptide Atlas, the launch of the Human Proteome Project, and the emergence of alternative splice variant transcripts and proteins as important features of evolution and pathogenesis. The current Plasma Peptide Atlas provides evidence on which peptides have been detected for every protein confidently identified in plasma; there are links to their spectra and their estimated abundance, facilitating the planning of targeted proteomics for biomarker studies. The Human Proteome Project (HPP) combines a chromosome-centric C-HPP with a biology and disease-driven B/D-HPP, upon a foundation of mass spectrometry, antibody, and knowledgebase resource pillars. The HPP aims to identify the approximately 7000 "missing proteins" and to characterize all proteins and their many isoforms. Success will enable the larger research community to utilize newly-available peptides, spectra, informative MS transitions, and databases for targeted analyses of priority proteins for each organ and disease. Among the isoforms of proteins, splice variants have the special feature of greatly enlarging protein diversity without enlarging the genome; evidence is accumulating of striking differential expression of splice variants in cancers. In this era of RNA-sequencing and advanced mass spectrometry, it is no longer sufficient to speak simply of increased or decreased expression of genes or proteins without carefully examining the splice variants in the protein mixture produced from each multi-exon gene. This article is part of a Special Issue entitled: Biomarkers: A Proteomic Challenge.