Quantitative mass spectrometric multiple reaction monitoring assays for major plasma proteins

Tissue-Specific Analysis of Secondary Metabolites Creates a Reliable Morphological Criterion for Quality Grading of Polygoni Multiflori Radix

In commercial herbal markets, Polygoni Multiflori Radix (PMR, the tuberous roots of Polygonum multiflorum Thunb.), a commonly-used Chinese medicinal material, is divided into different grades based on morphological features of size and weight. While more weight and larger size command a higher price, there is no scientific data confirming that the more expensive roots are in fact of better quality. To assess the inherent quality of various grades and of various tissues in PMR and to find reliable morphological indicators of quality, a method combining laser microdissection (LMD) and ultra-performance liquid chromatography triple-quadrupole mass spectrometry (UPLC-QqQ-MS/MS) was applied. Twelve major chemical components were quantitatively determined in both whole material and different tissues of PMR. Determination of the whole material revealed that traditional commercial grades based on size and weight of PRM did not correspond to any significant differences in chemical content. Instead, tissue-specific analysis indicated that the morphological features could be linked with quality in a new way. That is, PMR with broader cork and phloem, as seen in a transverse section, were typically of better quality as these parts are where the bioactive components accumulate. The tissue-specific analysis of secondary metabolites creates a reliable morphological criterion for quality grading of PMR.

Hierarchical structural component modeling of microRNA-mRNA integration analysis

BACKGROUND

Identification of multi-markers is one of the most challenging issues in personalized medicine era. Nowadays, many different types of omics data are generated from the same subject. Although many methods endeavor to identify candidate markers, for each type of omics data, few or none can facilitate such identification.

RESULTS

It is well known that microRNAs affect phenotypes only indirectly, through regulating mRNA expression and/or protein translation. Toward addressing this issue, we suggest a hierarchical structured component analysis of microRNA-mRNA integration ("HisCoM-mimi") model that accounts for this biological relationship, to efficiently study and identify such integrated markers. In simulation studies, HisCoM-mimi showed the better performance than the other three methods. Also, in real data analysis, HisCoM-mimi successfully identified more gives more informative miRNA-mRNA integration sets relationships for pancreatic ductal adenocarcinoma (PDAC) diagnosis, compared to the other methods.

CONCLUSION

As exemplified by an application to pancreatic cancer data, our proposed model effectively identified integrated miRNA/target mRNA pairs as markers for early diagnosis, providing a much broader biological interpretation.

Diagnostic Accuracy of Protein Glycation Sites in Long-Term Controlled Patients with Type 2 Diabetes Mellitus and Their Prognostic Potential for Early Diagnosis

Current screening tests for type 2 diabetes mellitus (T2DM) identify less than 50% of undiagnosed T2DM patients and provide no information about how the disease will develop in prediabetic patients. Here, twenty-nine protein glycation sites were quantified after tryptic digestion of plasma samples at the peptide level using tandem mass spectrometry and isotope-labelled peptides as internal standard. The glycation degrees were determined in three groups, i.e., 48 patients with a duration of T2DM exceeding ten years, 48 non-diabetic individuals matched for gender, BMI, and age, and 20 prediabetic men. In long-term controlled diabetic patients, 27 glycated peptides were detected at significantly higher levels, providing moderate diagnostic accuracies (ACCs) from 61 to 79%, allowing a subgrouping of patients in three distinct clusters. Moreover, a feature set of one glycated peptides and six established clinical parameters provided an ACC of 95%. The same number of clusters was identified in prediabetic males (ACC of 95%) using a set of eight glycation sites (mostly from serum albumin). All patients present in one cluster showed progression of prediabetic state or advanced towards diabetes in the following five years. Overall, the studied glycation sites appear to be promising biomarkers for subgrouping prediabetic patients to estimate their risk for the development of T2DM.

Assessment of microbiota:host interactions at the vaginal mucosa interface

There is increasing appreciation of the role that vaginal microbiota play in health and disease throughout a woman's lifespan. This has been driven partly by molecular techniques that enable detailed identification and characterisation of microbial community structures. However, these methods do not enable assessment of the biochemical and immunological interactions between host and vaginal microbiota involved in pathophysiology. This review examines our current knowledge of the relationships that exist between vaginal microbiota and the host at the level of the vaginal mucosal interface. We also consider methodological approaches to microbiomic, immunologic and metabolic profiling that permit assessment of these interactions. Integration of information derived from these platforms brings the potential for biomarker discovery, disease risk stratification and improved understanding of the mechanisms regulating vaginal microbial community dynamics in health and disease.

In-depth proteomic profiling of left ventricular tissues in human end-stage dilated cardiomyopathy

Dilated cardiomyopathy (DCM) is caused by reduced left ventricular (LV) myocardial function, which is one of the most common causes of heart failure (HF). We performed iTRAQ-coupled 2D-LC-MS/MS to profile the cardiac proteome of LV tissues from healthy controls and patients with end-stage DCM. We identified 4263 proteins, of which 125 were differentially expressed in DCM tissues compared to LV controls. The majority of these were membrane proteins related to cellular junctions and neuronal metabolism. In addition, these proteins were involved in membrane organization, mitochondrial organization, translation, protein transport, and cell death process. Four key proteins involved in the cell death process were also detected by western blotting, indicated that cell death was activated in DCM tissues. Furthermore, S100A1 and eEF2 were enriched in the “cellular assembly and organization” and “cell cycle” networks, respectively. We verified decreases in these two proteins in end-stage DCM LV samples through multiple reaction monitoring (MRM). These observations demonstrate that our understanding of the mechanisms underlying DCM can be deepened through comparison of the proteomes of normal LV tissues with that from end-stage DCM in humans.

An HS-MRM Assay for the Quantification of Host-cell Proteins in Protein Biopharmaceuticals by Liquid Chromatography Ion Mobility QTOF Mass Spectrometry

The analysis of low-level (1-100 ppm) protein impurities (e.g., host-cell proteins (HCPs)) in protein biotherapeutics is a challenging assay requiring high sensitivity and a wide dynamic range. Mass spectrometry-based quantification assays for proteins typically involve protein digestion followed by the selective reaction monitoring/multiple reaction monitoring (SRM/MRM) quantification of peptides using a low-resolution (Rs ~1,000) tandem quadrupole mass spectrometer. One of the limitations of this approach is the interference phenomenon observed when the peptide of interest has the "same" precursor and fragment mass (in terms of m/z values) as other co-eluting peptides present in the sample (within a 1-Da window). To avoid this phenomenon, we propose an alternative mass spectrometric approach, a high selectivity (HS) MRM assay that combines the ion mobility separation of peptide precursors with the high-resolution (Rs ~30,000) MS detection of peptide fragments. We explored the capabilities of this approach to quantify low-abundance peptide standards spiked in a monoclonal antibody (mAb) digest and demonstrated that it has the sensitivity and dynamic range (at least 3 orders of magnitude) typically achieved in HCP analysis. All six peptide standards were detected at concentrations as low as 0.1 nM (1 femtomole loaded on a 2.1-mm ID chromatographic column) in the presence of a high-abundance peptide background (2 µg of a mAb digest loaded on-column). When considering the MW of rabbit phosphorylase (97.2 kDa), from which the spiked peptides were derived, the LOQ of this assay is lower than 50 ppm. Relative standard deviations (RSD) of peak areas (n = 4 replicates) were less than 15% across the entire concentration range investigated (0.1-100 nM or 1-1,000 ppm) in this study.

Identifying Clinically Relevant Proteins for Targeted Analysis in the Development of a Multiplexed Proteomic Biomarker Assay

In recent years, hundreds of candidate protein biomarkers have been identified using discovery-based proteomics. Despite the large number of candidate biomarkers, few proteins advance to clinical validation. Here, we describe a hypothesis driven approach to identify candidate biomarkers, previously characterized in the literature, with the highest probability of clinical applicability. A ranking method, the hypothesis directed biomarker ranking (HDBR) system, was developed to score candidate biomarkers based on seven criteria deemed important in the selection of clinically useful biomarkers. The HDBR system was initially applied to identify candidate biomarkers for the development of a diagnostic test for the early detection of colorectal cancer, but this system can be widely applied to identify biomarkers of relevance in different disease states, for diagnosis, prognostication, or any other specific purpose.

The promise of targeted proteomics for quantitative network biology

Proteomics is a powerful tool for obtaining information on a large number of proteins with regard to their expression levels, interactions with other molecules, and posttranslational modifications. Whereas nontargeted, discovery proteomics uncovers differences in the proteomic landscape under different conditions, targeted proteomics has been developed to overcome the limitations of this approach with regard to quantitation. In addition to technical advances in instruments and informatics tools, the advent of the synthetic proteome composed of synthetic peptides or recombinant proteins has advanced the adoption of targeted proteomics across a wide range of research fields. Targeted proteomics can now be applied to measurement of the dynamics of any proteins of interest under a variety of conditions as well as to estimation of the absolute abundance or stoichiometry of proteins in a given network. Multiplexed targeted proteomics assays of high reproducibility and accuracy can provide insight at the quantitative level into entire networks that govern biological phenomena or diseases. Such assays will establish a new paradigm for data-driven science.

Determination of Site-Specific Phosphorylation Ratios in Proteins with Targeted Mass Spectrometry

We show that parallel reaction monitoring (PRM) can be used for exact quantification of phosphorylation ratios of proteins using stable-isotope-labeled peptides. We have compared two different PRM approaches on a digest of a U87 cell culture, namely, direct-PRM (tryptic digest measured by PRM without any further sample preparation) and TiO₂-PRM (tryptic digest enriched with TiO₂ cartridges, followed by PRM measurement); these approaches are compared for the following phosphorylation sites: neuroblast differentiation-associated protein (AHNAK S5480-p), calcium/calmodulin-dependent protein kinase type II subunit delta (CAMK2D T337-p), and epidermal growth factor receptor (EGFR S1166-p). A reproducible percentage of phosphorylation could be determined (CV 6-13%) using direct-PRM or TiO₂-PRM. In addition, we tested the approaches in a cell culture experiment in which U87 cells were deprived of serum. As a "gold standard" we included immune precipitation of EGFR followed by PRM (IP-PRM). For EGFR (S1166) and AHNAK (S5480) a statistical significant change in the percentage of phosphorylation could be observed as a result of serum deprivation; for EGFR (S1166) this change was observed for both TiO₂-PRM and IP-PRM. The presented approach has the potential to multiplex and to quantify the ratio of phosphorylation in a single analysis.

LC-MS/MS-Based Method for the Multiplex Detection of 24 Fentanyl Analogues and Metabolites in Whole Blood at Sub ng mL-1 Concentrations

The United States and numerous other countries worldwide are currently experiencing a public health crisis due to the abuse of illicitly manufactured fentanyl (IMF) and its analogues. This manuscript describes the development of a liquid chromatography-tandem mass spectrometry-based method for the multiplex detection of N = 24 IMF analogues and metabolites in whole blood at concentrations as low as 0.1-0.5 ng mL-1. These available IMFs were fentanyl, norfentanyl, furanyl norfentanyl, remifentanil acid, butyryl norfentanyl, remifentanil, acetyl fentanyl, alfentanil, AH-7921, U-47700, acetyl fentanyl 4-methylphenethyl, acrylfentanyl, para-methoxyfentanyl, despropionyl fentanyl (4-ANPP), furanyl fentanyl, despropionyl para-fluorofentanyl, carfentanil, (±)-cis-3-methyl fentanyl, butyryl fentanyl, isobutyryl fentanyl, sufentanil, valeryl fentanyl, para-fluorobutyryl fentanyl, and para-fluoroisobutyryl fentanyl. Most IMF analogues (N = 22) could be easily distinguished from one another; the isomeric forms butyryl/isobutyryl fentanyl and para-fluorobutyryl/para-fluoroisobutyryl fentanyl could not be differentiated. N = 13 of these IMF analogues were quantified for illustrative purposes, and their forensic quality control standards were also validated for limit of detection (0.017-0.056 ng mL-1), limit of quantitation (0.100-0.500 ng mL-1), selectivity/sensitivity, ionization suppression/enhancement (87-118%), process efficiency (60-95%), recovery (64-97%), bias (<20%), and precision (>80%). This flexible, time- and cost-efficient method was successfully implemented at the Montgomery County Coroner's Office/Miami Valley Regional Crime Laboratory in Dayton, Ohio, where it aided in the analysis of N = 725 postmortem blood samples collected from February 2015 to November 2016.

Defining tissue proteomes by systematic literature review

Defining protein composition is a key step in understanding the function of both healthy and diseased biological systems. There is currently little consensus between existing published proteomes in tissues such as the aorta, cartilage and organs such as skin. Lack of agreement as to both the number and identity of proteins may be due to issues in protein extraction, sensitivity/specificity of detection and the use of disparate tissue/cell sources. Here, we developed a method combining bioinformatics and systematic review to screen >32M articles from the Web of Science for evidence of proteins in healthy human skin. The resulting Manchester Proteome (www.manchesterproteome.manchester.ac.uk) collates existing evidence which characterises 2,948 skin proteins, 437 unique to our database and 2011 evidenced by both mass spectrometry and immune-based techniques. This approach circumvents the limitations of individual proteomics studies and can be applied to other species, organs, cells or disease-states. Accurate tissue proteomes will aid development of engineered constructs and offer insight into disease treatments by highlighting differences in proteomic composition.

Absolute Protein Quantification Using AQUA-Calibrated 2D-PAGE

Absolute protein quantification for the analysis of proteome dynamics is more and more required by the scientific community. Therefore a number of methods have recently been reported that aim at determining concentrations of single proteins in complex samples, all of them having their advantages and limitations. However, for all of these methods an accurate and protein unspecific determination of the total protein amount in a given sample is urgently needed. Here a ninhydrin-based assay established to reach this goal is described. Moreover, an optimized protocol for protein digestion is an inevitable prerequisite for all mass spectrometry-based approaches aiming at absolute protein quantification. In this chapter, various aspects are described which have to be considered during validation of a suitable digestion method and a detailed protocol is presented that can be applied to the digestion of soluble proteins originated from microbes.In order to provide an absolute protein quantification workflow applicable for small scale and large scale approaches, a step-by-step guide is provided for the so-called AQUA-strategy (AQUA = absolute quantification), including selection of suited standard peptides, the development of optimized MS methods and the determination of absolute protein concentration using stable isotope dilution and selected reaction monitoring (SID-SRM). Subsequently, a workflow is introduced that combines targeted mass spectrometry and two-dimensional polyacrylamide gel electrophoresis for the large-scale determination of absolute protein amounts.

The Human Plasma Proteome Draft of 2017: Building on the Human Plasma PeptideAtlas from Mass Spectrometry and Complementary Assays

Human blood plasma provides a highly accessible window to the proteome of any individual in health and disease. Since its inception in 2002, the Human Proteome Organization's Human Plasma Proteome Project (HPPP) has been promoting advances in the study and understanding of the full protein complement of human plasma and on determining the abundance and modifications of its components. In 2017, we review the history of the HPPP and the advances of human plasma proteomics in general, including several recent achievements. We then present the latest 2017-04 build of Human Plasma PeptideAtlas, which yields ∼43 million peptide-spectrum matches and 122,730 distinct peptide sequences from 178 individual experiments at a 1% protein-level FDR globally across all experiments. Applying the latest Human Proteome Project Data Interpretation Guidelines, we catalog 3509 proteins that have at least two non-nested uniquely mapping peptides of nine amino acids or more and >1300 additional proteins with ambiguous evidence. We apply the same two-peptide guideline to historical PeptideAtlas builds going back to 2006 and examine the progress made in the past ten years in plasma proteome coverage. We also compare the distribution of proteins in historical PeptideAtlas builds in various RNA abundance and cellular localization categories. We then discuss advances in plasma proteomics based on targeted mass spectrometry as well as affinity assays, which during early 2017 target ∼2000 proteins. Finally, we describe considerations about sample handling and study design, concluding with an outlook for future advances in deciphering the human plasma proteome.

Mass spectrometry for the evaluation of cardiovascular diseases based on proteomics and lipidomics

The identification and quantification of proteins and lipids is of major importance for the diagnosis, prognosis and understanding of the molecular mechanisms involved in disease development. Owing to its selectivity and sensitivity, mass spectrometry has become a key technique in analytical platforms for proteomic and lipidomic investigations. Using this technique, many strategies have been developed based on unbiased or targeted approaches to highlight or monitor molecules of interest from biomatrices. Although these approaches have largely been employed in cancer research, this type of investigation has been met by a growing interest in the field of cardiovascular disorders, potentially leading to the discovery of novel biomarkers and the development of new therapies. In this paper, we will review the different mass spectrometry- based proteomic and lipidomic strategies applied in cardiovascular diseases, especially atherosclerosis. Particular attention will be given to recent developments and the role of bioinformatics in data treatment. This review will be of broad interest to the medical community by providing a tutorial of how mass spectrometric strategies can support clinical trials.

Clinical veterinary proteomics: Techniques and approaches to decipher the animal plasma proteome

Over the last two decades, technological advancements in the field of proteomics have advanced our understanding of the complex biological systems of living organisms. Techniques based on mass spectrometry (MS) have emerged as powerful tools to contextualise existing genomic information and to create quantitative protein profiles from plasma, tissues or cell lines of various species. Proteomic approaches have been used increasingly in veterinary science to investigate biological processes responsible for growth, reproduction and pathological events. However, the adoption of proteomic approaches by veterinary investigators lags behind that of researchers in the human medical field. Furthermore, in contrast to human proteomics studies, interpretation of veterinary proteomic data is difficult due to the limited protein databases available for many animal species. This review article examines the current use of advanced proteomics techniques for evaluation of animal health and welfare and covers the current status of clinical veterinary proteomics research, including successful protein identification and data interpretation studies. It includes a description of an emerging tool, sequential window acquisition of all theoretical fragment ion mass spectra (SWATH-MS), available on selected mass spectrometry instruments. This newly developed data acquisition technique combines advantages of discovery and targeted proteomics approaches, and thus has the potential to advance the veterinary proteomics field by enhancing identification and reproducibility of proteomics data.

Development, validation and application of a micro-liquid chromatography-tandem mass spectrometry based method for simultaneous quantification of selected protein biomarkers of endothelial dysfunction in murine plasma

The objective of this study was to develop and validate the method based on micro-liquid chromatography-tandem mass spectrometry (microLC/MS-MRM) for simultaneous determination of adiponectin (ADN), von Willebrand factor (vWF), soluble form of vascular cell adhesion molecule 1 (sVCAM-1), soluble form of intercellular adhesion molecule 1 (sICAM-1) and syndecan-1 (SDC-1) in mouse plasma. The calibration range was established from 2.5pmol/mL to 5000pmol/mL for ADN; 5pmol/mL to 5000pmol/mL for vWF; 0.375pmol/mL to 250pmol/mL for sVCAM-1 and sICAM-1; and 0.25pmol/mL to 250pmol/mL for SDC-1. The method was applied to measure the plasma concentration of selected proteins in mice fed high-fat diet (HFD), and revealed the pro-thrombotic status by increased concentration of vWF (1.31±0.17 nmol/mL (Control) vs 1.98±0.09 nmol/mL (HFD), p <0.05) and the dysregulation of adipose tissue metabolism by decreased concentration of ADN (0.62±0.08 nmol/mL (Control) vs 0.37±0.06 nmol/mL (HFD), p <0.05). In conclusion, the microLC/MS-MRM-based method allows for reliable measurements of selected protein biomarkers of endothelial dysfunction in mouse plasma.

Highly Reproducible Automated Proteomics Sample Preparation Workflow for Quantitative Mass Spectrometry

Sample preparation for protein quantification by mass spectrometry requires multiple processing steps including denaturation, reduction, alkylation, protease digestion, and peptide cleanup. Scaling these procedures for the analysis of numerous complex biological samples can be tedious and time-consuming, as there are many liquid transfer steps and timed reactions where technical variations can be introduced and propagated. We established an automated sample preparation workflow with a total processing time for 96 samples of 5 h, including a 2 h incubation with trypsin. Peptide cleanup is accomplished by online diversion during the LC/MS/MS analysis. In a selected reaction monitoring (SRM) assay targeting 6 plasma biomarkers and spiked β-galactosidase, mean intraday and interday cyclic voltammograms (CVs) for 5 serum and 5 plasma samples over 5 days were <20%. In a highly multiplexed SRM assay targeting more than 70 proteins, 90% of the transitions from 6 plasma samples repeated on 3 separate days had total CVs below 20%. Similar results were obtained when the workflow was transferred to a second site: 93% of peptides had CVs below 20%. An automated trypsin digestion workflow yields uniformly processed samples in less than 5 h. Reproducible quantification of peptides was observed across replicates, days, instruments, and laboratory sites, demonstrating the broad applicability of this approach.

Qualitative and quantitative characterization of protein biotherapeutics with liquid chromatography mass spectrometry

In the last decade, the advancement of liquid chromatography mass spectrometry (LC/MS) techniques has enabled their broad application in protein characterization, both quantitatively and qualitatively. Owing to certain important merits of LC/MS techniques (e.g., high selectivity, flexibility, and rapid method development), LC/MS assays are often deemed as preferable alternatives to conventional methods (e.g., ligand-binding assays) for the analysis of protein biotherapeutics. At the discovery and development stages, LC/MS is generally employed for two purposes absolute quantification of protein biotherapeutics in biological samples and qualitative characterization of proteins. For absolute quantification of a target protein in bio-matrices, recent work has led to improvements in the efficiency of LC/MS method development, sample treatment, enrichment and digestion, and high-performance low-flow-LC separation. These advances have enhanced analytical sensitivity, specificity, and robustness. As to qualitative analysis, a range of techniques have been developed to characterize intramolecular disulfide bonds, glycosylation, charge variants, primary sequence heterogeneity, and the drug-to-antibody ratio of antibody drug conjugate (ADC), which has enabled a refined ability to assess product quality. In this review, we will focus on the discussion of technical challenges and strategies of LC/MS-based quantification and characterization of biotherapeutics, with the emphasis on the analysis of antibody-based biotherapeutics such as monoclonal antibodies (mAbs) and ADCs. © 2016 Wiley Periodicals, Inc. Mass Spec Rev 36:734-754, 2017.

Assessment of Extracellular Vesicles Purity Using Proteomic Standards

The increasing interest in extracellular vesicles (EVs) research is fueled by reports indicating their unique role in intercellular communication and potential connection to the development of common human diseases. The unique role assumes unique protein and nucleic acid cargo. Unfortunately, accurate analysis of EVs cargo faces a challenge of EVs isolation. Generally used isolation techniques do not separate different subtypes of EVs and even more, poorly separate EVs from non-EVs contaminants. Further development of EVs isolation protocols urgently needs a quantitative method of EVs purity assessment. We report here that multiple reaction monitoring assay using internal standards carrying peptides for quantification of EVs and non-EVs proteins is a suitable approach to assess purity of EVs preparations. As a first step in potential standardization of EVs isolation, we have evaluated polymer-based precipitation techniques and compared them to traditional ultracentrifugation protocol.

Identification of Serological Biomarkers for Early Diagnosis of Lung Cancer Using a Protein Array-Based Approach

Lung cancer (LC) remains the leading cause of mortality from malignant tumors worldwide. Currently, a lack of serological biomarkers for early LC diagnosis is a major roadblock for early intervention and prevention of LC. To undertake this challenge, we employed a two-phase strategy to discover and validate a biomarker panel using a protein array-based approach. In Phase I, we obtained serological autoimmune profiles of 80 LC patients and 20 healthy subjects on HuProt arrays, and identified 170 candidate proteins significantly associated with LC. In Phase II, we constructed a LC focused array with the 170 proteins, and profiled a large cohort, comprised of 352 LC patients, 93 healthy individuals, and 101 patients with lung benign lesions (LBL). The comparison of autoimmune profiles between the early stage LC and the combined group of healthy and LBL allowed us to identify and validate a biomarker panel of p53, HRas, and ETHE1 for diagnosis of early stage LC with 50% sensitivity at >90% specificity. Finally, the performance of this biomarker panel was confirmed in ELISA tests. In summary, this study represents one of the most comprehensive proteome-wide surveys with one of the largest (i.e. 1,101 unique samples) and most diverse (i.e. nine disease groups) cohorts, resulting in a biomarker panel with good performance.

Discovery of gastric cancer specific biomarkers by the application of serum proteomics

Current diagnostic markers for gastric cancer are not sufficiently specific or sensitive for use in clinical practice. The aims of this study are to compare the proteomes of serum samples from patients with gastric cancers and normal controls, and to develop useful tumor markers of gastric cancer by quantitative proteomic analysis. We identified a total of 388 proteins with a ≤1% FDR and with at least two unique peptides from the sera of each group. Among them, 215, 251, and 260 proteins were identified in serum samples of patients in an advanced cancer group, early cancer group, and normal control group, respectively. We selected differentially expressed proteins in cancer patients compared with those of normal controls via semiquantitative analyses comparing the spectral counts of identified proteins. These differentially expressed proteins were successfully verified using an MS-based quantitative assay, multiple reactions monitoring analysis. Four proteins (vitronectin, clusterin isoform 1, thrombospondin 1, and tyrosine-protein kinase SRMS) were shown to have significant changes between the cancer groups and the normal control group. These four serum proteins were able to discriminate gastric cancer patients from normal controls with sufficient specificity and selectivity.

NBPMF

Mass spectrometry (MS) is an analytical technique for determining the composition of a sample. In bottom-up techniques, peptide mass fingerprinting (PMF) is widely used to identify proteins from MS dataset. In this article, the authors developed a novel network-based inference software termed NBPMF. By analyzing peptide-protein bipartite network, they designed new peptide protein matching score functions. They present two methods: the static one, ProbS, is based on an independent probability framework; and the dynamic one, HeatS, depicts input data as dependent peptides. The authors also use linear regression to adjust the matching score according to the masses of proteins. In addition, they consider the order of retention time to further correct the score function. In post processing, a peak can only be assigned to one peptide in order to reduce random matches. Finally, the authors try to filter out false positive proteins. The experiments on simulated and real data demonstrate that their NBPMF approaches lead to significantly improved performance compared to several state-of-the-art methods.

Assessing the relevance of a multiplexed methodology for proteomic biomarker measurement in the invertebrate species Gammarus fossarum: A physiological and ecotoxicological study

Recently, a protein sequence database was built specifically for the sentinel non-model species Gammarus fossarum using a proteogenomics approach. A quantitative multiplexed targeted proteomics assay (using Selected Reaction Monitoring mass spectrometry) was then developed for a fast and simultaneous quantification of dozens of biomarker peptides specific of this freshwater sentinel crustacean species. In order to assess the relevance of this breakthrough methodology in ecotoxicology, the response patterns of a panel of 26 peptides reporting for 20 proteins from the Gammarus fossarum proteome with putative key functional roles (homeostasis, osmoregulation, nutrition, reproduction, molting,…) were recorded through male and female reproductive cycles and after exposure to environmental concentrations of cadmium and lead in laboratory-controlled conditions. Based on these results, we validated the implication of annotated vtg-like peptides in the oogenesis process, and the implication of Na⁺/K⁺ ATPase proteins in the molt cycle of organisms. Upon metal (cadmium and lead) contamination, peptides belonging to proteins annotated as involved in antioxidant and detoxification functions, immunity and molting were significantly down-regulated. Overall, this multiplex assay allowed gaining relevant insights upon disruption of different main functions in the sentinel species Gammarus fossarum. This breakthrough methodology in ecotoxicology offers a valid and high throughput alternative to currently used protocols, paving the way for future practical applications of proteogenomics-derived protein biomarkers in chemical risk assessment and environmental monitoring.

Deep-Dive Targeted Quantification for Ultrasensitive Analysis of Proteins in Nondepleted Human Blood Plasma/Serum and Tissues

Mass spectrometry-based targeted proteomics (e.g., selected reaction monitoring, SRM) is emerging as an attractive alternative to immunoassays for protein quantification. Recently we have made significant progress in SRM sensitivity for enabling quantification of low nanograms per milliliter to sub-naograms per milliliter level proteins in nondepleted human blood plasma/serum without affinity enrichment. However, precise quantification of extremely low abundance proteins (e.g., ≤ 100 pg/mL in blood plasma/serum) using targeted proteomics approaches still remains challenging, especially for these samples without available antibodies for enrichment. To address this need, we have developed an antibody-independent deep-dive SRM (DD-SRM) approach that capitalizes on multidimensional high-resolution reversed-phase liquid chromatography (LC) separation for target peptide separation and enrichment combined with precise selection of target peptide fractions of interest, significantly improving SRM sensitivity by ∼5 orders of magnitude when compared to conventional LC-SRM. Application of DD-SRM to human serum and tissue provides precise quantification of endogenous proteins at the ∼10 pg/mL level in nondepleted serum and at <10 copies per cell level in tissue. Thus, DD-SRM holds great promise for precisely measuring extremely low abundance proteins or protein modifications, especially when high-quality antibodies are not available.

Emerging Affinity-Based Proteomic Technologies for Large-Scale Plasma Profiling in Cardiovascular Disease

Plasma biomarkers that reflect molecular states of the cardiovascular system are central for clinical decision making. Routinely used plasma biomarkers include troponins, natriuretic peptides, and lipoprotein particles, yet interrogate only a modest subset of pathways relevant to cardiovascular disease. Systematic profiling of a larger portion of circulating plasma proteins (the plasma proteome) will provide opportunities for unbiased discovery of novel markers to improve diagnostic or predictive accuracy. In addition, proteomic profiling may inform pathophysiological understanding and point to novel therapeutic targets. Obstacles for comprehensive proteomic profiling include the immense size and structural heterogeneity of the proteome, and the broad range of abundance levels, as well. Proteome-wide, untargeted profiling can be performed in tissues and cells with tandem mass spectrometry. However, applications to plasma are limited by the need for complex preanalytical sample preparation stages limiting sample throughput. Multiplexing of targeted methods based on capture and detection of specific proteins are therefore receiving increasing attention in plasma proteomics. Immunoaffinity assays are the workhorse for measuring individual proteins but have been limited for proteomic applications by long development times, cross-reactivity preventing multiplexing, specificity issues, and incomplete sensitivity to detect proteins in the lower range of the abundance spectrum (below picograms per milliliter). Emerging technologies to address these issues include nucleotide-labeled immunoassays and aptamer reagents that can be automated for efficient multiplexing of thousands of proteins at high sample throughput, coupling of affinity capture methods to mass spectrometry for improved specificity, and ultrasensitive detection systems to measure low-abundance proteins. In addition, proteomics can now be integrated with modern genomics tools to comprehensively relate proteomic profiles to genetic variants, which may both influence binding of affinity reagents and serve to validate the target specificity of affinity assays. The application of deep quantitative proteomic profiling to large cohorts has thus become increasingly feasible with emerging affinity methods. The aims of this article are to provide the broad readership of Circulation with a timely overview of emerging methods for affinity proteomics and recent progress in cardiovascular medicine based on such methods.

Absolute Quantification of Toxicological Biomarkers via Mass Spectrometry

With the advent of "-omics" technologies there has been an explosion of data generation in the field of toxicology, as well as many others. As new candidate biomarkers of toxicity are being regularly discovered, the next challenge is to validate these observations in a targeted manner. Traditionally, these validation experiments have been conducted using antibody-based technologies such as Western blotting, ELISA, and immunohistochemistry. However, this often produces a significant bottleneck as the time, cost, and development of successful antibodies are often far outpaced by the generation of targets of interest. In response to this, there recently have been several developments in the use of triple quadrupole (QQQ) mass spectrometry (MS) as a platform to provide quantification of proteins. This technology does not require antibodies; it is typically less expensive and quicker to develop assays and has the opportunity for more accessible multiplexing. The speed of these experiments combined with their flexibility and ability to multiplex assays makes the technique a valuable strategy to validate biomarker discovery.

Identification of Differentially Expressed Splice Variants by the Proteogenomic Pipeline Splicify

Proteogenomics, i.e. comprehensive integration of genomics and proteomics data, is a powerful approach identifying novel protein biomarkers. This is especially the case for proteins that differ structurally between disease and control conditions. As tumor development is associated with aberrant splicing, we focus on this rich source of cancer specific biomarkers. To this end, we developed a proteogenomic pipeline, Splicify, which can detect differentially expressed protein isoforms. Splicify is based on integrating RNA massive parallel sequencing data and tandem mass spectrometry proteomics data to identify protein isoforms resulting from differential splicing between two conditions. Proof of concept was obtained by applying Splicify to RNA sequencing and mass spectrometry data obtained from colorectal cancer cell line SW480, before and after siRNA-mediated downmodulation of the splicing factors SF3B1 and SRSF1. These analyses revealed 2172 and 149 differentially expressed isoforms, respectively, with peptide confirmation upon knock-down of SF3B1 and SRSF1 compared with their controls. Splice variants identified included RAC1, OSBPL3, MKI67, and SYK. One additional sample was analyzed by PacBio Iso-Seq full-length transcript sequencing after SF3B1 downmodulation. This analysis verified the alternative splicing identified by Splicify and in addition identified novel splicing events that were not represented in the human reference genome annotation. Therefore, Splicify offers a validated proteogenomic data analysis pipeline for identification of disease specific protein biomarkers resulting from mRNA alternative splicing. Splicify is publicly available on GitHub (https://github.com/NKI-TGO/SPLICIFY) and suitable to address basic research questions using pre-clinical model systems as well as translational research questions using patient-derived samples, e.g. allowing to identify clinically relevant biomarkers.

The impact of growth hormone on proteomic profiles: a review of mouse and adult human studies

Growth hormone (GH) is a protein that is known to stimulate postnatal growth, counter regulate insulin's action and induce expression of insulin-like growth factor-1. GH exerts anabolic or catabolic effects depending upon on the targeted tissue. For instance, GH increases skeletal muscle and decreases adipose tissue mass. Our laboratory has spent the past two decades studying these effects, including the effects of GH excess and depletion, on the proteome of several mouse and human tissues. This review first discusses proteomic techniques that are commonly used for these types of studies. We then examine the proteomic differences found in mice with excess circulating GH (bGH mice) or mice with disruption of the GH receptor gene (GHR^-/-). We also describe the effects of increased and decreased GH action on the proteome of adult patients with either acromegaly, GH deficiency or patients after short-term GH treatment. Finally, we explain how these proteomic studies resulted in the discovery of potential biomarkers for GH action, particularly those related with the effects of GH on aging, glucose metabolism and body composition.

Quantitative proteomics in lung cancer

Lung cancer is the most common cause of cancer-related death worldwide, less than 7% of patients survive 10 years following diagnosis across all stages of lung cancer. Late stage of diagnosis and lack of effective and personalized medicine reflect the need for a better understanding of the mechanisms that underlie lung cancer progression. Quantitative proteomics provides the relative different protein abundance in normal and cancer patients which offers the information for molecular interactions, signaling pathways, and biomarker identification. Here we introduce both theoretical and practical applications in the use of quantitative proteomics approaches, with principles of current technologies and methodologies including gel-based, label free, stable isotope labeling as well as targeted proteomics. Predictive markers of drug resistance, candidate biomarkers for diagnosis, and prognostic markers in lung cancer have also been discovered and analyzed by quantitative proteomic analysis. Moreover, construction of protein networks enables to provide an opportunity to interpret disease pathway and improve our understanding in cancer therapeutic strategies, allowing the discovery of molecular markers and new therapeutic targets for lung cancer.

Improvements in Mass Spectrometry Assay Library Generation for Targeted Proteomics

In data-independent acquisition mass spectrometry (DIA-MS), targeted extraction of peptide signals in silico using mass spectrometry assay libraries is a successful method for the identification and quantification of proteins. However, it remains unclear if high quality assay libraries with more accurate peptide ion coordinates can improve peptide target identification rates in DIA analysis. In this study, we systematically improved and evaluated the common algorithmic steps for assay library generation and demonstrate that increased assay quality results in substantially higher identification rates of peptide targets from mouse organ protein lysates measured by DIA-MS. The introduced changes are (1) a new spectrum interpretation algorithm, (2) reapplication of segmented retention time normalization, (3) a ppm fragment mass error matching threshold, (4) usage of internal peptide fragments, and (5) a multilevel false discovery rate calculation. Taken together, these changes yielded 14-36% more identified peptide targets at 1% assay false discovery rate and are implemented in three new open source tools, Fraggle, Tramler, and Franklin, available at https://github.com/fickludd/eviltools . The improved algorithms provide ways to better utilize discovery MS data, translating to substantially increased DIA performance and ultimately better foundations for drawing biological conclusions in DIA-based experiments.

Pumilacidin-Like Lipopeptides Derived from Marine Bacterium Bacillus sp. Strain 176 Suppress the Motility of Vibrio alginolyticus

Bacterial motility is a crucial factor during the invasion and colonization processes of pathogens, which makes it an attractive therapeutic drug target. Here, we isolated a marine bacterium (Vibrio alginolyticus strain 178) from a seamount in the tropical West Pacific that exhibits vigorous motility on agar plates and severe pathogenicity to zebrafish. We found that V. alginolyticus 178 motility was significantly suppressed by another marine bacterium, Bacillus sp. strain 176, isolated from the same niche. We isolated, purified, and characterized two different cyclic lipopeptides (CLPs) from Bacillus sp. 176 using high-performance liquid chromatography, mass spectrometry, and nuclear magnetic resonance spectroscopy. The two related CLPs have a pumilacidin-like structure and were both effective inhibitors of V. alginolyticus 178 motility. The CLPs differ by only one methylene group in their fatty acid chains. In addition to motility suppression, the CLPs also induced cell aggregation in the medium and reduced adherence of V. alginolyticus 178 to glass substrates. Notably, upon CLP treatment, the expression levels of two V. alginolyticus flagellar assembly genes (flgA and flgP) dropped dramatically. Moreover, the CLPs inhibited biofilm formation in several other strains of pathogenic bacteria without inducing cell death. This study indicates that CLPs from Bacillus sp. 176 show promise as antimicrobial lead compounds targeting bacterial motility and biofilm formation with a low potential for eliciting antibiotic resistance.IMPORTANCE Pathogenic bacteria often require motility to establish infections and subsequently spread within host organisms. Thus, motility is an attractive therapeutic target for the development of novel antibiotics. We found that cyclic lipopeptides (CLPs) produced by marine bacterium Bacillus sp. strain 176 dramatically suppress the motility of the pathogenic bacterium Vibrio alginolyticus strain 178, reduce biofilm formation, and promote cellular aggregation without inducing cell death. These findings suggest that CLPs hold great promise as potential drug candidates targeting bacterial motility and biofilm formation with a low overall potential for triggering antibiotic resistance.

Identification of a distinctive phenotype for endocarditis-associated clonal complex 22 MRSA isolates with reduced vancomycin susceptibility

PURPOSE

We previously identified an association between CC22 meticillin-resistant Staphylococcus aureus (MRSA) bloodstream infection isolates with an elevated vancomycin MIC (V-MIC) in the susceptible range (1.5-2 mg l-1) and endocarditis. This study explores whether these isolates have a specific phenotype consistent with the clinical findings.

METHODOLOGY

CC22 and CC30 MRSA isolates with high (1.5-2 mg l-1) and low (≤0.5 mg l-1) V-MICs were tested for fibrinogen and fibronectin binding, virulence in a Galleria mellonella caterpillar model, phenol soluble modulin production and accessory gene regulator (agr) expression.

RESULTS

CC22 high V-MIC, but not CC30 high V-MIC isolates, showed sustained fibrinogen binding through a stationary growth phase and increased PSM production, specifically PSMα1, compared with respective low V-MIC isolates. Expression was lower in both CC22 and CC30 high V-MIC isolates compared with respective low V-MIC isolates, although there was no associated reduction in virulence in the caterpillar model.

CONCLUSIONS

The identification of a distinct phenotype for CC22 high V-MIC isolates supports the hypothesis that bacterial factors contribute to the mechanism underlying their association with endocarditis. Further study of these isolates could shed light on the molecular mechanism of endocarditis in humans.

Mass Spectrometry Approaches for Identification and Quantitation of Therapeutic Monoclonal Antibodies in the Clinical Laboratory

Therapeutic monoclonal antibodies (MAbs) are an important class of drugs used to treat diseases ranging from autoimmune disorders to B cell lymphomas to other rare conditions thought to be untreatable in the past. Many advances have been made in the characterization of immunoglobulins as a result of pharmaceutical companies investing in technologies that allow them to better understand MAbs during the development phase. Mass spectrometry is one of the new advancements utilized extensively by pharma to analyze MAbs and is now beginning to be applied in the clinical laboratory setting. The rise in the use of therapeutic MAbs has opened up new challenges for the development of assays for monitoring this class of drugs. MAbs are larger and more complex than typical small-molecule therapeutic drugs routinely analyzed by mass spectrometry. In addition, they must be quantified in samples that contain endogenous immunoglobulins with nearly identical structures. In contrast to an enzyme-linked immunosorbent assay (ELISA) for quantifying MAbs, mass spectrometry-based assays do not rely on MAb-specific reagents such as recombinant antigens and/or anti-idiotypic antibodies, and time for development is usually shorter. Furthermore, using molecular mass as a measurement tool provides increased specificity since it is a first-order principle unique to each MAb. This enables rapid quantification of MAbs and multiplexing. This review describes how mass spectrometry can become an important tool for clinical chemists and especially immunologists, who are starting to develop assays for MAbs in the clinical laboratory and are considering mass spectrometry as a versatile platform for the task.

A survey of proteomic biomarkers for heterotopic ossification in blood serum

Background

Heterotopic ossification (HO) is a significant problem for wounded warriors surviving high-energy blast injuries; however, currently, there is no biomarker panel capable of globally characterizing, diagnosing, and monitoring HO progression. The aim of this study was to identify biomarkers for HO using proteomic techniques and blood serum.

Methods

Isobaric tags for relative and absolute quantitation (iTRAQ) was used to generate a semi-quantitative global proteomics survey of serum from patients with and without heterotopic ossification. Leveraging the iTRAQ data, a targeted selection reaction monitoring mass spectrometry (SRM-MS) assay was developed for 10 protein candidates: alkaline phosphatase, osteocalcin, alpha-2 type I collagen, collagen alpha-1(V) chain isoform 2 preprotein, bone sialoprotein 2, phosphatidate phosphatase LPIN2, osteomodulin, protein phosphatase 1J, and RRP12-like protein.

Results

The proteomic survey of serum from both healthy and disease patients includes 1220 proteins and was enriched for proteins involved in the response to elevated platelet Ca⁺², wound healing, and extracellular matrix organization. Proteolytic peptides from three of the ten SRM-MS proteins, osteocalcin preprotein, osteomodulin precursor, and collagen alpha-1(v) chain isoform 2 preprotein from serum, are potential clinical biomarkers for HO.

Conclusions

This study is the first reported SRM-MS analysis of serum from individuals with and without heterotopic ossification, and differences in the serum proteomic profile between healthy and diseased subjects were identified. Furthermore, our results indicate that normal wound healing signals can impact the ability to identify biomarkers, and a multi-protein panel assay, including osteocalcin preproprotein, osteomodulin precursor, and collagen alpha-1(v) chain isoform 2 preprotein, may provide a solution for HO detection and monitoring.

Electronic supplementary material

The online version of this article (doi:10.1186/s13018-017-0567-2) contains supplementary material, which is available to authorized users.

A selected reaction monitoring mass spectrometric assessment of biomarker candidates diagnosing large-cell neuroendocrine lung carcinoma by the scaling method using endogenous references

Selected reaction monitoring mass spectrometry (SRM-MS) -based semi-quantitation was performed to assess the validity of 46 selected candidate proteins for specifically diagnosing large-cell neuroendocrine lung carcinoma (LCNEC) and differentiating it from other lung cancer subtypes. The scaling method was applied in this study using specific SRM peak areas (AUCs) derived from the endogenous reference protein that normalizes all SRM AUCs obtained for the candidate proteins. In a screening verification study, we found that seven out of the 46 candidate proteins were statistically significant for the LCNEC phenotype, including 4F2hc cell surface antigen heavy chain (4F2hc/CD98) (p-ANOVA ≤ 0.0012), retinal dehydrogenase 1 (p-ANOVA ≤ 0.0029), apolipoprotein A-I (p-ANOVA ≤ 0.0004), β-enolase (p-ANOVA ≤ 0.0043), creatine kinase B-type (p-ANOVA ≤ 0.0070), and galectin-3-binding protein (p-ANOVA = 0.0080), and phosphatidylethanolamine-binding protein 1 (p-ANOVA ≤ 0.0012). In addition, we also identified candidate proteins specific to the small-cell lung carcinoma (SCLC) subtype. These candidates include brain acid soluble protein 1 (p-ANOVA < 0.0001) and γ-enolase (p-ANOVA ≤ 0.0013). This new relative quantitation-based approach utilizing the scaling method can be applied to assess hundreds of protein candidates obtained from discovery proteomic studies as a first step of the verification phase in biomarker development processes.

Targeted Proteomics and Absolute Protein Quantification for the Construction of a Stoichiometric Host-Pathogen Surface Density Model

Sepsis is a systemic immune response responsible for considerable morbidity and mortality. Molecular modeling of host-pathogen interactions in the disease state represents a promising strategy to define molecular events of importance for the transition from superficial to invasive infectious diseases. Here we used the Gram-positive bacterium Streptococcus pyogenes as a model system to establish a mass spectrometry based workflow for the construction of a stoichiometric surface density model between the S. pyogenes surface, the surface virulence factor M-protein, and adhered human blood plasma proteins. The workflow relies on stable isotope labeled reference peptides and selected reaction monitoring mass spectrometry analysis of a wild-type strain and an M-protein deficient mutant strain, to generate absolutely quantified protein stoichiometry ratios between S. pyogenes and interacting plasma proteins. The stoichiometry ratios in combination with a novel targeted mass spectrometry method to measure cell numbers enabled the construction of a stoichiometric surface density model using protein structures available from the protein data bank. The model outlines the topology and density of the host-pathogen protein interaction network on the S. pyogenes bacterial surface, revealing a dense and highly organized protein interaction network. Removal of the M-protein from S. pyogenes introduces a drastic change in the network topology, validated by electron microscopy. We propose that the stoichiometric surface density model of S. pyogenes in human blood plasma represents a scalable framework that can continuously be refined with the emergence of new results. Future integration of new results will improve the understanding of protein-protein interactions and their importance for bacterial virulence. Furthermore, we anticipate that the general properties of the developed workflow will facilitate the production of stoichiometric surface density models for other types of host-pathogen interactions.

Glycated lysine-141 in haptoglobin improves the diagnostic accuracy for type 2 diabetes mellitus in combination with glycated hemoglobin HbA1c and fasting plasma glucose

BACKGROUND

Recent epidemiological studies indicate that only 30-50% of undiagnosed type 2 diabetes mellitus (T2DM) patients are identified using glycated hemoglobin (HbA1c) and elevated fasting plasma glucose (FPG) levels. Thus, novel biomarkers for early diagnosis and prognosis are urgently needed for providing early and personalized treatment.

METHODS

Here, we studied the glycation degrees of 27 glycation sites representing nine plasma proteins in 48 newly diagnosed male T2DM patients and 48 non-diabetic men matched for age (range 35-65 years). Samples were digested with trypsin and enriched for glycated peptides using boronic acid affinity chromatography. Quantification relied on mass spectrometry (multiple reaction monitoring) using isotope-labelled peptides as internal standard.

RESULTS

The combination of glycated lysine-141 of haptoglobin (HP K141) and HbA1c provided a sensitivity of 94%, a specificity of 98%, and an accuracy of 96% to identify T2DM. A set of 15 features considering three glycation sites in human serum albumin, HP K141, and 11 routine laboratory measures of T2DM, metabolic syndrome, obesity, inflammation, and insulin resistance provided a sensitivity of 98%, a specificity of 100%, and an accuracy of 99% for newly diagnosed T2DM patients.

CONCLUSIONS

Our studies demonstrated the great potential of glycation sites in plasma proteins providing an additional diagnostic tool for T2DM and elucidating that the combination of these sites with HbA1c and FPG could improve the diagnosis of T2DM.

Serum peptides as putative modulators of inflammation in psoriasis

BACKGROUND

Psoriasis is a refractory inflammatory disease, however, its pathophysiology is still not fully understood.

OBJECTIVE

We tried to identify novel serum peptides associated with the pathophysiology of psoriasis.

METHODS

Serum peptides from 24 patients with psoriasis vulgaris (PV), 10 patients with psoriatic arthritis (PsA), 14 patients with atopic dermatitis (AD), and 23 healthy control (HC) subjects were analyzed by mass spectrometry. The effects of some peptides on the secretion of humoral factors from dermal cells were investigated by cytokine arrays and ELISAs.

RESULTS

A total of 93 peptides were detected. 24, 20, 23, and 2 peptides showed at least 1.2-fold difference in ion intensity between the psoriasis (PV+PsA) and HC groups, between the PV+PsA and AD groups, between the PV and PsA groups, and between patients with severe-to-moderate PV (n=6) and those with mild PV (n=18), respectively (p<0.05). 13 out of 27 peptides that showed at least 1.5-fold ion intensity difference in the abovementioned 4 comparisons were identified. The parent proteins of the identified peptides included a coagulation factor, proteins involved in the maintenance of skin, and a protein relating to cytoskeleton. We focused on 2 peptides that were increased in the PV+PsA group: a fibrinogen α chain-derived peptide (1462m/z), the unmodified form of which was fibrinopeptide A-des-alanine (FPAdA), and a filaggrin (FLG)-derived peptide (1977m/z), a modified form of FLG_2099-2118 (Q₂₀₉₉pE, Q₂₁₁₅E; FLG-pEE). FPAdA stimulation increased the secretion of GROα from dermal microvascular endothelial cells (dMVECs) and decreased the secretion of lipocalin-2 from keratinocytes in comparison to FPAdA-resequenced peptide stimulation (GROα, 280.9±7.3pg/mL vs. 229.6±5.0pg/mL, p<0.001; lipocalin-2, 273±13pg/mL vs. 350±10pg/mL, p<0.01). Interestingly, FLG-pEE stimulation decreased the secretion of GROα, IL-8, and MCP-1 from dMVECs in comparison to FLG-derived control peptide stimulation (GROα, 844.3±47.5pg/mL vs. 1038.5±96.9pg/mL, p<0.05; IL-8, 2240.1±172.6pg/mL vs. 3221.8±523.7pg/mL, p<0.05; MCP-1, 4057.8±157.2pg/mL vs. 4619.1±213.4pg/mL, p<0.05).

CONCLUSIONS

The results suggested that some serum peptides are involved in the pathophysiology of psoriasis, regulating the secretion of inflammatory chemokines and an antimicrobial protein. The modulation of serum peptides may be a potential therapeutic strategy for psoriasis.

Targeted label-free quantification of interleukin-8 in PMA-activated U937 cell secretome by nanoLC-ESI-MS/MS-sSRM

Monocytes are a part of the innate immune system. Their differentiation into macrophages changes their cellular proteome and secretome. Particularly secretome components such as cytokines are crucial for immune response and inflammation in many diseases. Differentiation of human lymphoma cell line U937 can be triggered by phorbol 12-myristate 13-acetate (PMA). Screening of the cytokine release in U937 upon PMA stimulation by cytometric bead array almost exclusively showed interleukin-8 (IL-8). Next, a label-free nanoLC-ESI-MS/MS-sSRM method for quantification of IL-8 in the cell secretome was established and applied to monitor the time kinetics of PMA treatment in different concentrations. Targeted secretome analysis was achieved by scheduled SRM-MS using one proteotypic peptide as precursor ion and four mass transitions. Label-free quantification was performed by external calibration using IL-8 standard. Validation results indicated that the method was suited for the quantification of IL-8 in the secretome. The maximal IL-8 release of 62.4 ng/mL was observed after incubating cells treated by 50 ng/mL PMA for 48 h. The method can now be used for quantification of IL-8 release from different cells under various conditions. Furthermore, it can be easily expanded to other secreted proteins detected by untargeted screening methods.