Processing of serum proteins underlies the mass spectral fingerprinting of myocardial infarction

Comparison of the Human Plasma Peptides from the Fit of Fragmentation Spectra versus Accurate Monoisotopic Precursor Mass

In nature, ionized peptides with heavy isotopes and hydrogen rearrangements show a broad mass distribution with signals at discrete delta mass values from -3 to +5 Da by mass spectrometry (MS). For many peptides, the intensity of the +1 or +2 Da isotope exceeds the signal from the monoisotopic mass. Therefore, there is a need for a method that improves peptide identification from heavy isotopes or hydrogen rearrangements based on the fit of tandem mass spectra. Peptides may be identified using an accurate monoisotopic precursor mass with ≤0.1 Da. However, many peptides with heavy isotopes and H-loss can be identified and enumerated based on the fit of their MS/MS spectra alone in the absence of an accurate precursor monoisotopic mass (i.e., ± 3 Da) using the X!TANDEM MS/MS fitting algorithm. In this study, human plasma samples were analyzed with a highly resolving axially harmonic orbital ion trap (OIT) and a sensitive linear quadrupole ion trap (LIT). The MS/MS fragmentation spectra from the OIT can be fit to peptides from the monoisotopic (±0.1 Da) as well as all other precursor masses with a wide mass tolerance (±3 Da). The resulting delta mass distribution can then be plotted and compared to the predicted distribution of heavy isotopes and hydrogen rearrangements to provide a direct biophysical prediction and test the validity of the fit determined by accepting the best-fit MS/MS spectra. The OIT instrument, which has greater resolution, was sampled at 30 nL per minute, while the more sensitive LIT was sampled at 200 nL per minute. The MS/MS spectra generated by each instrument were fit to peptides within a wide window (±3 Da) using the rigorous X!TANDEM algorithm. The OIT and LIT results were compared in an SQL Server database and corrected against analytical and statistical controls. The delta mass distribution of the peptides with hydrogen rearrangements and heavy isotopes was determined from the fit MS/MS spectra using the R statistical program. The OIT sampled MS and MS/MS spectra from the high-intensity precursor ions by focusing on E7 to E9 detector counts. In contrast, the LIT sampled a range of precursor ion intensities focused from E4 to E7 and thus reached lower ion intensity values. As expected, the precursor mass [M + H]+ obtained by the OIT exhibited sharp delta mass peaks at -3, -2, -1, 0, +1, +2, +3, +4, and +5 Da due to naturally occurring heavy isotopes and hydrogen rearrangements. The collection of peptides and proteins identified by OIT and LIT was in qualitative and quantitative agreement with one another, with 99.9% overlap on 2726 protein gene symbols from human plasma and a highly significant relationship by regression analysis. The protein p-values, false discovery rate q-values, and comparisons to the noise MS/MS analytical control and random MS/MS statistical control confirmed the high-confidence MS/MS identifications from both instruments. MS/MS fragmentation spectra from the OIT were fit to peptides. The resulting precursor ion delta mass distribution showed a precise match to the predicted isotope distributions and hydrogen rearrangements of natural peptides. Thus, analysis of delta mass plots provided powerful biophysical evidence for the accuracy of plasma peptide identification from the fit of the MS/MS spectra alone. The high level of agreement on proteins and peptides and the proportional enumeration between proteins identified by the OIT and those identified independently using a LIT confirmed that plasma peptides and proteins may be identified and quantified from MS/MS spectra alone without the need for an accurate measure of the precursor mass. The greater sensitivity and low cost of searching MS/MS spectra in the absence of an accurate mass mean that it is possible to identify and quantify more proteins for the discovery of proteins in clinical populations.

Micro scale chromatography of human plasma proteins for nano LC-ESI-MS/MS

Organic precipitation of proteins with acetonitrile demonstrated complete protein recovery and improved chromatography of human plasma proteins. The separation of 25 μL of human plasma into 22 fractions on a QA SAX resin facilitated more effective protein discovery despite the limited sample size. Micro chromatography of plasma proteins over quaternary amine (QA) strong anion exchange (SAX) resins performed best, followed by diethylaminoethyl (DEAE), heparin (HEP), carboxymethyl cellulose (CMC), and propyl sulfate (PS) resins. Two independent statistical methods, Monte Carlo comparison with random MS/MS spectra and the rigorous X!TANDEM goodness of fit algorithm protein p-values corrected to false discovery rate q-values (q ≤ 0.01) agreed on at least 12,000 plasma proteins, each represented by at least three fully tryptic corrected peptide observations. There was qualitative agreement on 9393 protein/gene symbols between the linear quadrupole versus orbital ion trap but also quantitative agreement with a highly significant linear regression relationship between log observation frequency (F value 4,173, p-value 2.2e-16). The use of a QA resin showed nearly perfect replication of all the proteins that were also found using DEAE-, HEP-, CMC-, and PS-based chromatographic methods combined and together estimated the size of the size of the plasma proteome as ≥12,000 gene symbols.

Decoding the Challenges: navigating Intact Peptide Mass Spectrometry-Based Analysis for Biological Applications

Quantitative analysis of peptides in biological fluids offers a high diagnostic and prognostic tool to reflect the pathophysiological condition of the patient. Recently, methods based on liquid chromatography coupled with mass spectrometry (LC-MS) for the quantitative determination of intact peptides have been replacing traditionally used ligand-binding assays, which suffer from cross-reactivity issues. The use of "top-down" analysis of peptides is rapidly increasing since it does not undergo incomplete or non-reproducible digestion like "bottom-up" approaches. However, the low abundance of peptides and their peculiar characteristics, as well as the complexity of biological fluids, make their quantification challenging. Herein, the analytical pitfalls that may be encountered during the development of an LC-MS method for the analysis of intact peptides in biological fluids are discussed. Challenges in the pre-analytical phase, stability after sampling and sample processing, significantly impact the accuracy of peptide quantification. Emerging techniques, such as microextractions, are becoming crucial for improved sample cleanup and enrichment of target analytes. A comparison between the roles of high-resolution and low-resolution mass spectrometry in the quantification of intact peptides, as well as the introduction of supercharging reagents to enhance ionization, will be discussed.

Trypsin Digestion Conditions of Human Plasma for Observation of Peptides and Proteins from Tandem Mass Spectrometry

Previous meta-analysis indicated that plasma or serum proteome groups using various experimental conditions detected different peptides from the same plasma proteins, which is strong evidence for the veracity of blood fluid LC-ESI-MS/MS but also evidences that the trypsin digestion step is a key source of variation in plasma proteomics. Agreement between different digestion conditions and MS/MS algorithms may serve as an independent confirmation of the validity of the LC-ESI-MS/MS analysis of plasma peptides. Plasma contains a high percentage of albumin held together by multiple disulfide bonds; hence, reduction and/or alkylation may greatly enhance the digestion efficiency of albumin. Plasma proteins were precipitated in 90% acetonitrile, collected over quaternary amine resin, and eluted in NaCl prior to digestion treatments. To determine the effect of trypsin digestion methods, the plasma proteins were digested in 600 mM urea and 5% acetonitrile with trypsin alone, or reduced with 2 mM DTT followed by trypsin, or DTT followed by 15 mM iodoacetamide and then trypsin. The resulting peptides were analyzed by LC-ESI-MS/MS with a linear quadrupole ion trap (LIT). The MS/MS spectra were directly fit to peptides by the X!TANDEM and SEQUEST algorithms. Blank noise injections served as the analytical control, and 30 million random MS/MS served as the statistical control. Digesting human plasma with DTT reduction, or reduction and alkylation, resulted in a dramatic increase in the number and observation frequency of albumin peptides. In contrast, digestion with trypsin alone suppressed the observation of albumin, and instead, many low abundance plasma and cellular proteins showed higher observation frequency. Digestion with trypsin alone increased the observation frequency of APOC1, ACAN, ATRN, CPB2, GP2, GPX3, HBA1, PAPD5, PKD1, and many cellular proteins. After correction against noise and random controls, SEQUEST showed good agreement with the true positive plasma proteins identified by X!TANDEM and resulted in an R-squared of 0.5238 with an F-statistic of 10,930 on 9,935 protein gene symbols with a p-value < 2.2e-16. Digestion of plasma with trypsin alone avoids the complete digestion of albumin and permits the enhanced detection of some other cellular proteins from plasma. Different digestion approaches were complimentary and together resulted in a more comprehensive plasma proteome. The protein FDR q-values, the modest effect of background and Monte Carlo correction, and the significant STRING analysis were all consistent with the high fidelity of the rigorous X!TANDEM algorithm. In contrast, SEQUEST required significant correction against noise and statistical controls and selection of high cross correlation (XCorr) scores to show good agreement with X!TANDEM. There was qualitative and quantitative agreement between plasma proteins digested without alkylation from the orbital ion trap (OIT) versus the LIT instrument that showed highly significant regression against the X!TANDEM OIT monoisotopic results, those from heavy isotopes and other masses from X!TANDEM, and with those from MaxQuant. There was significant qualitative and quantitative agreement between the complementary digestion conditions consistent with the good fidelity of plasma analysis by LC-ESI-MS/MS with a sensitive linear ion trap.

Extraction of naturally occurring peptides versus the tryptic digestion of proteins from fetal versus adult bovine serum for LC-ESI-MS/MS

The naturally occurring peptides and digested proteins of fetal versus adult bovine serum were compared by LC-ESI-MS/MS after correction against noise from blank injections and random MS/MS spectra as statistical controls. Serum peptides were extracted by differential precipitation with mixtures of acetonitrile and water. Serum proteins were separated by partition chromatography over quaternary amine resin followed by tryptic digestion. The rigorous X!TANDEM goodness of fit algorithm that has a low error rate as demonstrated by low FDR q-values (q ≤ 0.01) showed qualitative and quantitative agreement with the SEQUEST cross correlation algorithm on 12,052 protein gene symbols. Tryptic digestion provided a quantitative identification of the serum proteins where observation frequency reflected known high abundance. In contrast, the naturally occurring peptides reflected the cleavage of common serum proteins such as C4A, C3, FGB, HPX, A2M but also proteins in lower concentration such as F13A1, IK, collagens and protocadherins. Proteins associated with cellular growth and development such as actins (ACT), ribosomal proteins like Ribosomal protein S6 (RPS6), synthetic enzymes and extracellular matrix factors were enriched in fetal calf serum. In contrast to the large literature from cord blood, IgG light chains were absent from fetal serum as observed by LC-ESI-MS/MS and confirmed by ELISA.

Biospecimen Qualification in a Clinical Biobank of Urological Diseases

Development of novel biomarkers for diagnosis of disease and assessment of treatment efficacy utilizes a wide range of biospecimens for discovery research. The fitness of biospecimens for the purpose of biomarker development depends on the clinical characteristics of the donor and on a number of critical and potentially uncontrolled pre-analytical variables. Pre-analytical factors influence the reliability of the biomarkers to be analyzed and can seriously impact analytic outcomes. Sample quality stratification assays and tools can be utilized by biorepositories to minimize bias resulting from samples' inconsistent quality. In this study, we evaluated the quality of biobanked specimens by comparing analytical outcomes at 1, 5, and 10 years after collection. Our results demonstrate that currently available assays and tools can be used by biobank laboratories to support objective biospecimen qualification. We have established a workflow to monitor the quality of different types of biospecimens and, in this study, present the results of a qualification exercise applied to fluid samples and their derivatives in the context of urological diseases.

LEDGF is a new growth factor in fetal serum

Fetal serum supports the immortal growth of mammalian cell lines in culture while adult serum leads to the terminal differentiation and death of cells in culture. Many of the proteins in fetal serum that support the indefinite division and growth of cancerous cell lines remain obscure. The peptides and proteins of fetal versus adult serum were analyzed by liquid chromatography, nano electrospray ionization and tandem mass spectrometry (LC-ESI-MS/MS). Three batches of fetal serum contained the Alpha Fetoprotein marker while adult serum batches did not. Insulin (INS), and insulin-like growth factor (ILGF), fibroblast growth factor (FGF), epidermal growth factor (EGF) and platelet derived growth factor (PDGF) were increased in fetal serum. New fetal growth factors including MEGF, HDGFRP and PSIP1 and soluble growth receptors such as TNFR, EGFR, NTRK2 and THRA were discovered. Addition of insulin or the homeotic transcription factor PSIP1, also referred to as Lens Epithelium Derived Growth Factor (LEDGF), partially restored the rounded phenotype of rapidly dividing cells but was not as effective as fetal serum. Thus, a new growth factor in fetal serum, LEDGF/PSIP1, was directly observed by tandem mass spectrometry and confirmed by add back experiments to cell culture media alongside insulin.

Omics for the Improvement of Abiotic, Biotic, and Agronomic Traits in Major Cereal Crops: Applications, Challenges, and Prospects

Omics technologies, namely genomics, transcriptomics, proteomics, metabolomics, and phenomics, are becoming an integral part of virtually every commercial cereal crop breeding program, as they provide substantial dividends per unit time in both pre-breeding and breeding phases. Continuous advances in omics assure time efficiency and cost benefits to improve cereal crops. This review provides a comprehensive overview of the established omics methods in five major cereals, namely rice, sorghum, maize, barley, and bread wheat. We cover the evolution of technologies in each omics section independently and concentrate on their use to improve economically important agronomic as well as biotic and abiotic stress-related traits. Advancements in the (1) identification, mapping, and sequencing of molecular/structural variants; (2) high-density transcriptomics data to study gene expression patterns; (3) global and targeted proteome profiling to study protein structure and interaction; (4) metabolomic profiling to quantify organ-level, small-density metabolites, and their composition; and (5) high-resolution, high-throughput, image-based phenomics approaches are surveyed in this review.

The plasma peptides of Alzheimer's disease

Background

A practical strategy to discover proteins specific to Alzheimer’s dementia (AD) may be to compare the plasma peptides and proteins from patients with dementia to normal controls and patients with neurological conditions like multiple sclerosis or other diseases. The aim was a proof of principle for a method to discover proteins and/or peptides of plasma that show greater observation frequency and/or precursor intensity in AD. The endogenous tryptic peptides of Alzheimer’s were compared to normals, multiple sclerosis, ovarian cancer, breast cancer, female normal, sepsis, ICU Control, heart attack, along with their institution-matched controls, and normal samples collected directly onto ice.

Methods

Endogenous tryptic peptides were extracted from blinded, individual AD and control EDTA plasma samples in a step gradient of acetonitrile for random and independent sampling by LC–ESI–MS/MS with a set of robust and sensitive linear quadrupole ion traps. The MS/MS spectra were fit to fully tryptic peptides within proteins identified using the X!TANDEM algorithm. Observation frequency of the identified proteins was counted using SEQUEST algorithm. The proteins with apparently increased observation frequency in AD versus AD Control were revealed graphically and subsequently tested by Chi Square analysis. The proteins specific to AD plasma by Chi Square with FDR correction were analyzed by the STRING algorithm. The average protein or peptide log₁₀ precursor intensity was compared across disease and control treatments by ANOVA in the R statistical system.

Results

Peptides and/or phosphopeptides of common plasma proteins such as complement C2, C7, and C1QBP among others showed increased observation frequency by Chi Square and/or precursor intensity in AD. Cellular gene symbols with large Chi Square values (χ2 ≥ 25, p ≤ 0.001) from tryptic peptides included KIF12, DISC1, OR8B12, ZC3H12A, TNF, TBC1D8B, GALNT3, EME2, CD1B, BAG1, CPSF2, MMP15, DNAJC2, PHACTR4, OR8B3, GCK, EXOSC7, HMGA1 and NT5C3A among others. Similarly, increased frequency of tryptic phosphopeptides were observed from MOK, SMIM19, NXNL1, SLC24A2, Nbla10317, AHRR, C10orf90, MAEA, SRSF8, TBATA, TNIK, UBE2G1, PDE4C, PCGF2, KIR3DP1, TJP2, CPNE8, and NGF amongst others. STRING analysis showed an increase in cytoplasmic proteins and proteins associated with alternate splicing, exocytosis of luminal proteins, and proteins involved in the regulation of the cell cycle, mitochondrial functions or metabolism and apoptosis. Increases in mean precursor intensity of peptides from common plasma proteins such as DISC1, EXOSC5, UBE2G1, SMIM19, NXNL1, PANO, EIF4G1, KIR3DP1, MED25, MGRN1, OR8B3, MGC24039, POLR1A, SYTL4, RNF111, IREB2, ANKMY2, SGKL, SLC25A5, CHMP3 among others were associated with AD. Tryptic peptides from the highly conserved C-terminus of DISC1 within the sequence MPGGGPQGAPAAAGGGGVSHRAGSRDCLPPAACFR and ARQCGLDSR showed a higher frequency and highest intensity in AD compared to all other disease and controls.

Conclusion

Proteins apparently expressed in the brain that were directly related to Alzheimer’s including Nerve Growth Factor (NFG), Sphingomyelin Phosphodiesterase, Disrupted in Schizophrenia 1 (DISC1), the cell death regulator retinitis pigmentosa (NXNl1) that governs the loss of nerve cells in the retina and the cell death regulator ZC3H12A showed much higher observation frequency in AD plasma vs the matched control. There was a striking agreement between the proteins known to be mutated or dis-regulated in the brains of AD patients with the proteins observed in the plasma of AD patients from endogenous peptides including NBN, BAG1, NOX1, PDCD5, SGK3, UBE2G1, SMPD3 neuronal proteins associated with synapse function such as KSYTL4, VTI1B and brain specific proteins such as TBATA.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12014-021-09320-2.

The plasma peptides of sepsis

Background

A practical strategy to discover sepsis specific proteins may be to compare the plasma peptides and proteins from patients in the intensive care unit with and without sepsis. The aim was to discover proteins and/or peptides that show greater observation frequency and/or precursor intensity in sepsis. The endogenous tryptic peptides of ICU-Sepsis were compared to ICU Control, ovarian cancer, breast cancer, female normal, sepsis, heart attack, Alzheimer’s and multiple sclerosis along with their institution-matched controls, female normals and normal samples collected directly onto ice.

Methods

Endogenous tryptic peptides were extracted from individual sepsis and control EDTA plasma samples in a step gradient of acetonitrile for random and independent sampling by LC–ESI–MS/MS with a set of robust and sensitive linear quadrupole ion traps. The MS/MS spectra were fit to fully tryptic peptides within proteins using the X!TANDEM algorithm. The protein observation frequency was counted using the SEQUEST algorithm after selecting the single best charge state and peptide sequence for each MS/MS spectra. The protein observation frequency of ICU-sepsis versus ICU Control was subsequently tested by Chi square analysis. The average protein or peptide log₁₀ precursor intensity was compared across disease and control treatments by ANOVA in the R statistical system.

Results

Peptides and/or phosphopeptides of common plasma proteins such as ITIH3, SAA2, SAA1, and FN1 showed increased observation frequency by Chi square (χ² > 9, p < 0.003) and/or precursor intensity in sepsis. Cellular gene symbols with large Chi square values from tryptic peptides included POTEB, CTNNA1, U2SURP, KIF24, NLGN2, KSR1, GTF2H1, KIT, RPS6KL1, VAV2, HSPA7, SMC2, TCEB3B, ZNF300, SUPV3L1, ADAMTS20, LAMB4, MCCC1, SUPT6H, SCN9A, SBNO1, EPHA1, ABLIM2, cB5E3.2, EPHA10, GRIN2B, HIVEP2, CCL16, TKT, LRP2 and TMF1 amongst others showed increased observation frequency. Similarly, increased frequency of tryptic phosphopeptides were observed from POM121C, SCN8A, TMED8, NSUN7, SLX4, MADD, DNLZ, PDE3B, UTY, DEPDC7, MTX1, MYO1E, RXRB, SYDE1, FN1, PUS7L, FYCO1, USP26, ACAP2, AHI1, KSR2, LMAN1, ZNF280D and SLC8A2 amongst others. Increases in mean precursor intensity in peptides from common plasma proteins such as ITIH3, SAA2, SAA1, and FN1 as well as cellular proteins such as COL24A1, POTEB, KANK1, SDCBP2, DNAH11, ADAMTS7, MLLT1, TTC21A, TSHR, SLX4, MTCH1, and PUS7L among others were associated with sepsis. The processing of SAA1 included the cleavage of the terminal peptide D/PNHFRPAGLPEKY from the most hydrophilic point of SAA1 on the COOH side of the cystatin C binding that was most apparent in ICU-Sepsis patients compared to all other diseases and controls. Additional cleavage of SAA1 on the NH2 terminus side of the cystatin binding site were observed in ICU-Sepsis. Thus there was disease associated variation in the processing of SAA1 in ICU-Sepsis versus ICU controls or other diseases and controls.

Conclusion

Specific proteins and peptides that vary between diseases might be discovered by the random and independent sampling of multiple disease and control plasma from different hospital and clinics by LC–ESI–MS/MS for storage in a relational SQL Server database and analysis with the R statistical system that will be a powerful tool for clinical research. The processing of SAA1 may play an unappreciated role in the inflammatory response to Sepsis.

Re-evaluation of the 18 non-human protein standards used to create the empirical statistical model for decoy library searching

The Empirical Statistical Model (ESM) for decoy library searching fused the expected amino acid sequence of 18 non-human protein standards to a human decoy library. The ESM assumed a priori the standards were pure such that only the 18 nominal proteins were true positive, all other proteins were false positive, there was no overlap in the peptides of non-human proteins versus human proteins, and that the score distribution of individual peptides would resolve true positive from false positive results or noise. The results of random and independent sampling by LC-ESI-MS/MS indicated that the fundamental assumptions of the ESM were not in good agreement with the actual purity of the commercial test standards and so the method showed a 99.7% false negative rate. The ESM for decoy library searching apparently showed poor agreement with SDS-PAGE using silver staining, goodness of fit of MS/MS spectra by X!TANDEM, FDR correction by Benjamini and Hochberg, or comparison to the observation frequency of null random MS/MS spectra, that all confirmed the standards contain hundreds of proteins with a low FDR of primary structural identification. The protein observation frequency increased with abundance and the log₁₀ precursor intensity distributions were Gaussian and nearly ideal for relative quantification.

The plasma peptides of breast versus ovarian cancer

Background

There is a need to demonstrate a proof of principle that proteomics has the capacity to analyze plasma from breast cancer versus other diseases and controls in a multisite clinical trial design. The peptides or proteins that show a high observation frequency, and/or precursor intensity, specific to breast cancer plasma might be discovered by comparison to other diseases and matched controls. The endogenous tryptic peptides of breast cancer plasma were compared to ovarian cancer, female normal, sepsis, heart attack, Alzheimer's and multiple sclerosis along with the institution-matched normal and control samples collected directly onto ice.

Methods

Endogenous tryptic peptides were extracted from individual breast cancer and control EDTA plasma samples in a step gradient of acetonitrile, and collected over preparative C18 for LC-ESI-MS/MS with a set of LTQ XL linear quadrupole ion traps working together in parallel to randomly and independently sample clinical populations. The MS/MS spectra were fit to fully tryptic peptides or phosphopeptides within proteins using the X!TANDEM algorithm. The protein observation frequency was counted using the SEQUEST algorithm after selecting the single best charge state and peptide sequence for each MS/MS spectra. The observation frequency was subsequently tested by Chi Square analysis. The log₁₀ precursor intensity was compared by ANOVA in the R statistical system.

Results

Peptides and/or phosphopeptides of common plasma proteins such as APOE, C4A, C4B, C3, APOA1, APOC2, APOC4, ITIH3 and ITIH4 showed increased observation frequency and/or precursor intensity in breast cancer. Many cellular proteins also showed large changes in frequency by Chi Square (χ² > 100, p < 0.0001) in the breast cancer samples such as CPEB1, LTBP4, HIF-1A, IGHE, RAB44, NEFM, C19orf82, SLC35B1, 1D12A, C8orf34, HIF1A, OCLN, EYA1, HLA-DRB1, LARS, PTPDC1, WWC1, ZNF562, PTMA, MGAT1, NDUFA1, NOGOC, OR1E1, OR1E2, CFI, HSA12, GCSH, ELTD1, TBX15, NR2C2, FLJ00045, PDLIM1, GALNT9, ASH2L, PPFIBP1, LRRC4B, SLCO3A1, BHMT2, CS, FAM188B2, LGALS7, SAT2, SFRS8, SLC22A12, WNT9B, SLC2A4, ZNF101, WT1, CCDC47, ERLIN1, SPFH1, EID2, THOC1, DDX47, MREG, PTPRE, EMILIN1, DKFZp779G1236 and MAP3K8 among others. The protein gene symbols with large Chi Square values were significantly enriched in proteins that showed a complex set of previously established functional and structural relationships by STRING analysis. An increase in mean precursor intensity of peptides was observed for QSER1 as well as SLC35B1, IQCJ-SCHIP1, MREG, BHMT2, LGALS7, THOC1, ANXA4, DHDDS, SAT2, PTMA and FYCO1 among others. In contrast, the QSER1 peptide QPKVKAEPPPK was apparently specific to ovarian cancer.

Conclusion

There was striking agreement between the breast cancer plasma peptides and proteins discovered by LC-ESI-MS/MS with previous biomarkers from tumors, cells lines or body fluids by genetic or biochemical methods. The results indicate that variation in plasma peptides from breast cancer versus ovarian cancer may be directly discovered by LC-ESI-MS/MS that will be a powerful tool for clinical research. It may be possible to use a battery of sensitive and robust linear quadrupole ion traps for random and independent sampling of plasma from a multisite clinical trial.

From old uraemic toxins to new uraemic toxins: place of 'omics'

Uraemic toxins seem to play an important role in the genesis of cardiovascular and renal damage in chronic kidney disease patients. This short article is divided into two thematic sections. The first part focuses on a selection of ‘old’ toxins for which recent data (published between 2016 and 2018) have provided a better understanding of the associated harmful mechanisms and which, in our opinion, nephrologists should be more aware of. The second part highlights new perspectives for identifying and quantifying these compounds using ‘omics’ techniques.

Hypertensive disorders of pregnancy: Strategy to develop clinical peptide biomarkers for more accurate evaluation of the pathophysiological status of this syndrome

Hypertensive disorders of pregnancy (HDP) is the most common and widely known as serious complication of pregnancy. As this syndrome is a major leading cause of maternal, fetal, and neonatal morbidity/mortality worldwide, many studies have sought to identify candidate molecules as potential disease biomarkers (DBMs) for use in clinical examinations. Accumulating evidence over the past 2 decades that the many proteolytic peptides appear in human humoral fluids, including peripheral blood, in association with an individual's health condition. This review provides the potential utility of peptidomic analysis for monitoring for pathophysiological status in HDP, and presents an overview of current status of peptide quantification technology. Especially, the technical limitations of the methods used for DBM discovery in the blood are discussed.

Protein Corona over Mesoporous Silica Nanoparticles: Influence of the Pore Diameter on Competitive Adsorption and Application to Prostate Cancer Diagnostics

Diagnostic tests based on proteomics analysis can have significant advantages over more traditional biochemical tests. However, low molecular weight (MW) protein biomarkers are difficult to identify by standard mass spectrometric analysis, as they are usually present at low concentrations and are masked by more abundant resident proteins. We have previously shown that mesoporous silica nanoparticles are able to capture a predominantly low MW protein fraction from the serum, as compared to the protein corona (PC) adsorbed onto dense silica nanoparticles. In this study, we begin by further investigating this effect using liquid chromatography-mass spectrometry (LC-MS)/MS and thermogravimetric analysis (TGA) to compare the MW of the proteins in the coronas of mesoporous silica nanoparticles with the same particle size but different pore diameters. Next, we examine the process by which two proteins, one small and one large, adsorb onto these mesoporous silica nanoparticles to establish a theory of why the corona becomes enriched in low MW proteins. Finally, we use this information to develop a novel system for the diagnosis of prostate cancer. An elastic net statistical model was applied to LC-MS/MS protein coronas from the serum of 22 cancer patients, identifying proteins specific to each patient group. These studies help to explain why low MW proteins predominate in the coronas of mesoporous silica nanoparticles, and they illustrate the ability of this information to supplement more traditional diagnostic tests.

Protein Corona over Mesoporous Silica Nanoparticles: Influence of the Pore Diameter on Competitive Adsorption and Application to Prostate Cancer Diagnostics

Diagnostic tests based on proteomics analysis can have significant advantages over more traditional biochemical tests. However, low molecular weight (MW) protein biomarkers are difficult to identify by standard mass spectrometric analysis, as they are usually present at low concentrations and are masked by more abundant resident proteins. We have previously shown that mesoporous silica nanoparticles are able to capture a predominantly low MW protein fraction from the serum, as compared to the protein corona (PC) adsorbed onto dense silica nanoparticles. In this study, we begin by further investigating this effect using liquid chromatography-mass spectrometry (LC-MS)/MS and thermogravimetric analysis (TGA) to compare the MW of the proteins in the coronas of mesoporous silica nanoparticles with the same particle size but different pore diameters. Next, we examine the process by which two proteins, one small and one large, adsorb onto these mesoporous silica nanoparticles to establish a theory of why the corona becomes enriched in low MW proteins. Finally, we use this information to develop a novel system for the diagnosis of prostate cancer. An elastic net statistical model was applied to LC-MS/MS protein coronas from the serum of 22 cancer patients, identifying proteins specific to each patient group. These studies help to explain why low MW proteins predominate in the coronas of mesoporous silica nanoparticles, and they illustrate the ability of this information to supplement more traditional diagnostic tests.

Differential urinary proteomics analysis of myocardial infarction using iTRAQ quantification

Myocardial infarction (MI) is a disease characterized by high morbidity and mortality rates. MI biomarkers are frequently used in clinical diagnosis; however, their specificity and sensitivity remain unsatisfactory. Urinary proteome is an easy, efficient and noninvasive source to examine biomarkers associated with various diseases. The present study, to the best of the authors' knowledge, is the first to examine the urinary proteome using the isobaric tags for relative and absolute quantitation (iTRAQ) technology to identify potential diagnostic biomarkers of MI. The urinary proteome was analyzed within 12 h following the first symptoms of early‑onset MI and at day 7 following percutaneous coronary intervention via iTRAQ labeling and two‑dimensional liquid chromatography‑tandem mass spectrometry. Candidate biomarkers were validated by multiple reaction monitoring (MRM) analysis. A total of 233 urinary proteins were differentially expressed. Gene enrichment analysis identified that the urinary proteome in patients with MI was associated with atherosclerosis, abnormal coagulation and abnormal cell metabolism. In total, 12 differentially expressed urinary proteins were validated by MRM analysis, five of which were associated with MI for the first time in the present study. Binary logistic regression analysis suggested that the combination of five urinary proteins (antithrombin‑III, complement C3, α‑1‑acid glycoprotein 1, serotransferrin and cathepsin Z) may be used to diagnose MI with 94% sensitivity and 93% specificity. In addition, the protein expression levels of three proteins were significantly restored to normal levels following surgical treatment. The verified candidate biomarkers may be used for the diagnosis of MI, and for monitoring the disease status and the effects of treatments for MI. The present results may facilitate future clinical applications of the urinary proteome to diagnose MI.

The plasma peptides of ovarian cancer

Background

It may be possible to discover new diagnostic or therapeutic peptides or proteins from blood plasma by using liquid chromatography and tandem mass spectrometry to identify, quantify and compare the peptides cleaved ex vivo from different clinical populations. The endogenous tryptic peptides of ovarian cancer plasma were compared to breast cancer and female cancer normal controls, other diseases with their matched or normal controls, plus ice cold plasma to control for pre-analytical variation.

Methods

The endogenous tryptic peptides or tryptic phospho peptides (i.e. without exogenous digestion) were analyzed from 200 μl of EDTA plasma. The plasma peptides were extracted by a step gradient of organic/water with differential centrifugation, dried, and collected over C18 for analytical HPLC nano electrospray ionization and tandem mass spectrometry (LC–ESI–MS/MS) with a linear quadrupole ion trap. The endogenous peptides of ovarian cancer were compared to multiple disease and normal samples from different institutions alongside ice cold controls. Peptides were randomly and independently sampled by LC–ESI–MS/MS. Precursor ions from peptides > E4 counts were identified by the SEQUEST and X!TANDEM algorithms, filtered in SQL Server, before testing of frequency counts by Chi Square (χ²), for analysis with the STRING algorithm, and comparison of precursor intensity by ANOVA in the R statistical system with the Tukey-Kramer Honestly Significant Difference (HSD) test.

Results

Peptides and/or phosphopeptides of common plasma proteins such as HPR, HP, HPX, and SERPINA1 showed increased observation frequency and/or precursor intensity in ovarian cancer. Many cellular proteins showed large changes in frequency by Chi Square (χ² > 60, p < 0.0001) in the ovarian cancer samples such as ZNF91, ZNF254, F13A1, LOC102723511, ZNF253, QSER1, P4HA1, GPC6, LMNB2, PYGB, NBR1, CCNI2, LOC101930455, TRPM5, IGSF1, ITGB1, CHD6, SIRT1, NEFM, SKOR2, SUPT20HL1, PLCE1, CCDC148, CPSF3, MORN3, NMI, XTP11, LOC101927572, SMC5, SEMA6B, LOXL3, SEZ6L2, and DHCR24. The protein gene symbols with large Chi Square values were significantly enriched in proteins that showed a complex set of previously established functional and structural relationships by STRING analysis. Analysis of the frequently observed proteins by ANOVA confirmed increases in mean precursor intensity in ZFN91, TRPM5, SIRT1, CHD6, RIMS1, LOC101930455 (XP_005275896), CCDC37 and GIMAP4 between ovarian cancer versus normal female and other diseases or controls by the Tukey–Kramer HSD test.

Conclusion

Here we show that separation of endogenous peptides with a step gradient of organic/water and differential centrifugation followed by random and independent sampling by LC–ESI–MS/MS with analysis of peptide frequency and intensity by SQL Server and R revealed significant difference in the ex vivo cleavage of peptides between ovarian cancer and other clinical treatments. There was striking agreement between the proteins discovered from cancer plasma versus previous biomarkers discovered in tumors by genetic or biochemical methods. The results indicate that variation in plasma proteins from ovarian cancer may be directly discovered by LC–ESI–MS/MS that will be a powerful tool for clinical research.

Electronic supplementary material

The online version of this article (10.1186/s12014-018-9215-z) contains supplementary material, which is available to authorized users.

The plasma peptidome

Background

It may be possible to discover new diagnostic or therapeutic peptides or proteins from blood plasma using LC–ESI–MS/MS to identify, with a linear quadrupole ion trap to identify, quantify and compare the statistical distributions of peptides cleaved ex vivo from plasma samples from different clinical populations.

Methods

A systematic method for the organic fractionation of plasma peptides was applied to identify and quantify the endogenous tryptic peptides from human plasma from multiple institutions by C18 HPLC followed nano electrospray ionization and tandem mass spectrometry (LC–ESI–MS/MS) with a linear quadrupole ion trap. The endogenous tryptic peptides, or tryptic phospho peptides (i.e. without exogenous digestion), were extracted in a mixture of organic solvent and water, dried and collected by preparative C18. The tryptic peptides from 6 institutions with 12 different disease and normal EDTA plasma populations, alongside ice cold controls for pre-analytical variation, were characterized by mass spectrometry. Each patient plasma was precipitated in 90% acetonitrile and the endogenous tryptic peptides extracted by a stepwise gradient of increasing water and then formic acid resulting in 10 sub-fractions. The fractionated peptides were manually collected over preparative C18 and injected for 1508 LC–ESI–MS/MS experiments analyzed in SQL Server R.

Results

Peptides that were cleaved in human plasma by a tryptic activity ex vivo provided convenient and sensitive access to most human proteins in plasma that show differences in the frequency or intensity of proteins observed across populations that may have clinical significance. Combination of step wise organic extraction of 200 μL of plasma with nano electrospray resulted in the confident identification and quantification ~ 14,000 gene symbols by X!TANDEM that is the largest number of blood proteins identified to date and shows that you can monitor the ex vivo proteolysis of most human proteins, including interleukins, from blood. A total of 15,968,550 MS/MS spectra ≥ E4 intensity counts were correlated by the SEQUEST and X!TANDEM algorithms to a federated library of 157,478 protein sequences that were filtered for best charge state (2+ or 3+) and peptide sequence in SQL Server resulting in 1,916,672 distinct best-fit peptide correlations for analysis with the R statistical system. SEQUEST identified some 140,054 protein accessions, or some ~ 26,000 gene symbols, proteins or loci, with at least 5 independent correlations. The X!TANDEM algorithm made at least 5 best fit correlations to more than 14,000 protein gene symbols with p-values and FDR corrected q-values of ~ 0.001 or less. Log₁₀ peptide intensity values showed a Gaussian distribution from E8 to E4 arbitrary counts by quantile plot, and significant variation in average precursor intensity across the disease and controls treatments by ANOVA with means compared by the Tukey–Kramer test. STRING analysis of the top 2000 gene symbols showed a tight association of cellular proteins that were apparently present in the plasma as protein complexes with related cellular components, molecular functions and biological processes.

Conclusions

The random and independent sampling of pre-fractionated blood peptides by LC-ESI-MS/MS with SQL Server-R analysis revealed the largest plasma proteome to date and was a practical method to quantify and compare the frequency or log₁₀ intensity of individual proteins cleaved ex vivo across populations of plasma samples from multiple clinical locations to discover treatment-specific variation using classical statistics suitable for clinical science. It was possible to identify and quantify nearly all human proteins from EDTA plasma and compare the results of thousands of LC–ESI–MS/MS experiments from multiple clinical populations using standard database methods in SQL Server and classical statistical strategies in the R data analysis system.

Electronic supplementary material

The online version of this article (10.1186/s12014-018-9211-3) contains supplementary material, which is available to authorized users.

Combining Desorption Electrospray Ionization Mass Spectrometry Imaging and Machine Learning for Molecular Recognition of Myocardial Infarction

Lipid profile changes in heart muscle have been previously linked to cardiac ischemia and myocardial infarction, but the spatial distribution of lipids and metabolites in ischemic heart remains to be fully investigated. We performed desorption electrospray ionization mass spectrometry imaging of hearts from in vivo myocardial infarction mouse models. In these mice, myocardial ischemia was induced by blood supply restriction via a permanent ligation of left anterior descending coronary artery. We showed that applying the machine learning algorithm of gradient boosting tree ensemble to the ambient mass spectrometry imaging data allows us to distinguish segments of infarcted myocardium from normally perfused hearts on a pixel by pixel basis. The machine learning algorithm selected 62 molecular ion peaks important for classification of each 200 μm-diameter pixel of the cardiac tissue map as normally perfused or ischemic. This approach achieved very high average accuracy (97.4%), recall (95.8%), and precision (96.8%) at a spatial resolution of ∼200 μm. In addition, we determined the chemical identity of 27 species, mostly small metabolites and lipids, selected by the algorithm as the most significant for cardiac pathology classification. This molecular signature of myocardial infarction may provide new mechanistic insights into cardiac ischemia, assist with infarct size assessment, and point toward novel therapeutic interventions.

Re-evaluation of the rabbit myosin protein standard used to create the empirical statistical model for decoy library searching

A Rabbit myosin standard, like that used to create the empirical statistical model, was randomly and independently sampled by liquid chromatography micro electrospray ionization and tandem mass spectrometry (LC-ESI-MS/MS) with a linear quadrupole ion trap. The rabbit myosin protein standard appeared pure by SDS-PAGE and CBBR staining but showed many other proteins by silver staining. The LC-MS intensity from myosin and IgG samples were above the 99% safe limit of detection and quantification computed from 36 blank LC-ESI-MS/MS runs. The myosin contained ≤406 Gene Symbols, open reading frames or loci where 79 protein types showed ≥3 peptides from X!TANDEM. Myosins, actin, troponin, other proteins showed 95%-100% homology between the rabbit versus the human decoy library. The myosin protein complex from STRING was true positive compared to random or noise spectra MS/MS with a low type I error (p-value) and low FDR (q-value) computed in R. SDS-PAGE, Western blot, comparison to random and noise MS/MS spectra, X!TANDEM p-values, FDR corrected q-values, and STRING all agreed that the error rate of LC-ESI-MS/MS with a quadrupole ion trap is far below that assumed a priori by the design of the empirical statistical model for decoy library searching.

Applications of MALDI-TOF mass spectrometry in clinical proteomics

INTRODUCTION

The development of precision medicine requires advanced technologies to address the multifactorial disease stratification and to support personalized treatments. Among omics techniques, proteomics based on Mass Spectrometry (MS) is becoming increasingly relevant in clinical practice allowing a phenotypic characterization of the dynamic functional status of the organism. From this perspective, Matrix Assisted Laser Desorption Ionization Time of Flight (MALDI-TOF) MS is a suitable platform for providing a high-throughput support to clinics. Areas covered: This review aims to provide an updated overview of MALDI-TOF MS applications in clinical proteomics. The most relevant features of this analysis have been discussed, highlighting both pre-analytical and analytical factors that are crucial in proteomics studies. Particular emphasis is placed on biofluids proteomics for biomarkers discovery and on recent progresses in clinical microbiology, drug monitoring, and minimal residual disease (MRD). Expert commentary: Despite some analytical limitations, the latest technological advances together with the easiness of use, the low time and low cost consuming and the high throughput are making MALDI-TOF MS instruments very attractive for the clinical practice. These features offer a significant potential for the routine of the clinical laboratory and ultimately for personalized medicine.

Assessment by Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry of the Effects of Preanalytical Variables on Serum Peptidome Profiles Following Long-Term Sample Storage

PURPOSE

Human serum and plasma are often used as clinical specimens in proteomics analyses, and peptidome profiling of human serum is a promising tool for identifying novel disease-associated biomarkers. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) is widely used for peptidomic biomarker discovery. Careful sample collection and handling are required as either can have a profound impact on serum peptidome patterns, yet the effects of preanalytical variables on serum peptidome profiles have not been completely elucidated. The present study investigated the effects of preanalytical variables, including storage temperature, duration (up to 12 months), and thawing methods, on MALDI-TOF MS-based serum peptidome patterns.

EXPERIMENTAL DESIGN

Aliquots of serum samples were pretreated with weak cation exchanger magnetic beads using an automated ClinProtRobot system and then analyzed by MALDI-TOF MS.

RESULTS

A number of significant differences in peak intensities were observed depending on sample processing variables.

CONCLUSIONS AND CLINICAL RELEVANCE

These peaks can be used as sample quality markers to assess the effects of long-term storage on serum peptidome profiles using MALDI-TOF MS.

Direct Assessment of Plasma/Serum Sample Quality for Proteomics Biomarker Investigation

Blood proteome analysis for biomarker discovery represents one of the most challenging tasks to be achieved through clinical proteomics due to the sample complexity, such as the extreme heterogeneity of proteins in very dynamic concentrations, and to the observation of proper sampling and storage conditions. Quantitative and qualitative proteomics profiling of plasma and serum could be useful both for the early detection of diseases and for the evaluation of pathological status. Two main sources of variability can affect the precision and accuracy of the quantitative experiments designed for biomarker discovery and validation. These sources are divided into two categories, pre-analytical and analytical, and are often ignored; however, they can contribute to consistent errors and misunderstanding in biomarker research. In this chapter, we review critical pre-analytical and analytical variables that can influence quantitative proteomics. According to guidelines accepted by proteomics community, we propose some recommendations and strategies for a proper proteomics analysis addressed to biomarker studies.

Affinity enrichment for mass spectrometry: improving the yield of low abundance biomarkers

INTRODUCTION

Mass spectrometry (MS) is the premier tool for discovering novel disease-associated protein biomarkers. Unfortunately, when applied to complex body fluid samples, MS has poor sensitivity for the detection of low abundance biomarkers (≪10 ng/mL), derived directly from the diseased tissue cells or pathogens. Areas covered: Herein we discuss the strengths and drawbacks of technologies used to concentrate low abundance analytes in body fluids, with the aim to improve the effective sensitivity for MS discovery. Solvent removal by dry-down or dialysis, and immune-depletion of high abundance serum or plasma proteins, is shown to have disadvantages compared to positive selection of the candidate biomarkers by affinity enrichment. A theoretical analysis of affinity enrichment reveals that the yield for low abundance biomarkers is a direct function of the binding affinity (Association/Dissociation rates) used for biomarker capture. In addition, a high affinity capture pre processing step can effectively dissociate the candidate biomarker from partitioning with high abundance proteins such as albumin. Expert commentary: Properly designed high affinity capture materials can enrich the yield of low abundance (0.1-10 picograms/mL) candidate biomarkers for MS detection. Affinity capture and concentration, as an upfront step in sample preparation for MS, combined with MS advances in software and hardware that improve the resolution of the chromatographic separation can yield a transformative new class of low abundance biomarkers predicting disease risk or disease latency.

A method for the extraction of the endogenous tryptic peptides (peptidome) from human EDTA plasma

The proteins identified from endogenous peptides agreed between serum versus plasma, and tryptic versus non-tryptic peptides, when collected by C18 alone and analyzed by liquid chromatography electrospray ionization and tandem mass spectrometry (LC-ESI-MS/MS) including amyloids, apolipoproteins, haptoglobin, complements, fibrinogens, hemopexin, antitrypsin and alpha 2 macroglobulin. Precipitation of polypeptides from plasma in 9 vol of 100% organic solvent followed by stepwise extraction of the insoluble pellet with an increasing fraction of water identified thousands of proteins. A Coomassie-blue protein binding assay, and tricine SDS-PAGE, showed that Acetonitrile-Water (AH) resulted in a greater relative enrichment of low molecular weight plasma polypeptides than Acetonitrile-Methanol Water (AMH). A total of 905,386 MS/MS spectra greater than ~10,000 (E4) counts were correlated by X!TANDEM to a federated human protein library of 153,124 different protein sequences that resulted in 58,223 fully tryptic peptides from 3463 Gene Symbols of which 1880 had ≥ 5 independent peptides (p ≤ 0.00001). The results were filtered and organized in an SQL database for analysis using the generic R statistical analysis system. Cellular proteins including secreted and exosome proteins, signaling factors, nucleic acid binding proteins, metabolic enzymes and uncharacterized factors were observed with a significant enrichment of expected protein-protein interactions by STRING analysis.

Random and independent sampling of endogenous tryptic peptides from normal human EDTA plasma by liquid chromatography micro electrospray ionization and tandem mass spectrometry

Background

Normal human EDTA plasma samples were collected on ice, processed ice cold, and stored in a freezer at – 80 °C prior to experiments. Plasma test samples from the – 80 °C freezer were thawed on ice or intentionally warmed to room temperature.

Methods

Protein content was measured by CBBR binding and the release of alcohol soluble amines by the Cd ninhydrin assay. Plasma peptides released over time were collected over C18 for random and independent sampling by liquid chromatography micro electrospray ionization and tandem mass spectrometry (LC–ESI–MS/MS) and correlated with X!TANDEM.

Results

Fully tryptic peptides by X!TANDEM returned a similar set of proteins, but was more computationally efficient, than “no enzyme” correlations. Plasma samples maintained on ice, or ice with a cocktail of protease inhibitors, showed lower background amounts of plasma peptides compared to samples incubated at room temperature. Regression analysis indicated that warming plasma to room temperature, versus ice cold, resulted in a ~ twofold increase in the frequency of peptide identification over hours–days of incubation at room temperature. The type I error rate of the protein identification from the X!TANDEM algorithm combined was estimated to be low compared to a null model of computer generated random MS/MS spectra.

Conclusion

The peptides of human plasma were identified and quantified with low error rates by random and independent sampling that revealed 1000s of peptides from hundreds of human plasma proteins from endogenous tryptic peptides.

Electronic supplementary material

The online version of this article (10.1186/s12014-017-9176-7) contains supplementary material, which is available to authorized users.

The proteins cleaved by endogenous tryptic proteases in normal EDTA plasma by C18 collection of peptides for liquid chromatography micro electrospray ionization and tandem mass spectrometry

The tryptic peptides from ice cold versus room temperature plasma were identified by C18 liquid chromatography and micro electrospray ionization tandem mass spectrometry (LC–ESI–MS/MS). Samples collected on ice showed low levels of endogenous tryptic peptides compared to the same samples incubated at room temperature. Plasma on ice contained peptides from albumin, complement, and apolipoproteins and others that were observed by the X!TANDEM and SEQUEST algorithms. In contrast to ice cold samples, after incubation at room temperature, greater numbers of tryptic peptides from well characterized plasma proteins, and from cellular proteins were observed. A total of 583,927 precursor ions and MS/MS spectra were correlated to 94,669 best fit peptides that reduced to 22,287 correlations to the best accession within a gene symbol and to 7174 correlations to at least 510 gene symbols with ≥ 5 independent MS/MS correlations (peptide counts) that showed FDR q-values ranging from E−9 (i.e. FDR = 0.000000001) to E−227. A set of 528 gene symbols identified by X!TANDEM and SEQUEST including C4B showed ≥ fivefold variation between ice cold versus room temperature incubation. STRING analysis of the protein gene symbols observed from endogenous peptides in normal plasma revealed an extensive protein-interaction network of cellular factors associated with cell signalling and regulation, the formation of membrane bound organelles, cellular exosomes and exocytosis network proteins. Taken together the results indicated that a pool of cellular proteins, or protein complexes, in plasma are apparently not stable and degrade soon after incubation at room temperature.

Freeze-dried plasma proteins are stable at room temperature for at least 1 year

Thirty human EDTA plasma samples from male and female subjects ranging in age from 24 to 74 years were collected on ice, processed ice cold and stored frozen at -80 °C, in liquid nitrogen (LN2), or freeze dried and stored at room temperature in a desiccator (FDRT) or freeze dried and stored at -20 °C for 1 year (FD-20). In a separate experiment, EDTA plasma samples were collected onto ice, processed ice cold and maintained on ice ± protease inhibitors versus incubated at room temperature for up to 96 h. Random and independent sampling by liquid chromatography and tandem mass spectrometry (LC-ESI-MS/MS), as correlated by the MASCOT, OMSSA, X!TANDEM and SEQUEST algorithms, showed that tryptic peptides from complement component 4B (C4B) were rapidly released in plasma at room temperature. Random sampling by LC-ESI-MS/MS showed that peptides from C4B were undetectable on ice, but peptides were cleaved from the mature C4B protein including NGFKSHALQLNNR within as little as 1 h at room temperature. The frequency and intensity of precursors within ± 3 m/z of the C4B peptide NGFKSHALQLNNR was confirmed by automated targeted analysis where the precursors from MS/MS spectra that correlated to the target sequence were analyzed in SQL/R. The C4B preproprotein was processed at the N terminus to release the mature chain that was cleaved on the carboxyl side of the isoprene C2 domain within a polar C terminal sequence of the mature C4B protein, to reveal the thioester reaction site, consistent with LC-ESI-MS/MS and Western blot. Random sampling showed that proteolytic peptides from complement component C4B were rarely observed with long term storage at - 80 °C in a freezer or in liquid nitrogen (LN2), freeze drying with storage at - 20 °C (FD-20 °C) or freeze drying and storage at room temperature (FDRT). Plasma samples maintained at room temperature (RT) showed at least 10-fold to 100-fold greater frequency of peptide correlation to C4B and measured peptide intensity compared to samples on ice for up to 72 h or stored at - 80 °C, LN2, FDRT or FD-20 °C for up to a year.

Thin, Soft, Skin-Mounted Microfluidic Networks with Capillary Bursting Valves for Chrono-Sampling of Sweat

Systems for time sequential capture of microliter volumes of sweat released from targeted regions of the skin offer the potential to enable analysis of temporal variations in electrolyte balance and biomarker concentration throughout a period of interest. Current methods that rely on absorbent pads taped to the skin do not offer the ease of use in sweat capture needed for quantitative tracking; emerging classes of electronic wearable sweat analysis systems do not directly manage sweat-induced fluid flows for sample isolation. Here, a thin, soft, "skin-like" microfluidic platform is introduced that bonds to the skin to allow for collection and storage of sweat in an interconnected set of microreservoirs. Pressure induced by the sweat glands drives flow through a network of microchannels that incorporates capillary bursting valves designed to open at different pressures, for the purpose of passively guiding sweat through the system in sequential fashion. A representative device recovers 1.8 µL volumes of sweat each from 0.8 min of sweating into a set of separate microreservoirs, collected from 0.03 cm² area of skin with approximately five glands, corresponding to a sweat rate of 0.60 µL min^-1 per gland. Human studies demonstrate applications in the accurate chemical analysis of lactate, sodium, and potassium concentrations and their temporal variations.

Application of Hydrogel Nanoparticles for the Capture, Concentration, and Preservation of Low-Abundance Biomarkers

In the recent years, a lot of emphasis has been placed on the discovery and detection of clinically relevant biomarkers. Biomarkers are crucial for the early detection of several diseases, and they play an important role in the improvement of current treatments, thus reducing patient mortality rate. Because biofluids account to 60% of the body mass, they represent a goldmine of significant biomarkers. Unfortunately, because of their low concentration in body fluids, their lability, and the presence of high abundance proteins (i.e., albumin and immunoglobulins), low abundance biomarkers are difficult to detect with mass spectrometry or immunoassays. Nanoparticles made of poly(N-isopropylacrylamide) (NIPAm) and functionalized with affinity reactive baits allow researchers to overcome these physiological barriers and in one single step capture, concentrate, and preserve labile biomarkers in complex body fluids (i.e. urine, blood, sweat, CSF). Although hydrogel nanoparticles have been largely studied and used as a drug delivery tool, our application focuses on their capturing abilities instead of the releasing of specific drug molecules. Once the functionalized nanoparticles are incubated with a biological fluid, small biomarkers are captured by the affinity baits while unwanted high abundance analytes are excluded. The potentially relevant biomarkers are then concentrated into small volumes. The concentration factor (up to 10,000-fold) successfully enhances the detection sensitivity of mass spectrometry and immunoassays allowing the detection of previously invisible proteins.

Assays for Qualification and Quality Stratification of Clinical Biospecimens Used in Research: A Technical Report from the ISBER Biospecimen Science Working Group

This technical report presents quality control (QC) assays that can be performed in order to qualify clinical biospecimens that have been biobanked for use in research. Some QC assays are specific to a disease area. Some QC assays are specific to a particular downstream analytical platform. When such a qualification is not possible, QC assays are presented that can be performed to stratify clinical biospecimens according to their biomolecular quality.

Evaluating the effects of preanalytical variables on the stability of the human plasma proteome

High quality clinical biospecimens are vital for biomarker discovery, verification, and validation. Variations in blood processing and handling can affect protein abundances and assay reliability. Using an untargeted LC-MS approach, we systematically measured the impact of preanalytical variables on the plasma proteome. Time prior to processing was the only variable that affected the plasma protein levels. LC-MS quantification showed that preprocessing times <6h had minimal effects on the immunodepleted plasma proteome, but by 4 days significant changes were apparent. Elevated levels of many proteins were observed, suggesting that in addition to proteolytic degradation during the preanalytical phase, changes in protein structure are also important considerations for protocols using antibody depletion. As to processing variables, a comparison of single- vs double-spun plasma showed minimal differences. After processing, the impact ⩽3 freeze-thaw cycles was negligible regardless of whether freshly collected samples were processed in short succession or the cycles occurred during 14-17 years of frozen storage (-80 °C). Thus, clinical workflows that necessitate modest delays in blood processing times or employ different centrifugation steps can yield valuable samples for biomarker discovery and verification studies.

Phenotype-Driven Plasma Biobanking Strategies and Methods

Biobank development and integration with clinical data from electronic medical record (EMR) databases have enabled recent strides in genomic research and personalized medicine. BioVU, Vanderbilt's DNA biorepository linked to de-identified clinical EMRs, has proven fruitful in its capacity to extensively appeal to numerous areas of biomedical and clinical research, supporting the discovery of genotype-phenotype interactions. Expanding on experiences in BioVU creation and development, we have recently embarked on a parallel effort to collect plasma in addition to DNA from blood specimens leftover after routine clinical testing at Vanderbilt. This initiative offers expanded utility of BioVU by combining proteomic and metabolomic approaches with genomics and/or clinical outcomes, widening the breadth for potential research and subsequent future impact on clinical care. Here, we describe the considerations and components involved in implementing a plasma biobank program from a feasibility assessment through pilot sample collection.

Identification of clinical biomarkers for pre-analytical quality control of blood samples

BACKGROUND

Pre-analytical conditions are key factors in maintaining the high quality of biospecimens. They are necessary for accurate reproducibility of experiments in the field of biomarker discovery as well as achieving optimal specificity of laboratory tests for clinical diagnosis. In research at the National Biobank of Korea, we evaluated the impact of pre-analytical conditions on the stability of biobanked blood samples by measuring biochemical analytes commonly used in clinical laboratory tests.

METHODS

We measured 10 routine laboratory analytes in serum and plasma samples from healthy donors (n = 50) with a chemistry autoanalyzer (Hitachi 7600-110). The analyte measurements were made at different time courses based on delay of blood fractionation, freezing delay of fractionated serum and plasma samples, and at different cycles (0, 1, 3, 6, 9) of freeze-thawing. Statistically significant changes from the reference sample mean were determined using the repeated-measures ANOVA and the significant change limit (SCL).

RESULTS

The serum levels of GGT and LDH were changed significantly depending on both the time interval between blood collection and fractionation and the time interval between fractionation and freezing of serum and plasma samples. The glucose level was most sensitive only to the elapsed time between blood collection and centrifugation for blood fractionation. Based on these findings, a simple formula (glucose decrease by 1.387 mg/dL per hour) was derived to estimate the length of time delay after blood collection. In addition, AST, BUN, GGT, and LDH showed sensitive responses to repeated freeze-thaw cycles of serum and plasma samples.

CONCLUSION

These results suggest that GGT and LDH measurements can be used as quality control markers for certain pre-analytical conditions (eg, delayed processing or repeated freeze-thawing) of blood samples which are either directly used in the laboratory tests or stored for future research in the biobank.

Comprehensive quantitative analysis of ovarian and breast cancer tumor peptidomes

Aberrant degradation of proteins is associated with many pathological states, including cancers. Mass spectrometric analysis of tumor peptidomes, the intracellular and intercellular products of protein degradation, has the potential to provide biological insights on proteolytic processing in cancer. However, attempts to use the information on these smaller protein degradation products from tumors for biomarker discovery and cancer biology studies have been fairly limited to date, largely due to the lack of effective approaches for robust peptidomics identification and quantification and the prevalence of confounding factors and biases associated with sample handling and processing. Herein, we have developed an effective and robust analytical platform for comprehensive analyses of tissue peptidomes, which is suitable for high-throughput quantitative studies. The reproducibility and coverage of the platform, as well as the suitability of clinical ovarian tumor and patient-derived breast tumor xenograft samples with postexcision delay of up to 60 min before freezing for peptidomics analysis, have been demonstrated. Moreover, our data also show that the peptidomics profiles can effectively separate breast cancer subtypes, reflecting tumor-associated protease activities. Peptidomics complements results obtainable from conventional bottom-up proteomics and provides insights not readily obtainable from such approaches.

A PSA-guided approach for a better diagnosis of prostatic adenocarcinoma based on MALDI profiling and peptide identification

BACKGROUND

Prostate cancer (PCa) is the second cause of mortality in men worldwide. The prostate-specific antigen (PSA) test is routinely adopted in diagnosis; nevertheless more reliable biomarkers are continuously under investigation by monitoring the release of molecules into the bloodstream. The serum protein profiles appear to provide cancer-specific fingerprints that help to discriminate patients (especially with low PSA level) from controls, improving the performance of existing clinical tests.

METHODS

Samples from healthy controls and PCa patients with low (≤4 ng/mL) and high PSA (>4 ng/mL) levels were analyzed by MALDI profiling, and by a multi fractionation approach coupled to ESI-MS for peaks identification.

RESULTS

MALDI profiling achieved to detect 10 and 14 changed peaks (p-value <0.05), respectively, in PCa patients with low and high PSA versus controls. In particular, a peak identified as C3f fragment, resulted overexpressed in low PSA PCa patients.

CONCLUSIONS

PSA test, coupled to MALDI profiling, is able to detect changes, specifically related to PCa, in low molecular weight protein range. Furthermore, for the first time in prostate cancer research, the identification and quantification of the small peptide C3f appears to be relevant for the detection of false negatives, providing an additive diagnostic power to PSA (p<0.01) and suggesting its use in clinical tests.

[Search for potential gastric cancer biomarkers using low molecular weight blood plasma proteome profiling by mass spectrometry]

Gastric cancer, one of the most widespread malignant tumors, still lacks reliable serum/plasma biomarkers of its early detection. In this study we have developed, unified, and tested a new methodology for search of gastric cancer biomarkers based on profiling of low molecular weight proteome (LMWP) (1-17 kDa). This approach included three main components: sample pre-fractionation, matrix-assisted laser desorption ionization time of flight mass spectrometry (MALDI-TOF-MS), data analysis by a bioinformatics software package. Applicability and perspectives of the developed approach for detection of potential gastric cancer markers during LMWP analysis have been demonstrated using 69 plasma samples from patients with gastric cancer (stages I-IV) and 238 control samples. The study revealed peptides/polypeptides, which may be potentially used for detection of this pathology.

Hydrogel nanoparticle harvesting of plasma or urine for detecting low abundance proteins

Novel biomarker discovery plays a crucial role in providing more sensitive and specific disease detection. Unfortunately many low-abundance biomarkers that exist in biological fluids cannot be easily detected with mass spectrometry or immunoassays because they are present in very low concentration, are labile, and are often masked by high-abundance proteins such as albumin or immunoglobulin. Bait containing poly(N-isopropylacrylamide) (NIPAm) based nanoparticles are able to overcome these physiological barriers. In one step they are able to capture, concentrate and preserve biomarkers from body fluids. Low-molecular weight analytes enter the core of the nanoparticle and are captured by different organic chemical dyes, which act as high affinity protein baits. The nanoparticles are able to concentrate the proteins of interest by several orders of magnitude. This concentration factor is sufficient to increase the protein level such that the proteins are within the detection limit of current mass spectrometers, western blotting, and immunoassays. Nanoparticles can be incubated with a plethora of biological fluids and they are able to greatly enrich the concentration of low-molecular weight proteins and peptides while excluding albumin and other high-molecular weight proteins. Our data show that a 10,000 fold amplification in the concentration of a particular analyte can be achieved, enabling mass spectrometry and immunoassays to detect previously undetectable biomarkers.

Colorectal cancer biomarker discovery and validation using LC-MS/MS-based proteomics in blood: truth or dare?

Globally, colorectal cancer (CRC) is the third most common malignant neoplasm. However, highly sensitive, specific, noninvasive tests that allow CRC diagnosis at an early stage are still needed. As circulatory blood reflects the physiological status of an individual and/or the disease status for several disorders, efforts have been undertaken to identify candidate diagnostic CRC markers in plasma and serum. In this review, the challenges, bottlenecks and promising properties of mass spectrometry (MS)-based proteomics in blood are discussed. More specifically, important aspects in clinical design, sample retrieval, sample preparation, and MS analysis are presented. The recent developments in targeted MS approaches in plasma or serum are highlighted as well.

Proteomics in atherothrombosis: a future perspective

Atherothrombosis is the primary cause of death in Western countries. The cellular and molecular mechanisms underlying atherosclerosis remain widely unknown. The complex nature of atherosclerotic cardiovascular diseases demands the development of novel technologies that enable discovery of new biomarkers for early disease detection and risk stratification, which may predict clinical outcome. In this review, we outline potential sources and recent proteomic approaches that could be applied in the search of novel biomarkers of cardiovascular risk. In addition, we describe some issues raised in relation to the application of proteomics to blood samples, as well as two novel emerging concepts, such as peptidomics and population proteomics. In the future, the use of high-throughput techniques (proteomic, genomics and metabolomics) will potentially identify novel patterns of biomarkers, which, along with traditional risk factors and imaging techniques, could help to target vulnerable patients and monitor the beneficial effects of pharmacological agents.

Effects of preanalytical variables on peptide and protein measurements in human serum and plasma: implications for clinical proteomics

There is a wealth of knowledge in the field of in vitro diagnostics with regard to preanalytical variables and their impact on the determination of peptide and protein analytes in human serum and plasma. This information is applicable to clinical proteomics investigations, which utilize the same sample types. Studies have demonstrated that the majority of variations and errors in in vitro diagnostics seem to occur in the preanalytical phase prior to specimen analysis. Preanalytical processes include study design, compliance of the subjects investigated, compliance of the technical staff in adherence to protocols, choice of specimens utilized and sample collection and processing. These variables can have a dramatic impact on the determination of analytes and can affect result outcomes, reproducibility and the validity of investigations. By drawing analogies to in vitro diagnostics practices, specific variables that are likely to impact the results of proteomics studies can be identified. Recognition of such variables is the first step towards their understanding and, eventually, controlling their impact. In this article, we will review preanalytical variables, provide examples for their effects on the determination of distinct peptides and proteins and discuss potential implications for clinical proteomics investigations.

Proteomic analysis of venous thromboembolism: an update

Venous thromboembolism is a complex, multifactorial disorder, the pathogenesis of which typically involves a variety of inherited or acquired factors. The multifactorial etiology of this disease and the partial correlation between genotype and prothrombotic phenotype limit greatly the value of genetic analysis in assessing thrombotic risk. The integration of several new 'omics' techniques enables a multifaceted and holistic approach to the study of venous thrombotic processes and pave the way to the search and identification of novel blood biomarkers and/or effectors of thrombus formation that can also be the possible future target of new anticoagulant and thrombolytic therapies for more personalized medicine. This review provides a comprehensive overview of the latest candidate proteomic biomarkers of venous thrombosis and of the proteomics studies relevant to its pathophysiology, some of which seem to confirm the existence of a common physiopathological basis for venous thromboembolism and atherothrombosis.