Quantitative Fragmentation Model for Bottom-Up Shotgun Lipidomics.

Quantitative bottom-up shotgun lipidomics relies on molecular species-specific "signature" fragments consistently detectable in tandem mass spectra of analytes and standards. Molecular species of glycerophospholipids are typically quantified using carboxylate fragments of their fatty acid moieties produced by higher-energy collisional dissociation of their molecular anions. However, employing standards whose fatty acids moieties are similar, yet not identical, to the target lipids could severely compromise their quantification. We developed a generic and portable fragmentation model implemented in the open-source LipidXte software that harmonizes the abundances of carboxylate anion fragments originating from fatty acid moieties having different sn-1/2 positions at the glycerol backbone, length of the hydrocarbon chain, and number and location of double bonds. The postacquisition adjustment enables unbiased absolute (molar) quantification of glycerophospholipid species independent of instrument settings, collision energy, and employed internal standards.

Rapid and deep proteomes by faster sequencing on a benchtop quadrupole ultra-high-field Orbitrap mass spectrometer.

Shotgun proteomics is a powerful technology for global analysis of proteins and their post-translational modifications. Here, we investigate the faster sequencing speed of the latest Q Exactive HF mass spectrometer, which features an ultra-high-field Orbitrap mass analyzer. Proteome coverage is evaluated by four different acquisition methods and benchmarked across three generations of Q Exactive instruments (ProteomeXchange data set PXD001305). We find the ultra-high-field Orbitrap mass analyzer to be capable of attaining a sequencing speed above 20 Hz, and it routinely exceeds 10 peptide spectrum matches per second or up to 600 new peptides sequenced per gradient minute. We identify 4400 proteins from 1 µg of HeLa digest using a 1 h gradient, which is an approximately 30% improvement compared to that with previous instrumentation. In addition, we show that very deep proteome coverage can be achieved in less than 24 h of analysis time by offline high-pH reversed-phase peptide fractionation, from which we identify more than 140,000 unique peptide sequences. This is comparable to state-of-the-art multiday, multienzyme efforts. Finally, the acquisition methods are evaluated for single-shot phosphoproteomics, where we identify 7600 unique HeLa phosphopeptides in one gradient hour and find the quality of fragmentation spectra to be more important than quantity for accurate site assignment.

Multiplexed MS/MS for improved data-independent acquisition.

In mass spectrometry-based proteomics, data-independent acquisition (DIA) strategies can acquire a single data set useful for both identification and quantification of detectable peptides in a complex mixture. However, DIA data are noisy owing to a typical five- to tenfold reduction in precursor selectivity compared to data obtained with data-dependent acquisition or selected reaction monitoring. We demonstrate a multiplexing strategy, MSX, for DIA analysis that increases precursor selectivity fivefold.

Targeted proteomic quantification on quadrupole-orbitrap mass spectrometer.

There is an immediate need for improved methods to systematically and precisely quantify large sets of peptides in complex biological samples. To date protein quantification in biological samples has been routinely performed on triple quadrupole instruments operated in selected reaction monitoring mode (SRM), and two major challenges remain. Firstly, the number of peptides to be included in one survey experiment needs to be increased to routinely reach several hundreds, and secondly, the degree of selectivity should be improved so as to reliably discriminate the targeted analytes from background interferences. High resolution and accurate mass (HR/AM) analysis on the recently developed Q-Exactive mass spectrometer can potentially address these issues. This instrument presents a unique configuration: it is constituted of an orbitrap mass analyzer equipped with a quadrupole mass filter as the front-end for precursor ion mass selection. This configuration enables new quantitative methods based on HR/AM measurements, including targeted analysis in MS mode (single ion monitoring) and in MS/MS mode (parallel reaction monitoring). The ability of the quadrupole to select a restricted m/z range allows one to overcome the dynamic range limitations associated with trapping devices, and the MS/MS mode provides an additional stage of selectivity. When applied to targeted protein quantification in urine samples and benchmarked with the reference SRM technique, the quadrupole-orbitrap instrument exhibits similar or better performance in terms of selectivity, dynamic range, and sensitivity. This high performance is further enhanced by leveraging the multiplexing capability of the instrument to design novel acquisition methods and apply them to large targeted proteomic studies for the first time, as demonstrated on 770 tryptic yeast peptides analyzed in one 60-min experiment. The increased quality of quadrupole-orbitrap data has the potential to improve existing protein quantification methods in complex samples and address the pressing demand of systems biology or biomarker evaluation studies.

Sensitive determination of prohibited drugs in dried blood spots (DBS) for doping controls by means of a benchtop quadrupole/Orbitrap mass spectrometer.

In the present study, a new type of mass spectrometer combining a quadrupole mass filter, a higher collision dissociation (HCD) cell and an Orbitrap detector, was evaluated for the analysis of dried blood spots (DBS) in doping controls. DBS analysis is characterized by the necessity to detect prohibited compounds in sub-nanogram-per-milliliter levels with high identification capacity. After extraction of DBS with an organic solvent and liquid chromatographic separation (using a regular C18-RP-analytical UHPLC-column) of target analytes, mass spectrometry is performed with a high-resolution full scan in positive and negative mode by means of electrospray ionisation. Single-product ion mass spectra are acquired using the data-dependent analysis mode (employing an inclusion list) for previously selected precursors of known prohibited compounds with fixed retention time ranges. Besides, a sensitive screening in a targeted approach, non-targeted analysis for retrospective data evaluation is thus possible. The chosen experimental design enables the determination of various drugs from different classes with one generic sample preparation which is shown for 26 selected model compounds (Δ(9)-tetrahydrocannabinol (THC), tetrahydrocannabinol-9-carboxylic acid (THC-COOH), methylhexaneamine, methylphenidate, cocaine, nikethamide, 3,4-methylenedioxyamphetamine, N-methyl-3,4-methylenedioxyamphetamine, strychnine, mesocarb, salbutamol, formoterol, clenbuterol, metandienone, stanozolol, bisoprolol, propranolol, metoprolol, anastrazole, clomiphene, exemestane, dexamethasone, budesonide, selective androgen receptor modulator (SARM) S4 (andarine), SARM S1, hydrochlorothiazide). Generally, only qualitative result interpretation was focussed upon, but for target analytes with deuterium-labelled internal standards (salbutamol, clenbuterol, cocaine, dexamethasone, THC-COOH and THC) quantitative analysis was also possible. Especially the most challenging analytes, THC and its carboxy metabolite, were detected in DBS at relevant concentrations (<0.5 ng/mL) using targeted HCD experiments. The method was validated for the parameters: specificity, linearity (0-20 ng/mL), precision (<25%), recovery (mean 60%), limit of detection/quantification, ion suppression, stability and accuracy (80-120%). Six isotope-labelled analogues used as internal standards facilitate a quantitative result interpretation which is of utmost importance especially for in-competition drug sports testing.

Peptide fingerprinting of Alzheimer's disease in cerebrospinal fluid: identification and prospective evaluation of new synaptic biomarkers.

BACKGROUND: Today, dementias are diagnosed late in the course of disease. Future treatments have to start earlier in the disease process to avoid disability requiring new diagnostic tools. The objective of this study is to develop a new method for the differential diagnosis and identification of new biomarkers of Alzheimer's disease (AD) using capillary-electrophoresis coupled to mass-spectrometry (CE-MS) and to assess the potential of early diagnosis of AD. METHODS AND FINDINGS: Cerebrospinal fluid (CSF) of 159 out-patients of a memory-clinic at a University Hospital suffering from neurodegenerative disorders and 17 cognitively-healthy controls was used to create differential peptide pattern for dementias and prospective blinded-comparison of sensitivity and specificity for AD diagnosis against the Criterion standard in a naturalistic prospective sample of patients. Sensitivity and specificity of the new method compared to standard diagnostic procedures and identification of new putative biomarkers for AD was the main outcome measure. CE-MS was used to reliably detect 1104 low-molecular-weight peptides in CSF. Training-sets of patients with clinically secured sporadic Alzheimer's disease, frontotemporal dementia, and cognitively healthy controls allowed establishing discriminative biomarker pattern for diagnosis of AD. This pattern was already detectable in patients with mild cognitive impairment (MCI). The AD-pattern was tested in a prospective sample of patients (n = 100) and AD was diagnosed with a sensitivity of 87% and a specificity of 83%. Using CSF measurements of beta-amyloid1-42, total-tau, and phospho(181)-tau, AD-diagnosis had a sensitivity of 88% and a specificity of 67% in the same sample. Sequence analysis of the discriminating biomarkers identified fragments of synaptic proteins like proSAAS, apolipoprotein J, neurosecretory protein VGF, phospholemman, and chromogranin A. CONCLUSIONS: The method may allow early differential diagnosis of various dementias using specific peptide fingerprints and identification of incipient AD in patients suffering from MCI. Identified biomarkers facilitate face validity for the use in AD diagnosis.

Naturally occurring human urinary peptides for use in diagnosis of chronic kidney disease.

Because of its availability, ease of collection, and correlation with physiology and pathology, urine is an attractive source for clinical proteomics/peptidomics. However, the lack of comparable data sets from large cohorts has greatly hindered the development of clinical proteomics. Here, we report the establishment of a reproducible, high resolution method for peptidome analysis of naturally occurring human urinary peptides and proteins, ranging from 800 to 17,000 Da, using samples from 3,600 individuals analyzed by capillary electrophoresis coupled to MS. All processed data were deposited in an Structured Query Language (SQL) database. This database currently contains 5,010 relevant unique urinary peptides that serve as a pool of potential classifiers for diagnosis and monitoring of various diseases. As an example, by using this source of information, we were able to define urinary peptide biomarkers for chronic kidney diseases, allowing diagnosis of these diseases with high accuracy. Application of the chronic kidney disease-specific biomarker set to an independent test cohort in the subsequent replication phase resulted in 85.5% sensitivity and 100% specificity. These results indicate the potential usefulness of capillary electrophoresis coupled to MS for clinical applications in the analysis of naturally occurring urinary peptides.

Quantitative-qualitative data acquisition using a benchtop Orbitrap mass spectrometer.

Current approaches to discovery-stage drug metabolism studies (pharmacokinetics, microsomal stability, etc.) typically use triple-quadrupole-based approaches for quantitative analysis. This necessitates the optimization of parameters such as Q1 and Q3 m/z values, collision energy, and interface voltages. These studies detect only the specified compound and information about other components, such as metabolites, is lost. The ability to perform full-scan acquisition for quantitative analysis would eliminate the need for compound optimization while enabling the detection of metabolites and other non-drug-related endogenous components. Such an instrument would have to provide sensitivity, selectivity, dynamic range, and scan speed suitable for discovery-stage quantitative studies. In this study, a prototype benchtop Orbitrap-based mass analyzer was used to collect both quantitative and qualitative data from human microsomal incubation samples as well as rat plasma from pharmacokinetic studies. Instrumental parameters such as scan speed, resolution, and mass accuracy are discussed in relation to the requirements for a quantitative-qualitative workflow. The ability to perform highly selective quantitative analysis while simultaneously characterizing metabolites from both in vitro and in vivo studies is discussed.

Urinary proteomic biomarkers in coronary artery disease.

Urinary proteomics is emerging as a powerful non-invasive tool for diagnosis and monitoring of variety of human diseases. We tested whether signatures of urinary polypeptides can contribute to the existing biomarkers for coronary artery disease (CAD). We examined a total of 359 urine samples from 88 patients with severe CAD and 282 controls. Spot urine was analyzed using capillary electrophoresis on-line coupled to ESI-TOF-MS enabling characterization of more than 1000 polypeptides per sample. In a first step a "training set" for biomarker definition was created. Multiple biomarker patterns clearly distinguished healthy controls from CAD patients, and we extracted 15 peptides that define a characteristic CAD signature panel. In a second step, the ability of the CAD-specific panel to predict the presence of CAD was evaluated in a blinded study using a "test set." The signature panel showed sensitivity of 98% (95% confidence interval, 88.7-99.6) and 83% specificity (95% confidence interval, 51.6-97.4). Furthermore the peptide pattern significantly changed toward the healthy signature correlating with the level of physical activity after therapeutic intervention. Our results show that urinary proteomics can identify CAD patients with high confidence and might also play a role in monitoring the effects of therapeutic interventions. The workflow is amenable to clinical routine testing suggesting that non-invasive proteomics analysis can become a valuable addition to other biomarkers used in cardiovascular risk assessment.

CE-MS analysis of the human urinary proteome for biomarker discovery and disease diagnostics.

Owing to its availability, ease of collection, and correlation with pathophysiology of diseases, urine is an attractive source for clinical proteomics. However, many proteomic studies have had only limited clinical impact, due to factors such as modest numbers of subjects, absence of disease controls, small numbers of defined biomarkers, and diversity of analytical platforms. Therefore, it is difficult to merge biomarkers from different studies into a broadly applicable human urinary proteome database. Ideally, the methodology for defining the biomarkers should combine a reasonable analysis time with high resolution, thereby enabling the profiling of adequate samples and recognition of sufficient features to yield robust diagnostic panels. Capillary electrophoresis coupled to mass spectrometry (CE-MS), which was used to analyze urine samples from healthy subjects and patients with various diseases, is a suitable approach for this task. The database of these datasets compiled from the urinary peptides enabled the diagnosis, classification, and monitoring of a wide range of diseases. CE-MS exhibits excellent performance for biomarker discovery and allows subsequent biomarker sequencing independent of the separation platform. This approach may elucidate the pathogenesis of many diseases, and better define especially renal and urological disorders at the molecular level.

Electrophoretic methods for analysis of urinary polypeptides in IgA-associated renal diseases.

We evaluated the utility of SDS-PAGE/Western blot and CE coupled with MS (CE-MS) for detection of urinary polypeptide biomarkers of renal disease in patients with IgA-associated glomerulonephritides. In a reference cohort of 402 patients with various renal disorders and 207 healthy controls, we defined CE-MS patterns of renal damage and IgA nephropathy (IgAN). In a blinded analysis of a separate cohort of patients with IgAN (n = 10), Henoch-Schoenlein purpura (HSP) with nephritis (n = 10), and IgA-associated glomerulonephritis due to hepatitis C virus (HCV)-induced cirrhosis (n = 9), and healthy controls (n = 12), we compared SDS-PAGE/Western blot and CE-MS against clinical urinalysis for detection of urinary proteins/polypeptides. Urinalysis indicated proteinuria for 50, 90, and 33% of patients, respectively, and for none of the healthy controls. SDS-PAGE/Western blot showed urinary polypeptides abnormality for 90, 80, and 67% of patients, respectively, and for none of the healthy controls. CE-MS indicated a Renal Damage Pattern in 80, 80, and 100 of patients, respectively, and in 17% of healthy controls, with the more specific IgAN Pattern in 90, 90, and 1%, respectively, and in none of the healthy controls. Based on differences in CE-MS patterns, the disease mechanisms may differ among various IgA-associated glomerulonephritides. These exploratory findings should be evaluated in a prospective study with contemporaneous renal biopsy and urinary testing. If validated, it may be feasible to adapt the CE-MS methodology to develop novel tests to detect renal injury at earlier stages, assess clinical manifestations, and monitor responses to therapy in patients with IgA-associated renal diseases.

Proteomic patterns predict acute graft-versus-host disease after allogeneic hematopoietic stem cell transplantation.

Acute graft-versus-host disease (aGvHD) contributes significantly to morbidity and mortality after allogeneic hematopoietic stem cell transplantation (allo-HSCT). Diagnosis of GvHD is mainly based on clinical features and tissue biopsies. A noninvasive, unbiased laboratory test for GvHD diagnosis does not exist. Here we describe the application of capillary electrophoresis coupled online with mass spectrometry (CE-MS) to 13 samples from 10 patients with aGvHD of grade II or more and 50 control samples from 23 patients without GvHD. About 170 GvHD-specific polypeptides were detected and a tentatively aGvHD-specific model consisting of 31 polypeptides was chosen, allowing correct classification of 13 of 13 (sensitivity 100.0% [95% confidence interval {CI} 75.1 to 100.0]) aGvHD samples and 49 of 50 (specificity 98.0% [95% CI 89.3 to 99.7]) control samples of the training set. The subsequent blinded evaluation of 599 samples enabled diagnosis of aGvHD greater than grade II, even prior to clinical diagnosis, with a sensitivity of 83.1% (95% CI 73.1 to 87.9) and a specificity of 75.6% (95% CI 71.6 to 79.4). Thus, high-resolution proteome analysis represents an unbiased laboratory-based screening method, enabling diagnosis, and possibly enabling preemptive therapy.

A functional annotation of subproteomes in human plasma.

The data collected by Human Proteome Organization's Plasma Proteome Pilot project phase was analyzed by members of our working group. Accordingly, a functional annotation of the human plasma proteome was carried out. Here, we report the findings of our analyses. First, bioinformatic analyses were undertaken to determine the likely sources of plasma proteins and to develop a protein interaction network of proteins identified in this project. Second, annotation of these proteins was performed in the context of functional subproteomes involved in the coagulation pathway, the mononuclear phagocytic system, the inflammation pathway, the cardiovascular system, and the liver; as well as the subset of proteins associated with DNA binding activities. Our analyses contributed to the Plasma Proteome Database (http://www.plasmaproteomedatabase.org), an annotated database of plasma proteins identified by HPPP as well as from other published studies. In addition, we address several methodological considerations including the selective enrichment of post-translationally modified proteins by the use of multi-lectin chromatography as well as the use of peptidomic techniques to characterize the low molecular weight proteins in plasma. Furthermore, we have performed additional analyses of peptide identification data to annotate cleavage of signal peptides, sites of intra-membrane proteolysis and post-translational modifications. The HPPP-organized, multi-laboratory effort, as described herein, resulted in much synergy and was essential to the success of this project.

Peptidomic analysis of human blood specimens: comparison between plasma specimens and serum by differential peptide display.

The human Plasma Proteome Project pilot phase aims to analyze serum and plasma specimens to elucidate specimen characteristics by various proteomic techniques to ensure sufficient sample quality for the HUPO main phase. We used our proprietary peptidomics technologies to analyze the samples distributed by HUPO. Peptidomics summarizes technologies for visualization, quantitation, and identification of the low-molecular-weight proteome (<15 kDa), the "peptidome." We analyzed all four HUPO specimens (EDTA plasma, citrate plasma, heparin plasma, and serum) from African- and Asian-American donors and compared them to in-house collected Caucasian specimens. One main finding focuses on the most suitable method of plasma specimen collection. Gentle platelet removal from plasma samples is beneficial for improved specificity. Platelet contamination or activation of platelets by low temperature prior to their removal leads to distinct and multiple peptide signals in plasma samples. Two different specimen collection protocols for platelet-poor plasma are recommended. Further emphasis is placed on the differences between plasma and serum on a peptidomic level. A large number of peptides, many of them in rather high abundance, are only present in serum and not detectable in plasma. This ex vivo generation of multiple peptides hampers discovery efforts and is caused by a variety of factors: the release of platelet-derived peptides, other peptides derived from cellular components or the clot, enzymatic activities of coagulation cascades, and other proteases. We conclude that specimen collection is a crucial step for successful peptide biomarker discovery in human blood samples. For analysis of the low-molecular-weight proteome, we recommend the use of platelet-depleted EDTA or citrate plasma.

Correlation-associated peptide networks of human cerebrospinal fluid.

Profiling of peptides and small proteins from either human body fluids or tissues by chromatography and subsequent mass spectrometry reveals several thousand individual peptide signals per sample. Any peptide is an intermediate in the course of biosynthesis, post-translational modification (PTM), proteolytic processing and degradation. Changes in the concentration of one peptide often affects the concentration of the other, hence a challenge consists in the development of suitable tools to turn this large amount of data into biologically relevant information. Comprehensive statistical analysis of the peptide profiling data allows associating peptides, which are closely related in terms of peptide biochemistry. Here, the bioinformatic concept of peptide networks, correlation-associated peptide networks (CANs), is introduced. Peptides with statistical similarity of their concentrations are grouped in form of networks, and these networks are interpreted in terms of peptide biochemistry. The spectrum of functional relationships found in cerebrospinal fluid CAN covers PTM and proteolytic degradation of peptides, clearance processing in the complement cascade, common secretion of peptides by neuroendocrine cells as well as ubiquitin-mediated degradation. Our results indicate that CAN is a powerful bioinformatic tool for the systematic analysis and interpretation of large peptidomics and proteomics data and helps to discover novel bioactive and diagnostic peptides.

Top-down identification of endogenous peptides up to 9 kDa in cerebrospinal fluid and brain tissue by nanoelectrospray quadrupole time-of-flight tandem mass spectrometry.

Recent work on protein and peptide biomarker patterns revealed the difficulties in identifying their molecular components, which is indispensable for validation of the biological context. Cerebrospinal fluid and brain tissue are used as sources to discover new biomarkers, e.g. for neurodegenerative diseases. Many of these biomarker candidates are peptides with a molecular mass of <10 kDa. Their identification is favourably achieved with a 'top-down' approach, because this requires less purification and an enzymatic cleavage will often not yield enough specific fragments for successful database searches. Here, we describe an approach using quadrupole time-of-flight mass spectrometry (TOFMS) as a highly efficient mass spectrometric purification and identification tool after off-line decomplexation of biological samples by liquid chromatography. After initial peptidomic screening with matrix-assisted laser desorption/ionization (MALDI) TOFMS, the elution behaviour in chromatography and the exact molecular mass were used to locate the same signals in nanoelectrospray measurements. Most of the peaks detected in MALDI-TOFMS could be retrieved in nanoelectrospray quadrupole TOFMS. Suitable collision energies for informative fragment spectra were investigated for different parent ions, charge states and molecular masses. After collision-induced dissociation, the resulting fragmentation data of multiply charged ions can become much more complicated than those derived from tryptic peptide digests. However, the mass accuracy and resolution of quadrupole TOF instruments results in high-quality data suitable for determining peptide sequences. The protein precursor, proteolytic processing and post-translational modifications were identified by automated database searches. This is demonstrated by the exemplary identifications of thymosin beta-4 (5.0 kDa) and NPY (4.3 kDa) from rat hypothalamic tissue and ubiquitin (8.6 kDa) from human cerebrospinal fluid. The high data quality should also allow for de novo identification. This methodology is generally applicable for peptides up to a molecular mass of about 10 kDa from body fluids, tissues or other biological sources.

Prerequisites for peptidomic analysis of blood samples: I. Evaluation of blood specimen qualities and determination of technical performance characteristics.

Proteomics studies aiming at a detailed analysis of proteins, and peptidomics, aiming at the analysis of the low molecular weight proteome (peptidome) offer a promising approach to discover novel biomarkers valuable for different crucial steps in detection, prevention and treatment of disease. Much emphasis has been given to the analysis of blood, since this source would by far offer the largest number of meaningful biomarker applications. Blood is a complex liquid tissue that comprises cells and extra-cellular fluid. The choice of suitable specimen collection is crucial to minimize artificial occurring processes during specimen collection and preparation (e.g. cell lysis, proteolysis). After specimen collection, sample preparation for peptidomics is carried out by physical methods (filtration, gel-chromatography, precipitation) which allow for separation based on molecular size, with and without immunodepletion of major abundant proteins. Differential Peptide Display (DPD) is an offline-coupled combination of Reversed-Phase-HPLC and MALDI mass spectrometry in combination with in-house developed data display and analysis tools. Identifications of peptides are carried out by additional mass spectrometric methods (e.g. online LC-ESI-MS/MS). In the work presented here, insights into semi-quantitative mass spectrometric profiling of plasma peptides by DPD are given. This includes proper specimen selection (plasma vs. serum), sample preparation, especially peptide extraction, the determination of sensitivity (i.e. by establishing detection limits of exogenously spiked peptides), the reproducibility for individual as well as for all peptides (Coefficient of Variation calculations) and quantification (correlation between signal intensity and concentration). Finally, the implications for clinical peptidomics are discussed.

Prerequisites for peptidomic analysis of blood samples: II. Analysis of human plasma after oral glucose challenge -- a proof of concept.

Mass spectrometric plasma analysis for biomarker discovery has become an exploratory focus in proteomic research: the challenges of analyzing plasma samples by mass spectrometry have become apparent not only since the human proteome organization (HUPO) has put much emphasis on the human plasma proteome. This work demonstrates fundamental proteomic research to reveal sensitivity and quantification capabilities of our Peptidomics technologies by detecting distinct changes in plasma peptide composition in samples after challenging healthy volunteers with orally administered glucose. Differential Peptide Display (DPD) is a technique for peptidomics studies to compare peptides from distinct biological samples. Mass spectrometry (MS) is used as a qualitative and quantitative analysis tool without previous trypsin digestion or labeling of the samples. Circulating peptides (< 15 kDa) were extracted from 1.3 mL plasma samples and the extracts separated by liquid chromatography into 96 fractions. Each fraction was subjected to MALDI MS, and mass spectra of all fractions were combined resulting in a 2D-display of > 2,000 peptides from each sample. Endogenous peptides that responded to oral glucose challenge were detected by DPD of pre-and post-challenge plasma samples from 16 healthy volunteers and subsequently identified by nESI-qTOF MS. Two of the 15 MS peaks that were significantly modulated by glucose challenge were subsequently identified as insulin and C-peptide. These results were validated by using immunoassays for insulin and C-peptide. This paper serves as a proof of principle for proteomic biomarker discovery down to the pM concentration range by using small amounts of human plasma.

High-throughput biomarker discovery and identification by mass spectrometry.

Native peptides and proteins are of increasing interest in biomedical research because they hold promise to represent a large number of useful diagnostic and therapeutic biomarkers. Discovery attempts from patient samples have to deal with the complexity of biology from a disease perspective as well as with a high individual variability. High throughput screening of samples is therefore the strategy of choice to detect relevant peptidic biomarkers, and requires a high order of automation particularly in the detection process. In this contribution, a novel technical approach employing a fully automated MALDI-TOF/TOF mass spectrometer is described. This approach combines high throughput biomarker discovery with the identification of corresponding endogenous peptides in one instrument and from the same set of samples. The degree of automation allows the analysis of thousands of chromatographic fractions corresponding to up to one hundred patient samples per day. The applied relative quantification via Differential Peptide Display((R)) is performed in a label-free way and shows a dynamic range of up to four orders of magnitude in the accessible peptide concentrations. The typical limit of detection is in the mid- to low-picomolar range for body fluids such as blood plasma, urine and cerebrospinal fluid. Sequence assignment via MALDI-TOF/TOF mass spectrometry is carried out either in an overview approach, characterizing rapidly the peptide composition e.g. of a novel sample, or in a directed approach, analyzing a list of biomarker candidates deduced from statistically significant abundance differences from the biomarker discovery process.

The concept of functional peptidomics for the discovery of bioactive peptides in cell culture models.

Detection and purification of novel bioactive peptides from biological sources is a scientific task that led to a substantial number of important discoveries. One major laborious approach used is the repetitive stepwise separation of the test sample into several fractions followed by the determination of their bioactivity, until purity allows for sequence identification. We tested whether functional peptidomics, a combination of biological read-outs with differential peptide display (DPD) is a suitable strategy to isolate bioactive peptides at lower workload and with improved success. Additionally, we evaluated the use of DPD to monitor the processing status of proinsulin by inhibition of the insulin processing pathway. The rat insulinoma cell line INS-1 stimulated either with 2 mmol/l or 10 mmol/l glucose was used as model to generate differential peptide displays. In parallel, the bioactivity of the supernatants from the INS-1 cells was measured by glucose uptake and lipolysis assays using the adipocyte cell line 3T3-L1. We were able to quickly and elegantly trace the known activity of insulin to increase glucose uptake and inhibit lipolysis. Following re-chromatography of selected fractions, relevant peptides were identified by DPD and bioassays: the rat insulin-1 precursor and two different insulin peptides. We demonstrated in a semi-quantitative fashion that inhibition of proinsulin processing leads to accumulation of the insulin precursor, and reduced secretion of insulin-1. Thus, we conclude that DPD is an attractive support technology in peptide purification strategies aiming to identify bioactive compounds, and is superior to ELISA in discriminating between the processing status of insulin and its precursor.