Reliability of human serum protein profiles generated with C8 magnetic beads assisted MALDI-TOF mass spectrometry

Next-generation pathology practices with mass spectrometry imaging

Mass spectrometry imaging (MSI) is a powerful technique that reveals the spatial distribution of various molecules in biological samples, and it is widely used in pathology-related research. In this review, we summarize common MSI techniques, including matrix-assisted laser desorption/ionization and desorption electrospray ionization MSI, and their applications in pathological research, including disease diagnosis, microbiology, and drug discovery. We also describe the improvements of MSI, focusing on the accumulation of imaging data sets, expansion of chemical coverage, and identification of biological significant molecules, that have prompted the evolution of MSI to meet the requirements of pathology practices. Overall, this review details the applications and improvements of MSI techniques, demonstrating the potential of integrating MSI techniques into next-generation pathology practices.

Screening Clones for Monoclonal Antibody Production Using Droplet Microfluidics Interfaced to Electrospray Ionization Mass Spectrometry

As one of the most critical steps in process development for protein therapeutics, clone selection and cell culture optimization require a large number of samples to be screened for high titer and desirable molecular profiles. Typical analytical techniques, such as chromatographic approaches, often take minutes per sample which are inefficient for large-scale screenings. Droplet microfluidics coupled to mass spectrometry (MS) represents an attractive approach due to its low volume requirements, high-throughput capabilities, label-free nature, and ability to handle complex mixtures. In this work, we coupled a modified protein cleanup protocol with a droplet-MS workflow for mAb titer screening to guide clone selection. With this droplet approach we achieved a throughput of 0.04 samples/s with an LoD of 0.15 mg/mL and an LoQ of 0.45 mg/mL. To test its performance in a real-world setting, this workflow was applied to a 35-clone screen, where the top 20% producing clones were identified. In addition, we coupled our sample cleanup protocol to a high-resolution MS and compared the glycan profiles of the high titer clones. This work demonstrates that droplet-MS provides a rapid way of clone screening and cell culture optimization based on titer and molecular structure of the expressed proteins. Future work is aimed at increasing the throughput and automation of this droplet-MS technique.

Systematic evaluation of repeatability of IR-MALDESI-MS and normalization strategies for correcting the analytical variation and improving image quality

Mass spectrometry imaging is a powerful tool widely used in biological, clinical, and forensic research, but its often poor repeatability limits its application for quantitative and large-scale analysis. A systematic evaluation of infrared matrix-assisted laser desorption electrospray ionization mass spectrometry (IR-MALDESI-MS) repeatability in absolute ion abundances during short- and long-term experiments was carried out on liver slices from the same rat with minimal biological variability to be expected. Results of median %RSDs ranging from 14 to 45, pooled %RMADs ranging from 11 to 33, and Pearson correlation coefficients ranging from 0.83 to 1.00 demonstrated an acceptable repeatability of IR-MALDESI-MS. Normalization is commonly applied for the purpose of accounting for analytical variability of spectra generated from different runs so as to reveal real biological differences. Nine data normalization strategies were performed on the rat liver data sets to examine their effects on reducing analytical variation, and further on a hen ovary data set containing more morphological features for the investigation of their impact on ion images. Results demonstrated that the majority of normalization approaches benefit data quality to some extent, and local normalization methods significantly outperform their global counterparts, resulting in a reduction of median %RSD up to 22. Local median normalization was found to be promisingly robust for both homogeneous and heterogeneous samples.

Evaluation of human breastmilk adulteration by combining Fourier transform infrared spectroscopy and partial least square modeling

A two-step chemometric procedure was developed on the attenuated total reflection-Fourier transform infrared data of human breastmilk to detect adulteration by water or cow milk. The samples, collected from a Milk Bank, were analyzed before and after adulteration with whole, skimmed, semi-skimmed cow milk and water. A preliminary clustering via principal component analysis distinguished three classes: pure milk, milk adulterated with water, and milk adulterated with cow milk. A first partial least square-discriminant analysis (PLS-DA) classification model was built and then applied on new samples to identify the specific adulterants. The external validation on this model reached 100% of the correct identification of pure milk and 90% of the type of adulterants. In the following step, four PLS calibration models were built to quantify the amount of the adulterant detected in the classification analysis. The prediction performance of these models on new samples showed satisfactory parameters with root mean square error of prediction and percentage relative error lower than 1.38% and 3.31%, respectively.

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.

Preparation of phenyl-functionalized magnetic mesoporous silica microspheres for the fast separation and selective enrichment of phenyl-containing peptides

Peptide enrichment before mass spectrometry analysis is essential for large-scale peptidomic studies, but challenges still remain. Herein, magnetic mesoporous silica microspheres with phenyl group modified interior pore walls were prepared by a facile sol-gel coating strategy, and were successfully applied for selective enrichment of phenyl-containing peptides in complex biological samples. The newly prepared nanomaterials possessed abundant silanol groups in the exterior surface and numerous phenyl groups in the interior pore walls, as well as a large surface area (592.6 m² /g), large pore volume (0.33 cm³ /g), uniform mesopores (3.8 nm), strong magnetic response (29.3 emu/g), and good dispersibility in aqueous solution. As a result of the unique structural properties and size-exclusion effect, the core-shell phenyl-functionalized magnetic mesoporous silica microspheres exhibited excellent performance in fast separation and selective enrichment of phenyl-containing peptides, and the adsorption capacity for bradykinin reached 22.55 mg/g. In addition, selective enrichment of phenyl-containing peptides from complex samples that are consist of peptides, large proteins, and human serum were achieved by using the as-prepared microspheres, followed by high-performance liquid chromatography with ultraviolet detection and electrospray ionization quadrupole time-of-flight mass spectrometry analysis. These results demonstrated the as-prepared microspheres would be a potential candidate for endogenous phenyl-containing peptides enrichment and biomarkers discovery in peptidome analysis.

Direct-S: a directed mass spectrometry method for biomarker verification in native serum

Serum has been the logical choice and most-used bio-specimen for monitoring biomarkers. However, direct analysis of low-abundance biomarkers in serum is still a problem. Here, we have established a directed mass spectrometry (inclusion list driven MS) method, Direct-S, for direct quantification of protein biomarkers in native serum samples without high-abundance protein depletion or pre-fractionation. In Direct-S, an (18)O-labeling technique was used to produce internal standards of the targeted peptides, and only targeted peptides were selected for tandem mass spectrometry (MS/MS) fragmentation to increase sensitivity and efficiency. The (16)O/(18)O ion pairs of target peptides and the elution time/fragmental pattern of the internal standards were used to facilitate the identification of the low-abundance peptides. Using Direct-S, three candidate biomarkers, α1-antitrypsin (A1AT), galectin-3 binding protein (LG3BP) and cathepsin D (CTSD), which represent different abundance levels, were quantified in serum samples of colorectal cancer (CRC) patients and healthy candidates. Direct-S exhibited good linearity of response from 20 fmol to 0.5 nmol (r > 0.9845). Reliable quantification across five orders of magnitude and as low as 71 pg μL(-1) was achieved in serum samples. In conclusion, Direct-S is a low cost, convenient and accurate method for verifying serum biomarkers.

Antibody microarray profiling of osteosarcoma cell serum for identifying potential biomarkers

The aim of the present study was to identify biomarkers in osteosarcoma (OS) cell serum by antibody microarray profiling, which may be used for OS diagnosis and therapy. An antibody microarray was used to detect the expression levels of cytokines in serum samples from 20 patients with OS and 20 healthy individuals. Significantly expressed cytokines in OS serum were selected when P<0.05 and fold change >2. An enzyme-linked immunosorbent assay (ELISA) was used to validate the antibody microarray results. Finally, classification accuracy was calculated by cluster analysis. Twenty one cytokines were significantly upregulated in OS cell serum samples compared with control samples. Expression of interleukin-6, monocyte chemoattractant protein-1, tumor growth factor-β, growth-related oncogene, hepatocyte growth factor, chemokine ligand 16, Endoglin, matrix metalloproteinase-9 and platelet-derived growth factor-AA was validated by ELISAs. OS serum samples and control samples were distinguished by significantly expressed cytokines with an accuracy of 95%. The results demonstrated that expressed cytokines identified by antibody microarray may be used as biomarkers for OS diagnosis and therapy.

Solid-phase extraction strategies to surmount body fluid sample complexity in high-throughput mass spectrometry-based proteomics

For large-scale and standardized applications in mass spectrometry- (MS-) based proteomics automation of each step is essential. Here we present high-throughput sample preparation solutions for balancing the speed of current MS-acquisitions and the time needed for analytical workup of body fluids. The discussed workflows reduce body fluid sample complexity and apply for both bottom-up proteomics experiments and top-down protein characterization approaches. Various sample preparation methods that involve solid-phase extraction (SPE) including affinity enrichment strategies have been automated. Obtained peptide and protein fractions can be mass analyzed by direct infusion into an electrospray ionization (ESI) source or by means of matrix-assisted laser desorption ionization (MALDI) without further need of time-consuming liquid chromatography (LC) separations.

Detection of pancreatic cancer using serum protein profiling

BACKGROUND

Currently, no suitable biomarkers for the early detection of pancreatic cancer (PC) are available. Proteins present in the serum could reflect a state of the disease. In this study, these profiles as a diagnostic marker for PC were evaluated.

METHODS

Serum samples were obtained from PC patients (n = 50 calibration set, n = 39 validation set) and healthy volunteers (n = 110 and n = 75 respectively) according to a uniform standardized collection and processing protocol. For peptide and protein isolation, automated solid-phase extraction (SPE) with Weak Cation Exchange (WCX) magnetic beads (MB) was performed using a 96-channel liquid handling platform. Protein profiles were obtained by mass spectrometry (MS) and evaluated by linear discriminant analysis with double cross-validation.

RESULTS

A discriminating profile for PC has been identified, with a sensitivity of 78% and a specificity of 89% in the calibration set with an area under the curve (AUC) of 90%. These results were validated with a sensitivity of 74% and a specificity of 91% (AUC 90%).

CONCLUSION

Serum profiles of healthy controls and PC can be discrimated between. Further research is warranted to evaluate specificity and whether this biosignature can be used for early detection in a high risk population.

Microchip emitter for solid-phase extraction-gradient elution-mass spectrometry

A microchip electrospray emitter with a magnetic bead trap has been designed for solid-phase extraction-gradient elution-mass spectrometry (SPE-GEMS). The goal of this method is the detection of analytes at low concentrations and it is here demonstrated using reverse phase coated magnetic beads (Mbs) for the preconcentration and detection of the peptides. The sample is passed through the chip, and the peptides are retained and enriched in the trap. After washing, the peptides are released sequentially by stepwise gradient elution and electrosprayed for mass spectrometry analysis. This approach allows effective sample desalting, enrichment, sequential elution, and MS detection without the introduction of an additional separation step after SPE. Efficient preconcentration of model peptides by SPE and sequential release and analysis of peptides by GEMS were demonstrated for diluted sample solutions within the range of 1 μM to 10 nM. Fortified human blood serum, protein digest and fractions collected after protein digest OFFGEL separation were analyzed by SPE-GEMS allowing the detection of low abundance peptides usually not observed by direct mass spectrometry analysis. A mathematical model for gradient elution is proposed.

Mapping O-glycosylation of apolipoprotein C-III in MALDI-FT-ICR protein profiles

Ultrahigh resolution MALDI-FT-ICR profiles were obtained from human serum samples that were processed using a fully automated RPC18-based magnetic bead method. Proteins were profiled from m/z value 6630 with a resolving power of 73 000 up to m/z value 12 600 with a resolving power of 37 000. In this study, a detailed evaluation was performed of the isoforms of apolipoprotein C-III, i.e. the different mucin-type core 1 O-glycans with the addition of one or two sialic acid residues. The MALDI-FT-ICR profiles are discussed with regard to reproducibility of the signal intensities as well as the accurate mass measurements. ESI-FT-ICR-MS/MS analyses of the same serum samples were performed to confirm the identity of apolipoprotein C-III glycoforms.

An automated plasma protein fractionation design: high-throughput perspectives for proteomic analysis

Background

Human plasma, representing the most complete record of the individual phenotype, is an appealing sample for proteomics analysis in clinical applications. Up to today, the major obstacle in a proteomics study of plasma is the large dynamic range of protein concentration and the efforts of many researchers focused on the resolution of this important drawback.

Findings

In this study, proteins from pooled plasma samples were fractionated according to their chemical characteristics on a home-designed SPE automated platform. The resulting fractions were digested and further resolved by reversed-phase liquid chromatography coupled with MALDI TOF/TOF mass spectrometry. A total of 712 proteins were successfully identified until a concentration level of ng/mL. Pearson correlation coefficient was used to test reproducibility.

Conclusions

Our multidimensional fractionation approach reduced the analysis time (2 days are enough to process 16 plasma samples filling a 96-well plate) over the conventional gel-electrophoresis or multi-LC column based methods. The robotic processing, avoiding contaminants or lack of sample handling skill, promises highly reproducible specimen analyses (more than 85% Pearson correlation). The automated platform here presented is flexible and easily modulated changing fractioning elements or detectors.

The proteomics big challenge for biomarkers and new drug-targets discovery

In the modern process of drug discovery, clinical, functional and chemical proteomics can converge and integrate synergies. Functional proteomics explores and elucidates the components of pathways and their interactions which, when deregulated, lead to a disease condition. This knowledge allows the design of strategies to target multiple pathways with combinations of pathway-specific drugs, which might increase chances of success and reduce the occurrence of drug resistance. Chemical proteomics, by analyzing the drug interactome, strongly contributes to accelerate the process of new druggable targets discovery. In the research area of clinical proteomics, proteome and peptidome mass spectrometry-profiling of human bodily fluid (plasma, serum, urine and so on), as well as of tissue and of cells, represents a promising tool for novel biomarker and eventually new druggable targets discovery. In the present review we provide a survey of current strategies of functional, chemical and clinical proteomics. Major issues will be presented for proteomic technologies used for the discovery of biomarkers for early disease diagnosis and identification of new drug targets.

Diagnostic biomarkers differentiating metastatic melanoma patients from healthy controls identified by an integrated MALDI-TOF mass spectrometry/bioinformatic approach

The prognosis of advanced metastatic melanoma (American Joint Committee on Cancer (AJCC) stage IV) remains dismal with a 5-year survival rate of 6-18%. In the present study, an integrated MALDI mass spectrometric approach combined with artificial neural networks (ANNs) analysis and modeling has been used for the identification of biomarker ions in serum from stage IV melanoma patients allowing the discrimination of metastatic disease from healthy status with high specificities of 92% for protein ions and 100% for peptide biomarkers. Our ANNs model also correctly classified 98% of a blind validation set of AJCC stage I melanoma samples as nonstage IV samples, emphasizing the power of the newly defined biomarkers to identify patients with late-stage metastatic melanoma. Sequence analysis identified peptides derived from metastasis-associated proteins; alpha 1-acid glycoprotein precursor-1/2 (AAG-1/2) and complement C3 component precursor-1 (CCCP-1). Furthermore, quantitation of serum AAG by an immunoassay showed a significant (p<0.001) increase in AAG serum concentration in stage IV patients in comparison with healthy volunteers; moreover; the quantity of AAG plotted against MALDI-MS peak intensity classified the groups into two distinct clusters. Ongoing studies of other disease stages will provide evidence whether our strategy is sufficiently robust to give rise to stage-specific protein/peptide signatures in melanoma.

Improved classification of breast cancer peptide and protein profiles by combining two serum workup procedures

Purpose

Detection of breast cancer at early stage increases patient’s survival. Mass spectrometry-based protein analysis of serum samples is a promising approach to obtain biomarker profiles for early detection. A combination of commonly applied solid-phase extraction procedures for clean-up may increase the number of detectable peptides and proteins. In this study, we have evaluated whether the classification performance of breast cancer profiles improves by using two serum workup procedures.

Methods

Serum samples from 105 breast cancer patients and 202 healthy volunteers were processed according to a standardized protocol implemented on a high-end liquid-handling robot. Peptide and protein enrichments were carried out using weak-cation exchange (WCX) and reversed-phase (RP) C18 magnetic beads. Profiles were acquired on a matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometer. In this way, two different biomarker profiles were obtained for each serum sample, yielding a WCX- and RPC18-dataset.

Results

The profiles were statistically evaluated with double cross-validation. Classification results of WCX- and RPC18-datasets were determined for each set separately and for the combination of both sets. Sensitivity and specificity were 82 and 87 % (WCX) and 73 and 93 % (RPC18) for the individual workup procedures. These values increased up to 84 and 95 %, respectively, upon combining the data.

Conclusion

It was found that MALDI-TOF peptide and protein profiles can be used for classification of breast cancer with high sensitivity and specificity. The classification performance even improved when two workup procedures were applied, since these provide a greater number of features (proteins).

Electronic supplementary material

The online version of this article (doi:10.1007/s00432-012-1273-4) contains supplementary material, which is available to authorized users.

Serum profiling by MALDI-TOF mass spectrometry as a diagnostic tool for domoic acid toxicosis in California sea lions

BACKGROUND

There are currently no reliable markers of acute domoic acid toxicosis (DAT) for California sea lions. We investigated whether patterns of serum peptides could diagnose acute DAT. Serum peptides were analyzed by MALDI-TOF mass spectrometry from 107 sea lions (acute DAT n = 34; non-DAT n = 73). Artificial neural networks (ANN) were trained using MALDI-TOF data. Individual peaks and neural networks were qualified using an independent test set (n = 20).

RESULTS

No single peak was a good classifier of acute DAT, and ANN models were the best predictors of acute DAT. Performance measures for a single median ANN were: sensitivity, 100%; specificity, 60%; positive predictive value, 71%; negative predictive value, 100%. When 101 ANNs were combined and allowed to vote for the outcome, the performance measures were: sensitivity, 30%; specificity, 100%; positive predictive value, 100%; negative predictive value, 59%.

CONCLUSIONS

These results suggest that MALDI-TOF peptide profiling and neural networks can perform either as a highly sensitive (100% negative predictive value) or a highly specific (100% positive predictive value) diagnostic tool for acute DAT. This also suggests that machine learning directed by populations of predictive models offer the ability to modulate the predictive effort into a specific type of error.

Quantitative statistical analysis of standard and human blood proteins from liquid chromatography, electrospray ionization, and tandem mass spectrometry

It will be important to determine if the parent and fragment ion intensity results of liquid chromatography, electrospray ionization and tandem mass spectrometry (LC-ESI-MS/MS) experiments have been randomly and independently sampled from a normal population for the purpose of statistical analysis by general linear models and ANOVA. The tryptic parent peptide and fragment ion m/z and intensity data in the mascot generic files from LC-ESI-MS/MS of purified standard proteins, and human blood protein fractionated by partition chromatography, were parsed into a Structured Query Language (SQL) database and were matched with protein and peptide sequences provided by the X!TANDEM algorithm. The many parent and/or fragment ion intensity values were log transformed, tested for normality, and analyzed using the generic Statistical Analysis System (SAS). Transformation of both parent and fragment intensity values by logarithmic functions yielded intensity distributions that closely approximate the log-normal distribution. ANOVA models of the transformed parent and fragment intensity values showed significant effects of treatments, proteins, and peptides, as well as parent versus fragment ion types, with a low probability of false positive results. Transformed parent and fragment intensity values were compared over all sample treatments, proteins or peptides by the Tukey-Kramer Honestly Significant Difference (HSD) test. The approach provided a complete and quantitative statistical analysis of LC-ESI-MS/MS data from human blood.

Reproducibility of mass spectrometry based protein profiles for diagnosis of ovarian cancer across clinical studies: A systematic review

The focus of this systematic review is to give an overview of the current status of clinical protein profiling studies using MALDI and SELDI MS platforms in the search for ovarian cancer biomarkers. A total of 34 profiling studies were qualified for inclusion in the review. Comparative analysis of published discriminatory peaks to peaks found in an original MALDI MS protein profiling study was made to address the key question of reproducibility across studies. An overlap was found despite substantial heterogeneity between studies relating to study design, biological material, pre-analytical treatment, and data analysis. About 47% of the peaks reported to be associated to ovarian cancer were also represented in our experimental study, and 34% of these redetected peaks also showed a significant difference between cases and controls in our study. Thus, despite known problems related to reproducibility an overlap in peaks between clinical studies was demonstrated, which indicate convergence toward a set of common discriminating, reproducible peaks for ovarian cancer. The potential of the discriminating protein peaks for clinical use as ovarian cancer biomarkers will be discussed and evaluated. This article is part of a Special Issue entitled: Proteomics: The clinical link.

Mass spectrometry of peptides and proteins from human blood

It is difficult to convey the accelerating rate and growing importance of mass spectrometry applications to human blood proteins and peptides. Mass spectrometry can rapidly detect and identify the ionizable peptides from the proteins in a simple mixture and reveal many of their post-translational modifications. However, blood is a complex mixture that may contain many proteins first expressed in cells and tissues. The complete analysis of blood proteins is a daunting task that will rely on a wide range of disciplines from physics, chemistry, biochemistry, genetics, electromagnetic instrumentation, mathematics and computation. Therefore the comprehensive discovery and analysis of blood proteins will rank among the great technical challenges and require the cumulative sum of many of mankind's scientific achievements together. A variety of methods have been used to fractionate, analyze and identify proteins from blood, each yielding a small piece of the whole and throwing the great size of the task into sharp relief. The approaches attempted to date clearly indicate that enumerating the proteins and peptides of blood can be accomplished. There is no doubt that the mass spectrometry of blood will be crucial to the discovery and analysis of proteins, enzyme activities, and post-translational processes that underlay the mechanisms of disease. At present both discovery and quantification of proteins from blood are commonly reaching sensitivities of ∼1 ng/mL.

MALDI-MS and multivariate analysis for the detection and quantification of different milk species

The extensive consumption of milk and dairy products makes these foodstuffs targets for potential adulteration with financial gains for unscrupulous producers. Such practices must be detected as these can impact negatively on product quality, labelling and even health. Matrix-assisted laser desorption/ionisation time-of-flight mass spectrometry (MALDI-ToF-MS) is a potentially useful technique, with proven abilities in protein identification and more recently through the use of internal standards for quantification purposes of specific proteins or peptides. In the current work, we therefore aim to explore the accuracy and attributes of MALDI-ToF-MS with chemometrics for the detection and quantification of milk adulteration. Three binary mixtures containing cows' and goats', cows' and sheep's, and goats' and sheep's milk and a fourth tertiary mixture containing all types of milk were prepared and analysed directly using MALDI-ToF-MS. In these mixtures, the milk concentrations of each milk varied from 0% to 100% in 5% steps. Multivariate statistical methods including partial least squares (PLS) regression and non-linear Kernel PLS regression were employed for multivariate calibration and final interpretation of the results. The results for PLS and KPLS were encouraging with between 2% and 13% root mean squared error of prediction on independent data; KPLS slightly outperformed PLS. We believe that these results show that MALDI-ToF-MS has excellent potential for future use in the dairy industry as a rapid method of detection and enumeration in milk adulteration.

MALDI-TOF serum profiling using semiautomated serum peptide capture with magnetic reversed phase (C18) beads

Mass spectrometry can be used to generate diagnostic peptide peak profiles "signatures" of serum samples. Peak profiles can be used to compare different sera and correlate samples (i.e., patient groups) with clinical data to assist in diagnosis, monitoring, and/or prediction. We describe the semiautomated capture of serum peptides/small proteins with magnetic beads that harbor C18 alkyl chains, the deposition of captured material on a target plate for MALDI-TOF mass spectrometry, as well as, general guidelines for data acquisition. We also include, in a separate note, a short manual version of the capture procedure. Overall, the serum sample processing protocol, reported here, is reproducible and robust. In conjunction with MALDI-TOF mass spectrometry, this protocol allows for the profiling of several hundreds of serum peptides.

Proteomic serum biomarkers and their potential application in cancer screening programs

Early diagnosis of cancer is of pivotal importance to reduce disease-related mortality. There is great need for non-invasive screening methods, yet current screening protocols have limited sensitivity and specificity. The use of serum biomarkers to discriminate cancer patients from healthy persons might be a tool to improve screening programs. Mass spectrometry based proteomics is widely applied as a technology for mapping and identifying peptides and proteins in body fluids. One commonly used approach in proteomics is peptide and protein profiling. Here, we present an overview of profiling methods that have the potential for implementation in a clinical setting and in national screening programs.

Quality control based on isotopic distributions for high-throughput MALDI-TOF and MALDI-FTICR serum peptide profiling

In this study, we have implemented a new quality control (QC) parameter for peptide profiling based on isotopic distributions. This QC parameter is an objective measure and facilitates automatic sorting of large numbers of peptide spectra. Peptides in human serum samples were enriched using reversed-phase C(18)-functionalized magnetic beads using a high-throughput robotic platform. High-resolution MALDI-TOF and ultrahigh resolution MALDI-FTICR mass spectra were obtained and a workflow was developed for automated analysis and evaluation of these profiles. To this end, the isotopic distributions of multiple peptides were quantified from both MALDI-TOF and MALDI-FTICR spectra. Odd peptide isotope distributions in TOF spectra could be rationalized from ultrahigh resolution FTICR spectra that showed overlap of different peptides. The comparison of isotope patterns with estimated polyaveragine distributions was used to calculate a QC value for each single mass spectrum. Sorting these QC values enabled the best MALDI spectrum to be selected from replicate spots. Moreover, using this approach spectra containing high intensities of polymers or other contaminants and lacking peptides of interest can be efficiently removed from a clinical dataset. In general, this method simplifies the exclusion of low quality spectra from further statistical analysis.

A new approach to determine camptothecin and its analogues affinity to human serum albumin

A novel and fast method for the determination of the binding kinetic data of ligand to protein has been developed. A new tool including human serum albumin-coated magnetic beads (HSA-MB) was used to determine the affinity of camptothecin (CPT) and its analogues to HSA. From the biological activity point of view, these compounds have potential anticancer activity. However, the numerous studies indicate that some of these analogues have a strong affinity to plasma proteins stopping their effective therapy. Thus, the problem of plasma protein binding behavior of CPT's analogues was the subject of this study.

Standardized preprocessing of urine for proteome analysis

Proteome/peptidome profiling of human urine is a promising tool for the discovery of novel disease-associated biomarkers. However, a wide range of preanalytic variables influence the results of proteome/peptidome analysis regardless of the method used. We present a validated pretreatment protocol, which allows standardization of preanalytic modalities and facilitates reproducible peptidome profiling of human urine by means of magnetic bead (MB) separation in combination with MALDI-TOF MS. Such a procedure is necessary for generating consistent and reliable data from which meaningful results may be obtained for biomarker discovery and general proteomic experiments.

Optimal preparation methods for automated matrix-assisted laser desorption/ionization time-of-flight mass spectrometry profiling of low molecular weight proteins and peptides

Mass spectrometry (MS) profiling of the proteome and peptidome for disease-associated patterns is a new concept in clinical diagnostics. The technique, however, is highly sensitive to external sources of variation leading to potentially unacceptable numbers of false positive and false negative results. Before MS profiling can be confidently implemented in a medical setting, standard experimental methods must be developed that minimize technical variance. Past studies of variance have focused largely on pre-analytical variation (i.e., sample collection, handling, etc.). Here, we examined how factors at the analytical stage including the matrix and solid-phase extraction influence MS profiling. Firstly, a standard peptide/protein sample was measured automatically by matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) MS across five consecutive days using two different preparation methods, dried droplet and sample/matrix, of four types of matrix: alpha-cyano-4-hydroxycinnamic acid (HCCA), sinapinic acid (SA), 2,5-dihydroxybenzoic acid (DHB) and 2,5-dihydroxyacetophenone (DHAP). The results indicated that the matrix preparation greatly influenced a number of key parameters of the spectra including repeatability (within-day variability), reproducibility (inter-day variability), resolution, signal strength, background intensity and detectability. Secondly, an investigation into the variance associated with C8 magnetic bead extraction of the standard sample prior to automated MS profiling demonstrated that the process did not adversely affect these same parameters. In fact, the spectra were generally more robust following extraction. Thirdly, the best performing matrix preparations were evaluated using C8 magnetic bead extracted human plasma. We conclude that the DHAP prepared according to the dried-droplet method is the most appropriate matrix to use when performing automated MS profiling.

Progressive degradation of serum samples limits proteomic biomarker discovery

Preanalytical variables play a key role in discovery of biomarkers. Although the effect of several preanalytical variables on the mass spectral profiles has been studied extensively, little is known about long-term storage of serum samples. This is important because samples used in case-control or epidemiological studies are usually stored for a long time before analysis. Here we evaluated long-term storage effects on mass spectral peak patterns of serum peptides extracted using weak cation exchange magnetic beads. For this, 20 serum samples stored at -80 degrees C were divided equally into two groups based on their storage time. We found that intensities of 26 mass spectral peaks significantly varied between these two groups. Intensities of these peaks significantly correlated with storage time. Genetic algorithm-based models generated using these 26 peaks could classify 63 additional samples into these two groups with 100% and 96% accuracy, respectively. We also show that storing samples for 10 months at -80 and -20 degrees C results in the appearance/disappearance or intensity variation of peaks, some of which were previously reported as disease biomarkers.