Analysis of human serum by liquid chromatography–mass spectrometry: Improved sample preparation and data analysis

Design and synthesis of a TICT-based red-emissive fluorescent probe for the rapid and selective detection of HSA in human biofluids and live cell imaging

Here, we report the design and synthesis of a D⋯π⋯A-based fluorescent probe, (E)-4-(4-(dibutylamine)-2-hydroxystyryl)-1-methylquinolin-1-ium (DHMQ), which is nonfluorescent in ∼100% PBS buffer medium due to a twisted intra molecular charge transfer (TICT) phenomenon and it becomes highly fluorescent (∼149 fold) in the presence of human serum albumin (HSA), owing to the restriction of its intramolecular free rotation inside the hydrophobic binding cavity of HSA. The site-selective fluorescence displacement assay and molecular docking studies clearly reveal that DHMQ selectively binds at subdomain IB of HSA. The 3σ/slope method was adopted to determine the limit of detection (LOD) value, which was as low as 2.39 nM in ∼100% PBS medium, indicating its high sensitivity towards HSA. The low dissociation constant value [Kd = (1.066 ± 0.017) μM] suggests a strong complexation between the DHMQ and HSA. Importantly, it has been demonstrated that DHMQ is capable of detecting HSA in real human serum and urine samples and was found to be suitable for live cell imaging of HSA.

Pd@Pt nanoparticle-linked immunosorbent assay for quantification of Collagen type II

The evaluation of specific protein content in engineered tissues provides a gateway for developing regenerative medicine treatments. Since collagen type II, the major component of articular cartilage, is critical for the blossoming field of articular cartilage tissue engineering, the interest in this protein is growing rapidly. Accordingly, the need for quantification of collagen type II is increasing as well. In this study, we provide recent results for a new quantifying nanoparticle sandwich immunoassay technique for collagen type II. Since mesoporous palladium@platinum (Pd@Pt) nanoparticles have peroxidase-like catalytic activities, these nanoparticles were utilized in an enzyme-linked immunosorbent assay (ELISA)-like format to circumvent the need for traditional enzymes. These nanoparticles were easily conjugated with anti-collagen type II antibodies by the natural affinity interaction and used to develop a direct sandwich ELISA-like format for nanoparticle-linked immunosorbent assays. Using this method, we obtained a limit of detection of 1 ng mL-1, a limit of quantification of 9 ng mL-1. and a broad linear range between 1 ng mL-1 and 50 μg mL-1 for collagen type II with an average relative standard deviation of 5.5%, useable over a pH range of 7 - 9 at least. The assay was successfully applied to quantify collagen type II in cartilage tissues and compared with the results of commercial ELISAs and gene expression by reverse transcription-quantitative polymerase chain reaction. This method provides a thermally stable and cost-efficient alternative to traditional ELISAs. It also extends the application of nanoparticle-linked immunosorbent assays, thereby providing the potential to quantify other proteins and apply the technology in the medical, environmental, and biotechnology industry fields.

A general procedure for rounding m/z values in low-resolution mass spectra

It was revealed that nominal mass spectra extracted from the same NetCDF file using different gas chromatography/mass spectrometry (GC/MS) software products are not identical. This phenomenon is caused by differences in algorithms used for rounding floating-point m/z values to integers. It was found that all programs under consideration (AMDIS, ChemStation, ChromaTOF, MS Search, OpenChrom) use different procedures. It is necessary to know how fractional parts of accurate m/z values of ions are distributed to determine which algorithm yields more robust results. We estimated the respective distribution using two databases (PubChem and NIST). As a result, we came up with a procedure that minimizes the influence of random errors on rounding to integer m/z values. The procedure we suggest is to sum intensities of all floating-point m/z values in a bin [MZ - 0.38; MZ + 0.62] and assign MZ as a nominal m/z value, where MZ is an integer m/z value.

A novel target and biomarker benzothiazolyl-naphthalimide probes for precisely and selective detection of serum albumin and anticancer activity

N-Benzothiazolyl-1,8-naphthalimide based fluorescence probes were designed and synthesized for selective detection of human serum albumin (HSA) and Bovine serum albumin (BSA) among various bioanalytes and further studied for their in...

Molecular markers for cervical cancer screening

INTRODUCTION

Cervical cancer remains a significant healthcare problem, notably in low- to middle-income countries. While a negative test for hrHPV has a predictive value of more than 99.5%, its positive predictive value is less than 10% for CIN2+ stages. This makes the use of a so-called triage test indispensable for population-based screening to avoid referring women, that are ultimately at low risk of developing cervical cancer, to a gynecologist. This review will give an overview of tests that are based on epigenetic marker panels and protein markers.

AREAS COVERED

There is a medical need for molecular markers with a better predictive value to discriminate hrHPV-positive women that are at risk of developing cervical cancer from those that are not. Areas covered are epigenetic and protein markers as well as health economic considerations in view of the fact that most cases of cervical cancer arise in low-to-middle-income countries.

EXPERT OPINION

While there are biomarker assays based on changes at the nucleic acid (DNA methylation patterns, miRNAs) and at the protein level, they are not widely used in population screening. Combining nucleic acid-based and protein-based tests could improve the overall specificity for discriminating CIN2+ lesions that carry a low risk of progressing to cervical cancer within the screening interval from those that carry an elevated risk. The challenge is to reduce unnecessary referrals without an undesired increase in false-negative diagnoses resulting in cases of cervical cancer that could have been prevented. A further challenge is to develop tests for low-and middle-income countries, which is critical to reduce the worldwide burden of cervical cancer.

Nanodiamond for Sample Preparation in Proteomics

Protein analysis of potential disease markers in blood is complicated by the fact that proteins in plasma show very different abundances. As a result, high-abundance proteins dominate the analysis, which often render the analysis of low-abundance proteins impossible. Depleting high-abundance proteins is one strategy to solve this problem. Here, we present, for the first time, a very simple approach based on selective binding of serum proteins to the surface of nanodiamonds. In our first proof-of-principle experiments, we were able to detect, on average, eight proteins that are present at a concentration of 1 ng/mL (instead of 0.5 ng/mL in the control without sample preparation). Remarkably, we detect proteins down to a concentration of 400 pg/mL after only one simple depletion step. Among the proteins we could analyze are also numerous disease biomarkers, including markers for multiple cancer forms, cardiovascular diseases, or Alzheimer's disease. Remarkably, many of the biomarkers we find also could not be detected with a state-of-the-art ultrahigh-performance liquid chromatography column (which depletes the 64 most-abundant serum proteins).

A Routine 'Top-Down' Approach to Analysis of the Human Serum Proteome

Serum provides a rich source of potential biomarker proteoforms. One of the major obstacles in analysing serum proteomes is detecting lower abundance proteins owing to the presence of hyper-abundant species (e.g., serum albumin and immunoglobulins). Although depletion methods have been used to address this, these can lead to the concomitant removal of non-targeted protein species, and thus raise issues of specificity, reproducibility, and the capacity for meaningful quantitative analyses. Altering the native stoichiometry of the proteome components may thus yield a more complex series of issues than dealing directly with the inherent complexity of the sample. Hence, here we targeted method refinements so as to ensure optimum resolution of serum proteomes via a top down two-dimensional gel electrophoresis (2DE) approach that enables the routine assessment of proteoforms and is fully compatible with subsequent mass spectrometric analyses. Testing included various fractionation and non-fractionation approaches. The data show that resolving 500 µg protein on 17 cm 3–10 non-linear immobilised pH gradient strips in the first dimension followed by second dimension resolution on 7–20% gradient gels with a combination of lithium dodecyl sulfate (LDS) and sodium dodecyl sulfate (SDS) detergents markedly improves the resolution and detection of proteoforms in serum. In addition, well established third dimension electrophoretic separations in combination with deep imaging further contributed to the best available resolution, detection, and thus quantitative top-down analysis of serum proteomes.

Preparation and characterization of a packed bead immobilized trypsin reactor integrated into a PDMS microfluidic chip for rapid protein digestion

This paper demonstrates the design, efficiency and applicability of a simple, inexpensive and high sample throughput microchip immobilized enzymatic reactor (IMER) for rapid protein digestion. The IMER contains conventional silica particles with covalently immobilized trypsin packed inside of a poly(dimethylsiloxane) (PDMS) microchip channel (10mm×1mm×35µm). The microchip consists of 9 different channels, enabling 9 simultaneous protein digestions. Trypsin was covalently immobilized using carbodiimide activation, the ideal trypsin/silica particle ratio (i.e. measured mass ratio before the immobilization reaction) was determined. The amount of immobilized trypsin was 10-15μg trypsin for 1mg silica particle. Migration times of CZE peptide maps showed good repeatability and reproducibility (RSD%=0.02-0.31%). The IMER maintained its activity for 2 months, in this period it was used effectively for rapid proteolysis. Four proteins (myoglobin, lysozyme, hemoglobin and albumin) in a wide size range (15-70kDa) were digested to demonstrate the applicability of the reactor. Their CZE peptide maps were compared to peptide maps obtained from standard in-solution digestion of the four proteins. The number of peptide peaks correlated well with the theoretically expected peptide number in both cases, the peak patterns of the electropherograms were similar, however, digestion with the microchip IMER requires only <10s, while in-solution digestion takes 16h. LC-MS/MS peptide mapping was also carried out, the four proteins were identified with satisfying sequence coverages (29-50%), trypsin autolysis peptides were not detected. The protein content of human serum was digested with the IMER and with in-solution digestion.

Identification of Analytical Factors Affecting Complex Proteomics Profiles Acquired in a Factorial Design Study with Analysis of Variance: Simultaneous Component Analysis

Complex shotgun proteomics peptide profiles obtained in quantitative differential protein expression studies, such as in biomarker discovery, may be affected by multiple experimental factors. These preanalytical factors may affect the measured protein abundances which in turn influence the outcome of the associated statistical analysis and validation. It is therefore important to determine which factors influence the abundance of peptides in a complex proteomics experiment and to identify those peptides that are most influenced by these factors. In the current study we analyzed depleted human serum samples to evaluate experimental factors that may influence the resulting peptide profile such as the residence time in the autosampler at 4 °C, stopping or not stopping the trypsin digestion with acid, the type of blood collection tube, different hemolysis levels, differences in clotting times, the number of freeze-thaw cycles, and different trypsin/protein ratios. To this end we used a two-level fractional factorial design of resolution IV (2(IV)(7-3)). The design required analysis of 16 samples in which the main effects were not confounded by two-factor interactions. Data preprocessing using the Threshold Avoiding Proteomics Pipeline (Suits, F.; Hoekman, B.; Rosenling, T.; Bischoff, R.; Horvatovich, P. Anal. Chem. 2011, 83, 7786-7794, ref 1) produced a data-matrix containing quantitative information on 2,559 peaks. The intensity of the peaks was log-transformed, and peaks having intensities of a low t-test significance (p-value > 0.05) and a low absolute fold ratio (<2) between the two levels of each factor were removed. The remaining peaks were subjected to analysis of variance (ANOVA)-simultaneous component analysis (ASCA). Permutation tests were used to identify which of the preanalytical factors influenced the abundance of the measured peptides most significantly. The most important preanalytical factors affecting peptide intensity were (1) the hemolysis level, (2) stopping trypsin digestion with acid, and (3) the trypsin/protein ratio. This provides guidelines for the experimentalist to keep the ratio of trypsin/protein constant and to control the trypsin reaction by stopping it with acid at an accurately set pH. The hemolysis level cannot be controlled tightly as it depends on the status of a patient's blood (e.g., red blood cells are more fragile in patients undergoing chemotherapy) and the care with which blood was sampled (e.g., by avoiding shear stress). However, its level can be determined with a simple UV spectrophotometric measurement and samples with extreme levels or the peaks affected by hemolysis can be discarded from further analysis. The loadings of the ASCA model led to peptide peaks that were most affected by a given factor, for example, to hemoglobin-derived peptides in the case of the hemolysis level. Peak intensity differences for these peptides were assessed by means of extracted ion chromatograms confirming the results of the ASCA model.

Sample preparation strategies for targeted proteomics via proteotypic peptides in human blood using liquid chromatography tandem mass spectrometry

The simultaneous quantification of protein concentrations via proteotypic peptides in human blood by liquid chromatography coupled to quadrupole MS/MS is an important field of bioanalytical research with a high potential for routine diagnostic applications. This review summarizes currently available sample preparation procedures and trends for absolute protein quantification in blood using LC-MS/MS. It discusses approaches of transferring established qualitative protocols to a quantitative analysis regarding their reliability and reproducibility. Techniques used to enhance method sensitivity such as the depletion of high-abundant proteins or the immunoaffinity enrichment of proteins and peptides are described. Furthermore, workflows for (i) protein denaturation, (ii) disulfide bridge reduction and (iii) thiol alkylation as well as (iv) enzymatic digestion for absolute protein quantification are presented. The main focus is on the tryptic digestion as a bottleneck of protein quantification via proteotypic peptides. Conclusively, requirements for a high-throughput application are discussed.

A panel of regulated proteins in serum from patients with cervical intraepithelial neoplasia and cervical cancer

We developed a discovery-validation mass-spectrometry-based pipeline to identify a set of proteins that are regulated in serum of patients with cervical intraepithelial neoplasia (CIN) and squamous cell cervical cancer using iTRAQ, label-free shotgun, and targeted mass-spectrometric quantification. In the discovery stage we used a "pooling" strategy for the comparative analysis of immunodepleted serum and revealed 15 up- and 26 down-regulated proteins in patients with early- (CES) and late-stage (CLS) cervical cancer. The analysis of nondepleted serum samples from patients with CIN, CES, an CLS and healthy controls showed significant changes in abundance of alpha-1-acid glycoprotein 1, alpha-1-antitrypsin, serotransferrin, haptoglobin, alpha-2-HS-glycoprotein, and vitamin D-binding protein. We validated our findings using a fast UHPLC/MRM method in an independent set of serum samples from patients with cervical cancer or CIN and healthy controls as well as serum samples from patients with ovarian cancer (more than 400 samples in total). The panel of six proteins showed 67% sensitivity and 88% specificity for discrimination of patients with CIN from healthy controls, a stage of the disease where current protein-based biomarkers, for example, squamous cell carcinoma antigen (SCCA), fail to show any discrimination. Additionally, combining the six-protein panel with SCCA improves the discrimination of patients with CES and CLS from healthy controls.

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.

Biological and methodical challenges of blood-based proteomics in the field of neurological research

Biomarker discovery is an application of major importance in today's proteomic research. There is an urgent need for suitable biomarkers to improve diagnostic tools and treatment in various neurological diseases, such as neurodegenerative disorders. Recent years have witnessed an enormous interest in proteomics, which is currently seen as an invaluable tool to shed more light on complex interacting signalling pathways and molecular networks involved in several neuropathological conditions. However, while first results of proteomic research studies have sparked much public attention, the momentum of further proteomic biomarker research in neurological disorders may suffer by its very complex methodology which is sensitive to various sources of artefacts. A major source of variability is proteome perturbation caused by sample handling/preservation (preanalytical phase) and processing/measurement (analytical phase). The aim of the present review is to summarize the current literature focusing on the crucial role played by preanalytical and analytical factors that affect the quality of samples and the reliability of the data produced in blood-based proteomic biomarker research in neurology, which may apply to Alzheimer's disease (AD) as well as other neurological disorders. Procedures for sample preparation and protocols for the analysis of serum and plasma samples will be delineated. Finally, the potential usefulness of bioinformatics--allowing for the assembly, store, and processing of data--as well as its contribution to the execution of proteomic studies will be critically discussed.

Selective enrichment and sensitive detection of peptide and protein biomarkers in human serum using polymeric reverse micelles and MALDI-MS

Reverse-micelle forming amphiphilic homopolymers with carboxylic acid and quaternary amine substituents are used to selectively enrich biomarker peptides and protein fragments from human serum prior to matrix assisted laser desorption/ionization mass spectrometry (MALDI-MS) analysis. After depletion of human serum albumin (HSA) and immunoglobulin G (IgG), low abundance peptide biomarkers can be selectively enriched and detected by MALDI-MS at clinically relevant concentrations by using the appropriate homopolymer(s) and extraction pH value(s). Three breast cancer peptide biomarkers, bradykinin, C4a, and ITIH(4), were chosen to test this new approach, and detection limits of 0.5 ng mL(-1), 0.08 ng mL(-1), and 0.2 ng mL(-1), respectively, were obtained. In addition, the amphiphilic homopolymers were used to detect prostate specific antigen (PSA) at concentrations as low as 0.5 ng mL(-1) by targeting a surrogate peptide fragment of this protein biomarker. Selective enrichment and sensitive MS detection of low abundance peptide/protein biomarkers by these polymeric reverse micelles should be a sensitive and straightforward approach for biomarker screening in human serum.

"The quest for biomarkers": are we on the right technical track?

The discovery phase of biomarkers of diagnostic or therapeutic interest started a decade ago with the very rapid development of proteomic investigations. In spite of the development of innovative technologies and multiple approaches, the "harvest" is still modest. Various reasons justified the encountered difficulties and most of them have been circumvented by specific sample treatments or dedicated analytical approaches. Nevertheless, the situation of very modest biomarker discovery level did not change much. This review intends to specifically analyze the main approaches used for biomarker discovery phase and evaluate related advantages and disadvantages. Thus, preliminary sample treatments such as fractionation, depletion and reduction of dynamic concentration range will critically be discussed and then the main differential expression investigation methods analyzed. Combinations of technologies are also discussed along with possible proposals to federate associations of complementary technologies for better chances of success.

Setup for human sera MALDI profiling: the case of rhEPO treatment

The implementation of high-throughput technologies based on qualitative and quantitative methodologies for the characterization of complex protein mixtures is increasingly required in clinical laboratories. MALDI profiling is a robust and sensitive technology although the serum high dynamic range imposes a major limitation hampering the identification of less abundant species decreasing the quality of MALDI profiling. A setup to improve these parameters has been performed for recombinant human erythropoietin (rhEPO) monitoring in serum, analyzing the effects of two commercially available columns (MARS Hu7 and Hu14) for immunodepletion, and two matrices (α-cyano-4-hydroxycinnamic acid and 2',4'-dihydroxyacetophenone) for peak quality improvement. The immunodepletion capability of both columns was determined by 2-D DIGE, which precisely revealed the efficacy of Hu14 in protein removal and the serum dynamic range decrement. In addition, the type of matrix, the sample dilution, and the efficacy of optimized parameters were used for serum profiling of ten healthy subjects before and after rhEPO treatment. The principal component analysis indicates that a combination of Hu14 column and 2',4'-dihydroxyacetophenone matrix increases data quality allowing the discrimination between treated and untreated samples, making serum MALDI profiling suitable for clinical monitoring of rhEPO.

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.

State of the art in tumor antigen and biomarker discovery

Our knowledge of tumor immunology has resulted in multiple approaches for the treatment of cancer. However, a gap between research of new tumors markers and development of immunotherapy has been established and very few markers exist that can be used for treatment. The challenge is now to discover new targets for active and passive immunotherapy. This review aims at describing recent advances in biomarkers and tumor antigen discovery in terms of antigen nature and localization, and is highlighting the most recent approaches used for their discovery including “omics” technology.

Evaluation of three high abundance protein depletion kits for umbilical cord serum proteomics

Background

High abundance protein depletion is a major challenge in the study of serum/plasma proteomics. Prior to this study, most commercially available kits for depletion of highly abundant proteins had only been tested and evaluated in adult serum/plasma, while the depletion efficiency on umbilical cord serum/plasma had not been clarified. Structural differences between some adult and fetal proteins (such as albumin) make it likely that depletion approaches for adult and umbilical cord serum/plasma will be variable. Therefore, the primary purposes of the present study are to investigate the efficiencies of several commonly-used commercial kits during high abundance protein depletion from umbilical cord serum and to determine which kit yields the most effective and reproducible results for further proteomics research on umbilical cord serum.

Results

The immunoaffinity based kits (PROTIA-Sigma and 5185-Agilent) displayed higher depletion efficiency than the immobilized dye based kit (PROTBA-Sigma) in umbilical cord serum samples. Both the PROTIA-Sigma and 5185-Agilent kit maintained high depletion efficiency when used three consecutive times. Depletion by the PROTIA-Sigma Kit improved 2DE gel quality by reducing smeared bands produced by the presence of high abundance proteins and increasing the intensity of other protein spots. During image analysis using the identical detection parameters, 411 ± 18 spots were detected in crude serum gels, while 757 ± 43 spots were detected in depleted serum gels. Eight spots unique to depleted serum gels were identified by MALDI- TOF/TOF MS, seven of which were low abundance proteins.

Conclusions

The immunoaffinity based kits exceeded the immobilized dye based kit in high abundance protein depletion of umbilical cord serum samples and dramatically improved 2DE gel quality for detection of trace biomarkers.

Biomarker discovery in biological specimens (plasma, hair, liver and kidney) of diabetic mice based upon metabolite profiling using ultra-performance liquid chromatography with electrospray ionization time-of-flight mass spectrometry

BACKGROUND

The number of diabetic patients has recently been increasing worldwide. Diabetes is a multifactorial disorder based on environmental factors and genetic background. In many cases, diabetes is asymptomatic for a long period and the patient is not aware of the disease. Therefore, the potential biomarker(s), leading to the early detection and/or prevention of diabetes mellitus, are strongly required. However, the diagnosis of the prediabetic state in humans is a very difficult issue, because the lifestyle is variable in each person. Although the development of a diagnosis method in humans is the goal of our research, the extraction and structural identification of biomarker candidates in several biological specimens (i.e., plasma, hair, liver and kidney) of ddY strain mice, which undergo naturally occurring diabetes along with aging, were carried out based upon a metabolite profiling study.

METHODS

The low-molecular-mass compounds including metabolites in the biological specimens of diabetic mice (ddY-H) and normal mice (ddY-L) were globally separated by ultra-performance liquid chromatography (UPLC) using different reversed-phase columns (i.e., T3-C18 and HS-F5) and detected by electrospray ionization time-of-flight mass spectrometry (ESI-TOF-MS). The biomarker candidates related to diabetes mellitus were extracted from a multivariate statistical analysis, such as an orthogonal partial least-squares-discriminant analysis (OPLS-DA), followed by a database search, such as ChemSpider, KEGG and HMDB.

RESULTS

Many metabolites and unknown compounds in each biological specimen were detected as the biomarker candidates related to diabetic mellitus. Among them, the elucidation of the chemical structures of several possible metabolites, including more than two biological specimens, was carried out along with the comparison of the tandem MS/MS analyses using authentic compounds. One metabolite was clearly identified as N-acetyl-L-leucine based upon the MS/MS spectra and the retention time on the chromatograms.

CONCLUSIONS

N-acetyl-L-leucine is an endogenous compound included in all biological specimens (plasma, hair, liver and kidney). Therefore, this metabolite appears to be a potential biomarker candidate related to diabetes. Although the structures of other biomarker candidates have still not yet determined, the present approach based upon a metabolite profiling study using UPLC-ESI-TOF-MS could be helpful for understanding the abnormal state of various diseases.

Practical analytical approach for the identification of biomarker candidates in prediabetic state based upon metabonomic study by ultraperformance liquid chromatography coupled to electrospray ionization time-of-flight mass spectrometry

The number of diabetic patients has recently been increasing worldwide. Thus, the discovery of potential diabetic biomarker(s), leading to the early detection and/or prevention of diabetes mellitus, is strongly required. The diagnosis of the prediabetic state in humans is a very difficult issue because of the lifestyle differences in each person and ethical consideration. Upon the basis of these considerations, animal experiments using ddY strain mice (ddY-H), which undergo naturally occurring diabetes along with age, were carried out in this study. Biomarker discovery based upon a metabonome study is now quite common, the same as that in the proteome analysis. Reversed-phase liquid chromatography-mass spectrometry (LC-MS) has mainly been used for the extensive analysis of low-molecular mass compounds including metabolites. The metabolites in the plasma of diabetic mice (ddY-H) and normal mice (ddY-L) were exhaustively separated and detected by ultraperformance liquid chromatography along with electrospray ionization time-of-flight mass spectrometry (UPLC-ESI-TOF-MS) using T3-C18 and HS-F5 columns. The biomarker candidates related to diabetes mellitus were extracted from the metabolite profiling of ddY-H and ddY-L at 5, 9 13, and 20 weeks old using a multivariate statistical analysis such as orthogonal partial least-squares-discriminant analysis (OPLS-DA). Various metabolites and unknown compounds were detected as biomarker candidates related to diabetic mellitus. Furthermore, the concentration of several metabolites on Lysine biosynthesis and Lysine degradation pathways were remarkably changed between the 9-week old ddY-H and ddY-L mice. Because a couple of biomarker candidates related to the prediabetic state were identified using the present approach, the metabolite profiling study could be helpful for understanding the abnormal state of various diseases.

High-abundance proteins depletion for serum proteomic analysis: concomitant removal of non-targeted proteins

In clinical and pharmaceutical proteomics, serum and plasma are frequently used for detection of early diagnostic biomarkers for therapeutic targets. Although obtaining these body fluid samples is non-invasive and easy, they contain some abundant proteins that mask other protein components present at low concentrations. The challenge in identifying serum biomarkers is to remove the abundant proteins, uncovering and enriching at the same time the low-abundance ones. The depletion strategies, however, could lead to the concomitant removal of some non-targeted proteins that may be of potential interest. In this study, we compared three different methods aimed to deplete high-abundance proteins from human serum, focusing on the identification of non-specifically bound proteins which might be eventually removed. A Cibacron blue-dye-based method for albumin removal, an albumin and IgG immunodepletion method and an immunoaffinity column (Multiple Affinity Removal System) that simultaneously removes a total of six high-abundance proteins, were investigated. The bound proteins were eluted, separated by two-dimensional gel electrophoresis and identified by Nano LC-CHIP-MS system. Flow-through fractions and bound fractions were also analysed with the ProteinChip technology SELDI-TOF-MS. Our results showed that the methods tested removed not only the targeted proteins with high efficiency, but also some non-targeted proteins. We found that the Multiple Affinity Removal Column improved the intensity of low-abundance proteins, displayed new protein spots and increased resolution. Notably, the column showed the lowest removal of untargeted proteins, proved to be the most promising depletion approach and a reliable method for serum preparation prior to proteomic studies.

Detecting low-abundance vasoactive peptides in plasma: progress toward absolute quantitation using nano liquid chromatography-mass spectrometry

Profiling changes in the concentration of functionally related peptide hormones is critical to understanding the etiology of many diseases and therapies. We present novel data using nano liquid chromatography-mass spectrometry (LC-MS) to simultaneously measure a select group of vasoactive peptides (angiotensin, bradykinin, and related hormones) in 50-microl plasma samples, enabling repeated sampling in rodent models. By chromatographically resolving target peptides and using multiple reaction monitoring to enhance MS sensitivity, linear responses down to 10(-17) mol were achieved. Purification of plasma peptides by either methanol precipitation or off-line high-performance liquid chromatography (HPLC) fractionation enabled the detection of endogenous peptides and revealed approaches for enhancing recovery. As proof of principle, seven vasoactive peptides were profiled before, during, and after acute angiotensin-converting enzyme (ACE) inhibition in an anesthetized rat. Of note was an apparent 10-fold increase in vasodilatory bradykinin that reversed after drug infusion but relatively minor changes in angiotensin II levels. Targeted MS analysis used to profile functionally related peptides or other analytes will greatly enhance our ability to define the sequence of events regulating complex and dynamic physiological processes.

Bioanalysis of recombinant proteins and antibodies by mass spectrometry

In recent years, biotechnologically-derived drugs have been a major focus of research and development in the pharmaceutical industry. Their pharmacokinetics and pharmacokinetic/pharmacodynamic relationships impact every stage of the development process and require their assessment in the circulation in preclinical species and in humans. To this end, immunoassays are a reference, but standardisation remains an issue owing to the restricted pattern of antibody specificity and interference with endogenous components. As an alternative, we report here analytical strategies involving liquid chromatography coupled to mass spectrometry (LC-MS) for the accurate quantification of therapeutic proteins and antibodies in biological fluids.

Optimization of SELDI-TOF protein profiling for analysis of cervical mucous

Cervical mucous, produced in the region where cervical neoplasia occurs, is thought to be a good choice for discovery of biomarkers to improve cervical cancer screening. In this study, SELDI-TOF MS analysis was used to evaluate parameters for protein profiling of mucous. Proteins were extracted from mucous collected with Weck-Cel sponges. Several parameters like extraction reagent, loading protein concentration, matrix type, bind/wash conditions and sample fractionation, on different protein chip surfaces were evaluated. SELDI peak number and consistency in the resulting spectra were used to evaluate each condition. Analysis of spectra generated by different protein chips revealed an average of 30 peaks in the 2.5-30 kDa mass range using sinnapinic acid in the unfractionated sample. Sample concentration and buffer conditions evaluated did not lead to large alterations in the profiles. Quality control spectra were reproducible with intra- and inter-assay intensity CV for CM10, H50 and Q10 arrays being less than 20% and 30% respectively. IMAC30-Cu chips had higher intra- and inter-assay CV's at 25% and 35%. Current data showed that optimizing pre-analytical parameters can help in standardization and reproducibility of protein profiles produced by cervical mucous, and thus can be used for protein biomarker discovery with the SELDI platform.

Matrix-assisted laser desorption/ionisation mass spectrometry imaging of lipids in rat brain tissue with integrated unsupervised and supervised multivariant statistical analysis

To date matrix-assisted laser desorption/ionisation mass spectrometry imaging (MALDI-MSI) analysis has been largely concerned with mapping the distribution of known analytes in tissues. An important step in the progression of its applications is the determination of unknown variants for metabolite and protein profiling in both clinical studies and studies of disease. Principal component analysis (PCA) is a statistical approach which can be used as a means of determining latent variables in multivariate data sets. In the work reported here, PCA, in both unsupervised and supervised modes, has been used to differentiate brain regions based on their lipid composition determined by MALDI-MSI. PCA has been shown to be useful in the determination of hidden variables between spectra taken from six regions of brain tissue. It is possible to identify ions of interest from the loadings plot which are likely to be more prominent in the different regions of the brain and thus differentiating between white and grey matter. It is also possible to distinguish between the grey Cerebellar Cortex and the Hippocampal formation, due to the grey Cerebellar Cortex having a positive PC2 and the Hippocampal formation having a negative PC2 score; this is only possible in supervised PCA with this data set because with unsupervised PCA the two regions overlap.

Label-free proteomics of serum

In this chapter we describe a method to analyze human serum with the goal of discovering disease-related changes in the serum proteome. The methodology is based on the removal of the six most abundant serum proteins by immunoaffinity chromatography. This step is followed by trypsin digestion and reversed-phase high-performance liquid chromatography (HPLC) coupled on-line to mass spectrometry (MS) using either a capillary HPLC or a microfluidics chip HPLC system. The obtained, highly complex data sets are processed and statistically analyzed to discover significant differences between groups of samples. The complete analytical procedure will be described with serum samples, to which a given amount of horse heart cytochrome c has been added as well as with serum samples from early stage cervical cancer patients prior to and after therapy. The use of reversed-phase HPLC to separate serum proteins at 80 degrees C with subsequent analysis by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) in order to lower the concentration sensitivity will also be briefly described.

Metabolic profiling of rat hair and screening biomarkers using ultra performance liquid chromatography with electrospray ionization time-of-flight mass spectrometry

An exhaustive analysis of metabolites in hair samples has been performed for the first time using ultra performance liquid chromatography with electrospray ionization time-of-flight mass spectrometry (UPLC-ESI-TOF-MS). The hair samples were collected from spontaneously hypertensive model rats (SHR/Izm), stroke-prone SHR (SHRSP/Izm) and Wistar Kyoto (WKY/Izm) rats, and were analyzed by UPLC-ESI-TOF-MS; a multivariate statistical analysis method, such as the principal component analysis (PCA), was then used for screening the biomarkers. From the samples derived from the group of SHRSP/Izm at weeks 10, 18, 26 and 34, we successfully detected a potential biomarker of stroke, which existed at much higher concentrations as compared with that in the other groups. However, a significant difference could not be found at weeks less than 7 before the rats were subjected to stroke and hypertension. In addition, the present method was applicable to screening not only the disease markers, but also the markers related to aging. The method utilizing hair samples is expected to be quite useful for screening biomarkers of many other diseases, and not limited to stroke and hypertension.

Sedimentation field flow fractionation of immunoglobulin A coated polystyrene beads

The amount of immunoglobulin A (IgA) adsorbed on the surface of two different samples of polystyrene (PS) microbeads was evaluated using differential sedimentation field flow fractionation (SdFFF) analyses. For the first time, the SdFFF separations obtained by using, as mobile phase, solutions common to many biochemical procedures and applications have been compared and discussed. Good separation results were achieved in the different carriers, and the SdFFF gave equivalent mass per particle values in all carriers provided that the pH and ionic strength conditions of the eluents were well controlled. The IgA adsorption process onto PS occurred by maintaining unaltered the capacity of the PS-IgA substrate to selectively recognize anti-IgA (aIgA), as proven by elution of the ternary complex PS-IgA-aIgA and from the monitored lack of reaction when the PS-IgA was placed in contact with aIgE.

HPLC-chip-mass spectrometry for protein signature identifications

This work investigates the use of an HPLC-chip microfluidic device interfaced to an IT mass spectrometer to search for biomarker signatures. To that end, the identification of autoantigens is chosen as a model. It not only constitutes a proof of concept model but also the growing interest in autoantibodies and autoantigens as new markers of diseases provides a practical application at the same time. The peptides are separated by the HPLC-chip system allowing suitable resolution and reproducibility. The determination of two parameters that characterize a peptide sequence during LC-MS/MS analyses, retention time (RT) and m/z ratio, improves the identification of a number of peptides derived from protein digests. These findings illustrate that accurate RT measurement obtained in a microfluidic device is useful to obtain mass/retention time (MRT) pairs for a given peptide, which can contribute to the definition of biomarker signatures.

Chemometric analysis of complex hyphenated data

Component detection algorithm (CODA) is a method to quickly extract the high-quality mass chromatograms from complex liquid chromatography/electrospray ionization mass spectrometry (LC/MS) data sets, saving operators hours of analysis time. It appeared, however, that mass chromatograms with a limited baseline problem were ignored. This paper describes several methods to increase the tolerance for mass chromatograms with a baseline.

Sample preparation for serum/plasma profiling and biomarker identification by mass spectrometry

In this article, we present an overview of the different strategies for sample preparation for identification by mass spectrometry (MS) of biomarkers from serum and/or plasma. We consider the effects of the variables involved in sample collection, handling and storage, and describe different approaches for removal of high abundance proteins and serum/plasma fractionation. We review the advantages and disadvantages of such techniques as centrifugal ultrafiltration, different formats for solid phase extraction, organic solvent extraction, gel and capillary electrophoresis, and liquid chromatography. We also discuss a variety of current proteomic methods and their main applications for biomarker-related studies.

Clinical validation of an immunoaffinity LC-MS/MS assay for the quantification of a collagen type II neoepitope peptide: A biomarker of matrix metalloproteinase activity and osteoarthritis in human urine

The degradation of type II collagen has been associated with the pathology of osteoarthritis (OA). Matrix metalloproteinases (MMPs) are enzymes that are responsible for catalyzing the degradation of collagen and, therefore, are pursued as potential targets for the treatment of OA. Collagen-derived peptides identified as a reflection of in vivo MMP activity have been investigated as target biomarkers of MMP activity as well as potential biomarkers of OA disease state and/or progression. An immunoaffinity liquid chromatography-tandem mass spectrometry (LC-MS/MS) assay developed for the quantification of the most abundant urinary type II collagen neoepitope (uTIINE) peptide, a 45-mer with 5 HO-proline residues resulting from MMP-13-catalyzed degradation, was validated for clinical use. Validation experiments were designed with attention to specific challenges related to quantification of endogenous analytes. The validated method is sensitive, selective, accurate (<15% relative error) and precise (<15% coefficient of variation) over a linear range of 0.156-7.50 ng/ml. Sample stability and inter- and intrasubject variability were evaluated in the urine of normal and OA populations. The method was applied to analyze human urine samples from clinical studies investigating the utility of uTIINE as a potential biomarker for OA.

Methods for samples preparation in proteomic research

Sample preparation is one of the most crucial processes in proteomics research. The results of the experiment depend on the condition of the starting material. Therefore, the proper experimental model and careful sample preparation is vital to obtain significant and trustworthy results, particularly in comparative proteomics, where we are usually looking for minor differences between experimental-, and control samples. In this review we discuss problems associated with general strategies of samples preparation, and experimental demands for these processes.

Proteomics analysis in lung cancer: challenges and opportunities

Recent technological developments in proteomic analysis are bringing us new insights into the molecular classification of tumours. Although proteomic analysis in cancer profiling is still under development both in terms of the instruments used and the data analytical tools, this method has great potential advantages for the analysis of biospecimens of many types. Direct measurement of abnormally expressed or modified proteins in the tumour tissue and/or patient blood may be an effective approach for discovering new biomarkers. Proteomics has the significant advantage of being able to discern not only changes in expression levels but also in post-translational modifications. Thus, the proteomics approach to protein profiling and biomarker discovery uncovers biomarkers from a different viewpoint than microarray analysis. This review summarizes the range of proteomics technologies employed for cancer profiling, and how they have been used to derive new classification models for human lung cancer.

Nondigest liberation of biomarkers from plasma: A novel two-stage ultrafiltration approach

A simple procedure for sample preparation of human plasma by two stages of ultrafiltration using one device is described. Our approach is useful for nondigest liberation of biomarkers bound to albumin and other plasma proteins. The analyte contained in the ultrafiltrate can be directly analyzed without additional sample preparation, and quantified by 2-D RP-RP LC/MS.

The blood peptidome: a higher dimension of information content for cancer biomarker discovery

The low-molecular-weight range of the circulatory proteome is termed the 'peptidome', and could be a rich source of cancer-specific diagnostic information because it is a 'recording' of the cellular and extracellular enzymatic events that take place at the level of the cancer-tissue microenvironment. This new information archive seems to mainly exist in vivo, bound to high-abundance proteins such as albumin. Measuring panels of peptidome markers might be more sensitive and specific than conventional biomarker approaches. We discuss the advantages and disadvantages of various methods for studying the peptidome.