Evaluation of three principally different intact protein prefractionation methods for plasma biomarker discovery

Proteomics to study cancer immunity and improve treatment

Cancer survival and progression depend on the ability of tumor cells to avoid immune recognition. Advances in the understanding of cancer immunity and tumor immune escape mechanisms enabled the development of immunotherapeutic approaches. In patients with otherwise incurable metastatic cancers, immunotherapy resulted in unprecedented response rates with the potential for durable complete responses. However, primary and acquired resistance mechanisms limit the efficacy of immunotherapy. Further therapeutic advances require a deeper understanding of the interplay between immune cells and tumors. Most high-throughput studies within the past decade focused on an omics characterization at DNA and RNA level. However, proteins are the molecular effectors of genomic information; therefore, the study of proteins provides deeper understanding of cellular functions. Recent advances in mass spectrometry (MS)-based proteomics at a system-wide scale may allow translational and clinical discoveries by enabling the analysis of understudied post-translational modifications, subcellular protein localization, cell signaling, and protein-protein interactions. In this review, we discuss the potential contribution of MS-based proteomics to preclinical and clinical research findings in the context of tumor immunity and cancer immunotherapies.

Advancements in automation for plasma proteomics sample preparation

Automation is necessary to increase sample processing throughput for large-scale clinical analyses. Replacement of manual pipettes with robotic liquid handler systems is especially helpful in processing blood-based samples, such as plasma and serum. These samples are very heterogenous, and protein expression can vary greatly from sample-to-sample, even for healthy controls. Detection of true biological changes requires that variation from sample preparation steps and downstream analytical detection methods, such as mass spectrometry, remains low. In this mini-review, we discuss plasma proteomics protocols and the benefits of automation towards enabling detection of low abundant proteins and providing low sample error and increased sample throughput. This discussion includes considerations for automation of major sample depletion and/or enrichment strategies for plasma toward mass spectrometry detection.

LC-MS/MS-Based Serum Protein Profiling for Identification of Candidate Biomarkers in Pakistani Rheumatoid Arthritis Patients

Rheumatoid arthritis is an autoimmune disorder of complex disease etiology. Currently available serological diagnostic markers lack in terms of sensitivity and specificity and thus additional biomarkers are warranted for early disease diagnosis and management. We aimed to screen and compare serum proteome profiles of rheumatoid arthritis serotypes with healthy controls in the Pakistani population for identification of potential disease biomarkers. Serum samples from rheumatoid arthritis patients and healthy controls were enriched for low abundance proteins using ProteoMinerTM columns. Rheumatoid arthritis patients were assigned to one of the four serotypes based on anti-citrullinated peptide antibodies and rheumatoid factor. Serum protein profiles were analyzed via liquid chromatography-tandem mass spectrometry. The changes in the protein abundances were determined using label-free quantification software ProgenesisQITM followed by pathway analysis. Findings were validated in an independent cohort of patients and healthy controls using an enzyme-linked immunosorbent assay. A total of 213 proteins were identified. Comparative analysis of all groups (false discovery rate < 0.05, >2-fold change, and identified with ≥2 unique peptides) identified ten proteins that were differentially expressed between rheumatoid arthritis serotypes and healthy controls including pregnancy zone protein, selenoprotein P, C4b-binding protein beta chain, apolipoprotein M, N-acetylmuramoyl-L-alanine amidase, catalytic chain, oncoprotein-induced transcript 3 protein, Carboxypeptidase N subunit 2, Apolipoprotein C-I and Apolipoprotein C-III. Pathway analysis predicted inhibition of liver X receptor/retinoid X receptor activation pathway and production of nitric oxide and reactive oxygen species pathway in macrophages in all serotypes. A catalogue of potential serum biomarkers for rheumatoid arthritis were identified. These biomarkers can be further evaluated in larger cohorts from different populations for their diagnostic and prognostic potential.

Coordinating Effect of VEGFC and Oleic Acid Participates to Tumor Lymphangiogenesis

Simple Summary

In cancer, the lymphatic system is hijacked by tumor cells that escape from primary tumor and metastasize to the sentinel lymph nodes. Tumor lymphangiogenesis is stimulated by the vascular endothelial growth factors-C (VEGFC) after binding to its receptor VEGFR-3. However, how VEGFC cooperates with other molecules to promote lymphatic neovessel growth has not been fully determined. Here, we showed that tumor lymphangiogenesis developed in tumoral lesions and in their surrounding adipose tissue (AT). Interestingly, lymphatic vessel density correlated with an increase in circulating free fatty acids (FFA) in the lymph from tumor-bearing mice. We showed that adipocyte-released FFA are uploaded by lymphatic endothelial cells (LEC) to stimulate their sprouting. Lipidomic analysis identified the monounsaturated oleic acid (OA) as the major circulating FFA in the lymph in a tumoral context. OA transporters FATP-3, -6 and CD36 were only upregulated on LEC in the presence of VEGFC showing a collaborative effect of these molecules. OA released from adipocytes is taken up by LECs to stimulate the fatty acid β-oxidation, leading to increased adipose tissue lymphangiogenesis. Our results provide new insights on the dialogue between tumors and adipocytes via the lymphatic system and identify a key role for adipocyte-derived FFA in the promotion of lymphangiogenesis, revealing novel therapeutic opportunities for inhibitors of lymphangiogenesis in cancer.

Abstract

In cancer, the lymphatic system is hijacked by tumor cells that escape from primary tumor and metastasize to the sentinel lymph nodes. Tumor lymphangiogenesis is stimulated by the vascular endothelial growth factors-C (VEGFC) after binding to its receptor VEGFR-3. However, how VEGFC cooperates with other molecules to promote lymphatics growth has not been fully determined. We showed that lymphangiogenesis developed in tumoral lesions and in surrounding adipose tissue (AT). Interestingly, lymphatic vessel density correlated with an increase in circulating free fatty acids (FFA) in the lymph from tumor-bearing mice. We showed that adipocyte-released FFA are uploaded by lymphatic endothelial cells (LEC) to stimulate their sprouting. Lipidomic analysis identified the monounsaturated oleic acid (OA) as the major circulating FFA in the lymph in a tumoral context. OA transporters FATP-3, -6 and CD36 were only upregulated on LEC in the presence of VEGFC showing a collaborative effect of these molecules. OA stimulates fatty acid β-oxidation in LECs, leading to increased AT lymphangiogenesis. Our results provide new insights on the dialogue between tumors and adipocytes via the lymphatic system and identify a key role for adipocyte-derived FFA in the promotion of lymphangiogenesis, revealing novel therapeutic opportunities for inhibitors of lymphangiogenesis in cancer.

Proteomic analysis of pancreatic ductal adenocarcinoma

INTRODUCTION

Pancreatic ductal adenocarcinoma (PDAC), which represents approximately 80% of all pancreatic cancers, is a highly aggressive malignant disease and one of the most lethal among all cancers. Overall, the 5-year survival rate among all pancreatic cancer patients is less than 9%; these rates have shown little change over the past 30 years. A more comprehensive understanding of the molecular mechanisms underlying this complex disease is crucial to the development of new diagnostic tools for early detection and disease monitoring, as well as to identify new and more effective therapeutics to improve patient outcomes.

AREA COVERED

We summarize recent advances in proteomic strategies and mass spectrometry to identify new biomarkers for early detection and monitoring of disease progression, predict response to therapy, and to identify novel proteins that have the potential to be 'druggable' therapeutic targets. An overview of proteomic studies that have been conducted to further our mechanistic understanding of metastasis and chemotherapy resistance in PDAC disease progression will also be discussed.

EXPERT COMMENTARY

The results from these PDAC proteomic studies on a variety of PDAC sample types (e.g., blood, tissue, cell lines, exosomes, etc.) provide great promise of having a significant clinical impact and improving patient outcomes.

Top-Down Proteomics Applied to Human Cerebrospinal Fluid

Cerebrospinal fluid (CSF) is the fluid of choice to study pathologies and disorders of the central nervous system (CNS). Its composition, especially its proteins and peptides, holds the promise that it may reflect the pathological state of an individual. Traditionally, proteins and peptides in CSF have been analyzed using bottom-up proteomics technologies in the search of high proteome coverage. However, the limited protein sequence coverage of this technology means that information regarding post-translational modifications (PTMs) and alternative splice variants is lost. As an alternative technology, top-down proteomics offers low to medium proteome coverage, but high protein coverage enabling almost a full characterization of the proteins' primary structure. This allows us to precisely identify distinct molecular forms of proteins (proteoforms) as well as naturally occurring bioactive peptide fragments, which could be of critical biological relevance and would otherwise remain undetected with a classical proteomics approach.Here, we describe various strategies including sample preparation protocols, off-line intact protein prefractionation, and LC-MS/MS methods together with data analysis pipelines to analyze cerebrospinal fluid (CSF) by top-down proteomics. However, there is not a unique or standardized method and the selection of the top-down strategy will depend on the exact goal of the study. Here, we describe various top-down proteomics methods that enable rapid protein characterization and may be an excellent companion analytical workflow in the search for new protein biomarkers in neurodegenerative diseases.

Analysis of the plasma proteome using iTRAQ and TMT-based Isobaric labeling

Over the past decade, chemical labeling with isobaric tandem mass tags, such as isobaric tags for relative and absolute quantification reagents (iTRAQ) and tandem mass tag (TMT) reagents, has been employed in a wide range of different clinically orientated serum and plasma proteomics studies. In this review the scope of these works is presented with attention to the areas of research, methods employed and performance limitations. These applications have covered a wide range of diseases, disorders and infections, and have implemented a variety of different preparative and mass spectrometric approaches. In contrast to earlier works, which struggled to quantify more than a few hundred proteins, increasingly these studies have provided deeper insight into the plasma proteome extending the numbers of quantified proteins to over a thousand.

Differential protein expression profiles of cyst fluid from papillary thyroid carcinoma and benign thyroid lesions

Cystic papillary thyroid carcinoma (cPTC) is a subgroup of PTC presenting a diagnostic challenge at fine needle aspiration biopsy (FNAB). To further investigate this entity we aimed to characterize protein profiles of cyst fluids from cPTC and benign thyroid cystic lesions. In total, 20 cPTCs and 56 benign thyroid cystic lesions were studied. Profiling by liquid chromatography tandem mass spectrometry (LC-MS/MS) was performed on cyst fluids from a subset of cases after depletion, and selected proteins were further analyzed by Western blot (WB), immunohistochemistry (IHC) and enzyme-linked immunosorbent assay (ELISA). A total of 1,581 proteins were detected in cyst fluids, of which 841 were quantified in all samples using LC-MS/MS. Proteins with different expression levels between cPTCs and benign lesions were identified by univariate analysis (41 proteins) and multivariate analysis (59 proteins in an orthogonal partial least squares model). WB analyses of cyst fluid and IHC on corresponding tissue samples confirmed a significant up-regulation of cytokeratin 19 (CK-19/CYFRA 21-1) and S100A13 in cPTC vs. benign lesions. These findings were further confirmed by ELISA in an extended material of non-depleted cyst fluids from cPTCs (n = 17) and benign lesions (n = 55) (p<0.05). Applying a cut-off at >55 ng/ml for CK-19 resulted in 82% specificity and sensitivity. For S100A13 a cut-off at >230 pg/ml revealed a 94% sensitivity, but only 35% specificity. This is the first comprehensive catalogue of the protein content in fluid from thyroid cysts. The up-regulations of CK-19 and S100A13 suggest their possible use in FNAB based preoperative diagnostics of cystic thyroid lesions.

Mass spectrometry in cancer biomarker research: a case for immunodepletion of abundant blood-derived proteins from clinical tissue specimens

The discovery of clinically relevant cancer biomarkers using mass spectrometry (MS)-based proteomics has proven difficult, primarily because of the enormous dynamic range of blood-derived protein concentrations and the fact that the 22 most abundant blood-derived proteins constitute approximately 99% of the total plasma protein mass. Immunodepletion of clinical body fluid specimens (e.g., serum/plasma) for the removal of highly abundant proteins is a reasonable and reproducible solution. Often overlooked, clinical tissue specimens also contain a formidable amount of highly abundant blood-derived proteins present in tissue-embedded networks of blood/lymph capillaries and interstitial fluid. Hence, the dynamic range impediment to biomarker discovery remains a formidable obstacle, regardless of clinical sample type (solid tissue and/or body fluid). Thus, we optimized and applied simultaneous immunodepletion of blood-derived proteins from solid tissue and peripheral blood, using clear cell renal cell carcinoma as a model disease. Integrative analysis of data from this approach and genomic data obtained from the same type of tumor revealed concordant key pathways and protein targets germane to clear cell renal cell carcinoma. This includes the activation of the lipogenic pathway characterized by increased expression of adipophilin (PLIN2) along with 'cadherin switching', a phenomenon indicative of transcriptional reprogramming linked to renal epithelial dedifferentiation. We also applied immunodepletion of abundant blood-derived proteins to various tissue types (e.g., adipose tissue and breast tissue) showing unambiguously that the removal of abundant blood-derived proteins represents a powerful tool for the reproducible profiling of tissue proteomes. Herein, we show that the removal of abundant blood-derived proteins from solid tissue specimens is of equal importance to depletion of body fluids and recommend its routine use in the context of biological discovery and/or cancer biomarker research. Finally, this perspective presents the background, rationale and strategy for using tissue-directed high-resolution/accuracy MS-based shotgun proteomics to detect genuine tumor proteins in the peripheral blood of a patient diagnosed with nonmetastatic cancer, employing concurrent liquid chromatography-MS analysis of immunodepleted clinical tissue and blood specimens.

Significant increase of plasma tetranectin in ovx mice as defined by proteomics analysis

BACKGROUND

Proteomics is recognized as a useful tool in the dynamic screening of plasma protein expression. This study aimed to identify increased expressions of novel plasma proteins in ovariectomized mice (ovx) using selective reaction monitoring (SRM) validation in combination with electrospray ionized-quadrupole time-of-flight mass spectrometry (ESI-Q-TOF-MS) screening.

MATERIALS AND METHODS

Twenty-week-old female C57BL/6 mice were ovariectomized or subjected to surgical exposure of the ovaries alone (sham). Blood plasma protein at 4 weeks after these operations was pooled for the ovx and sham group each and separated on SDS-PAGE, and then digested by peptides, which were first differentially displayed by ESI-Q-TOF-MS analysis. Mass spectra of peptides upregulated more than twofold in ovx compared to sham mice were selected for protein identification by ESI-Q-TOF-MS. The selected peptides were further validated in independent samples by SRM using electrospray ionized-triple quadrupole-linear ion trap mass spectrometry (ESI-QqLIT-MS). Optimum transitions for SRM were manually chosen for their high specificity in identifying peptides derived from the candidate proteins.

RESULTS

Differential analysis of peptides revealed 1,108 upregulated peptides in ovx compared with sham control mice. Among the upregulated peptides, 231 nonredundant proteins were identified. Validation analysis for the potential use of these proteins as markers of bone turnover was performed using ESI-QqLIT-MS. The four proteins from the plasma samples, namely mannose-binding lectin-C, major urinary protein 2, type I collagen alpha 2 chain, and tetranectin, were evaluated in a blinded manner. A statistically significant elevation of all four proteins in the plasma of ovx mice was confirmed by SRM. Of the four upregulated plasma proteins, tetranectin increased by almost 50 times in the ovx mice compared with the sham mice.

CONCLUSIONS

On the basis of proteomics analysis, this study demonstrated that four plasma proteins were significantly elevated in the ovx mice; of these, tetranectin was markedly upregulated by almost 50 times compared with the sham mice.

Mass spectrometry-based plasma proteomics: state of the art and future outlook

Mass spectrometry-based plasma proteomics is a field where intense research has been performed during the last decade. Being closely linked to biomarker discovery, the field has received a fair amount of criticism, mostly due to the low number of novel biomarkers reaching the clinic. However, plasma proteomics is under gradual development with improvements on fractionation methods, mass spectrometry instrumentation and analytical approaches. These recent developments have contributed to the revival of plasma proteomics. The goal of this review is to summarize these advances, focusing in particular on fractionation methods, both for targeted and global mass spectrometry-based plasma analysis.

Interactomic approach for evaluating nucleophosmin-binding proteins as biomarkers for Ewing's sarcoma

Nucleophosmin (NPM) is a novel prognostic biomarker for Ewing's sarcoma. To evaluate the prognostic utility of NPM, we conducted an interactomic approach to characterize the NPM protein complex in Ewing's sarcoma cells. A gene suppression assay revealed that NPM promoted cell proliferation and the invasive properties of Ewing's sarcoma cells. FLAG-tag-based affinity purification coupled with liquid chromatography-tandem mass spectrometry identified 106 proteins in the NPM protein complex. The functional classification suggested that the NPM complex participates in critical biological events, including ribosome biogenesis, regulation of transcription and translation, and protein folding, that are mediated by these proteins. In addition to JAK1, a candidate prognostic biomarker for Ewing's sarcoma, the NPM complex, includes 11 proteins known as prognostic biomarkers for other malignancies. Meta-analysis of gene expression profiles of 32 patients with Ewing's sarcoma revealed that 6 of 106 were significantly and independently associated with survival period. These observations suggest a functional role as well as prognostic value of these NPM complex proteins in Ewing's sarcoma. Further, our study suggests the potential applications of interactomics in conjunction with meta-analysis for biomarker discovery.

MALDI-target integrated platform for affinity-captured protein digestion

To address immunocapture of proteins in large cohorts of clinical samples high throughput sample processing is required. Here a method using the proteomic sample platform, ISET (integrated selective enrichment target) that integrates highly specific immunoaffinity capture of protein biomarker, digestion and sample cleanup with a direct interface to mass spectrometry is presented. The robustness of the on-ISET protein digestion protocol was validated by MALDI MS analysis of model proteins, ranging from 40 fmol to 1 pmol per nanovial. On-ISET digestion and MALDI MS/MS analysis of immunoaffinity captured disease-associated biomarker PSA (prostate specific antigen) from human seminal plasma are presented.

A novel prefractionation method combining protein and peptide isoelectric focusing in immobilized pH gradient strips

To increase sensitivity and analytical depth in shotgun proteomics, prefractionation of complex samples is often used. Here we describe a novel prefractionation method, Sandwich high resolution isoelectric focusing, which combines both protein and peptide isoelectric focusing. In the first step, intact proteins are separated on the basis of isoelectric point (pI) using traditional immobilized pH gradient (IPG) strips. Segments in the IPG-strip containing proteins of interest are subsequently cut out and applied to in-strip digestion, without subsequent peptide elution. In the second peptide isoelectric focusing step, the strip segments are used as loading bridges. The peptides are thereby directly applied to the peptide isoelectric focusing, without an intermediate elution step, and separated on narrow range IPG strips to reduce the complexity on the peptide level. In the final step, the peptides are eluted into 96-well plates and analyzed with mass spectrometry. In a proof of principle experiment, using this method to zoom in on pI regions of interest in human plasma, we identify over 800 proteins, with concentrations spanning over 6 orders of magnitude.

Precursor ion exclusion for enhanced identification of plasma biomarkers

PURPOSE

Our study aims to establish a plasma biomarker analysis workflow, with fewer fractionation steps, for enhanced identification of plasma biomarkers by precursor ion exclusion (PIE).

EXPERIMENTAL DESIGN

Plasma samples were depleted for highly abundant proteins, then further fractionated by molecular weight (MW), before trypsinization for LTQ-Orbitrap mass analysis. Data-dependent acquisition (DDA) was used for baseline analysis. PIE involves the re-injection of samples with exclusion of the previously identified peptides. We compared analyses using multiple PIE iterations, compared to DDA, for plasma interrogation

RESULTS

A higher percentage of unique plasma peptides was identified with PIE, compared to DDA. The first PIE iteration reveals an increase of 75-112% more peptides than the DDA method alone. PIE can interrogate complex plasma samples with the percentage of peptides identified successively increasing with even ≥4 iterations. The total number of peptides identified increases rapidly across the first three PIE iterations and then continues more slowly up to nine iterations.

CONCLUSIONS AND CLINICAL RELEVANCE

Iterative injections with PIE resulted in many more peptide identifications in plasma samples of varying degrees of complexity, compared to re-injections using similar DDA parameters. PIE methods may therefore expand our ability to recover plasma peptides for plasma biomarker discovery.

Sample displacement chromatography as a method for purification of proteins and peptides from complex mixtures

Sample displacement chromatography (SDC) in reversed-phase and ion-exchange modes was introduced approximately twenty years ago. This method takes advantage of relative binding affinities of components in a sample mixture. During loading, there is a competition among different sample components for the sorption on the surface of the stationary phase. SDC was first used for the preparative purification of proteins. Later, it was demonstrated that this kind of chromatography can also be performed in ion-exchange, affinity and hydrophobic-interaction mode. It has also been shown that SDC can be performed on monoliths and membrane-based supports in both analytical and preparative scale. Recently, SDC in ion-exchange and hydrophobic interaction mode was also employed successfully for the removal of trace proteins from monoclonal antibody preparations and for the enrichment of low abundance proteins from human plasma. In this review, the principals of SDC are introduced, and the potential for separation of proteins and peptides in micro-analytical, analytical and preparative scale is discussed.

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.

Improvements in proteomic metrics of low abundance proteins through proteome equalization using ProteoMiner prior to MudPIT

Ideally, shotgun proteomics would facilitate the identification of an entire proteome with 100% protein sequence coverage. In reality, the large dynamic range and complexity of cellular proteomes results in oversampling of abundant proteins, while peptides from low abundance proteins are undersampled or remain undetected. We tested the proteome equalization technology, ProteoMiner, in conjunction with Multidimensional Protein Identification Technology (MudPIT) to determine how the equalization of protein dynamic range could improve shotgun proteomics methods for the analysis of cellular proteomes. Our results suggest low abundance protein identifications were improved by two mechanisms: (1) depletion of high abundance proteins freed ion trap sampling space usually occupied by high abundance peptides and (2) enrichment of low abundance proteins increased the probability of sampling their corresponding more abundant peptides. Both mechanisms also contributed to dramatic increases in the quantity of peptides identified and the quality of MS/MS spectra acquired due to increases in precursor intensity of peptides from low abundance proteins. From our large data set of identified proteins, we categorized the dominant physicochemical factors that facilitate proteome equalization with a hexapeptide library. These results illustrate that equalization of the dynamic range of the cellular proteome is a promising methodology to improve low abundance protein identification confidence, reproducibility, and sequence coverage in shotgun proteomics experiments, opening a new avenue of research for improving proteome coverage.

A systematic analysis of the effects of increasing degrees of serum immunodepletion in terms of depth of coverage and other key aspects in top-down and bottom-up proteomic analyses

Immunodepletion of clinical fluids to overcome the dominance by a few very abundant proteins has been explored but studies are few, commonly examining only limited aspects with one analytical platform. We have systematically compared immunodepletion of 6, 14, or 20 proteins using serum from renal transplant patients, analysing reproducibility, depth of coverage, efficiency, and specificity using 2-D DIGE (‘top-down’) and LC-MS/MS (‘bottom-up’). A progressive increase in protein number (≥2 unique peptides) was found from 159 in unfractionated serum to 301 following 20 protein depletion using a relatively high-throughput 1-D-LC-MS/MS approach, including known biomarkers and moderate–lower abundance proteins such as NGAL and cytokine/growth factor receptors. On the contrary, readout by 2-D DIGE demonstrated good reproducibility of immunodepletion, but additional proteins seen tended to be isoforms of existing proteins. Depletion of 14 or 20 proteins followed by LC-MS/MS showed excellent reproducibility of proteins detected and a significant overlap between columns. Using label-free analysis, greater run-to-run variability was seen with the Prot20 column compared with the MARS14 column (median %CVs of 30.9 versus 18.2%, respectively) and a corresponding wider precision profile for the Prot20. These results illustrate the potential of immunodepletion followed by 1-D nano-LC-LTQ Orbitrap Velos analysis in a moderate through-put biomarker discovery process.

High abundance proteins depletion vs low abundance proteins enrichment: comparison of methods to reduce the plasma proteome complexity

BACKGROUND

To date, the complexity of the plasma proteome exceeds the analytical capacity of conventional approaches to isolate lower abundance proteins that may prove to be informative biomarkers. Only complex multistep separation strategies have been able to detect a substantial number of low abundance proteins (<100 ng/ml). The first step of these protocols is generally the depletion of high abundance proteins by the use of immunoaffinity columns or, alternatively, the enrichment of by the use of solid phase hexapeptides ligand libraries.

METHODOLOGY/PRINCIPAL FINDINGS

Here we present a direct comparison of these two approaches. Following either approach, the plasma sample was further fractionated by SCX chromatography and analyzed by RP-LC-MS/MS with a Q-TOF mass spectrometer. The depletion of the 20 most abundant plasma proteins allowed the identification of about 25% more proteins than those detectable following low abundance proteins enrichment. The two datasets are partially overlapping and the identified proteins belong to the same order of magnitude in terms of plasma concentration.

CONCLUSIONS/SIGNIFICANCE

Our results show that the two approaches give complementary results. However, the enrichment of low abundance proteins has the great advantage of obtaining much larger amount of material that can be used for further fractionations and analyses and emerges also as a cheaper and technically simpler approach. Collectively, these data indicate that the enrichment approach seems more suitable as the first stage of a complex multi-step fractionation protocol.

Microfluidic enrichment of small proteins from complex biological mixture on nanoporous silica chip

The growing field of miniaturized diagnostics is hindered by a lack of pre-analysis treatments that are capable of processing small sample volumes for the detection of low concentration analytes in a high-throughput manner. This letter presents a novel, highly efficient method for the extraction of low-molecular weight (LMW) proteins from biological fluids, represented by a mixture of standard proteins, using integrated microfluidic systems. We bound a polydimethylsiloxane layer patterned with a microfluidic channel onto a well-defined nanoporous silica substrate. Using rapid, pressure-driven fractionation steps, this system utilizes the size-exclusion properties of the silica nanopores to remove high molecular weight proteins while simultaneously isolating and enriching LMW proteins present in the biological sample. The introduction of the microfluidic component offers important advantages such as high reproducibility, a simple user interface, controlled environment, the ability to process small sample volumes, and precise quantification. This solution streamlines high-throughput proteomics research on many fronts and may find broad acceptance and application in clinical diagnostics and point of care detection.

Plasma biomarker discovery using 3D protein profiling coupled with label-free quantitation

In-depth quantitative profiling of human plasma samples for biomarker discovery remains quite challenging. One promising alternative to chemical derivatization with stable isotope labels for quantitative comparisons is direct, label-free, quantitative comparison of raw LC-MS data. But, in order to achieve high-sensitivity detection of low-abundance proteins, plasma proteins must be extensively pre-fractionated, and results from LC-MS runs of all fractions must be integrated efficiently in order to avoid misidentification of variations in fractionation from sample to sample as "apparent" biomarkers. This protocol describes a powerful 3D protein profiling method for comprehensive analysis of human serum or plasma proteomes, which combines abundant protein depletion and high-sensitivity GeLC-MS/MS with label-free quantitation of candidate biomarkers.

Proteomic and metabolomic profiles in atherothrombotic vascular disease

Atherothrombosis remains a major cause of morbidity and mortality in the western world. The underlying processes associated with clinical expression of atherothrombosis include oxidative stress and proteolysis in relation to neovascularisation and intraplaque hemorrhages, leading to immuno-inflammatory response, cell death, and extracellular matrix breakdown. The complex biological multifactorial nature of atherothrombosis requires the development of novel technologies that allow the analysis of cellular and molecular processes responsible for the transition to disease phenotypes and the discovery of new diagnostic and prognostic biomarkers. In the present article, we have reviewed recent advances in the application of proteomic and metabolomic techniques to the study of atherothrombosis. We have focused on recent studies analyzing cells involved in hemo-thrombus formation (platelets, red blood cells, and polymorphonuclear cells), as well as tissues, tissue-conditioned media, and plasma of atherothrombotic patients. In the future, the application of these high-throughput technologies, along with imaging techniques, in systems biology approaches will help to individualize medicine.

Quantitative iTRAQ-Based Proteomic Identification of Candidate Biomarkers for Diabetic Nephropathy in Plasma of Type 1 Diabetic Patients

Introduction

As part of a clinical proteomics programme focused on diabetes and its complications, it was our goal to investigate the proteome of plasma in order to find improved candidate biomarkers to predict diabetic nephropathy.

Methods

Proteins derived from plasma from a cross-sectional cohort of 123 type 1 diabetic patients previously diagnosed as normoalbuminuric, microalbuminuric or macroalbuminuric were enriched with hexapeptide library beads and subsequently pooled within three groups. Proteins from the three groups were compared by online liquid chromatography and tandem mass spectrometry in three identical repetitions using isobaric mass tags (iTRAQ). The results were further analysed with ingenuity pathway analysis. Levels of apolipoprotein A1, A2, B, C3, E and J were analysed and validated by a multiplex immunoassay in 20 type 1 diabetic patients with macroalbuminuria and 10 with normoalbuminuria.

Results

A total of 112 proteins were identified in at least two out of three replicates. The global protein ratios were further evaluated by ingenuity pathway analysis, resulting in the recognition of apolipoprotein A2, B, C3, D and E as key nodes in the top-rated network. The multiplex immunoassay confirmed the overall protein expression patterns observed by the iTRAQ analysis.

Conclusion

The candidate biomarkers discovered in this cross-sectional cohort may turn out to be progression biomarkers and might have several clinical applications in the treatment and monitoring of diabetic nephropathy; however, they need to be confirmed in a longitudinal cohort.

Electronic supplementary material

The online version of this article (doi:10.1007/s12014-010-9053-0) contains supplementary material, which is available to authorized users.

Ligand-binding mass spectrometry to study biotransformation of fusion protein drugs and guide immunoassay development: strategic approach and application to peptibodies targeting the thrombopoietin receptor

The knowledge of in vivo biotransformation (e.g., proteolysis) of protein therapeutic candidates reveals structural liabilities that impact stability. This information aids the development and confirmation of ligand-binding assays with the required specificity for bioactive moieties (including intact molecule and metabolites) for appropriate PK profiling. Furthermore, the information can be used for re-engineering of constructs to remove in vivo liabilities in order to design the most stable candidates. We have developed a strategic approach of ligand-binding mass spectrometry (LBMS) to study biotransformation of fusion proteins of peptides fused to human Fc ("peptibodies") using anti-human Fc immunoaffinity capture followed by tiered mass spectrometric interrogation. LBMS offers the combined power of selectivity of ligand capture with the specificity and detailed molecular-level information of mass spectrometry. In this paper, we demonstrate the preclinical application of LBMS to three peptibodies, AMG531 (romiplostim), AMG195(linear), and AMG195(loop), that target the thrombopoietin receptor. The data show that ligand capture offers excellent sample cleanup and concentration of intact peptibodies and metabolites for subsequent query by matrix-assisted laser desorption ionization time-of-flight mass spectrometry for identification of in vivo proteolytic points. Additional higher-resolution analysis by nanoscale liquid chromatography interfaced with electrospray ionization mass spectrometry is required for identification of heterogeneous metabolites. Five proteolytic points are accurately identified for AMG531 and two for AMG195(linear), while AMG195(loop) is the most stable construct in rats. We recommend the use of LBMS to assess biotransformation and in vivo stability during early preclinical phase development for all novel fusion proteins.

Comparison of three methods for fractionation and enrichment of low molecular weight proteins for SELDI-TOF-MS differential analysis

In most diseases, the clinical need for serum/plasma markers has never been so crucial, not only for diagnosis, but also for the selection of the most efficient therapies, as well as exclusion of ineffective or toxic treatment. Due to the high sample complexity, prefractionation is essential for exploring the deep proteome and finding specific markers. In this study, three different sample preparation methods (i.e., highly abundant protein precipitation, restricted access materials (RAM) combined with IMAC chromatography and peptide ligand affinity beads) were investigated in order to select the best fractionation step for further differential proteomic experiments focusing on the LMW proteome (MW inferior to 40,000 Da). Indeed, the aim was not to cover the entire plasma/serum proteome, but to enrich potentially interesting tissue leakage proteins. These three methods were evaluated on their reproducibility, on the SELDI-TOF-MS peptide/protein peaks generated after fractionation and on the information supplied. The studied methods appeared to give complementary information and presented good reproducibility (below 20%). Peptide ligand affinity beads were found to provide efficient depletion of HMW proteins and peak enrichment in protein/peptide profiles.

Challenges for biomarker discovery in body fluids using SELDI-TOF-MS

Protein profiling using SELDI-TOF-MS has gained over the past few years an increasing interest in the field of biomarker discovery. The technology presents great potential if some parameters, such as sample handling, SELDI settings, and data analysis, are strictly controlled. Practical considerations to set up a robust and sensitive strategy for biomarker discovery are presented. This paper also reviews biological fluids generally available including a description of their peculiar properties and the preanalytical challenges inherent to sample collection and storage. Finally, some new insights for biomarker identification and validation challenges are provided.

Post analysis data acquisition for the iterative MS/MS sampling of proteomics mixtures

The identification of peptides by microcapillary liquid chromatography-tandem mass spectrometry (microLC-MS/MS) has become routine because of the development of fast scanning mass spectrometers, data-dependent acquisition, and database searching algorithms. However, many peptides within the detection limit of the mass spectrometer remain unidentified because of limitations in MS/MS sampling speed despite the dynamic range and peak capacity of the instrument. We have developed an automated approach that uses the mass spectra from high resolution microLC-MS data to define the molecular species present in the mixture and directs the acquisition of MS/MS spectra to precursors that were missed in prior analyses. This approach increases the coverage of the molecular species sampled by MS/MS and consequently the number of peptides and proteins identified during the acquisition of technical or biological replicates using a simple one-dimensional chromatographic separation. The combination of a unique workflow and custom software contribute to the improved identification of molecular features detected in proteomics experiments of complex protein mixtures.

Advances in Nutrigenomics research: novel and future analytical approaches to investigate the biological activity of natural compounds and food functions

In recent years, nutrition research has moved from classical epidemiology and physiology to molecular biology and genetics. Following this trend, Nutrigenomics has emerged as a novel and multidisciplinary research field in nutritional science that aims to elucidate how diet can influence human health. It is already well known that bioactive food compounds can interact with genes affecting transcription factors, protein expression and metabolite production. The study of these complex interactions requires the development of advanced analytical approaches combined with bioinformatics. Thus, to carry out these studies Transcriptomics, Proteomics and Metabolomics approaches are employed together with an adequate integration of the information that they provide. In this article, an overview of the current methodologies and a thorough revision of the advances in analytical technologies and their possibilities for future developments and applications in the field of Nutrigenomics is provided.

Analysis of human plasma proteins: a focus on sample collection and separation using free-flow electrophoresis

Due to ease of accessibility, plasma has become the sample of choice for proteomics studies directed towards biomarker discovery intended for use in diagnostics, prognostics and even in theranostics. The result of these extensive efforts is a long list of potential biomarkers, very few of which have led to clinical utility. Why have so many potential biomarkers failed validation? Herein, we address certain issues encountered, which complicate biomarker discovery efforts originating from plasma. The advantages of stabilizing the sample at collection by the addition of protease inhibitors are discussed. The principles of free-flow electrophoresis (FFE) separation are provided together with examples applying to various studies. Finally, particular attention is given to plasma or serum analysis using multidimensional separation strategies into which the FFE is incorporated. The advantages of using FFE separation in these workflows are discussed.