Challenges in translating plasma proteomics from bench to bedside: update from the NHLBI Clinical Proteomics Programs

The emerging scientific field of proteomics encompasses the identification, characterization, and quantification of the protein content or proteome of whole cells, tissues, or body fluids. The potential for proteomic technologies to identify and quantify novel proteins in the plasma that can function as biomarkers of the presence or severity of clinical disease states holds great promise for clinical use. However, there are many challenges in translating plasma proteomics from bench to bedside, and relatively few plasma biomarkers have successfully transitioned from proteomic discovery to routine clinical use. Key barriers to this translation include the need for "orthogonal" biomarkers (i.e., uncorrelated with existing markers), the complexity of the proteome in biological samples, the presence of high abundance proteins such as albumin in biological samples that hinder detection of low abundance proteins, false positive associations that occur with analysis of high dimensional datasets, and the limited understanding of the effects of growth, development, and age on the normal plasma proteome. Strategies to overcome these challenges are discussed.     

Comparative proteome analyses of human plasma following in vivo lipopolysaccharide administration using multidimensional separations coupled with tandem mass spectrometry

There is significant interest in characterization of the human plasma proteome due to its potential for providing biomarkers applicable to clinical diagnosis and treatment and for gaining a better understanding of human diseases. We describe here a strategy for comparative proteome analyses of human plasma, which is applicable to biomarker identifications for various disease states. Multidimensional liquid chromatography-mass spectrometry (LC-MS/MS) has been applied to make comparative proteome analyses of plasma samples from an individual prior to and 9 h after lipopolysaccharide (LPS) administration. Peptide peak areas and the number of peptide identifications for each protein were used to evaluate the reproducibility of LC-MS/MS and to compare relative changes in protein concentration between the samples following LPS treatment. A total of 804 distinct plasma proteins (not including immunoglobulins) were confidently identified with 32 proteins observed to be significantly increased in concentration following LPS administration, including several known inflammatory response or acute-phase mediators such as C-reactive protein, serum amyloid A and A2, LPS-binding protein, LPS-responsive and beige-like anchor protein, hepatocyte growth factor activator, and von Willebrand factor, and thus, constituting potential biomarkers for inflammatory response.     

Discovery of regulatory molecular events and biomarkers using 2D capillary chromatography and mass spectrometry

An important component of proteomic research is the high-throughput discovery of novel proteins and protein-protein interactions that control molecular events that contribute to critical cellular functions and human disease. The interactions of proteins are essential for cellular functions. Identifying perturbation of normal cellular protein interactions is vital for understanding the disease process and intervening to control the disease. A second area of proteomics research is the discovery of proteins that will serve as biomarkers for the early detection, diagnosis and drug treatment response for specific diseases. These studies have been referred to as clinical proteomics. To discover biomarkers, proteomics research employs the quantitative comparison of peptide and protein expression in body fluids and tissues from diseased individuals (case) versus normal individuals (control). Methods that couple 2D capillary liquid chromatography (LC) and tandem mass spectrometry (MS/MS) analysis have greatly facilitated this discovery science. Coupling 2D-LC/MS/MS analysis with automated genome-assisted spectra interpretation allows a direct, high-throughput and high-sensitivity identification of thousands of individual proteins from complex biological samples. The systematic comparison of experimental conditions and controls allows protein function or disease states to be modeled. This review discusses the different purification and quantification strategies that have been developed and used in combination with 2D-LC/MS/MS and computational analysis to examine regulatory protein networks and clinical samples.     

Discovery of regulatory molecular events and biomarkers using 2D capillary chromatography and mass spectrometry

An important component of proteomic research is the high-throughput discovery of novel proteins and protein–protein interactions that control molecular events that contribute to critical cellular functions and human disease. The interactions of proteins are essential for cellular functions. Identifying perturbation of normal cellular protein interactions is vital for understanding the disease process and intervening to control the disease. A second area of proteomics research is the discovery of proteins that will serve as biomarkers for the early detection, diagnosis and drug treatment response for specific diseases. These studies have been referred to as clinical proteomics. To discover biomarkers, proteomics research employs the quantitative comparison of peptide and protein expression in body fluids and tissues from diseased individuals (case) versus normal individuals (control). Methods that couple 2D capillary liquid chromatography (LC) and tandem mass spectrometry (MS/MS) analysis have greatly facilitated this discovery science. Coupling 2D-LC/MS/MS analysis with automated genome-assisted spectra interpretation allows a direct, high-throughput and high-sensitivity identification of thousands of individual proteins from complex biological samples. The systematic comparison of experimental conditions and controls allows protein function or disease states to be modeled. This review discusses the different purification and quantification strategies that have been developed and used in combination with 2D-LC/MS/MS and computational analysis to examine regulatory protein networks and clinical samples.     

Relative quantification of serum proteins from pancreatic ductal adenocarcinoma patients by stable isotope dilution liquid chromatography-mass spectrometry

We report an innovative multiplexed liquidchromatography-multiple reaction monitoring/mass spectrometry (LC-MRM/MS)-based assay for rapidly measuring a large number of disease specific protein biomarkers in human serum. Furthermore, this approach uses stable isotope dilution methodology to reliably quantify candidate protein biomarkers. Human serum was diluted using a stable isotope labeled proteome (SILAP) standard prepared from the secretome of pancreatic cell lines, subjected to immunoaffinity removal of the most highly abundant proteins, trypsin digested, and analyzed by LC-MRM/MS. The method was found to be precise, linear, and specific for the relative quantification of 72 proteins when analyte response was normalized to the relevant internal standard (IS) from the SILAP. The method made it possible to determine statistically different concentrations for three proteins (cystatin M, IGF binding protein 7, and villin 2) in control and pancreatic cancer patient samples. This method proves the feasibility of using a SILAP standard in combination with stable isotope dilution LC-MRM/MS analysis of tryptic peptides to compare changes in the concentration of candidate protein biomarkers in human serum.     

Global and targeted quantitative proteomics for biomarker discovery

The extraordinary developments made in proteomic technologies in the past decade have enabled investigators to consider designing studies to search for diagnostic and therapeutic biomarkers by scanning complex proteome samples using unbiased methods. The major technology driving these studies is mass spectrometry (MS). The basic premises of most biomarker discovery studies is to use the high data-gathering capabilities of MS to compare biological samples obtained from healthy and disease-afflicted patients and identify proteins that are differentially abundant between the two specimen. To meet the need to compare the abundance of proteins in different samples, a number of quantitative approaches have been developed. In this article, many of these will be described with an emphasis on their advantageous and disadvantageous for the discovery of clinically useful biomarkers.     

Proteomic analysis of cervical-vaginal fluid: identification of novel biomarkers for detection of intra-amniotic infection

Intra-amniotic infection (IAI) is associated with preterm birth and perinatal mortality. To identify potential biomarkers, we performed a comprehensive survey of the cervical-vaginal fluid (CVF) proteome from a primate IAI model utilizing multidimensional protein identification technology (LC/LC-MS/MS) and MALDI-TOF-MS analyses. Analyses of CVF proteome identified 205 unique proteins and differential expression of 27 proteins in controls and IAI samples. Protein expression signatures and immunodetection of specific biomarkers identified can be employed for noninvasive detection of IAI.     

Characterization of the human gastric fluid proteome reveals distinct pH-dependent protein profiles: implications for biomarker studies

Gastric fluid is a source of gastric cancer biomarkers. However, very little is known about the normal gastric fluid proteome and its biological variations. In this study, we performed a comprehensive analysis of the human gastric fluid proteome using samples obtained from individuals with benign gastric conditions. Gastric fluid proteins were prefractionated using ultracentrifuge filters (3 kDa cutoff) and analyzed by two-dimensional gel electrophoresis (2-DE) and multidimensional LC-MS/MS. Our 2-DE analysis of 170 gastric fluid samples revealed distinct protein profiles for acidic and neutral samples, highlighting pH effects on protein composition. By 2D LC-MS/MS analysis of pooled samples, we identified 284 and 347 proteins in acidic and neutral samples respectively (FDR ≤1%), of which 265 proteins (72.4%) overlapped. However, unlike neutral samples, most proteins in acidic samples were identified from peptides in the filtrate (i.e., <3 kDa). Consistent with this finding, immunoblot analysis of six potential gastric cancer biomarkers rarely detected full-length proteins in acidic samples. These findings have important implications for biomarker studies because a majority of gastric cancer patients have neutral gastric fluid compared to noncancer controls. Consequently, sample stratification, choice of proteomic approaches, and validation strategy can profoundly affect the interpretation of biomarker findings. These observations should help to refine gastric fluid biomarker studies.     

Mass spectrometry-based expression profiling of clinical prostate cancer

The maturation of MS technologies has provided a rich opportunity to interrogate protein expression patterns in normal and disease states by applying expression protein profiling methods. Major goals of this research strategy include the identification of protein biomarkers that demarcate normal and disease populations, and the identification of therapeutic biomarkers for the treatment of diseases such as cancer (Celis, J. E., and Gromov, P. (2003) Proteomics in translational cancer research: Toward an integrated approach. Cancer Cell 3, 9-151). Prostate cancer is one disease that would greatly benefit from implementing MS-based expression profiling methods because of the need to stratify the disease based on molecular markers. In this review, we will summarize the current MS-based methods to identify and validate biomarkers in human prostate cancer. Lastly, we propose a reverse proteomic approach implementing a quantitative MS research strategy to identify and quantify biomarkers implicated in prostate cancer development. With this approach, the absolute levels of prostate cancer biomarkers will be identified and quantified in normal and diseased samples by measuring the levels of native peptide biomarkers in relation to a chemically identical but isotopically labeled reference peptide. Ultimately, a centralized prostate cancer peptide biomarker expression database could function as a repository for the identification, quantification, and validation of protein biomarker(s) during prostate cancer progression in men.     

Absolute quantification of microbial proteomes at different states by directed mass spectrometry

Over the past decade, liquid chromatography coupled with tandem mass spectrometry (LC–MS/MS) has evolved into the main proteome discovery technology. Up to several thousand proteins can now be reliably identified from a sample and the relative abundance of the identified proteins can be determined across samples. However, the remeasurement of substantially similar proteomes, for example those generated by perturbation experiments in systems biology, at high reproducibility and throughput remains challenging. Here, we apply a directed MS strategy to detect and quantify sets of pre‐determined peptides in tryptic digests of cells of the human pathogen Leptospira interrogans at 25 different states. We show that in a single LC–MS/MS experiment around 5000 peptides, covering 1680 L. interrogans proteins, can be consistently detected and their absolute expression levels estimated, revealing new insights about the proteome changes involved in pathogenic progression and antibiotic defense of L. interrogans. This is the first study that describes the absolute quantitative behavior of any proteome over multiple states, and represents the most comprehensive proteome abundance pattern comparison for any organism to date.     

Shotgun proteomic analysis of human-induced sputum

Induced sputum is a readily accessible biological fluid whose composition may alter as a consequence of disease. To date, however, the proteins that routinely populate this biofluid are largely unknown, in part due to the technical difficulties in processing such mucin-rich samples. To provide a catalogue of sputum proteins, we have surveyed the proteome of human-induced sputum (sputome). A combination of 2-D gel analysis and GeLC-MS/MS allowed a total of 191 human proteins to be confidently assigned. In addition to the expected components, several hitherto unreported proteins were found to be present, including three members of the annexin family, kallikreins 1 and 11, and peroxiredoxins 1, 2 and 5. Other sets of proteins identified included four proteins previously annotated as hypothetical or conserved hypothetical. Taken together, these data represent the first extensive survey of the proteome of induced sputum and provide a platform for future identification of biomarkers of lung disease.     

Quantitative Proteome Analysis of Brain Subregions and Spinal Cord from Experimental Autoimmune Encephalomyelitis Mice by TMT‐Based Mass Spectrometry

Multiple sclerosis (MS) is an autoimmune disease of the central nervous system (CNS); its cause is unknown. To understand the pathogenesis of MS, researchers often use the experimental autoimmune encephalomyelitis (EAE) mouse model. Here, the aim is to build a proteome map of the biological changes that occur during MS at the major onset sites—the brain and the spinal cord. Quantitative proteome profiling is performed in five specific brain regions and the spinal cord of EAE and healthy mice with high‐resolution mass spectrometry based on tandem mass tags. On average, 7400 proteins per region are quantified, with the most differentially expressed proteins in the spinal cord (1691), hippocampus (104), frontal cortex (83), cerebellum (63), brainstem (50), and caudate nucleus (41). Moreover, region‐specific and commonly expressed proteins in each region are identified and bioinformatics analysis is performed. Pathway analysis reveals that protein clusters resemble their functions in disease pathogenesis (i.e., by inducing inflammatory responses, immune activation, and cell–cell adhesion). In conclusion, the study provides an understanding of the pathogenesis of MS in the EAE animal model. It is expected that the comprehensive proteome map of the brain and spinal cord can be used to identify biomarkers for the pathogenesis of MS.     

Characterizing phosphoproteins and phosphoproteomes using mass spectrometry.

The reversible phosphorylation of proteins plays a major role in many vital cellular processes by modulating protein function and transmitting signals within cellular pathways and networks. Because phosphorylation is dynamic and the sites of modification cannot be predicted by an organism's genome, proteomic measurements are required to identify sites of and changes in the phosphorylation state of proteins. The low stoichiometry of phosphorylation sites that accompany the multifarious nature of protein phosphorylation in biological systems continues to challenge the dynamic range of present mass spectrometry (MS) technologies and proteomic measurements, despite the preponderance of research and analytical methods devoted to this area. This review addresses some of the strategies and limitations involving the use of MS to map and quantify changes in protein phosphorylation sites for samples that range from a single protein to an entire proteome, and presents several compelling reasons as to why comprehensive phosphorylation site analysis has proven to be so elusive without a hypothesis-driven experimental approach to elicit more meaningful and confident results.     

Differential Levels of Alpha-2-Macroglobulin,Haptoglobin and Sero-Transferrin as Adjunct Markers for TB Diagnosis and Disease Progression in the Malnourished Tribal Population of Melghat,India

Lack of diagnostic capacity has been a crucial barrier preventing an effective response to the challenges of malnutrition and tuberculosis (TB). Point-of-care diagnostic tests for TB in immuno-incompetent, malnourished population are thus needed to ensure rapid and accurate detection. The aim of the study was to identify potential biomarkers specific for TB infection and progression to overt disease in the malnourished population of Melghat. A prospective cohort study was conducted in the year 2009 through 2011 in six villages of the Melghat region. 275 participants consisting of malnourished cases with a) active TB (n = 32), b) latent TB infection (n = 90), c) with no clinical or bacteriological signs of active or latent TB (n = 130) and healthy control subjects (n = 23) were recruited for the study. The proteome changes of the host serum in response to Mycobacterium tuberculosis (M.tb) infection were investigated using one dimensional electrophoresis in combination with matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS). Three most differentially expressed proteins; alpha-2-macroglobulin (A-2-M), sero-transferrin and haptoglobin were identified by MALDI-TOF MS analysis, which were up-regulated in the malnourished patients with active TB and down-regulated in the malnourished patients compared with the healthy controls. Additionally, follow-up studies indicated that the expression of these proteins increased to nearly two folds in patients who developed active disease from latent state. Our preliminary results suggest that A-2-M, sero-transferrin and haptoglobin may be clinically relevant host biomarkers for TB diagnosis and disease progression in the malnourished population. This study provides preliminary framework for an in-depth analysis of the biomarkers in larger well-characterized cohorts. Evaluation of these biomarkers in follow-up cases may further aid in improving TB diagnosis.     

Higher dimensional (Hi-D) separation strategies dramatically improve the potential for cancer biomarker detection in serum and plasma

The plasma proteome has a wide dynamic range of protein concentrations and is dominated by a few highly abundant proteins. Discovery of novel cancer biomarkers using proteomics is particularly challenging because specific biomarkers are expected to be low abundance proteins with normal blood concentrations of low nanograms per milliliter or less. Conventional, one- and two-dimensional proteomic methods including 2D PAGE, 2D DIGE, LC-MS/MS, and LC/LC-MS/MS do not have the capacity to consistently detect many proteins in this range. In contrast, new higher dimensional (Hi-D) separation strategies, utilizing more than two dimensions of fractionation, can profile the low abundance proteome.     

Proteomic analysis of recurrent joint inflammation in juvenile idiopathic arthritis

The synovial fluid proteome in juvenile idiopathic arthritis was investigated to isolate joint-specific biomarkers that are expressed in patients displaying recurrent joint inflammation. To identify the synovial specific proteome, matched synovial fluid and plasma samples were subjected to protein separation by 2-dimension electrophoresis (2DE). Forty-three protein spots, overexpressed in the joint, were identified. Synovial fluids from children with single-event knee joint inflammation were then compared with a group with recurrent knee disease. Nine synovial specific proteins were significantly differentially expressed in the recurrent group. Proteolytic fragments of collagen X, fibrin beta-chain, and T-cell receptor alpha-region have been identified among this protein cluster. Putative biomarkers, overexpressed in the joint and differentially expressed in children with recurrent joint inflammation, have been identified. These proteins may play a significant role determining the pathological state within the chronically inflamed joint and influence disease progression in JIA. This is the first study of the synovial proteome in children.     

Dynamic changes of urinary proteins in a rat model of acute hypercoagulable state induced by tranexamic acid

The hypercoagulable state leads to the development of thrombotic diseases, but it is difficult to diagnose due to the lack of available biomarkers. This study aimed to investigate systematic changes of the urinary proteome in the acute hypercoagulable state. A rat model of the acute hypercoagulable state was induced by an antifibrinolytic agent tranexamic acid and urine samples were collected for proteomic analysis by liquid chromatography-tandem mass spectrometry. A total of 28 differential proteins were detected in the urinary proteome of the model rats, of which 12 had been previously considered as candidate biomarkers such as myoglobin, and 10 had been considered stable in healthy human urine. Of the 28 differentially expressed proteins 18 had counterparts in humans. Of these 18 proteins, 10 were members of the human core urinary proteome distributed in a variety of human tissues but concentrated in the urinary and digestive systems. Fumarylacetoacetase was verified as a potential marker of the acute hypercoagulable state by Western blot analysis. In conclusion, urine proteome analysis is a powerful approach to identify potential biomarkers of acute hypercoagulable state.     

Identification of psoriatic arthritis mediators in synovial fluid by quantitative mass spectrometry

Background

Synovial fluid (SF) is a dynamic reservoir for proteins originating from the synovial membrane, cartilage, and plasma, and may therefore reflect the pathophysiological conditions that give rise to arthritis. Our goal was to identify and quantify protein mediators of psoriatic arthritis (PsA) in SF.

Methods

Age and gender-matched pooled SF samples from 10 PsA and 10 controls [early osteoarthritis (OA)], were subjected to label-free quantitative proteomics using liquid chromatography coupled to mass spectrometry (LC-MS/MS), to identify differentially expressed proteins based on the ratios of the extracted ion current of each protein between the two groups. Pathway analysis and public database searches were conducted to ensure these proteins held relevance to PsA. Multiplexed selected reaction monitoring (SRM) assays were then utilized to confirm the elevated proteins in the discovery samples and in an independent set of samples from patients with PsA and controls.

Results

We determined that 137 proteins were differentially expressed between PsA and control SF, and 44 were upregulated. The pathways associated with these proteins were acute-phase response signalling, granulocyte adhesion and diapedesis, and production of nitric oxide and reactive oxygen species in macrophages. The expression of 12 proteins was subsequently quantified using SRM assays.

Conclusions

Our in-depth proteomic analysis of the PSA SF proteome identified 12 proteins which were significantly elevated in PsA SF compared to early OA SF. These proteins may be linked to the pathogenesis of PsA, as well serve as putative biomarkers and/or therapeutic targets for this disease.     

A novel adipocytokine, vaspin inhibits platelet-derived growth factor-BB-induced migration of vascular smooth muscle cells

Orthodontic treatment induces various biological responses, including tooth movement and remodeling of alveolar bone. Although some studies have investigated the contribution of orthodontic procedures to changes in saliva conditions, little is known about the effects of different treatment durations on the saliva proteome. To identify the discriminating protein profiles in unstimulated whole saliva of orthodontic patients with different treatment durations, we used matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) combined with magnetic bead, and peptide mass fingerprints were created by scanning MS signals. Saliva samples from 40 patients (10 in each of four groups: the group without an appliance and groups under treatment for 2, 7, and 12 months) were analyzed. The results showed eight mass peaks with significant differences. Furthermore, mass peak intensities at proteins 1817.7, 2010.7, 2744 and 2710.2 Da represented a steady time-dependent increasing trend, whereas protein 4134 Da exhibited a decreasing tendency. Differential expression of the peptidome profile also occurred in the multiple comparisons, and we established a fitting model. Thus, the potential discriminating biomarkers investigated in this study reflected the complicated changes in periodontal tissues during orthodontic treatment and indicated dynamic interactions between orthodontic treatment and the saliva proteome. The results provide novel insights into alterations in salivary proteins due to different orthodontic treatment durations and may lead to the development of a therapeutic monitoring strategy for orthodontics.