Prefractionation techniques in proteome analysis: the mining tools of the third millennium

An enhanced label-free proteomics approach for deep-diving into equine plasma proteome, including the discovery of protein biomarkers for strenuous exercise

Plasma proteins have been a valuable source of biomarkers for clinical uses and for monitoring of the illicit use of prohibited substances or practices in equine sports. We have previously reported the first use of label-free proteomics in profiling equine plasma proteome. This study aimed to refine the method by systematically evaluating various plasma fractionation methods and the use of narrower precursor mass ranges in data-independent acquisition (DIA) mass spectrometry (MS). Tandem fractionations of equine plasma with octanoic acid precipitation followed by solid-phase extraction (SPE) with C4 cartridges provided the largest increase in the number of new proteins identified. The use of two narrow precursor mass ranges of m/z 400-600 and 600-800 in DIA not only identified most proteins detectable by using a single mass range of m/z 350-1500 but also identified ~27% more proteins. The improved method was applied to analyse the plasma proteome of 'postrace' samples which, unlike other samples, had been collected from racehorses soon after racing. Multivariate data analysis has identified upregulation of 14 proteins and downregulation of six proteins in postrace plasma compared with the non-postrace plasma samples. Literature review of these proteins has provided evidence of exercise-induced haemolysis and changes in antioxidant enzyme activities, kinin system, insulin signalling and energy metabolism after strenuous exercise. The improved method has enabled a deeper profiling of the equine plasma proteome and identified the proteins associated with normal physiological changes after racing which are potential confounding factors in the development of a biomarker approach for doping control.

Sample Treatment for Urine Proteomics

Urine is a biological fluid that can be collected noninvasively in relatively large quantities which can be used for the search of biomarkers of disease, both diseases of the urological tract and systemic diseases. One of the most important aspects in proteomic studies is sample treatment before further analysis. Methods of preparation of a urine sample depend on the techniques that will be used later for separation and identification of the proteins. Also, urine preparation should be as simple as possible to increase reproducibility. Normal urine has a much diluted protein concentration with a high-salt content, which interferes with proteomic analysis. Thus, an initial step in the handling of urine sample should be to concentrate and eliminate salts. As range of protein concentrations in urine spans several orders of magnitude, effective proteomic analyses require either removal of most abundant protein or enrichment of the less abundant ones. In this chapter, we discuss the aspects related to the collection and treatment of urine for proteomic studies.

Middle-down approach: a choice to sequence and characterize proteins/proteomes by mass spectrometry

Owing to rapid growth in the elucidation of genome sequences of various organisms, deducing proteome sequences has become imperative, in order to have an improved understanding of biological processes. Since the traditional Edman method was unsuitable for high-throughput sequencing and also for N-terminus modified proteins, mass spectrometry (MS) based methods, mainly based on soft ionization modes: electrospray ionization and matrix-assisted laser desorption/ionization, began to gain significance. MS based methods were adaptable for high-throughput studies and applicable for sequencing N-terminus blocked proteins/peptides too. Consequently, over the last decade a new discipline called 'proteomics' has emerged, which encompasses the attributes necessary for high-throughput identification of proteins. 'Proteomics' may also be regarded as an offshoot of the classic field, 'biochemistry'. Many protein sequencing and proteomic investigations were successfully accomplished through MS dependent sequence elucidation of 'short proteolytic peptides (typically: 7-20 amino acid residues), which is called the 'shotgun' or 'bottom-up (BU)' approach. While the BU approach continues as a workhorse for proteomics/protein sequencing, attempts to sequence intact proteins without proteolysis, called the 'top-down (TD)' approach started, due to ambiguities in the BU approach, e.g., protein inference problem, identification of proteoforms and the discovery of posttranslational modifications (PTMs). The high-throughput TD approach (TD proteomics) is yet in its infancy. Nevertheless, TD characterization of purified intact proteins has been useful for detecting PTMs. With the hope to overcome the pitfalls of BU and TD strategies, another concept called the 'middle-down (MD)' approach was put forward. Similar to BU, the MD approach also involves proteolysis, but in a restricted manner, to produce 'longer' proteolytic peptides than the ones usually obtained in BU studies, thereby providing better sequence coverage. In this regard, special proteases (OmpT, Sap9, IdeS) have been used, which can cleave proteins to produce longer proteolytic peptides. By reviewing ample evidences currently existing in the literature that is predominantly on PTM characterization of histones and antibodies, herein we highlight salient features of the MD approach. Consequently, we are inclined to claim that the MD concept might have widespread applications in future for various research areas, such as clinical, biopharmaceuticals (including PTM analysis) and even for general/routine characterization of proteins including therapeutic proteins, but not just limited to analysis of histones or antibodies.

Predictive chromatography of peptides and proteins as a complementary tool for proteomics

In the last couple of decades, considerable effort has been focused on developing methods for quantitative and qualitative proteome characterization. The method of choice in this characterization is mass spectrometry used in combination with sample separation. One of the most widely used separation techniques at the front end of a mass spectrometer is high performance liquid chromatography (HPLC). A unique feature of HPLC is its specificity to the amino acid sequence of separated peptides and proteins. This specificity may provide additional information about the peptides or proteins under study which is complementary to the mass spectrometry data. The value of this information for proteomics has been recognized in the past few decades, which has stimulated significant effort in the development and implementation of computational and theoretical models for the prediction of peptide retention time for a given sequence. Here we review the advances in this area and the utility of predicted retention times for proteomic applications.

Use of liquid isoelectric focusing (OFFGEL) on the discovery of meat tenderness biomarkers

Protein biomarkers of meat tenderness are known to be of primary importance for the prediction of meat quality, and hence, industry profitability. Proteome analysis was performed on meat from 8 Main Anjou beef cattle, previously classified as tender or tough meats by Warner Bratzler shear force measurements. Myofibrillar fraction of Longissimus thoracis muscle was separated by a novel fractionation approach based on liquid isoelectric focusing (OFFGEL) and further analyzed by SDS-PAGE and liquid chromatography coupled to tandem mass spectrometry. Obtained OFFGEL fraction profiles were reproducible allowing the comparison of both meat qualities and revealing 7 protein bands capable to discriminate between tender and tough samples. The proteins present in these bands were troponin T, Heat Shock protein beta-1, creatine kinase, actin, troponin C, myosins 1 and 2 and myozenin-1. The latter protein has not been previously reported as a marker of meat tenderness.

SIGNIFICANCE

This study introduces an innovative proteomic approach for the study of muscle proteome. The fact of obtaining fractions in liquid state after OFFGEL fractionation allows for a faster analysis of proteins by mass spectrometry, being an interesting alternative to more classical proteomic approaches based on two dimensional gel electrophoresis (2-DE).

Understanding Leishmania parasites through proteomics and implications for the clinic

INTRODUCTION

Leishmania spp. are causative agents of leishmaniasis, a broad-spectrum neglected vector-borne disease. Genomic and transcriptional studies are not capable of solving intricate biological mysteries, leading to the emergence of proteomics, which can provide insights into the field of parasite biology and its interactions with the host. Areas covered: The combination of genomics and informatics with high throughput proteomics may improve our understanding of parasite biology and pathogenesis. This review analyses the roles of diverse proteomic technologies that facilitate our understanding of global protein profiles and definition of parasite development, survival, virulence and drug resistance mechanisms for disease intervention. Additionally, recent innovations in proteomics have provided insights concerning the drawbacks associated with conventional chemotherapeutic approaches and Leishmania biology, host-parasite interactions and the development of new therapeutic approaches. Expert commentary: With progressive breakthroughs in the foreseeable future, proteome profiles could provide target molecules for vaccine development and therapeutic intervention. Furthermore, proteomics, in combination with genomics and informatics, could facilitate the elimination of several diseases. Taken together, this review provides an outlook on developments in Leishmania proteomics and their clinical implications.

Fractionation of Soluble Proteins Using DEAE-Sepharose, SP-Sepharose, and Phenyl Sepharose Chromatographies for Proteomics

In order to simplify a complex mixture of soluble proteins from tissues, a protocol to fractionate samples prior to two-dimensional (2D) gel electrophoresis has been developed. These methods involve the use of DEAE-Sepharose, SP-Sepharose, and phenyl Sepharose chromatographic columns and the fractionation of the protein mixtures based on differential anionic, cationic, and hydrophobic properties of the proteins, respectively. Fractionation of the soluble proteins with DEAE-Sepharose can result in an increase in the number of detectable 2D gel spots. These gel spots are amenable to protein identification by using in-gel trypsin digestions, matrix-assisted laser desorption/ionization time-of-flight mass spectrometry, and peptide mass fingerprinting. The DEAE-Sepharose column fractionation acts to partition soluble proteins from cell extracts. Similarly, a SP-Sepharose column can fractionate soluble proteins and increase the number of detectable gel spots. Lastly, fractionation of cell extract with a phenyl Sepharose column can also result in an increase in the number of detectable 2D gel spots. This chapter describes an easy, inexpensive way to fractionate soluble proteins and a way to better profile proteomes.

Current state of the art for enhancing urine biomarker discovery

INTRODUCTION

Urine is a highly desirable biospecimen for biomarker analysis because it can be collected recurrently by non-invasive techniques, in relatively large volumes. Urine contains cellular elements, biochemicals, and proteins derived from glomerular filtration of plasma, renal tubule excretion, and urogenital tract secretions that reflect, at a given time point, an individual's metabolic and pathophysiologic state.

AREAS COVERED

High-resolution mass spectrometry, coupled with state of the art fractionation systems are revealing the plethora of diagnostic/prognostic proteomic information existing within urinary exosomes, glycoproteins, and proteins. Affinity capture pre-processing techniques such as combinatorial peptide ligand libraries and biomarker harvesting hydrogel nanoparticles are enabling measurement/identification of previously undetectable urinary proteins. Expert commentary: Future challenges in the urinary proteomics field include a) defining either single or multiple, universally applicable data normalization methods for comparing results within and between individual patients/data sets, and b) defining expected urinary protein levels in healthy individuals.

Construction and characterization of the Korean whole saliva proteome to determine ethnic differences in human saliva proteome

As the first step to discover protein disease biomarkers from saliva, global analyses of the saliva proteome have been carried out since the early 2000s, and more than 3,000 proteins have been identified in human saliva. Recently, ethnic differences in the human plasma proteome have been reported, but such corresponding studies on human saliva in this aspect have not been previously reported. Thus, here, in order to determine ethnic differences in the human saliva proteome, a Korean whole saliva (WS) proteome catalogue indexing 480 proteins was built and characterized through nLC-Q-IMS-TOF analyses of WS samples collected from eleven healthy South Korean male adult volunteers for the first time. Identification of 226 distinct Korean WS proteins, not observed in the integrated human saliva protein dataset, and significant gene ontology distribution differences in the Korean WS proteome compared to the integrated human saliva proteome strongly support ethnic differences in the human saliva proteome. Additionally, the potential value of ethnicity-specific human saliva proteins as biomarkers for diseases highly prevalent in that ethnic group was confirmed by finding 35 distinct Korean WS proteins likely to be associated with the top 10 deadliest diseases in South Korea. Finally, the present Korean WS protein list can serve as the first level reference for future proteomic studies including disease biomarker studies on Korean saliva.

Preparative isoelectric focusing in a cellulose-based separation medium

An improved preparative method based on isoelectric focusing of analytes in a cellulose-based separation medium is described in this study. Cellulose is suspended in an aqueous solution of simple buffers, ethylene glycol, glycerol, nonionic surfactant, and colored pI markers. Water partially evaporates during focusing run and the separation takes place in an in situ generated layer of cellulose, which has a gel-like appearance at the end of analysis. Final positions of analytes are indicated by the positions of zones of focused pI markers. Fractions, segments of the separation medium with analytes, can be simply collected by spatula and analyzed by downstream analytical methods. Good focusing ability of the new method and almost quantitative recovery of model proteins, cytochrome c and bovine serum albumin, was verified by gel electrophoresis and capillary isoelectric focusing of the collected fractions.

A Comprehensive Guide for Performing Sample Preparation and Top-Down Protein Analysis

Methodologies for the global analysis of proteins in a sample, or proteome analysis, have been available since 1975 when Patrick O′Farrell published the first paper describing two-dimensional gel electrophoresis (2D-PAGE). This technique allowed the resolution of single protein isoforms, or proteoforms, into single ‘spots’ in a polyacrylamide gel, allowing the quantitation of changes in a proteoform′s abundance to ascertain changes in an organism′s phenotype when conditions change. In pursuit of the comprehensive profiling of the proteome, significant advances in technology have made the identification and quantitation of intact proteoforms from complex mixtures of proteins more routine, allowing analysis of the proteome from the ‘Top-Down’. However, the number of proteoforms detected by Top-Down methodologies such as 2D-PAGE or mass spectrometry has not significantly increased since O’Farrell’s paper when compared to Bottom-Up, peptide-centric techniques. This article explores and explains the numerous methodologies and technologies available to analyse the proteome from the Top-Down with a strong emphasis on the necessity to analyse intact proteoforms as a better indicator of changes in biology and phenotype. We arrive at the conclusion that the complete and comprehensive profiling of an organism′s proteome is still, at present, beyond our reach but the continuing evolution of protein fractionation techniques and mass spectrometry brings comprehensive Top-Down proteome profiling closer.

Simple Means for Fractionating Protein Based on Isoelectric Point without Ampholyte

In this paper, we develop a simple electrokinetic means for fractionating protein samples according to their pI values without using ampholytes. The method uses inexpensive equipment, and its consumables are primarily ammonium acetate buffers. A key component of its apparatus is a dialysis membrane interface that eliminates electrolysis-caused protein oxidation/reduction and constrains proteins in the desired places. We demonstrate its feasibility for fractionating standard proteins and real-world samples. With the elimination of ampholytes, we can analyze the fractionated proteins directly by a matrix assisted laser desorption/ionization time-of-flight mass spectrometer. Important experimental parameters are also discussed in order to obtain good fractionation results.

Serum markers of pre-eclampsia identified on proteomics

AIM

Pre-eclampsia (PE) is a disorder of pregnancy associated with maternal and fetal mortality and morbidity. The aim of the present study was to use proteomics to identify biomarkers of, and elucidate the pathogenesis of, PE.

METHODS

Serum samples were analyzed using peptide ligand library beads (PLLB) on liquid chromatography-mass spectrometry/mass spectrometry. Retinol-binding protein 4 (RBP4) was used as the target protein for further validation on enzyme-linked immunosorbent assay, immunohistochemistry and real-time polymerase chain reaction. Transwell invasion assay was used to evaluate whether RBP4 affects the invasive ability of trophoblast tumor cells.

RESULTS

Twenty upregulated and 17 downregulated proteins were differentially expressed between severe PE patients and healthy pregnant women. Those proteins were further classified according to molecular function and biological process according to the gene ontology terms. RBP4 concentration was significantly lower in women with severe PE than in those with healthy pregnancy.

CONCLUSIONS

RBP4 is able to function as biomarker to distinguish severe PE from normal pregnancy. More importantly, these results may shed light on the role of RPB4 in the pathogenesis in PE. Further studies are required to validate these results, and determine the precise role of RBP4 in the pathogenesis of PE.

A cost-effective method to get insight into the peritoneal dialysate effluent proteome

Protein depletion with acetonitrile and protein equalization with dithiothreitol have been assessed with success as proteomics tools for getting insight into the peritoneal dialysate effluent proteome. The methods proposed are cost-effective, fast and easy of handling, and they match the criteria of analytical minimalism: low sample volume and low reagent consumption. Using two-dimensional gel electrophoresis and peptide mass fingerprinting, a total of 72 unique proteins were identified. Acetonitrile depletes de PDE proteome from high-abundance proteins, such as albumin, and enriches the sample in apolipo-like proteins. Dithiothreitol equalizes the PDE proteome by diminishing the levels of albumin and enriching the extract in immunoglobulin-like proteins. The annotation per gene ontology term reveals the same biological paths being affected for patients undergoing peritoneal dialysis, namely that the largest number of proteins lost through peritoneal dialysate are extracellular proteins involved in regulation processes through binding.

SIGNIFICANCE

Renal failure is a growing problem worldwide, and particularly in Europe where the population is getting older. Up-to-date there is a focus of interest in peritoneal dialysis (PD), as it provides a better quality of life and autonomy of the patients than other renal replacement therapies such as haemodialysis. However, PD can only be used during a short period of years, as the peritoneum lost its permeability through time. Therefore to make a breakthrough in PD and consequently contribute to better healthcare system it is urgent to find a group of biomarkers of peritoneum degradation. Here we report on two cost-effective methods for protein depletion in peritoneal dialysate effluent (PDE). The use of ACN and DTT over PDE to deplete high abundant proteins or to equalize the concentration of proteins, respectively, performs well and with similar protein profiles than when the same chemicals are used in human plasma samples. ACN depletes de PDE proteome from large proteins, such as albumin, and enriches the sample in apolipoproteins. DTT equalizes the PDE proteome by diminishing the levels of large proteins such as albumin and enriching the extract in immunoglobulins. Although the number and type of proteins identified are different, the annotation per gene ontology term reveals the same biological paths being affected for patients undergoing peritoneal dialysate. Thus, the largest number of proteins lost through peritoneal dialysate belongs to the group of extracellular proteins involved in regulation processes through binding. As for the searching of biomarkers, DTT seems to be the most promising of the two methods because acts as an equalizer and it allows interrogating more proteins in the same sample.

Silicon: Potential to Promote Direct and Indirect Effects on Plant Defense Against Arthropod Pests in Agriculture

Silicon has generally not been considered essential for plant growth, although it is well recognized that many plants, particularly Poaceae, have substantial plant tissue concentrations of this element. Recently, however, the International Plant Nutrition Institute [IPNI] (2015), Georgia, USA has listed it as a "beneficial substance". This reflects that numerous studies have now established that silicon may alleviate both biotic and abiotic stress. This paper explores the existing knowledge and recent advances in elucidating the role of silicon in plant defense against biotic stress, particularly against arthropod pests in agriculture and attraction of beneficial insects. Silicon confers resistance to herbivores via two described mechanisms: physical and biochemical/molecular. Until recently, studies have mainly centered on two trophic levels; the herbivore and plant. However, several studies now describe tri-trophic effects involving silicon that operate by attracting predators or parasitoids to plants under herbivore attack. Indeed, it has been demonstrated that silicon-treated, arthropod-attacked plants display increased attractiveness to natural enemies, an effect that was reflected in elevated biological control in the field. The reported relationships between soluble silicon and the jasmonic acid (JA) defense pathway, and JA and herbivore-induced plant volatiles (HIPVs) suggest that soluble silicon may enhance the production of HIPVs. Further, it is feasible that silicon uptake may affect protein expression (or modify proteins structurally) so that they can produce additional, or modify, the HIPV profile of plants. Ultimately, understanding silicon under plant ecological, physiological, biochemical, and molecular contexts will assist in fully elucidating the mechanisms behind silicon and plant response to biotic stress at both the bi- and tri-trophic levels.

Analytical platforms in vitreoretinal proteomics

Current proteomic technologies can effectively be used to study the proteins of the vitreous body and retina in health and disease. The use of appropriate samples, analytical platform and bioinformatic method are essential factors to consider when undertaking such studies. Certain proteins may hinder the detection and evaluation of more relevant proteins associated with pathological processes if not carefully considered, particularly in the sample preparation and data analysis stages. The utilization of more than one quantification technique and database search program to expand the level of proteome coverage and analysis will help to generate more robust and worthwhile results. This review discusses important aspects of sample processing and the use of label and label-free quantitative proteomics strategies applied to the vitreous and retina.

Advances in urinary proteome analysis and applications in systems biology

The urinary proteome is the focus of many studies due to the ease of urine collection and the relative proteome stability. Systems biology allows the combination of multiple omics studies, forming a link between proteomics, metabolomics, genomics and transcriptomics. In-depth data interpretation is achieved by bioinformatics analysis of -omics data sets. It is expected that the contribution of systems biology to the study of the urinary proteome will offer novel insights. The main focus of this review is on technical aspects of proteomics studies, available tools for systems biology analysis and the application of urinary proteomics in clinical studies and systems biology.

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

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

Proteomics analysis of the peritoneal dialysate effluent reveals the presence of calcium-regulation proteins and acute inflammatory response

Background

Peritoneal dialysis (PD) is a form of renal replacement used for advanced chronic kidney disease. PD effluent holds a great potential for biomarker discovery for diagnosis and prognosis. In this study a novel approach to unravelling the proteome of PD effluent based-on dithiothreitol depletion followed by 2D-SDS-PAGE and protein identification using tandem mass spectrometry is proposed.

Results

A total of 49 spots were analysed revealing 25 proteins differentially expressed, among them many proteins involved in calcium regulation.

Conclusions

Remarkably, a group of proteins dealing with calcium metabolism and calcium regulation has been found to be lost through peritoneal dialysate effluent, giving thus a potential explanation to the calcification of soft tissues in patients subjected to peritoneal dialysis and kidney injury. Comparison of literature dealing with PD is difficult due to differences in sample treatment and analytical methodologies.

Progress and challenges for abiotic stress proteomics of crop plants

Plants are continually challenged to recognize and respond to adverse changes in their environment to avoid detrimental effects on growth and development. Understanding the mechanisms that crop plants employ to resist and tolerate abiotic stress is of considerable interest for designing agriculture breeding strategies to ensure sustainable productivity. The application of proteomics technologies to advance our knowledge in crop plant abiotic stress tolerance has increased dramatically in the past few years as evidenced by the large amount of publications in this area. This is attributed to advances in various technology platforms associated with MS-based techniques as well as the accessibility of proteomics units to a wider plant research community. This review summarizes the work which has been reported for major crop plants and evaluates the findings in context of the approaches that are widely employed with the aim to encourage broadening the strategies used to increase coverage of the proteome.

Role and challenges of proteomics in pharma and biotech: technical, scientific and commercial perspective

Contemporary proteomics, currently in its exponential growth phase, is a bewildering array of tools. Proteomic methods are the result of a convergence of rapidly improving mass spectrometry technologies, protein chemistry and separation sciences, genomics and bioinformatics. Strides in improving proteomics technologies to map and measure proteomes and subproteomes are being made. However, no single proteomic platform appears ideally suited to address all research needs or accomplish ambitious goals satisfactorily. However, proteomics is in a unique position to contribute to protein discovery and to public health in terms of better biomarkers, diagnostics and treatment of disease. While the potential is great, many challenges and issues remain to be solved. Fundamental issues, such as biological variability, pre-analytic factors and analytical reproducibility, remain to be resolved. Neither an all-genetic approach nor an all-proteomic approach will solve biological complexity. Proteomics will be the foundation for constructing and extracting useful knowledge to pharma and biotech depicted in the following path: data --> structured data --> information --> information architecture --> knowledge --> useful knowledge.

Effects of post-electrophoretic analysis on variance in gel-based proteomics

2D electrophoresis (2DE) is a prominent separation method for complex proteomes. Although recent advances have increased the utility of this method in quantitative proteomics studies, many sources of variance still exist. This review discusses the post-electrophoretic sources of variance in current 2DE analysis. The essential improvements in protein visualization and software algorithms that have made 2DE a leading quantitative proteomics method are briefly reviewed. A number of shortcomings in the post-electrophoretic analysis of 2DE data that require further attention are highlighted. Topics discussed include protein visualization and image acquisition, internal standards and normalization methods, background subtraction algorithms, normality of distribution, and the need for standardized tests for the evaluation of 2DE analysis software packages.

Proteomics in atherothrombosis: a future perspective

Atherothrombosis is the primary cause of death in Western countries. The cellular and molecular mechanisms underlying atherosclerosis remain widely unknown. The complex nature of atherosclerotic cardiovascular diseases demands the development of novel technologies that enable discovery of new biomarkers for early disease detection and risk stratification, which may predict clinical outcome. In this review, we outline potential sources and recent proteomic approaches that could be applied in the search of novel biomarkers of cardiovascular risk. In addition, we describe some issues raised in relation to the application of proteomics to blood samples, as well as two novel emerging concepts, such as peptidomics and population proteomics. In the future, the use of high-throughput techniques (proteomic, genomics and metabolomics) will potentially identify novel patterns of biomarkers, which, along with traditional risk factors and imaging techniques, could help to target vulnerable patients and monitor the beneficial effects of pharmacological agents.

Analysis of mass spectrometry data from the secretome of an explant model of articular cartilage exposed to pro-inflammatory and anti-inflammatory stimuli using machine learning

BACKGROUND

Osteoarthritis (OA) is an inflammatory disease of synovial joints involving the loss and degeneration of articular cartilage. The gold standard for evaluating cartilage loss in OA is the measurement of joint space width on standard radiographs. However, in most cases the diagnosis is made well after the onset of the disease, when the symptoms are well established. Identification of early biomarkers of OA can facilitate earlier diagnosis, improve disease monitoring and predict responses to therapeutic interventions.

METHODS

This study describes the bioinformatic analysis of data generated from high throughput proteomics for identification of potential biomarkers of OA. The mass spectrometry data was generated using a canine explant model of articular cartilage treated with the pro-inflammatory cytokine interleukin 1 β (IL-1β). The bioinformatics analysis involved the application of machine learning and network analysis to the proteomic mass spectrometry data. A rule based machine learning technique, BioHEL, was used to create a model that classified the samples into their relevant treatment groups by identifying those proteins that separated samples into their respective groups. The proteins identified were considered to be potential biomarkers. Protein networks were also generated; from these networks, proteins pivotal to the classification were identified.

RESULTS

BioHEL correctly classified eighteen out of twenty-three samples, giving a classification accuracy of 78.3% for the dataset. The dataset included the four classes of control, IL-1β, carprofen, and IL-1β and carprofen together. This exceeded the other machine learners that were used for a comparison, on the same dataset, with the exception of another rule-based method, JRip, which performed equally well. The proteins that were most frequently used in rules generated by BioHEL were found to include a number of relevant proteins including matrix metalloproteinase 3, interleukin 8 and matrix gla protein.

CONCLUSIONS

Using this protocol, combining an in vitro model of OA with bioinformatics analysis, a number of relevant extracellular matrix proteins were identified, thereby supporting the application of these bioinformatics tools for analysis of proteomic data from in vitro models of cartilage degradation.

An integrated approach for comparative proteomic analysis of human bile reveals overexpressed cancer-associated proteins in malignant biliary stenosis

Proteomics is a key tool in the identification of new bile biomarkers for differentiating malignant and nonmalignant biliary stenoses. Unfortunately, the complexity of bile and the presence of molecules interfering with protein analysis represent an obstacle for quantitative proteomic studies in bile samples. The simultaneous need to introduce purification steps and minimize the use of pre-fractionation methods inevitably leads to protein loss and limited quantifications. This dramatically reduces the chance of identifying new potential biomarkers. In the present study, we included differential centrifugation as a preliminary step in a quantitative proteomic workflow involving iTRAQ labeling, peptide fractionation by OFFGEL electrophoresis and LC-MS/MS, to compare protein expression in bile samples collected from patients with malignant or nonmalignant biliary stenoses. A total of 1267 proteins were identified, including a set of 322 newly described bile proteins, mainly belonging to high-density cellular fractions. The subsequent comparative analysis led to a 5-fold increase in the number of quantified proteins over previously published studies and highlighted 104 proteins overexpressed in malignant samples. Finally, immunoblot verifications performed on a cohort of 8 malignant (pancreatic adenocarcinoma, n=4; cholangiocarcinoma, n=4) and 5 nonmalignant samples (chronic pancreatitis, n=3; biliary stones, n=2) confirmed the results of proteomic analysis for three proteins: olfactomedin-4, syntenin-2 and Ras-related C3 botulinum toxin substrate 1. This article is part of a Special Issue entitled: Biomarkers: A Proteomic Challenge.

Multiplexed electrokinetic sample fractionation, preconcentration and elution for proteomics

Both 6 and 8-channel integrated microfluidic sample pretreatment devices capable of performing "in space" sample fractionation, collection, preconcentration and elution of captured analytes via sheath flow assisted electrokinetic pumping are described. Coatings and monolithic polymer beds were developed for the glass devices to provide cationic surface charge and anodal electroosmotic flow for delivery to an electrospray emitter tip. A mixed cationic ([2-(methacryloyloxy)ethyl] trimethylammonium chloride) (META) and hydrophobic butyl methacrylate-based monolithic porous polymer, photopolymerized in the 6- or 8-fractionation channels, was used to capture and preconcentrate samples. A 0.45 wt% META loaded bed generated comparable anodic electroosmotic flow to the cationic polymer PolyE-323 coated channel segments in the device. The balanced electroosmotic flow allowed stable electrokinetic sheath flow to prevent cross contamination of separated protein fractions, while reducing protein/peptide adsorption on the channel walls. Sequential elution of analytes trapped in the SPE beds revealed that the monolithic columns could be efficiently used to provide sheath flow during elution of analytes, as demonstrated for neutral carboxy SNARF (residual signal, 0.08% RSD, n = 40) and charged fluorescein (residual signal, 2.5% n = 40). Elution from monolithic columns showed reproducible performance with peak area reproducibility of ~8% (n = 6 columns) in a single sequential elution and the run-to-run reproducibility was 2.4-6.7% RSD (n = 4) for elution from the same bed. The demonstrated ability of this device design and operation to elute from multiple fractionation beds into a single exit channel for sample analysis by fluorescence or electrospray mass spectrometry is a crucial component of an integrated fractionation and assay system for proteomics.

Coupling supported lipid bilayer electrophoresis with matrix-assisted laser desorption/ionization-mass spectrometry imaging

Herein, we describe a new analytical platform utilizing advances in heterogeneous supported lipid bilayer (SLB) electrophoresis and matrix-assisted laser desorption/ionization-mass spectrometry (MALDI-MS) imaging. This platform allowed for the separation and visualization of both charged and neutral lipid membrane components without the need for extrinsic labels. A heterogeneous SLB was created using vesicles containing monosialoganglioside GM1, disialoganglioside GD1b, POPC, as well as the ortho and para isomers of Texas Red-DHPE. These components were then separated electrophoretically into five resolved bands. This represents the most complex separation by SLB electrophoresis performed to date. The SLB samples were flash frozen in liquid ethane and dried under vacuum before imaging with MALDI-MS. Fluorescence microscopy was employed to confirm the position of the Texas Red labeled lipids, which agreed well with the MALDI-MS imaging results. These results clearly demonstrate this platform's ability to isolate and identify nonlabeled membrane components within an SLB.

Detection of Bovine Alpha-S1-Casein in Term and Preterm Human Colostrum with Proteomic Techniques

Due to increased social awareness of allergens and population hyper-sensitization, the reported incidence of allergic reactions to food allergens has increased over the past two decades. Cow's milk proteins (CMPs) are among the most common food allergens. The aim of this study was to use proteomics techniques to investigate cow's milk allergens in both full-term human colostrum and in preterm newborns' mothers - where both groups showed no prior allergen detection – in order to understand whether cow's milk allergens could be a cause of sensitization established through lactation. The most relevant finding was the detection of the intact bovine alpha-S1-casein in both term and preterm colostrum. Using techniques detailed in this paper and which allowed for direct protein identification, β-lactoglobulin was not detected in any of the colostrum samples. According to our results, bovine alpha 1 casein is considered a major cow's milk allergen, is readily secreted in human milk, and so could be considered a possible cause of sensitization in exclusively breastfed infants.

Defining the extracellular matrix using proteomics

The cell microenvironment has a profound influence on the behaviour, growth and survival of cells. The extracellular matrix (ECM) provides not only mechanical and structural support to cells and tissues but also binds soluble ligands and transmembrane receptors to provide spatial coordination of signalling processes. The ability of cells to sense the chemical, mechanical and topographical features of the ECM enables them to integrate complex, multiparametric information into a coherent response to the surrounding microenvironment. Consequently, dysregulation or mutation of ECM components results in a broad range of pathological conditions. Characterization of the composition of ECM derived from various cells has begun to reveal insights into ECM structure and function, and mechanisms of disease. Proteomic methodologies permit the global analysis of subcellular systems, but extracellular and transmembrane proteins present analytical difficulties to proteomic strategies owing to the particular biochemical properties of these molecules. Here, we review advances in proteomic approaches that have been applied to furthering our understanding of the ECM microenvironment. We survey recent studies that have addressed challenges in the analysis of ECM and discuss major outcomes in the context of health and disease. In addition, we summarize efforts to progress towards a systems-level understanding of ECM biology.

The application of quantification techniques in proteomics for biomedical research

The systematic analysis of biological processes requires an understanding of the quantitative expression patterns of proteins, their interacting partners and their subcellular localization. This information was formerly difficult to accrue as the relative quantification of proteins relied on antibody-based methods and other approaches with low throughput. The advent of soft ionization techniques in mass spectrometry plus advances in separation technologies has aligned protein systems biology with messenger RNA, DNA, and microarray technologies to provide data on systems as opposed to singular protein entities. Another aspect of quantitative proteomics that increases its importance for the coming few years is the significant technical developments underway both for high pressure liquid chromatography and mass spectrum devices. Hence, robustness, reproducibility and mass accuracy are still improving with every new generation of instruments. Nonetheless, the methods employed require validation and comparison to design fit for purpose experiments in advanced protein analyses. This review considers the newly developed systematic protein investigation methods and their value from the standpoint that relative or absolute protein quantification is required de rigueur in biomedical research.

Combinatorial peptide ligand libraries to discover liver disease biomarkers in plasma samples

High-abundance proteins present in blood plasma make the detection of low-abundance proteins extremely difficult by proteomics technology. Hexapeptide combinatorial ligand libraries can be used to investigate the hidden proteome in depth. Here we describe how liver disease biomarkers can be successfully discovered in blood plasma by two main steps: preparative methods that reduce the dynamic range of protein concentration, and analytic methods that allow resolution of proteins. Thus, blood plasma from hepatitis B virus infected patients were treated with ProteoMiner™ enrichment kit and analyzed by two dimensional gel electrophoresis and mass spectrometry. This approach allowed us to identify plasma gelsolin as possible candidate biomarker for hepatitis B-associated liver cirrhosis.

Sequential extraction results in improved proteome profiling of medicinal plant Pinellia ternata tubers, which contain large amounts of high-abundance proteins

Pinellia ternata tuber is one of the well-known Chinese traditional medicines. In order to understand the pharmacological properties of tuber proteins, it is necessary to perform proteome analysis of P. ternata tubers. However, a few high-abundance proteins (HAPs), mainly mannose-binding lectin (agglutinin), exist in aggregates of various sizes in the tubers and seriously interfere with proteome profiling by two-dimensional electrophoresis (2-DE). Therefore, selective depletion of these HAPs is a prerequisite for enhanced proteome analysis of P. ternata tubers. Based on differential protein solubility, we developed a novel protocol involving two sequential extractions for depletion of some HAPs and prefractionation of tuber proteins prior to 2-DE. The first extraction using 10% acetic acid selectively extracted acid-soluble HAPs and the second extraction using the SDS-containing buffer extracted remaining acid-insoluble proteins. After application of the protocol, 2-DE profiles of P. ternata tuber proteins were greatly improved and more protein spots were detected, especially low-abundance proteins. Moreover, the subunit composition of P. ternata lectin was analyzed by electrophoresis. Native lectin consists of two hydrogen-bonded subunits (11 kDa and 25 kDa) and the 11 kDa subunit was a glycoprotein. Subsequently, major HAPs in the tubers were analyzed by mass spectrometry, with nine protein spots being identified as lectin isoforms. The methodology was easy to perform and required no specialized apparatus. It would be useful for proteome analysis of other tuber plants of Araceae.

Sequential depletion of human serum for the search of osteoarthritis biomarkers

Background

The field of biomarker discovery, development and application has been the subject of intense interest and activity, especially with the recent emergence of new technologies, such as proteomics-based approaches. In proteomics, search for biomarkers in biological fluids such as human serum is a challenging issue, mainly due to the high dynamic range of proteins present in these types of samples. Methods for reducing the content of most highly abundant proteins have been developed, including immunodepletion or protein equalization. In this work, we report for the first time the combination of a chemical sequential depletion method based in two protein precipitations with acetonitrile and DTT, with a subsequent two-dimensional difference in-gel electrophoresis (2D-DIGE) analysis for the search of osteoarthritis (OA) biomarkers in human serum. The depletion method proposed is non-expensive, of easy implementation and allows fast sample throughput.

Results

Following this workflow, we have compared sample pools of human serum obtained from 20 OA patients and 20 healthy controls. The DIGE study led to the identification of 16 protein forms (corresponding to 14 different proteins) that were significantly (p < 0.05) altered in OA when compared to controls (8 increased and 7 decreased). Immunoblot analyses confirmed for the first time the increase of an isoform of Haptoglobin beta chain (HPT) in sera from OA patients.

Conclusions

Altogether, these data demonstrate the utility of the proposed chemical sequential depletion for the analysis of sera in protein biomarker discovery approaches, exhibit the usefulness of quantitative 2D gel-based strategies for the characterization of disease-specific patterns of protein modifications, and also provide a list of OA biomarker candidates for validation.

Investigation of ovarian cancer associated sialylation changes in N-linked glycopeptides by quantitative proteomics

Background

In approximately 80% of patients, ovarian cancer is diagnosed when the patient is already in the advanced stages of the disease. CA125 is currently used as the marker for ovarian cancer; however, it lacks specificity and sensitivity for detecting early stage disease. There is a critical unmet need for sensitive and specific routine screening tests for early diagnosis that can reduce ovarian cancer lethality by reliably detecting the disease at its earliest and treatable stages.

Results

In this study, we investigated the N-linked sialylated glycopeptides in serum samples from healthy and ovarian cancer patients using Lectin-directed Tandem Labeling (LTL) and iTRAQ quantitative proteomics methods. We identified 45 N-linked sialylated glycopeptides containing 46 glycosylation sites. Among those, ten sialylated glycopeptides were significantly up-regulated in ovarian cancer patients’ serum samples. LC-MS/MS analysis of the non-glycosylated peptides from the same samples, western blot data using lectin enriched glycoproteins of various ovarian cancer type samples, and PNGase F (+/−) treatment confirmed the sialylation changes in the ovarian cancer samples.

Conclusion

Herein, we demonstrated that several proteins are aberrantly sialylated in N-linked glycopeptides in ovarian cancer and detection of glycopeptides with abnormal sialylation changes may have the potential to serve as biomarkers for ovarian cancer.