Equalizer technology - Equal rights for disparate beads

Exploring affinity chromatography in proteomics: A comprehensive review

Over the past decades, the proteomics field has undergone rapid growth. Progress in mass spectrometry and bioinformatics, together with separation methods, has brought many innovative approaches to the study of the molecular biology of the cell. The potential of affinity chromatography was recognized immediately after its first application in proteomics, and since that time, it has become one of the cornerstones of many proteomic protocols. Indeed, this chromatographic technique exploiting the specific binding between two molecules has been employed for numerous purposes, from selective removal of interfering (over)abundant proteins or enrichment of scarce biomarkers in complex biological samples to mapping the post-translational modifications and protein interactions with other proteins, nucleic acids or biologically active small molecules. This review presents a comprehensive survey of this versatile analytical tool in current proteomics. To navigate the reader, the haphazard space of affinity separations is classified according to the experiment's aims and the separated molecule's nature. Different types of available ligands and experimental strategies are discussed in further detail for each of the mentioned procedures.

Proteomics evaluation of five economical commercial abundant protein depletion kits for enrichment of diseases-specific biomarkers from blood serum

Blood serum is arguably the most analyzed biofluid for disease prediction and diagnosis. Herein, we benchmarked five different serum abundant protein depletion (SAPD) kits with regard to the identification of disease-specific biomarkers in human serum using bottom-up proteomics. As expected, the IgG removal efficiency among the SAPD kits is highly variable, ranging from 70% to 93%. A pairwise comparison of database search results showed a 10%-19% variation in protein identification among the kits. Immunocapturing-based SAPD kits against IgG and albumin outperformed the others in the removal of these two abundant proteins. Conversely, non-antibody-based methods (i.e., kits using ion exchange resins) and kits leveraging a multi-antibody approach were proven to be less efficient in depleting IgG/albumin from samples but led to the highest number of identified peptides. Notably, our results indicate that different cancer biomarkers could be enriched up to 10% depending on the utilized SAPD kit compared with the undepleted sample. Additionally, functional analysis of the bottom-up proteomic results revealed that different SAPD kits enrich distinct disease- and pathway-specific protein sets. Overall, our study emphasizes that a careful selection of the appropriate commercial SAPD kit is crucial for the analysis of disease biomarkers in serum by shotgun proteomics.

BioMIPs: molecularly imprinted silk fibroin nanoparticles to recognize the iron regulating hormone hepcidin

The possibility to prepare molecularly imprinted nanoparticles from silk fibroin was recently demonstrated starting from methacrylated silk fibroin and choosing a protein as template. Here, we attempted the imprinting of fibroin-based molecularly imprinted polymers (MIPs), called bioMIPs, using as a template hepcidin that is a iron-metabolism regulator-peptide, possessing a hairpin structure. A homogeneous population (PDI < 0.2) of bioMIPs with size ~50 nm was produced. The bioMIPs were selective for the template; the estimated dissociation constant for hepcidin was KD = 3.6 ± 0.5 10-7 M and the average number of binding sites per bioMIP was equal to 2. The bioMIPs used in a competitive assay for hepcidin in serum showed a detection range of 1.01 10-7- 6.82 10-7 M and a limit of detection of 3.29 10-8 M.

Nanodiamond Solid-Phase Extraction and Triton X-114 Cloud Point Separation for Robust Fractionation and Shotgun Proteomics Analysis of the Human Serum Proteome

Human serum is one of the most attractive specimens in biomarker research. However, its overcomplicated properties have hindered the analysis of low-abundance proteins by conventional mass spectrometry techniques. This work proposes an innovative strategy for utilizing nanodiamonds (NDs) in combination with Triton X-114 protein extraction to fractionate the crude serum to six pH-tuned fractions, simplifying the overall proteome and facilitating protein profiling with high efficiency. A total of 663 proteins are identified and evenly distributed among the fractions along with 39 FDA-approved biomarkers─a remarkable increase from the 230 proteins found in unfractionated crude serum. In the low-abundance protein section, 88 proteins with 7 FDA-approved biomarkers are detected─a marked increase from the 15 proteins (2 biomarkers) observed in the untreated sample. Notably, fractions at pH 11, derived from the aqueous phase of detergent separation, suggest potential applications in rapid and robust serum proteome analysis. Notably, by outlining the excellent properties of NDs for proteomic research, this work suggests a promising extraction protocol utilizing the great compatibility of NDs with streamlined serum proteomics and identifies potential avenues for future developments. Finally, we believe that this work not just improves shotgun proteomics but also opens up studies on the interaction between NDs and the human proteome. Data are available via ProteomeXchange with the identifier PXD029710.

Proteomics informed by transcriptomics for a qualitative and quantitative analysis of the sialoproteome of adult Ornithodoros moubata ticks

Background

The argasid tick Ornithodoros moubata is the main vector in mainland Africa of African swine fever virus and the spirochete Borrelia duttoni, which causes human relapsing fever. The elimination of populations of O. moubata would contribute to the prevention and control of these two serious diseases. Anti-tick vaccines are an eco-friendly and sustainable means of eliminating tick populations. Tick saliva forms part of the tick-host interface, and knowledge of its composition is key to the identification and selection of vaccine candidate antigens. The aim of the present work is to increase the body of data on the composition of the saliva proteome of adult O. moubata ticks, particularly of females, since in-depth knowledge of the O. moubata sialome will allow the identification and selection of novel salivary antigens as targets for tick vaccines.

Methods

We analysed samples of female and male saliva using two different mass spectrometry (MS) approaches: data-dependent acquisition liquid chromatography-tandem MS (LC–MS/MS) and sequential window acquisition of all theoretical fragment ion spectra–MS (SWATH-MS). To maximise the number of proteins identified, a proteomics informed by transcriptomics analysis was applied using the O. moubata salivary transcriptomic dataset previously obtained by RNA-Seq.

Results

SWATH-MS proved to be superior to LC–MS/MS for the study of female saliva, since it identified 61.2% more proteins than the latter, the reproducibility of results was enhanced with its use, and it provided a quantitative picture of salivary components. In total, we identified 299 non-redundant proteins in the saliva of O. moubata, and quantified the expression of 165 of these in both male and female saliva, among which 13 were significantly overexpressed in females and 40 in males. These results indicate important quantitative differences in the saliva proteome between the sexes.

Conclusions

This work expands our knowledge of the O. moubata sialome, particularly that of females, by increasing the number of identified novel salivary proteins, which have different functions at the tick–host feeding interface. This new knowledge taken together with information on the O. moubata sialotranscriptome will allow a more rational selection of salivary candidates as antigen targets for tick vaccine development.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s13071-021-04892-2.

Analysis of differential strategies to enhance detection of low-abundance proteins in the bovine serum proteome

Serum-based biomarkers hold propitious applications for addressing livestock health, and management. However, discovery of protein biomarkers in complex biological fluids like serum is wholly intractable due to the large dynamic range of protein concentrations; that is, ˜10-12 high abundance proteins constitute >90% of the total protein content and effectively mask proteomic detection of low-abundance biomarkers. Toward addressing this limitation, we test a continuous elution size-based fractionation method, and two approaches that use affinity interaction-based separation of proteins in preparing bovine serum, and compare liquid chromatography tandem mass spectrometry protein identification to neat serum. Our results identify the high-abundance proteins in bovine serum, and demonstrate dynamic range compression and improved protein identification with the different enrichment methods. Although these findings indicate the highest protein number identified in bovine serum (445 proteins, all methods combined), and by any single sample processing method (312 proteins) to date, they still remain lower than levels deemed necessary for biomarker discovery. As such, this investigation revealed limitations to resolving the bovine serum proteome, and the need for species-specific tools for immunodepleting high-abundance proteins. In concert, this study represents a step toward advancing sample preparation methods for bovine serum biomarker identification.

Proteins Involved in the Induction of Procoagulant Activity and Autoimmune Response in Patients With Primary Antiphospholipid Syndrome

The aim of this study was to determine the plasma protein profile of patients with primary antiphospholipid syndrome (PAPS) compared to healthy controls and identify proteins that might be used in the evaluation, diagnosis, and prognosis of this condition. The sample consisted of 14 patients with PAPS and 17 sex- and age-matched controls. Plasma samples were submitted to proteomic analysis (albumin and immunoglobulin G depletion, concentration, digestion, and label-free data-independent mass spectrometry). The software ExpressionE was used to quantify intergroup differences in protein expression. The analysis yielded 65 plasma proteins of which 11 were differentially expressed (9 upregulated and 2 downregulated) in relation to controls. Four of these are known to play a role in pathophysiological mechanisms of thrombosis: fibrinogen α chain, fibrinogen α chain, apolipoprotein C-III, and α-1-glycoprotein-1. Our analysis revealed autoimmune response and the presence of proteins believed to be functionally involved in the induction of procoagulant activity in patients with PAPS. Further studies are necessary to confirm our findings and may eventually lead to the development of significantly more accurate diagnostic tools.

Effects of Alanyl-Glutamine Treatment on the Peritoneal Dialysis Effluent Proteome Reveal Pathomechanism-Associated Molecular Signatures

Peritoneal dialysis (PD) is a modality of renal replacement therapy in which the high volumes of available PD effluent (PDE) represents a rich source of biomarkers for monitoring disease and therapy. Although this information could help guide the management of PD patients, little is known about the potential of PDE to define pathomechanism-associated molecular signatures in PD.

We therefore subjected PDE to a high-performance multiplex proteomic analysis after depletion of highly-abundant plasma proteins and enrichment of low-abundance proteins. A combination of label-free and isobaric labeling strategies was applied to PDE samples from PD patients (n = 20) treated in an open-label, randomized, two-period, cross-over clinical trial with standard PD fluid or with a novel PD fluid supplemented with alanyl-glutamine (AlaGln).

With this workflow we identified 2506 unique proteins in the PDE proteome, greatly increasing coverage beyond the 171 previously-reported proteins. The proteins identified range from high abundance plasma proteins to low abundance cellular proteins, and are linked to larger numbers of biological processes and pathways, some of which are novel for PDE. Interestingly, proteins linked to membrane remodeling and fibrosis are overrepresented in PDE compared with plasma, whereas the proteins underrepresented in PDE suggest decreases in host defense, immune-competence and response to stress. Treatment with AlaGln-supplemented PD fluid is associated with reduced activity of membrane injury-associated mechanisms and with restoration of biological processes involved in stress responses and host defense.

Our study represents the first application of the PDE proteome in a randomized controlled prospective clinical trial of PD. This novel proteomic workflow allowed detection of low abundance biomarkers to define pathomechanism-associated molecular signatures in PD and their alterations by a novel therapeutic intervention.

Digging More Missing Proteins Using an Enrichment Approach with ProteoMiner

Human Proteome Project (HPP) aims at mapping entire human proteins with a systematic effort upon all the emerging techniques, which would enhance understanding of human biology and lay a foundation for development of medical applications. Until now, 2563 missing proteins (MPs, PE2-4) are still undetected even using the most sensitive approach of protein detection. Herein, we propose that enrichment of low-abundance proteins benefits MPs finding. ProteoMiner is an equalizing technique by reducing high-abundance proteins and enriching low-abundance proteins in biological liquids. With triton X-100/TBS buffer extraction, ProteoMiner enrichment, and peptide fractionation, 20 MPs (at least two non-nested unique peptides with more than eight a.a. length) with 60 unique peptides were identified from four human tissues including eight membrane/secreted proteins and five nucleus proteins. Then 15 of them were confirmed with two non-nested unique peptides (≥9 a.a.) identified by matching well with their chemically synthetic peptides in PRM assay. Hence, these results demonstrated ProteoMiner as a powerful means in discovery of MPs.

What was old is new again: using the host response to diagnose infectious disease

A century of advances in infectious disease diagnosis and treatment changed the face of medicine. However, challenges continue to develop including multi-drug resistance, globalization that increases pandemic risks and high mortality from severe infections. These challenges can be mitigated through improved diagnostics, focusing on both pathogen discovery and the host response. Here, we review how 'omics' technologies improve sepsis diagnosis, early pathogen identification and personalize therapy. Such host response diagnostics are possible due to the confluence of advanced laboratory techniques (e.g., transcriptomics, metabolomics, proteomics) along with advanced mathematical modeling such as machine learning techniques. The road ahead is promising, but obstacles remain before the impact of such advanced diagnostic modalities is felt at the bedside.

Is isolation of comprehensive human plasma peptidomes an achievable quest?

The low molecular weight (LMW; <10kDa)* plasma peptidome has been considered a source of useful diagnostic biomarkers and potentially therapeutic molecules, as it contains many cytokines, peptide hormones, endogenous peptide products and potentially bioactive fragments derived from the parent proteome. The small size of the peptides allows them almost unrestricted vascular and interstitial access, and hence distribution across blood-brain barriers, tumour and other vascular permeability barriers. Therefore, the peptidome may carry specific signatures or fingerprints of an individual's health, wellbeing or disease status. This occurs primarily because of the advantage the peptidome has in being readily accessible in human blood and/or other biofluids. However, the co-expression of highly abundant proteins (>10kDa) and other factors present inherently in human plasma make direct analysis of the blood peptidome one of the most challenging tasks faced in contemporary analytical biochemistry. A comprehensive compendium of extraction and fractionation tools has been collected concerning the isolation and micromanipulation of peptides. However, the search for a reliable, accurate and reproducible single or combinatorial separation process for capturing and analysing the plasma peptidome remains a challenge. This review outlines current techniques used for the separation and detection of plasma peptides and suggests potential avenues for future investigation. This article is part of a Special Issue entitled: HUPO 2014.

The role of proteomics in understanding biological mechanisms of sepsis

Sepsis is a systemic inflammatory state caused by infection. Complications of this infection with multiple organ failure lead to more lethal conditions, such as severe sepsis and septic shock. Sepsis is one of the leading causes of US deaths. Novel biomarkers with high sensitivity and specificity may be helpful for early diagnosis of sepsis and for improvement of patient outcomes through the development of new therapies. Mass spectrometry-based proteomics offers powerful tools to identify such biomarkers and furthermore to give insight to fundamental mechanisms of this clinical condition. In this review, we summarize findings from proteomics studies of sepsis and how their applications have provided more understanding into the pathogenesis of septic infection. Literatures related to "proteomics", "sepsis", "systemic inflammatory response syndrome", "severe sepsis", "septic infection", and "multiple organ dysfunction syndrome" were searched using PubMed. Findings about neonatal and adult sepsis are discussed separately. Within the adult sepsis studies, results are grouped based on the models (e.g., human or animal). Across investigations in clinical populations and in rodent and mammalian animal models, biological pathways, such as inflammatory and acute phase response, coagulation, complement, mitochondrial energy metabolism, chaperones, and oxidative stress, are altered at the protein level. These proteomics studies have discovered many novel biomarker candidates of septic infection. Validation the clinical use of these biomarker candidates may significantly impact the diagnosis and prognosis of sepsis. In addition, the molecular mechanisms revealed by these studies may also guide the development of more effective treatments.

Proteomic demonstration of the recurrent presence of inter-alpha-inhibitor H4 heavy-chain during aspergillosis induced in an animal model

Invasive pulmonary aspergillosis remains a matter of great concern in oncology/haematology, intensive care units and organ transplantation departments. Despite the availability of various diagnostic tools with attractive features, new markers of infection are required for better medical care. We therefore looked for potential pulmonary biomarkers of aspergillosis, by carrying out two-dimensional (2D) gel electrophoresis comparing the proteomes of bronchial-alveolar lavage fluids (BALF) from infected rats and from control rats presenting non-specific inflammation, both immunocompromised. A bioinformatic analysis of the 2D-maps revealed significant differences in the abundance of 20 protein spots (ANOVA P-value<0.01; q-value<0.03; power>0.8). One of these proteins, identified by mass spectrometry, was considered of potential interest: inter-alpha-inhibitor H4 heavy-chain (ITIH4), characterised for the first time in this infectious context. Western blotting confirmed its overabundance in all infected BALF, particularly at early stages of murine aspergillosis. Further investigations were carried on rat serum, and confirmed that ITIH4 levels increased during experimental aspergillosis. Preliminary results in human samples strengthened this trend. To our knowledge, this is the first description of the involvement of ITIH4 in aspergillosis.

The challenge of the proteome dynamic range and its implications for in-depth proteomics

The dynamic range of the cellular proteome approaches seven orders of magnitude-from one copy per cell to ten million copies per cell. Since a proteome's abundance distribution represents a nearly symmetric bell-shape curve on the logarithmic copy number scale, detection of half of the expressed cellular proteome, i.e. approximately 5000 proteins, should be a relatively straightforward task with modern mass spectrometric instrumentation that exhibits four orders of magnitude of the dynamic range, while deeper proteome analysis should be progressively more difficult. Indeed, metaanalysis of 15 recent papers that claim detection of >5000 protein groups reveals that the half-proteome analyses currently requires ≈5 h of chromatographic separation, while deeper analyses yield on average ≤20 new proteins per hour of chromatographic gradient. Therefore, a typical proteomics experiment consists of a "high-content" part, with the detection rate of approximately 1000 proteins/h, and a "low-content" tail with much lower rate of discovery and respectively, lower cost efficiency. This result calls for disruptive innovation in deep proteomics analysis.

Human serum proteome analysis: new source of markers in metabolic disorders

The prevalence of metabolic disorders (MDs), especially diabetes, is rapidly increasing worldwide, leading to an increasing risk of cardiovascular and other socially relevant complications. To boost MD biomarker discovery, advanced proteomics can harmonize metabolomics. Indeed, the rapid development of mass spectrometry (MS) has designated proteomics as an emerging platform to interrogate the plasma/serum proteome for the discovery of next-generation biomarkers exploitable for risk assessment, early detection and prognosis of MDs. Preanalytical plasma/serum treatment, such as combinatorial peptide ligand libraries with nano-liquid chromatography coupled with tandem MS or selected reaction monitoring coupled to triple-quadrupole time-of-flight instruments, are proven clinical laboratory techniques for quantitative analyses. New strategies, such as SWATH™ MS, which allows us to systematically characterize and quantify query sample sets of 'any protein of interest' in complex biological samples, may dramatically improve next-generation MD biomarkers, especially considering the plethora of candidates coming from the 'bioreactor' gut microbiota affecting MD onset and progression.

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.

Looking deep inside: detection of low-abundance proteins in leaf extracts of Arabidopsis and phloem exudates of pumpkin

The field of proteomics suffers from the immense complexity of even small proteomes and the enormous dynamic range of protein concentrations within a given sample. Most protein samples contain a few major proteins, which hamper in-depth proteomic analysis. In the human field, combinatorial hexapeptide ligand libraries (CPLL; such as ProteoMiner) have been used for reduction of the dynamic range of protein concentrations; however, this technique is not established in plant research. In this work, we present the application of CPLL to Arabidopsis (Arabidopsis thaliana) leaf proteins. One- and two-dimensional gel electrophoresis showed a decrease in high-abundance proteins and an enrichment of less abundant proteins in CPLL-treated samples. After optimization of the CPLL protocol, mass spectrometric analyses of leaf extracts led to the identification of 1,192 proteins in control samples and an additional 512 proteins after the application of CPLL. Upon leaf infection with virulent Pseudomonas syringae DC3000, CPLL beads were also used for investigating the bacterial infectome. In total, 312 bacterial proteins could be identified in infected Arabidopsis leaves. Furthermore, phloem exudates of pumpkin (Cucurbita maxima) were analyzed. CPLL prefractionation caused depletion of the major phloem proteins 1 and 2 and improved phloem proteomics, because 67 of 320 identified proteins were detectable only after CPLL treatment. In sum, our results demonstrate that CPLL beads are a time- and cost-effective tool for reducing major proteins, which often interfere with downstream analyses. The concomitant enrichment of less abundant proteins may facilitate a deeper insight into the plant proteome.

Investigation of plasma biomarkers in HIV-1/HCV mono- and coinfected individuals by multiplex iTRAQ quantitative proteomics

The analysis of plasma samples from HIV-1/HCV mono- and coinfected individuals by quantitative proteomics is an efficient strategy to investigate changes in protein abundances and to characterize the proteins that are the effectors of cellular functions involved in viral pathogenesis. In this study, the infected and healthy plasma samples (in triplicate) were treated with ProteoMiner beads to equalize protein concentrations and subjected to 4-plex iTRAQ labeling and liquid chromatography/mass spectrometry (LC-MS/MS) analysis. A total of 70 proteins were identified with high confidence in the triplicate analysis of plasma proteins and 65% of the proteins were found to be common among the three replicates. Apolipoproteins and complement proteins are the two major classes of proteins that exhibited differential regulation. The results of quantitative analysis revealed that APOA2, APOC2, APOE, C3, HRG proteins were upregulated in the plasma of all the three HIV-1 mono-, HCV mono-, and coinfected patient samples compared to healthy control samples. Ingenuity pathway analysis (IPA) of the upregulated proteins revealed that they are implicated in the hepatic lipid metabolism, inflammation, and acute-phase response signaling pathways. Thus, we identified several differentially regulated proteins in HIV-1/HCV mono and coinfected plasma samples that may be potential biomarkers for liver disease.

Sample preparation techniques for the untargeted LC-MS-based discovery of peptides in complex biological matrices

Although big progress has been made in sample pretreatment over the last years, there are still considerable limitations when it comes to overcoming complexity and dynamic range problems associated with peptide analyses from biological matrices. Being the little brother of proteomics, peptidomics is a relatively new field of research aiming at the direct analysis of the small proteins, called peptides, many of which are not amenable for typical trypsin-based analytics. In this paper, we present an overview of different techniques and methods currently used for reducing a sample's complexity and for concentrating low abundant compounds to enable successful peptidome analysis. We focus on techniques which can be employed prior to liquid chromatography coupled to mass spectrometry for peptide detection and identification and indicate their advantages as well as their shortcomings when it comes to the untargeted analysis of native peptides from complex biological matrices.

Depletion of hemoglobin and carbonic anhydrase from erythrocyte cytosolic samples by preparative clear native electrophoresis

Proteomic analysis of red cells is compromised by the presence of high-abundance proteins (hemoglobin and carbonic anhydrase-1), which completely obscure low-abundance species. The depletion method presented here involves performing native gel electrophoresis in a polyacrylamide gel tube using a modified electroelution cell. The electrophoretic run is interrupted intermittently to allow the recovery of at least three different liquid fractions, which can be analyzed by both native PAGE and 2D isoelectric focusing SDS-PAGE, or by shotgun mass spectrometry analysis after trypsin in-solution protein digestion. This low-cost, reproducible technique can be used to process large amounts of sample, and it increases the likelihood of detecting low-abundance proteins, thereby resulting in greater proteome coverage. The separation procedure takes approximately 6-7 h.

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.

Proteomic analysis of plasma derived from platelet buffy coats during storage at room temperature. An application of ProteoMiner™ technology

The present study was aimed at revealing new insights into the analysis of storage-related processes occurring in the supernatants of platelet concentrates (PCs) derived from pooled buffy coats suspended in whole plasma. To reduce the dynamic range of plasma protein concentrations and access low-abundance proteins, we made use of a solid-phase combinatorial peptide ligand library, known under the trade name of ProteoMiner™. Afterwards, two-dimensional electrophoresis (2-DE) was coupled with mass spectrometry (MS) to reveal changes in proteomic profiles. Several storage-induced protein alterations were identified including changes to major plasma proteins. In particular, a precursor of the secretory form of clusterin was shown to accumulate during storage of PC supernatants, together with platelet-derived tropomyosin, suggesting a progressive loss of platelet integrity. Platelet-released proteins following activation have also been detected (alpha-1-B-glycoprotein, kininogen-1, and serpin proteinase inhibitor 8). Moreover, specific protein fragments (vitronectin, plakoglobin, hornerin, and apolipoprotein A-IV) were found to be modulated upon storage, possibly indicating a time-dependent buffy-coat PC deterioration. Globally, our findings provided the disclosure of unique proteins in PC supernatants with respect to previous studies conducted in similar experimental conditions, suggesting ProteoMiner enrichment technology to be a possible complementary tool in the identification of diagnostically relevant proteins as age/quality biomarkers of therapeutic products.

Reduction of protein concentration range difference followed by multicolumn fractionation prior to 2-DE and LC-MS/MS profiling of serum proteins

This article is concerned with the reduction of protein concentration range differences by the peptide beads library technology (ProteoMiner™ or "equalizer" technology), which in principle allows the enrichment of proteins to the same concentration level (i.e. protein equalizer) regardless of the original protein abundance in a given biological fluid such as human serum, which is the subject of our investigation. After the equalization step, the captured proteins from human serum were fractionated on a series of tandem monolithic columns with surface-bound iminodiacetic acid ligands to which three different metal ions, namely, Zn²+, Ni²+ and Cu²+ were immobilized to yield the so-called immobilized metal affinity chromatography columns. These three monolithic columns were connected to a reversed-phase column packed with polystyrene divinyl benzene beads. Aliquots taken from the four collected fractions from the four tandem columns were subsequently fractionated by 2-DE. Also, aliquots from the four collected fractions were tryptically digested and analyzed by LC-MS/MS. The strategy of subsequent fractionation on the four tandem columns after equalization allowed the identification of more proteins than simply using the equalization by ProteoMiner™ . The equalizer technology was compared to the immuno-subtraction approach. While the ProteoMiner™ technology is superior in terms of the overall number of captured proteins, it only complements the immuno-subtraction approach since the latter can capture the proteins that were not captured by the former.

Deep insights into the plant proteome by pretreatment with combinatorial hexapeptide ligand libraries

Proteome analyses suffer from the large complexity of even small proteomes. Additionally, in many protein samples a few highly abundant proteins are hindering detailed proteomic studies, since they mask low abundant proteins. Recently, a new technology has emerged, which reduces dynamic range of protein concentrations within a given sample using combinatorial hexapeptide ligand libraries (CPLLs). This technique has been widely used in the microbial, animal and human fields and is now going to enter plant research. It can be a useful tool for fractionation of protein samples and might help to get a deeper insight into specific plant proteomes. In this review we describe the CPLL protein fractionation, summarize its possible applications in the plant field and discuss the limitations of this method.

In-depth analysis of the chicken egg white proteome using an LTQ Orbitrap Velos

Background

Hen's egg white has been the subject of intensive chemical, biochemical and food technological research for many decades, because of its importance in human nutrition, its importance as a source of easily accessible model proteins, and its potential use in biotechnological processes. Recently the arsenal of tools used to study the protein components of egg white has been complemented by mass spectrometry-based proteomic technologies. Application of these fast and sensitive methods has already enabled the identification of a large number of new egg white proteins. Recent technological advances may be expected to further expand the egg white protein inventory.

Results

Using a dual pressure linear ion trap Orbitrap instrument, the LTQ Orbitrap Velos, in conjunction with data analysis in the MaxQuant software package, we identified 158 proteins in chicken egg white with two or more sequence unique peptides. This group of proteins identified with very high confidence included 79 proteins identified in egg white for the first time. In addition, 44 proteins were identified tentatively.

Conclusions

Our results, apart from identifying many new egg white components, indicate that current mass spectrometry technology is sufficiently advanced to permit direct identification of minor components of proteomes dominated by a few major proteins without resorting to indirect techniques, such as chromatographic depletion or peptide library binding, which change the composition of the proteome.

Popeye strikes again: The deep proteome of spinach leaves

The cytoplasmic proteome of spinach leaves (Spinacia oleracea L) has been investigated with the help of commercially available (ProteoMiner) combinatorial peptide ligand libraries and with home-made ligand beads as prepared in our laboratory. The protein capture had been performed at three pH values (4.0, 7.0 and 9.3) and elution performed in 4% boiling SDS, 20mM DTT. The total number of unique gene products identified amounts to 322 proteins, of which 114 are in common with the control, untreated sample, 18 are present only in the control and 190 represent the new species detected with the help of all combined eluates and likely represent low-abundance species. This is the first in depth exploration of the spinach cytoplasmic proteome and might enable further studies on interaction, regulation and expression of proteins biological processes in combination or not with transcriptomics data.

Application of highly sensitive saturation labeling to the analysis of differential protein expression in infected ticks from limited samples

Background

Ticks are vectors of pathogens that affect human and animal health worldwide. Proteomics and genomics studies of infected ticks are required to understand tick-pathogen interactions and identify potential vaccine antigens to control pathogen transmission. One of the limitations for proteomics research in ticks is the amount of protein that can be obtained from these organisms. In the work reported here, individual naturally-infected and uninfected Rhipicephalus spp. ticks were processed using a method that permits simultaneous extraction of DNA, RNA and proteins. This approach allowed using DNA to determine pathogen infection, protein for proteomics studies and RNA to characterize mRNA levels for some of the differentially expressed proteins. Differential protein expression in response to natural infection with different pathogens was characterized by two-dimensional (2-D) differential in gel electrophoresis (DIGE) saturation labeling in combination with mass spectrometry analysis. To our knowledge, this is the first report of the application of DIGE saturation labeling to study tick proteins.

Results

Questing and feeding Rhipicephalus spp. adult ticks were collected in 27 farms located in different Sicilian regions. From 300 collected ticks, only 16 were found to be infected: R. sanguineus with Rickettsia conorii and Ehrlichia canis; R. bursa with Theileria annulata; and R. turanicus with Anaplasma ovis. The proteomic analysis conducted from a limited amount of proteins allowed the identification of host, pathogen and tick proteins differentially expressed as a consequence of infection.

Conclusion

These results showed that DIGE saturation labeling is a powerful technology for proteomics studies in small number of ticks and provided new information about the effect of pathogen infection in ticks.