In-depth analysis of the human tear proteome

The tears, a critical body fluid of the surface of the eye, contain an unknown number of molecules including proteins/peptides, lipids, small molecule metabolites, and electrolytes. There have been continued efforts for exploring the human tear proteome to develop biomarkers of disease. In this study, we used the high speed TripleTOF 5600 system as the platform to analyze the human tear proteome from healthy subjects (3 females and 1 male, average age: 36±14). We have identified 1543 proteins in the tears with less than 1% false discovery rate, which represents the largest number of human tear proteins reported to date. The data set was analyzed for gene ontology (GO) and compared with the human plasma proteome, NEIBank lacrimal gland gene dataset and NEIBank cornea gene dataset. This comprehensive tear protein list may serve as a reference list of human tear proteome for biomarker research of ocular diseases or establishment of MRM (Multiple Reaction Monitoring) assays for targeted analysis. Tear fluid is a useful and an accessible source not only for evaluating ocular surface tissues (cornea and conjunctiva), inflammation, lacrimal gland function and a number of disease conditions, such as dry eye as well as response to treatment.     

Longitudinal analysis of taurine induced effects on the tear proteome of contact lens wearers and dry eye patients using a RP-RP-Capillary-HPLC-MALDI TOF/TOF MS approach

Tear proteomic studies revealed distinct similarities between contact lens wearers and dry eye patients. AMO Complete® multipurpose contact lens cleaning solutions containing taurine seem to have a beneficial effect regarding contact lens induced dry eye. To illuminate the effect of taurine on the tear proteome of contact lens wearers and sicca patients we developed a gel-based RP-RP capillary HPLC–MALDI TOF/TOF MS strategy. Two contact lens wearer groups, one using eye drops containing 0.05% taurine; the other for control physiological NaCl solution were monitored. Also, a third group of sicca patients using taurine solution was studied (N = 4 individuals/group). Tear pools of each group at six time points over 5 weeks were analyzed. In summary 267 tear proteins were identified. We found a protein subset showing a linear taurine response with R² values ≥ 0.5. Taurine effects were detected predominantly in the contact lens group demonstrated by distinct level decreases. Most protein candidates were related to inflammation. Since levels of these proteins differentiate from those of a healthy non-contact lens wearer reference they are supposed to be involved in contact lens induced dry eye and should be focused on in further studies.     

Quantitative proteome analysis using differential stable isotopic labeling and microbore LC-MALDI MS and MS/MS

We demonstrate an approach for global quantitative analysis of protein mixtures using differential stable isotopic labeling of the enzyme-digested peptides combined with microbore liquid chromatography (LC) matrix-assisted laser desorption ionization (MALDI) mass spectrometry (MS). Microbore LC provides higher sample loading, compared to capillary LC, which facilitates the quantification of low abundance proteins in protein mixtures. In this work, microbore LC is combined with MALDI MS via a heated droplet interface. The compatibilities of two global peptide labeling methods (i.e., esterification to carboxylic groups and dimethylation to amine groups of peptides) with this LC-MALDI technique are evaluated. Using a quadrupole-time-of-flight mass spectrometer, MALDI spectra of the peptides in individual sample spots are obtained to determine the abundance ratio among pairs of differential isotopically labeled peptides. MS/MS spectra are subsequently obtained from the peptide pairs showing significant abundance differences to determine the sequences of selected peptides for protein identification. The peptide sequences determined from MS/MS database search are confirmed by using the overlaid fragment ion spectra generated from a pair of differentially labeled peptides. The effectiveness of this microbore LC-MALDI approach is demonstrated in the quantification and identification of peptides from a mixture of standard proteins as well as E. coli whole cell extract of known relative concentrations. It is shown that this approach provides a facile and economical means of comparing relative protein abundances from two proteome samples.     

Single unit filter-aided method for fast proteomic analysis of tear fluid

Human tear fluid is a complex mixture containing high concentrations of proteins and is increasingly becoming an important source for studying protein biomarkers of eye-related diseases such as Graves’ ophthalmopathy. Today, the Schirmer tear test is the most widely used technique for tear collection. However, sample handling and protein extraction from these strips have been highly challenging. Cutting and removal of the Schirmer strips after extraction, which may lead to sample loss prior to downstream analysis, are some of the challenges to consider. To address some of these limitations, we have developed a single-unit filter-aided method for both sample handling and protein extraction. In addition, we systematically investigated the most suitable conditions for protein extraction from these strips. Among the different extraction conditions applied, extraction with 100 mM ammonium bicarbonate containing 50 mM NaCl resulted in the highest number of identified proteins using one-dimensional liquid chromatography tandem mass spectrometry (LC–MS/MS). Moreover, 1526 proteins were identified when the optimized extraction method was combined with two-dimensional LC–MS/MS analysis, demonstrating the applicability of this novel approach to the study of the tear proteome. This dataset of identified proteins represents a comprehensive catalogue of the tear proteome and may serve as a list for future biomarker research.     

Methods and approaches for the comprehensive characterization and quantification of cellular proteomes using mass spectrometry.

Proteomics has been proposed as one of the key technologies in the postgenomic era. So far, however, the comprehensive analysis of cellular proteomes has been a challenge because of the dynamic nature and complexity of the multitude of proteins in cells and tissues. Various approaches have been established for the analyses of proteins in a cell at a given state, and mass spectrometry (MS) has proven to be an efficient and versatile tool. MS-based proteomics approaches have significantly improved beyond the initial identification of proteins to comprehensive characterization and quantification of proteomes and their posttranslational modifications (PTMs). Despite these advances, there is still ongoing development of new technologies to profile and analyze cellular proteomes more completely and efficiently. In this review, we focus on MS-based techniques, describe basic approaches for MS-based profiling of cellular proteomes and analysis methods to identify proteins in complex mixtures, and discuss the different approaches for quantitative proteome analysis. Finally, we briefly discuss novel developments for the analysis of PTMs. Altered levels of PTM, sometimes in the absence of protein expression changes, are often linked to cellular responses and disease states, and the comprehensive analysis of cellular proteome would not be complete without the identification and quantification of the extent of PTMs of proteins.     

JUMPptm: Integrated software for sensitive identification of post-translational modifications and its application in Alzheimer's disease study

Background : Mass spectrometry (MS)-based proteomic analysis of posttranslational modifications (PTMs) usually requires the pre-enrichment of modified proteins or peptides. However, recent ultra-deep whole proteome profiling generates millions of spectra in a single experiment, leaving many unassigned spectra, some of which may be derived from PTM peptides. Methods : Here we present JUMPptm, an integrative computational pipeline, to extract PTMs from unenriched whole proteome. JUMPptm combines the advantages of JUMP, MSFragger and Comet search engines, and includes de novo tags, customized database search and peptide filtering, which iteratively analyzes each PTM by a multi-stage strategy to improve sensitivity and specificity. Results : We applied JUMPptm to the deep brain proteome of Alzheimer's disease (AD), and identified 34,954 unique peptides with phosphorylation, methylation, acetylation, ubiquitination, and others. The phosphorylated peptides were validated by enriched phosphoproteome from the same sample. TMT-based quantification revealed 482 PTM peptides dysregulated at different stages during AD progression. For example, the acetylation of numerous mitochondrial proteins is significantly decreased in AD. A total of 60 PTM sites are found in the pan-PTM map of the Tau protein. Conclusion : The JUMPptm program is an effective tool for pan-PTM analysis and the resulting AD pan-PTM profile serves as a valuable resource for AD research.     

Assessment of Blood Contamination in Biological Fluids Using MALDI-TOF MS

Biological fluid sample collection often includes the risk of blood contamination that may alter the proteomic profile of biological fluid. In proteomics studies, exclusion of contaminated samples is usually based on visual inspection and counting of red blood cells in the sample; analysis of specific blood derived proteins is less used. To fill the gap, we developed a fast and sensitive method for ascertainment of blood contamination in crude biological fluids, based on specific blood-derived protein, hemoglobin detection by MALDI-TOF MS. The MALDI-TOF MS based method allows detection of trace hemoglobin with the detection limit of 0.12 nM. UV-spectrometry, which was used as reference method, was found to be less sensitive. The main advantages of the presented method are that it is fast, effective, sensitive, requires very small sample amount and can be applied for detection of blood contamination in various biological fluids collected for proteomics studies. Method applicability was tested on human cerebrospinal and follicular fluid, which proteomes generally do not contain hemoglobin, however, which possess high risk for blood contamination. Present method successfully detected the blood contamination in 12 % of cerebrospinal fluid and 24 % of follicular fluid samples. High percentage of contaminated samples accentuates the need for initial inspection of proteomic samples to avoid incorrect results from blood proteome overlap.     

Molecular weight assessment of proteins in total proteome profiles using 1D-PAGE and LC/MS/MS

Background  

The observed molecular weight of a protein on a 1D polyacrylamide gel can provide meaningful insight into its biological function. Differences between a protein's observed molecular weight and that predicted by its full length amino acid sequence can be the result of different types of post-translational events, such as alternative splicing (AS), endoproteolytic processing (EPP), and post-translational modifications (PTMs). The characterization of these events is one of the important goals of total proteome profiling (TPP). LC/MS/MS has emerged as one of the primary tools for TPP, but since this method identifies tryptic fragments of proteins, it has not generally been used for large-scale determination of the molecular weight of intact proteins in complex mixtures.     

Multidimensional protein profiling technology and its application to human plasma proteome

In clinical and diagnostic proteomics, it is essential to develop a comprehensive and robust system for proteome analysis. Although multidimensional liquid chromatography/tandem mass spectrometry (LC/MS/MS) systems have been recently developed as powerful tools especially for identification of protein complexes, these systems still some drawbacks in their application to clinical research that requires an analysis of a large number of human samples. Therefore, in this study, we have constructed a technically simple and high throughput protein profiling system comprising a two-dimensional (2D)-LC/MS/MS system which integrates both a strong cation exchange (SCX) chromatography and a microLC/MS/MS system with micro-flowing reversed-phase chromatography. Using the microLC/MS/MS system as the second dimensional chromatography, SCX separation has been optimized as an off-line first dimensional peptide fractionation. To evaluate the performance of the constructed 2D-LC/MS/MS system, the results of detection and identification of proteins were compared using digests mixtures of 6 authentic proteins with those obtained using one-dimensional microLC/MS/MS system. The number of peptide fragments detected and the coverage of protein sequence were found to be more than double through the use of our newly built 2D-LC/MS/MS system. Furthermore, this multidimensional protein profiling system has been applied to plasma proteome in order to examine its feasibility for clinical proteomics. The experimental results revealed the identification of 174 proteins from one serum sample depleted HSA and IgG which corresponds to only 1 microL of plasma, and the total analysis run time was less than half a day, indicating a fairly high possibility of practicing clinical proteomics in a high throughput manner.     

Unrestrictive identification of multiple post-translational modifications from tandem mass spectrometry using an error-tolerant algorithm based on an extended sequence tag approach

Identification of post-translational modifications (PTMs) is important to understanding the biological functions of proteins. MS/MS is a useful tool to identify PTMs. Most existing search tools are restricted to take only a few types of PTMs as input. Here we describe a new algorithm, called MOD(i) (pronounced "mod eye"), that rapidly searches for all known types of PTMs at once without limiting a multitude of modified sites in a peptide. MOD(i) introduces the notion of a tag chain, a combination structure made from multiple sequence tags, that effectively localizes modified regions within a spectrum and overcomes de novo sequencing errors common in tag-based approaches. MOD(i) showed its performance competence by identifying various types of PTMs in analysis of PTM-rich proteins such as glyceraldehyde-3-phosphate dehydrogenase and lens protein. We demonstrated that MOD(i) innovatively manages the computational complexity of identifying multiple PTMs in a peptide, which may exist in a greater variety than usually expected. In addition, it is suggested that MOD(i) has great potential to discover novel modifications.     

Clinical-scale high-throughput human plasma proteome analysis: lung adenocarcinoma

Clinical proteomics requires the stable and reproducible analysis of a large number of human samples. We report a high-throughput comprehensive protein profiling system comprising a fully automated, on-line, two-dimensional microflow liquid chromatography/tandem mass spectrometry (2-D microLC-MS/MS) system for use in clinical proteomics. A linear ion-trap mass spectrometer (ITMS) also known as a 2-D ITMS instrument, which is characterized by high scan speed, was incorporated into the microLC-MS/MS system in order to obtain highly improved sensitivity and resolution in MS/MS acquisition. This system was used to evaluate bovine serum albumin and human 26S proteasome. Application of these high-throughput microLC conditions and the 2-D ITMS resulted in a 10-fold increase in sensitivity in protein identification. Additionally, peptide fragments from the 26S proteasome were identified three-fold more efficiently than by the conventional 3-D ITMS instrument. In this study, the 2-D microLC-MS/MS system that uses linear 2-D ITMS has been applied for the plasma proteome analysis of a few samples from healthy individuals and lung adenocarcinoma patients. Using the 2-D and 1-D microLC-MS/MS analyses, approximately 250 and 100 different proteins were detected, respectively, in each HSA- and IgG-depleted sample, which corresponds to only 0.4 microL of blood plasma. Automatic operation enabled the completion of a single run of the entire 1-D and 2-D microLC-MS/MS analyses within 11 h. Investigation of the data extracted from the protein identification datasets of both healthy and adenocarcinoma groups revealed that several of the group-specific proteins could be candidate protein disease markers expressed in the human blood plasma. Consequently, it was demonstrated that this high-throughput microLC-MS/MS protein profiling system would be practically applicable to the discovery of protein disease markers, which is the primary objective in clinical plasma proteome projects.     

Direct tandem mass spectrometry reveals limitations in protein profiling experiments for plasma biomarker discovery

The low molecular weight plasma proteome and its biological relevance are not well defined; therefore, experiments were conducted to directly sequence and identify peptides observed in plasma and serum protein profiles. Protein fractionation, matrix-assisted laser desorption ionization mass spectrometry (MALDI-MS) profiling, and liquid-chromatography coupled to MALDI tandem mass spectrometry (MS/MS) sequencing were used to analyze the low molecular weight proteome of heparinized plasma. Four fractionation techniques using functionally derivatized 96-well plates were used to extract peptides from plasma. Tandem TOF was successful for identifying peptides up to m/z 5500 with no prior knowledge of the sequence and was also used to verify the sequence assignments for larger ion signals. The peptides (n>250) sequenced in these profiles came from a surprisingly small number of proteins (n approximately 20), which were all common to plasma, including fibrinogen, complement components, antiproteases, and carrier proteins. The cleavage patterns were consistent with those of known plasma proteases, including initial cleavages by thrombin, plasmin and complement proteins, followed by aminopeptidase and carboxypeptidase activity. On the basis of these data, we discuss limitations in biomarker discovery in the low molecular weight plasma or serum proteome using crude fractionation coupled to MALDI-MS profiling.     

Human body fluid proteome analysis

The focus of this article is to review the recent advances in proteome analysis of human body fluids, including plasma/serum, urine, cerebrospinal fluid, saliva, bronchoalveolar lavage fluid, synovial fluid, nipple aspirate fluid, tear fluid, and amniotic fluid, as well as its applications to human disease biomarker discovery. We aim to summarize the proteomics technologies currently used for global identification and quantification of body fluid proteins, and elaborate the putative biomarkers discovered for a variety of human diseases through human body fluid proteome (HBFP) analysis. Some critical concerns and perspectives in this emerging field are also discussed. With the advances made in proteomics technologies, the impact of HBFP analysis in the search for clinically relevant disease biomarkers would be realized in the future.     

Multidimensional fractionation of the bovine skeletal muscle proteome.

The ultimate goal of proteomics is to understand complex biological systems. The first step toward this end is the discovery of protein differences by profiling a given proteome. One approach to proteome profiling is to fractionate it into intact proteins, with subsequent identification and quantitation. In this work, lysates of bovine skeletal muscle were prepared. Reproducible proteome profiles were generated by an automatic two-dimensional protein fractionation system. Proteins were separated by isoelectric point and then by hydrophobicity. The data collected from both separations were used to generate proteome profiles. A high protein content fraction with pl above 8.5 was digested with trypsin, and its main protein component was identified as lysozyme C by matrix assisted laser desorption/ionization-time of flight mass spectrometry.     

Identification of hemopexin in tear film

Human tear fluid is a complex mixture of aqueous lipids, proteins, enzymes, and other biochemical and cellular elements. By conventional comparative proteomic approaches, we investigated the proteome in human tear fluid and compared the tear protein profile of normal control subjects with that of patients suffering from the ocular inflammatory disease vernal keratoconjunctivitis (VKC). Collected tear samples were directed to two-dimensional polyacrylamide gel electrophoresis protein separation and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry peptide identification. Six differentially expressed proteins—interleukin 4, phospholipase A2, albumin, lactoferrin, hemopexin, and lipocalin—were displayed. Hemopexin had not been reported previously in tear film. Enzyme-linked immunosorbent assay confirmed that hemopexin concentrations were significantly higher in VKC tear samples and increased with disease stages. The results implied clinical interest of hemopexin in the tear proteome and eye diseases.     

Data-independent acquisition proteomics methods for analyzing post-translational modifications

Protein post-translational modifications (PTMs) increase the functional diversity of the cellular proteome. Accurate and high throughput identification and quantification of protein PTMs is a key task in proteomics research. Recent advancements in data-independent acquisition (DIA) mass spectrometry (MS) technology have achieved deep coverage and accurate quantification of proteins and PTMs. This review provides an overview of DIA data processing methods that cover three aspects of PTMs analysis, that is, detection of PTMs, site localization, and characterization of complex modification moieties, such as glycosylation. In addition, a survey of deep learning methods that boost DIA-based PTMs analysis is presented, including in silico spectral library generation, as well as feature scoring and error rate control. The limitations and future directions of DIA methods for PTMs analysis are also discussed. Novel data analysis methods will take advantage of advanced MS instrumentation techniques to empower DIA MS for in-depth and accurate PTMs measurements.     

The utility of proteases in proteomics,from sequence profiling to structure and function analysis

In mass spectrometry (MS)-based bottom-up proteomics, protease digestion plays an essential role in profiling both proteome sequences and post-translational modifications (PTMs). Trypsin is the gold standard in digesting intact proteins into small-size peptides, which are more suitable for high-performance liquid chromatography (HPLC) separation and tandem MS (MS/MS) characterization. However, protein sequences lacking Lys and Arg cannot be cleaved by trypsin and may be missed in conventional proteomic analysis. Proteases with cleavage sites complementary to trypsin are widely applied in proteomic analysis to greatly improve the coverage of proteome sequences and PTM sites. In this review, we survey the common and newly emerging proteases used in proteomics analysis mainly in the last 5 years, focusing on their unique cleavage features and specific proteomics applications such as missing protein characterization, new PTM discovery, and de novo sequencing. In addition, we summarize the applications of proteases in structural proteomics and protein function analysis in recent years. Finally, we discuss the future development directions of new proteases and applications in proteomics.     

Gaining knowledge from previously unexplained spectra-application of the PTM-Explorer software to detect PTM in HUPO BPP MS/MS data

A novel software tool named PTM-Explorer has been applied to LC-MS/MS datasets acquired within the Human Proteome Organisation (HUPO) Brain Proteome Project (BPP). PTM-Explorer enables automatic identification of peptide MS/MS spectra that were not explained in typical sequence database searches. The main focus was detection of PTMs, but PTM-Explorer detects also unspecific peptide cleavage, mass measurement errors, experimental modifications, amino acid substitutions, transpeptidation products and unknown mass shifts. To avoid a combinatorial problem the search is restricted to a set of selected protein sequences, which stem from previous protein identifications using a common sequence database search. Prior to application to the HUPO BPP data, PTM-Explorer was evaluated on excellently manually characterized and evaluated LC-MS/MS data sets from Alpha-A-Crystallin gel spots obtained from mouse eye lens. Besides various PTMs including phosphorylation, a wealth of experimental modifications and unspecific cleavage products were successfully detected, completing the primary structure information of the measured proteins. Our results indicate that a large amount of MS/MS spectra that currently remain unidentified in standard database searches contain valuable information that can only be elucidated using suitable software tools.     

Proteomics analysis of human amniotic fluid

Amniotic fluid is a dynamic and complex mixture that reflects the physiological status of the developing fetus. In this study, the human amniotic fluid (AF) proteome of a 16-18-week normal pregnancy was profiled and analyzed to investigate the composition and functions of this fluid. Due to the complexity of AF, we utilized three different fractionation strategies to provide greater coverage. Two types of two-dimensional LC/MS/MS as well as an LC-SDS-PAGE-LC-MS/MS platform were used. A total of 16 AF samples between gestational ages of 16 and 18 weeks from women carrying chromosomally normal fetuses were analyzed by one of the three fractionation methods followed by a common reverse phase LC-MS/MS step. Mascot and The Global Proteome Machine engines were used to search the International Protein Index human database for peptide sequence identification. The list of proteins was generated by combining the results of both engines through the PeptideProphet of Scaffold software. All identified proteins were combined to generate the AF proteome comprising 1,026 unique gene matches or 842 non-redundant proteins. This list includes most of the currently used biomarkers for pregnancy-associated pathologic conditions such as preterm delivery, intra-amniotic infection, and chromosomal anomalies of the fetus. The subcellular localization, tissue expression, functions, and networks of the AF proteome were analyzed by various bioinformatic tools. These data will contribute to the better understanding of amniotic fluid function and to the discovery of novel biomarkers for prenatal diagnosis of fetal abnormalities.