Spruce proteome DB: a resource for conifer proteomics research

Proteomics research is hampered in many organisms due to a lack of an appropriate reference genome sequence that can be used in the interpretation of tandem mass spectrometry data for the identification of proteins. Public DNA sequence repositories have grown to considerable size and can, in most cases, serve to provide at least partial interpretation of a large-scale proteomics dataset. However, when species-specific sequences or sequences from a closely related species are available, a boutique sequence database can provide considerable increases in specificity, confidence, and completeness of protein identification. Here, we describe the development of a protein database from a large-scale expressed sequence tag and full-length complementary DNA sequencing project in the economically and ecologically important spruce (Picea) genus.     

A transformer architecture for retention time prediction in liquid chromatography mass spectrometry-based proteomics

Accurate retention time (RT) prediction is important for spectral library-based analysis in data-independent acquisition mass spectrometry-based proteomics. The deep learning approach has demonstrated superior performance over traditional machine learning methods for this purpose. The transformer architecture is a recent development in deep learning that delivers state-of-the-art performance in many fields such as natural language processing, computer vision, and biology. We assess the performance of the transformer architecture for RT prediction using datasets from five deep learning models Prosit, DeepDIA, AutoRT, DeepPhospho, and AlphaPeptDeep. The experimental results on holdout datasets and independent datasets exhibit state-of-the-art performance of the transformer architecture. The software and evaluation datasets are publicly available for future development in the field.     

Reference map for liquid chromatography–mass spectrometry-based quantitative proteomics

The accurate mass and time (AMT) tag strategy has been recognized as a powerful tool for high-throughput analysis in liquid chromatography–mass spectrometry (LC–MS)-based proteomics. Due to the complexity of the human proteome, this strategy requires highly accurate mass measurements for confident identifications. We have developed a method of building a reference map that allows relaxed criteria for mass errors yet delivers high confidence for peptide identifications. The samples used for generating the peptide database were produced by collecting cysteine-containing peptides from T47D cells and then fractionating the peptides using strong cationic exchange chromatography (SCX). LC–tandem mass spectrometry (MS/MS) data from the SCX fractions were combined to create a comprehensive reference map. After the reference map was built, it was possible to skip the SCX step in further proteomic analyses. We found that the reference-driven identification increases the overall throughput and proteomic coverage by identifying peptides with low intensity or complex interference. The use of the reference map also facilitates the quantitation process by allowing extraction of peptide intensities of interest and incorporating models of theoretical isotope distribution.     

Advances in ionisation techniques for mass spectrometry-based omics research

Omics analysis by mass spectrometry (MS) is a vast field, with proteomics, metabolomics and lipidomics dominating recent research by exploiting biological MS ionisation techniques. Traditional MS ionisation techniques such as electrospray ionisation have limitations in analyte-specific sensitivity, modes of sampling and throughput, leading to many researchers investigating new ionisation methods for omics research. In this review, we examine the current landscape of these new ionisation techniques, divided into the three groups of (electro)spray-based, laser-based and other miscellaneous ionisation techniques. Due to the wide range of new developments, this review can only provide a starting point for further reading on each ionisation technique, as each have unique benefits, often for specialised applications, which promise beneficial results for different areas in the omics world.     

Mass spectrometry-based proteomics for translational research: a technical overview

Mass spectrometry-based investigation of clinical samples enables the high-throughput identification of protein biomarkers. We provide an overview of mass spectrometry-based proteomic techniques that are applicable to the investigation of clinical samples. We address sample collection, protein extraction and fractionation, mass spectrometry modalities, and quantitative proteomics. Finally, we examine the limitations and further potential of such technologies. Liquid chromatography fractionation coupled with tandem mass spectrometry is well suited to handle mixtures of hundreds or thousands of proteins. Mass spectrometry-based proteome elucidation can reveal potential biomarkers and aid in the development of hypotheses for downstream investigation of the molecular mechanisms of disease.     

Defining salivary biomarkers using mass spectrometry-based proteomics: a systematic review

Recent advancements in mass spectrometric proteomics provide a promising result in utilizing saliva to explore biomarkers for diagnostic purposes. However, the issues of specificity or redundancy of disease-associated salivary biomarkers have not been described. This systematic review was therefore aimed to define and summarize disease-related salivary biomarkers identified by mass spectrometry proteomics. Peer-reviewed articles published through July 2009 within three databases were reviewed. Out of 243 articles, 21 studies were selected in this systematic review with conditions including Sj?gren's syndrome, squamous cell carcinoma, dental caries, diabetes, breast cancer, periodontitis, gastric cancer, systemic sclerosis, oral lichen planus, bleeding oral cavity, and graft-versus-host disease. The sample size ranged from 3-41 in both diseased and control subjects, with no consensus on sample collection protocol. One hundred eighty biomarkers were identified in total; 87 upregulated, 63 downregulated, and 30 varying based on disease. Except for Sj?gren's syndrome, the majority of studies with the same disease produce inconsistent biomarkers. Larger sample size and standardization of sample collection/treatment protocol may improve future studies.     

Isolation of cell surface proteins for mass spectrometry-based proteomics

Defining the cell surface proteome has profound importance for understanding cell differentiation and cell–cell interactions, as well as numerous pathogenic abnormalities. Owing to their hydrophobic nature, plasma membrane proteins that reside on the cell surface pose analytical challenges and, despite efforts to overcome difficulties, remain under-represented in proteomic studies. Limitations in the classically employed ultracentrifugation-based approaches have led to the invention of more elaborate techniques for the purification of cell surface proteins. Three of these methods – cell surface coating with cationic colloidal silica beads, biotinylation and chemical capture of surface glycoproteins – allow for marked enrichment of this subcellular proteome, with each approach offering unique advantages and characteristics for different experiments. In this article, we introduce the principles of each purification method and discuss applications from the recent literature.     

Evaluation of comprehensive multidimensional separations using reversed-phase, reversed-phase liquid chromatography/mass spectrometry for shotgun proteomics

Two-dimensional liquid-chromatographic (LC) separation followed by mass spectrometric (MS) analysis was examined for the identification of peptides in complex mixtures as an alternative to widely used two-dimensional gel electrophoresis followed by MS analysis for use in proteomics. The present method involves the off-line coupling of a narrow-bore, polymer-based, reversed-phase column using an acetonitrile gradient in an alkaline mobile phase in the first dimension with octadecylsilanized silica (ODS)-based nano-LC/MS in the second dimension. After the first separation, successive fractions were acidified and dried off-line, then loaded on the second dimension column. Both columns separate peptides according to hydrophobicity under different pH conditions, but more peptides were identified than with the conventional technique for shotgun proteomics, that is, the combination of a strong cation exchange column with an ODS column, and the system was robust because no salts were included in the mobile phases. The suitability of the method for proteomics measurements was evaluated.     

A protein processing filter method for bacterial identification by mass spectrometry-based proteomics

A "one-pot" alternative method for processing proteins and isolating peptide mixtures from bacterial samples is presented for liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis and data reduction. The conventional in-solution digestion of the protein contents of bacteria is compared to a small disposable filter unit placed inside a centrifuge vial for processing and digestion of bacterial proteins. Each processing stage allows filtration of excess reactants and unwanted byproduct while retaining the proteins. Upon addition of trypsin, the peptide mixture solution is passed through the filter while retaining the trypsin enzyme. The peptide mixture is then analyzed by LC-MS/MS with an in-house BACid algorithm for a comparison of the experimental unique peptides to a constructed proteome database of bacterial genus, specie, and strain entries. The concentration of bacteria was varied from 10 × 10(7) to 3.3 × 10(3) cfu/mL for analysis of the effect of concentration on the ability of the sample processing, LC-MS/MS, and data analysis methods to identify bacteria. The protein processing method and dilution procedure result in reliable identification of pure suspensions and mixtures at high and low bacterial concentrations.     

A liquid chromatography/mass spectrometry-based method for the selection of ATP competitive kinase inhibitors

The currently approved kinase inhibitors for therapeutic uses and a number of kinase inhibitors that are undergoing clinical trials are directed toward the adenosine triphosphate (ATP) binding site of protein kinases. The 5'-fluorosulfonylbenzoyl 5'-adenosine (FSBA) is an ATP-affinity reagent that covalently modifies a conserved lysine present in the nucleotide-binding site of most kinases. The authors have developed a liquid chromatography/mass spectrometry-based method to monitor binding of ATP competitive protein kinase inhibitors using FSBA as a nonselective activity-based probe for protein kinases. Their method provides a general, rapid, and reproducible means to screen and validate selective ATP competitive inhibitors of protein kinases.     

The chloroplast grana proteome defined by intact mass measurements from liquid chromatography mass spectrometry

Proteomics seeks to address the entire complement of protein gene products of an organism, but experimental analysis of such complex mixtures is biased against low abundance and membrane proteins. Electrospray-ionization mass spectrometry coupled with reverse-phase chromatography was used to separate and catalogue all detectable proteins in samples of photosystem II-enriched thylakoid membrane subdomains (grana) from pea and spinach. Around 90 intact mass tags were detected corresponding to approximately 40 gene products with variable post-translational covalent modifications. Provisional identity of 30 of these gene products was proposed based upon coincidence of measured mass with that calculated from genomic sequence. Analysis of isolated photosystem II complexes allowed detection and resolution of a minor population of D1 (PsbA) that was apparently palmitoylated and not detected in less purified preparations. Based upon observed +80-Da adducts, D1, D2 (PsbD), CP43 (PsbC), two Lhcbs, and PsbH were confirmed to be phosphorylated, and a new phosphoprotein was proposed to be the product of psbT. The appearance of a second +80-Da adduct on PsbH provides direct evidence for a second phosphorylation site on PsbH, complicating interpretation of its role in regulation of thylakoid membrane organization and function, including light-state transitions. Adducts of +32 Da, presumably arising from oxidative modification during illumination, were associated with more highly phosphorylated forms of PsbH implying a relationship between the two phenomena. Intact mass proteomics of organellar subfractions and more highly purified protein complexes provides increasingly detailed insights into functional genomics of photosynthetic membranes.     

Advances in mass spectrometry-based cancer research and analysis: from cancer proteomics to clinical diagnostics

Introduction: The last 20 years have seen significant improvements in the analytical capabilities of biological mass spectrometry (MS). Studies using advanced MS have resulted in new insights into cell biology and the etiology of diseases as well as its use in clinical applications.

Areas covered: This review discusses recent developments in MS-based technologies and their cancer-related applications with a focus on proteomics. It also discusses the issues around translating the research findings to the clinic and provides an outline of where the field is moving.

Expert commentary: Proteomics has been problematic to adapt for the clinical setting. However, MS-based techniques continue to demonstrate potential in novel clinical uses beyond classical cancer proteomics.     

Portrait of a pathogen: the Mycobacterium tuberculosis proteome in vivo

Background

Mycobacterium tuberculosis (Mtb), the causative agent of tuberculosis (TB), is a facultative intracellular pathogen that can persist within the host. The bacteria are thought to be in a state of reduced replication and metabolism as part of the chronic lung infection. Many in vitro studies have dissected the hypothesized environment within the infected lung, defining the bacterial response to pH, starvation and hypoxia. While these experiments have afforded great insight, the picture remains incomplete. The only way to study the combined effects of these environmental factors and the mycobacterial response is to study the bacterial response in vivo.

Methodology/Principal Findings

We used the guinea pig model of tuberculosis to examine the bacterial proteome during the early and chronic stages of disease. Lungs were harvested thirty and ninety days after aerosol challenge with Mtb, and analyzed by liquid chromatography-mass spectrometry. To date, in vivo proteomics of the tubercle bacillus has not been described and this work has generated the first large-scale shotgun proteomic data set, comprising over 500 unique protein identifications. Cell wall and cell wall processes, and intermediary metabolism and respiration were the two major functional classes of proteins represented in the infected lung. These classes of proteins displayed the greatest heterogeneity indicating important biological processes for establishment of a productive bacterial infection and its persistence. Proteins necessary for adaptation throughout infection, such as nitrate/nitrite reduction were found at both time points. The PE-PPE protein class, while not well characterized, represented the third most abundant category and showed the most consistent expression during the infection.

Conclusions/Significance

Cumulatively, the results of this work may provide the basis for rational drug design – identifying numerous Mtb proteins, from essential kinases to products involved in metal regulation and cell wall remodeling, all present throughout the course of infection.     

Prefractionation of proteome by liquid isoelectric focusing prior to two-dimensional liquid chromatography mass spectrometric identification

Due to the complexity of proteomes, developing methods of sample fractionation, separation, concentration, and detection have become urgent to the identification of large numbers of proteins, as well as the acquisition of those proteins in low abundance. In this work, liquid isoelectric focusing (LIEF) combined with 2D-LC-MS/MS was applied to the proteome of Saccharomyces cerevisiae. This yielded a total of 1795 proteins that were detected and identified by 30 fractions of protein prefractionation. Categorization of these hits demonstrated the ability of this technology to detect and identify proteins rarely seen in proteome analysis without protein fractionation. LIEF-2D-LC-MS/MS also produced improved resolution of low-abundance proteins. Furthermore, we analyzed the characteristics of proteins obtained by LIEF-2D-LC-MS/MS. 1103 proteins with CAI under 0.2 were identified, allowing us to specifically obtain detailed biochemical information on these kind proteins. It was observed that LIEF-2D-LC-MS/MS is useful for large-scale proteome analysis and may be specifically applied to systems with wide dynamic ranges.     

Streptococcus pyogenes in human plasma: adaptive mechanisms analyzed by mass spectrometry-based proteomics

Streptococcus pyogenes is a major bacterial pathogen and a potent inducer of inflammation causing plasma leakage at the site of infection. A combination of label-free quantitative mass spectrometry-based proteomics strategies were used to measure how the intracellular proteome homeostasis of S. pyogenes is influenced by the presence of human plasma, identifying and quantifying 842 proteins. In plasma the bacterium modifies its production of 213 proteins, and the most pronounced change was the complete down-regulation of proteins required for fatty acid biosynthesis. Fatty acids are transported by albumin (HSA) in plasma. S. pyogenes expresses HSA-binding surface proteins, and HSA carrying fatty acids reduced the amount of fatty acid biosynthesis proteins to the same extent as plasma. The results clarify the function of HSA-binding proteins in S. pyogenes and underline the power of the quantitative mass spectrometry strategy used here to investigate bacterial adaptation to a given environment.     

Improving the reliability and throughput of mass spectrometry-based proteomics by spectrum quality filtering

In contemporary peptide-centric or non-gel proteome studies, vast amounts of peptide fragmentation data are generated of which only a small part leads to peptide or protein identification. This motivates the development and use of a filtering algorithm that removes spectra that contribute little to protein identification. Removal of unidentifiable spectra reduced both the amount of computational and human time spent on analyzing spectra as well as the chances of obtaining false identifications. Thorough testing on various proteome datasets from different instruments showed that the best suggested machine-learning classifier is, on average, able to recognize half of the unidentified spectra as bad spectra. Further analyses showed that several unidentified spectra classified as good were derived from peptides carrying unanticipated amino acid modifications or contained sequence tags that allowed peptide identification using homology searches. The implementation of the classifiers is available under the GNU General Public License at http://www.bioinfo.no/software/spectrumquality.     

Comprehensive two-dimensional liquid chromatography mass spectrometric profiling of the rat hippocampal proteome

In this study, we performed the first high‐throughput and comprehensive proteomic profiling of the rat hippocampal proteome. Using a combination of 2‐D LC‐MS and data analysis with the Rosetta Elucidator^® system, we identified 1340 unique proteins. Functional classification showed that most of these were associated with synaptic function and comprised a high proportion of phosphorylated proteins and analytically challenging classes of membrane proteins such as ion channel receptor subunits.     

Stoichiometry of chromatin-associated protein complexes revealed by label-free quantitative mass spectrometry-based proteomics

Many cellular proteins assemble into macromolecular protein complexes. The identification of protein–protein interactions and quantification of their stoichiometry is therefore crucial to understand the molecular function of protein complexes. Determining the stoichiometry of protein complexes is usually achieved by mass spectrometry-based methods that rely on introducing stable isotope-labeled reference peptides into the sample of interest. However, these approaches are laborious and not suitable for high-throughput screenings. Here, we describe a robust and easy to implement label-free relative quantification approach that combines the detection of high-confidence protein–protein interactions with an accurate determination of the stoichiometry of the identified protein–protein interactions in a single experiment. We applied this method to two chromatin-associated protein complexes for which the stoichiometry thus far remained elusive: the MBD3/NuRD and PRC2 complex. For each of these complexes, we accurately determined the stoichiometry of the core subunits while at the same time identifying novel interactors and their stoichiometry.     

Analysis of the adenovirus type 5 proteome by liquid chromatography and tandem mass spectrometry methods

We compared detection sensitivity and protein sequence coverage of the adenovirus type 5 proteome achievable by liquid chromatography and tandem mass spectroscopy (LC/MS/MS) using three sample preparation and clean up methods. Tryptic digestion was performed on either purified viral proteins or whole virus, and followed by shotgun sequencing using tandem mass spectrometry for peptide identification. We used a recombinant adenovirus type 5 as a test system. The methods included separation of adenoviral proteins by reversed-phase high-performance liquid chromatography followed by tryptic digestion and analysis by LC/MS/MS. Alternatively, the purified whole virus was digested with trypsin and the peptides separated either by one-dimensional (reversed-phase) or by two-dimensional (cation exchange and reversed-phase) chromatography and analyzed by tandem mass spectrometry. A total of 11 protein species were identified from 154 peptides. All of the major viral proteins were found. In addition, two minor proteins, the 23 kDa viral protease and the late L1 protein, were identified for the first time by chromatography based assays. The 23 kDa viral protease, present at only 10 copies per virus, and representing 0.2% of the protein content of the virus, was detected by the 2D LC/MS/MS analysis of the whole virus digest from a sample containing only 70 fmols of the protein. This demonstrates the high sensitivity and selectivity of the method. The 2D LC/MS/MS analysis of the whole virus digest was also able to detect all viral proteins with copy numbers at or above 10/virus particle, with broad coverage of the amino acid sequences. Coverage ranged from 2 to 54%, a majority between 20 and 35%, suggesting the possibility of using this analysis to assess the purity of the virus preparations. This broad coverage may also provide a useful approach to identify posttranslational modifications on the structural proteins of the adenovirus.