Increased proteome coverage by combining PAGE and peptide isoelectric focusing: Comparative study of gel‐based separation approaches

The in‐depth analysis of complex proteome samples requires fractionation of the sample into subsamples prior to LC‐MS/MS in shotgun proteomics experiments. We have established a 3D workflow for shotgun proteomics that relies on protein separation by 1D PAGE, gel fractionation, trypsin digestion, and peptide separation by in‐gel IEF, prior to RP‐HPLC‐MS/MS. Our results show that applying peptide IEF can significantly increase the number of proteins identified from PAGE subfractionation. This method delivers deeper proteome coverage and provides a large degree of flexibility in experimentally approaching highly complex mixtures by still relying on protein separation according to molecular weight in the first dimension.     

Shotgun proteome analysis utilising mixed mode (reversed phase‐anion exchange chromatography) in conjunction with reversed phase liquid chromatography mass spectrometry analysis

The 2‐D peptide separations employing mixed mode reversed phase anion exchange (MM (RP‐AX)) HPLC in the first dimension in conjunction with RP chromatography in the second dimension were developed and utilised for shotgun proteome analysis. Compared with strong cation exchange (SCX) typically employed for shotgun proteomic analysis, peptide separations using MM (RP‐AX) revealed improved separation efficiency and increased peptide distribution across the elution gradient. In addition, improved sample handling, with no significant reduction in the orthogonality of the peptide separations was observed. The shotgun proteomic analysis of a mammalian nuclear cell lysate revealed additional proteome coverage (2818 versus 1125 unique peptides and 602 versus 238 proteins) using the MM (RP‐AX) compared with the traditional SCX hyphenated to RP‐LC‐MS/MS. The MM analysis resulted in approximately 90% of the unique peptides identified present in only one fraction, with a heterogeneous peptide distribution across all fractions. No clustering of the predominant peptide charge states was observed during the gradient elution. The application of MM (RP‐AX) for 2‐D LC proteomic studies was also extended in the analysis of iTRAQ‐labelled HeLa and cyanobacterial proteomes using nano‐flow chromatography interfaced to the MS/MS. We demonstrate MM (RP‐AX) HPLC as an alternative approach for shotgun proteomic studies that offers significant advantages over traditional SCX peptide separations.     

Liquid chromatography MALDI MS/MS for membrane proteome analysis

Membrane proteins play critical roles in many biological functions and are often the molecular targets for drug discovery. However, their analysis presents a special challenge largely due to their highly hydrophobic nature. We present a surfactant-aided shotgun proteomics approach for membrane proteome analysis. In this approach, membrane proteins were solubilized and digested in the presence of SDS followed by newly developed auto-offline liquid chromatography/matrix-assisted laser desorption ionization (LC/MALDI) tandem MS analysis. Because of high tolerance of MALDI to SDS, one-dimensional (1D) LC separation can be combined with MALDI for direct analysis of protein digests containing SDS, without the need for extensive sample cleanup. In addition, the heated droplet interface used in LC/MALDI can work with high flow LC separations, allowing a relatively large amount of protein digest to be used for 1D LC/MALDI which facilitates the detection of low abundance proteins. The proteome identification results obtained by LC/MALDI are compared to the gel electrophoresis/MS method as well as the shotgun proteomics method using 2D LC/electrospray ionization MS. It is demonstrated that, while LC/MALDI provides more extensive proteome coverage compared to the other two methods, these three methods are complementary to each other and a combination of these methods should provide a more comprehensive membrane proteome analysis.     

A comparison of MS/MS‐based,stable‐isotope‐labeled,quantitation performance on ESI‐quadrupole TOF and MALDI‐TOF/TOF mass spectrometers

The peptide‐based quantitation accuracy and precision of LC‐ESI (QSTAR Elite) and LC‐MALDI (4800 MALDI TOF/TOF) were compared by analyzing identical Escherichia coli tryptic digests containing iTRAQ‐labeled peptides of defined abundances (1:1, 2.5:1, 5:1, and 10:1). Only 51.4% of QSTAR spectra were used for quantitation by ProteinPilot Software versus 66.7% of LC‐MALDI spectra. The average protein sequence coverages for LC‐ESI and LC‐MALDI were 24.0 and 18.2% (14.9 and 8.4 peptides per protein), respectively. The iTRAQ‐based expression ratios determined by ProteinPilot from the 57 467 ESI‐MS/MS and 26 085 MALDI‐MS/MS spectra were analyzed for measurement accuracy and reproducibility. When the relative abundances of peptides within a sample were increased from 1:1 to 10:1, the mean ratios calculated on both instruments differed by only 0.7–6.7% between platforms. In the 10:1 experiment, up to 64.7% of iTRAQ ratios from LC‐ESI MS/MS spectra failed S/N thresholds and were excluded from quantitation, while only 0.1% of the equivalent LC‐MALDI iTRAQ ratios were rejected. Re‐analysis of an archived LC‐MALDI sample set stored for 5 months generated 3715 MS/MS spectra for quantitation, compared with 3845 acquired originally, and the average ratios differed by only 3.1%. Overall, MS/MS‐based peptide quantitation performance of offline LC‐MALDI was comparable with on‐line LC‐ESI, which required threefold less time. However, offline LC‐MALDI allows the re‐analysis of archived HPLC‐separated samples.     

GOAT – A simple LC‐MS/MS gradient optimization tool

Modern nano‐HPLC systems are capable of extremely precise control of solvent gradients, allowing high‐resolution separation of peptides. Most proteomics laboratories use a simple linear analytical gradient for nano‐LC‐MS/MS experiments, though recent evidence indicates that optimized non‐linear gradients result in increased peptide and protein identifications from cell lysates. In concurrent work, we examined non‐linear gradients for the analysis of samples fractionated at the peptide level, where the distribution of peptide retention times often varies by fraction. We hypothesized that greater coverage of these samples could be achieved using per‐fraction optimized gradients. We demonstrate that the optimized gradients improve the distribution of peptides throughout the analysis. Using previous generation MS instrumentation, a considerable gain in peptide and protein identifications can be realized. With current MS platforms that have faster electronics and achieve shorter duty cycle, the improvement in identifications is smaller. Our gradient optimization method has been implemented in a simple graphical tool (GOAT) that is MS‐vendor independent, does not require peptide ID input, and is freely available for non‐commercial use at http://proteomics.swmed.edu/goat/     

Data‐independent acquisition‐based SWATH‐MS for quantitative proteomics: a tutorial

Many research questions in fields such as personalized medicine, drug screens or systems biology depend on obtaining consistent and quantitatively accurate proteomics data from many samples. SWATH‐MS is a specific variant of data‐independent acquisition (DIA) methods and is emerging as a technology that combines deep proteome coverage capabilities with quantitative consistency and accuracy. In a SWATH‐MS measurement, all ionized peptides of a given sample that fall within a specified mass range are fragmented in a systematic and unbiased fashion using rather large precursor isolation windows. To analyse SWATH‐MS data, a strategy based on peptide‐centric scoring has been established, which typically requires prior knowledge about the chromatographic and mass spectrometric behaviour of peptides of interest in the form of spectral libraries and peptide query parameters. This tutorial provides guidelines on how to set up and plan a SWATH‐MS experiment, how to perform the mass spectrometric measurement and how to analyse SWATH‐MS data using peptide‐centric scoring. Furthermore, concepts on how to improve SWATH‐MS data acquisition, potential trade‐offs of parameter settings and alternative data analysis strategies are discussed.     

Spectral Libraries for SWATH‐MS Assays for Drosophila melanogaster and Solanum lycopersicum

Quantitative proteomics methods have emerged as powerful tools for measuring protein expression changes at the proteome level. Using MS‐based approaches, it is now possible to routinely quantify thousands of proteins. However, prefractionation of the samples at the protein or peptide level is usually necessary to go deep into the proteome, increasing both MS analysis time and technical variability. Recently, a new MS acquisition method named SWATH is introduced with the potential to provide good coverage of the proteome as well as a good measurement precision without prior sample fractionation. In contrast to shotgun‐based MS however, a library containing experimental acquired spectra is necessary for the bioinformatics analysis of SWATH data. In this study, spectral libraries for two widely used models are built to study crop ripening or animal embryogenesis, Solanum lycopersicum (tomato) and Drosophila melanogaster, respectively. The spectral libraries comprise fragments for 5197 and 6040 proteins for S. lycopersicum and D. melanogaster, respectively, and allow reproducible quantification for thousands of peptides per MS analysis. The spectral libraries and all MS data are available in the MassIVE repository with the dataset identifiers MSV000081074 and MSV000081075 and the PRIDE repository with the dataset identifiers PXD006493 and PXD006495.     

Improving MHC‐I Ligand Identifications from LC‐MS/MS Data by Incorporating Allelic Peptide Motifs

MHC class I (MHC‐I)‐bound ligands play a pivotal role in CD8 T cell immunity and are hence of major interest in understanding and designing immunotherapies. One of the most commonly utilized approaches for detecting MHC ligands is LC‐MS/MS. Unfortunately, the effectiveness of current algorithms to identify MHC ligands from LC‐MS/MS data is limited because the search algorithms used were originally developed for proteomics approaches detecting tryptic peptides. Consequently, the analysis often results in inflated false discovery rate (FDR) statistics and an overall decrease in the number of peptides that pass FDR filters. Andreatta et al. describe a new scoring tool (MS‐rescue) for peptides from MHC‐I immunopeptidome datasets. MS‐rescue incorporates the existence of MHC‐I peptide motifs to rescore peptides from ligandome data. The tool is demonstrated here using peptides assigned from LC‐MS/MS data with PEAKs software but can be deployed on data from any search algorithm. This new approach increased the number of peptides identified by up to 20–30% and promises to aid the discovery of novel MHC‐I ligands with immunotherapeutic potential.     

A comparison of nLC-ESI-MS/MS and nLC-MALDI-MS/MS for GeLC-based protein identification and iTRAQ-based shotgun quantitative proteomics.

The use of nLC-ESI-MS/MS in shotgun proteomics experiments and GeLC-MS/MS analysis is well accepted and routinely available in most proteomics laboratories. However, the same cannot be said for nLC-MALDI MS/MS, which has yet to experience such widespread acceptance, despite the fact that the MALDI technology offers several critical advantages over ESI. As an illustration, in an analysis of moderately complex sample of E. coli proteins, the use MALDI in addition to ESI in GeLC-MS/MS resulted in a 16% average increase in protein identifications, while with more complex samples the number of additional protein identifications increased by an average of 45%. The size of the unique peptides identified by MALDI was, on average, 25% larger than the unique peptides identified by ESI, and they were found to be slightly more hydrophilic. The insensitivity of MALDI to the presence of ionization suppression agents was shown to be a significant advantage, suggesting it be used as a complement to ESI when ion suppression is a possibility. Furthermore, the higher resolution of the TOF/TOF instrument improved the sensitivity, accuracy, and precision of the data over that obtained using only ESI-based iTRAQ experiments using a linear ion trap. Nevertheless, accurate data can be generated with either instrument. These results demonstrate that coupling nanoLC with both ESI and MALDI ionization interfaces improves proteome coverage, reduces the deleterious effects of ionization suppression agents, and improves quantitation, particularly in complex samples.     

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.     

Microproteomics with microfluidic‐based cell sorting: Application to 1000 and 100 immune cells

Ultimately, cell biology seeks to define molecular mechanisms underlying cellular functions. However, heterogeneity within cell populations must be considered for optimal assay design and data interpretation. Although single‐cell analyses are desirable for addressing this issue, practical considerations, including assay sensitivity, limit their broad application. Therefore, omics studies on small numbers of cells in defined subpopulations represent a viable alternative for elucidating cell functions at the molecular level. MS‐based proteomics allows in‐depth proteome exploration, although analyses of small numbers of cells have not been pursued due to loss during the multistep procedure involved. Thus, optimization of the proteomics workflow to facilitate the analysis of rare cells would be useful. Here, we report a microproteomics workflow for limited numbers of immune cells using non‐damaging, microfluidic chip‐based cell sorting and MS‐based proteomics. Samples of 1000 or 100 THP‐1 cells were sorted, and after enzymatic digestion, peptide mixtures were subjected to nano‐LC‐MS analysis. We achieved reasonable proteome coverage from as few as 100‐sorted cells, and the data obtained from 1000‐sorted cells were as comprehensive as those obtained using 1 μg of whole cell lysate. With further refinement, our approach could be useful for studying cell subpopulations or limited samples, such as clinical specimens.     

Large-scale identification of proteins in human salivary proteome by liquid chromatography/mass spectrometry and two-dimensional gel electrophoresis-mass spectrometry

Human saliva contains a large number of proteins and peptides (salivary proteome) that help maintain homeostasis in the oral cavity. Global analysis of human salivary proteome is important for understanding oral health and disease pathogenesis. In this study, large-scale identification of salivary proteins was demonstrated by using shotgun proteomics and two-dimensinal gel electrophoresis-mass spectrometry (2-DE-MS). For the shotgun approach, whole saliva proteins were prefractionated according to molecular weight. The smallest fraction, presumably containing salivary peptides, was directly separated by capillary liquid chromatography (LC). However, the large protein fractions were digested into peptides for subsequent LC separation. Separated peptides were analyzed by on-line electrospray tandem mass spectrometry (MS/MS) using a quadrupole-time of flight mass spectrometer, and the obtained spectra were automatically processed to search human protein sequence database for protein identification. Additionally, 2-DE was used to map out the proteins in whole saliva. Protein spots 105 in number were excised and in-gel digested; and the resulting peptide fragments were measured by matrix-assisted laser desorption/ionization-mass spectrometry and sequenced by LC-MS/MS for protein identification. In total, we cataloged 309 proteins from human whole saliva by using these two proteomic approaches.     

Drawbacks in the use of unconventional hydrophobic anhydrides for histone derivatization in bottom‐up proteomics PTM analysis

MS‐based proteomics has become the most utilized tool to characterize histone PTMs. Since histones are highly enriched in lysine and arginine residues, lysine derivatization has been developed to prevent the generation of short peptides (<6 residues) during trypsin digestion. One of the most adopted protocols applies propionic anhydride for derivatization. However, the propionyl group is not sufficiently hydrophobic to fully retain the shortest histone peptides in RP LC, and such procedure also hampers the discovery of natural propionylation events. In this work we tested 12 commercially available anhydrides, selected based on their safety and hydrophobicity. Performance was evaluated in terms of yield of the reaction, MS/MS fragmentation efficiency, and drift in retention time using the following samples: (i) a synthetic unmodified histone H3 tail, (ii) synthetic modified histone peptides, and (iii) a histone extract from cell lysate. Results highlighted that seven of the selected anhydrides increased peptide retention time as compared to propionic, and several anhydrides such as benzoic and valeric led to high MS/MS spectra quality. However, propionic anhydride derivatization still resulted, in our opinion, as the best protocol to achieve high MS sensitivity and even ionization efficiency among the analyzed peptides.     

ICPLQuant – A software for non‐isobaric isotopic labeling proteomics

The main goal of many proteomics experiments is an accurate and rapid quantification and identification of regulated proteins in complex biological samples. The bottleneck in quantitative proteomics remains the availability of efficient software to evaluate and quantify the tremendous amount of mass spectral data acquired during a proteomics project. A new software suite, ICPLQuant, has been developed to accurately quantify isotope‐coded protein label (ICPL)‐labeled peptides on the MS level during LC‐MALDI and peptide mass fingerprint experiments. The tool is able to generate a list of differentially regulated peptide precursors for subsequent MS/MS experiments, minimizing time‐consuming acquisition and interpretation of MS/MS data. ICPLQuant is based on two independent units. Unit 1 performs ICPL multiplex detection and quantification and proposes peptides to be identified by MS/MS. Unit 2 combines MASCOT MS/MS protein identification with the quantitative data and produces a protein/peptide list with all the relevant information accessible for further data mining. The accuracy of quantification, selection of peptides for MS/MS‐identification and the automated output of a protein list of regulated proteins are demonstrated by the comparative analysis of four different mixtures of three proteins (Ovalbumin, Horseradish Peroxidase and Rabbit Albumin) spiked into the complex protein background of the DGPF Proteome Marker.     

Adenosine‐to‐Inosine RNA Editing in Mouse and Human Brain Proteomes

Proteogenomics is based on the use of customized genome or RNA sequencing databases for interrogation of shotgun proteomics data in search for proteome‐level evidence of genome variations or RNA editing. In this work, the products of adenosine‐to‐inosine RNA editing in human and murine brain proteomes are identified using publicly available brain proteome LC‐MS/MS datasets and an RNA editome database compiled from several sources. After filtering of false‐positive results, 20 and 37 sites of editing in proteins belonging to 14 and 32 genes are identified for murine and human brain proteomes, respectively. Eight sites of editing identified with high spectral counts overlapped between human and mouse brain samples. Some of these sites have been previously reported using orthogonal methods, such as α‐amino‐3‐hydroxy‐5‐methyl‐4‐isoxazolepropionic acid (AMPA) glutamate receptors, CYFIP2, coatomer alpha. Also, differential editing between neurons and microglia is demonstrated in this work for some of the proteins from primary murine brain cell cultures. Because many edited sites are still not characterized functionally at the protein level, the results provide a necessary background for their further analysis in normal and diseased cells and tissues using targeted proteomic approaches.     

More than 100,000 detectable peptide species elute in single shotgun proteomics runs but the majority is inaccessible to data-dependent LC-MS/MS

Shotgun proteomics entails the identification of as many peptides as possible from complex mixtures. Here we investigate how many peptides are detectable by high resolution MS in standard LC runs of cell lysate and how many of them are accessible to data-dependent MS/MS. Isotope clusters were determined by MaxQuant and stringently filtered for charge states and retention times typical of peptides. This resulted in more than 100,000 likely peptide features, of which only about 16% had been targeted for MS/MS. Three instrumental attributes determine the proportion of additional peptides that can be identified: sequencing speed, sensitivity, and precursor ion isolation. In our data, an MS/MS scan rate of 25/s would be necessary to target all peptide features, but this drops to less than 17/s for reasonably abundant peptides. Sensitivity is a greater challenge, with many peptide features requiring long MS/MS injection times (>250 ms). The greatest limitation, however, is the generally low proportion of the target peptide ion intensity in the MS/MS selection window (the "precursor ion fraction" or PIF). Median PIF is only 0.14, making the peptides difficult to identify by standard MS/MS methods. Our results aid in developing strategies to further increase coverage in shotgun proteomics.     

SWATH enables precise label‐free quantification on proteome scale

MS‐based proteomics has emerged as a powerful tool in biological studies. The shotgun proteomics strategy, in which proteolytic peptides are analyzed in data‐dependent mode, enables a detection of the most comprehensive proteome (>10 000 proteins from whole‐cell lysate). The quantitative proteomics uses stable isotopes or label‐free method to measure relative protein abundance. The isotope labeling strategies are more precise and accurate compared to label‐free methods, but labeling procedures are complicated and expensive, and the sample number and types are also limited. Sequential window acquisition of all theoretical mass spectra (SWATH) is a recently developed technique, in which data‐independent acquisition is coupled with peptide spectral library match. In principle SWATH method is able to do label‐free quantification in an MRM‐like manner, which has higher quantification accuracy and precision. Previous data have demonstrated that SWATH can be used to quantify less complex systems, such as spiked‐in peptide mixture or protein complex. Our study first time assessed the quantification performance of SWATH method on proteome scale using a complex mouse‐cell lysate sample. In total 3600 proteins got identified and quantified without sample prefractionation. The SWATH method shows outstanding quantification precision, whereas the quantification accuracy becomes less perfect when protein abundances differ greatly. However, this inaccuracy does not prevent discovering biological correlates, because the measured signal intensities had linear relationship to the sample loading amounts; thus the SWATH method can predict precisely the significance of a protein. Our results prove that SWATH can provide precise label‐free quantification on proteome scale.     

PAS‐cal: A repetitive peptide sequence calibration standard for MALDI mass spectrometry

Mass spectrometers equipped with matrix‐assisted laser desorption/ionization (MALDI‐MS) require frequent multipoint calibration to obtain good mass accuracy over a wide mass range and across large numbers of samples. In this study, we introduce a new synthetic peptide mass calibration standard termed PAS‐cal tailored for MALDI‐MS based bottom‐up proteomics. This standard consists of 30 peptides between 8 and 37 amino acids long and each constructed to contain repetitive sequences of Pro, Ala and Ser as well as one C‐terminal arginine residue. MALDI spectra thus cover a mass range between 750 and 3200 m/z in MS mode and between 100 and 3200 m/z in MS/MS mode. Our results show that multipoint calibration of MS spectra using PAS‐cal peptides compares well to current commercial reagents for protein identification by PMF. Calibration of tandem mass spectra from LC‐MALDI experiments using the longest peptide, PAS‐cal37, resulted in smaller fragment ion mass errors, more matching fragment ions and more protein and peptide identifications compared to commercial standards, making the PAS‐cal standard generically useful for bottom‐up proteomics.     

Bottom‐up proteome analysis of E. coli using capillary zone electrophoresis‐tandem mass spectrometry with an electrokinetic sheath‐flow electrospray interface

The Escherichia coli proteome was digested with trypsin and fractionated using SPE on a C18 SPE column. Seven fractions were collected and analyzed by CZE‐ESI‐MS/MS. The separation was performed in a 60‐cm‐long linear polyacrylamide‐coated capillary with a 0.1% v/v formic acid separation buffer. An electrokinetic sheath‐flow electrospray interface was used to couple the separation capillary with an Orbitrap‐Velos operating in higher‐energy collisional dissociation mode. Each CZE‐ESI‐MS/MS run lasted 50 min and total MS time was 350 min. A total of 23 706 peptide spectra matches, 4902 peptide IDs, and 871 protein group IDs were generated using MASCOT with false discovery rate less than 1% on the peptide level. The total mass spectrometer analysis time was less than 6 h, the sample identification rate (145 proteins/h) was more than two times higher than previous studies of the E. coli proteome, and the amount of sample consumed (<1 μg) was roughly fourfold less than previous studies. These results demonstrate that CZE is a useful tool for the bottom‐up analysis of prokaryote proteomes.     

Chemical de‐O‐glycosylation of glycoproteins for application in LC‐based proteomics

We describe a cyclic on‐column procedure for the sequential degradation of complex O‐glycans on proteins or peptides by periodate oxidation of sugars and cleavage of oxidation products by elimination. Desialylated glycoproteins were immobilized to alkali‐stable, reversed‐phase Poros 20 beads followed by two degradation cycles and the eluted apoproteins were either separated by SDS gel electrophoresis or digested with trypsin prior to LC/ESI‐MS. We demonstrate on the peptide and protein level that even complex glycan moieties are removed under mild conditions with only minimal effects on structural integrity of the peptide core by fragmentation, dehydration or by racemization of the Lys/Arg residues. The protocol is applicable on gel‐immobilized glycoproteins after SDS gel electrophoresis. Conversion of O‐glycoproteins into their corresponding apoproteins should result in facilitated accessibility of tryptic cleavage sites, increase the numbers of peptide fragments, and accordingly enhance protein coverage and identification rates within the subproteome of mucin‐type O‐glycoproteins.