Concepts and strategies of soybean seed proteomics using the shotgun proteomics approach

ABSTRACT

Introduction: The last decade has yielded significant developments in the field of proteomics, especially in mass spectrometry (MS) and data analysis tools. In particular, a shift from gel-based to MS-based proteomics has been observed, thereby providing a platform with which to construct proteome atlases for all life forms. Nevertheless, the analysis of plant proteomes, especially those of samples that contain high-abundance proteins (HAPs), such as soybean seeds, remains challenging.

Areas covered: Here, we review recent progress in soybean seed proteomics and highlight advances in HAPs depletion methods and peptide pre-fractionation, identification, and quantification methods. We also suggest a pipeline for future proteomic analysis, in order to increase the dynamic coverage of the soybean seed proteome.

Expert opinion: Because HAPs limit the dynamic resolution of the soybean seed proteome, the depletion of HAPs is a prerequisite of high-throughput proteome analysis, and owing to the use of two-dimensional gel electrophoresis-based proteomic approaches, few soybean seed proteins have been identified or characterized. Recent advances in proteomic technologies, which have significantly increased the proteome coverage of other plants, could be used to overcome the current complexity and limitation of soybean seed proteomics.     

Detecting differential and correlated protein expression in label-free shotgun proteomics

Recent studies have revealed a relationship between protein abundance and sampling statistics, such as sequence coverage, peptide count, and spectral count, in label-free liquid chromatography-tandem mass spectrometry (LC-MS/MS) shotgun proteomics. The use of sampling statistics offers a promising method of measuring relative protein abundance and detecting differentially expressed or coexpressed proteins. We performed a systematic analysis of various approaches to quantifying differential protein expression in eukaryotic Saccharomyces cerevisiae and prokaryotic Rhodopseudomonas palustris label-free LC-MS/MS data. First, we showed that, among three sampling statistics, the spectral count has the highest technical reproducibility, followed by the less-reproducible peptide count and relatively nonreproducible sequence coverage. Second, we used spectral count statistics to measure differential protein expression in pairwise experiments using five statistical tests: Fisher's exact test, G-test, AC test, t-test, and LPE test. Given the S. cerevisiae data set with spiked proteins as a benchmark and the false positive rate as a metric, our evaluation suggested that the Fisher's exact test, G-test, and AC test can be used when the number of replications is limited (one or two), whereas the t-test is useful with three or more replicates available. Third, we generalized the G-test to increase the sensitivity of detecting differential protein expression under multiple experimental conditions. Out of 1622 identified R. palustris proteins in the LC-MS/MS experiment, the generalized G-test detected 1119 differentially expressed proteins under six growth conditions. Finally, we studied correlated expression of these 1119 proteins by analyzing pairwise expression correlations and by delineating protein clusters according to expression patterns. Through pairwise expression correlation analysis, we demonstrated that proteins co-located in the same operon were much more strongly coexpressed than those from different operons. Combining cluster analysis with existing protein functional annotations, we identified six protein clusters with known biological significance. In summary, the proposed generalized G-test using spectral count sampling statistics is a viable methodology for robust quantification of relative protein abundance and for sensitive detection of biologically significant differential protein expression under multiple experimental conditions in label-free shotgun proteomics.     

Management and visualization of whole genome shotgun assemblies using SAM

We have designed and implemented a system to manage whole genome shotgun sequences and whole genome sequence assembly data flow. The Sequence Assembly Manager (SAM) consists primarily of a MySQL relational database and Perl applications designed to easily manipulate and coordinate the analysis of sequence information and to view and report genome assembly progress through its Common Gateway Interface (CGI) web interface. The application includes a tool to compare sequence assemblies to fingerprint maps that has been used successfully to improve and validate both maps and sequence assemblies of the Rhodococcus sp.RHAI and Cryptococcus neoformans WM276 genomes.     

Phage-induced expression of CRISPR-associated proteins is revealed by shotgun proteomics in Streptococcus thermophilus

The CRISPR/Cas system, comprised of clustered regularly interspaced short palindromic repeats along with their associated (Cas) proteins, protects bacteria and archaea from viral predation and invading nucleic acids. While the mechanism of action for this acquired immunity is currently under investigation, the response of Cas protein expression to phage infection has yet to be elucidated. In this study, we employed shotgun proteomics to measure the global proteome expression in a model system for studying the CRISPR/Cas response in S. thermophilus DGCC7710 infected with phage 2972. Host and viral proteins were simultaneously measured following inoculation at two different multiplicities of infection and across various time points using two-dimensional liquid chromatography tandem mass spectrometry. Thirty-seven out of forty predicted viral proteins were detected, including all proteins of the structural virome and viral effector proteins. In total, 1,013 of 2,079 predicted S. thermophilus proteins were detected, facilitating the monitoring of host protein synthesis changes in response to virus infection. Importantly, Cas proteins from all four CRISPR loci in the S. thermophilus DGCC7710 genome were detected, including loci previously thought to be inactive. Many Cas proteins were found to be constitutively expressed, but several demonstrated increased abundance following infection, including the signature Cas9 proteins from the CRISPR1 and CRISPR3 loci, which are key players in the interference phase of the CRISPR/Cas response. Altogether, these results provide novel insights into the proteomic response of S. thermophilus, specifically CRISPR-associated proteins, upon phage 2972 infection.     

Advances in shotgun proteomics and the analysis of membrane proteomes

The emergence of shotgun proteomics has facilitated the numerous biological discoveries made by proteomic studies. However, comprehensive proteomic analysis remains challenging and shotgun proteomics is a continually changing field. This review details the recent developments in shotgun proteomics and describes emerging technologies that will influence shotgun proteomics going forward. In addition, proteomic studies of integral membrane proteins remain challenging due to the hydrophobic nature in integral membrane proteins and their general low abundance levels. However, there have been many strategies developed for enriching, isolating and separating membrane proteins for proteomic analysis that have moved this field forward. In summary, while shotgun proteomics is a widely used and mature technology, the continued pace of improvements in mass spectrometry and proteomic technology and methods indicate that future studies will have an even greater impact on biological discovery.     

Functional analysis of proteins and protein species using shotgun proteomics and linear mathematics

Covalent post-translational modification of proteins is the primary modulator of protein function in the cell. It greatly expands the functional potential of the proteome compared to the genome. In the past few years shotgun proteomics-based research, where the proteome is digested into peptides prior to mass spectrometric analysis has been prolific in this area. It has determined the kinetics of tens of thousands of sites of covalent modification on an equally large number of proteins under various biological conditions and uncovered a transiently active regulatory network that extends into diverse branches of cellular physiology. In this review, we discuss this work in light of the concept of protein speciation, which emphasizes the entire post-translationally modified molecule and its interactions and not just the modification site as the functional entity. Sometimes, particularly when considering complex multisite modification, all of the modified molecular species involved in the investigated condition, the protein species must be completely resolved for full understanding. We present a mathematical technique that delivers a good approximation for shotgun proteomics data.     

Defining the role of the Escherichia coli chaperone SecB using comparative proteomics

To improve understanding and identify novel substrates of the cytoplasmic chaperone SecB in Escherichia coli, we analyzed a secB null mutant using comparative proteomics. The secB null mutation did not affect cell growth but caused significant differences at the proteome level. In the absence of SecB, dynamic protein aggregates containing predominantly secretory proteins accumulated in the cytoplasm. Unprocessed secretory proteins were detected in radiolabeled whole cell lysates. Furthermore, the assembly of a large fraction of the outer membrane proteome was slowed down, whereas its steady state composition was hardly affected. In response to aggregation and delayed sorting of secretory proteins, cytoplasmic chaperones DnaK, GroEL/ES, ClpB, IbpA/B, and HslU were up-regulated severalfold, most likely to stabilize secretory proteins during their delayed translocation and/or rescue aggregated secretory proteins. The SecB/A dependence of 12 secretory proteins affected by the secB null mutation (DegP, FhuA, FkpA, OmpT, OmpX, OppA, TolB, TolC, YbgF, YcgK, YgiW, and YncE) was confirmed by "classical" pulse-labeling experiments. Our study more than triples the number of known SecB-dependent secretory proteins and shows that the primary role of SecB is to facilitate the targeting of secretory proteins to the Sec-translocase.     

Thermodynamic analysis of protein-ligand interactions in complex biological mixtures using a shotgun proteomics approach

Shotgun proteomics protocols are widely used for the identification and/or quantitation of proteins in complex biological samples. Described here is a shotgun proteomics protocol that can be used to identify the protein targets of biologically relevant ligands in complex protein mixtures. The protocol combines a quantitative proteomics platform with a covalent modification strategy, termed Stability of Proteins from Rates of Oxidation (SPROX), which utilizes the denaturant dependence of hydrogen peroxide-mediated oxidation of methionine side chains in proteins to assess the thermodynamic properties of proteins and protein-ligand complexes. The quantitative proteomics platform involves the use of isobaric mass tags and a methionine-containing peptide enhancement strategy. The protocol is evaluated in a ligand binding experiment designed to identify the proteins in a yeast cell lysate that bind the well-known enzyme cofactor, β-nicotinamide adenine dinucleotide (NAD+). The protocol is also used to investigate the protein targets of resveratrol, a biologically active ligand with less well-understood protein targets. A known protein target of resveratrol, cytosolic aldehyde dehydrogenase, was identified in addition to six other potential new proteins targets including four that are associated with the protein translation machinery, which has previously been implicated as a target of resveratrol.     

Comparative secretome analysis of human follicular dermal papilla cells and fibroblasts using shotgun proteomics

The dermal papilla cells (DPCs) of hair follicles are known to secrete paracrine factors for follicular cells. Shotgun proteomic analysis was performed to compare the expression profiles of the secretomes of human DPCs and dermal fibroblasts (DFs). In this study, the proteins secreted by DPCs and matched DFs were analyzed by 1DE/LTQ FTICR MS/MS, semi-quantitatively determined using emPAI mole percent values and then characterized using protein interaction network analysis. Among the 1,271 and 1,188 proteins identified in DFs and DPCs, respectively, 1,529 were further analyzed using the Ingenuity Pathway Analysis tool. We identified 28 DPC-specific extracellular matrix proteins including transporters (ECM1, A2M), enzymes (LOX, PON2), and peptidases (C3, C1R). The biochemically- validated DPC-specific proteins included thrombospondin 1 (THBS1), an insulin-like growth factor binding protein3 (IGFBP3), and, of particular interest, an integrin beta1 subunit (ITGB1) as a key network core protein. Using the shotgun proteomic technique and network analysis, we selected ITGB1, IGFBP3, and THBS1 as being possible hair-growth modulating protein biomarkers.     

Fast and accurate identification of semi-tryptic peptides in shotgun proteomics

MOTIVATION: One of the major problems in shotgun proteomics is the low peptide coverage when analyzing complex protein samples. Identifying more peptides, e.g. non-tryptic peptides, may increase the peptide coverage and improve protein identification and/or quantification that are based on the peptide identification results. Searching for all potential non-tryptic peptides is, however, time consuming for shotgun proteomics data from complex samples, and poses a challenge for a routine data analysis. RESULTS: We hypothesize that non-tryptic peptides are mainly created from the truncation of regular tryptic peptides before separation. We introduce the notion of truncatability of a tryptic peptide, i.e. the probability of the peptide to be identified in its truncated form, and build a predictor to estimate a peptide's truncatability from its sequence. We show that our predictions achieve useful accuracy, with the area under the ROC curve from 76% to 87%, and can be used to filter the sequence database for identifying truncated peptides. After filtering, only a limited number of tryptic peptides with the highest truncatability are retained for non-tryptic peptide searching. By applying this method to identification of semi-tryptic peptides, we show that a significant number of such peptides can be identified within a searching time comparable to that of tryptic peptide identification.     

Modeling the feasibility of whole genome shotgun sequencing using a pairwise end strategy

In pairwise end sequencing, sequences are determined from both ends of random subclones derived from a DNA target. Sufficiently similar overlapping end sequences are identified and grouped into contigs. When a clone's paired end sequences fall in different contigs, the contigs are connected together to form scaffolds. Increasingly, the goals of pairwise strategies are large and highly repetitive genomic targets. Here, we consider large-scale pairwise strategies that employ mixtures of subclone sizes. We explore the properties of scaffold formation within a hybrid theory/simulation mathematical model of a genomic target that contains many repeat families. Using this model, we evaluate problems that may arise, such as falsely linked end sequences (due either to random matches or to homologous repeats) and scaffolds that terminate without extending the full length of the target. We illustrate our model with an exploration of a strategy for sequencing the human genome. Our results show that, for a strategy that generates 10-fold sequence coverage derived from the ends of clones ranging in length from 2 to 150 kb, using an appropriate rule for detecting overlaps, we expect few false links while obtaining a single scaffold extending the length of each chromosome.     

On the relevance of peptide sequence permutations in shotgun proteomics studies

In collision-induced dissociation (CID) of peptides, it has been observed that rearrangement processes can take place that appear to permute/scramble the original primary structure, which may in principle adversely affect peptide identification. Here, an analysis of sequence permutation in tandem mass spectra is presented for a previously published proteomics study on P. aeruginosa (Scherl et al., J. Am. Soc. Mass Spectrom.2008, 19, 891) conducted using an LTQ-orbitrap. Overall, 4878 precursor ions are matched by considering the accurate mass (i.e., <5 ppm) of the precursor ion and at least one fragment ion that confirms the sequence. The peptides are then grouped into higher- and lower-confidence data sets, using five fragment ions as a cutoff for higher-confidence identification. It is shown that the propensity for sequence permutation increases with the length of the tryptic peptide in both data sets. A higher charge state (i.e., 3+ vs 2+) also appears to correlate with a higher appearance of permuted masses for larger peptides. The ratio of these permuted sequence ions, compared to all tandem mass spectral peaks, reaches ～25% in the higher-confidence data set, compared to an estimated incidence of false positives for permuted masses (maximum ～8%), based on a null-hypothesis decoy data set.     

Optimization and use of peptide mass measurement accuracy in shotgun proteomics

Mass spectrometers that provide high mass accuracy such as FT-ICR instruments are increasingly used in proteomic studies. Although the importance of accurately determined molecular masses for the identification of biomolecules is generally accepted, its role in the analysis of shotgun proteomic data has not been thoroughly studied. To gain insight into this role, we used a hybrid linear quadrupole ion trap/FT-ICR (LTQ FT) mass spectrometer for LC-MS/MS analysis of a highly complex peptide mixture derived from a fraction of the yeast proteome. We applied three data-dependent MS/MS acquisition methods. The FT-ICR part of the hybrid mass spectrometer was either not exploited, used only for survey MS scans, or also used for acquiring selected ion monitoring scans to optimize mass accuracy. MS/MS data were assigned with the SEQUEST algorithm, and peptide identifications were validated by estimating the number of incorrect assignments using the composite target/decoy database search strategy. We developed a simple mass calibration strategy exploiting polydimethylcyclosiloxane background ions as calibrant ions. This strategy allowed us to substantially improve mass accuracy without reducing the number of MS/MS spectra acquired in an LC-MS/MS run. The benefits of high mass accuracy were greatest for assigning MS/MS spectra with low signal-to-noise ratios and for assigning phosphopeptides. Confident peptide identification rates from these data sets could be doubled by the use of mass accuracy information. It was also shown that improving mass accuracy at a cost to the MS/MS acquisition rate substantially lowered the sensitivity of LC-MS/MS analyses. The use of FT-ICR selected ion monitoring scans to maximize mass accuracy reduced the number of protein identifications by 40%.     

Combination of two-dimensional electrophoresis and shotgun peptide sequencing in comparative proteomics

Two-dimensional electrophoresis (2-DE) and shotgun peptide sequencing are the two major technologies to compare the expression profile of proteins, which is also referred to as comparative proteomics or quantitative proteomics. Although the methodologies, such as difference gel electrophoresis for 2-DE and isotope-coded affinity tags for shotgun peptide sequencing, have made rapid progress, these two approaches have their own strengths and weaknesses. Therefore, the combination of the two methodologies is beneficial for the purpose of better comparative proteomics, especially in comprehensive coverage of the proteome and protein information such as post-translational modifications.     

BuildSummary: using a group-based approach to improve the sensitivity of peptide/protein identification in shotgun proteomics

The target-decoy database search strategy is widely accepted as a standard method for estimating the false discovery rate (FDR) of peptide identification, based on which peptide-spectrum matches (PSMs) from the target database are filtered. To improve the sensitivity of protein identification given a fixed accuracy (frequently defined by a protein FDR threshold), a postprocessing procedure is often used that integrates results from different peptide search engines that had assayed the same data set. In this work, we show that PSMs that are grouped by the precursor charge, the number of missed internal cleavage sites, the modification state, and the numbers of protease termini and that the proteins grouped by their unique peptide count should be filtered separately according to the given FDR. We also develop an iterative procedure to filter the PSMs and proteins simultaneously, according to the given FDR. Finally, we present a general framework to integrate the results from different peptide search engines using the same FDR threshold. Our method was tested with several shotgun proteomics data sets that were acquired by multiple LC/MS instruments from two different biological samples. The results showed a satisfactory performance. We implemented the method in a user-friendly software package called BuildSummary, which can be downloaded for free from http://www.proteomics.ac.cn/software/proteomicstools/index.htm as part of the software suite ProteomicsTools.     

Identification of isochore boundaries in the human genome using the technique of wavelet multiresolution analysis

Incorporated with the Z curve method, the technique of wavelet multiresolution (also known as multiscale) analysis has been proposed to identify the boundaries of isochores in the human genome. The human MHC sequence and the longest contigs of human chromosomes 21 and 22 are used as examples. The boundary between the isochores of Class III and Class II in the MHC sequence has been detected and found to be situated at the position 2,490,368bp. This result is in good agreement with the experimental evidence. An isochore with a length of about 7Mb in chromosome 21 has been identified and found to be gene- and Alu-poor. We have also found that the G+C content of chromosome 21 is more homogeneous than that of chromosome 22. Compared with the window-based methods, the present method has the highest resolution for identifying the boundaries of isochores, even at a scale of single base. Compared with the entropic segmentation method, the present method has the merits of more intuitiveness and less calculations. The important conclusion drawn in this study is that the segmentation points, at which the G+C content undergoes relatively dramatic changes, do exist in the human genome. These 'singularity' points may be considered to be candidates of isochore boundaries in the human genome. The method presented is a general one and can be used to analyze any other genomes.     

Implementation and evaluation of relative and absolute quantification in shotgun proteomics with label-free methods

Tandem mass spectrometry allows for fast protein identification in a complex sample. As mass spectrometers get faster, more sensitive and more accurate, methods were devised by many academic research groups and commercial suppliers that allow protein research also in quantitative respect. Since label-free methods are an attractive alternative to labeling approaches for proteomics researchers seeking for accurate quantitative results we evaluated several open-source analysis tools in terms of performance on two reference data sets, explicitly generated for this purpose.In this paper we present an implementation, T3PQ (Top 3 Protein Quantification), of the method suggested by Silva and colleagues for LC-MS^E applications and we demonstrate its applicability to data generated on FT-ICR instruments acquiring in data dependent acquisition (DDA) mode. In order to validate this method and to show its usefulness also for absolute protein quantification, we generated a reference data set of a sample containing four different proteins with known concentrations. Furthermore, we compare three other label-free quantification methods using a complex biological sample spiked with a standard protein in defined concentrations. We evaluate the applicability of these methods and the quality of the results in terms of robustness and dynamic range of the spiked-in protein as well as other proteins also detected in the mixture. We discuss drawbacks of each method individually and consider crucial points for experimental designs. The source code of our implementation is available under the terms of the GNU GPLv3 and can be downloaded from sourceforge (http://fqms.svn.sourceforge.net/svnroot/fqms). A tarball containing the data used for the evaluation is available on the FGCZ web server (http://fgcz-data.uzh.ch/public/T3PQ.tgz).     

Strategic shotgun proteomics approach for efficient construction of an expression map of targeted protein families in hepatoma cell lines

An expression map of the most abundant proteins in human hepatoma HepG2 cells was established by a combination of complementary shotgun proteomics approaches. Two-dimensional liquid chromatography (LC)-nano electrospray ionization (ESI) tandem mass spectrometry (MS/MS) as well as one-dimensional LC-matrix-assisted laser desorption/ionization MS/MS were evaluated and shown that additional separation introduced at the peptide level was not as efficient as simple prefractionation of protein extracts in extending the range and total number of proteins identified. Direct LC-nanoESI MS/MS analyses of peptides from total solubilized fraction and the excised gel bands from one-dimensional sodium dodecyl sulfate-polyacrylamide gel electrophoresis fractionated insolubilized fraction afforded the best combination in efficient construction of a nonredundant cell map. Compiling data from multiple variations of rapid shotgun proteomics analyses is nonetheless useful to increase sequence coverage and confidence of hits especially for those proteins identified primarily by a single or two peptide matches. While the returned hit score in general reflects the abundance of the respective proteins, it is not a reliable index for differential expression. Using another closely related hepatoma Hep3B as a comparative basis, 16 proteins with more than two-fold difference in expression level as defined by spot intensity in two-dimensional gel electrophoresis analysis were identified which notably include members of the heat shock protein (Hsp) and heterogeneous nuclear ribonucleoprotein (hnRPN) families. The observed higher expression level of hnRNP A2/B1 and Hsp90 in Hep3B led to a search for reported functional roles mediated in concert by both these multifunctional cellular chaperones. In agreement with the proposed model for telomerase and telomere bound proteins in promoting their interactions, data was obtained which demonstrated that the expression proteomics data could be correlated with longer telomeric length in tumorigenic Hep3B. This biological significance constitutes the basis for further delineation of the dynamic interactions and modifications of the two protein families and demonstrated how proteomic and biological investigation could be mutually substantiated in a productive cycle of hypothesis and pattern driven research.