Enabling proteomic studies with RNA‐Seq: The proteome of tomato pollen as a test case

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Lectin affinity chromatography (LAC) can provide a valuable front-end enrichment strategy for the study of N-glycoproteins and has been used to characterize a broad range eukaryotic N-glycoproteomes. Moreover, studies with mammalian systems have suggested that the use of multiple lectins with different affinities can be particularly effective. A multi-lectin approach has also been reported to provide a significant benefit for the analysis of plant N-glycoproteins; however, it has yet to be determined whether certain lectins, or combinations of lectins are optimal for plant N-glycoproteome profiling; or whether specific lectins show preferential association with particular N-glycosylation sites or N-glycan structures. We describe here a comparative study of three mannose-binding lectins, concanavalin A, snowdrop lectin, and lentil lectin, to profile the N-glycoproteome of mature green stage tomato (Solanum lycopersicum) fruit pericarp. Through coupling lectin affinity chromatography with a shotgun proteomics strategy, we identified 448 putative N-glycoproteins, whereas a parallel lectin affinity chromatography plus hydrophilic interaction chromatography analysis revealed 318 putative N-glycosylation sites on 230 N-glycoproteins, of which 100 overlapped with the shotgun analysis, as well as 17 N-glycan structures. The use of multiple lectins substantially increased N-glycoproteome coverage and although there were no discernible differences in the structures of N-glycans, or the charge, isoelectric point (pI) or hydrophobicity of the glycopeptides that differentially bound to each lectin, differences were observed in the amino acid frequency at the ؊1 and ؉1 subsites of the N-glycosylation sites. We also demonstrated an alternative and complementary in planta recombinant expression strategy, followed by affinity MS analysis, to identify the putative N-glycan structures of glycoproteins whose abundance is too low to be readily determined by a shotgun approach, and/or combined with deglycosylation for predicted deamidated sites, using a xyloglucan-specific endoglucanase inhibitor protein as an example. Molecular & Cellular

Section: Methodsmentioning

confidence: 99%

A Comparative Study of Lectin Affinity Based Plant N-Glycoproteome Profiling Using Tomato Fruit as a Model

Ruiz‐May

Hucko

Howe

et al. 2014

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“…As nonmodel organisms, both plantain and banana lack complete genomic sequence information, which has imposed obvious limits on protein identification through predictive matching or peptide sequences. However, in the past few years, next generation sequencing technologies have provided a new paradigm for genome and transcriptome (RNA-Seq) analysis for nonmodel organisms with unknown genomes (34). Recently we have completed a plantain RNASeq database (submitted to NCBI databases with submission number as SRA054939), facilitating iTRAQ-based quantitative proteomics to investigate the dynamic proteome response to cold stress.…”

mentioning

confidence: 99%

Quantitative Proteomic Analysis Reveals that Antioxidation Mechanisms Contribute to Cold Tolerance in Plantain (Musa paradisiaca L.; ABB Group) Seedlings

Yang

et al. 2012

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104

Banana and its close relative, plantain are globally important crops and there is considerable interest in optimizing their cultivation. Plantain has superior cold tolerance compared with banana and a thorough understanding of the molecular mechanisms and responses of plantain to cold stress has great potential value for developing cold tolerant banana cultivars. In this study, we used iTRAQbased comparative proteomic analysis to investigate the temporal responses of plantain to cold stress. Plantain seedlings were exposed for 0, 6, and 24 h of cold stress at 8°C and subsequently allowed to recover for 24 h at 28°C. A total of 3477 plantain proteins were identified, of which 809 showed differential expression from the three treatments. The majority of differentially expressed proteins were predicted to be involved in oxidation-reduction, including oxylipin biosynthesis, whereas others were associated with photosynthesis, photorespiration, and several primary metabolic processes, such as carbohydrate metabolic process and fatty acid beta-oxidation. Western blot analysis and enzyme activity assays were performed on seven differentially expressed, cold-response candidate plantain proteins to validate the proteomics data. Similar analyses of the seven candidate proteins were performed in cold-sensitive banana to examine possible functional conservation, and to compare the results to equivalent responses between the two species. Consistent results were achieved by Western blot and enzyme activity assays, demonstrating that the quantitative proteomics data collected in this study are reliable. Our results suggest that an increase of antioxidant capacity through adapted ROS scavenging capability, reduced production of ROS, and decreased lipid peroxidation contribute to molecular mechanisms for the increased cold tolerance in plantain. To the best of our knowledge, this is the first report of a global investigation on molecular responses of plantain to cold stress by proteomic analysis. Molecular & Cellular

“…Next, these exon sequences are assembled into all theoretical exon-exon (and exon-intron) combinations, and then the sequences are translated into polypeptide sequences and used for MS-based searching to discover novel splice variant peptides (27)(28)(29)(30). To extend this approach, several research groups have restricted their exon-exon database to include only those sequences corroborated with transcript expression data (31)(32)(33), thereby eliminating spurious sequences. Two other approaches developed include a method that directly translates RNA sequence from expressed sequence tag (EST) contigs (34 -37) and a proteogenomics strategy that uses the genome as a template for peptide sequence alignment (38,39).…”

mentioning

confidence: 99%

Discovery and Mass Spectrometric Analysis of Novel Splice-junction Peptides Using RNA-Seq

Sheynkman

Shortreed

Frey

et al. 2013

120

205

Human proteomic databases required for MS peptide identification are frequently updated and carefully curated, yet are still incomplete because it has been challenging to acquire every protein sequence from the diverse assemblage of proteoforms expressed in every tissue and cell type. In particular, alternative splicing has been shown to be a major source of this cell-specific proteomic variation. Many new alternative splice forms have been detected at the transcript level using next generation sequencing methods, especially RNA-Seq, but it is not known how many of these transcripts are being translated. Leveraging the unprecedented capabilities of next generation sequencing methods, we collected RNA-Seq and proteomics data from the same cell population (Jurkat cells) and created a bioinformatics pipeline that builds customized databases for the discovery of novel splicejunction peptides. Eighty million paired-end Illumina reads and ϳ500,000 tandem mass spectra were used to identify 12,873 transcripts (19,320 including isoforms) and 6810 proteins. We developed a bioinformatics workflow to retrieve high-confidence, novel splice junction sequences from the RNA data, translate these sequences into the analogous polypeptide sequence, and create a customized splice junction database for MS searching. Based on the RefSeq gene models, we detected 136,123 annotated and 144,818 unannotated transcript junctions. Of those, 24,834 unannotated junctions passed various quality filters (e.g. minimum read depth) and these entries were translated into 33,589 polypeptide sequences and used for database searching. We discovered 57 splice junction peptides not present in the Uniprot-Trembl proteomic database comprising an array of different splicing events, including skipped exons, alternative donors and acceptors, and noncanonical transcriptional start sites. To our knowledge this is the first example of using sample-specific RNA-Seq data to create a splice-junction database and discover new peptides resulting from alternative splicing. Mass spectrometry-based proteomics relies on accurate databases to identify and quantify proteins, including those derived from splice variants, indels, and single nucleotide variants (SNVs) 1 (1). Most computational search algorithms detect peptides by scoring the degree of similarity between in silico derived and experimental peptide spectra, and thus can only identify peptides that are present in the proteomic database. If the polypeptide sequence is not present in the database used for searching, even if the peptide is present in the sample, it will fail to be detected.Human proteomic databases used for mass spectrometric peptide identification are frequently updated and carefully curated, yet are still incomplete. Despite efforts to comprehensively annotate every gene product, there are still many undiscovered proteoforms (2) because the complete human proteome-the aggregate of all protein products expressed in every tissue, cell, and cellular state-turns out to be vastly more complex than was...