Plant proteogenomics: from protein extraction to improved gene predictions

Transcriptome and Proteome Co-Profiling Offers an Understanding of Pre-Harvest Sprouting (PHS) Molecular Mechanisms in Wheat (Triticum aestivum)

While wheat (Triticum aestivum L.) is a widely grown and enjoyed crop, the diverse and complex global situation and climate are exacerbating the instability of its supply. In particular, pre-harvest sprouting (PHS) is one of the major abiotic stresses that frequently occurs due to irregular climate conditions, causing serious damage to wheat and its quality. In this study, transcriptomic analysis with RNA-seq and proteomic analysis with LC-MS/MS were performed in PHS-treated spikes from two wheat cultivars presenting PHS sensitivity and tolerance, respectively. A total of 13,154 differentially expressed genes (DEGs) and 706 differentially expressed proteins (DEPs) were identified in four comparison groups between the susceptible/tolerant cultivars. Gene function and correlation analysis were performed to determine the co-profiled genes and proteins affected by PHS treatment. In the functional annotation of each comparative group, similar functions were confirmed in each cultivar under PHS treatment; however, in Keumgang PHS+7 (K7) vs. Woori PHS+7 (W7), functional annotations presented clear differences in the "spliceosome" and "proteasome" pathways. In addition, our results indicate that alternative splicing and ubiquitin-proteasome support the regulation of germination and seed dormancy. This study provides an advanced understanding of the functions involved in transcription and translation related to PHS mechanisms, thus enabling specific proposals for the further analysis of germination and seed dormancy mechanisms and pathways in wheat.

First comprehensive analysis of lysine succinylation in paper mulberry (Broussonetia papyrifera)

BACKGROUND

Lysine succinylation is a naturally occurring post-translational modification (PTM) that is ubiquitous in organisms. Lysine succinylation plays important roles in regulating protein structure and function as well as cellular metabolism. Global lysine succinylation at the proteomic level has been identified in a variety of species; however, limited information on lysine succinylation in plant species, especially paper mulberry, is available. Paper mulberry is not only an important plant in traditional Chinese medicine, but it is also a tree species with significant economic value. Paper mulberry is found in the temperate and tropical zones of China. The present study analyzed the effects of lysine succinylation on the growth, development, and physiology of paper mulberry.

RESULTS

A total of 2097 lysine succinylation sites were identified in 935 proteins associated with the citric acid cycle (TCA cycle), glyoxylic acid and dicarboxylic acid metabolism, ribosomes and oxidative phosphorylation; these pathways play a role in carbon fixation in photosynthetic organisms and may be regulated by lysine succinylation. The modified proteins were distributed in multiple subcellular compartments and were involved in a wide variety of biological processes, such as photosynthesis and the Calvin-Benson cycle.

CONCLUSION

Lysine-succinylated proteins may play key regulatory roles in metabolism, primarily in photosynthesis and oxidative phosphorylation, as well as in many other cellular processes. In addition to the large number of succinylated proteins associated with photosynthesis and oxidative phosphorylation, some proteins associated with the TCA cycle are succinylated. Our study can serve as a reference for further proteomics studies of the downstream effects of succinylation on the physiology and biochemistry of paper mulberry.

Peptimapper: proteogenomics workflow for the expert annotation of eukaryotic genomes

Background

Accurate structural annotation of genomes is still a challenge, despite the progress made over the past decade. The prediction of gene structure remains difficult, especially for eukaryotic species, and is often erroneous and incomplete. We used a proteogenomics strategy, taking advantage of the combination of proteomics datasets and bioinformatics tools, to identify novel protein coding-genes and splice isoforms, assign correct start sites, and validate predicted exons and genes.

Results

Our proteogenomics workflow, Peptimapper, was applied to the genome annotation of Ectocarpus sp., a key reference genome for both the brown algal lineage and stramenopiles. We generated proteomics data from various life cycle stages of Ectocarpus sp. strains and sub-cellular fractions using a shotgun approach. First, we directly generated peptide sequence tags (PSTs) from the proteomics data. Second, we mapped PSTs onto the translated genomic sequence. Closely located hits (i.e., PSTs locations on the genome) were then clustered to detect potential coding regions based on parameters optimized for the organism. Third, we evaluated each cluster and compared it to gene predictions from existing conventional genome annotation approaches. Finally, we integrated cluster locations into GFF files to use a genome viewer. We identified two potential novel genes, a ribosomal protein L22 and an aryl sulfotransferase and corrected the gene structure of a dihydrolipoamide acetyltransferase. We experimentally validated the results by RT-PCR and using transcriptomics data.

Conclusions

Peptimapper is a complementary tool for the expert annotation of genomes. It is suitable for any organism and is distributed through a Docker image available on two public bioinformatics docker repositories: Docker Hub and BioShaDock. This workflow is also accessible through the Galaxy framework and for use by non-computer scientists at https://galaxy.protim.eu.

Data are available via ProteomeXchange under identifier PXD010618.

Electronic supplementary material

The online version of this article (10.1186/s12864-019-5431-9) contains supplementary material, which is available to authorized users.

Shotgun proteomic analysis of photoperiod regulated dormancy induction in grapevine

Certain grapevine genotypes become dormant in response to decreasing photoperiod and others require low temperature or both environmental cues to induce dormancy. This study used a proteomic approach to gain an understanding of the underlying molecular events involved in bud dormancy commitment. Two F₂ siblings (F2-110 and F2-040) with differences in photoperiod induced dormancy responsiveness were subjected to long day (LD, 15 h, paradormancy maintenance or dormancy inhibition) or short day (SD, 13 h, endodormancy commitment) treatment. Proteins were extracted at two time points (28 days and 42 days) of LD and SD photoperiod exposure, and label-free quantitative shotgun proteomic analysis was performed for three biological replicates of each treatment and time point. A total of 1577 non-redundant proteins were identified in the combined dataset of eight different conditions (2 genotypes, 2 photoperiods and 2 timepoints, available via ProteomeXchange with identifier PXD001627). Genotype specific patterns of budbreak and protein expression were detected in response to the differential photoperiod treatment at the two time points. Peroxidases, dehydrogenases and superoxide dismutases were more abundant at 42 SD than at 28 SD in the dormancy responsive F2-110, suggesting that oxidative stress response related proteins could be markers of endodormancy commitment in grapevine buds.

Five omic technologies are concordant in differentiating the biochemical characteristics of the berries of five grapevine (Vitis vinifera L.) cultivars

Background

Grape cultivars and wines are distinguishable by their color, flavor and aroma profiles. Omic analyses (transcripts, proteins and metabolites) are powerful tools for assessing biochemical differences in biological systems.

Results

Berry skins of red- (Cabernet Sauvignon, Merlot, Pinot Noir) and white-skinned (Chardonnay, Semillon) wine grapes were harvested near optimum maturity (°Brix-to-titratable acidity ratio) from the same experimental vineyard. The cultivars were exposed to a mild, seasonal water-deficit treatment from fruit set until harvest in 2011. Identical sample aliquots were analyzed for transcripts by grapevine whole-genome oligonucleotide microarray and RNAseq technologies, proteins by nano-liquid chromatography-mass spectroscopy, and metabolites by gas chromatography-mass spectroscopy and liquid chromatography-mass spectroscopy. Principal components analysis of each of five Omic technologies showed similar results across cultivars in all Omic datasets. Comparison of the processed data of genes mapped in RNAseq and microarray data revealed a strong Pearson’s correlation (0.80). The exclusion of probesets associated with genes with potential for cross-hybridization on the microarray improved the correlation to 0.93. The overall concordance of protein with transcript data was low with a Pearson’s correlation of 0.27 and 0.24 for the RNAseq and microarray data, respectively. Integration of metabolite with protein and transcript data produced an expected model of phenylpropanoid biosynthesis, which distinguished red from white grapes, yet provided detail of individual cultivar differences. The mild water deficit treatment did not significantly alter the abundance of proteins or metabolites measured in the five cultivars, but did have a small effect on gene expression.

Conclusions

The five Omic technologies were consistent in distinguishing cultivar variation. There was high concordance between transcriptomic technologies, but generally protein abundance did not correlate well with transcript abundance. The integration of multiple high-throughput Omic datasets revealed complex biochemical variation amongst five cultivars of an ancient and economically important crop species.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-2115-y) contains supplementary material, which is available to authorized users.

Data from a proteomic baseline study of Assemblage A in Giardia duodenalis

Eight Assemblage A strains from the protozoan parasite Giardia duodenalis were analysed using label-free quantitative shotgun proteomics, to evaluate inter- and intra-assemblage variation and complement available genetic and transcriptomic data. Isolates were grown in biological triplicate in axenic culture, and protein extracts were subjected to in-solution digest and online fractionation using Gas Phase Fractionation (GPF). Recent reclassification of genome databases for subassemblages was evaluated for database-dependent loss of information, and proteome composition of different isolates was analysed for biologically relevant assemblage-independent variation. The data from this study are related to the research article “Quantitative proteomics analysis of Giardia duodenalis Assemblage A – a baseline for host, assemblage and isolate variation” published in Proteomics (Emery et al., 2015 [1]).

Protein identification and quantification from riverbank grape, Vitis riparia: Comparing SDS-PAGE and FASP-GPF techniques for shotgun proteomic analysis

Protein sample preparation optimisation is critical for establishing reproducible high throughput proteomic analysis. In this study, two different fractionation sample preparation techniques (in-gel digestion and in-solution digestion) for shotgun proteomics were used to quantitatively compare proteins identified in Vitis riparia leaf samples. The total number of proteins and peptides identified were compared between filter aided sample preparation (FASP) coupled with gas phase fractionation (GPF) and SDS-PAGE methods. There was a 24% increase in the total number of reproducibly identified proteins when FASP-GPF was used. FASP-GPF is more reproducible, less expensive and a better method than SDS-PAGE for shotgun proteomics of grapevine samples as it significantly increases protein identification across biological replicates. Total peptide and protein information from the two fractionation techniques is available in PRIDE with the identifier PXD001399 (http://proteomecentral.proteomexchange.org/dataset/PXD001399).

Quantitative proteomic analysis of cabernet sauvignon grape cells exposed to thermal stresses reveals alterations in sugar and phenylpropanoid metabolism

Grapes (Vitis vinifera) are a valuable fruit crop and wine production is a major industry. Global warming and expanded range of cultivation will expose grapes to more temperature stresses in future. Our study investigated protein level responses to abiotic stresses, with particular reference to proteomic changes induced by the impact of four different temperature stress regimes, including both hot and cold temperatures, on cultured grape cells. Cabernet Sauvignon cell suspension cultures grown at 26°C were subjected to 14 h of exposure to 34 and 42°C for heat stress, and 18 and 10°C for cold stress. Cells from the five temperatures were harvested in biological triplicates and label-free quantitative shotgun proteomic analysis was performed. A total of 2042 non-redundant proteins were identified from the five temperature points. Fifty-five proteins were only detected in extreme heat stress conditions (42°C) and 53 proteins were only detected at extreme cold stress conditions (10°C). Gene Ontology (GO) annotations of differentially expressed proteins provided insights into the metabolic pathways that are involved in temperature stress in grape cells. Sugar metabolism displayed switching between alternative and classical pathways during temperature stresses. Additionally, nine proteins involved in the phenylpropanoid pathway were greatly increased in abundance at extreme cold stress, and were thus found to be cold-responsive proteins. All MS data have been deposited in the ProteomeXchange with identifier PXD000977 (http://proteomecentral.proteomexchange.org/dataset/PXD000977).

Proteogenomics: emergence and promise

Proteogenomics, or the integration of proteomics with genomics and transcriptomics, is emerging as the next step towards a unified understanding of cellular functions. Looking globally and simultaneously at gene structure, RNA expression, protein synthesis and post-translational modifications have become technically feasible and offer a new perspective to molecular processes. Recent publications have highlighted the value of proteogenomics in oncology for defining the molecular signature of human tumors, and translation to other areas of biomedicine and life sciences is anticipated. This mini-review will discuss recent developments, challenges and perspectives in proteogenomics.

PGP: parallel prokaryotic proteogenomics pipeline for MPI clusters, high-throughput batch clusters and multicore workstations

SUMMARY

We present the first public release of our proteogenomic annotation pipeline. We have previously used our original unreleased implementation to improve the annotation of 46 diverse prokaryotic genomes by discovering novel genes, post-translational modifications and correcting the erroneous annotations by analyzing proteomic mass-spectrometry data. This public version has been redesigned to run in a wide range of parallel Linux computing environments and provided with the automated configuration, build and testing facilities for easy deployment and portability.

AVAILABILITY AND IMPLEMENTATION

Source code is freely available from https://bitbucket.org/andreyto/proteogenomics under GPL license. It is implemented in Python and C++. It bundles the Makeflow engine to execute the workflows.

CONTACT

atovtchi@jcvi.org.