Specific Protein Database Creation from Transcriptomics Data in Nonmodel Species: Holm Oak (Quercus ilex L.).

Proteomics encompasses efforts to identify all the proteins of a proteome, with most of studies about plant proteomics based on a bottom-up mass spectrometry (MS) strategy, in which the proteins are subjected to digestion by trypsin and the tryptic fragments are subjected to MS analysis. The identification of proteins from MS/MS spectra has been performed using different algorithms (Mascot, Sequest) against plant protein sequence databases such as UniProtKB or NCBI_Viridiplantae. But these databases are not the best choice for nonmodel species where they are underrepresented, resulting in poor identification rates. A high identification rate requires a sequenced and well-annotated genome of the species under investigation. For nonmodel organisms, the identification of proteins is challenging since, in the best of the cases, only hits or orthologs instead of gene products are identified. However, in the absence of a sequenced genome, this situation can be improved using transcriptome data to generate a specific species database to compare proteins. In this chapter, we report the protein database construction from RNA-Seq data in a nonmodel species, in this particular case Holm oak (Q. ilex).

Optimizing Shotgun Proteomics Analysis for a Confident Protein Identification and Quantitation in Orphan Plant Species: The Case of Holm Oak (Quercus ilex).

The proteomics of orphan, unsequenced, and recalcitrant organisms is highly challenging. This is the case of the typical Mediterranean forest tree Holm oak (Quercus ilex). Proteomics has moved on quite fast from the classical 2DE-MS to shotgun or gel-free/label-free approaches, with the latter possessing a series of advantages over the gel-based ones. Before translating proteomics data into biological knowledge, a few questions as to the analysis technique itself have to be answered including its confidence in protein identification and quantification. It is important to clearly differentiate a hit from an ortholog and gene product identification, with the difference depending on the database and the confidence parameters (score, number of peptides, and coverage). With respect to quantification and for comparative purposes it is important to make sure that we are within the linear dynamic range. For that, a calibration curve based on mass spectrometry analysis of a serial dilution of the extracts should be performed. Thus, just by validating our data with the aim of improving the quality of the analysis enables us to give a correct interpretation of our results. We show a method that aims to improve the confidence in protein identification and quantification in the orphan species Q. ilex using a shotgun proteomics approach.

Ion Torrent and lllumina, two complementary RNA-seq platforms for constructing the holm oak (Quercus ilex) transcriptome.

Transcriptome analysis is widely used in plant biology research to explore gene expression across a large variety of biological contexts such as those related to environmental stress and plant-pathogen interaction. Currently, next generation sequencing platforms are used to obtain a high amount of raw data to build the transcriptome of any plant. Here, we compare Illumina and Ion Torrent sequencing platforms for the construction and analysis of the holm oak (Quercus ilex) transcriptome. Genomic analysis of this forest tree species is a major challenge considering its recalcitrant character and the absence of previous molecular studies. In this study, Quercus ilex raw sequencing reads were obtained from Illumina and Ion Torrent and assembled by three different algorithms, MIRA, RAY and TRINITY. A hybrid transcriptome combining both sequencing technologies was also obtained in this study. The RAY-hybrid assembly generated the most complete transcriptome (1,116 complete sequences of which 1,085 were single copy) with a E90N50 of 1,122 bp. The MIRA-Illumina and TRINITY-Ion Torrent assemblies annotated the highest number of total transcripts (62,628 and 74,058 respectively). MIRA-Ion Torrent showed the highest number of shared sequences (84.8%) with the oak transcriptome. All the assembled transcripts from the hybrid transcriptome were annotated with gene ontology grouping them in terms of biological processes, molecular functions and cellular components. In addition, an in silico proteomic analysis was carried out using the translated assemblies as databases. Those from Ion Torrent showed more proteins compared to the Illumina and hybrid assemblies. This new generated transcriptome represents a valuable tool to conduct differential gene expression studies in response to biotic and abiotic stresses and to assist and validate the ongoing Q. ilex whole genome sequencing.

A Multi-Omics Analysis Pipeline for the Metabolic Pathway Reconstruction in the Orphan Species Quercus ilex.

Holm oak (Quercus ilex) is the most important and representative species of the Mediterranean forest and of the Spanish agrosilvo-pastoral "dehesa" ecosystem. Despite its environmental and economic interest, Holm oak is an orphan species whose biology is very little known, especially at the molecular level. In order to increase the knowledge on the chemical composition and metabolism of this tree species, the employment of a holistic and multi-omics approach, in the Systems Biology direction would be necessary. However, for orphan and recalcitrant plant species, specific analytical and bioinformatics tools have to be developed in order to obtain adequate quality and data-density before to coping with the study of its biology. By using a plant sample consisting of a pool generated by mixing equal amounts of homogenized tissue from acorn embryo, leaves, and roots, protocols for transcriptome (NGS-Illumina), proteome (shotgun LC-MS/MS), and metabolome (GC-MS) studies have been optimized. These analyses resulted in the identification of around 62629 transcripts, 2380 protein species, and 62 metabolites. Data are compared with those reported for model plant species, whose genome has been sequenced and is well annotated, including Arabidopsis, japonica rice, poplar, and eucalyptus. RNA and protein sequencing favored each other, increasing the number and confidence of the proteins identified and correcting erroneous RNA sequences. The integration of the large amount of data reported using bioinformatics tools allows the Holm oak metabolic network to be partially reconstructed: from the 127 metabolic pathways reported in KEGG pathway database, 123 metabolic pathways can be visualized when using the described methodology. They included: carbohydrate and energy metabolism, amino acid metabolism, lipid metabolism, nucleotide metabolism, and biosynthesis of secondary metabolites. The TCA cycle was the pathway most represented with 5 out of 10 metabolites, 6 out of 8 protein enzymes, and 8 out of 8 enzyme transcripts. On the other hand, gaps, missed pathways, included metabolism of terpenoids and polyketides and lipid metabolism. The multi-omics resource generated in this work will set the basis for ongoing and future studies, bringing the Holm oak closer to model species, to obtain a better understanding of the molecular mechanisms underlying phenotypes of interest (productive, tolerant to environmental cues, nutraceutical value) and to select elite genotypes to be used in restoration and reforestation programs, especially in a future climate change scenario.

A year (2014-2015) of plants in Proteomics journal. Progress in wet and dry methodologies, moving from protein catalogs, and the view of classic plant biochemists.

The present review is an update of the previous one published in Proteomics 2015 Reviews special issue [Jorrin-Novo, J. V. et al., Proteomics 2015, 15, 1089-1112] covering the July 2014-2015 period. It has been written on the bases of the publications that appeared in Proteomics journal during that period and the most relevant ones that have been published in other high-impact journals. Methodological advances and the contribution of the field to the knowledge of plant biology processes and its translation to agroforestry and environmental sectors will be discussed. This review has been organized in four blocks, with a starting general introduction (literature survey) followed by sections focusing on the methodology (in vitro, in vivo, wet, and dry), proteomics integration with other approaches (systems biology and proteogenomics), biological information, and knowledge (cell communication, receptors, and signaling), ending with a brief mention of some other biological and translational topics to which proteomics has made some contribution.

Contrasting Roles of the Apoplastic Aspartyl Protease APOPLASTIC, ENHANCED DISEASE SUSCEPTIBILITY1-DEPENDENT1 and LEGUME LECTIN-LIKE PROTEIN1 in Arabidopsis Systemic Acquired Resistance.

Systemic acquired resistance (SAR) is an inducible immune response that depends on ENHANCED DISEASE SUSCEPTIBILITY1 (EDS1). Here, we show that Arabidopsis (Arabidopsis thaliana) EDS1 is required for both SAR signal generation in primary infected leaves and SAR signal perception in systemic uninfected tissues. In contrast to SAR signal generation, local resistance remains intact in eds1 mutant plants in response to Pseudomonas syringae delivering the effector protein AvrRpm1. We utilized the SAR-specific phenotype of the eds1 mutant to identify new SAR regulatory proteins in plants conditionally expressing AvrRpm1. Comparative proteomic analysis of apoplast-enriched extracts from AvrRpm1-expressing wild-type and eds1 mutant plants led to the identification of 12 APOPLASTIC, EDS1-DEPENDENT (AED) proteins. The genes encoding AED1, a predicted aspartyl protease, and another AED, LEGUME LECTIN-LIKE PROTEIN1 (LLP1), were induced locally and systemically during SAR signaling and locally by salicylic acid (SA) or its functional analog, benzo 1,2,3-thiadiazole-7-carbothioic acid S-methyl ester. Because conditional overaccumulation of AED1-hemagglutinin inhibited SA-induced resistance and SAR but not local resistance, the data suggest that AED1 is part of a homeostatic feedback mechanism regulating systemic immunity. In llp1 mutant plants, SAR was compromised, whereas the local resistance that is normally associated with EDS1 and SA as well as responses to exogenous SA appeared largely unaffected. Together, these data indicate that LLP1 promotes systemic rather than local immunity, possibly in parallel with SA. Our analysis reveals new positive and negative components of SAR and reinforces the notion that SAR represents a distinct phase of plant immunity beyond local resistance.

Back to Osborne. Sequential protein extraction and LC-MS analysis for the characterization of the Holm oak seed proteome.

It is impossible to capture in just one experiment all or most of the total set of protein species that constitute the cell's proteome. Thus, according to our results, and even considering that they depend on the experimental system carried out (plant, yeast, fungi, or bacteria), the best protein extraction protocol yielded less than 20 % of the total amount of proteins, as determined by the Kjeldahl method. For this reason, protein cataloguing and the whole proteome characterization require the use of firstly, fractionation techniques at the cellular, subcellular, protein, or peptide level, and secondly, the use of complementary approaches.Within our current research on Holm oak (Quercus ilex subsp. ballota), we aim to characterize its seed proteome. For that we have optimized an experimental workflow in which the Osborne sequential protein extraction (Osborne, Science 28:417-427, 1908) is combined with downstream electrophoretic protein separation or shotgun MS analysis. In general, it can be used to study any plant seed, as well as to investigate on seed maturation and germination, genotype characterization, allergens identification, food traceability, and substantial equivalence, among others.