Functional modelling of an equine bronchoalveolar lavage fluid proteome provides experimental confirmation and functional annotation of equine genome sequences

The equine genome sequence enables the use of high-throughput genomic technologies in equine research, but accurate identification of expressed gene products and interpreting their biological relevance require additional structural and functional genome annotation. Here, we employ the equine genome sequence to identify predicted and known proteins using proteomics and model these proteins into biological pathways, identifying 582 proteins in normal cell-free equine bronchoalveolar lavage fluid (BALF). We improved structural and functional annotation by directly confirming the in vivo expression of 558 (96%) proteins, which were computationally predicted previously, and adding Gene Ontology (GO) annotations for 174 proteins, 108 of which lacked functional annotation. Bronchoalveolar lavage is commonly used to investigate equine respiratory disease, leading us to model the associated proteome and its biological functions. Modelling of protein functions using Ingenuity Pathway Analysis identified carbohydrate metabolism, cell-to-cell signalling, cellular function, inflammatory response, organ morphology, lipid metabolism and cellular movement as key biological processes in normal equine BALF. Comparative modelling of protein functions in normal cell-free bronchoalveolar lavage proteomes from horse, human, and mouse, performed by grouping GO terms sharing common ancestor terms, confirms conservation of functions across species. Ninety-one of 92 human GO categories and 105 of 109 mouse GO categories were conserved in the horse. Our approach confirms the utility of the equine genome sequence to characterize protein networks without antibodies or mRNA quantification, highlights the need for continued structural and functional annotation of the equine genome and provides a framework for equine researchers to aid in the annotation effort.     

Protein profiling in potato (Solanum tuberosum L.) leaf tissues by differential centrifugation

Foliar diseases, such as late blight, result in serious threats to potato production. As such, potato leaf tissue becomes an important substrate to study biological processes, such as plant defense responses to infection. Nonetheless, the potato leaf proteome remains poorly characterized. Here, we report protein profiling of potato leaf tissues using a modified differential centrifugation approach to separate the leaf tissues into cell wall and cytoplasmic fractions. This method helps to increase the number of identified proteins, including targeted putative cell wall proteins. The method allowed for the identification of 1484 nonredundant potato leaf proteins, of which 364 and 447 were reproducibly identified proteins in the cell wall and cytoplasmic fractions, respectively. Reproducibly identified proteins corresponded to over 70% of proteins identified in each replicate. A diverse range of proteins was identified based on their theoretical pI values, molecular masses, functional classification, and biological processes. Such a protein extraction method is effective for the establishment of a highly qualified proteome profile.     

Wheat leaf proteome analysis using sequence data of proteins separated by two-dimensional electrophoresis

Identifying wheat leaf protein expression is a major challenge of functional genomics. Using two-dimensional gel electrophoresis 541 wheat leaf proteins were separated and 55 of them were sequenced by nano liquid chromatography-tandem mass spectrometry. Peptide sequence data were screened against protein banks and expressed sequence tag public banks. Among these 55 spots, 20 proteins were found in wheat and 21 in other grass families (http://www.ncbi.nlm.nih.gov/). Twelve proteins showed similarities with other eukaryotic plant species. One protein showed homology to a bacterial sequence and another protein remained unknown. In 18 cases a significant score was found for the wheat TUC (Tentative Unique Contigs) of the PlantGDB (http://www.plantgdb.org/) data. In several cases, different spots were identified as corresponding to the same protein that can probably be attributed to the hexaploid structure of wheat. The identified proteins were classified in six groups and their role is discussed. Most of them (31/55) are involved in carbohydrate metabolism.     

Proteomic analysis of Medicago truncatula root plastids

Despite the recognized importance of non‐photosynthetic plastids in a wide array of plant processes, the root plastid proteome of soil‐grown plants still remains to be explored. In this study, we used a protocol allowing the isolation of Medicago truncatula root plastids with sufficient protein recovery and purity for their subsequent in‐depth analysis by nanoscale capillary LC‐MS/MS. Besides providing the first picture of a root plastid proteome, the results obtained highlighted the identification of 266 protein candidates whose functional distribution mainly resembled that of wheat endosperm amyloplasts and tobacco proplastids together with displaying major differences to those reported for chloroplasts. Most of the identified proteins have a role in nucleic acid‐related processes (16%), carbohydrate (15%) and nitrogen/sulphur (12%) metabolisms together with stress response mechanisms (10%). It is noteworthy that BLAST searches performed against the proteins reported in different plastidomes allowed detecting 30 putative root plastid proteins for which homologues were previously unsuspected as plastid‐located, most of them displaying a common putative role in participating in the plant cell responses against abiotic and/or biotic stresses. Taken together, the data obtained provide new insights into the functioning of root plastids and reinforce the emerging idea for an important role of these organelles in sustaining plant defence reactions.     

Proteomic characterization of wheat amyloplasts using identification of proteins by tandem mass spectrometry

We describe the initial characterization of the wheat amyloplast proteome, consisting of the identification and classification of 171 proteins. Whole amyloplasts and purified amyloplast membranes were prepared from wheat (Triticum aestivum). Protein extracts were examined by one-dimensional and two-dimensional electrophoresis, followed by high performance liquid chromatography-tandem mass spectrometry of separated proteins. Tandem mass spectrometry data of individual peptides was then searched by SEQUEST, using a database containing known protein sequences from both wheat and other homologous cereal crops. Using this approach we identified 108 proteins from whole amyloplasts and 63 proteins from purified amyloplast membranes. The majority of protein identifications were derived from protein sequences from cereal crops other than wheat, for which relatively little gene sequence data is available. The highest percentage of protein identifications obtained from any individual species was 46% of the total number of proteins identified, using sequence data found in our proprietary rice (Oryza sativa) genome database.     

Mapping the proteome of thylakoid membranes by de novo sequencing of intermembrane peptide domains

The proteome of a membrane compartment has been investigated by de novo sequence analysis after tryptic in gel digestion. Protein complexes and corresponding protein subunits were separated by a 2-D Blue Native (BN)/SDS-PAGE system. The transmembrane proteins of thylakoid membranes from a higher plant (Hordeum vulgare L.) were identified by the primary sequence of hydrophilic intermembrane peptide domains using nano ESI-MS/MS-analysis. Peptide analysis revealed that lysine residues of membrane proteins are primarily situated in the intermembrane domains. We concluded that esterification of lysine residues with fluorescent dyes may open the opportunity to label membrane proteins still localized in native protein complexes within the membrane phase. We demonstrate that covalent labelling of membrane proteins with the fluorescent dye Cy3 allows high sensitive visualization of protein complexes after 2-D BN/SDS-PAGE. We show that pre-electrophoretic labelling of protein subunits supplements detection of proteins by post-electrophoretic staining with silver and CBB and assists in completing the identification of the membrane proteome.     

The holm oak leaf proteome: analytical and biological variability in the protein expression level assessed by 2-DE and protein identification tandem mass spectrometry de novo sequencing and sequence similarity searching

As a first approach in establishing the holm oak leaf proteome, we have optimised a protocol for this plant and tissue which includes the following steps: trichloroacetic acid-acetone extraction, two-dimensional gel electrophoresis (2-DE) on pH 5 to 8 linear gradient immobilised pH gradient strips as the first dimension, and sodium dodecyl sulfate-polyacrylamide gel electrophoresis on 13% polyacrylamide gels as the second one. Proteins were detected by Coomassie staining. Gel images were recorded and digitalized, and the protein spots quantified by using a linear regression equation of protein quantity on spot volume obtained against standard proteins. Analytical variance was calculated for one-hundred protein spots from three replicate 2-DE gels of the same protein extract. Biological variance was determined for the same protein spots from independent tissue extracts corresponding to leaves from different trees, or the same tree at different orientations or sampling times during a day. Values of 26% for the analytical variance and 58.6% for the biological variance among independent trees were obtained. These values provide a quantified and statistical basis for the evaluation of protein expression changes in comparative proteomic investigations with this species. A representative set of the major proteins, covering the isoelectric point range of 5 to 8 and the relative molecular mass(r) range of 14 to 78 kDa, were subjected to liquid chromatography-tandem mass spectrometry analysis. Due to the absence of Quercus DNA or protein sequence databases, a method based on the procedure reported by Liska and Shevchenko including de novo sequencing and BLAST similarity searching against other plant species databases was used for protein identification. Out of 43 analysed spots, 35 were positively identified. The identified proteins mainly corresponded to enzymes involved in photosynthesis and energetic metabolism, with a significant number corresponding to RubisCO.     

Prediction and analysis of paralogous proteins in Trichomonas vaginalis genome

Trichomonas vaginalis causes trichomoniasis, second most sexually transmitted disease. The genome sequence draft of T. vaginalis was published by The Institute of Genomic Research reveals an abnormally large genome size of 160 Mb. It was speculated that a significant portion of the proteome contains paralogous proteins. The present study was aimed at identification and analysis of the paralogous proteins. The all against all search approach is used to identify the paralogous proteins. The dataset of proteins was retrieved from TIGR and TrichDB FTP server. The BLAST-P program performed all against all database searches against the protein database of Trichomonas vaginalis available at NCBI genome database. In the present study about 50,000 proteins were searched where 2,700 proteins were found to be paralogous under the rigid selection criteria. The Pfam database search has identified significant number of paralogous proteins which were further categorized among different 1496 paralogous protein in pfam families, 1027 paralogous protein contains domain, 60 proteins were having different repeats and 1092 paralogous protein sequences of clans. Such identification and functional annotation of paralogous proteins will also help in removing paralogous proteins from possible drug targets in future. Presence of huge number of paralogous proteins across wide range of gene families and domains may be one of the possible mechanisms involved in the T. vaginalis genome expansion and evolution.     

Proteome analysis of Arabidopsis thaliana by two-dimensional gel electrophoresis and matrix-assisted laser desorption/ionisation-time of flight mass spectrometry

In the present study we show results of a large-scale proteome analysis of the recently sequenced plant Arabidopsis thaliana. On the basis of a previously published sequential protein extraction protocol, we prepared protein extracts from eight different A. thaliana tissues (primary leaf, leaf, stem, silique, seedling, seed, root, and inflorescence) and analysed these by two-dimensional gel electrophoresis. A total of 6000 protein spots, from three of these tissues, namely primary leaf, silique and seedling, were excised and the contained proteins were analysed by matrix assisted laser desorption/ionisation time of flight mass spectrometry peptide mass fingerprinting. This resulted in the identification of the proteins contained in 2943 spots, which were found to be products of 663 different genes. In this report we present and discuss the methodological and biological results of our plant proteome analysis.     

Annotated proteome of a human T-cell lymphoma.

As the reliable identification of proteins by tandem mass spectrometry becomes increasingly common, the full characterization of large data sets of proteins remains a difficult challenge. Our goal was to survey the proteome of a human T-cell lymphoma-derived cell line in a single set of experiments and present an automated method for the annotation of lists of proteins. A downstream application of these data includes the identification of novel pathogenetic and candidate diagnostic markers of T-cell lymphoma. Total protein isolated from cytoplasmic, membrane, and nuclear fractions of the SUDHL-1 T-cell lymphoma cell line was resolved by SDS-PAGE, and the entire gel lanes digested and analyzed by tandem mass spectrometry. Acquired data files were searched against the UniProt protein database using the SEQUEST algorithm. Search results for each subcellular fraction were analyzed using INTERACT and ProteinProphet. All protein identifications with an error rate of less than 10% were directly exported into excel and analyzed using GOMiner (NIH/NCI). The Gene ontology molecular function and cell location data were summarized for the identified proteins and results exported as user-interactive directed acyclic graphs. A total of 1105 unique proteins were identified and fully annotated, including numerous proteins that had not been previously characterized in lymphoma, in functional categories such as cell adhesion, migration, signaling, and stress response. This study demonstrates the utility of currently available bioinformatics tools for the robust identification and annotation of large numbers of proteins in a batchwise fashion.     

DNA-binding protein prediction using plant specific support vector machines: validation and application of a new genome annotation tool

There are currently 151 plants with draft genomes available but levels of functional annotation for putative protein products are low. Therefore, accurate computational predictions are essential to annotate genomes in the first instance, and to provide focus for the more costly and time consuming functional assays that follow. DNA-binding proteins are an important class of proteins that require annotation, but current computational methods are not applicable for genome wide predictions in plant species. Here, we explore the use of species and lineage specific models for the prediction of DNA-binding proteins in plants. We show that a species specific support vector machine model based on Arabidopsis sequence data is more accurate (accuracy 81%) than a generic model (74%), and based on this we develop a plant specific model for predicting DNA-binding proteins. We apply this model to the tomato proteome and demonstrate its ability to perform accurate high-throughput prediction of DNA-binding proteins. In doing so, we have annotated 36 currently uncharacterised proteins by assigning a putative DNA-binding function. Our model is publically available and we propose it be used in combination with existing tools to help increase annotation levels of DNA-binding proteins encoded in plant genomes.     

Towards an understanding of wheat chloroplasts: a methodical investigation of thylakoid proteome

We utilized Percoll density gradient centrifugation to isolate and fractionate chloroplasts of Korean winter wheat cultivar cv. Kumgang (Triticum aestivum L.). The resulting protein fractions were separated by one dimensional polyacrylamide gel electrophoresis (1D-PAGE) coupled with LTQ-FTICR mass spectrometry. This enabled us to detect and identify 767 unique proteins. Our findings represent the most comprehensive exploration of a proteome to date. Based on annotation information from the UniProtKB/Swiss-Prot database and our analyses via WoLF PSORT and PSORT, these proteins are localized in the chloroplast (607 proteins), chloroplast stroma (145), thylakoid membrane (342), lumens (163), and integral membranes (166). In all, 67% were confirmed as chloroplast thylakoid proteins. Although nearly complete protein coverage (89% proteins) has been accomplished for the key chloroplast pathways in wheat, such as for photosynthesis, many other proteins are involved in regulating carbon metabolism. The identified proteins were assigned to 103 functional categories according to a classification system developed by the iProClass database and provided through Protein Information Resources. Those functions include electron transport, energy, cellular organization and biogenesis, transport, stress responses, and other metabolic processes. Whereas most of these proteins are associated with known complexes and metabolic pathways, about 13% of the proteins have unknown functions. The chloroplast proteome contains many proteins that are localized to the thylakoids but as yet have no known function. We propose that some of these familiar proteins participate in the photosynthetic pathway. Thus, our new and comprehensive protein profile may provide clues for better understanding that photosynthetic process in wheat.     

Proteomic Analysis to Identify Tightly-Bound Cell Wall Protein in Rice Calli

Rice is a model plant widely used for basic and applied research programs. Plant cell wall proteins play key roles in a broad range of biological processes. However, presently, knowledge on the rice cell wall proteome is rudimentary in nature. In the present study, the tightly-bound cell wall proteome of rice callus cultured cells using sequential extraction protocols was developed using mass spectrometry and bioinformatics methods, leading to the identification of 1568 candidate proteins. Based on bioinformatics analyses, 389 classical rice cell wall proteins, possessing a signal peptide, and 334 putative non-classical cell wall proteins, lacking a signal peptide, were identified. By combining previously established rice cell wall protein databases with current data for the classical rice cell wall proteins, a comprehensive rice cell wall proteome, comprised of 496 proteins, was constructed. A comparative analysis of the rice and Arabidopsis cell wall proteomes revealed a high level of homology, suggesting a predominant conservation between monocot and eudicot cell wall proteins. This study importantly increased information on cell wall proteins, which serves for future functional analyses of these identified rice cell wall proteins.