Optimization for peptide sample preparation for urine peptidomics

Analysis of native or endogenous peptides in biofluids can provide valuable insights into disease mechanisms. Furthermore, the detected peptides may also have utility as potential biomarkers for non-invasive monitoring of human diseases. The non-invasive nature of urine collection and the abundance of peptides in the urine makes analysis by high-throughput ‘peptidomics’ methods , an attractive approach for investigating the pathogenesis of renal disease. However, urine peptidomics methodologies can be problematic with regards to difficulties associated with sample preparation. The urine matrix can provide significant background interference in making the analytical measurements that it hampers both the identification of peptides and the depth of the peptidomics read when utilizing LC-MS based peptidome analysis. We report on a novel adaptation of the standard solid phase extraction (SPE) method to a modified SPE (mSPE) approach for improved peptide yield and analysis sensitivity with LC-MS based peptidomics in terms of time, cost, clogging of the LC-MS column, peptide yield, peptide quality, and number of peptides identified by each method. Expense and time requirements were comparable for both SPE and mSPE, but more interfering contaminants from the urine matrix were evident in the SPE preparations (e.g., clogging of the LC-MS columns, yellowish background coloration of prepared samples due to retained urobilin, lower peptide yields) when compared to the mSPE method. When we compared data from technical replicates of 4 runs, the mSPE method provided significantly improved efficiencies for the preparation of samples from urine (e.g., mSPE peptide identification 82% versus 18% with SPE; p = 8.92E-05). Additionally, peptide identifications, when applying the mSPE method, highlighted the biology of differential activation of urine peptidases during acute renal transplant rejection with distinct laddering of specific peptides, which was obscured for most proteins when utilizing the conventional SPE method. In conclusion, the mSPE method was found to be superior to the conventional, standard SPE method for urine peptide sample preparation when applying LC-MS peptidomics analysis due to the optimized sample clean up that provided improved experimental inference from the confidently identified peptides.     

ARAMEMNON,a novel database for Arabidopsis integral membrane proteins

A specialized database (DB) for Arabidopsis membrane proteins, ARAMEMNON, was designed that facilitates the interpretation of gene and protein sequence data by integrating features that are presently only available from individual sources. Using several publicly available prediction programs, putative integral membrane proteins were identified among the approximately 25,500 proteins in the Arabidopsis genome DBs. By averaging the predictions from seven programs, approximately 6,500 proteins were classified as transmembrane (TM) candidate proteins. Some 1,800 of these contain at least four TM spans and are possibly linked to transport functions. The ARAMEMNON DB enables direct comparison of the predictions of seven different TM span computation programs and the predictions of subcellular localization by eight signal peptide recognition programs. A special function displays the proteins related to the query and dynamically generates a protein family structure. As a first set of proteins from other organisms, all of the approximately 700 putative membrane proteins were extracted from the genome of the cyanobacterium Synechocystis sp. and incorporated in the ARAMEMNON DB. The ARAMEMNON DB is accessible at the URL http://aramemnon.botanik.uni-koeln.de.     

PDB-UF: database of predicted enzymatic functions for unannotated protein structures from structural genomics

Background  

The number of protein structures from structural genomics centers dramatically increases in the Protein Data Bank (PDB). Many of these structures are functionally unannotated because they have no sequence similarity to proteins of known function. However, it is possible to successfully infer function using only structural similarity.     

GERMINATE. a generic database for integrating genotypic and phenotypic information for plant genetic resource collections

The extensive germplasm resource collections that are now available for major crop plants and their wild relatives will increasingly provide valuable biological and bioinformatics resources for plant physiologists and geneticists to dissect the molecular basis of key traits and to develop highly adapted plant material to sustain future breeding programs. A key to the efficient deployment of these resources is the development of information systems that will enable the collection and storage of biological information for these plant lines to be integrated with the molecular information that is now becoming available through the use of high-throughput genomics and post-genomics technologies. The GERMINATE database has been designed to hold a diverse variety of data types, ranging from molecular to phenotypic, and to allow querying between such data for any plant species. Data are stored in GERMINATE in a technology-independent manner, such that new technologies can be accommodated in the database as they emerge, without modification of the underlying schema. Users can access data in GERMINATE databases either via a lightweight Perl-CGI Web interface or by the more complex Genomic Diversity and Phenotype Connection software. GERMINATE is released under the GNU General Public License and is available at http://germinate.scri.sari.ac.uk/germinate/.     

The homeodomain resource: a prototype database for a large protein family

The Homeodomain Resource is an annotated collection of non-redundant protein sequences, three-dimensional structures and genomic information for the homeodomain protein family. Release 2.0 contains 765 full-length homeodomain-containing sequences, 29 experimentally derived structures and 116 homeobox loci implicated in human genetic disorders. Entries are fully hyperlinked to facilitate easy retrieval of the original records from source databases. A simple search engine with a graphical user interface is provided to query the component databases and assemble customized data sets. A new feature for this release is the addition of more automated methods for database searching, maintenance and implementation of efficient data management. The Homeodomain Resource is freely available through the WWW at http://genome.nhgri.nih.gov/homeodomain     

Arabidopsis thaliana,a plant Drosophila

Arabidopsis thaliana is a small cruciferous weed which grows naturally, mainly in Europe. Because of its qualities of small size, rapid growth, low chromosome number and self-fertilisation, I adapted it to aseptic growth in purified agar in sterile test-tubes. I found that it secreted various substances into the medium, but not in type or amount likely to interfere with the expression of biosynthetic mutants. Following X-irradiation of seed, I obtained a number of mutants, including several lethals. One lethal mutant I discovered to be deficient in thiamine synthesis. It was the first biosynthetic mutant to be found in flowering plants.     

The Arabidopsis Information Resource (TAIR): a comprehensive database and web-based information retrieval, analysis, and visualization system for a model plant

Arabidopsis thaliana, a small annual plant belonging to the mustard family, is the subject of study by an estimated 7000 researchers around the world. In addition to the large body of genetic, physiological and biochemical data gathered for this plant, it will be the first higher plant genome to be completely sequenced, with completion expected at the end of the year 2000. The sequencing effort has been coordinated by an international collaboration, the Arabidopsis Genome Initiative (AGI). The rationale for intensive investigation of Arabidopsis is that it is an excellent model for higher plants. In order to maximize use of the knowledge gained about this plant, there is a need for a comprehensive database and information retrieval and analysis system that will provide user-friendly access to Arabidopsis information. This paper describes the initial steps we have taken toward realizing these goals in a project called The Arabidopsis Information Resource (TAIR) (www.arabidopsis.org).     

The TRIPLES database: a community resource for yeast molecular biology

TRIPLES is a web-accessible database of TRansposon-Insertion Phenotypes, Localization and Expression in Saccharomyces cerevisiae—a relational database housing nearly half a million data points generated from an ongoing study using large-scale transposon mutagenesis to characterize gene function in yeast. At present, TRIPLES contains three principal data sets (i.e. phenotypic data, protein localization data and expression data) for over 3500 annotated yeast genes as well as several hundred non-annotated open reading frames. In addition, the TRIPLES web site provides online order forms linked to each data set so that users may request any strain or reagent generated from this project free of charge. In response to user requests, the TRIPLES web site has undergone several recent modifications. Our localization data have been supplemented with approximately 500 fluorescent micrographs depicting actual staining patterns observed upon indirect immunofluorescence analysis of indicated epitope-tagged proteins. These localization data, as well as all other data sets within TRIPLES, are now available in full as tab-delimited text. To accommodate increased reagent requests, all orders are now cataloged in a separate database, and users are notified immediately of order receipt and shipment. Also, TRIPLES is one of five sites incorporated into the new functional analysis tool Function Junction provided by the Saccharomyces Genome Database. TRIPLES may be accessed from the Yale Genome Analysis Center (YGAC) homepage at http://ygac.med.yale.edu.     

The mouse genome database: a resource for today and tomorrow

The Mouse Genome Database supports the use of mice in genome research, offering researchers information on gene characterization, genetic maps, comparative genomic data, and phenotypes.     

The PRINTS database: a resource for identification of protein families

The PRINTS database houses a collection of protein fingerprints, which may be used to assign family and functional attributes to uncharacterised sequences, such as those currently emanating from the various genome-sequencing projects. The April 2002 release includes 1,700 family fingerprints, encoding approximately 10,500 motifs, covering a range of globular and membrane proteins, modular polypeptides and so on. Fingerprints are groups of conserved motifs that, taken together, provide diagnostic protein family signatures. They derive much of their potency from the biological context afforded by matching motif neighbours; this makes them at once more flexible and powerful than single-motif approaches. The technique further departs from other pattern-matching methods by readily allowing the creation of fingerprints at superfamily-, family- and subfamily-specific levels, thereby allowing more fine-grained diagnoses. Here, we provide an overview of the method of protein fingerprinting and how the results of fingerprint analyses are used to build PRINTS and its relational cousin, PRINTS-S.     

UniCarb-DB: a database resource for glycomic discovery

Glycosylation is one of the most important post-translational modifications of proteins, known to be involved in pathogen recognition, innate immune response and protection of epithelial membranes. However, when compared to the tools and databases available for the processing of high-throughput proteomic data, the glycomic domain is severely lacking. While tools to assist the analysis of mass spectrometry (MS) and HPLC are continuously improving, there are few resources available to support liquid chromatography (LC)-MS/MS techniques for glycan structure profiling. Here, we present a platform for presenting oligosaccharide structures and fragment data characterized by LC-MS/MS strategies. The database is annotated with high-quality datasets and is designed to extend and reinforce those standards and ontologies developed by existing glycomics databases. AVAILABILITY: http://www.unicarb-db.org     

AraCyc: a biochemical pathway database for Arabidopsis

AraCyc is a database containing biochemical pathways of Arabidopsis, developed at The Arabidopsis Information Resource (http://www.arabidopsis.org). The aim of AraCyc is to represent Arabidopsis metabolism as completely as possible with a user-friendly Web-based interface. It presently features more than 170 pathways that include information on compounds, intermediates, cofactors, reactions, genes, proteins, and protein subcellular locations. The database uses Pathway Tools software, which allows the users to visualize a bird's eye view of all pathways in the database down to the individual chemical structures of the compounds. The database was built using Pathway Tools' Pathologic module with MetaCyc, a collection of pathways from more than 150 species, as a reference database. This initial build was manually refined and annotated. More than 20 plant-specific pathways, including carotenoid, brassinosteroid, and gibberellin biosyntheses have been added from the literature. A list of more than 40 plant pathways will be added in the coming months. The quality of the initial, automatic build of the database was compared with the manually improved version, and with EcoCyc, an Escherichia coli database using the same software system that has been manually annotated for many years. In addition, a Perl interface, PerlCyc, was developed that allows programmers to access Pathway Tools databases from the popular Perl language. AraCyc is available at the tools section of The Arabidopsis Information Resource Web site (http://www.arabidopsis.org/tools/aracyc).     

The Arabidopsis petal: a model for plant organogenesis

Organogenesis entails the regulation of cell division, cell expansion, cell and tissue type differentiation, and patterning of the organ as a whole. Petals are ideally suited to dissecting these processes. Petals are dispensable for growth and reproduction, enabling varied manipulations to be carried out with ease. In Arabidopsis, petals have a simple laminar structure with a small number of cell types, facilitating the analysis of organogenesis. This review summarizes recent studies that have illuminated some of the complex interplay between the genetic pathways controlling petal specification, growth and differentiation in Arabidopsis. These advances, coupled with the advantages of using petals as a model experimental system, provide an excellent platform to investigate the underlying mechanisms driving plant organogenesis.     

RiTE database: a resource database for genus-wide rice genomics and evolutionary biology

Background

Comparative evolutionary analysis of whole genomes requires not only accurate annotation of gene space, but also proper annotation of the repetitive fraction which is often the largest component of most if not all genomes larger than 50 kb in size.

Results

Here we present the Rice TE database (RiTE-db) - a genus-wide collection of transposable elements and repeated sequences across 11 diploid species of the genus Oryza and the closely-related out-group Leersia perrieri. The database consists of more than 170,000 entries divided into three main types: (i) a classified and curated set of publicly-available repeated sequences, (ii) a set of consensus assemblies of highly-repetitive sequences obtained from genome sequencing surveys of 12 species; and (iii) a set of full-length TEs, identified and extracted from 12 whole genome assemblies.

Conclusions

This is the first report of a repeat dataset that spans the majority of repeat variability within an entire genus, and one that includes complete elements as well as unassembled repeats. The database allows sequence browsing, downloading, and similarity searches. Because of the strategy adopted, the RiTE-db opens a new path to unprecedented direct comparative studies that span the entire nuclear repeat content of 15 million years of Oryza diversity.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1762-3) contains supplementary material, which is available to authorized users.     

AraPerox. A database of putative Arabidopsis proteins from plant peroxisomes

To identify unknown proteins from plant peroxisomes, the Arabidopsis genome was screened for proteins with putative major or minor peroxisome targeting signals type 1 or 2 (PTS1 or PTS2), as defined previously (Reumann S [2004] Plant Physiol 135: 783-800). About 220 and 60 proteins were identified that carry a putative PTS1 or PTS2, respectively. To further support postulated targeting to peroxisomes, several prediction programs were applied and the putative targeting domains analyzed for properties conserved in peroxisomal proteins and for PTS conservation in homologous plant expressed sequence tags. The majority of proteins with a major PTS and medium to high overall probability of peroxisomal targeting represent novel nonhypothetical proteins and include several enzymes involved in beta-oxidation of unsaturated fatty acids and branched amino acids, and 2-hydroxy acid oxidases with a predicted function in fatty acid alpha-oxidation, as well as NADP-dependent dehydrogenases and reductases. In addition, large protein families with many putative peroxisomal isoforms were recognized, including acyl-activating enzymes, GDSL lipases, and small thioesterases. Several proteins are homologous to prokaryotic enzymes of a novel aerobic hybrid degradation pathway for aromatic compounds and proposed to be involved in peroxisomal biosynthesis of plant hormones like jasmonic acid, auxin, and salicylic acid. Putative regulatory proteins of plant peroxisomes include protein kinases, small heat shock proteins, and proteases. The information on subcellular targeting prediction, homology, and in silico expression analysis for these Arabidopsis proteins has been compiled in the public database AraPerox to accelerate discovery and experimental investigation of novel metabolic and regulatory pathways of plant peroxisomes.