Sequence Database Search Research Articles

Identification of novel PTEN-binding partners: PTEN interaction with fatty acid binding protein FABP4

PTEN is a tumor suppressor with dual protein and lipid-phosphatase activity, which is frequently deleted or mutated in many human advanced cancers. Recent studies have also demonstrated that PTEN is a promising target in type II diabetes and obesity treatment. Using C-terminal PTEN sequence in pEG202-NLS as bait, yeast two-hybrid screening on Mouse Embryo, Colon Cancer, and HeLa cDNA libraries was carried out. Isolated positive clones were validated by mating assay and identified through automated DNA sequencing and BLAST database searches. Sequence analysis revealed a number of PTEN-binding proteins linking this phosphatase to a number of different signaling cascades, suggesting that PTEN may perform other functions besides tumor-suppressing activity in different cell types. In particular, the interplay between PTEN function and adipocyte-specific fatty-acid-binding protein FABP4 is of notable interest. The demonstrable tautology of PTEN to FABP4 suggested a role for this phosphatase in the regulation of lipid metabolism and adipocyte differentiation. This interaction was further studied using coimmunoprecipitation and gel-filtration assays. Finally, based on Biacore assay, we have calculated the K(D) of PTEN-FABP4 complex, which is around 2.8 microM.

GenBank.

GenBank® is a comprehensive database that contains publicly available nucleotide sequences for more than 300 000 organisms named at the genus level or lower, obtained primarily through submissions from individual laboratories and batch submissions from large-scale sequencing projects, including whole genome shotgun (WGS) and environmental sampling projects. Most submissions are made using the web-based BankIt or standalone Sequin programs, and accession numbers are assigned by GenBank staff upon receipt. Daily data exchange with the European Molecular Biology Laboratory Nucleotide Sequence Database in Europe and the DNA Data Bank of Japan ensures worldwide coverage. GenBank is accessible through the NCBI Entrez retrieval system, which integrates data from the major DNA and protein sequence databases along with taxonomy, genome, mapping, protein structure and domain information, and the biomedical journal literature via PubMed. BLAST provides sequence similarity searches of GenBank and other sequence databases. Complete bi-monthly releases and daily updates of the GenBank database are available by FTP. To access GenBank and its related retrieval and analysis services, begin at the NCBI homepage: www.ncbi.nlm.nih.gov.

Characterization of mouse UDP-glucose pyrophosphatase, a Nudix hydrolase encoded by the Nudt14 gene

Recombinant mouse UDP-glucose pyrophosphatase (UGPPase), encoded by the Nudt14 gene, was produced in Escherichia coli and purified close to homogeneity. The enzyme catalyzed the conversion of [β- 32P]UDP-glucose to [ 32P]glucose-1-P and UMP, confirming that it hydrolyzed the pyrophosphate of the nucleoside diphosphate sugar to generate glucose-1-P and UMP. The enzyme was also active toward ADP-ribose. Activity is dependent on the presence of Mg 2+ and was greatest at alkaline pH above 8. Kinetic analysis indicated a K m of ∼4 mM for UDP-glucose and ∼0.3 mM for ADP-ribose. Based on V max/ K m values, the enzyme was ∼20-fold more active toward ADP-ribose. UGPPase behaves as a dimer in solution and can be cross-linked to generate a species of M r 54,000 from a monomer of 30,000 as judged by SDS–PAGE. The dimerization was not affected by the presence of glucose-1-P or UDP-glucose. Using antibodies raised against the recombinant protein, Western analysis indicated that UGPPase was widely expressed in mouse tissues, including skeletal muscle, liver, kidney, heart, lung, fat, heart and pancreas with a lower level in brain. It was generally present as a doublet when analyzed by SDS–PAGE, suggesting the occurrence of some form of post-translational modification. Efforts to interconvert the species by adding or inhibiting phosphatase activity were unsuccessful, leaving the nature of the modification unknown. Sequence alignments and database searches revealed related proteins in species as distant as Drosophila melanogaster and Caenorhabditis elegans.

Multipotent Adult Germline Stem Cells and Embryonic Stem Cells: Comparative Proteomic Approach

Spermatogonial stem cells isolated from the adult mouse testis acquire under certain culture conditions pluripotency and become so-called multipotent adult germline stem cells (maGSCs). They can be differentiated into somatic cells of the three germ layers. We investigated a subset of the maGSCs and ESCs proteomes using cell lines derived from two different mouse strains, narrow range immobilized pH gradients to favor the detection of less abundant proteins, and DIGE to ensure confident comparison between the two cell types. 2-D reference maps of maGSCs and ESCs in the pI ranges 3-6 and 5-8 were created, and protein entities were further processed for protein identification. By peptide mass fingerprinting and tandem mass spectrometry combined with searches of protein sequence databases, a set of 409 proteins was identified, corresponding to a library of 166 nonredundant stem cell-associated proteins. The identified proteins were classified according to their main known/postulated functions using bioinformatics. Furthermore, we used DIGE to highlight the ESC-like nature of maGSCs on the proteome scale. We concluded that the proteome of maGSCs is highly similar to that of ESCs as we could identify only a small subset of 18 proteins to be differentially expressed between the two cell types. Moreover, comparative analysis of the cell line proteomes from two different mouse strains showed that the interindividual differences in maGSCs proteomes are minimal. With our study, we created for the first time a proteomic map for maGSCs and compared it to the ESCs proteome from the same mouse. We confirmed on the proteome level the ESC-like nature of maGSCs.

Transcriptome response of the Pacific oyster (Crassostrea gigas) to infection with Vibrio tubiashii using cDNA AFLP differential display

We used qualitative complementary DNA-amplified fragment length polymorphism (cDNA-AFLP) differential display analysis and real-time, quantitative PCR (RT-qPCR) to identify genes in the Pacific oyster Crassostrea gigas, whose transcription either changes in response to exposure to a pathogenic bacterium (Vibrio tubiashii) or varies between families known to differ in sensitivity to heat stress, before and at 12 and 36 h after bacterial exposure at a temperature of 25 degrees C. These conditions simulate those associated with summer mortality syndrome, a poorly understood cause of massive mortalities in cultured Pacific oysters in North America, Asia and Europe. Using 32 AFLP primer pairs, we identified 92 transcript-derived fragments that are qualitatively differentially expressed. We then cloned and sequenced 14 of these fragments, designed fragment-specific primers and quantified their transcription patterns using RT-qPCR. Most of the differences in transcription patterns between stress-tolerant and stress-sensitive families were evident before bacterial exposure, and genes that responded to bacterial exposure did so in parallel between stress-sensitive and stress-tolerant families. Blast searches of sequence databases revealed that these fragments represent genes involved in immune response as well as genes related to metabolic processes. Our data support the hypothesis that family level differences in resistance to stress in Pacific oysters are largely attributable to constitutive differences in gene transcription or 'general vigour' that are detectable before and maintained after infection, rather than being due to induced responses at the transcriptome level.

At4g24160, a Soluble Acyl-Coenzyme A-Dependent Lysophosphatidic Acid Acyltransferase

Human CGI-58 (for comparative gene identification-58) and YLR099c, encoding Ict1p in Saccharomyces cerevisiae, have recently been identified as acyl-CoA-dependent lysophosphatidic acid acyltransferases. Sequence database searches for CGI-58 like proteins in Arabidopsis (Arabidopsis thaliana) revealed 24 proteins with At4g24160, a member of the alpha/beta-hydrolase family of proteins being the closest homolog. At4g24160 contains three motifs that are conserved across the plant species: a GXSXG lipase motif, a HX(4)D acyltransferase motif, and V(X)(3)HGF, a probable lipid binding motif. Dendrogram analysis of yeast ICT1, CGI-58, and At4g24160 placed these three polypeptides in the same group. Here, we describe and characterize At4g24160 as, to our knowledge, the first soluble lysophosphatidic acid acyltransferase in plants. A lipidomics approach revealed that At4g24160 has additional triacylglycerol lipase and phosphatidylcholine hydrolyzing enzymatic activities. These data establish At4g24160, a protein with a previously unknown function, as an enzyme that might play a pivotal role in maintaining the lipid homeostasis in plants by regulating both phospholipid and neutral lipid levels.

Utilization of SSR and cDNA markers for screening known QTLs for late blight (Phytophthora infestans) resistance in potato

All published QTLs and genes for Phytophthora resistance were projected onto the bins of a high-density reference map of potato. Further, a transcriptome map containing around 700 cDNA-AFLP (TDF) markers was anchored to this map. We have analysed cDNA markers which are co-located with these resistance QTLs by cloning, sequencing and by performing homology searches in public sequence databases. Several interesting homologies were detected with typical resistance and stress response genes. On the other hand, we have screened all known QTL locations on the 12 potato chromosomes via linked SSR markers for the presence of a selectable QTL for Phytophthora resistance in four genetic backgrounds. Progenies descended from different Solanum wild species as resistance sources. Leaf and tuber resistances were analysed. In all case studies, several selectable QTLs were detected which descended from either parent. Tuber and leaf QTLs varied from progeny to progeny and between leaves and tubers. In none of the progenies were resistance levels of leaf and tuber blight correlated.

Identification of iron-acquisition proteins of Avibacterium paragallinarum

When Avibacterium paragallinarum reference strain 0083 (serovar A) was grown in an iron-restricted culture medium, the expression of the 60, 68 and 93 kDa outer membrane proteins increased as compared with normal media. Sera of chickens experimentally infected with Av. paragallinarum recognized these iron-restriction induced proteins, suggesting their expression in vivo. The three outer membrane proteins were identified as transferrin receptor and iron transport proteins by mass spectroscopy and a search in sequence databases. As these proteins have been reported to be regulated by the Fur protein in many bacteria, we investigated, through molecular methods, the presence of the fur gene in Av. paragallinarum. A candidate fur gene of Av. paragallinarum was amplified by polymerase chain reaction using complementary primers to conserved regions of fur gene sequences from members of the Pasteurellaceae family. The nucleotide sequence of the cloned gene, from ATG to TAA stop codon, was 453 base pairs in length and the deduced amino acid sequence showed 94% identity with Fur sequences of Actinobacillus pleuropneumoniae and Haemophilus ducreyi. The Av. paragallinarum deduced Fur protein (17.8 kDa) amino acid sequence contains the N-terminal helix–turn–helix DNA-binding domain and the two iron-binding sites in the C-terminal end, typical of other described Fur proteins. The study of iron-restriction-induced proteins and the mechanism regulating their expression could lead to an understanding of the responses of Av. paragallinarum to survive in an iron-restricted environment on host mucosal surfaces.

ESG: extended similarity group method for automated protein function prediction

Importance of accurate automatic protein function prediction is ever increasing in the face of a large number of newly sequenced genomes and proteomics data that are awaiting biological interpretation. Conventional methods have focused on high sequence similarity-based annotation transfer which relies on the concept of homology. However, many cases have been reported that simple transfer of function from top hits of a homology search causes erroneous annotation. New methods are required to handle the sequence similarity in a more robust way to combine together signals from strongly and weakly similar proteins for effectively predicting function for unknown proteins with high reliability. We present the extended similarity group (ESG) method, which performs iterative sequence database searches and annotates a query sequence with Gene Ontology terms. Each annotation is assigned with probability based on its relative similarity score with the multiple-level neighbors in the protein similarity graph. We will depict how the statistical framework of ESG improves the prediction accuracy by iteratively taking into account the neighborhood of query protein in the sequence similarity space. ESG outperforms conventional PSI-BLAST and the protein function prediction (PFP) algorithm. It is found that the iterative search is effective in capturing multiple-domains in a query protein, enabling accurately predicting several functions which originate from different domains. ESG web server is available for automated protein function prediction at http://dragon.bio.purdue.edu/ESG/.

Accurate and Sensitive Peptide Identification with Mascot Percolator

Sound scoring methods for sequence database search algorithms such as Mascot and Sequest are essential for sensitive and accurate peptide and protein identifications from proteomic tandem mass spectrometry data. In this paper, we present a software package that interfaces Mascot with Percolator, a well performing machine learning method for rescoring database search results, and demonstrate it to be amenable for both low and high accuracy mass spectrometry data, outperforming all available Mascot scoring schemes as well as providing reliable significance measures. Mascot Percolator can be readily used as a stand alone tool or integrated into existing data analysis pipelines.

Low Cost, Scalable Proteomics Data Analysis Using Amazon’s Cloud Computing Services and Open Source Search Algorithms

One of the major difficulties for many laboratories setting up proteomics programs has been obtaining and maintaining the computational infrastructure required for the analysis of the large flow of proteomics data. We describe a system that combines distributed cloud computing and open source software to allow laboratories to set up scalable virtual proteomics analysis clusters without the investment in computational hardware or software licensing fees. Additionally, the pricing structure of distributed computing providers, such as Amazon Web Services, allows laboratories or even individuals to have large-scale computational resources at their disposal at a very low cost per run. We provide detailed step-by-step instructions on how to implement the virtual proteomics analysis clusters as well as a list of current available preconfigured Amazon machine images containing the OMSSA and X!Tandem search algorithms and sequence databases on the Medical College of Wisconsin Proteomics Center Web site ( http://proteomics.mcw.edu/vipdac ).

A Simulated MS/MS Library for Spectrum-to-spectrum Searching in Large Scale Identification of Proteins

Identifying peptides from mass spectrometric fragmentation data (MS/MS spectra) using search strategies that map protein sequences to spectra is computationally expensive. An alternative strategy uses direct spectrum-to-spectrum matching against a reference library of previously observed MS/MS that has the advantage of evaluating matches using fragment ion intensities and other ion types than the simple set normally used. However, this approach is limited by the small sizes of the available peptide MS/MS libraries and the inability to evaluate the rate of false assignments. In this study, we observed good performance of simulated spectra generated by the kinetic model implemented in MassAnalyzer (Zhang, Z. (2004) Prediction of low-energy collision-induced dissociation spectra of peptides. Anal. Chem. 76, 3908-3922; Zhang, Z. (2005) Prediction of low-energy collision-induced dissociation spectra of peptides with three or more charges. Anal. Chem. 77, 6364-6373) as a substitute for the reference libraries used by the spectrum-to-spectrum search programs X!Hunter and BiblioSpec and similar results in comparison with the spectrum-to-sequence program Mascot. We also demonstrate the use of simulated spectra for searching against decoy sequences to estimate false discovery rates. Although we found lower score discrimination with spectrum-to-spectrum searches than with Mascot, particularly for higher charge forms, comparable peptide assignments with low false discovery rate were achieved by examining consensus between X!Hunter and Mascot, filtering results by mass accuracy, and ignoring score thresholds. Protein identification results are comparable to those achieved when evaluating consensus between Sequest and Mascot. Run times with large scale data sets using X!Hunter with the simulated spectral library are 7 times faster than Mascot and 80 times faster than Sequest with the human International Protein Index (IPI) database. We conclude that simulated spectral libraries greatly expand the search space available for spectrum-to-spectrum searching while enabling principled analyses and that the approach can be used in consensus strategies for large scale studies while reducing search times.

The promoter of the Arabidopsis thaliana BAN gene is active in proanthocyanidin-accumulating cells of the Brassica napus seed coat

As part of an ongoing research program dedicated to the understanding of proanthocyanidin (PA) accumulation in Brassica napus seed coat, transgenic rapeseed plants carrying a 2.3-kb fragment of the Arabidopsis thaliana BAN promoter (ProAtBAN) fused to the uidA reporter gene (GUS) were generated. Analysis of these plants revealed that ProAtBAN was activated in B. napus seed coat, following a spatio-temporal pattern that was very similar to the PA deposition profile in rapeseed and also to the one previously described in Arabidopsis. ProAtBAN activity occurred as soon as the early stages of embryogenesis and was restricted to the cells where PAs were shown to accumulate. Therefore, the Arabidopsis BAN promoter can be used to trigger gene expression in B. napus seed coat for both genetic engineering and functional validation of candidate genes. In addition, these data strongly suggest that the transcriptional regulatory network of the BAN gene is conserved between Arabidopsis and rapeseed. This is consistent with the fact that similarity searches of the public rapeseed sequence databases allowed recovering the rapeseed homologs for several BAN regulators, namely TT1, TT2, TT8, TT16 and TTG1, which have been previously described in Arabidopsis.

A software pipeline for processing and identification of fungal ITS sequences.

BackgroundFungi from environmental samples are typically identified to species level through DNA sequencing of the nuclear ribosomal internal transcribed spacer (ITS) region for use in BLAST-based similarity searches in the International Nucleotide Sequence Databases. These searches are time-consuming and regularly require a significant amount of manual intervention and complementary analyses. We here present software – in the form of an identification pipeline for large sets of fungal ITS sequences – developed to automate the BLAST process and several additional analysis steps. The performance of the pipeline was evaluated on a dataset of 350 ITS sequences from fungi growing as epiphytes on building material.ResultsThe pipeline was written in Perl and uses a local installation of NCBI-BLAST for the similarity searches of the query sequences. The variable subregion ITS2 of the ITS region is extracted from the sequences and used for additional searches of higher sensitivity. Multiple alignments of each query sequence and its closest matches are computed, and query sequences sharing at least 50% of their best matches are clustered to facilitate the evaluation of hypothetically conspecific groups. The pipeline proved to speed up the processing, as well as enhance the resolution, of the evaluation dataset considerably, and the fungi were found to belong chiefly to the Ascomycota, with Penicillium and Aspergillus as the two most common genera. The ITS2 was found to indicate a different taxonomic affiliation than did the complete ITS region for 10% of the query sequences, though this figure is likely to vary with the taxonomic scope of the query sequences.ConclusionThe present software readily assigns large sets of fungal query sequences to their respective best matches in the international sequence databases and places them in a larger biological context. The output is highly structured to be easy to process, although it still needs to be inspected and possibly corrected for the impact of the incomplete and sometimes erroneously annotated fungal entries in these databases. The open source pipeline is available for UNIX-type platforms, and updated releases of the target database are made available biweekly. The pipeline is easily modified to operate on other molecular regions and organism groups.

Characterizing the D2 Statistic: Word Matches in Biological Sequences

Word matches are often used in sequence comparison methods, either as a measure of sequence similarity or in the first search steps of algorithms such as BLAST or BLAT. The D2 statistic is the number of matches of words of k letters between two sequences. Recent advances have been made in the characterization of this statistic and in the approximation of its distribution. Here, these results are extended to the case of approximate word matches. We compute the exact value of the variance of the D2 statistic for the case of a uniform letter distribution, and introduce a method to provide accurate approximations of the variance in the remaining cases. This enables the distribution of D2 to be approximated for typical situations arising in biological research. We apply these results to the identification of cis-regulatory modules, and show that this method detects such sequences with a high accuracy. The ability to approximate the distribution of D2 for both exact and approximate word matches will enable the use of this statistic in a more precise manner for sequence comparison, database searches, and identification of transcription factor binding sites.

CUDASW++: optimizing Smith-Waterman sequence database searches for CUDA-enabled graphics processing units

BackgroundThe Smith-Waterman algorithm is one of the most widely used tools for searching biological sequence databases due to its high sensitivity. Unfortunately, the Smith-Waterman algorithm is computationally demanding, which is further compounded by the exponential growth of sequence databases. The recent emergence of many-core architectures, and their associated programming interfaces, provides an opportunity to accelerate sequence database searches using commonly available and inexpensive hardware.FindingsOur CUDASW++ implementation (benchmarked on a single-GPU NVIDIA GeForce GTX 280 graphics card and a dual-GPU GeForce GTX 295 graphics card) provides a significant performance improvement compared to other publicly available implementations, such as SWPS3, CBESW, SW-CUDA, and NCBI-BLAST. CUDASW++ supports query sequences of length up to 59K and for query sequences ranging in length from 144 to 5,478 in Swiss-Prot release 56.6, the single-GPU version achieves an average performance of 9.509 GCUPS with a lowest performance of 9.039 GCUPS and a highest performance of 9.660 GCUPS, and the dual-GPU version achieves an average performance of 14.484 GCUPS with a lowest performance of 10.660 GCUPS and a highest performance of 16.087 GCUPS.ConclusionCUDASW++ is publicly available open-source software. It provides a significant performance improvement for Smith-Waterman-based protein sequence database searches by fully exploiting the compute capability of commonly used CUDA-enabled low-cost GPUs.

プロテオーム解析における液体クロマトグラフィー３段階質量分析法（ＬＣ／ＭＳ｀３´） の有用性について

Protein identification via mass spectrometry (MS) relies primarily on protein sequence databases. Identification resulting from a sequence database search in the tandem mass spectrometry (MS/MS) experiments for the digested peptides is derived from an algorithm based on statistical confidence, and therefore, it often pro- ides false-positive identifications. Although one can apply high-resolution MS such as Fourier-transform mass spectrometer (FT-MS) to obtain results with high confidence, the instrumentation is expensive and the results are still probability based. Therefore, we introduced data-dependent triple stage mass spectrometry (MS3) into our well-established liquid chromatography/tandem mass spectrometry (LC/MS/MS) analysis of linear ion trap MS to achieve evidence-based protein identification. Peptide sequencing by MS3 analysis can provide a direct evidence for a sequence elucidated by MS/MS data and help determine whether the search results are correct.

Proteomics Analysis of the Excretory/Secretory Component of the Blood-feeding Stage of the Hookworm, Ancylostoma caninum

Hookworms are blood-feeding intestinal parasites of mammalian hosts and are one of the major human ailments affecting approximately 600 million people worldwide. These parasites form an intimate association with the host and are able to avoid vigorous immune responses in many ways including skewing of the response phenotype to promote parasite survival and longevity. The primary interface between the parasite and the host is the excretory/secretory component, a complex mixture of proteins, carbohydrates, and lipids secreted from the surface or oral openings of the parasite. The composition of this complex mixture is for the most part unknown but is likely to contain proteins important for the parasitic lifestyle and hence suitable as drug or vaccine targets. Using a strategy combining the traditional technology of one-dimensional SDS-PAGE and the newer fractionation technology of OFFGEL electrophoresis we identified 105 proteins from the excretory/secretory products of the blood-feeding stage of the dog hookworm, Ancylostoma caninum. Highly represented among the identified proteins were lectins, including three C-type lectins and three beta-galactoside-specific S-type galectins, as well as a number of proteases belonging to the three major classes found in nematodes, aspartic, cysteine, and metalloproteases. Interestingly 28% of the identified proteins were homologous to activation-associated secreted proteins, a family of cysteine-rich secreted proteins belonging to the sterol carrier protein/Tpx-1/Ag5/PR-1/Sc-7 (TAPS) superfamily. Thirty-four of these proteins were identified suggesting an important role in host-parasite interactions. Other protein families identified included hyaluronidases, lysozyme-like proteins, and transthyretin-like proteins. This work identified a suite of proteins important for the parasitic lifestyle and provides new insight into the biology of hookworm infection.

Peptizer, a Tool for Assessing False Positive Peptide Identifications and Manually Validating Selected Results

False positive peptide identifications are a major concern in the field of peptidecentric, mass spectrometry-driven gel-free proteomics. They occur in regions where the score distributions of true positives and true negatives overlap. Removal of these false positive identifications necessarily involves a trade-off between sensitivity and specificity. Existing postprocessing tools typically rely on a fixed or semifixed set of assumptions in their attempts to optimize both the sensitivity and the specificity of peptide and protein identification using MS/MS spectra. Because of the expanding diversity in available proteomics technologies, however, these postprocessing tools often struggle to adapt to emerging technology-specific peculiarity. Here we present a novel tool named Peptizer that solves this adaptability issue by making use of pluggable assumptions. This research-oriented postprocessing tool also includes a graphical user interface to perform efficient manual validation of suspect identifications for optimal sensitivity recovery. Peptizer is open source software under the Apache2 license and is written in Java.

Factors That Contribute to the Misidentification of Tyrosine Nitration by Shotgun Proteomics

The high selectivity and throughput of tandem mass spectrometry allow for rapid identification and localization of various posttranslational protein modifications from complex mixtures by shotgun approaches. Although sequence database search algorithms provide necessary support to process the potentially enormous quantity of MS/MS spectra generated from large scale tandem mass spectrometry experiments, false positive identifications of peptide modifications may exist even after implementation of stringent identification criteria. In this report, we describe factors that lead to misinterpretation of MS/MS spectra as well as common chemical and experimental artifacts that generate false positives using the proteomics-based identification of tyrosine nitration as an example. In addition to the proposed manual validation criteria, the importance of peptide synthesis and subsequent MS/MS characterization for validation of peptide nitration demonstrated by several examples from earlier publications is also presented.