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Nucleic acids were separated by ion-exchange chromatography on 30 x 4.6 and 100 x 4.6 mm columns packed with a micropellicular anion exchanger made of 3-microns rigid polystyrene-based non-porous microspheres with a covalently bound hydrophilic layer and DEAE functional groups at the surface. The stationary phase particles showed negligible swelling in methanol according to permeability measurements with water and methanol. Nucleic acids and their fragments including synthetic single-stranded oligonucleotides, linear, nicked and supercoiled DNAs as well as DNA restriction fragments were separated in less than 5 min, a time scale that is much smaller than that of conventional high-performance liquid chromatographic analysis for such samples. When only buffer and sodium chloride were used in the eluent for the separation of double-stranded DNA restriction fragments pGEM-3Z/Taq I, electrophoretic analysis of the effluent revealed the presence of smaller fragments in the bands of the larger ones. Upon addition of ethylenediaminetetraacetic (EDTA) salt to the eluent, however, such contamination by shorter fragments was no longer observed. In the absence of EDTA, magnesium chloride in the eluent at a concentration of 1 mM precluded the separation of the restriction fragments under otherwise identical chromatographic conditions.

BackgroundThe mosquito,Armigeres subalbatus, mounts a distinctively robust innate immune response when infected with the nematodeBrugia malayi, a causative agent of lymphatic filariasis. In order to mine the transcriptome for new insight into the cascade of events that takes place in response to infection in this mosquito, 6 cDNA libraries were generated from tissues of adult female mosquitoes subjected to immune-response activation treatments that lead to well-characterized responses, and from aging, naïve mosquitoes. Expressed sequence tags (ESTs) from each library were produced, annotated, and subjected to comparative analyses.ResultsSix libraries were constructed and used to generate 44,940 expressed sequence tags, of which 38,079 passed quality filters to be included in the annotation project and subsequent analyses. All of these sequences were collapsed into clusters resulting in 8,020 unique sequence clusters or singletons. EST clusters were annotated and curated manually within ASAP (A Systematic Annotation Package for Community Analysis of Genomes) web portal according to BLAST results from comparisons to Genbank, and theAnopheles gambiaeandDrosophila melanogastergenome projects.ConclusionThe resulting dataset is the first of its kind for this mosquito vector and provides a basis for future studies of mosquito vectors regarding the cascade of events that occurs in response to infection, and thereby providing insight into vector competence and innate immunity.

Summary form only given. Traditional domain database only provides the sequence related information, such as the consensus sequence or a position-specific scoring matrix. The so-called integrated domain databases, such as InterPro or CDD (conserved domain database), only integrates the information from different types of domain databases. The functional information, such as alternative splicing, tissue, protein interactions, etc., are usually missing. Therefore, it is important to have an integrated protein domain database, which will create a user-centric environment for biologists. The advantage of creating an integrated database for domains, instead of genes, is to discover the relations within a gene family. We have used death domain as an example to explain how to integrate the genome, transcriptome, and proteome information together. In this user-centric bioinformatics environment, the users may use information to make observations and even to create hypothesis for biomedical research. In other words, information integration is essential for information-driven biomedical research. For example, by integrating the alternative splicing and the protein domain information, a protein variant that may show inhibitory effect on signal transduction can be observed. By integrating tissue information with alternative splicing, protein variant that will be expressed in a given type of tissue might be revealed. Besides, by integrating tissue and histology information with pathway, the difference of a pathway in normal versus tumor cells would be clear. This system can be readily be applied to other protein domains. Thus, we name the whole program package "integrated domain resource (IDR)". The ultimate goal for this database is to integrate medical information into the system, so the relation of genotype and phenotype can be established in the future.

Mosquito-borne diseases, including dengue, malaria, and lymphatic filariasis, exact a devastating toll on global health and economics, killing or debilitating millions every year (54). Mosquito innate immune responses are at the forefront of concerted research efforts aimed at defining potential target genes that could be manipulated to engineer pathogen resistance in vector populations. We aimed to describe the pivotal role that circulating blood cells (called hemocytes) play in immunity by generating a total of 11,952 Aedes aegypti and 12,790 Armigeres subalbatus expressed sequence tag (EST) sequences from immune response-activated hemocyte libraries. These ESTs collapsed into 2,686 and 2,107 EST clusters, respectively. The clusters were used to adapt the web-based interface for annotating bacterial genomes called A Systematic Annotation Package for Community Analysis of Genomes (ASAP) for analysis of ESTs. Each cluster was categorically characterized and annotated in ASAP based on sequence similarity to five sequence databases. The sequence data and annotations can be viewed in ASAP at https://asap.ahabs.wisc.edu/annotation/php/ASAP1.htm . The data presented here represent the results of the first high-throughput in vivo analysis of the transcriptome of immunocytes from an invertebrate. Among the sequences are those for numerous immunity-related genes, many of which parallel those employed in vertebrate innate immunity, that have never been described for these mosquitoes.

PALS db is a collection of Putative Alternative Splicing information from 19 936 human UniGene clusters and 16 615 mouse UniGene clusters. Alternative splicing (AS) sites were predicted by using the longest messenger RNA (mRNA) sequence in each UniGene cluster as the reference sequence. This sequence was aligned with related sequences in UniGene and dbEST to reveal the AS. This information was presented with six features: (i) literature aliases were used to improve the result of a gene name search; (ii) the quality of a prediction can be easily judged from the color-coded similarity and the scaled length of an alignment; (iii) we have clustered those EST sequences that support the same AS site together to enhance the users’ confidence on a prediction; (iv) the users can also set up the alignment criteria interactively to recover false negatives; (v) tissue distribution can be displayed by placing the mouse cursor over an alignment; (vi) gene features will be analyzed at foreign sites by submitting the selected mRNA or its encoded protein as a query. Using these features, the users cannot only discover putative AS sites in silico, but also make new observations by combining AS information with tissue distributions or with gene features. PALS db is available at http:// palsdb.ym.edu.tw/.

Background MicroRNAs are very small non-coding RNAs that interact with microRNA recognition elements (MREs) on their target messenger RNAs. Varying the concentration of a given microRNA may influence the expression of many target proteins. Yet, the expression of a specific target protein can be fine-tuned by alternative cleavage and polyadenylation to the corresponding mRNA. Results This study showed that alternative splicing of mRNA is a fine-tuning mechanism in the cellular regulatory network. The splicing-regulated MREs are often highly repressive MREs. This phenomenon was observed not only in the hsa-miR-148a-regulated DNMT3B gene, but also in many target genes regulated by hsa-miR-124, hsa-miR-1, and hsa-miR-181a. When a gene contains multiple MREs in transcripts, such as the VEGF gene, the splicing-regulated MREs are again the highly repressive MREs. Approximately one-third of the analysable human MREs in MiRTarBase and TarBase can potentially perform the splicing-regulated fine-tuning. Interestingly, the high (+30%) repression ratios observed in most of these splicing-regulated MREs indicate associations with functions. For example, the MRE-free transcripts of many oncogenes, such as N-RAS and others may escape microRNA-mediated suppression in cancer tissues. Conclusions This fine-tuning mechanism revealed associations with highly repressive MRE. Since high-repression MREs are involved in many important biological phenomena, the described association implies that splicing-regulated MREs are functional. A possible application of this observed association is in distinguishing functionally relevant MREs from predicted MREs.

Functional phosphoproteomics is applied to gain the molecular insights into oncogenic RAS-mediated signaling pathway in lung adenocarcinoma. By means of immobilized metal affinity chromatography, mass spectrometry and a robust label-free quantitative system, we compared the phosphorylation profiles of five cell lines including immortalized normal human bronchial epithelial cells (HBECs) (wt KRAS), 3KTR (KRASG12V-transfected HBECs), A549 (KRASG12D), H322 (amplified KRAS), and H1299 (NRASQ61K). This resulted in the quantification of 1508 phosphorylation events and detection of regulated events across the cell lines. NetworKIN analysis of 2-fold regulated events (n=77) induced by oncogenic RAS in HBECs revealed 20 novel site-specific phosphorylation targets of MAP kinases. By browsing through STRING database, we identified 44 known substrates of MAP kinases in the interactome of phosphoproteins in this study. Further analysis of the site-specific upstream kinases of regulated phosphorylation events revealed the significant increase in basal kinases such as PAK, AKT/PKB and PKA in H1299 (large cell carcinoma) relative to A549 and H322 (adenocarcinoma). This increase in basal kinases may in-turn modulate the output of RAS-mediated MAPK signaling in large cell carcinoma cells (H1299). Supporting these results, majority of the regulated phosphorylation events (n=77) including MAPK, identified in HBECs expressing oncogenic RAS, were also differentially regulated in A549 and H322 but not in H1299. Further, inferring pathway signatures by integrating expression data of phosphorylation profiles to pathway interaction database, revealed the activation of MAPK signaling in 3KTR, A549 and H322 but not in H1299, whereas the activation of AKT and inactivation of mTOR signaling in H1299. Taken together, we demonstrate the phosphorylation targets, molecular regulation, and pathway activity signatures of onogenic RAS-mediated MAPK signaling in lung adenocarcinoma. Furthermore, the method introduced here to infer the pathway signatures is adaptable for future studies. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 5565.

The 2008 annual conference of the Asia Pacific Bioinformatics Network (APBioNet), Asia's oldest bioinformatics organisation set up in 1998, was organized as the 7th International Conference on Bioinformatics (InCoB), jointly with the Bioinformatics and Systems Biology in Taiwan (BIT 2008) Conference, Oct. 20–23, 2008 at Taipei, Taiwan. Besides bringing together scientists from the field of bioinformatics in this region, InCoB is actively involving researchers from the area of systems biology, to facilitate greater synergy between these two groups. Marking the 10th Anniversary of APBioNet, this InCoB 2008 meeting followed on from a series of successful annual events in Bangkok (Thailand), Penang (Malaysia), Auckland (New Zealand), Busan (South Korea), New Delhi (India) and Hong Kong. Additionally, tutorials and the Workshop on Education in Bioinformatics and Computational Biology (WEBCB) immediately prior to the 20th Federation of Asian and Oceanian Biochemists and Molecular Biologists (FAOBMB) Taipei Conference provided ample opportunity for inducting mainstream biochemists and molecular biologists from the region into a greater level of awareness of the importance of bioinformatics in their craft. In this editorial, we provide a brief overview of the peer-reviewed manuscripts accepted for publication herein, grouped into thematic areas. As the regional research expertise in bioinformatics matures, the papers fall into thematic areas, illustrating the specific contributions made by APBioNet to global bioinformatics efforts.

Background Schizophrenia is a complex disease with multiple factors contributing to its pathogenesis. In addition to environmental factors, genetic factors may also increase susceptibility. In other words, schizophrenia is a highly heritable disease. Some candidate genes have been deduced on the basis of their known function with others found on the basis of chromosomal location. Individuals with multiple candidate genes may have increased risk. However it is not clear what kind of gene combinations may produce the disease phenotype. Their collective effect remains to be studied. Results Most pathways except metabolic pathways are rich in protein-protein interactions (PPIs). Thus, the PPI network contains pathway information, even though the upstream-downstream relation of PPI is yet to be explored. Here we have constructed a PPI sub-network by extracting the nearest neighbour of the 36 reported candidate genes described in the literature. Although these candidate genes were discovered by different approaches, most of the proteins formed a cluster. Two major protein interaction modules were identified on the basis of the pairwise distance among the proteins in this sub-network. The large and small clusters might play roles in synaptic transmission and signal transduction, respectively, based on gene ontology annotation. The protein interactions in the synaptic transmission cluster were used to explain the interaction between the NRG1 and CACNG2 genes, which was found by both linkage and association studies. This working hypothesis is supported by the co-expression analysis based on public microarray gene expression. Conclusion On the basis of the protein interaction network, it appears that the NRG1-triggered NMDAR protein internalization and the CACNG2 mediated AMPA receptor recruiting may act together in the glutamatergic signalling process. Since both the NMDA and AMPA receptors are calcium channels, this process may regulate the influx of Ca2+. Reducing the cation influx might be one of the disease mechanisms for schizophrenia. This PPI network analysis approach combined with the support from co-expression analysis may provide an efficient way to propose pathogenetic mechanisms for various highly heritable diseases.

Background Genome-wide disease-gene finding approaches may sometimes provide us with a long list of candidate genes. Since using pure experimental approaches to verify all candidates could be expensive, a number of network-based methods have been developed to prioritize candidates. Such tools usually have a set of parameters pre-trained using available network data. This means that re-training network-based tools may be required when existing biological networks are updated or when networks from different sources are to be tried. Results We developed a parameter-free method, interconnectedness (ICN), to rank candidate genes by assessing the closeness of them to known disease genes in a network. ICN was tested using 1,993 known disease-gene associations and achieved a success rate of ~44% using a protein-protein interaction network under a test scenario of simulated linkage analysis. This performance is comparable with those of other well-known methods and ICN outperforms other methods when a candidate disease gene is not directly linked to known disease genes in a network. Interestingly, we show that a combined scoring strategy could enable ICN to achieve an even better performance (~50%) than other methods used alone. Conclusions ICN, a user-friendly method, can well complement other network-based methods in the context of prioritizing candidate disease genes.