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PubMed2005

[A novel mutation of WFS1 gene in Chinese patients with Wolfram syndrome].

OBJECTIVE: Wolfram syndrome is an autosomal recessive disorder characterized by early-onset diabetes mellitus, diabetes insipidus, optic atrophy and deafness. The aim of this study was to scan the WFS1 gene mutations in a Chinese Wolfram syndrome pedigree. METHODS: Eight exons and flanking introns of WFS1 gene were screened using PCR-DNA direct sequencing. Effects of the mutation on the structure and function of the WFS1 gene product, Wolframin, were evaluated by bioinformatics. RESULTS: A novel mutation, F417del, in the WFS1 gene was identified. The patient was homozygous of this mutation and the consanguineous parents were heterozygous. The mutation causes the lose of a non-polar amino acid, which was located in the transmembrane domain of the protein product. Bioinformatics predicted that the mutation altered the secondary structure of the transmembrane domain and decreased the hydrophobicity of F417del protein. CONCLUSIONS: This study identified a novel mutation of WFS1 gene and represented the first cause of molecular characterization of Chinese Wolfram syndrome patients.

Adult↗

PubMed2005

[Proteomic analysis of prostate cancer using surface enhanced laser desorption/ionization mass spectrometry].

OBJECTIVE: To identify the serum biomarkers of prostate cancer by using protein chip and bioinformatics. METHODS: Eighty three prostate cancer (PCA) patients and ninety five healthy people from mass screen in Changchun were detected by surface-enhanced laser desorption/ionization mass spectrometry (SELDI-MS). The data of spectra were analyzed by bioinformatics tools-Biomarker Wizard and Biomarker Pattern. RESULTS: Compared with the spectra of healthy people, there were 18 potential markers detected in the spectra of the PCA patients, the protein expression was high in 4 of which and low in the 10 of which. The softwares Biomarkerwizard and Biomarker Pattern automatically, under given conditions, selected 8 biomarker proteins to be used to establish a five layer decision tree differentiate to diagnose PCA and differentiate PCA from healthy people with a specificity of 92.632% and a sensitivity of 96.386%. CONCLUSION: New serum biomarkers of PCA have been identified, and this SELDI mass spectrometry coupled with decision tree classification algorithm will provide a highly accurate and innovative approach for the early diagnosis of PCA.

Aged↗

PubMed2006

Analysis and management of HIV peptide microarray experiments.

OBJECTIVES: To develop a tool for then easy and user-friendly management of peptide microarray experiments and for the use of the results of these experiments for the study the immune response against HIV virus infection in clinical samples. METHODS: Applying bioinformatics and statistics for the analysis of data coming from microarray experiments as well as implementing a MIAME (Minimum Information About a Microarray Experiment) compliant database for managing and annotating experiments, results and samples. RESULTS: We present a new tool for managing not only nucleic acid microarray experiments but also protein microarray experiments. From the analysis of experimental data, we can detect different profiles in the reactivity of the sera with different genotypes. CONCLUSIONS: We have developed a new tool for managing microarray data including clinical annotations for the samples as well as the capability of annotating other microarray formats different to those based on nucleic acids. The use of peptide microarrays and bioinformatics analysis opens a new scope for the characterization of the immune response, and analyzing and identifying the humoral response of viruses with different genotypes.

Computational Biology↗

PubMed2006

[caCORE: core architecture of bioinformation on cancer research in America].

A critical factor in the advancement of biomedical research is the ease with which data can be integrated, redistributed and analyzed both within and across domains. This paper summarizes the Biomedical Information Core Infrastructure built by National Cancer Institute Center for Bioinformatics in America (NCICB). The main product from the Core Infrastructure is caCORE--cancer Common Ontologic Reference Environment, which is the infrastructure backbone supporting data management and application development at NCICB. The paper explains the structure and function of caCORE: (1) Enterprise Vocabulary Services (EVS). They provide controlled vocabulary, dictionary and thesaurus services, and EVS produces the NCI Thesaurus and the NCI Metathesaurus; (2) The Cancer Data Standards Repository (caDSR). It provides a metadata registry for common data elements. (3) Cancer Bioinformatics Infrastructure Objects (caBIO). They provide Java, Simple Object Access Protocol and HTTP-XML application programming interfaces. The vision for caCORE is to provide a common data management framework that will support the consistency, clarity, and comparability of biomedical research data and information. In addition to providing facilities for data management and redistribution, caCORE helps solve problems of data integration. All NCICB-developed caCORE components are distributed under open-source licenses that support unrestricted usage by both non-profit and commercial entities, and caCORE has laid the foundation for a number of scientific and clinical applications. Based on it, the paper expounds caCORE-base applications simply in several NCI projects, of which one is CMAP (Cancer Molecular Analysis Project), and the other is caBIG (Cancer Biomedical Informatics Grid). In the end, the paper also gives good prospects of caCORE, and while caCORE was born out of the needs of the cancer research community, it is intended to serve as a general resource. Cancer research has historically contributed to many areas beyond tumor biology. At the same time, the paper makes some suggestions about the study at the present time on biomedical informatics in China.

Computational Biology↗

PubMed2006

Blast2GO goes grid: developing a grid-enabled prototype for functional genomics analysis.

The vast amount in complexity of data generated in Genomic Research implies that new dedicated and powerful computational tools need to be developed to meet their analysis requirements. Blast2GO (B2G) is a bioinformatics tool for Gene Ontology-based DNA or protein sequence annotation and function-based data mining. The application has been developed with the aim of affering an easy-to-use tool for functional genomics research. Typical B2G users are middle size genomics labs carrying out sequencing, ETS and microarray projects, handling datasets up to several thousand sequences. In the current version of B2G. The power and analytical potential of both annotation and function data-mining is somehow restricted to the computational power behind each particular installation. In order to be able to offer the possibility of an enhanced computational capacity within this bioinformatics application, a Grid component is being developed. A prototype has been conceived for the particular problem of speeding up the Blast searches to obtain fast results for large datasets. Many efforts have been done in the literature concerning the speeding up of Blast searches, but few of them deal with the use of large heterogeneous production Grid Infrastructures. These are the infrastructures that could reach the largest number of resources and the best load balancing for data access. The Grid Service under development will analyse requests based on the number of sequences, splitting them accordingly to the available resources. Lower-level computation will be performed through MPIBLAST. The software architecture is based on the WSRF standard.

Computational Biology↗

PubMed2006

The University of Washington Health Sciences Library BioCommons: an evolving Northwest biomedical research information support infrastructure.

SETTING: The University of Washington Health Sciences Libraries and Information Center BioCommons serves the bioinformatics needs of researchers at the university and in the vibrant for-profit and not-for-profit biomedical research sector in the Washington area and region. PROGRAM COMPONENTS: The BioCommons comprises services addressing internal University of Washington, not-for-profit, for-profit, and regional and global clientele. The BioCommons is maintained and administered by the BioResearcher Liaison Team. The BioCommons architecture provides a highly flexible structure for adapting to rapidly changing resources and needs. EVALUATION MECHANISMS: BioCommons uses Web-based pre- and post-course evaluations and periodic user surveys to assess service effectiveness. Recent surveys indicate substantial usage of BioCommons services and a high level of effectiveness and user satisfaction. NEXT STEPS/FUTURE DIRECTIONS: BioCommons is developing novel collaborative Web resources to distribute bioinformatics tools and is experimenting with Web-based competency training in bioinformation resource use.

Academic Medical Centers↗

PubMed2006

[Screening and cloning of the down-regulation gene by recombinant interferon-B using suppression subtractive hybridization technique.].

BACKGROUND: To construct a subtractive cDNA library of target genes down-regulated in human hepatocarcinoma cell line HepG2 cells treated with IFNB, and clone genes of the down-regulation by IFNB using suppression subtractive hybridization (SSH) technology and bioinformatics techniques. METHODS: The mRNA was isolated from HepG2 cells induced by recombinant interferon-B and 0.9 percent sodium chloride, respectively, then cDNA was synthesized. After restriction enzyme Rsa I digestion, small sizes cDNAs were obtained. Then tester cDNA was divided into two portions and each was ligated to the specific cDNA adaptor 1 and adaptor 2 respectively. After tester cDNA was hybridized with driver cDNA twice and underwent two times of nested PCR, the DNA fragment was subcloned into T/A plasmid vectors to set up the subtractive library. Amplification of the library was carried out with E.coli strain DH5a. The cDNA was sequenced and analyzed in GenBank with Blast search after PCR. RESULTS: The subtractive library of genes down-regulation in HepG2 cells treated with recombination interferon-B was constructed successfully. The amplified library contained 58 positive clones. Colony PCR and sequence analysis was performed in 35 clones randomly, and the full length sequences were obtained with bioinformatics method. Altogether 12 coding sequences were obtained. CONCLUSION: A subtractive cDNA library of genes down-regulation in HepG2 cells treated with IFNB using SSH technique was constructed successfully, which brings some new clues for studying the regulation mechenism of IFNB in liver cells.

Cloning, Molecular↗

PubMed2006

Molecular cloning of a novel cDNA from Mus muscular BALB/c mice encoding glycosyl hydrolase family 1: a homolog of human lactase-phlorizin hydrolase.

OBJECTIVE: To study the mechanism of lactose intolerance (LI) by cloning the mouse lactase cDNA and recombining a vector. METHODS Total murine RNA was isolated from the small intestine of a 4-week-old BALB/c mouse (d). Gene-specific primers were designed and synthesized according to the cDNA sequences of lactase-phlorizin hydrolase (LPH) in human, rat, and rabbit. A coding sequence (CDS) fragment was obtained using RT-PCR, and inserted into a clone vector pNEB-193, then the cDNA was sequenced and analyzed using bioinformatics. RESULTS: The cDNA from the BALB/c mouse with 912 bp encoding 303 amino acid residues. Analysis of the deduced amino acid sequence using bioinformatics revealed that this cDNA shared extensive sequence homology with human LPH containing a conserved glycosyl hydrolase family 1 motif important for regulating lactase intolerance. CONCLUSION: BALB/c mouse LPH cDNA (GenBank accession No: AY751548) provides a necessary foundation for study of the biological function and regulatory mechanism of the lactose intolerance in mice.

Animals↗

PubMed1997

Novel techniques for visualising biological information.

The major challenge facing the bioinformatics community is the continuing increase in the number, size and complexity of biological databases with which it must contend. The goal of the research discussed herein is the development and utilisation of techniques that allow researchers to extract new and useful information from these burgeoning information resources using advanced visualisation methods and paradigms, coupled with distributed object technologies that allow communications between applications and remote databases. Visualisation has roles not only in analysis, but also in building more user-friendly interfaces, implementing methods to navigate large information spaces intuitively and powerful techniques to browse and query data. By using platform-independent object-oriented programming languages, these resources may be developed as reusable pieces of software componentry with their methods and interfaces defined fully, and then distributed through organisations such as the bioWidget Consortium. The widget and object-oriented approach is a powerful paradigm in developing new applications from existing components. Development time is reduced and greater time is spent on analysing these data, rather than in the writing of monolithic applications. More powerful applications can be constructed from components interacting in concert and offers the opportunity of a new generation of bioinformatics tools.

Base Composition↗

PubMed1996

A protocol for maintaining multidatabase referential integrity.

The bioinformatics community is becoming increasingly reliant on the creation of links among biological databases (DBs) as a foundation for DB interoperability. For example, a link might be created from a protein in one DB (such as PIR), to a gene in another DB (such as GDB), by storing the unique identifier (id) of the gene object within an attribute of the protein object. User interfaces can then support navigation from the protein to the gene, and multiDB queries can join the protein with the gene. The unique id of the gene is serving as a foreign key. However, a variety of factors, such as changes in the underlying biology, can cause object ids to become invalid, thus producing invalid links among DBs. Invalid links are a violation of multidatabase referential integrity. We propose a network protocol whereby a database administrator can provide information about changes to the identifiers of objects in their database via Internet, to allow other databases to maintain referential integrity. We request comments from the bioinformatics community for the purpose of building a consensus on the proposed protocol.

Computational Biology↗

PubMed2025

Prediction and Evaluation of Protein Aggregation with Computational Methods.

Protein and peptide aggregation has recently become one of the most studied biomedical problems due to its central role in several neurodegenerative disorders and of biotechnological importance. Multiple in silico methods, databases, tools, and algorithms have been developed to predict aggregation of proteins and peptides to better understand fundamental mechanisms of various aggregation diseases. Here, we attempt to provide a brief overview of bioinformatic methods and tools to better understand molecular mechanisms of aggregation disorders. Furthermore, through a better understanding of protein aggregation mechanisms, it might be possible to design novel therapeutic agents to treat and hopefully prevent protein aggregation diseases.

Computational Biology↗

PubMed2025

Spatial Genomic Approaches to Investigate HOX Genes in Mouse Brain Tissues.

Spatial transcriptomic tools are an upcoming and powerful way to investigate targeted gene expression patterns within tissues. These tools offer the unique advantage of visualizing and understanding gene expression while preserving tissue integrity, thereby maintaining the spatial context of genes. Curio is a robust spatial transcriptomic tool that facilitates high throughput comprehensive spatial gene expression analysis across the entir e transcriptome with high efficiency. Here, we present a bioinformatics protocol for performing whole transcriptome gene expression analysis of mouse brain tissue using Curio. Specifically, we demonstrate using computational techniques to visualize expression patterns of various HOX genes in the mouse brain.

Animals↗

PubMed2027

Global Genomic Surveillance.

Global genomic surveillance has emerged as a foundational pillar of public health in the twenty-first century, enabling real-time tracking of pathogen evolution and informing outbreak response. This chapter examines the strategic architecture of global genomic surveillance, focusing on its application to arboviruses such as chikungunya virus (CHIKV). It explores the integration of genomic data with epidemiological, clinical, and environmental information within a One Health framework, while addressing critical challenges in governance, equity, and interoperability. The discussion covers the entire genomic surveillance workflow, from sample collection and sequencing to bioinformatic analysis and phylogenetic inference, and highlights the transformative role of artificial intelligence (AI) in predictive surveillance. By analyzing global initiatives, operational barriers, and emerging technologies, this chapter underscores the necessity of sustainable, equitable, and interoperable genomic systems to proactively address current and future infectious disease threats.

Humans↗

PubMed2024

Detection of mitochondrial tDRs in killifish embryos and other non-model organisms.

In recent years a diversity of small noncoding RNAs have been identified that originate from the mitochondrial genome. These mitosRNAs are often dominated by tRNA-derived small RNAs (mito-tDRs). Differential expression of mito-tDRs is associated with responses to stress. They also appear to be expressed differentially during development and their expression may be enriched in stress-tolerant animals. Very little is currently known about roles or modes of action of these sequences, although they are implicated in a diversity of processes such as cell cycle regulation, mRNA stability, regulation of ROS production, and import of proteins into the mitochondrion. To better understand the various roles these sequences may play, it is critical that we understand their diversity, cellular location, and the context for their expression. This protocol outlines the methodologies used to detect mitosRNAs, including mito-tDRs, in embryos and cells of the annual killifish Austrofundulus limnaeus. We highlight critical steps in the isolation of RNA, creation of sequencing libraries, bioinformatics processing of sequence data, and methods for validation of expression that support a robust discovery pipeline for mitosRNAs even from species with incomplete reference genome sequences.

Animals↗

PubMed2025

Integrated multi-omics analysis reveals TMEM147 as an immunosuppressive prognostic biomarker in LUAD.

TMEM147, an endoplasmic reticulum (ER) membrane protein, is implicated in lung adenocarcinoma (LUAD) progression, although its precise role remains unclear. To elucidate its function, this study integrated bioinformatics analyses with experimental validation. First, TMEM147 expression was assessed using TCGA and GEO datasets, with validation performed in LUAD cell lines. Survival analysis evaluated its prognostic significance. Subsequently, Gene Ontology (GO)/Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses and single-sample gene set enrichment analysis (ssGSEA) were employed to identify associated functional pathways and interactions within the tumor immune microenvironment. Transcription factor binding predictions and in vitro functional assays (migration, invasion, proliferation) further characterized TMEM147's role. Results indicated that TMEM147 was significantly upregulated in LUAD and correlated with poor outcomes in patients. FLI1 was predicted as a key transcriptional regulator of TMEM147. Furthermore, TMEM147 expression influenced immune cell infiltration profiles and was associated with pathways involved in ribonucleoprotein biogenesis and oxidative phosphorylation (OXPHOS). Importantly, silencing TMEM147 significantly reduced cancer cell migration, invasion, and proliferation. These findings collectively suggest that TMEM147 promotes LUAD progression and holds potential as both a prognostic biomarker and a therapeutic target.

Bioinformatics analysis↗

PubMed2025

Insulin receptor variants: Extending the traditional Mendelian spectrum.

PURPOSE: INSR encodes the insulin receptor, the essential entrainer of growth and metabolism to nutritional cues. INSR variants cause a spectrum of monogenic insulin resistance (IR) syndromes, namely, type A insulin resistance, Rabson-Mendenhall, and Donohue syndromes. However, to our knowledge, no large cohort studies focused on variant classification and its diagnostic value have been described. METHODS: This multicentric cohort study included 73 patients carrying INSR variants, referred for IR by 52 centers from 6 countries. Variants were classified using new bioinformatic tools relying on different prediction mechanisms and the American College of Medical Genetics and Genomics guidelines. RESULTS: Besides expanding the INSR mutational spectrum, this study suggested a semidominant inheritance in several Donohue/Rabson-Mendenhall syndrome families. Questioning strictly Mendelian inheritance, heterozygous loss-of-function (LoF) variants were mostly found in overweight patients, with a higher LoF frequency in IR patients than in the general population (odds ratio 5.77). Diagnostic challenges arose when trying to refine classification criteria for variants of uncertain significance. Among the variant effect predictors assessed, MISTIC and AlphaMissense outperformed REVEL. CONCLUSION: The spectrum of INSR-related disorders extends beyond traditional entities. Heterozygous INSR LoF variants may increase IR susceptibility. International collaboration and functional assays are needed to drive precision medicine forward.

Humans↗

PubMed2024

A Proteogenomic Pipeline for the Analysis of Protein Biosynthesis Errors in the Human Pathogen Candida albicans.

Candida albicans is a diploid pathogen known for its ability to live as a commensal fungus in healthy individuals but causing both superficial infections and disseminated candidiasis in immunocompromised patients where it is associated with high morbidity and mortality. Its success in colonizing the human host is attributed to a wide range of virulence traits that modulate interactions between the host and the pathogen, such as optimal growth rate at 37 °C, the ability to switch between yeast and hyphal forms, and a remarkable genomic and phenotypic plasticity. A fascinating aspect of its biology is a prominent heterogeneous proteome that arises from frequent genomic rearrangements, high allelic variation, and high levels of amino acid misincorporations in proteins. This leads to increased morphological and physiological phenotypic diversity of high adaptive potential, but the scope of such protein mistranslation is poorly understood due to technical difficulties in detecting and quantifying amino acid misincorporation events in complex protein samples. We have developed and optimized mass spectrometry and bioinformatics pipelines capable of identifying rare amino acid misincorporation events at the proteome level. We have also analyzed the proteomic profile of an engineered C. albicans strain that exhibits high level of leucine misincorporation at protein CUG sites and employed an in vivo quantitative gain-of-function fluorescence reporter system to validate our LC-MS/MS data. C. albicans misincorporates amino acids above the background level at protein sites of diverse codons, particularly at CUG, confirming our previous data on the quantification of leucine incorporation at single CUG sites of recombinant reporter proteins, but increasing misincorporation of Leucine at these sites does not alter the translational fidelity of the other codons. These findings indicate that the C. albicans statistical proteome exceeds prior estimates, suggesting that its highly plastic phenome may also be modulated by environmental factors due to translational ambiguity.

Candida albicans↗

PubMed2026

Integrated exome and mitochondrial genome sequencing reveals the genetic landscape of primary mitochondrial diseases: findings from a large Tunisian cohort.

Primary mitochondrial diseases are a heterogeneous group of neurometabolic disorders recognized as the most common metabolic genetic diseases. They manifest at any age, affecting any tissue or organ, especially those with high energy demands, and are caused by pathogenic variants in both mitochondrial and nuclear genomes. Here, we aimed to describe the genetic spectrum of a Tunisian pediatric cohort with suspected mitochondrial diseases. We recruited 47 unrelated families who underwent exome sequencing as a first-tier test followed by whole mitochondrial genome sequencing for unsolved cases. Dedicated bioinformatic pipelines and prediction tools were used to determine the potential disease-causing variants. Sanger sequencing confirmed the presence and segregation within parents. For the newly identified variants, structural modeling was conducted to study the impact of these variants on protein structure and motions. Dual genome sequencing yielded a molecular diagnosis in 33/47 families (70%) and 18/47 (38%) showed disease-causing variants in genes encoding mitochondrial proteins. Among them, four families disclosed novel variants in FASTKD2, SERAC1 and GATB, which were supported by in-depth in silico and structural analyses demonstrating their deleterious effect. The remaining families (32%, 15/47) disclosed other metabolic and neurological disorders. An exome-first strategy delivers a high diagnostic yield in Tunisia, where consanguinity remains high and simultaneously captures mitochondrial and non-mitochondrial etiologies. Mitochondrial sequencing remains indispensable in the case of an inconclusive exome. Thus, our data expand the clinical and genetic spectrum of primary mitochondrial diseases in Tunisia, an underrepresented and admixed population.

Humans↗