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At least 1,171 records · Page 65Linked to original sources
PubMed2005

Analysis of the golden Syrian hamster anterior pituitary gland proteome by ion trap mass spectrometry.

We utilized mass spectrometry (MS) and bioinformatics to investigate the proteome of the anterior pituitary gland (AP). Subcellular fractions of APs from 2-month-old male Golden Syrian hamsters were prepared for protein denaturation, treatment with trypsin and analyses utilizing micro liquid chromatography MS/MS and the database search software SEQUEST. In the nuclear, non-nuclear 100,000 x g and cytosolic fractions we identified 76, 52 and 52 different proteins, respectively. A total of 145 distinct proteins were detected. We identified growth hormone, prolactin, pro-opiomelanocortin, the alpha-subunit for the glycoprotein hormones, luteinizing hormone-beta and follicle-stimulating hormone-beta. Groups of other identified proteins included hormone processing, secretion granule associated, non-hormonal endoplasmic reticulum associated, calcium binding, protein kinase C associated histone and non-histone chromosomal material, other RNA-binding, splicing factors, heterogeneous nuclear ribonucleoproteins, helicases, lamins, microfilament associated, microtubule associated, adenosine triphosphate and guanosine diphosphate associated, keratins, lysosomal, ribosomal, enzymes in glycolysis and the tricarboxylic and pentose phosphate paths, glutathione associated, transmethylation, catabolic and unknown protein products as well as blood hemoglobins. Proteins previously not reported in the AP, such as fertility protein SP22, were identified. The proteins identified in the present study form a foundation for defining the proteome in normal adult male AP.

Animals↗
PubMed2005

Physiological proteomics: cells, organs, biological fluids, and biomarkers.

Proteomic research is accelerating rapidly because of marked advances in protein labeling techniques, mass spectrometry (MS), and bioinformatics. Two-dimensional difference gel electrophoresis (2D-DIGE) is being used effectively in conjunction with liquid chromatography tandem MS (LC-MS/MS) and/or matrix-assisted laser desorption/ionization time-of-flight MS (MALDI-ToF MS) and database search software to quantify relative changes in the levels of proteins in two samples. It is now possible in a single study to identify and quantify large numbers of proteins and their posttranslational modifications in different biological samples. Comparisons can be made between groups of animals in different physiological states or in response to experimental treatment. Differences between normal individuals and those in disease states can form the foundation for elucidation of causative factors of disease and the identification of biomarkers for the diseased state. This symposium includes original research that compares the erythrocyte plasma membrane proteome in the normal and the sickle cell state, evaluates the anterior pituitary gland proteome in the ovariectomized rat in response to estrogen, and assesses proteomic methodology employed to identify potentially useful biomarkers in human cells and fluids for clinical medicine. It is directed not only to investigators working in these fields but also to a diverse group of scientists working in the biological and biomedical fields to stimulate cross-disciplinary awareness, interest, and collaboration.

Anemia, Sickle Cell↗
PubMed2002

Primer on medical genomics. Part IV: Expression proteomics.

Proteomics, simply defined, is the study of proteomes. More completely, proteomics is defined as the study of all proteins, including their relative abundance, distribution, posttranslational modifications, functions, and interactions with other macromolecules, in a given cell or organism within a given environment and at a specific stage in the cell cycle. Proteins carry out the biological functions encoded by genes; hence, once the initial stage of genome sequencing and gene discovery is completed, a study of the proteome must be undertaken to address fundamental biological questions. The 3 broad areas are expression proteomics, which catalogues the relative abundance of proteins; cell-mapping or cellular proteomics, which delineates functional protein-protein interactions and organelle-specific protein distribution; and structural proteomics, which characterizes the 3-dimensional structure of proteins. With these approaches, proteins are studied on a global scale using a synergistic combination of powerful, high-throughput technologies, including 2-dimensional polyacrylamide gel electrophoresis, mass spectrometry, multidimensional liquid chromatography, and bioinformatics. Mass spectrometry, which provides highly accurate molecular mass measurements, has emerged as the analytical technology of choice for protein identification, characterization, and sequencing. This task has been made considerably easier with the availability of complete, nonredundant, and annotated genome sequence databases for many organisms. This article reviews the area of expression proteomics.

Biotechnology↗
PubMed2005

An in silico mining for simple sequence repeats from expressed sequence tags of zebrafish, medaka, Fundulus, and Xiphophorus.

Teleost fish genome projects involving model species are resulting in a rapid accumulation of genomic and expressed DNA sequences in public databases. The expressed sequence tags (ESTs) collected in the databases can be mined for the analysis of both structural and functional genomics. In this study, we in silico analyzed 49,430 unigenes representing a total of 692,654 ESTs from four model fish for their potential use in developing simple sequence repeats (SSRs), or microsatellites. After bioinformatical mining, a total of 3,018 EST derived SSRs (EST-SSRs) were identified for 2,335 SSR containing ESTs (SSR-ESTs). The frequency of identified SSR-ESTs ranged from 1.5% for Xiphophorus to 7.3% for zebrafish. The dinucleotide repeat motif is the most abundant SSR, accounting for 47%, 52%, 64%, and 78% for medaka, Fundulus, zebrafish, and Xiphophorus, respectively. Simulation analysis suggests that a majority of these EST-SSRs have sufficient flanking sequences for polymerase chain reaction (PCR) primer design. Comparative DNA sequence analyses of SSR-ESTs identified several cross-species SSRs and sequences that may be used as cross-reference genes in comparative studies. For example, the flanking sequences of one SSR (CTG)n within the pituitary tumor-transforming gene (PTTG) 1 interacting protein (PTTGIP), showed conservation spanning the medaka, Fundulus, human, and mouse genomes. This study provides a large body of information on EST-SSRs that can be useful for the development of polymorphic markers, gene mapping, and comparative genome analysis. Functional analysis of these SSR-ESTs may reveal their role in metabolism and gene evolution of these model species.

Amino Acid Sequence↗
PubMed2006

Autophagy and related processes in trypanosomatids: insights from genomic and bioinformatic analyses.

The targeting in eukaryotic cells of cellular components to the lysosome or vacuole for degradation is called autophagy. Not only cytoplasmic macromolecules and bulk cytoplasm are subject to this process; entire organelles such as peroxisomes can be degraded. Autophagy of peroxisomes is called pexophagy. Unpublished evidence suggests that the analogous processing of glycosomes in the protozoan kinetoplastids occurs. Taking advantage of the (near-) complete status of three trypanosomatid genomes, a census of components of autophagy and related processes has been undertaken in these organisms. Simple database searches were supplemented by more advanced analyses where necessary. At most, only half of the components characterized in yeasts are present in trypanosomatids suggesting an unexpectedly streamlined version of autophagy occurs in these organisms. The cytoplasm-to-vacuole targeting (Cvt) system for delivery of proteins to the vacuole seems entirely absent in trypanosomatids. The accuracy of the census is supported by the coordinated absence of functionally linked components such as the conjugation system involving ATG12, ATG5, ATG10 and ATG16 that acts at the step of vesicle expansion and completion. Overall, the results are consistent with a scenario of taxon-specific addition of components to a minimal core, a hypothesis that should be readily testable by further genomic surveys allied to laboratory experiments. A bioinformatics analysis of the trypanosomatidal proteins was carried out, highlighting the paucity of information available regarding their structures and enabling prioritization of targets for future structural biology work.

Animals↗
PubMed2006

DisProt: the Database of Disordered Proteins.

The Database of Protein Disorder (DisProt) links structure and function information for intrinsically disordered proteins (IDPs). Intrinsically disordered proteins do not form a fixed three-dimensional structure under physiological conditions, either in their entireties or in segments or regions. We define IDP as a protein that contains at least one experimentally determined disordered region. Although lacking fixed structure, IDPs and regions carry out important biological functions, being typically involved in regulation, signaling and control. Such functions can involve high-specificity low-affinity interactions, the multiple binding of one protein to many partners and the multiple binding of many proteins to one partner. These three features are all enabled and enhanced by protein intrinsic disorder. One of the major hindrances in the study of IDPs has been the lack of organized information. DisProt was developed to enable IDP research by collecting and organizing knowledge regarding the experimental characterization and the functional associations of IDPs. In addition to being a unique source of biological information, DisProt opens doors for a plethora of bioinformatics studies. DisProt is openly available at http://www.disprot.org.

Databases, Protein↗
PubMed1993

Confocal microscopy and cellular bioinformatics.

An exhaustive description of most biological data requires, besides a set of analytic information, an eidetic representation of the data itself. In this paper, two topics are presented. The first one is confocal microscopy, an advanced technique to produce multidimensional cellular and subcellular structures images. The second one is a software application, named BIOCELL, based on a relational database management system, developed to provide the biologist with an integrated tool to handle simultaneously cell biology linguistic and eidetic information.

Biotechnology↗
PubMed2026

Phage bioinformatics tools: a review of computational approaches for bacteriophage research.

Rising clinical interest in phage therapy and the exponential growth of metagenomic sequence catalogues have driven a rapid expansion of bacteriophage bioinformatics. More than 80 dedicated tools, mostly published since 2020, now span identification, assembly, annotation, taxonomy, lifestyle prediction, defence-system detection, and host prediction. Aimed at experienced practitioners and developers, this review synthesizes the field through the lens of three successive computational paradigms: sequence homology, bounded by database completeness; machine learning, constrained by labelled training data; and foundation models, which now achieve Matthews correlation coefficients above 0.95 in identification tasks and, through structure-informed prediction, raise functional annotation to over half of phage genes. Furthermore, we map the upstream components, namely, gene callers, homology engines, protein language models, and structural search tools, that underpin most downstream pipelines, exposing shared infrastructure and ecosystem-level fragility when dependencies change. To translate this into practice, we propose web-based and command-line reference workflows calibrated to user expertise and sample types. Finally, we set an agenda for the next wave of tool development. Roughly half of phage genes still resist functional annotation despite structural methods; no broadly generalizable strain-level host predictor exists for phage therapy; varying true-positive rates (0%-97%) underscore the absence of standardized community benchmarks analogous to Critical Assessment of Structure Prediction or Critical Assessment of Metagenome Interpretation. As generative genome models begin designing synthetic phages, progress will depend less on producing standalone tools than on rigorous evaluation, interoperable infrastructure, and clinically meaningful prediction targets.

Computational Biology↗
PubMed2025

Construction and accuracy assessment of an efferocytosis-related prognostic model for ovarian cancer: A diagnostic accuracy study.

The study aimed to investigate the prognostic significance of efferocytosis-related genes in ovarian cancer (OC) with regard to cancer development, progression, invasion, and metastasis. OC cohorts were assembled from bioinformatics repositories. Utilizing consensus clustering analysis, distinct clusters were delineated based on the intersection of OC-related genes and efferocytosis-related genes. A prognostic signature specific to efferocytosis in OC was developed using data from The Cancer Genome Atlas, validated against the gene expression omnibus database, and subjected to independent prognostic analysis. Subsequently, a nomogram model was formulated. Moreover, investigations encompassed the immune microenvironment, immunotherapy, mutation profiling, drug sensitivity assessments, drug prediction models, and molecular docking analyses. Finally, quantitative reverse transcription polymerase chain reaction (qRT-PCR) assays were employed to ascertain the mRNA expression levels of key genes. Five key genes, FCGBP, BTN3A3, WDR91, SLC25A45, and BTNL3, were identified as significantly associated with OC. Both datasets and qRT-PCR demonstrated elevated expression levels of FCGBP and WDR91 in OC. Notably, AFLATOXIN B1 exhibited strong binding affinity to SLC25A45, ciclopirox to BTN3A3, and irinotecan to WDR91. The risk score, age, and stage were identified as independent prognostic factors, with the nomogram displaying efficacy in predicting OC patient survival. Variations in the immune cell infiltration profiles, including naive B cells, and expression levels of 6 immune checkpoint genes, such as CTLA4, were notable. High tumor mutation burden scores were associated with improved survival outcomes. Additionally, significant differences in the IC50 values of 123 anticancer drugs were observed between the 2 risk groups. This findings of this study highlight the efficacy of the efferocytosis-associated risk model in predicting the survival outcomes of OC patients, thus providing a novel reference for prognostic prediction in OC patients.

Humans↗
PubMed2003

A reference ontology for biomedical informatics: the Foundational Model of Anatomy.

The Foundational Model of Anatomy (FMA), initially developed as an enhancement of the anatomical content of UMLS, is a domain ontology of the concepts and relationships that pertain to the structural organization of the human body. It encompasses the material objects from the molecular to the macroscopic levels that constitute the body and associates with them non-material entities (spaces, surfaces, lines, and points) required for describing structural relationships. The disciplined modeling approach employed for the development of the FMA relies on a set of declared principles, high level schemes, Aristotelian definitions and a frame-based authoring environment. We propose the FMA as a reference ontology in biomedical informatics for correlating different views of anatomy, aligning existing and emerging ontologies in bioinformatics ontologies and providing a structure-based template for representing biological functions.

Abstracting and Indexing↗
PubMed2003

Bioinformatics in the post-sequence era.

In the past decade, bioinformatics has become an integral part of research and development in the biomedical sciences. Bioinformatics now has an essential role both in deciphering genomic, transcriptomic and proteomic data generated by high-throughput experimental technologies and in organizing information gathered from traditional biology. Sequence-based methods of analyzing individual genes or proteins have been elaborated and expanded, and methods have been developed for analyzing large numbers of genes or proteins simultaneously, such as in the identification of clusters of related genes and networks of interacting proteins. With the complete genome sequences for an increasing number of organisms at hand, bioinformatics is beginning to provide both conceptual bases and practical methods for detecting systemic functional behaviors of the cell and the organism.

Computational Biology↗
PubMed2005

The use of microarrays to study the anaerobic response in Arabidopsis.

BACKGROUND AND AIMS: The use of microarrays to characterize the transcript profile of Arabidopsis under various experimental conditions is rapidly expanding. This technique provides a huge amount of expression data, requiring bioinformatics tools to allow the proposal of working hypotheses. The aim of this study was to test the usefulness of this approach to examine the anaerobic response of Arabidopsis by evaluating the reliability of microarray data sets and by interrogation of microarray databases for the expression data of a set of anoxia-inducible genes. METHODS: User-driven software tools that display large gene expression datasets onto diagrams of metabolic pathways were used. The Genevestigator software was used to explore the expression of anoxia-inducible genes throughout the life cycle of Arabidopsis as well as relative to plant organs. T-DNA tagged mutants for selected genes identified from our microarray analysis were searched in the Arabidopsis thaliana Insertion Database, looking for insertional mutants from the Salk collection. KEY RESULTS: The results indicate that microarray data can provide the basis for new hypotheses in the field of plant responses to anaerobiosis and also provide knowledge for a targeted screening of Arabidopsis mutants. CONCLUSIONS: Research on plant responses to anaerobiosis can enormously benefit from the microarray technology.

Anaerobiosis↗
PubMed2004

WILMA-automated annotation of protein sequences.

Large-scale annotation of sets of proteins is a frequently occurring task in association with genome sequencing projects. Here, we present an automated platform for the functional annotation of large sets of protein sequences. Various bioinformatics tools are used to achieve a comprehensive description of protein sequences and to link these results to standard Gene Ontology descriptors for molecular function, biological processes and cellular components. Access to the annotation is provided via a web-interface and database queries. These interfaces allow to formulate proteome wide queries as well as the investigation of details of individual results. WILMA annotations of the proteomes of Homo sapiens, Mus musculus, Arabidopsis thaliana and Caenorhabditis elegans are accessible at http://www.came.sbg.ac.at/wilma/

Amino Acid Sequence↗
PubMed2005

KEGG as a glycome informatics resource.

Bioinformatics approaches to carbohydrate research have recently begun using large amounts of protein and carbohydrate data. In this field called glycome informatics, the foremost necessity is a comprehensive resource for genome-scale bioinformatics analysis of glycan data. Although the accumulation of experimental data may be useful as a reference of biological and biochemical information on carbohydrates, this is insufficient for bioinformatics analysis. Thus, we have developed a glycome informatics resource (http://www.genome.jp/kegg/glycan/) in KEGG (Kyoto Encyclopedia of Genes and Genomes), an integrated knowledge base of protein networks, genomic information, and chemical information. This review describes three noteworthy features: (1) GLYCAN, a database of carbohydrate structures; (2) glycan-related pathways; and (3) Composite Structure Map (CSM), a map illustrating all possible variations of carbohydrate structures within organisms. GLYCAN includes two useful tools: an intuitive drawing tool called KegDraw, and an efficient glycan search and alignment tool called KEGG Carbohydrate Matcher (KCaM). KEGG's glycan biosynthesis and metabolism pathways, integrating carbohydrate structures, proteins, and reactions, are also a pivotal resource. CSM is constructed as a bridge between carbohydrate functions and structures. CSM is able to display, for example, expression data of glycosyltransferases in a compact manner. In all the KEGG resources, various objects including KEGG pathways, chemical compounds, as well as carbohydrate structures are commonly represented as graphs, which are widely studied and utilized in the computer science field.

Carbohydrates↗
PubMed2006

The proteome: structure, function and evolution.

This paper reports two studies to model the inter-relationships between protein sequence, structure and function. First, an automated pipeline to provide a structural annotation of proteomes in the major genomes is described. The results are stored in a database at Imperial College, London (3D-GENOMICS) that can be accessed at www.sbg.bio.ic.ac.uk. Analysis of the assignments to structural superfamilies provides evolutionary insights. 3D-GENOMICS is being integrated with related proteome annotation data at University College London and the European Bioinformatics Institute in a project known as e-protein (http://www.e-protein.org/). The second topic is motivated by the developments in structural genomics projects in which the structure of a protein is determined prior to knowledge of its function. We have developed a new approach PHUNCTIONER that uses the gene ontology (GO) classification to supervise the extraction of the sequence signal responsible for protein function from a structure-based sequence alignment. Using GO we can obtain profiles for a range of specificities described in the ontology. In the region of low sequence similarity (around 15%), our method is more accurate than assignment from the closest structural homologue. The method is also able to identify the specific residues associated with the function of the protein family.

Computational Biology↗
PubMed2006

A dehydration-inducible gene in the truffle Tuber borchii identifies a novel group of dehydrins.

BACKGROUND: The expressed sequence tag M6G10 was originally isolated from a screening for differentially expressed transcripts during the reproductive stage of the white truffle Tuber borchii. mRNA levels for M6G10 increased dramatically during fruiting body maturation compared to the vegetative mycelial stage. RESULTS: Bioinformatics tools, phylogenetic analysis and expression studies were used to support the hypothesis that this sequence, named TbDHN1, is the first dehydrin (DHN)-like coding gene isolated in fungi. Homologs of this gene, all defined as "coding for hypothetical proteins" in public databases, were exclusively found in ascomycetous fungi and in plants. Although complete (or almost complete) fungal genomes and EST collections of some Basidiomycota and Glomeromycota are already available, DHN-like proteins appear to be represented only in Ascomycota. A new and previously uncharacterized conserved signature pattern was identified and proposed to Uniprot database as the main distinguishing feature of this new group of DHNs. Expression studies provide experimental evidence of a transcript induction of TbDHN1 during cellular dehydration. CONCLUSION: Expression pattern and sequence similarities to known plant DHNs indicate that TbDHN1 is the first characterized DHN-like protein in fungi. The high similarity of TbDHN1 with homolog coding sequences implies the existence of a novel fungal/plant group of LEA Class II proteins characterized by a previously undescribed signature pattern.

Amino Acid Sequence↗
PubMed2024

Use of extracellular vesicle microRNA profiles in patients with acute myeloid leukemia for the identification of novel biomarkers.

OBJECTIVES: This study aimed to establish clinically significant microRNA (miRNA) sets using extracellular vesicles (EVs) from bone marrow (BM) aspirates of patients with acute myelogenous leukemia (AML), and to identify the genes that interact with these EV-derived miRNAs in AML. MATERIALS AND METHODS: BM aspirates were collected from 32 patients with AML at the time of AML diagnosis. EVs were isolated using size-exclusion chromatography. A total of 965 EV-derived miRNAs were identified in all the samples. RESULTS: We analyzed the expression levels of these EV-derived miRNAs of the favorable (n = 10) and non-favorable (n = 22) risk groups; we identified 32 differentially expressed EV-derived miRNAs in the non-favorable risk group. The correlation of these miRNAs with risk stratification and patient survival was analyzed using the information of patients with AML from The Cancer Genome Atlas (TCGA) database. Of the miRNAs with downregulated expression in the non-favorable risk group, hsa-miR-181b and hsa-miR-143 were correlated with non-favorable risk and short overall survival. Regarding the miRNAs with upregulated expression in the non-favorable risk group, hsa-miR-188 and hsa-miR-501 were correlated with non-favorable risk and could predict poor survival. Through EV-derived miRNAs-mRNA network analysis using TCGA database, we identified 21 mRNAs that could be potential poor prognosis biomarkers. CONCLUSIONS: Overall, our findings revealed that EV-derived miRNAs can serve as biomarkers for risk stratification and prognosis in AML. In addition, these EV-derived miRNA-based bioinformatic analyses could help efficiently identify mRNAs with biomarker potential, similar to the previous cell-based approach.

Humans↗
PubMed2004

A model for training the new bioinformationist.

OBJECTIVES: The objectives were to examine the effectiveness of a curriculum designed to increase bioinformatics competencies of librarians with diverse backgrounds and to identify demographic factors that may affect the learning process. METHODS: Sixteen professional staff participated in a 12-week training course consisting of 5 distinct modules: molecular biology, genetic analysis, biotechnology, research literature, and databases. Participants completed a 120-question pretest and an 88-question posttest designed to evaluate the effectiveness of the training. RESULTS: Training was deemed successful as all participants scored higher on the posttest than the pretest. Data analysis was conducted in relation to participant background. Holding a biology degree did not seem to affect posttest results. Years of experience, however, had an impact on final scores in the databases section, as senior team members had greater difficulty learning the material. DISCUSSION: As the need for specialized information in the area of molecular biology and genetics becomes more central for the effectiveness of organizations, it is crucial for libraries to quickly align with those needs by having a clear vision for increasing the skills and competencies of their staff in this subject area. This paper describes an effective model for learning that was developed and tested by the Eskind Biomedical Library.

Biotechnology↗