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PubMed2006

AbMiner: a bioinformatic resource on available monoclonal antibodies and corresponding gene identifiers for genomic, proteomic, and immunologic studies.

BACKGROUND: Monoclonal antibodies are used extensively throughout the biomedical sciences for detection of antigens, either in vitro or in vivo. We, for example, have used them for quantitation of proteins on "reverse-phase" protein lysate arrays. For those studies, we quality-controlled > 600 available monoclonal antibodies and also needed to develop precise information on the genes that encode their antigens. Translation among the various protein and gene identifier types proved non-trivial because of one-to-many and many-to-one relationships. To organize the antibody, protein, and gene information, we initially developed a relational database in Filemaker for our own use. When it became apparent that the information would be useful to many other researchers faced with the need to choose or characterize antibodies, we developed it further as AbMiner, a fully relational web-based database under MySQL, programmed in Java. DESCRIPTION: AbMiner is a user-friendly, web-based relational database of information on > 600 commercially available antibodies that we validated by Western blot for protein microarray studies. It includes many types of information on the antibody, the immunogen, the vendor, the antigen, and the antigen's gene. Multiple gene and protein identifier types provide links to corresponding entries in a variety of other public databases, including resources for phosphorylation-specific antibodies. AbMiner also includes our quality-control data against a pool of 60 diverse cancer cell types (the NCI-60) and also protein expression levels for the NCI-60 cells measured using our high-density "reverse-phase" protein lysate microarrays for a selection of the listed antibodies. Some other available database resources give information on antibody specificity for one or a couple of cell types. In contrast, the data in AbMiner indicate specificity with respect to the antigens in a pool of 60 diverse cell types from nine different tissues of origin. CONCLUSION: AbMiner is a relational database that provides extensive information from our own laboratory and other sources on more than 600 available antibodies and the genes that encode the antibodies' antigens. The data will be made freely available at http://discover.nci.nih.gov/abminer.

Antibodies, Monoclonal↗
PubMed2006

A comparative study of cells in inflammation, EAE and MS using biomedical literature data mining.

Biomedical literature and database annotations, available in electronic forms, contain a vast amount of knowledge resulting from global research. Users, attempting to utilize the current state-of-the-art research results are frequently overwhelmed by the volume of such information, making it difficult and time-consuming to locate the relevant knowledge. Literature mining, data mining, and domain specific knowledge integration techniques can be effectively used to provide a user-centric view of the information in a real-world biological problem setting. Bioinformatics tools that are based on real-world problems can provide varying levels of information content, bridging the gap between biomedical and bioinformatics research. We have developed a user-centric bioinformatics research tool, called BioMap, that can provide a customized, adaptive view of the information and knowledge space. BioMap was validated by using inflammatory diseases as a problem domain to identify and elucidate the associations among cells and cellular components involved in multiple sclerosis (MS) and its animal model, experimental allergic encephalomyelitis (EAE). The BioMap system was able to demonstrate the associations between cells directly excavated from biomedical literature for inflammation, EAE and MS. These association graphs followed the scale-free network behavior (average gamma = 2.1) that are commonly found in biological networks.

Animals↗
PubMed2006

Counting the zinc-proteins encoded in the human genome.

Metalloproteins are proteins capable of binding one or more metal ions, which may be required for their biological function, or for regulation of their activities or for structural purposes. Genome sequencing projects have provided a huge number of protein primary sequences, but, even though several different elaborate analyses and annotations have been enabled by a rich and ever-increasing portfolio of bioinformatic tools, metal-binding properties remain difficult to predict as well as to investigate experimentally. Consequently, the present knowledge about metalloproteins is only partial. The present bioinformatic research proposes a strategy to answer the question of how many and which proteins encoded in the human genome may require zinc for their physiological function. This is achieved by a combination of approaches, which include: (i) searching in the proteome for the zinc-binding patterns that, on their turn, are obtained from all available X-ray data; (ii) using libraries of metal-binding protein domains based on multiple sequence alignments of known metalloproteins obtained from the Pfam database; and (iii) mining the annotations of human gene sequences, which are based on any type of information available. It is found that 1684 proteins in the human proteome are independently identified by all three approaches as zinc-proteins, 746 are identified by two, and 777 are identified by only one method. By assuming that all proteins identified by at least two approaches are truly zinc-binding and inspecting the proteins identified by a single method, it can be proposed that ca. 2800 human proteins are potentially zinc-binding in vivo, corresponding to 10% of the human proteome, with an uncertainty of 400 sequences. Available functional information suggests that the large majority of human zinc-binding proteins are involved in the regulation of gene expression. The most abundant class of zinc-binding proteins in humans is that of zinc-fingers, with Cys4 and Cys2His2 being the most common types of coordination environment.

Computational Biology↗
PubMed2006

Inhibitory effects of procyanidin B(2) dimer on lipid-laden macrophage formation.

A proteomic analysis of procyanidin B(2) isolated from cocoa against oxidized low-density lipoprotein-induced lipid-laden macrophage formation was performed. Of approximately 400 detected proteins, 12 were differentially expressed as a result of B(2) treatment. They were subsequently identified by liquid chromatography-electrospray ionization-tandem mass spectrometry and the SWISS-PROT database. Further reverse transcriptase-polymerase chain reaction and Western blot analysis revealed that B(2) strongly inhibited arachidonic acid inflammatory reactions, apoptosis, and their coupled mitogen-activated protein kinase and NF-kappaB pathways. To highlight proteins or genes with similar expressed patterns and similarly biological function induced by B(2) in lipid-laden macrophages, a cluster and Kyoto Encyclopedia of Genes and Genomes pathway analysis were performed. The data were mapped to multiple pathways. Further validation of the bioinformatic results revealed that activation of Wnt signaling may contribute to the cardioprotection of B(2). The differentially expressed genes and proteins mentioned above induced by B(2) are through regulating nuclear transcription factors, activating peroxisome proliferator-activated receptor-gamma and inhibiting AP-1 mRNA expressions. These in vitro data help to interpret the beneficial effects of B(2) in reducing the risk of atherosclerosis after consumption of flavonoid-rich foods. Many differentially expressed genes induced by B(2) help to uncover novel targets and may help to target disease interactions in atherosclerosis in the future.

Amino Acid Sequence↗
PubMed2006

The NeuARt II system: a viewing tool for neuroanatomical data based on published neuroanatomical atlases.

BACKGROUND: Anatomical studies of neural circuitry describing the basic wiring diagram of the brain produce intrinsically spatial, highly complex data of great value to the neuroscience community. Published neuroanatomical atlases provide a spatial framework for these studies. We have built an informatics framework based on these atlases for the representation of neuroanatomical knowledge. This framework not only captures current methods of anatomical data acquisition and analysis, it allows these studies to be collated, compared and synthesized within a single system. RESULTS: We have developed an atlas-viewing application ('NeuARt II') in the Java language with unique functional properties. These include the ability to use copyrighted atlases as templates within which users may view, save and retrieve data-maps and annotate them with volumetric delineations. NeuARt II also permits users to view multiple levels on multiple atlases at once. Each data-map in this system is simply a stack of vector images with one image per atlas level, so any set of accurate drawings made onto a supported atlas (in vector graphics format) could be uploaded into NeuARt II. Presently the database is populated with a corpus of high-quality neuroanatomical data from the laboratory of Dr Larry Swanson (consisting 64 highly-detailed maps of PHAL tract-tracing experiments, made up of 1039 separate drawings that were published in 27 primary research publications over 17 years). Herein we take selective examples from these data to demonstrate the features of NeuArt II. Our informatics tool permits users to browse, query and compare these maps. The NeuARt II tool operates within a bioinformatics knowledge management platform (called 'NeuroScholar') either as a standalone or a plug-in application. CONCLUSION: Anatomical localization is fundamental to neuroscientific work and atlases provide an easily-understood framework that is widely used by neuroanatomists and non-neuroanatomists alike. NeuARt II, the neuroinformatics tool presented here, provides an accurate and powerful way of representing neuroanatomical data in the context of commonly-used brain atlases for visualization, comparison and analysis. Furthermore, it provides a framework that supports the delivery and manipulation of mapped data either as a standalone system or as a component in a larger knowledge management system.

Anatomy, Artistic↗
PubMed2006

A nonsense polymorphism (Y319X) of the solute carrier family 6 member 18 (SLC6A18) gene is not associated with hypertension and blood pressure in Japanese.

We investigated the possible association of solute carrier family 6 member 18 (SLC6A18) with hypertension and blood pressure in Japanese, since the homologous murine XT2 gene was recently reported to be associated with hypertension. The entire coding region of SLC6A18 was sequenced in 30 unrelated Japanese subjects. The deleterious effects of the observed nonsynonymous single nucleotide polymorphisms (SNPs) on the phenotype were predicted using bioinformatics software. We tested the associations of one deleterious SNP (Y319X) with blood pressure and hypertension in a general population of 1,004 subjects in one area of Japan. Both quantitative and qualitative analyses adjusting for age and body mass index (BMI) as covariates were undertaken. Four synonymous (P7P, T32T, G37G and V387V), three missense (S12C, I32T and L478P) and one nonsense (Y319X: g1230757 C > G) polymorphisms were found. One of the synonymous polymorphisms was novel (V387V) by reference to the dbSNP database. The Y319X genotype distribution of CC:CG:GG in this population showed frequencies of 0.382, 0.461 and 0.156, respectively, which followed Hardy-Weinberg equilibrium. The nonsense polymorphism had odds ratios of 0.83 (confidence interval [CI] = 0.59-1.15, p = 0.26) in males and 0.96 (CI = 0.72-1.29, p = 0.80) in females with hypertension or current medication for hypertension. For the quantitative analysis, we excluded the current medication subgroup. The nonsense allele was not a significant predictor for systolic or diastolic blood pressure. This is the first report showing that a single polymorphism in SLC6A18 is not associated with hypertension or blood pressure in Japanese.

Adult↗
PubMed2004

Candidate genes for nicotine dependence via linkage, epistasis, and bioinformatics.

Many smoking-related phenotypes are substantially heritable. One genome scan of nicotine dependence (ND) has been published and several others are in progress and should be completed in the next 5 years. The goal of this hypothesis-generating study was two-fold. First, we present further analyses of our genome scan data for ND published by Straub et al. [1999: Mol Psychiatry 4:129-144] (PMID: 10208445). Second, we used the method described by Cox et al. [1999: Nat Genet 21:213-215] (PMID: 9988276) to search for epistatic loci across the markers used in the genome scan. The overall results of the genome scan nearly reached the rigorous Lander and Kruglyak [1995: Nat Genet 11:241-247] criteria for "significant" linkage with the best findings on chromosomes 10 and 2. We then looked for correspondence between genes located in the 10 regions implicated in affected sibling pair (ASP) and epistatic linkage analyses with a list of genes suggested by microarray studies of experimental nicotine exposure and candidate genes from the literature. We found correspondence between linkage and microarray/candidate gene studies for genes involved with the mitogen-activated protein kinase (MAPK) signaling system, nuclear factor kappa B (NFKB) complex, neuropeptide Y (NPY) neurotransmission, a nicotinic receptor subunit (CHRNA2), the vesicular monoamine transporter (SLC18A2), genes in pathways implicated in human anxiety (HTR7, TDO2, and the endozepine-related protein precursor, DKFZP434A2417), and the micro 1-opioid receptor (OPRM1). Although the hypotheses resulting from these linkage and bioinformatic analyses are plausible and intriguing, their ultimate worth depends on replication in additional linkage samples and in future experimental studies.

Chromosome Mapping↗
PubMed2004

Poxvirus bioinformatics.

Biochemical and functional analysis of poxvirus genomes, genes, and proteins has entered a new era with the recent sequencing of more than 30 poxvirus genomes. The management and analysis of this volume of sequence data in an efficient and effective manner requires specialized computer software. This chapter describes a number of bioinformatics techniques useful for analyzing poxvirus genomes. Some of the software discussed here have been developed by members of the Poxvirus Bioinformatics Resource Center (PBRC; funded by National Institutes of Health [NIH]) specifically for use with poxvirus genomes. These programs or, more accurately, suites of programs have many functions dedicated to poxvirus genome characterization. Significantly, this software has been designed with ease of use at a single location as the major goal.

Computational Biology↗
PubMed2005

Bioinformatic approaches to assigning protein function from novel sequence data.

The current pace of functional genomic initiatives and genome sequencing projects has provided researchers with a bewildering array of sequence and biological data to analyze. The disease system-driven approach to identifying key genes frequently identifies nucleotide and protein sequences for which the gene and protein function are not known in sufficient detail to allow informed follow-up. Using a range of bioinformatic tools and sequence-based clues, most of unassigned sequences can now be annotated. This chapter takes as an example an unannotated expressed sequence tag, describing how to identify its related gene, and how to annotate the encoded protein using sequence, profile, and structure-based annotation methodologies.

Computational Biology↗
PubMed2024

Bioinformatics analysis of ferroptosis in frozen shoulder.

OBJECTIVES: Frozen shoulder is a common shoulder disease that significantly affects the patient's life and work. Ferroptosis is a new type of programmed cell death, which is involved in many diseases. However, there have been no studies reporting the relationship between frozen shoulders and ferroptosis. This study identified potential molecular markers of ferroptosis in frozen shoulders to provide more effective strategies for the treatment of frozen shoulders. METHODS: GSE238053 was downloaded from the Gene Expression Omnibus (GEO) dataset and intersected with ferroptosis genes to obtain differentially expressed genes (DEGs). The signaling pathways and biological functions of DEGs were performed by WebGestalt and Metascape. The interactions related to these DEGs and the key genes between frozen shoulders and ferroptosis was performed by STRING and Cytoscape. A frozen shoulders rat model was used to validate our predicted genes, Western Blot and qRT-PCR was used to assess the expression levels of our genes of interest. RESULTS: A total of 34 DEGs between GSE238053 and Ferroptosis Database were obtained, most of which were involved in the HIF-1 signaling pathway and inflammatory response. A protein-protein interaction network was obtained by Cytoscape and the key genes (IL-6, HMOX1 and TLR4) were screened by MCODE. Our results of Western Blot showed that the protein expression level of TLR4 and HMOX1 were elevated, and the protein level of IL-6 decreased in frozen shoulders rat model. The mRNA level after frozen shoulders showed that IL-6 was upregulated, whereas TLR4 and HMOX1were downregulated. CONCLUSIONS: The results demonstrated that ferroptosis may affect the pathological process of frozen shoulders through these signaling pathways and genes. The identification of IL-6, HMOX1 and TLR4 genes can provide new therapeutic targets for frozen shoulders.

Ferroptosis↗
PubMed2025

Evaluating 12 automated, whole-genome sequencing analysis pipelines for Mycobacterium tuberculosis complex: a comparative study.

BACKGROUND: Reliance on complex, custom-built bioinformatics pipelines is a barrier to the implementation of whole-genome sequencing (WGS) of Mycobacterium tuberculosis in high-burden settings in some low-income and middle-income countries (LMICs). Automated analysis pipelines could address this inequity in access to WGS-based diagnostics and surveillance. This study aimed to systematically evaluate the performance and usability of publicly available WGS pipelines for M tuberculosis. METHODS: We identified automated M tuberculosis WGS analysis pipelines through searches of PubMed and GitHub from database inception up to Aug 31, 2024. Accuracy, cost, accessibility, and scalability were assessed for each pipeline. We evaluated the accuracy of genotypic drug susceptibility testing (gDST) using publicly available sequences with phenotypic susceptibility data for 12 antituberculosis drugs. We estimated pooled sensitivity and specificity for each pipeline, across all drugs, by conducting a bivariate meta-analysis, with random effects representing between-drug variability. Lineage classifications were compared, and a previously epidemiologically well-characterised dataset was used to compare measures of genomic relatedness. FINDINGS: Among 28 candidate pipelines, 16 were excluded as they were unmaintained and inexecutable. 12 pipelines (11 compatible with Illumina and four compatible with Nanopore), all free to use, were included for evaluation. Six pipelines processed and stored data remotely, but for five of these six, scalability was limited by the need to upload sequences through web portals. For local processing pipelines, scalability was dependent on substantial local computational resources, data storage capacity, and command-line interfaces that limited user-friendliness. Only one of six remote-processing pipelines removed human DNA sequences before server upload. gDST was similarly accurate across ten of 11 Illumina-compatible pipelines and three of four Nanopore-compatible pipelines. All pipelines classified the main lineages consistently, although there were differences at sublineage resolution. Outputs from three of four pipelines reporting genomic relatedness were compatible with commonly cited single nucleotide polymorphism difference thresholds. INTERPRETATION: Numerous automated analysis pipelines capable of enhancing equity in M tuberculosis WGS are available. Given the overall similarities between the pipelines evaluated in this study in terms of gDST performance, lineage classification, and genomic relatedness inference, non-functional attributes such as availability, accessibility, scalability, and privacy could represent the point of difference for prospective users in LMICs with a high burden of tuberculosis. FUNDING: The Rhodes Trust, Wellcome, Ellison Institute of Technology, and the UK National Institute for Health and Care Research Oxford Biomedical Research Centre.

Mycobacterium tuberculosis↗
PubMed2004

Deciphering regulatory patterns of inflammatory gene expression from interleukin-1-stimulated human endothelial cells.

OBJECTIVE: Endothelial cells comprise a key component of the inflammatory response. We set out to obtain a comprehensive overview of the immediate-early to early gene expression program of interleukin-1 (IL-1)-stimulated endothelial cells and to identify novel transcription factors and regulatory elements. METHODS AND RESULTS: Human umbilical vein endothelial cells (HUVECs) were stimulated with IL-1 for 0, 0.5, 1, 2.5, and 6 hours and analyzed using Affymetrix U133 microarrays. A total of 137 genes were found to be regulated >4-fold, including 18 transcription factors. The expression of selected genes was confirmed by real-time polymerase chain reaction. Cluster analysis was performed in order to group genes according to their expression profiles. To identify novel transcription factor-binding sites, the corresponding promoters were extracted from databases and analyzed for regulatory elements that were over-represented in specific clusters. Several potentially novel DNA binding sites were identified, and one was shown to specifically bind an IL-1-inducible protein from HUVEC. CONCLUSIONS: These results demonstrate that in the early phase after stimulation, IL-1 evokes a complex gene expression program that includes positive but also negative (feedback) regulators of diverse endothelial cell functions. Furthermore, the identification of a new promoter regulatory element demonstrates the feasibility of the bioinformatics-driven approach to discover novel regulatory mechanisms.

Binding Sites↗
PubMed2005

Correlation-associated peptide networks of human cerebrospinal fluid.

Profiling of peptides and small proteins from either human body fluids or tissues by chromatography and subsequent mass spectrometry reveals several thousand individual peptide signals per sample. Any peptide is an intermediate in the course of biosynthesis, post-translational modification (PTM), proteolytic processing and degradation. Changes in the concentration of one peptide often affects the concentration of the other, hence a challenge consists in the development of suitable tools to turn this large amount of data into biologically relevant information. Comprehensive statistical analysis of the peptide profiling data allows associating peptides, which are closely related in terms of peptide biochemistry. Here, the bioinformatic concept of peptide networks, correlation-associated peptide networks (CANs), is introduced. Peptides with statistical similarity of their concentrations are grouped in form of networks, and these networks are interpreted in terms of peptide biochemistry. The spectrum of functional relationships found in cerebrospinal fluid CAN covers PTM and proteolytic degradation of peptides, clearance processing in the complement cascade, common secretion of peptides by neuroendocrine cells as well as ubiquitin-mediated degradation. Our results indicate that CAN is a powerful bioinformatic tool for the systematic analysis and interpretation of large peptidomics and proteomics data and helps to discover novel bioactive and diagnostic peptides.

Chemical Fractionation↗
PubMed2000

Investigating the genetic control of stem cell behavior.

The precise control of hematopoietic stem cell fate decisions involves molecules that are differentially expressed in the stem cell versus its non-stem progeny. The construction of representative and high quality cDNA libraries containing stem cell-specific sequences is a first step in elucidating stem cell control mechanisms. Automated bioinformatics in conjunction with high-throughput random sequencing and high-density parallel array hybridization studies make it possible to dissect stem cell molecular pathways and networks. It is the differential analysis of these interacting pathways which will provide the greatest insights into the biological differences underlying stem cell behavior.

Computational Biology↗
PubMed2025

Expression and prognosis of CXCL13 in uterine corpus endometrial carcinoma based on bioinformatics analysis.

OBJECTIVE: The biological significance of the chemokine ligand C-X-C motif chemokine ligand 13 (CXCL13) may play a significant role in the pathogenesis of uterine corpus endometrial carcinoma (UCEC). This study aims to identify and verify CXCL13 with predictive value for prognosis in UCEC. METHODS: CXCL13 mRNA expression differences were analyzed using R software in three independent datasets: one each from The Cancer Genome Atlas (TCGA) and two from the Gene Expression Omnibus (GEO), namely GSE17025 and GSE106191. The correlation between CXCL13 expression and prognosis was evaluated by Kaplan-Meier analysis. Univariate and multivariate Cox analyses were utilized to construct a prognostic nomogram. Tumor Immune Estimation Resource (TIMER) and the Tumor and Immune System Interaction Database (TISIDB) were employed to assess the relationship between CXCL13 and tumor immune infiltration. Coexpressed genes with CXCL13 were identified by the Spearman correlation analysis. A CXCL13 protein-protein interaction (PPI) network was constructed with the STRING website tool and hub genes were screened out. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genome (KEGG) analyses were performed with the "clusterProfiler" R package. Gene set enrichment analysis (GSEA) was used to identify underlying biological mechanisms. A drug-gene interaction network was constructed in the Comparative Toxicogenomics Database (CTD). RESULTS: High CXCL13 mRNA expression were validated in UCEC in the above three independent datasets. High CXCL13 expression was associated with favorable prognosis in UCEC. A nomogram for predicting the 1-, 3-, and 5-year survival probability in UCEC was construct based on CXCL13 expression and other clinical parameters. The use of Spearman correlation indicated certain correlation between CXCL13 and immune cells and immune checkpoint (ICP) genes. Seven hub genes were upregulated in UCEC, namely CXCL9, IFNG, CXCL10, CXCL11, GBP5, CCL18, and GZMB. The expression and prognostic relevance of CXCL9, IFNG, GBP5, and GZMB were in accordance with CXCL13. The main biological processes enriched were cytokine-cytokine receptor interaction and chemokine signaling pathway. CONCLUSIONS: The above comprehensive analyses suggest that CXCL13 may serve as a potential prognostic biomarker for UCEC, specifically for early-stage UCEC.

CXCL13↗
PubMed2004

Tutorial section: domains and motifs - proteins in bite-sized chunks.

Possibly the ultimate goal of bioinformatics is to be able to predict protein tertiary structure and chemical functionality from the initial amino acid sequence. Despite the best efforts of many researchers over the past two decades, a reliable modelling method has yet to be found and the folding problem continues to be a hurdle for scientists.

Amino Acid Motifs↗
PubMed2000

Systematic subcellular localization of novel proteins identified by large-scale cDNA sequencing.

As a first step towards a more comprehensive functional characterization of cDNAs than bioinformatic analysis, which can only make functional predictions for about half of the cDNAs sequenced, we have developed and tested a strategy that allows their systematic and fast subcellular localization. We have used a novel cloning technology to rapidly generate N- and C-terminal green fluorescent protein fusions of cDNAs to examine the intracellular localizations of > 100 expressed fusion proteins in living cells. The entire analysis is suitable for automation, which will be important for scaling up throughput. For > 80% of these new proteins a clear intracellular localization to known structures or organelles could be determined. For the cDNAs where bioinformatic analyses were able to predict possible identities, the localization was able to support these predictions in 75% of cases. For those cDNAs where no homologies could be predicted, the localization data represent the first information.

Animals↗
PubMed2003

Molecular phylogeny of the kelch-repeat superfamily reveals an expansion of BTB/kelch proteins in animals.

BACKGROUND: The kelch motif is an ancient and evolutionarily-widespread sequence motif of 44-56 amino acids in length. It occurs as five to seven repeats that form a beta-propeller tertiary structure. Over 28 kelch-repeat proteins have been sequenced and functionally characterised from diverse organisms spanning from viruses, plants and fungi to mammals and it is evident from expressed sequence tag, domain and genome databases that many additional hypothetical proteins contain kelch-repeats. In general, kelch-repeat beta-propellers are involved in protein-protein interactions, however the modest sequence identity between kelch motifs, the diversity of domain architectures, and the partial information on this protein family in any single species, all present difficulties to developing a coherent view of the kelch-repeat domain and the kelch-repeat protein superfamily. To understand the complexity of this superfamily of proteins, we have analysed by bioinformatics the complement of kelch-repeat proteins encoded in the human genome and have made comparisons to the kelch-repeat proteins encoded in other sequenced genomes. RESULTS: We identified 71 kelch-repeat proteins encoded in the human genome, whereas 5 or 8 members were identified in yeasts and around 18 in C. elegans, D. melanogaster and A. gambiae. Multiple domain architectures were identified in each organism, including previously unrecognised forms. The vast majority of kelch-repeat domains are predicted to form six-bladed beta-propellers. The most prevalent domain architecture in the metazoan animal genomes studied was the BTB/kelch domain organisation and we uncovered 3 subgroups of human BTB/kelch proteins. Sequence analysis of the kelch-repeat domains of the most robustly-related subgroups identified differences in beta-propeller organisation that could provide direction for experimental study of protein-binding characteristics. CONCLUSION: The kelch-repeat superfamily constitutes a distinct and evolutionarily-widespread family of beta-propeller domain-containing proteins. Expansion of the family during the evolution of multicellular animals is mainly accounted for by a major expansion of the BTB/kelch domain architecture. BTB/kelch proteins constitute 72 % of the kelch-repeat superfamily of H. sapiens and form three subgroups, one of which appears the most-conserved during evolution. Distinctions in propeller blade organisation between subgroups 1 and 2 were identified that could provide new direction for biochemical and functional studies of novel kelch-repeat proteins.

Amino Acid Motifs↗