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Targeted covalent inactivation of protein kinases by resorcylic acid lactone polyketides.

Resorcylic acid lactones containing a cis-enone are susceptible to Michael addition reactions and are potent inhibitors of several protein kinases. A structural-bioinformatics analysis identified a conserved Cys residue in the ATP-binding site of the kinases reported to be inhibited by cis-enone resorcylic acid lactones but absent in those that are not. Mining of the kinome database revealed that a subset of some 46 kinases contained this Cys residue. Screening a panel of 124 kinases with the resorcylic acid lactone hypothemycin showed that 18 of 19 targets containing the conserved Cys were inhibited. Kinetic analyses showed time-dependent inhibition, a hallmark of covalent inactivation, and biochemical studies of the interaction of extracellular signal-regulated kinase (ERK)2 with hypothemycin confirmed covalent adduct formation. Resorcylic acid lactones are unique among kinase inhibitors in that they target mitogen-activated protein (MAP) kinase pathways at four levels: mitogen receptors, MAP kinase kinase (MEK)1/2 and ERK1/2, and certain downstream ERK substrates. Cell lines dependent on the activation of Tyr kinase mitogen receptor targets of the resorcylic acid lactones were unusually sensitive toward hypothemycin and showed the expected inhibition of kinase phosphorylation due to inhibition of the mitogen receptors and/or MEK1/2 and ERK1/2. Among cells without mitogen receptor targets, those harboring an ERK pathway-activating B-RAF V600E mutation were selectively and potently inhibited by hypothemycin. Hypothemycin also prevented stimulated activation of the p38 cascade through inhibition of the Cys-containing targets MEK3/6 and TGF-beta-activated kinase 1 and of the JNK/SAPK (c-Jun N-terminal kinase/stress-activated protein kinase) cascade through inhibition of MEK4/7.

Adenosine Triphosphate↗

CpG Island microarray probe sequences derived from a physical library are representative of CpG Islands annotated on the human genome.

An effective tool for the global analysis of both DNA methylation status and protein-chromatin interactions is a microarray constructed with sequences containing regulatory elements. One type of array suited for this purpose takes advantage of the strong association between CpG Islands (CGIs) and gene regulatory regions. We have obtained 20,736 clones from a CGI Library and used these to construct CGI arrays. The utility of this library requires proper annotation and assessment of the clones, including CpG content, genomic origin and proximity to neighboring genes. Alignment of clone sequences to the human genome (UCSC hg17) identified 9595 distinct genomic loci; 64% were defined by a single clone while the remaining 36% were represented by multiple, redundant clones. Approximately 68% of the loci were located near a transcription start site. The distribution of these loci covered all 23 chromosomes, with 63% overlapping a bioinformatically identified CGI. The high representation of genomic CGI in this rich collection of clones supports the utilization of microarrays produced with this library for the study of global epigenetic mechanisms and protein-chromatin interactions. A browsable database is available on-line to facilitate exploration of the CGIs in this library and their association with annotated genes or promoter elements.

Base Sequence↗

An analysis of the Sargasso Sea resource and the consequences for database composition.

BACKGROUND: The environmental sequencing of the Sargasso Sea has introduced a huge new resource of genomic information. Unlike the protein sequences held in the current searchable databases, the Sargasso Sea sequences originate from a single marine environment and have been sequenced from species that are not easily obtainable by laboratory cultivation. The resource also contains very many fragments of whole protein sequences, a side effect of the shotgun sequencing method.These sequences form a significant addendum to the current searchable databases but also present us with some intrinsic difficulties. While it is important to know whether it is possible to assign function to these sequences with the current methods and whether they will increase our capacity to explore sequence space, it is also interesting to know how current bioinformatics techniques will deal with the new sequences in the resource. RESULTS: The Sargasso Sea sequences seem to introduce a bias that decreases the potential of current methods to propose structure and function for new proteins. In particular the high proportion of sequence fragments in the resource seems to result in poor quality multiple alignments. CONCLUSION: These observations suggest that the new sequences should be used with care, especially if the information is to be used in large scale analyses. On a positive note, the results may just spark improvements in computational and experimental methods to take into account the fragments generated by environmental sequencing techniques.

Amino Acid Sequence↗

The bioinformatics approach to identifying pathogenic variants for colorectal cancer (CRC).

Colorectal cancer (CRC) is the third most prevalent cancer globally, accounting for 9.6% of newly diagnosed cases and 9.3% of cancer-related deaths. It develops from the uncontrolled proliferation of glandular cells in the colon and rectum and is categorized into three primary types: sporadic, hereditary, and colitis-associated. While genetic susceptibility is a key factor in CRC pathogenesis, identifying high-impact pathogenic variants remains a significant challenge. This study integrates bioinformatics and population genetics approaches to identify CRC-associated single-nucleotide polymorphisms (SNPs) with potential clinical significance. CRC-associated SNPs were extracted from the Genome-Wide Association Studies (GWAS) Catalog, functionally annotated via HaploReg, and validated via Ensembl. In addition, expression quantitative trait locus (eQTL) data from the GTEx database were used to assess the effects of these variants on gene expression across human tissues. Our analysis identified three high-priority SNPs (rs9379084, rs3184504, and rs11557154) associated with the RREB1, ATXN2, SH2B3, and DCAF12 genes, which exhibited marked allele frequency differences among populations. These findings suggest potential biomarkers for CRC risk assessment and highlight the importance of genetic screening across diverse populations.

Bioinformatics↗

Application of genomics and proteomics for identification of bacterial gene products as potential vaccine candidates.

The ability of bioinformatics to characterize genomic sequences from pathogenic bacteria for prediction of genes that may encode vaccine candidates, e.g. surface localized proteins, has been evaluated. By applying appropriate tools for genomic mining to the published sequence of Haemophilus influenzae Rd genome, it was possible to identify a putative vaccine candidate, the outer membrane lipoprotein, P6. Proteomics complements genomics by offering abilities to rapidly identify the products of predicted genes, e.g. proteins in outer membrane preparations. The ability to identify the P6 protein uniquely from entries in a sequence database from the expected peptide-mass fingerprint of P6 demonstrates the power of proteomics. The application of proteomics for identification of vaccine candidates for another pathogenic bacterium, Helicobacter pylori using two different approaches is described. The first involves rapid identification of a series of monoclonal antibody reactive proteins from N-terminal sequence tags. The other approach involves identification of proteins in outer membrane preparations by 2-D electrophoresis followed by trypsin digestion and peptide mass map analysis. Our combined studies demonstrate that utilization of genome sequences by application of bioinformatics through genomics and proteomics can expedite the vaccine discovery process by rapidly providing a set of potential candidates for further testing.

Antibodies, Bacterial↗

Online analysis of development.

The genomics revolution has altered the very nature of research in molecular biology, from how to find genes to how to find out what specific genes do. Given the availability of so many fully (or nearly) sequenced genomes, it is now relatively easy to track down dozens or even hundreds of genes relevant to a particular field of study. Unfortunately, up till now, the tools for determining what these genes actually do in embryos and cells have not kept pace, but the burgeoning field of bioinformatics should help correct this shortcoming and introduce the power of genomics to the study of developmental biology. In this review, some of the bioinformatics resources relevant to developmental biologists are described along with some simple approaches for applying these tools to analyzing early development.

Anatomy↗

PF-IND: probability algorithm and software for separation of plant and fungal sequences.

The separation of plant and fungal sequences in EST pools by bioinformatic methods is difficult because of sequence similarities between plants and fungi, lack of enough sequence information, and the short length of the isolated fragments. An algorithm and software that utilize the differences in codon usage bias to discriminate between plant and fungal sequences are described. The software (PF-IND) includes five pairs of fungi and their host plants that can be used to analyze a large number of related species. Analysis of a sequence provides an arbitrary value that defines the likelihood that a sequence will be a fungal or a plant gene. The software can distinguish between homologous fungal and plant genes and it helps identify the correct reading frame of unknown expressed sequence tags (ESTs) for which BLAST analyses do not provide clear information. Short sequences of 100-150 bp can be analyzed with high confidence. PF-IND analysis of 100 sequences derived from fungal infected plants identified the origin of 94 sequences. Only 66 sequences were identified by a BLASTX analysis of the same 100 ESTs. Overall, PF-IND is a novel bioinformatic tool aimed at assisting the research of fungus-plant interactions.

Algorithms↗

Novel splice site variants in GBA1 are associated with Gaucher disease and genotype-phenotype correlations.

BACKGROUND: Variants in GBA1 are associated with neurodegenerative disease. This study aimed to explore pathogenic GBA1 variants. METHODS: Four patients with progressive myoclonic epilepsy (PME) and extremely low β-glucosidase levels were recruited. Whole-exome sequencing and long-range PCR were performed to identify GBA1 variants. Bioinformatic analyses were used to predict the impact of the identified variants. A literature review was performed to explore the genotype-phenotype correlations. GBA1 expression data across different brain regions and developmental stages were analyzed using the BrainSpan database. RT-PCR was performed to verify the splicing effects. RESULTS: Compound heterozygous GBA1 variants were identified in four patients. Five distinct variants were detected, including two novel splice site variants (c.308-2A>G and c.762-2A>C) and three previously reported variants. All identified variants were rare or absent in gnomAD. Splice site variants c.308-2A>G and c.762-2A>C were predicted to cause aberrant splicing. Minigene-based splicing assays coupled with RT-PCR and Sanger sequencing confirmed that both variants cause complete exon skipping (exon 4 and exon 7, respectively). All patients presented with PME onset in childhood/adolescence, intellectual regression, low β-glucosidase, and diffuse brain atrophy and were subsequently diagnosed with Gaucher disease type 3. GBA1 expression in the brain showed two distinct peaks: one in infancy and another after five years of age. The onset age of PME aligned with the second GBA1 expression peak (after five years of age). CONCLUSION: This study identified compound heterozygous GBA1 variants, including two novel candidate pathogenic splice site variants, in Gaucher disease type 3 patients, expanding the known mutational spectrum.

Humans↗

Comprehensive post-genomic data analysis approaches integrating biochemical pathway maps.

Post-genomic era research is focusing on studies to attribute functions to genes and their encoded proteins, and to describe the regulatory networks controlling metabolic, protein synthesis and signal transduction pathways. To facilitate the analysis of experiments using post-genomic technologies, new concepts for linking the vast amount of raw data to a biological context have to be developed. Visual representations of pathways help biologists to understand the complex relationships between components of metabolic networks, and provide an invaluable resource for the integration of transcriptomics, proteomics and metabolomics data sets. Besides providing an overview of currently available bioinformatic tools for plant scientists, we introduce BioPathAt, a newly developed visual interface that allows the knowledge-based analysis of genome-scale data by integrating biochemical pathway maps (BioPathAtMAPS module) with a manually scrutinized gene-function database (BioPathAtDB) for the model plant Arabidopsis thaliana. In addition, we discuss approaches for generating a biochemical pathway knowledge database for A. thaliana that includes, in addition to accurate annotation, condensed experimental information regarding in vitro and in vivo gene/protein function.

Computational Biology↗

Computational systems analysis of developmental toxicity: design, development and implementation of a Birth Defects Systems Manager (BDSM).

Birth defects and developmental disabilities remain an important public health issue worldwide. With the availability of genomic sequences from a growing number of human and model organisms and the rapid expansion of the public repositories holding large-scale gene expression datasets, a computational systems analysis of developmental toxicology can incorporate this vast digital information toward the realization of predictive models for complex disease. Here we describe the initial design, development and implementation of a Birth Defects Systems Manager (BDSM). The project was motivated by the need for a computational-bioinformatics infrastructure to manage vast digital information from functional genomics and for a new knowledge environment specifically engineered for the analysis of developmental processes and toxicities. Proof-of-concept tested BDSM using meta-analysis of gene expression data collected from different laboratories, technology platforms, and study models. The composite dataset incorporated 232 microarray comparisons of RNA samples by single or dual microarray platforms, cDNA or oligonucleotide based probes, and human or mouse sequence information. Preliminary results identified system-level features in the embryonic transcriptome as it reacted to various developmental-teratological stimuli. BDSM is open access through the worldwide web (http://systemsanalysis.louisville.edu/) and can be integrated with other bioinformatics tools and resources to advance the pace of discovery in birth defects research.

Animals↗

Mass spectrometric analysis of N- and O-glycosylation of tissues and cells.

Mass spectrometry has been at the forefront of glycobiological analysis for more than two decades. Recent advances in technology, coupled with increased global appreciation of the importance of the glycome in solving biological problems, have laid the foundations for an unprecedented increase in output. Under the auspices of major international consortia, significant progress is being made towards the development of integrated databases of specific cell and tissue N- and O-glycan profiles. Tools for the automation of both sample handling and data analysis are enabling a more concerted approach to glycan structural analysis. When combined with complementary transcriptomics and bioinformatics analyses, these tools will facilitate a new systems glycobiology approach to research.

Animals↗

Computation of recurrent minimal genomic alterations from array-CGH data.

MOTIVATION: The identification of recurrent genomic alterations can provide insight into the initiation and progression of genetic diseases, such as cancer. Array-CGH can identify chromosomal regions that have been gained or lost, with a resolution of approximately 1 mb, for the cutting-edge techniques. The extraction of discrete profiles from raw array-CGH data has been studied extensively, but subsequent steps in the analysis require flexible, efficient algorithms, particularly if the number of available profiles exceeds a few tens or the number of array probes exceeds a few thousands. RESULTS: We propose two algorithms for computing minimal and minimal constrained regions of gain and loss from discretized CGH profiles. The second of these algorithms can handle additional constraints describing relevant regions of copy number change. We have validated these algorithms on two public array-CGH datasets. AVAILABILITY: From the authors, upon request. CONTACT: celine@lri.fr SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Algorithms↗

RNA structure comparison, motif search and discovery using a reduced representation of RNA conformational space.

Given the wealth of new RNA structures and the growing list of RNA functions in biology, it is of great interest to understand the repertoire of RNA folding motifs. The ability to identify new and known motifs within novel RNA structures, to compare tertiary structures with one another and to quantify the characteristics of a given RNA motif are major goals in the field of RNA research; however, there are few systematic ways to address these issues. Using a novel approach for visualizing and mathematically describing macromolecular structures, we have developed a means to quantitatively describe RNA molecules in order to rapidly analyze, compare and explore their features. This approach builds on the alternative eta,theta convention for describing RNA torsion angles and is executed using a new program called PRIMOS. Applying this methodology, we have successfully identified major regions of conformational change in the 50S and 30S ribosomal subunits, we have developed a means to search the database of RNA structures for the prevalence of known motifs and we have classified and identified new motifs. These applications illustrate the powerful capabilities of our new RNA structural convention, and they suggest future adaptations with important implications for bioinformatics and structural genomics.

Algorithms↗

The genetic program of hematopoietic stem cells.

Blood cell production originates from a rare population of multipotent, self-renewing stem cells. A genome-wide gene expression analysis was performed in order to define regulatory pathways in stem cells as well as their global genetic program. Subtracted complementary DNA libraries from highly purified murine fetal liver stem cells were analyzed with bioinformatic and array hybridization strategies. A large percentage of the several thousand gene products that have been characterized correspond to previously undescribed molecules with properties suggestive of regulatory functions. The complete data, available in a biological process-oriented database, represent the molecular phenotype of the hematopoietic stem cell.

Amino Acid Sequence↗

Study on the phylogenetic tree of human platelet glycoproteins.

Platelet glycoprotein is an important group of glycoproteins on platelets. Several types of platelet glycoproteins have been studied for their functions in the hemostasis system. A bioinformatic analysis was performed to find out how the platelet glycoproteins' genes are related to each other. A multiple sequence alignment phylogenetic tree was performed to present the family tree of the human platelet glycoproteins recorded in the genomic database, ExPASY. These derived sequences from the database were processed by ClustalW and subsequently used for preparation of the distance matrix by Phylip protdist. The final generated phylogenetic tree of human platelet glycoproteins was presented and discussed.

Blood Platelets↗

PhyloNaP: a user-friendly database of phylogeny for natural product-producing enzymes.

SUMMARY: Phylogenetic analysis is widely used to predict enzyme function, yet building annotated and reusable trees is labor-intensive and requires extensive knowledge about the specific enzymes. Existing resources rarely cover biosynthetic enzymes and lack the context needed for meaningful analysis. We present PhyloNaP, the first large-scale resource dedicated to phylogenies of biosynthetic enzymes. PhyloNaP provides ∼51 000 annotated and interactive trees enriched with chemical, functional, and taxonomic information. Users can classify their own sequences via phylogenetic placement, enabling functional inference in an evolutionary context. A contribution portal allows the community to submit curated trees. By combining scale, breadth of annotation, and interactive functionality, PhyloNaP fills a major gap in bioinformatics resources for enzyme discovery and annotation, with immediate applications to secondary metabolism and beyond. AVAILABILITY AND IMPLEMENTATION: Freely available on the web at https://phylonap.cs.uni-tuebingen.de.

Phylogeny↗

MitoRes: a resource of nuclear-encoded mitochondrial genes and their products in Metazoa.

BACKGROUND: Mitochondria are sub-cellular organelles that have a central role in energy production and in other metabolic pathways of all eukaryotic respiring cells. In the last few years, with more and more genomes being sequenced, a huge amount of data has been generated providing an unprecedented opportunity to use the comparative analysis approach in studies of evolution and functional genomics with the aim of shedding light on molecular mechanisms regulating mitochondrial biogenesis and metabolism. In this context, the problem of the optimal extraction of representative datasets of genomic and proteomic data assumes a crucial importance. Specialised resources for nuclear-encoded mitochondria-related proteins already exist; however, no mitochondrial database is currently available with the same features of MitoRes, which is an update of the MitoNuc database extensively modified in its structure, data sources and graphical interface. It contains data on nuclear-encoded mitochondria-related products for any metazoan species for which this type of data is available and also provides comprehensive sequence datasets (gene, transcript and protein) as well as useful tools for their extraction and export. DESCRIPTION: MitoRes http://www2.ba.itb.cnr.it/MitoRes/ consolidates information from publicly external sources and automatically annotates them into a relational database. Additionally, it also clusters proteins on the basis of their sequence similarity and interconnects them with genomic data. The search engine and sequence management tools allow the query/retrieval of the database content and the extraction and export of sequences (gene, transcript, protein) and related sub-sequences (intron, exon, UTR, CDS, signal peptide and gene flanking regions) ready to be used for in silico analysis. CONCLUSION: The tool we describe here has been developed to support lab scientists and bioinformaticians alike in the characterization of molecular features and evolution of mitochondrial targeting sequences. The way it provides for the retrieval and extraction of sequences allows the user to overcome the obstacles encountered in the integrative use of different bioinformatic resources and the completeness of the sequence collection allows intra- and interspecies comparison at different biological levels (gene, transcript and protein).

Animals↗