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PubMed2005

APOBEC4, a new member of the AID/APOBEC family of polynucleotide (deoxy)cytidine deaminases predicted by computational analysis.

Using iterative database searches, we identified a new subfamily of the AID/APOBEC family of RNA/DNA editing cytidine deaminases. The new subfamily, which is represented by readily identifiable orthologs in mammals, chicken, and frog, but not fishes, was designated APOBEC4. The zinc-coordinating motifs involved in catalysis and the secondary structure of the APOBEC4 deaminase domain are evolutionarily conserved, suggesting that APOBEC4 proteins are active polynucleotide (deoxy)cytidine deaminases. In reconstructed maximum likelihood phylogenetic trees, APOBEC4 forms a distinct clade with a high statistical support. APOBEC4 and APOBEC1 are joined in a moderately supported cluster clearly separated from AID, APOBEC2 and APOBEC3 subfamilies. In mammals, APOBEC4 is expressed primarily in testis which suggests the possibility that it is an editing enzyme for mRNAs involved in spermatogenesis.

APOBEC Deaminases↗

PubMed2002

In silico approaches to mechanistic and predictive toxicology: an introduction to bioinformatics for toxicologists.

Bioinformatics, or in silico biology, is a rapidly growing field that encompasses the theory and application of computational approaches to model, predict, and explain biological function at the molecular level. This information rich field requires new skills and new understanding of genome-scale studies in order to take advantage of the rapidly increasing amount of sequence, expression, and structure information in public and private databases. Toxicologists are poised to take advantage of the large public databases in an effort to decipher the molecular basis of toxicity. With the advent of high-throughput sequencing and computational methodologies, expressed sequences can be rapidly detected and quantitated in target tissues by database searching. Novel genes can also be isolated in silico, while their function can be predicted and characterized by virtue of sequence homology to other known proteins. Genomic DNA sequence data can be exploited to predict target genes and their modes of regulation, as well as identify susceptible genotypes based on single nucleotide polymorphism data. In addition, highly parallel gene expression profiling technologies will allow toxicologists to mine large databases of gene expression data to discover molecular biomarkers and other diagnostic and prognostic genes or expression profiles. This review serves to introduce to toxicologists the concepts of in silico biology most relevant to mechanistic and predictive toxicology, while highlighting the applicability of in silico methods using select examples.

Cluster Analysis↗

PubMed2000

A case for evolutionary genomics and the comprehensive examination of sequence biodiversity.

Comparative analysis is one of the most powerful methods available for understanding the diverse and complex systems found in biology, but it is often limited by a lack of comprehensive taxonomic sampling. Despite the recent development of powerful genome technologies capable of producing sequence data in large quantities (witness the recently completed first draft of the human genome), there has been relatively little change in how evolutionary studies are conducted. The application of genomic methods to evolutionary biology is a challenge, in part because gene segments from different organisms are manipulated separately, requiring individual purification, cloning, and sequencing. We suggest that a feasible approach to collecting genome-scale data sets for evolutionary biology (i.e., evolutionary genomics) may consist of combination of DNA samples prior to cloning and sequencing, followed by computational reconstruction of the original sequences. This approach will allow the full benefit of automated protocols developed by genome projects to be realized; taxon sampling levels can easily increase to thousands for targeted genomes and genomic regions. Sequence diversity at this level will dramatically improve the quality and accuracy of phylogenetic inference, as well as the accuracy and resolution of comparative evolutionary studies. In particular, it will be possible to make accurate estimates of normal evolution in the context of constant structural and functional constraints (i.e., site-specific substitution probabilities), along with accurate estimates of changes in evolutionary patterns, including pairwise coevolution between sites, adaptive bursts, and changes in selective constraints. These estimates can then be used to understand and predict the effects of protein structure and function on sequence evolution and to predict unknown details of protein structure, function, and functional divergence. In order to demonstrate the practicality of these ideas and the potential benefit for functional genomic analysis, we describe a pilot project we are conducting to simultaneously sequence large numbers of vertebrate mitochondrial genomes.

Animals↗

PubMed1986

Purification and characterization of human interleukin-1 beta expressed in recombinant Escherichia coli.

The high-level expression of human interleukin-1 beta in Escherichia coli is described. The protein contributes about 12% of the total cell protein and is associated with the soluble cytoplasmic fraction of the cell. A method for the purification of the protein is given which is based on anion- and cation-exchange chromatographies. The isolated protein, shown to be homogeneous by several analytical methods, has been characterized by amino acid analysis, N- and C-terminal sequence analysis and analytical centrifugation. The protein is biologically active as demonstrated by two different in vitro assays, namely, the mononuclear cell factor (IL-1/MCF) assay and lymphocyte activating factor (IL-1/LAF) assay. The specific activities determined with the IL-1/MCF and IL-1/LAF assays, are 2 X 10(7) and 4 X 10(7) units mg-1, respectively.

Amino Acid Sequence↗

PubMed2003

A complexity reduction algorithm for analysis and annotation of large genomic sequences.

DNA is a universal language encrypted with biological instruction for life. In higher organisms, the genetic information is preserved predominantly in an organized exon/intron structure. When a gene is expressed, the exons are spliced together to form the transcript for protein synthesis. We have developed a complexity reduction algorithm for sequence analysis (CRASA) that enables direct alignment of cDNA sequences to the genome. This method features a progressive data structure in hierarchical orders to facilitate a fast and efficient search mechanism. CRASA implementation was tested with already annotated genomic sequences in two benchmark data sets and compared with 15 annotation programs (10 ab initio and 5 homology-based approaches) against the EST database. By the use of layered noise filters, the complexity of CRASA-matched data was reduced exponentially. The results from the benchmark tests showed that CRASA annotation excelled in both the sensitivity and specificity categories. When CRASA was applied to the analysis of human Chromosomes 21 and 22, an additional 83 potential genes were identified. With its large-scale processing capability, CRASA can be used as a robust tool for genome annotation with high accuracy by matching the EST sequences precisely to the genomic sequences.

Algorithms↗

PubMed2005

Profile-based direct kernels for remote homology detection and fold recognition.

MOTIVATION: Protein remote homology detection is a central problem in computational biology. Supervised learning algorithms based on support vector machines are currently one of the most effective methods for remote homology detection. The performance of these methods depends on how the protein sequences are modeled and on the method used to compute the kernel function between them. RESULTS: We introduce two classes of kernel functions that are constructed by combining sequence profiles with new and existing approaches for determining the similarity between pairs of protein sequences. These kernels are constructed directly from these explicit protein similarity measures and employ effective profile-to-profile scoring schemes for measuring the similarity between pairs of proteins. Experiments with remote homology detection and fold recognition problems show that these kernels are capable of producing results that are substantially better than those produced by all of the existing state-of-the-art SVM-based methods. In addition, the experiments show that these kernels, even when used in the absence of profiles, produce results that are better than those produced by existing non-profile-based schemes. AVAILABILITY: The programs for computing the various kernel functions are available on request from the authors.

Algorithms↗

PubMed2006

Alterations in immunological and neurological gene expression patterns in Alzheimer's disease tissues.

Microarray technology was utilized to isolate disease-specific changes in gene expression by sampling across inferior parietal lobes of patients suffering from late onset AD or non-AD-associated dementia and non-demented controls. Primary focus was placed on understanding how inflammation plays a role in AD pathogenesis. Gene ontology analysis revealed that the most differentially expressed genes related to nervous system development and function and neurological disease followed by genes involved in inflammation and immunological signaling. Pathway analysis also implicated a role for chemokines and their receptors, specifically CXCR4 and CCR3, in AD. Immunohistological analysis revealed that these chemokine receptors are upregulated in AD patients. Western analysis demonstrated an increased activation of PKC, a downstream mediator of chemokine receptor signaling, in the majority of AD patients. A very specific cohort of genes related to amyloid beta accumulation and clearance were found to be significantly altered in AD. The most significantly downregulated gene in this data set was the endothelin converting enzyme 2 (ECE2), implicated in amyloid beta clearance. These data were subsequently confirmed by real-time PCR and Western blot analysis. Together, these findings open up new avenues of investigation and possible therapeutic strategies targeting inflammation and amyloid clearance in AD patients.

Aged↗

PubMed2001

Applications of yeast in drug discovery.

The yeast Saccharomyces cerevisiae is perhaps the best-studied eukaryotic organism. Its experimental tractability, combined with the remarkable conservation of gene function throughout evolution, makes yeast the ideal model genetic organism. Yeast is a non-pathogenic model of fungal pathogens used to identify antifungal targets suitable for drug development and to elucidate mechanisms of action of antifungal agents. As a model of fundamental cellular processes and metabolic pathways of the human, yeast has improved our understanding and facilitated the molecular analysis of many disease genes. The completion of the Saccharomyces genome sequence helped launch the post-genomic era, focusing on functional analyses of whole genomes. Yeast paved the way for the systematic analysis of large and complex genomes by serving as a test bed for novel experimental approaches and technologies, tools that are fast becoming the standard in drug discovery research

Antifungal Agents↗

PubMed2006

[Isolation and characterization of a new Pseudomonas strain against Phytophthora capsici].

One Pseudomonas strain GP72, which was against Phytophthora capsici, was isolated from green pepper rhizosphere in Jiangsu province. It had distinctively inhibitive effect on several kinds of pathogenic fungi; mostly of them are soilborne pathogens. Therefore, this strain may be used for an effective biocontrol strain in the crop protection. The morphological, biochemical and physiological characteristics, Biolog GN, G + C mol% content and 16S rDNA sequence analysis of this strain were studied. In comparison and conclusion of all the experimental data, GP72 is identified as Pseudomonas chlororaphis. The strain is single-cellular and motile by means of single polar flagellum. It was not able to accumulate ploy-beta-hydroxybutyrate. Compared to P. aureofaciens 30-84, the strain was able to survive at the concentration of 5% NaCl. It could strongly utilize 45 of 95 carbon-substrates; weakly utilize 6 of the whole carbon-substrates and never utilize 43 of the whole carbon-substrates resulting from analysis of Biolog GN, bearing the similarity probability of 98% with Pseudomonas chlororaphis and with the similarity index 0.72. The G + C content of the strain DNA was 65.1 mol% using the thermal denaturation method. A phylogenetic tree was constructed by comparing with the validly published 16S rDNA sequences of the related type strains from GenBank, using the Neighbor-Joining method of Saitou and Nei and the Clustal X program to do the multiple alignments. The tree topology was tested by a bootstrap analysis of 1000 samplings. The overall similarity value between strain GP72 and typical is the closest in the phylogenetic tree. For the latest taxonomical development has put genus Pseudomonas aureofaciens to the genus Pseudomonas chlororaphis, then it is appropriate to say that GP72 belongs to the genus Pseudomonas chlororaphis. This is the first time in China to report that a strain of Pseudomonas chlororaphis was isolated from green pepper rhizosphere, having a strong inhibitive effect on Phytophthora capsici and other soilborne pathogenic fungus. The other characteristics and the biocontrol mechanism are yet to be further studied.

Base Composition↗

PubMed2005

Generation of biologically active interleukin-1beta by meprin B.

Interleukin-1beta (IL-1beta) is a proinflammatory cytokine that is synthesized as an inactive precursor molecule that must be proteolytically processed to generate the biologically active form. Maturation of the precursor is primarily performed by caspase-1, an intracellular cysteine protease; however, processing by other proteases has been described. Meprins are cell surface and secreted metalloproteases expressed by renal and intestinal brush-border membranes, leukocytes, and cancer cells. In this study we show that purified recombinant meprin B can process the interleukin-1beta precursor to a biologically active form. Amino-terminal sequencing and mass spectrometry analysis of the product of digestion by activated meprin B determined that proteolytic cleavage resulted in an additional six amino acids relative to the site utilized by caspase-1. The biological activity of the meprin B-cleaved cytokine was confirmed by measuring the proliferative response of helper T-cells. These results suggest that meprin may play an important role in activation of this proinflammatory cytokine in various pathophysiological conditions.

Amino Acid Sequence↗

PubMed2005

In vitro and in silico cloning of Xenopus laevis SOD2 cDNA and its phylogenetic analysis.

By using the methodology of both wet and dry biology (i.e., RT-PCR and cycle sequencing, and biocomputational technology, respectively) and the data obtained through the Genome Projects, we have cloned Xenopus laevis SOD2 (MnSOD) cDNA and determined its nucleotide sequence. These data and the deduced protein primary structure were compared with all the other SOD2 nucleotide and amino acid sequences from eukaryotes and prokaryotes, published in public databases. The analysis was performed by using both Clustal W, a well known and widely used program for sequence analysis, and AntiClustAl, a new algorithm recently created and implemented by our group. Our results demonstrate a very high conservation of the enzyme amino acid sequence during evolution, which proves a close structure-function relationship. This is to be expected for very ancient molecules endowed with critical biological functions, performed through a specific structural organization. The nucleotide sequence conservation is less pronounced: this too was foreseeable, due to neutral mutations and to the species-specific codon usage. The data obtained by using AntiClustAl are comparable with those produced with Clustal W, which validates this algorithm as an important new tool for biocomputational analysis. Finally, it is noteworthy that evolutionary trees, drawn by using all the available data on SOD2 nucleotide sequences and amino acid and either Clustal W or AntiClustAl, are comparable to those obtained through phylogenetic analysis based on fossil records.

Amino Acid Sequence↗

PubMed2026

CpGene: a web application for epigenetic signature identification from DNA methylation arrays.

MOTIVATION: DNA methylation (DNAme) is the best studied epigenetic mechanism that plays pivotal role in tissue differentiation and epigenetic disruption has been correlated to diverse disease types (e.g. cancer, metabolic disorders). While various DNAme array platforms have been discovered, data analysis remains a challenging task which often requires in-depth bioinformatic expertise. Here, we developed a user-friendly web-based application for data analysis and visualization that accommodates users ranging from early-career basic/translational researchers to experienced bioinformaticians. RESULTS: CpGene is a web application for analyzing DNA methylation array data. It supports Illumina 450K, EPIC, and EPICv2 methylation array platforms and processes .idat files with integrated preprocessing, normalization, and quality control. Biomarker discovery is available through either classic differential methylation point analysis or machine learning-based feature selection as well as gene enrichment analysis. Results are summarized with clear visualizations, to aid interpretation. By combining these functions in a unified interface, CpGene streamlines methylation analysis and helps identify CpG sites and genes with biological and clinical relevance. AVAILABILITY AND IMPLEMENTATION: CpGene is openly accessible as a web service through http://cpgene.duckdns.org:8001/ and it's source code is available on https://github.com/kostaslazaros/cpgenene.

DNA Methylation↗

PubMed2006

[A research on Ig heavy chain constant region of five Acipenseridae].

Analyzed the immunoglobulin (Ig) heavy chain constant regions of Russian sturgeon (A. gueldenstaedtii); Sterlte sturgeon (A. ruthenus); Amur sturgeon (A. schrenckii); Chinese sturgeon (A. sinensis) and Great sturgeon (Huso huso) with molecular biology and bioinformatics methods. We cloned IgH nucleic acid sequences by RT-PCR using the specific primer, then determined the characteristics and functions of the amino acid sequences and plotted out the sequence into four sub-regions (CH1-CH4), of which CH4 sub-regions one another had the highest identity. According to the analysis of the variation expectation value (Kaa), species differentiation time (T) in the CH4 sub-region phylogenetic tree, we found that Chinese sturgeon and the theoretical common ancestor of the other five sturgeon form the first bifurcation of the tree, while, among the five left, Amur sturgeon and Huso sturgeon, Russian sturgeon and Siberian sturgeon, Siberian sturgeon (sequence from GenBank), Sterlte itself form another three bifurcations respectively. This result can clearly explain the relations of taxonomic status, geographical distribution and evolution among the species studied.

Amino Acid Sequence↗

PubMed2006

Tissue expression map of a large number of expressed sequence tags and its application to in silico screening of stress response genes in common wheat.

In order to assess global changes in gene expression patterns in stress-induced tissues, we conducted large-scale analysis of expressed sequence tags (ESTs) in common wheat. Twenty-one cDNA libraries derived from stress-induced tissues, such as callus, as well as liquid cultures and abiotic stress conditions (temperature treatment, desiccation, photoperiod, moisture and ABA) were constructed. Several thousand colonies were randomly selected from each of these 21 cDNA libraries and sequenced from both the 5' and 3' ends. By computing abundantly expressed ESTs, correlated expression patterns of genes across the tissues were monitored. Furthermore, the relationships between gene expression profiles among the stress-induced tissues were inferred from the gene expression patterns. Multi-dimensional analysis of EST data is analogous to microarray experiments. As an example, genes specifically induced and/or suppressed by cold acclimation and heat-shock treatments were selected in silico. Four hundred and ninety genes showing fivefold induction or 218 genes for suppression in comparison to the control expression level were selected. These selected genes were annotated with the BLAST search. Furthermore, gene ontology was conducted for these genes with the InterPro search. Because genes regulated in response to temperature treatment were successfully selected, this method can be applied to other stress-treated tissues. Then, the method was applied to screen genes in response to abiotic stresses such as drought and ABA treatments. In silico selection of screened genes from virtual display should provide a powerful tool for functional plant genomics.

Abscisic Acid↗

PubMed2005

Chipper: discovering transcription-factor targets from chromatin immunoprecipitation microarrays using variance stabilization.

Chromatin immunoprecipitation combined with microarray technology (Chip2) allows genome-wide determination of protein-DNA binding sites. The current standard method for analyzing Chip2 data requires additional control experiments that are subject to systematic error. We developed methods to assess significance using variance stabilization, learning error-model parameters without external control experiments. The method was validated experimentally, shows greater sensitivity than the current standard method, and incorporates false-discovery rate analysis. The corresponding software ('Chipper') is freely available. The method described here should help reveal an organism's transcription-regulatory 'wiring diagram'.

Analysis of Variance↗

PubMed2001

Long-term culture of human immunodeficiency virus type 1 resulting in loss of glycosylation sites.

Cultures of human immunodeficiency virus type 1 (HIV-1) provided a model for the study of mutations in the absence of host antibodies. Replicate cultures of biological and molecular clones of HIV-1 were passaged weekly for 30 or 34 weeks. Eight regions of HIV-1 genomic RNA were analyzed by means of single-strand conformation polymorphism analysis and nucleotide sequencing. Six mutations were detected in the biological clones. Two were G-->A substitutions. The frequency of mutations was higher in V1 compared to that in other regions (P = 0.01). Three mutations involved loss of potential glycosylation sites in V1. These results show that mutations in the viral genome may result from selection by factors other than host immune pressures.

Amino Acid Sequence↗

PubMed2005

Protein encoding genes in an ancient plant: analysis of codon usage, retained genes and splice sites in a moss, Physcomitrella patens.

BACKGROUND: The moss Physcomitrella patens is an emerging plant model system due to its high rate of homologous recombination, haploidy, simple body plan, physiological properties as well as phylogenetic position. Available EST data was clustered and assembled, and provided the basis for a genome-wide analysis of protein encoding genes. RESULTS: We have clustered and assembled Physcomitrella patens EST and CDS data in order to represent the transcriptome of this non-seed plant. Clustering of the publicly available data and subsequent prediction resulted in a total of 19,081 non-redundant ORF. Of these putative transcripts, approximately 30% have a homolog in both rice and Arabidopsis transcriptome. More than 130 transcripts are not present in seed plants but can be found in other kingdoms. These potential "retained genes" might have been lost during seed plant evolution. Functional annotation of these genes reveals unequal distribution among taxonomic groups and intriguing putative functions such as cytotoxicity and nucleic acid repair. Whereas introns in the moss are larger on average than in the seed plant Arabidopsis thaliana, position and amount of introns are approximately the same. Contrary to Arabidopsis, where CDS contain on average 44% G/C, in Physcomitrella the average G/C content is 50%. Interestingly, moss orthologs of Arabidopsis genes show a significant drift of codon fraction usage, towards the seed plant. While averaged codon bias is the same in Physcomitrella and Arabidopsis, the distribution pattern is different, with 15% of moss genes being unbiased. Species-specific, sensitive and selective splice site prediction for Physcomitrella has been developed using a dataset of 368 donor and acceptor sites, utilizing a support vector machine. The prediction accuracy is better than those achieved with tools trained on Arabidopsis data. CONCLUSION: Analysis of the moss transcriptome displays differences in gene structure, codon and splice site usage in comparison with the seed plant Arabidopsis. Putative retained genes exhibit possible functions that might explain the peculiar physiological properties of mosses. Both the transcriptome representation (including a BLAST and retrieval service) and splice site prediction have been made available on http://www.cosmoss.org, setting the basis for assembly and annotation of the Physcomitrella genome, of which draft shotgun sequences will become available in 2005.

Alternative Splicing↗

PubMed2006

Phytophthora genome sequences uncover evolutionary origins and mechanisms of pathogenesis.

Draft genome sequences have been determined for the soybean pathogen Phytophthora sojae and the sudden oak death pathogen Phytophthora ramorum. Oömycetes such as these Phytophthora species share the kingdom Stramenopila with photosynthetic algae such as diatoms, and the presence of many Phytophthora genes of probable phototroph origin supports a photosynthetic ancestry for the stramenopiles. Comparison of the two species' genomes reveals a rapid expansion and diversification of many protein families associated with plant infection such as hydrolases, ABC transporters, protein toxins, proteinase inhibitors, and, in particular, a superfamily of 700 proteins with similarity to known oömycete avirulence genes.

Algal Proteins↗