Biomedical subjects

Youping Deng

Publications and source records attributed to Youping Deng.

At least 19 recordsLinked to original sources

PubMed2026

Analysis of Genetic Factors in a Family With Short Stature.

BACKGROUND: To elucidate the genetic underpinnings of short stature in a familial cohort of five individuals. METHODS: A family with a history of short stature from Zhongnan Hospital of Wuhan University was the subject of this study. Peripheral blood samples were collected from family members for whole exome sequencing and Sanger sequencing to identify genetic anomalies. RESULTS: The male proband, aged 3 years and 10 months, had significant growth retardation, with a height of 91 cm (< 3rd percentile) and a weight of 13 kg (< 3rd percentile). Whole exome sequencing identified a missense mutation in the COL1A2 gene (c.577G>A, p.Gly193Ser) with maternal inheritance. Sanger sequencing confirmed this mutation in the mother and half-sister. According to American College of Medical Genetics and Genomics (ACMG) guidelines, this variant was classified as likely pathogenic. Additionally, a heterozygous mutation in the GH1 gene (c.291+1G>A) was detected in the father and grandfather, contributing to the familial short stature phenotype. CONCLUSION: In this family, we identified that variants in the COL1A2 and the GH1 can each cause short stature. This reflects both the genetic consistency and complexity of short stature, which is highly dependent on comprehensive genetic testing.

Humans↗

PubMed2007

PSM/SH2-B distributes selected mitogenic receptor signals to distinct components in the PI3-kinase and MAP kinase signaling pathways.

The Pro-rich, PH, and SH2 domain containing mitogenic signaling adapter PSM/SH2-B has been implicated as a cellular partner of various mitogenic receptor tyrosine kinases and related signaling mechanisms. Here, we report in a direct comparison of three peptide hormones, that PSM participates in the assembly of distinct mitogenic signaling complexes in response to insulin or IGF-I when compared to PDGF in cultured normal fibroblasts. The complex formed in response to insulin or IGF-I involves the respective peptide hormone receptor and presumably the established components leading to MAP kinase activation. However, our data suggest an alternative link from the PDGF receptor via PSM directly to MEK1/2 and consequently also to p44/42 activation, possibly through a scaffold protein. At least two PSM domains participate, the SH2 domain anticipated to link PSM to the respective receptor and the Pro-rich region in an association with an unidentified downstream component resulting in direct MEK1/2 and p44/42 regulation. The PDGF receptor signaling complex formed in response to PDGF involves PI 3-kinase in addition to the same components and interactions as described for insulin or IGF-I. PSM associates with PI 3-kinase via p85 and in addition the PSM PH domain participates in the regulation of PI 3-kinase activity, presumably through membrane interaction. In contrast, the PSM Pro-rich region appears to participate only in the MAP kinase signal. Both pathways contribute to the mitogenic response as shown by cell proliferation, survival, and focus formation. PSM regulates p38 MAP kinase activity in a pathway unrelated to the mitogenic response.

Animals↗

PubMed2006

Development of computations in bioscience and bioinformatics and its application: review of the Symposium of Computations in Bioinformatics and Bioscience (SCBB06).

The first symposium of computations in bioinformatics and bioscience (SCBB06) was held in Hangzhou, China on June 21-22, 2006. Twenty-six peer-reviewed papers were selected for publication in this special issue of BMC Bioinformatics. These papers cover a broad range of topics including bioinformatics theories, algorithms, applications and tool development. The main technical topics contain gene expression analysis, sequence analysis, genome analysis, phylogenetic analysis, gene function prediction, molecular interaction and system biology, genetics and population study, immune strategy, protein structure prediction and proteomics.

Biological Science Disciplines↗

PubMed2006

Parallelization of multicategory support vector machines (PMC-SVM) for classifying microarray data.

BACKGROUND: Multicategory Support Vector Machines (MC-SVM) are powerful classification systems with excellent performance in a variety of data classification problems. Since the process of generating models in traditional multicategory support vector machines for large datasets is very computationally intensive, there is a need to improve the performance using high performance computing techniques. RESULTS: In this paper, Parallel Multicategory Support Vector Machines (PMC-SVM) have been developed based on the sequential minimum optimization-type decomposition method for support vector machines (SMO-SVM). It was implemented in parallel using MPI and C++ libraries and executed on both shared memory supercomputer and Linux cluster for multicategory classification of microarray data. PMC-SVM has been analyzed and evaluated using four microarray datasets with multiple diagnostic categories, such as different cancer types and normal tissue types. CONCLUSION: The experiments show that the PMC-SVM can significantly improve the performance of classification of microarray data without loss of accuracy, compared with previous work.

Algorithms↗

PubMed2006

Identification of new members of hydrophobin family using primary structure analysis.

BACKGROUND: Hydrophobins are fungal proteins that can turn into amphipathic membranes at hydrophilic/hydrophobic interfaces by self-assembly. The assemblages by Class I hydrophobins are extremely stable and possess the remarkable ability to change the polarity of the surface. One of its most important industrial applications is its usage as paint. Without detailed knowledge of the 3D structure and self-assembly principles of hydrophobins, it is difficult to make significant progress in furthering its research. RESULTS: In order to provide useful information to hydrophobin researchers, we analyzed primary structure of hydrophobins to gain more insight about these proteins. In this paper, we presented an in-depth primary sequence analysis using batch BLAST search of the database, sequence filtering by programming and motif finding by MEME. We used batch BLAST to find similar sequences in the NCBI nr database. Then we used MEME to find out motifs. Based on the newly found motifs and the well-known C-CC-C-C-CC-C pattern we used MAST to search the entire nr database. At the end, domain search and phylogenetic analysis were conducted to confirm the result. After searching the nr database with the new PSSM-format motifs identified by MEME, many sequences from various species were found by MAST. Filtering process by pattern, domain and length left 9 qualified candidates. CONCLUSION: All of 9 newly identified potential hydrophobins possess the common pattern and hydrophobin domain. From the multiple sequence alignment result, we can see that some of them are grouped very close to other known hydrophobins, which means their phylogenetic relationship is very close and it is highly plausible that they are indeed hydrophobin proteins.

Amino Acid Sequence↗

PubMed2006

SVM Classifier - a comprehensive java interface for support vector machine classification of microarray data.

MOTIVATION: Graphical user interface (GUI) software promotes novelty by allowing users to extend the functionality. SVM Classifier is a cross-platform graphical application that handles very large datasets well. The purpose of this study is to create a GUI application that allows SVM users to perform SVM training, classification and prediction. RESULTS: The GUI provides user-friendly access to state-of-the-art SVM methods embodied in the LIBSVM implementation of Support Vector Machine. We implemented the java interface using standard swing libraries. We used a sample data from a breast cancer study for testing classification accuracy. We achieved 100% accuracy in classification among the BRCA1-BRCA2 samples with RBF kernel of SVM. CONCLUSION: We have developed a java GUI application that allows SVM users to perform SVM training, classification and prediction. We have demonstrated that support vector machines can accurately classify genes into functional categories based upon expression data from DNA microarray hybridization experiments. Among the different kernel functions that we examined, the SVM that uses a radial basis kernel function provides the best performance. The SVM Classifier is available at http://mfgn.usm.edu/ebl/svm/.

Cluster Analysis↗

PubMed2006

Analysis and functional annotation of expressed sequence tags from the fall armyworm Spodoptera frugiperda.

BACKGROUND: Little is known about the genome sequences of lepidopteran insects, although this group of insects has been studied extensively in the fields of endocrinology, development, immunity, and pathogen-host interactions. In addition, cell lines derived from Spodoptera frugiperda and other lepidopteran insects are routinely used for baculovirus foreign gene expression. This study reports the results of an expressed sequence tag (EST) sequencing project in cells from the lepidopteran insect S. frugiperda, the fall armyworm. RESULTS: We have constructed an EST database using two cDNA libraries from the S. frugiperda-derived cell line, SF-21. The database consists of 2,367 ESTs which were assembled into 244 contigs and 951 singlets for a total of 1,195 unique sequences. CONCLUSION: S. frugiperda is an agriculturally important pest insect and genomic information will be instrumental for establishing initial transcriptional profiling and gene function studies, and for obtaining information about genes manipulated during infections by insect pathogens such as baculoviruses.

Animals↗

PubMed2006

A Fourier transformation based method to mine peptide space for antimicrobial activity.

BACKGROUND: Naturally occurring antimicrobial peptides are currently being explored as potential candidate peptide drugs. Since antimicrobial peptides are part of the innate immune system of every living organism, it is possible to discover new candidate peptides using the available genomic and proteomic data. High throughput computational techniques could also be used to virtually scan the entire peptide space for discovering out new candidate antimicrobial peptides. RESULT: We have identified a unique indexing method based on biologically distinct characteristic features of known antimicrobial peptides. Analysis of the entries in the antimicrobial peptide databases, based on our indexing method, using Fourier transformation technique revealed a distinct peak in their power spectrum. We have developed a method to mine the genomic and proteomic data, for the presence of peptides with potential antimicrobial activity, by looking for this distinct peak. We also used the Euclidean metric to rank the potential antimicrobial peptides activity. We have parallelized our method so that virtually any given protein space could be data mined, in search of antimicrobial peptides. CONCLUSION: The results show that the Fourier transform based method with the property based coding strategy could be used to scan the peptide space for discovering new potential antimicrobial peptides.

Amino Acid Sequence↗

PubMed2006

RiboaptDB: a comprehensive database of ribozymes and aptamers.

BACKGROUND: Catalytic RNA molecules are called ribozymes. The aptamers are DNA or RNA molecules that have been selected from vast populations of random sequences, through a combinatorial approach known as SELEX. The selected oligo-nucleotide sequences (~200 bp in length) have the ability to recognize broad range of specific ligands by forming binding pockets. These novel aptamer sequences can bind to nucleic acids, proteins or small organic and inorganic chemical compounds and have many potential uses in medicine and technology. RESULTS: The comprehensive sequence information on aptamers and ribozymes that have been generated by in vitro selection methods are included in this RiboaptDB database. Such types of unnatural data generated by in vitro methods are not available in the public 'natural' sequence databases such as GenBank and EMBL. The amount of sequence data generated by in vitro selection experiments has been accumulating exponentially. There are 370 artificial ribozyme sequences and 3842 aptamer sequences in the total 4212 sequences from 423 citations in this RiboaptDB. We included general search feature, and individual feature wise search, user submission form for new data through online and also local BLAST search. CONCLUSION: This database, besides serving as a storehouse of sequences that may have diagnostic or therapeutic utility in medicine, provides valuable information for computational and theoretical biologists. The RiboaptDB is extremely useful for garnering information about in vitro selection experiments as a whole and for better understanding the distribution of functional nucleic acids in sequence space. The database is updated regularly and is publicly available at http://mfgn.usm.edu/ebl/riboapt/.

Aptamers, Nucleotide↗

PubMed2006

Caspase-3 and -7 mediate apoptosis of human Chang's conjunctival cells induced by enterovirus 70.

Enterovirus 70 (EV70) is the major etiological agent of acute hemorrhagic conjunctivitis (AHC). EV70 m.o.i.- (multiplicity of infection) and time-dependently induced apoptosis in human Chang's conjunctival (HCC) cells. UV- or heat-inactivated EV70 did not induce apoptosis. EV70-induced apoptosis was inhibited by cycloheximide and methoxysuccinyl-Ala-Ala-Pro-Val-chloromethylketone (MPCMK), but not actinomycin D and guanidine.HCl (although guanidine.HCl inhibited the apoptosis induced by EV70 infection at 0.5 PFU/cell for 18 h). EV70 infection induced activation of caspase-3 and -7 and degradation of the constitutively activated caspase-6. EV70-induced apoptotic DNA ladders and activated caspase-3 and -7, correlated with virus release. Caspase inhibitor IX (Z-VD-FMK) inhibited EV70-induced apoptosis and virus release, but not intracellular viral production. The results suggest that infectious virus and the syntheses of viral proteins especially EV70 proteases, but not viral genome RNA, are required for caspase-3 and -7-mediated EV70-induced apoptosis, and that apoptosis through cell lysis promotes EV70 release from HCC cells.

Apoptosis↗

PubMed2006

Molecular basis of plant gene expression during aphid invasion: wheat Pto- and Pti-like sequences are involved in interactions between wheat and Russian wheat aphid (Homoptera: Aphididae).

The Russian wheat aphid, Diuraphis noxia (Mordvilko) (Homoptera: Aphididae), is a major pest of bread wheat, Triticum aestivum L. (em Thell), in most wheat-growing areas worldwide. Aphid-resistant cultivars are used to combat this pest, but very little is known about the molecular basis of resistance. In this study, differential gene expression in D. noxia biotype 1-resistant wheat plants containing the Dnx gene and D. noxia biotype 1 feeding on Dnx plants was investigated using suppressive subtraction hybridization. The derived subtracted cDNA library includes sequences similar to Pto and Pti1, genes involved in gene-for-gene recognition of and resistance to bacterial speck disease in tomato, Lycopersicon esculentum (L.). Pto- and Pti1-like sequences contain an activation domain with conserved amino acid residues crucial for avr protein recognition and binding by Pto, and avr-Pto phosphorylation of Pti1. Wheat defense signaling is represented by sequences putatively involved in producing sterols, jasmonates, Ca2+, and abscisic and gibberellic acids. We suggest that reductions in populations of D. noxia fed Dnx plants are related to the expression of sequences involved in defensive chemical production, cellular transport, and exocytosis. Dnx plant tolerance of D. noxia feeding is proposed to be based on the expression of sequences putatively involved in self-defense against reactive oxygen species and toxins, and proteolysis; DNA, RNA, and protein synthesis; chloroplast and mitochondrial function; carbohydrate metabolism; and maintenance of cell homeostasis. D. noxia unsuccessfully counter Dnx by expressing sequences putatively involved in detoxification; proteolysis; DNA, RNA, protein, and lipid synthesis; carbohydrate metabolism; and mitochondrial function.

Amino Acid Sequence↗

PubMed2005

Glucocorticoid regulation of genes in the amiloride-sensitive sodium transport pathway by semicircular canal duct epithelium of neonatal rat.

The lumen of the inner ear has an unusually low concentration of endolymphatic Na+, which is important for transduction processes. We have recently shown that glucocorticoid receptors (GR) stimulate absorption of Na+ by semicircular canal duct (SCCD) epithelia. In the present study, we sought to determine the presence of genes involved in the control of the amiloride-sensitive Na+ transport pathway in rat SCCD epithelia and whether their level of expression was regulated by glucocorticoids using quantitative real-time RT-PCR. Transcripts were present for alpha-, beta-, and gamma-subunits of the epithelial sodium channel (ENaC); the alpha1-, alpha3-, beta1-, and beta3-isoforms of Na+-K+-ATPase; inwardly rectifying potassium channels [IC50 of short circuit current (Isc) for Ba2+: 210 microM] Kir2.1, Kir2.2, Kir2.3, Kir2.4, Kir3.1, Kir3.3, Kir4.1, Kir4.2, Kir5.1, and Kir7.1; sulfonyl urea receptor 1 (SUR1); GR; mineralocorticoid receptor (MR); 11beta-hydroxysteroid dehydrogenase (11beta-HSD) types 1 and 2; serum- and glucocorticoid-regulated kinase 1 (Sgk1); and neural precursor cell-expressed developmentally downregulated 4-2 (Nedd4-2). On the other hand, transcripts for the alpha4-subunit of Na+-K+-ATPase, Kir1.1, Kir3.2, Kir3.4, Kir6.1, Kir6.2, and SUR2 were found to be absent, and Isc was not inhibited by glibenclamide. Dexamethasone (100 nM for 24 h) not only upregulated the transcript expression of alpha-ENaC (approximately 4-fold), beta2-subunit (approximately 2-fold) and beta3-subunit (approximately 8-fold) of Na+-K+-ATPase, Kir2.1 (approximately 5-fold), Kir2.2 (approximately 9-fold), Kir2.4 (approximately 3-fold), Kir3.1 (approximately 3- fold), Kir3.3 (approximately 2-fold), Kir4.2 (approximately 3-fold), Kir7.1 (approximately 2-fold), Sgk1 (approximately 4-fold), and Nedd4-2 (approximately 2-fold) but also downregulated GR (approximately 3-fold) and 11beta-HSD1 (approximately 2-fold). Expression of GR and 11beta-HSD1 was higher than MR and 11beta-HSD2 in the absence of dexamethasone. Dexamethasone altered transcript expression levels (alpha-ENaC and Sgk1) by activation of GR but not MR. Proteins were present for the alpha-, beta-, and gamma-subunits of ENaC and Sgk1, and expression of alpha- and gamma-ENaC was upregulated by dexamethasone. These findings are consistent with the genomic stimulation by glucocorticoids of Na+ absorption by SCCD and provide an understanding of the therapeutic action of glucocorticoids in the treatment of Meniere's disease.

11-beta-Hydroxysteroid Dehydrogenases↗

PubMed2005

Computationally analyzing the possible biological function of YJL103C--an ORF potentially involved in the regulation of energy process in yeast.

Although the complete genomes of a number of organisms have been sequenced, the biological functions of many genes are still not known. Because experimentally studying the functions of those genes one by one requires tremendous time, it is vital to use published resources like microarray gene expression data for computational analysis of gene functions. One example is YJL103C, a yeast gene of unknown function in the Saccharomyces Genome Database (SGD). It is possible to quickly infer its biological function by computational analysis. In this study, we present an efficient model to explore the biological function of a novel gene using microarray data. We showed that the expression pattern of YJL103C is most similar to the genes in the energy group and respiratory chain subgroup. We further found that YJL103C contains a HAP2,3,4 box in its promoter region and a cytochrome C heme-binding signature in its protein sequence. Our findings define a potential role for YJL103C in the regulation of energy metabolism, specifically in the process of oxidative phosphorylation. Similar bioinformatics methods can be applied to infer the biological functions of other novel genes in organisms for which microarray data are available. In this work, we selected a single gene of unknown function as a case study. By focusing on the power of computer analysis and bioinformatics on the available microarray data, we have determined the likely biological function of YJL103C. Our study provides a method by which to explore the potential function of other genes currently annotated as having an unknown function in any organism for which global gene expression data are available.

Binding Sites↗

PubMed2004

Incremental genetic K-means algorithm and its application in gene expression data analysis.

BACKGROUND: In recent years, clustering algorithms have been effectively applied in molecular biology for gene expression data analysis. With the help of clustering algorithms such as K-means, hierarchical clustering, SOM, etc, genes are partitioned into groups based on the similarity between their expression profiles. In this way, functionally related genes are identified. As the amount of laboratory data in molecular biology grows exponentially each year due to advanced technologies such as Microarray, new efficient and effective methods for clustering must be developed to process this growing amount of biological data. RESULTS: In this paper, we propose a new clustering algorithm, Incremental Genetic K-means Algorithm (IGKA). IGKA is an extension to our previously proposed clustering algorithm, the Fast Genetic K-means Algorithm (FGKA). IGKA outperforms FGKA when the mutation probability is small. The main idea of IGKA is to calculate the objective value Total Within-Cluster Variation (TWCV) and to cluster centroids incrementally whenever the mutation probability is small. IGKA inherits the salient feature of FGKA of always converging to the global optimum. C program is freely available at http://database.cs.wayne.edu/proj/FGKA/index.htm. CONCLUSIONS: Our experiments indicate that, while the IGKA algorithm has a convergence pattern similar to FGKA, it has a better time performance when the mutation probability decreases to some point. Finally, we used IGKA to cluster a yeast dataset and found that it increased the enrichment of genes of similar function within the cluster.

Algorithms↗

PubMed2004

Joint analysis of two microarray gene-expression data sets to select lung adenocarcinoma marker genes.

BACKGROUND: Due to the high cost and low reproducibility of many microarray experiments, it is not surprising to find a limited number of patient samples in each study, and very few common identified marker genes among different studies involving patients with the same disease. Therefore, it is of great interest and challenge to merge data sets from multiple studies to increase the sample size, which may in turn increase the power of statistical inferences. In this study, we combined two lung cancer studies using microarray GeneChip, employed two gene shaving methods and a two-step survival test to identify genes with expression patterns that can distinguish diseased from normal samples, and to indicate patient survival, respectively. RESULTS: In addition to common data transformation and normalization procedures, we applied a distribution transformation method to integrate the two data sets. Gene shaving (GS) methods based on Random Forests (RF) and Fisher's Linear Discrimination (FLD) were then applied separately to the joint data set for cancer gene selection. The two methods discovered 13 and 10 marker genes (5 in common), respectively, with expression patterns differentiating diseased from normal samples. Among these marker genes, 8 and 7 were found to be cancer-related in other published reports. Furthermore, based on these marker genes, the classifiers we built from one data set predicted the other data set with more than 98% accuracy. Using the univariate Cox proportional hazard regression model, the expression patterns of 36 genes were found to be significantly correlated with patient survival (p < 0.05). Twenty-six of these 36 genes were reported as survival-related genes from the literature, including 7 known tumor-suppressor genes and 9 oncogenes. Additional principal component regression analysis further reduced the gene list from 36 to 16. CONCLUSION: This study provided a valuable method of integrating microarray data sets with different origins, and new methods of selecting a minimum number of marker genes to aid in cancer diagnosis. After careful data integration, the classification method developed from one data set can be applied to the other with high prediction accuracy.

Adenocarcinoma↗

PubMed2004

Differentially expressed genes in the lens of mimecan-null mice.

PURPOSE: Members of the small leucine-rich proteoglycans (SLRP) gene family are essential for normal collagen fibrillogenesis in various connective tissues and important regulators of cellular growth, differentiation, and tissue repair. Mimecan is a member of this gene family and is expressed in many connective tissues. We have previously reported that knockout of the mouse mimecan gene results in abnormal collagen fibrillogenesis, mainly in the cornea and skin. During the course of our studies on biological roles of mimecan in the eye, we found that this gene is expressed in the mouse lens. Here, we sought to identify gene expression changes in the lens that are associated with the absence of mimecan. METHODS: Reverse transcription-polymerase chain reaction amplification (RT-PCR), in situ hybridization (ISH), and immunohistochemistry (IHC) were used to determine mimecan expression in human and mouse eyes. Microarray hybridization was used to determine gene expression differences between lenses isolated from mimecan-null and wild type mice. Relative quantitative RT-PCR was used to verify the expression levels of a subset of the identified genes. RESULTS: By ISH and IHC, mimecan mRNA was detected in cornea and lens at embryonic day 16.5 (E16.5) and postnatal day 10 (P10) mouse eyes. By RT-PCR, mimecan mRNA was detected in human cornea, lens, iris, and retina. In mimecan-null mice lenses, microarray analysis of 5,002 mouse genes demonstrated a more than two fold increase in expression of 65 genes and a more than two fold decrease in expression of 76 genes. Among genes with increased expression were cell adhesion molecules, G-protein coupled receptors, intracellular signaling molecules, genes involved in protein biosynthesis and degradation, and genes involved in immune function. Decreased expression was found in extracellular matrix molecules, calcium binding and transporting proteins, and genes known for their roles in regulating cellular motility. Intriguingly, decreased gene expression was observed with two SLRP family members, biglycan and condroadherin, as well as with several stress-response proteins, including gammaA-crystallin, hemoglobin alpha 1, and metallothionein 1. Quantitative RT-PCR confirmed changes in expression of 12 genes selected from the arrays. CONCLUSIONS: In this report we present the first demonstration that mimecan is constitutively expressed in the vertebrate lens. The results from gene expression profiling reveal the ability of mimecan to influence expression of biglycan and chondroadherin, thereby indicating possible novel regulatory interactions between these SLRP family members. As with mimecan, the expression of chondroadrein in vertebrate lens has not been reported previously. Our results provide insight into the function of mimecan in the lens and enable further characterization of molecular mechanisms by which this protein exerts its biological roles.

Animals↗

PubMed2004

Computational identification of novel chitinase-like proteins in the Drosophila melanogaster genome.

MOTIVATION: Multiple chitinases as well as lectins closely related to them have been characterized previously from many insect species and the corresponding genes/cDNAs have been cloned. However, the identification of the entire assortment of genes for chitinase family proteins and their differences in biochemical properties have not been carried out in any individual insect species. The completion of the entire DNA sequence of Drosophila melanogaster (fruit fly) genome and identification of open reading frames presents an opportunity to study the structures and functions of chitinase-like proteins, and also to identify new members of this family in Drosophila. We are, therefore, interested in studying the functional genomics of chitinase-like gene families in insects. METHODS: We searched the Drosophila protein sequences database using fully characterized insect chitinase sequences and BLASTP software, identified all the putative chitinase-like proteins encoded in Drosophila genome, and predicted their structures using domain analysis tools. A phylogenetic analysis of the chitinase-like proteins from Drosophila and several other insect species was carried out. The structures of these chitinases were modeled using homology modeling software. RESULTS: Our analysis revealed the presence of 18 chitinase-like proteins in the Drosophila protein database. Among these are seven novel chitinase-like proteins that contain four signature amino acid sequences of chitinases belonging to family 18 glycosylhydrolases, including both acidic and hydrophobic amino acid residues critical for enzyme activity. All the proteins contain at least one catalytic domain with one having four catalytic domains. Phylogenetic analysis of chitinase-like proteins from Drosophila and other insects revealed an evolutionary relationship among all these proteins, which indicated gene duplication and domain shuffling to generate the observed diversity in the encoded proteins. Homology modeling showed that all the Drosophila chitinase-like proteins contain one or more catalytic domains with a (alpha/beta)8 barrel-like structure. Our results suggest that insects utilize multiple family 18 chitinolytic enzymes and also non-enzymatic chitinase-like proteins for degrading/remodeling/binding to chitin in different insect anatomical extracellular structures, such as the cuticle, peritrophic membrane, trachea and mouth parts during insect development, and possibly for other roles including chitin synthesis. AVAILABILITY: Perl program and supplementary material are available at http://www.ksu.edu/bioinformatics/supplementary.htm

Amino Acid Sequence↗

PubMed2004

Tobacco genes induced by the bacterial effector protein AvrPto.

The type III effector protein AvrPto acts as a virulence factor in susceptible plants lacking a cognate resistance gene but triggers hypersensitive response and disease resistance in tomato plants carrying the Pto gene or in tobacco plants carrying an unknown resistance gene. To assist the characterization of cellular responses caused by AvrPto in the plant, a pathogen-free system was adopted to isolate genes up-regulated 12 h after induced expression of AvrPto. By using subtraction cloning and transgenic tobacco plants expressing avrPto as a transgene, we isolated 125 nonredundant cDNA clones that represent avrPto-response genes (ARG). In addition to genes that are known to be induced by Pto-avrPto recognition, a number of new genes were also isolated. Most of ARG showed a specific induction in tobacco plants challenged with incompatible or nonhost pathogens. The use of an avrPto mutant that selectively eliminated the avrPto recognition in tobacco demonstrated that the ARG were induced in a highly specific manner by the avirulence, instead of the virulence activity of avrPto.

Bacterial Proteins↗