Greenwell, P.

Rughooputh, S.

WestminsterResearch

     University of Westminster Eprints http://eprints.wmin.ac.uk   Bioinformatics in the identification of glycosidase genes in the Chlamydia genome  Pamela Greenwell Sanjiv Rughooputh  School of Biosciences    This is an electronic version of an article published in Molecular and Cellular Proteomics, 2 (9). 826, September 2003. Molecular and Cellular Proteomics is available online at:  http://www.mcponline.org/cgi/reprint/2/9/825   The Eprints service at the University of Westminster aims to make the research output of the University available to a wider audience.  Copyright and Moral Rights remain with the authors and/or copyright owners. Users are permitted to download and/or print one copy for non-commercial private study or research.  Further distribution and any use of material from within this archive for profit-making enterprises or for commercial gain is strictly forbidden.       Whilst further distribution of specific materials from within this archive is forbidden, you may freely distribute the URL of the University of Westminster Eprints (http://eprints.wmin.ac.uk).   In case of abuse or copyright appearing without permission e-mail wattsn@wmin.ac.uk. 71.5Novel Algorithms for Terminal SequenceLibraries’ ConstructionT. Chen, J. H. Li, and T. M. ChenCidmax Corporation, London, ON, CanadaIn general, the terminal sequences include 5-and 3-end of ORF, 5-UTRand 3UTR. Those are resources for selecting of signature sequence whichrefers to a molecular characteristic of sense, antisense sequences of geneand the corresponding peptide sequences. Those sequences are usefulfor designing oligonucleotide probes (6mers to 24mers) and epitope(penta-peptide and above) for DNA, protein microarrays and PCR primerssystematically. We propose series novel algorithms that consist ofX.sup.(n-m) and its derivatives for the sequence prediction, deducing andidentification. X  61 in ORF and X  20 in its corresponding peptidesequences. X  64 in 5-UTR and 3-UTR sequences. n represents thelength of the entire length of the designed sequence measured by codonor essential amino acid (expressed codon). m represents the length of thepre-determined terminal oriented sequence of the entire sequence meas-ured by codon or essential amino acid (expressed codon). For example,5-ATG in 5-ATGGCACTC is the pre-determined terminal oriented se-quence. m  1. n  3. Algorithms of 61.sup.(n-1) / 20.sup.(n-1), 61.sup.n/ 20.sup.n, 61.sup.(n-2) / 20.sup.(n-2), 64.sup.(n-1) and 64.sup.n coulddefine both sense and antisense sequences for ORF, 5-UTR and 3-UTRrespectively. Codon-based algorithm of 61.sup.(n-m) could represent ORFsequences from either 5- or 3-end while eliminates all the nonsensecodon within themselves. It could represent both ORF and its correspond-ing peptide sequence. In contrast, algorithm of 4.sup.n could not do so butcreate huge artificial sequence redundancy. The advantages of the novelalgorithms are enormous: For example: from 5-ATG to its downstreamsequence within the length of 9mers of ORF, there are total 3,721 distinctcodon-based oligonucleotides whereas 262,144 distinct nucleotide-based oligonucleotides were deduced by algorithm of 4.sup.n.71.6Bioinformatics in the Identification ofGlycosidase Genes in the ChlamydiaGenomeP. Greenwell and S. RughooputhUniversity of Westminster, London, U.K.Following the cloning of the 1,042,519-bp Chlamydia trachomatis ge-nome, it was thought that identification of genes, utilizing homologysearches, would be simple. However, more than 25% of the DNA se-quenced has yet to be assigned function, with over 200 gene productsclassified as hypothetical proteins. The organism expresses the glycosi-dases a-mannosidase and b-N-acetylglucosaminidase and therefore mustpossess the relevant genes. We undertook homology searches usingBLASTN and BLASTP to identify regions conserved across a wide rangeof prokaryotes and interrogated the C.trachomatis genome to locate therelevant genes. Surprisingly little homology was found. Interrogation witha-mannosidase sequences yielded matches with only 2 or 3 proteins, allbut one of which had been allocated functions unrelated to glycosidases.Areas of homology lay outside conserved regions for prokaryote a-man-nosidase. Interrogation of the genome with the b-hexosaminidase fromNeisseria meningitidis revealed a 29% identity (34.25% ungapped) over165 amino acids with the hypothetical protein CT391. The homology lieswithin a conserved area of the prokaryotic b-N-acetylglucosaminidase.Nevertheless, this is only scant evidence of identity. Although the use ofbioinformatics as a tool for the rapid identification of the genes has notbeen a complete success, it will prove vital when the enzymes have beenpurified and N-terminal sequence has been obtained. Interrogation of thegenome at this stage will allow us to allocate function to, as yet, unchar-acterized genes, and determine why the primary bioinformatics failed toidentify the appropriate sequences.71.7Prediction of Post-translational GPIAnchor Modification of Protein ByMachine LearningG. Poisson, A. Bergeron, C. Chauve, and P. SimardDe´partement d’informatique, Universite´ Du Que´bec A` Montre´al,Montre´al, QC, CanadaAn anchoring Glycosylphosphatidylinositol (GPI) is a complex structure ofmembrane anchoring, resulting from a post-translational modification. Itprimarily anchors proteins to membranes, but also have other functionssuch as participation in signalling mechanisms. However protein se-quence database, such as SWISS-PROT, propose few sequences havingthis modification, mainly due to the difficulty to identify its presence.Moreover, the publicly available tools fail to predict more than 25% ofthese known GPI anchors. Using machine-learning approach we wereable to achieved a better predictive capacity. We present here a model ofartificial neural network (retro-propagation resilient) pipelined to a HiddenMarkov Model (HMM) which makes it possible to obtain between 83% and92% of recognition of GPI present in SWISS-PROT and TrEMBL. Ananalysis of the known proteins present in the human proteome (as of 2003)was undertaken and reveals the presence of this modification in about 1%of the available sequences. The set of human GPI anchors predicted bythis analysis will be publicly available.HUPO 2nd Annual & IUBMB XIX World Congress, October 8–11, Montreal826 Molecular & Cellular Proteomics 2.9

Bioinformatics in the identification of glycosidase genes in the Chlamydia genome

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Bioinformatics in the identification of glycosidase genes in the Chlamydia genome

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