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The authors wish it to be known that, in their opinion, the first two authors should be regarded as joint First Authors
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MODOMICS is the first comprehensive database resource for systems biology of RNA modification. It integrates information about the chemical structure of modified nucleosides, their localization in RNA sequences, pathways of their biosynthesis and enzymes that carry out the respective reactions. MODOMICS also provides literature information, and links to other databases, including the available protein sequence and structure data. The current list of modifications and pathways is comprehensive, while the dataset of enzymes is limited to Escherichia coli and Saccharomyces cerevisiae and sequence alignments are presented only for tRNAs from these organisms. RNAs and enzymes from other organisms will be included in the near future. MODOMICS can be queried by the type of nucleoside (e.g. A, G, C, U, I, m1A, nm5s2U, etc.), type of RNA, position of a particular nucleoside, type of reaction (e.g. methylation, thiolation, deamination, etc.) and name or sequence of an enzyme of interest. Options for data presentation include graphs of pathways involving the query nucleoside, multiple sequence alignments of RNA sequences and tabular forms with enzyme and literature data. The contents of MODOMICS can be accessed through the World Wide Web at http://genesilico.pl/modomics/.
Naturally occurring RNAs contain numerous chemically altered nucleosides. They are formed by enzymatic modification of the primary transcripts during the complex RNA maturation process. To date, over 100 structurally distinguishable modified nucleosides originating from different types of RNAs from many diverse organisms of the three major phylogenetic domains of life have been reported and collected in the RNAMods database (1,2). The location and distribution of various types of modification vary greatly between different RNA molecules, organisms and organelles. The largest number of modified nucleosides with the greatest structural diversity is found in transfer RNAs (tRNAs) (3). Other types of RNA (rRNA, mRNA, snRNA, snoRNA and even the recently discovered miRNA) also contain modified nucleosides; however, they cannot match tRNAs with respect to abundance and diversity of modifications [see ref. (4) and the collection of reviews in books (5,6)].
We have collected all the currently known RNA modifications from the RNAMods database (2) and the tRNA sequences from the Bayreuth database (3). We have extended the set of RNA modifications to include the most recent additions reported in the literature and we have carefully refined the type and location of modifications in Escherichia coli and Saccharomyces cerevisiae tRNA sequences based on an extensive survey of the published data. Furthermore, based on a very extensive literature search we have compiled the set of known and predicted modification reactions (and the responsible enzymes, if available) that lead from the unmodified precursors to all known modified nucleosides. For all RNA modification enzymes from E.coli and S.cerevisiae, we have collected the available information concerning alternative gene and protein names, amino acid sequence, 3D structure, cofactor requirements and literature (PubMed) references to the key analyses. To date, such a comprehensive set of metabolic reactions involving nucleosides in RNA has never been reported. Similarly, our collection of enzymes is much more complete, accurate and up-to-date than the subsets of proteins involved in metabolism of RNA modifications stored in general-purpose enzyme and genome databases, such as BRENDA (7), EcoCyc (8), SGD (9), etc.
MODOMICS is a relational database that links together the datasets of modification reactions/pathways, RNA-modifying enzymes and the sequences of target RNAs, which can be queried via three convenient menus, ‘PATHWAYS’, ‘ENZYMES’ and ‘RNAs’. The modification pathways are represented as a set of graphs visualized with GRAPHVIZ (http://www.graphviz.org/), in which the nodes represent the modified nucleosides, and the edges represent the transformations (real or putative) between them, e.g. enzymatic reactions. Currently, the pathway dataset comprises five graphs, corresponding to all known modifications of adenosine (A), cytidine (C), guanosine (G), uridine (U) and the queuosine pathway (Q), of which the graph of U modifications is clearly most diversified. The ‘PATHWAYS’ menu offers a variety of filtering options to display a whole graph or its fragment corresponding to reactions that occur in a particular kingdom of life (Eukaryota, Archaea, Bacteria or viruses) or an organellum (currently only mitochondrial modifications are supported), in a particular subset or RNAs (tRNAs, rRNAs, mRNAs, small RNAs or chromosomal RNAs), and hypermodifications that result from processing of an already modified nucleoside (e.g. I and its derivatives, Ψ and its derivatives, etc.). All nodes of the (sub)graph, e.g. the images of all nucleosides, are hyperlinked to dynamically generated windows comprising two panels (example shown in Figure 1). The upper panel displays basic information about the selected nucleoside, including its common name, one letter code in the tRNA sequence database, symbol used in MODOMICS and the chemical structure in the SMILES code hyperlinked to the corresponding image generated using the SMI2GIF script kindly provided by the Daylight Chemical Information Systems Inc (http://www.daylight.com/). The lower panel includes a subgraph of reactions leading to the selected nucleoside from its precursor(s) (unless the selected nucleoside is the precursor itself), and all known hypermodifications formed from that nucleoside.
All edges of the (sub)graph, e.g. arrows that connect the images of nucleosides, are hyperlinked to static ‘reaction’ windows comprising one or more panels (example shown in Figure 2). The upper panel displays basic information about the selected reaction, namely the type of RNA in which it is conducted and its occurrence in the phylogenetic context (inferred from the knowledge of the phylogenetic distribution of the substrate and the product nucleoside). Other panels display information about enzymes known to catalyze the selected reaction in different substrates and in different organisms. Currently, the database of enzymes includes only proteins from E.coli and S.cerevisiae, but will be expanded in the future and may eventually comprise all orthologs of the functionally characterized enzymes identifiable in fully sequenced genomes. At this moment, however, MODOMICS includes only enzymes and corresponding protein cofactors that have been experimentally validated, of which most (but not all) have known amino acid sequences. The enzyme panels are also directly accessible from the ‘ENZYMES’ menu, which lists all entries of the current database in the tabular form, which can be sorted by the name(s) (e.g. Trm1, Dus2, MnmC, etc.), enzyme type (e.g. methyltransferase, deaminase, etc.) or the organism of origin. The enzyme database can be also searched by identifying entries, whose fields match the query formulated as a regular expression (e.g. ‘Trm*’, ‘*pus*’, ‘m1*’ or ‘*transferase’, etc.). The enzyme names include both the traditional one(s), which have been quite erratically inferred from different characteristics of the gene, the protein, the organism, the type of the reaction, or even the whole pathway (e.g. Tgs1p, Abd1p, Gar1p, Nop1p, MnmA, GidA, etc.), as well as a novel name given according to the newly developed, uniform nomenclature (H.G. and J.M.B., manuscript in preparation). The enzyme panel lists all relevant types of reactions between nucleosides in different substrates and provides the EC numbers (if available) and links to the corresponding entries in the BRENDA database (7). Other information about the enzyme concerns the sequence (if available) and includes the name of the open reading frame in the genome, the NCBI GenPept (10) and SwissProt (11) accession numbers, the experimentally solved structure in the PDB (12) (in the future it will also include experimentally validated computational models) and the literature information concerning experimental characterization of the protein, identification of the gene, and possibly a structural analysis, together with links to the relevant database entries.
The ‘RNAs’ menu allows displaying multiple sequence alignments of homologous RNA families, in which the modifications have been observed. Currently, this dataset is complementary to the enzyme dataset and includes only tRNA sequences from S.cerevisiae (both cytoplasmic and mitochondrial) and E.coli, and the corresponding unmodified tDNA sequences. In the future it will be extended to manually validated tRNA sequences from other model organisms, for which the tRNA data are available (3), as well as to tDNA sequences predicted from the fully sequenced genomes [e.g. the tRNomics dataset from ref. (13)]. It will also include other RNA sequences with identified modifications, such as rRNAs and various small non-coding RNAs. The content of the currently available tRNA sequence alignment can be filtered according to several options, including the organism and strain or taxon of origin, anticodon and amino acid specificity.
The data are accessible freely for research purposes at the URL http://genesilico.pl/modomics/. Images of pathways are available by Email request to the first author (at lp.ociliseneg@hds). Scientists interested in adding data (modifications, RNA sequences, enzymes, etc.) or in using the enzyme information in MODOMICS to predict the modification status of RNA molecules from the DNA sequence are encouraged to contact the senior authors (at lp.ociliseneg@bmai or firstname.lastname@example.org). This article should be cited in research projects assisted by the use of MODOMICS.
The authors are grateful to Daylight Chemical Information Systems Inc. for providing their SMI2GIF service. MODOMICS would not be possible without the data from publicly available databases, in particular the RNAMods database and the Bayreuth tRNA dataset. J.M.B. was supported by the EMBO/HHMI Young Investigator Programme. S.D.-H. was supported by the NIH (grant 5R01AI056034-02). Travel expenses between Poland and France were covered by EGIDE (Polonium grant #07558WK) and by the CEMBM Center of Excellence grant from the 5th Framework Programme of the European Union (contract #QLK6-CT-2002-90363). The Open Access publication charges for this article were waived by Oxford University Press.
Conflict of interest statement. None declared.