Blin, Kai

Weber, Tilmann

Wohlleben, Wolfgang

Nucleic Acids Research

Kai Blin

Wolfgang Wohlleben

Tilmann Weber

Crossref

Patscanui: an intuitive web interface for searching patterns in DNA and protein data

Patterns in biological sequences frequently signify interesting features in the underlying molecule. Many tools exist to search for well-known patterns. Less support is available for exploratory analysis, where no well-defined patterns are known yet. PatScanUI (https://patscan.secondarymetabolites.org/) provides a highly interactive web interface to the powerful generic pattern search tool PatScan. The complex PatScan-patterns are created in a drag-and-drop aware interface allowing researchers to do rapid prototyping of the often complicated patterns useful to identifying features of interest

Online Research Database In Technology

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Downloaded from orbit.dtu.dk on: Jul 07, 2018Patscanui: an intuitive web interface for searching patterns in DNA and protein dataBlin, Kai; Wohlleben, Wolfgang; Weber, TilmannPublished in:Nucleic Acids ResearchLink to article, DOI:10.1093/nar/gky321Publication date:2018Document VersionPublisher's PDF, also known as Version of recordLink back to DTU OrbitCitation (APA):Blin, K., Wohlleben, W., & Weber, T. (2018). Patscanui: an intuitive web interface for searching patterns in DNAand protein data. Nucleic Acids Research, 46(W1), W205-W208. DOI: 10.1093/nar/gky321Published online 2 May 2018 Nucleic Acids Research, 2018, Vol. 46, Web Server issue W205–W208doi: 10.1093/nar/gky321Patscanui: an intuitive web interface for searchingpatterns in DNA and protein dataKai Blin1, Wolfgang Wohlleben2 and Tilmann Weber1,*1The Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Kgs. Lyngby, Denmarkand 2Interfaculty Institute for Microbiology and Infection Medicine, Eberhard Karls University of Tu¨bingen, Tu¨bingen,GermanyReceived February 15, 2018; Revised April 09, 2018; Editorial Decision April 13, 2018; Accepted April 17, 2018ABSTRACTPatterns in biological sequences frequently sig-nify interesting features in the underlying molecule.Many tools exist to search for well-knownpatterns. Less support is available for ex-ploratory analysis, where no well-defined pat-terns are known yet. PatScanUI (https://patscan.secondarymetabolites.org/) provides a highly inter-active web interface to the powerful generic patternsearch tool PatScan. The complex PatScan-patternsare created in a drag-and-drop aware interface allow-ing researchers to do rapid prototyping of the oftencomplicated patterns useful to identifying features ofinterest.INTRODUCTIONMany interesting biological features can be identified basedon characteristic patterns in DNA and protein sequences.Bioinformatics tools and databases make use of such se-quence patterns to address specific research questions, fromidentifying potential sgRNA sequences in CRISPR appli-cations (such as CRISPy-web (1)) or identifying tandemrepeats (2) to the PROSITE Database (3). However, thesetools usually are restricted to their very specific use-caseand mostly use pre-defined static patterns to search for. Ifnew motifs are identified in research papers or using mo-tif discovery tools like MEME (4) or HOMER (5), it oftentakes significant time until they find their way into dedicatedsoftware tools. Being able to efficiently search for arbitrarysequence patterns directly allows researchers to bridge thistechnological gap.In 1997, Dsouza et al. published the generic patternsearch tool PatScan (6), allowing to search for DNA andprotein sequence patterns using an expressive pattern lan-guage: It is possible to specify patterns that match complexstructures such as repeats, hairpins, stem loops and pseu-doknots. Weight matrices can be used as patterns, and pat-ternsmay also contain ambiguity codes for nucleotides. Pat-terns can be repeated, with or without mismatches, inser-tions, and deletions, and complemented.PatScan is available from the SEED servers website (http://blog.theseed.org/servers/2010/07/scan-for-matches.html).Unfortunately, PatScan is not easily accessible to re-searchers without scripting background as it is acommand-line only tool that also requires learningthe complex pattern language. There is no built-in helpfunction, constructing more complex patterns can quicklyturn unwieldy, and there is no syntax checking to helpfinding typos in patterns.In order to solve the usability challenges and make flexi-ble pattern searching more available to the biology commu-nity, we have developed an interactive web-based interface,PatScanUI. Our web server supports all pattern types usedin the command-line utility while ensuring that all elementsof the pattern are valid and provides extensive help and tu-torial sections. While creating patterns, parts of the patterncan be rearranged using simple drag & drop operation.DESIGN AND IMPLEMENTATIONPatScanUI consists of two components. The browser-basedweb client is implemented in JavaScript and handles creat-ing and validating the pattern set users want to run. Thewebclient uses Knockout.js (http://knockoutjs.com/) to link theunderlying data model to the user interface. The data modelverifies that only valid patterns can be created and submit-ted to the server. On the server side, the Python-based Flaskframework (http://flask.pocoo.org/) handles file uploads, re-ceiving search pattern sets and running the PatScan com-mand line tool.PatScanUI accepts FASTA-formatted input files contain-ing one or more sequences and provides output in fourdifferent formats. The PatScan command line tool returnsmatches in FASTA format, and also has a further process-ing script that returns a more compact representation. Inaddition to these two formats, PatScanUI also can outputthe matches in GFF3 and BED format. Outputs are shown*To whom correspondence should be addressed. Tel: +45 24 89 61 32; Email: tiwe@biosustain.dtu.dkC© The Author(s) 2018. Published by Oxford University Press on behalf of Nucleic Acids Research.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), whichpermits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.Downloaded from https://academic.oup.com/nar/article-abstract/46/W1/W205/4990781by DTU Library - Technical Information Center of Denmark useron 03 July 2018W206 Nucleic Acids Research, 2018, Vol. 46, Web Server issueFigure 1. PatScan output displayed in FASTA format. Different outputformats can be selected using the buttons on top. The ‘Save’ button belowthe text field allows saving the output to a file in the selected format.in a text box for quick iterations while developing the pat-tern, and can also be downloaded in any of the four formats(Figure 1).FEATURES AND APPLICATIONSPatScanUI supports all pattern types supported by thecommand line tool. Available patterns depend on the in-put molecule, as some pattern types are available forDNA/protein sequences only. String patterns take a stringof bases or amino acids that should be identified in the in-put sequences. ForDNA input, the IUPACambiguity codesmay be used as well. Range patterns match a length of ar-bitrary nucleotides or amino acids and are usually used asspaces between more specific patterns. Complement pat-terns are exclusive to DNA inputs and match the reversecomplement of a previously defined pattern. Repeat pat-terns match a previously matched pattern again. Alterna-tive patterns take any two patterns and require just one ofthem to match. Length limit patterns allow adding a lengthconstraint to previous matches and are usually utilized withmultiple range patterns. Weight patterns present a hybrid ofposition specific scoring and probability matrices for DNAsequences. The probability of encountering a specific basein a particular position in percent are used to sum up a to-tal match score, the weight. The weight pattern also takesa minimum score threshold, allowing to filter out matchesthat are not good enough. On protein inputs, the ‘any of’and ‘not any of’ allow to specify a list of amino acids thatneed to be present or absent at a particular position. Inorder to support unusual base-pairings in e.g. RNA se-quences, alternative complementation rules can be definedto specify which base can pair with which. String, comple-ment, and repeat patterns also support matching with vari-ations, so it is possible to specify how many mutations, in-sertions or deletions are acceptable for the pattern to stillmatch.With PatScanUI, all these pattern types––or combina-tions thereof––can be interactively explored and assembled.In order to better explain the various pattern types sup-ported by PatScan, we present an exemplary biological ap-plication. Starting out with a relatively simple pattern, wewill keep adding more pattern types to capture more of thebiological nuances and demonstrate how PatScanUI can beuseful for quick exploratory analysis of a sequence. For evenmore detail on how to run the analysis, see the tutorial onthe PatScanUI website.Example: finding iron-response elements in bacteriaBesides its catalytic function in the TCA cycle, the aconi-tase enzyme has an important regulatory function in bothEukaryotes and Prokaryotes. When active as a regulator,aconitase binds specific structural motifs in mRNA, so-called iron-response elements (IREs). In Eukaryotes, aconi-tase is highly sensitive to iron deprivation and oxidativestress (7,8). In bacteria, the role of aconitase seems to besimilar (9), though the recognition sequence is less pre-served (10). Aconitase recognises the RNA stem loop struc-ture of the IRE consisting of a C bulge, a stem of six nu-cleotides, and a loop of five or six nucleotides. In Eukary-otes, the loop sequence always is CAGUG, in Bacteria,more variations to both stem and loop are possible. In thisexample, we will build up a set of patterns to identify pu-tative bacterial IREs in the bacterium Streptomyces coeli-color. The 5′ UTR sequences used for this example and astep-by-step guide are provided on the PatScanUI tutorialpage (https://patscan.secondarymetabolites.org/tutorial).The basic IRE pattern is CN1N2N3N4N5N6CAGUGN’6N’5N’4N’3N’2N’1, where Nx is any nucleotide, andN’x is its complement (7). An initial attempt at finding sucha pattern using PatScan would use a number of string pat-terns and a complement pattern. Just using a string pat-tern with CNNNNNNCAGUGNNNNNN would fail toensure the second set of Ns would be the reverse comple-ment of the first, so instead we need to break the pattern upinto three pieces:One for the C base, one for the first half of the stem con-sisting of six Ns, and one for the loop section consisting ofDownloaded from https://academic.oup.com/nar/article-abstract/46/W1/W205/4990781by DTU Library - Technical Information Center of Denmark useron 03 July 2018Nucleic Acids Research, 2018, Vol. 46, Web Server issue W207Figure 2. UI-driven design of complex PatScan patterns. The individual parts of the pattern––in this example the search for IRE elements––can be interac-tively assembled by dragging the respective ‘pattern element’ into the working area. PatScanUI then generates the PatScan pattern, which is used to searchthe submitted sequence by pressing the ‘Submit’ button.the CAGUG part. A complement pattern for the secondhalf of the stem then captures the complete IRE.On the example input of S. coelicolor 5′ UTR regions,this pattern does not give any results. The reason for this isthat the IREmotif in bacteria is more variable (9). Notably,the stem region does not need to have six perfect matches.Using the ‘variations’ option on the complement pattern toallow one mismatch relaxes the requirement enough to findhits. The loop region in IREs can contain an additional baseafter the CAGUG sequence (7), this can be supported byadding a range pattern for a range from 0 to 1.Another variation that is common on bacterial IREs isthat the stem of the stem loop structure is only five baseslong, not six. Replacing the string pattern of Ns with an-other range pattern allows this.Not only the stem region but also the loop region canhave variations in bacteria. Notably, the loop sequenceGAGAG has also been reported to be functional (10). Tosupport searching for CAGUG or GAGAG at the sametime, we can use the alternative pattern. It is basically a con-tainer that can hold any two other patterns, one of whichhas to match.By default, PatScan uses the regular DNA complementa-tion rules to determine which bases can be in a reverse com-plement. IREs are RNA sequences, so additional GU/UGpairs are possible. To support this, you can create customalternative complementation rules (Figure 2).If we wanted to explore further alternatives to the looppattern sequence, we could nest multiple ‘alternative pat-terns’ to create a deeper logical branching. That approachdoes get a bit unwieldy, though. A better option is to insteaduse a weight pattern.CONCLUSIONSPatScanUI provides a user-friendly interface to design anddevelop complex search patterns for various applicationsbased on the powerful PatScan pattern-matching engine.Due to the possibility to interactively edit and optimizethe patterns, the tool is well suited to rapidly prototypepattern-matching strategies, without requiring scripting orcommand-line tools.DATA AVAILABILITYPatScanUI is available from https://patscan.secondarymetabolites.org/. This website is free andopen to all users and there is no login requirement. Sourcecode is available under the OSI-approved AGPL licensefrom https://github.com/kblin/patscanui/.FUNDINGNovo Nordisk Foundation [NNF10CC1016517,NNF16OC0021746 to T.W.]; German Ministry of Educa-tion and Research (BMBF) [0315585A to W.W.]. Fundingfor open access charge: Novo Nordisk Foundation.Conflict of interest statement.None declared.REFERENCES1. Blin,K., Pedersen,L.E., Weber,T. and Lee,S.Y. (2016) CRISPy-web:an online resource to design sgRNAs for CRISPR applications.Synth. Syst. Biotechnol., 1, 118–121.2. Benson,G. (1999) Tandem repeats finder: a program to analyze DNAsequences. Nucleic Acids Res., 27, 573–580.3. Sigrist,C.J.A., de Castro,E., Cerutti,L., Cuche,B.A., Hulo,N.,Bridge,A., Bougueleret,L. and Xenarios,I. (2013) New andDownloaded from https://academic.oup.com/nar/article-abstract/46/W1/W205/4990781by DTU Library - Technical Information Center of Denmark useron 03 July 2018W208 Nucleic Acids Research, 2018, Vol. 46, Web Server issuecontinuing developments at PROSITE. Nucleic Acids Res., 41,D344–D347.4. Bailey,T.L., Boden,M., Buske,F.A., Frith,M., Grant,C.E.,Clementi,L., Ren,J., Li,W.W. and Noble,W.S. (2009) MEME SUITE:tools for motif discovery and searching. Nucleic Acids Res., 37,W202–W208.5. Heinz,S., Benner,C., Spann,N., Bertolino,E., Lin,Y.C., Laslo,P.,Cheng,J.X., Murre,C., Singh,H. and Glass,C.K. (2010) Simplecombinations of lineage-determining transcription factors primecis-regulatory elements required for macrophage and B cell identities.Mol. Cell, 38, 576–589.6. Dsouza,M., Larsen,N. and Overbeek,R. (1997) Searching forpatterns in genomic data. Trends Genet., 13, 497.7. Hentze,M.W. and Ku¨hn,L.C. (1996) Molecular control of vertebrateiron metabolism: mRNA-based regulatory circuits operated by iron,nitric oxide, and oxidative stress. Proc. Natl. Acad. Sci. U.S.A., 93,8175–8182.8. Rouault,T.A. and Klausner,R.D. (1996) Iron-sulfur clusters asbiosensors of oxidants and iron. Trends Biochem. Sci., 21, 174–177.9. Ale´n,C. and Sonenshein,A.L. (1999) Bacillus subtilis aconitase is anRNA-binding protein. Proc. Natl. Acad. Sci. U.S.A., 96,10412–10417.10. Michta,E., Schad,K., Blin,K., Ort-Winklbauer,R., Ro¨ttig,M.,Kohlbacher,O., Wohlleben,W., Schinko,E. and Mast,Y. (2012) Thebifunctional role of aconitase in Streptomyces viridochromogenesTu¨494. Environ. Microbiol., 14, 3203–3219.Downloaded from https://academic.oup.com/nar/article-abstract/46/W1/W205/4990781by DTU Library - Technical Information Center of Denmark useron 03 July 2018

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Patscanui: an intuitive web interface for searching patterns in DNA and protein data

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