PMCCPMCCPMCC

Search tips
Search criteria 

Advanced

 
Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
 
Curr Protoc Bioinformatics. Author manuscript; available in PMC 2013 June 1.
Published in final edited form as:
PMCID: PMC3427849
NIHMSID: NIHMS386143

Using the Reactome Database

Abstract

There is considerable interest in the bioinformatics community in creating pathway databases. The Reactome project (a collaboration between the Ontario Institute for Cancer Research, Cold Spring Harbor Laboratory, New York University Medical Center and the European Bioinformatics Institute) is one such pathway database and collects structured information on all the biological pathways and processes in the human. It is an expert-authored and peer-reviewed, curated collection of well-documented molecular reactions that span the gamut from simple intermediate metabolism to signaling pathways and complex cellular events. This information is supplemented with likely orthologous molecular reactions in mouse, rat, zebrafish, worm and other model organisms. This unit describes how to use the Reactome database to learn the steps of a biological pathway; navigate and browse through the Reactome database; identify the pathways in which a molecule of interest is involved; use the Pathway and Expression analysis tools to search the database for and visualize possible connections within user-supplied experimental data set and Reactome pathways; and the Species Comparison tool to compare human and model organism pathways.

Keywords: Reactome, reaction, pathway, database, biological pathway, pathway analysis, interaction network, pathway visualization

The completion of multiple genomes in recent years has led to an explosion of information about known and predicted gene products. This information explosion has been accelerated by the invention of high throughput techniques, such as next-generation DNA sequencing, RNA sequencing, expression microarrays (see Chapter 7), ChIP-chip, and ChIP-seq, which now allow biologists to generate huge experimental data sets that cannot easily be interpreted by simple inspection. Biological pathway databases have come to play a key role in the interpretation of such data sets. They capture what is already known about the interplay of genes, proteins and small molecules using a data model that is accessible to computation. For example, a microarray experiment that changes the expression pattern of thousands of genes may only affect the expression patterns of a small handful of biochemical pathways. Hence there is a high degree of interest in the bioinformatics community in creating pathway databases. The Reactome project, covered in this unit, is one such database. It is a curated collection of well-documented molecular reactions that span the gamut from simple intermediate metabolism (e.g., sugar catabolism) to complex cellular events such as the mitotic cell cycle. These reactions are gathered by experts in the field, peer reviewed, and edited by professional staff members prior to being published in the database. A semi-automated procedure supplements this information by identifying likely orthologous molecular reactions in mouse, rat, zebrafish, worm and other model organisms.

The protocols in this unit illustrate how to use Reactome to learn the steps of a biological pathway and how a suite of data analysis tools can assist with the interpretation of user-supplied experimental data sets. Basic Protocol 1 describes how to navigate and browse through the Reactome database. Basic Protocol 2 and Alternate Protocol 1 explain how to identify the pathways in which a molecule of interest is involved using either the common name or accession number, respectively. Alternative Protocol 2 describes when and how to use the Advanced Search Feature. Basic Protocol 3 and Alternative Protocol 3 details how to use Pathway Analysis to perform identifier mapping and overrepresentation analysis, respectively. Basic Protocol 4 explains how to overlay pathway diagrams with expression data. Basic Protocol 5 describes using the Species Comparison tool to compare model organism and human pathways.

NOTE: This information is based on Reactome in November 2011. Some of the web pages may have changed somewhat since the unit written.

BASIC PROTOCOL 1

BROWSING A REACTOME PATHWAY

This protocol will introduce the basic navigational techniques needed to browse the Reactome database.

Necessary Resources

Hardware

Computer capable of supporting a Web browser and an Internet connection

Software

Any modern Web browser such as Firefox, Safari, Chrome and Internet Explorer will work to display Reactome web pages.

  • 1.
    Point the browser to the Reactome home page at http://www.reactome.org.
    • The home page (Fig. 8.7.1) has several elements.
      Figure 8.7.1
      The Reactome home page (www.reactome.org) features a navigation bar and side panel provides access to pathway analysis tools and pathway data.
      The navigation bar, at the very top of the page provides access to the top-level sections, tools and resources of the Reactome site. “About” is a description of the project as a whole; “Content” is an extensive table of contents for the resource; “Documentation” provides access to user guides and information about Reactome; “Download” provides access to the whole database as a single bulk or individual data set download; and the “Contact Us” for assistance with a Reactome question or troubleshooting a problem. “Outreach” section provides information on how to cite Reactome contents in journal articles and access to training and tutorial resources.
      The tool bar, located on the left side of the home page, provides access to some of the frequently used analysis tools: an interactive pathway browser, online pathway analysis, a gene expression analysis tool, and a cross-species comparison tool. A simple search tool, above the analysis buttons, permits flexible keyword, accession number, and database identifier queries on the Reactome database. Access is also available to some of the more popular bulk pathway downloads in formats, including BioPAX, SBML and PDF.
      The main text section provides entry points for “Pathway of the Month”, curation statistics, and training and outreach materials, including video tutorials, news and information about the project.
  • 2.
    To begin browsing the reactions contained within the DNA Repair pathway, click on the “Browse Pathways” button on the home page. Scroll down the Pathway hierarchy panel, and click on the “DNA Repair” pathway link. This will load a page corresponding to the top level of the DNA Repair pathway for Homo sapiens (Fig. 8.7.2). Click on the plus (“+”) symbol adjacent to the DNA Repair to open this level of the hierarchy, revealing the pathway subentries.
    Figure 8.7.2
    The top-level page describing DNA Repair. The panel to the left contains an expanding hierarchical representation of the current pathway, showing the subpathways that participate in it. The interactive pathway diagram to the right is the main human-readable ...
    • The Reactome Pathway Browser consists of four key elements:
      The analyze bar, at the top of the page provides a species selector, with drop-down list of species. Reactome data is human-centric, data for other species is inferred from human pathways - pathway steps may be missing for other organisms if they are not identified by the inference process. Selecting an organism from the species selector will refresh the pathway browser with the inferred pathway diagram from the selected model organism, if it is conserved. The “Home” button returns the user to the Reactome homepage. The “Analyze, Annotate & Upload” button controls the interactive tools associated with the pathway diagrams.
      The pathway hierarchy panel, occupying the vertical rectangle on the far left of the screen, provides a scrolling display of all Reactome canonical pathways in a hierarchy. The six headings underneath DNA Repair are the major divisions of the pathway, such as Base Excision Repair and Double-Strand Break Repair. The plus (“+”) symbol implies that there are subheadings underneath the headings. Clicking on a plus (“+”) symbol will expand the topic to show its subparts. The sub-pathways and reactions within each canonical pathway can be hidden by clicking on the minus (“−”) symbol to the left of the pathway name.
      The visualization panel, to the right of the hierarchy panel, displays an interactive pathway diagram that can be panned and zoomed in Google Map style. The pathway diagram uses the conventions of the Systems Biology Graphical Notation (SBGN) format to distinguish the molecules and reactions by shape, color and cellular location, to provide a dynamic framework for pathway visualization and data analysis. In the top left-hand corner of the pathway diagram, there is an icon with 4 different sizes of blue circle, which allows users to chose the zoom level and scroll across the pathway diagram. Users can also zoom using the mouse wheel, and click and drag the diagram. The thumbnail image, in the lower right-corner of the visualization panel can be used to navigate quickly to a region of interest in the pathway diagram
      The details panel, below the visualization panel contains the description of the pathway. This is the meat of the information contained within Reactome. The main screen begins with the document identifier (DOI) and stable Reactome record identifier (e.g. REACT_216.1), the authors, peer reviewers, and editors for this pathway, along with the date that the pathway was first released. This is followed by a text “summation” that describes the pathway. Below the summation are more details about the pathway, including the taxon in which the event occurs, supporting citations, the Gene Ontology classification(s) of the pathway (“Represents GO biological process”), and the cellular compartment in which the pathway is known to occur. Further down are two important fields. The field that reads “Equivalent event(s) in other organism(s)” allows one to jump to the corresponding processes in the other model organism systems. Clicking the “Participating molecules” button lists all proteins, nucleic acids, complexes and small molecules, and complexes of these entities that are involved in any of the myriad aspects of DNA Repair. Selecting a model organism from the “Compare human pathway to” drop-down menu will display an inter-species pathway-comparison view (see Protocol 4 for more details). Pathway diagrams and annotations can be downloaded in a variety of formats by clicking one of the links adjacent to the “Download pathway in one of the formats” field.
  • 3.
    Drill down into the Global Genomic Nucleotide Excision Repair subpathway as follows. The second last entry in the DNA Repair pathway hierarchy is Nucleotide Excision Repair. Click on the plus (“+”) symbol to open this level of the hierarchy, revealing the subentries “Global Genomic NER (GG-NER)” and “Transcription-coupled NER (TC-NER)”. Click on the plus (“+”) symbol to the left of Global Genomic NER (GG-NER) and then click on the Global Genomic NER (GG-NER) link, to reveal the page shown in Figure 8.7.3.
    Figure 8.7.3
    The Global Genomic NER (GG-NER) subpathway event hierarchy (left), pathway diagram (right) and details panel (bottom). The highlighting in the pathway diagram indicates the reactions involved in this subpathway only.
    • Notice that the pathway hierarchy panel has now expanded by a level to reveal the relationship between Global Genomic Nucleotide Excision Repair and the more general pathways that it belongs to on the one hand, and to the more specific pathways (“DNA Damage Recognition…”, “Formation of incision complex…”, etc.) on the other hand. Furthermore, the pathway diagram in the visualization panel changes, highlighting the reactions that are involved in Global Genomic Nucleotide Excision Repair. When a subpathway in the hierarchy is selected, its name and the name of the parent pathway are highlighted in the hierarchy, and in the pathway diagram as green squares highlighting the nodes of all reactions that are components of the subpathway. The details panel will display further information about the subpathway in text form, and is accompanied by a cartoon overview, and subpathway summation and annotations.
  • 4.
    In order to drill down to the reaction level, continue to click on subpathways. Eventually the reaction level will be reached, where processes are described as the interactions of individual molecules. To see this, return to the pathway hierarchy and click first on plus (“+”) symbol to the left of DNA Damage Recognition in GG-NER and then click on “XPC:HR23B complex binds to damaged DNA site with lesion [Homo sapiens]” to go to the page shown in Figure 8.7.4.
    Figure 8.7.4
    An individual reaction. Notice that the reaction is highlighted by a single green box in the pathway diagram, and that the details panel now shows the constituent input and output molecular compounds that participate in this reaction.
    • Clicking a reaction in the pathway hierarchy will cause the reaction name and the name of the subpathway(s) and parent pathways to be highlighted. The corresponding reaction node in the pathway diagram will also be highlighted with a green box. Furthermore, the Details panel will update to show particulars of the selected reaction. These new fields include Input, which lists the molecules that enter the reaction, and Output, which lists the molecules that result from the reaction. In the case of the current reaction, the inputs are the damaged DNA substrate and the XPC:HR23B nucleotide excision complex, while the output is the complex of XPC:HR23B with the damaged DNA. In other words, this reaction describes the binding of XPC:HR23B to damaged DNA prior to the subsequent enzymatic reactions that cleave the DNA and excise the damaged base pair.
      Two other new fields are also shown. “Preceding event(s)” describes the reaction that immediately precedes this one temporally, in this case “XPC binds to HR23B forming a heterodimeric complex‥‥”. “Following event(s)” describes the reaction that immediately follows this one: “Recruitment of repair factors to form preincision complex…”. One can click on the preceding and following events to follow the reactions backward and forward in time. If the preceding or following reaction is not currently visible in the visualization panel, the pathway diagram will re-center on the selected object, highlight it with a green box and refresh the pathway hierarchy to highlight the name of the reaction and the parent pathway/subpathway.
  • 5.
    Move to the next reaction by clicking on the “Following event(s)” link, “Recruitment of repair factors to form preincision complex.” This will lead to the page shown in Figure 8.7.5, which describes the recruitment of six new proteins and complexes to create a single complex bound at the site of the damaged DNA. This page shows a preceding event of “XPC:HR23B complex binds to damaged DNA site with lesion [Homo sapiens],” which is the page shown in Figure 8.7.4, and a following event of “Formation of open bubble structure in DNA by helicases [Homo sapiens].” By clicking on the “Following event(s)” link, it would be possible to continue to follow the process forward in time.
    Figure 8.7.5
    After clicking the “Following event(s)” link in the previous figure, the next step in the GG-NER pathway is displayed.
    • The relationship between the “levels” of the pathway hierarchy on the one hand and the “Preceding event(s)” and “Following event(s)” links, on the other hand, may not be immediately clear. The nested levels of the pathway hierarchy reflect levels of abstraction in the conceptual organization of pathways. As one moves deeper into the hierarchy, the contents of the pathway diagram become more and more specific and move closer to the biochemical reaction level. The “Preceding event(s)” and “Following event(s)” links, on the other hand, usually only appear when one is at the reaction level, and move backward and forward in time, remaining always at individual reactions. It might seem to be redundant to have this dual mode of navigation, but it is there for a good reason. Because biological knowledge is incomplete, there are many instances where it is known that “something happens next,” but the specific molecules that are involved in this next step are not yet characterized. In this case, the “Following event(s)” link will be missing, and one must step up in the hierarchy to a more general description of the pathway in order to connect to the next known, well-characterized reaction in the process.
      Figure 8.7.5 also illustrates an important aspect of Reactome, the References section at the bottom of the screen. Some type of provenance supports every reaction described in the database. The three main types of provenance are direct literature citations, an indirect assertion made by arguing from protein-based similarity in a model organism, and an assertion made by the author of the module. In the case of direct literature citations, the citation describes experiments performed using a system derived from the taxon under consideration. For example, the first reference in the current reaction describes in vivo experiments performed on human tissue culture cells that provided direct evidence via molecular cross-linking of an association between the XPC:HR23B/DNA complex and the repair factors recruited during this step.
      Often, knowledge of human biology is derived from work on model organisms. If understanding of a reaction is derived from work on a model organism system, the references will describe those experiments. Internally, direct evidence and indirect evidence from model organisms are kept distinct, but the user interface does not currently reflect that fact.
      Finally, the high-level, more general pathways will usually be based on an assertion by the author of the module and supported by one or more review articles.
  • 6.
    Reactome provides information about the subunits of a complex, as well as the larger ensembles of proteins that a complex participates in. In this example, from the “Recruitment of repair factors to form preincision complex” page, click on the “TFIIH” entity in the pathway diagram. This will update the Details panel to display information about the TFIIH (transcription factor IIH) complex (Fig. 8.7.6).
    Figure 8.7.6
    This page describes the TFIIH complex. In addition to describing its subunit structure, the details panel displays all the macromolecular complexes and pathways in which TFIIH participates. The context sensitive menu displays all the components of the ...
    • The Complex Details panel will include new fields, such as “Hierarchical view of the components”, which list the complex components, and “Component of”, which list the other complexes that TFIIH is a component. This is followed by the Gene Ontology molecular activity term(s) associated with the activity of the complex (“Biochemical activities”), all events that are catalyzed by it (“Catalyses events”), all that consume it (“Consumed by events”), and all that produce TFIIH (“Produced by events”).
  • 7.
    To learn more about the protein subunits of the TFIIH complex, right click on the “TFIIH” icon in the pathway diagram, as is shown in Figure 8.7.6. This will invoke a context sensitive menu displaying two options: “Other Pathways” and “Participating Molecules”. Select “Participating Molecules”, scroll down the list of molecules names and click on the “Cdk7 [nucleoplasm]” subunit to load the Protein Details panel that describes it (Fig. 8.7.7).
    Figure 8.7.7
    The reference entity page describes the relationship between a molecule as it is represented in Reactome and one or more entries in a third-party database such as UniProt.
    • Information about any protein, small molecule or set represented in the pathway diagram can also be displayed in the Details panel by selecting the object within the diagram. The fields with the Protein Details panel include: links to UniProt, Ensembl, and other reference databases that describe the molecule (“Links to corresponding entries in other databases”), other external identifiers and synonyms (“Other identifiers related to this sequence”), primary external reference identifier (“Reference entity”), the Gene Ontology cellular component annotation (“Cellular compartment”), complexes this protein belongs to (“Component of”), all events that consume it (“Consumed by events”), alternate or post-translationally modified forms of the protein (“Other forms of this molecule”) and equivalent molecules in other species if they exist (“Entities deduced on the basis of this entity”). If the protein belongs to a catalytic reaction, there are three additional fields shown. “Catalyst” describes the protein or complex that catalyzes the reaction. “Essential catalyst component” describes the component of the complex or protein domain that contributes to the catalytic reaction. “GO molecular function” represents the activity of a catalyst.
  • 8.
    To navigate to other pathways that the TFIIH complex participates in the Reactome database, select the “TFIIH” icon in the pathway diagram and click the right button of your mouse to engage the context sensitive menu. Select “Other Pathways”, scroll down the list of pathway names and click on “HIV Life Cycle” (Fig. 8.7.8).
    Figure 8.7.8
    The context sensitive menu displays the other pathways that the TFIIH complex participates.
  • 9.
    • Selecting a particular pathway will redirect the Pathway Browser to display the selected pathway diagram and highlighting with a green box, the TFIIH entity. “Mousing-over” the highlighted pathways reveals that, in addition to the DNA Excision Repair pathway that has been browsed in the steps above, TFIIH also participates in HIV Life Cycle, RNA Polymerase II Transcription, mRNA Capping and RNA Polymerase I, RNA Polymerase III and Mitochondrial Transcription. This connection between HIV Life Cycle, RNA transcription and DNA Repair might surprise biologists who are not well acquainted with DNA Excision Repair, and illustrates how Reactome bridges the disciplines.
  • 9.
    Repeat Step 8 but this time select “Nucleotide Excision Repair” to return to the previous pathway diagram. To display the proteins that interact with XPA protein entity, select the “XPA protein [nucleoplasm]” icon in the pathway diagram and click the right button on your mouse to invoke the context sensitive menu and select “Display Interactors” (Fig. 8.7.9).
    Figure 8.7.9
    An interaction overlay of proteins from IntAct that interact with XPA protein.
    • The Molecular Interaction Overlay surrounds the selected pathway diagram entity with a set of boxes representing protein-protein or protein-small molecule interactors. At this time, only interactors can be displayed for individual pathway protein entitities and not for complexes or molecule sets. Clicking “Hide Interactors” in the context sensitive menu removes interactors from the selected diagram entity. Selecting “Export Interactors” will displays the interactors for the selected pathway protein as a downloadable PSI-MITAB formatted list in a new browser tab/window. The default interaction database is IntAct. However, other sources of interaction data (protein-protein, protein-small molecule or user-supplied list) can be selected using the Analyze, Update & Annotate button on the analyze bar. A maximum of 10 interactors will be displayed at a time for the selected pathway protein and a white box superimposed onto the selected protein displays the total number of interactors known by the source database. Using the “Analyze, Update & Annotate” button, it is possible to view up to 50 interactors for every protein in the pathway diagram and download a table with all interactors per protein from the selected interaction database. The lines and boxes that compose the interaction overlay are interactive. “Mousing-over” an interactor (node) produces a pop-up containing the name and identifier of the protein. Clicking on the node will launch a new web page displaying the reference database for the interactor. For example, clicking a protein interactor will open the UniProt entry in a new window. Clicking a line connecting the pathway protein to the interactor (edge) opens a new window containing details of the interaction from the source database.

BASIC PROTOCOL 2

FINDING THE PATHWAYS INVOLVING A GENE OR PROTEIN

This protocol will describe how to identify pathways and reactions that involve a gene or protein of interest. For the purposes of illustration, the cyclin-dependent kinase 7 gene will be used, which has the following identifiers:

Protein product:Common name: Cdk7
UniProt (SwissProt): P50613 (CDK7_HUMAN)
Gene:Entrez Gene: 1022
GenBank: NM_001799
Ensembl: ENSG00000134058.

See Alternate Protocol 1 to search by a database accession number rather than by a common name.

Necessary Resources

Hardware

Computer capable of supporting a Web browser and an Internet connection

Software

Any modern Web browser such as Firefox, Safari, Chrome and Internet Explorer will work to display Reactome web pages.

  1. Point the browser to the Reactome home page at http://www.reactome.org.
  2. On the home page (Fig. 8.7.1), in the search bar near the top of the page (see annotation to step 1 of Basic Protocol 1), click the text box, type Cdk7, then press the “Search” button. After a few second, you will be presented with a results page similar to Figure 8.7.10.
    Figure 8.7.10
    Results from the Cdc7 quick search on the Reactome home page are displayed.
    • Search results are organized based upon record type, i.e. Reaction, Pathway, Protein or Other (includes literature and complex) and is identified by an icon and type name preceding the title of the result. Underneath the result title is a brief descriptive summation of the Reactome record. The search term will be highlighted yellow if they appear within the title or descriptive text. Clicking on the title of the search result will connect to the corresponding Reactome web page. At the top of the results page, the Type Selector Bar provides a set of tick boxes that includes a count by type for the displayed results. This section tells the user that Reactome knows of 30 Pathways, 70 Reactions, 4 Proteins and 55 Other records have something to do with Cdc7. Unchecking boxes for type categories allows you to limit results by type, i.e. unselect the type(s) that you don't want to see and then click the “Show” button to reload the results page. The navigation tool, at the bottom of the page, will navigate to see additional hits. All the results can be displayed in a single page by clicking “Show all results”. If it is necessary to restrict the search to a specific species, the organism can be selected from the Species drop-down menu at the top of the search results page and the search repeated.
  3. Navigate to the Cdk7 entry by clicking on the “Protein: UniProt:P50613 CDK7 (Homo sapiens)” link. This will lead to the page shown in Figure 8.6.7.
    • This protein record is called the “reference entity” page and describes everything that Reactome knows about Cdk7, including its names in other online databases, the protein complexes that it belongs to, and the pathways and reactions that it participates in. Any of these links can be clicked to begin browsing the pathways involving Cdk7.

ALTERNATE PROTOCOL 1

FINDING THE PATHWAYS INVOLVING A GENE OR PROTEIN USING UniProt (SwissProt), Ensembl, OR Entrez Gene IDENTIFIER

Instead of searching for a gene or protein using its common name, as described in Basic Protocol 2, one may wish to use the accession number by which it is known in GenBank, SwissProt, Ensembl, or Gene. The steps for doing so, using a UniProt (SwissProt) accession number, are presented here. The same procedure works for GenBank, Ensembl or Entrez Gene identifiers.

Necessary Resources

Hardware

Computer capable of supporting a Web browser and an Internet connection

Software

Any modern Web browser such as Firefox, Safari, Chrome and Internet Explorer will work to display Reactome web pages.

  1. Point the browser to the Reactome home page at http://www.reactome.org.
  2. On the home page (Fig. 8.7.1), in the search box near the top left of the page (see annotation to step 1 of Basic Protocol 1), type P50613, then press the “Search” button.
    • This brings up the search results page (see Basic Protocol 2, step 2) similar to the one shown in Figure 8.7.10.
  3. Navigate to the molecule, reaction or pathway of interest. Clicking on the “Protein: UniProt:P50613 CDK7 (Homo sapiens)”, loads the reference entity page as shown in Figure 8.7.7. From here it is possible to navigate to the pathways and reactions in which Cdk7 takes part, and view the complexes that contain Cdk7.

ALTERNATE PROTOCOL 2

USING ADVANCED SEARCH

The simple searches shown in Basic Protocol 2 and Alternate Protocol 1 will suffice for many situations. However, the default search casts a very wide net and may return more hits than one wants. If this is the case, one may wish to use the Advanced Search, which gives much finer control over the search. To illustrate, this protocol describe how to search for complexes that contain “Pyruvate dehydrogenase”, whose default search returns multiple hits on compounds, events, literature references, and other database entries.

Necessary Resources

Hardware

Computer capable of supporting a Web browser and an Internet connection

Software

Any modern Web browser such as Firefox, Safari, Chrome and Internet Explorer will work to display Reactome web pages.

  1. Point the Web browser to the Reactome home page at http://www.reactome.org.
  2. On the home page (Fig. 8.7.1), under the “Tools” in the Navigation bar, select “Advanced Search”.
    • The advanced search method permits specific schema-based queries for particular types of Reactome data. This option searches for records (instances) in the database by multiple field (attribute) values. Queries are combined together with boolean AND operators. The advanced search modes, include (i) “with EXACT PHRASE ONLY”, returns hits that contain the exact query phrase; (ii) “matching REGULAR EXPRESSION”, treats the query phrase as a PERL regular expression and returns hits that contain the query words, even as a substring; (iii) “with ALL of the words”, returns hits that contain all of the query words in any order; (iv) with ANY of the words, returns hits to any word in the query phrase; (v) “with the EXACT PHRASE”, returns only those hits that exactly MATCH the query phrase; (vi) “!=”, returns hits that do NOT MATCH query phrase; (vii) “with no value”, returns hits for which the selected field of a given class has no value; and (viii) “with any value”, returns hits for which the selected field of a given Class has any value (not zero or blank).
  3. Go to the “Restrict search to class” pull-down menu and select “Complex” to limit the search to database entries for complexes. Select “name” under the first row “Field name”, select “with ALL of the words” from the next drop-down menu and type Pyruvate dehydrogenase into the text box. Press the “Search” button to launch the query.
    • This will return a list of 80 complexes that contain the words “Pyruvate dehydrogenase”, including pyruvate dehydrogenase E1 complex [mitochondrial matrix], pyruvate dehydrogenase E2 trimer [mitochondrial matrix] and pyruvate dehydrogenase complex [mitochondrial matrix]. By default, the search will find all matches across all the species known to Reactome. If one wishes to see matches in to a specific species, one can change the search parameters as in step 4.
  4. To see matches in another species, press the browser’s Back button to return to the Advanced search entry page. Select “species” under the second row “Field name”, select “with ALL of the words” from the next drop-down menu and type Rattus norvegicus into the final text box. Press the “Search” button to launch the advanced query.
    • A page will appear displaying 5 matches on the orthologous set of pyruvate dehydrogenase complexes in the Norway rat.
  5. If the search is retrieving unwanted matches, it is possible to further limit the set of hits by specifying an exact match for “pyruvate dehydrogenase complex,” which will find database objects that match the search phrase exactly from end to end. Press the browser’s Back button to return to the advanced search page. Change the query mode setting from “with ALL of the words” to “with the EXACT PHRASE” It will also be necessary to modify the search phrase from “pyruvate dehydrogenase” to “pyruvate dehydrogenase complex” and change the species back to “Homo sapiens”. Press the “Search” button to launch the query.
    • A page will appear displaying 2 matches that contain the exact words “Pyruvate dehydrogenase complex”, including pyruvate dehydrogenase complex [mitochondrial matrix] and phosphorylated pyruvate dehydrogenase complex [mitochondrial matrix].

BASIC PROTOCOL 3

USING REACTOME PATHWAY ANALYSIS TOOL TO ANNOTATE A PROTEIN LIST WITH REACTOME PATHWAY DATA

The Pathway Analysis tool allows one to analyze lists of genes or proteins by providing services for ID mapping and pathway assignment (default) and overrepresentation analysis (see Alternative Protocol 3 for further details). It is a powerful exploratory tool that is linked to the Reactome Pathway Browser. To illustrate how it works, this protocol will describe the analysis of a list of UniProt identifiers to determine which Reactome pathways they associate with.

Necessary Resources

Hardware

Computer capable of supporting a Web browser and an Internet connection.

Software

Any modern Web browser such as Firefox, Safari, Chrome and Internet Explorer will work to display Reactome web pages.

  1. Point the browser to the Reactome home page at http://www.reactome.org.
  2. In the sidebar of the home page, click the “Map IDs to Pathways” button to open the Pathway Analysis data entry page.
  3. To demonstrate the ID mapping and pathway assignment features (default setting), click the “Example” button to automatically load a list of human UniProt identifiers into the data entry box and then click the “Analyse” button.
    • The entry page consists of a data entry box that supports typing and pasting of a list of gene or protein identifiers or accession numbers. Alternatively, the “Browse” button can be used to locate a file for uploading prior to analysis. Several identifier and accession number types are currently supported, including Entrez Gene, OMIM, InterPro, UniProt, GenBank/EMBL/DDBJ, Ensembl, RefPep, RefSeq, Affymetrix, Agilent and Illumina. Database identifiers that contain only numbers, such as those from Entrez Gene must be prefixed by the source database name and a colon (e.g. EntrezGene:4314).
  4. After step 3 has been carried out, the ID Mapping and Pathway assignment will determine all likely matches between the submitted list of genes or proteins and the pathways in the Reactome database. After a few seconds, a table of results entitled “Pathway Assignment” will appear (Figure 8.7.11).
    Figure 8.7.11
    The sortable table of results for the “Pathway Assignment” mode of the Reactome Pathway Analysis tool.
    • The “Pathway Assignment” table consists of columns that can be sorted by pressing the arrows next to the column title. A small white arrow appears next to the column title, indicating the direction of the sort. In the first column, the UniProt identifiers represent every protein identified from the submitted list. If a submitted identifier was not recognized, it will only be displayed in column 1 and all other cells in that row will be blank. The other columns represent: the reference UniProt identifier, the species in which the pathway exists, and a list of pathway names in which the protein is found.
  5. Re-sort the “UniProt ID” column by clicking the small white arrow twice (next to the column title) and then click on the UniProt ID: Q9Y6Y9 in the “UniProt” column to linkout to a new web page describing the reference UniProt protein.
  6. Go back to the “Pathway Assignment” table of results. Find and click on “Gene Expression” from the “Pathway names column” to open a new window displaying the pathway diagram for the selected pathway.
  7. Return to the results table. At the top of the table, select “Comma-separated values” from the “Select format to download this table:” drop-down menu and click the “Download” button to download a table of results.
    • The Download feature also permits the downloading of a Microsoft Excel spreadsheet (“Microsoft Xcel”) or “Tab-separated Values” file for record keeping or further analysis.

ALTERNATIVE BASIC PROTOCOL 3

USING PATHWAY ANALYSIS TOOL TO IDENTIFY STATISTICALLY OVERREPRESENTED EVENTS

The pathway overrepresentation analysis determines whether any Reactome pathway annotations are statistically enriched within a set of genes or proteins as specified by a user-supplied list of identifiers or accession numbers. As an example, this protocol will describe the analysis of a list of UniProt identifiers to identify enriched Reactome pathways.

Necessary Resources

Hardware

Computer capable of supporting a Web browser and an Internet connection

Software

Any modern Web browser such as Firefox, Safari, Chrome and Internet Explorer will work to display Reactome web pages.

  1. Point the browser to the Reactome home page at http://www.reactome.org.
  2. In the sidebar of the home page, click the “Pathway Analysis” button to launch the data entry page for the Pathway Analysis.
  3. Click the “Example” button on the data entry page, select the “Overrepresentation analysis” radio button and click the “Analyse” button. After a few seconds, a color-coded interactive list of events will appear as in Figure 8.7.12.
    Figure 8.7.12
    The results for the “overrepresentation analysis” mode of the Reactome Pathway Analysis tool.
    • Each pathway is colored according to the unadjusted probability of identifying a given number or more proteins in this pathway by chance. The warmer the color, the higher the level of overrepresentation is for a given pathway. Top-level pathways are arranged upon the lowest p-value of their subpathway constituents. To the right of the pathway name is the p-value (derived from the hypogeometric test) and the ratio of the number of proteins from the submitted set that matched the pathway/the total number of proteins in the pathway.
  4. Click the plus (“+”) symbol before the “Gene Expression” event name to reveal the “Matching identifiers” list of the identifiers and associated proteins that contributed to the overrepresentation score.
    • The top-level pathways, and any subpathways they contain, can be expanded using the plus (“+”) symbols. Alternatively, the entire overrepresentation event hierarchy can be displayed and hidden using the “Open All” and “Close All” buttons, respectively.
  5. Scroll down the results page to the “Statistically over-represented events as an ordered list” section to view the same results in a tabular form.
    • The contents of the table are interactive. Clicking on the pathway name in the “Name of this Event” column will open the pathway diagram for the selected pathway. Clicking on a UniProt identifier in the “Submitted identifiers mapping to this Event” column will open a new web page describing the reference protein record in Reactome. The results displayed in this table can be downloaded by clicking the “Results in a tab-delimited text file” link.
  6. Navigate further down the results page to the third section entitled “Reactions coloured according to the number of genes or compounds (as specified by the submitted list of identifiers)” to view a “Reaction Map” of all reactions colored by the number of participants in the reaction that were included in the submitted list.
    • The “Reaction Map” provides a classical and interactive graphical representation of Reactome reactions and pathways. A pathway is depicted as a set of interconnected arrows, each representing a reaction. "Mousing-over" a color-coded arrow will display the reaction name. Each reaction is colored according to participating number of genes specified by a list of submitted identifiers. The warmer the color, the higher the level of overrepresentation is for a given reaction. Clicking on a reaction arrow will display the selected reaction in the pathway diagrams. The “Reaction Map” image is also available for download in PNG, SVG and PDF formats.
  7. To display the final section of the overrepresentation results page, scroll down to the “Mapping from submitted identifiers to Reactions” section.
    • The table columns represent: i) the submitted UniProt ID, ii) the protein name, iii) the Reactome Reaction ID, and iv) the Reaction name. Clicking on a Reaction name link will open the pathway browser, highlighting the selected reaction in the pathway diagram.

BASIC PROTOCOL 4

USING REACTOME EXPRESSION ANALYSIS TOOL TO OVERLAY EXPRESSION DATA ONTO REACTOME PATHWAY DIAGRAMS

The Expression Analysis tool assists with the biological interpretation of large and complex gene or protein datasets through the visualization of thousands of data points in the context of Reactome pathway diagrams. To demonstrate how this tool works, this protocol will describe the analysis of a gene expression data set.

Necessary Resources

Hardware

Computer capable of supporting a Web browser and an Internet connection

Software

Any modern Web browser such as Firefox, Safari, Chrome and Internet Explorer will work to display Reactome web pages.

  1. Point the browser to the Reactome home page at http://www.reactome.org.
  2. In the sidebar of the home page, click the “Analyse Expression Data” button to launch the data entry page for the Expression Analysis.
    • The Expression analysis data entry page is similar in design to the Pathway Analysis entry page and will accept the same types of database identifiers and accession numbers. However, the Expression analysis data entry page will also support columns containing numerical values (e.g. fold change, expression data, abundance or statistical value). Data should be formatted as a tab-delimited file, where the first column contains the identifiers and subsequent columns contain the numerical values.
  3. Click the “Example” button on the “Upload expression data” page and then click “Analyse”. After a few seconds, a table of results entitled “Expression per Pathway” will appear.
    • The “Example” dataset is derived from a gene expression microarray, consisting of a column of Affymetrix Human Genome U133 Plus 2.0 Array probe identifiers, followed by five columns of normalized expression data derived from different time points (i.e. 10h_control, 10h, 14h, 18h and 24h). The “Expression per Pathway” results are presented as a sortable table that can be downloaded as a Microsoft Excel spreadsheet or a tab- or comma-separated values formats. The sortable table contains one row for each Reactome pathway and six columns: i) pathway name, ii) species, iii) total number of proteins in the pathway, iv) proteins in the pathway represented in the submitted data, a graphic representing the ratio of the values in column 3 and 4, and a “View” button that launches the Pathway Browser and displays the relevant pathway diagram.
  4. Re-sort the “% in data” column by clicking the small white arrow once (next to the column title) and then click the “View” button for “Double-Strand Break Repair” to open the Pathway Browser in a new window, as is shown in Figure 8.7.13.
    Figure 8.7.13
    The pathway browser displaying the colored physical entities that correspond to gene expression values of experimental data.
    • Be sure the web browser is configured to see pop-ups for Reactome otherwise the pathway browser will not launch.
  5. At the top-left of the pathway diagram panel is the navigation and zoom tool. Click on the second highest circle to zoom out and use the arrows to scroll about the pathway diagram (the mouse wheel also zooms).
    • The coloring will be done according to the average of the numeric values of all identifiers. The color scale automatically adjusts to fit the range represented in the dataset, with blue for the lowest expression values and red for the highest expression values. Black colored nodes represent complexes and grey colored entities are proteins or small molecules with no accompanying values in the input data set. The submitted identifier and numerical value are overlaid onto the physical entities of the pathway diagram.
  6. Click on the highest circle to zoom in and then “Mouse-over” the “DNA-PK:DNA complex” (black colored entity) to show the name of the complex. Right click on the same complex entity and select “Display Participating Molecules”.
    • A popup box should appear, with a grid of colored squares inside it, representing expression levels for the complex components. “Mousing-over” the colored boxes of the DNA-PK:DNA complex will display the names of the individual protein components of the complex, the expression values and the Affymetrix probe identifier.
  7. At the base of the diagram, you will see a bar containing the text “Experiment: 10h_control” and two arrows. Click on the forward arrow four times.
    • Some of the entities will change color, reflecting changes in their expression over the different time points.

BASIC PROTOCOL 5

COMPARE INFERRED MODEL ORGANISM AND HUMAN PATHWAYS USING THE SPECIES COMPARISON TOOL

The comparative analysis of pathways and biological process offers important information on their evolution, supports metabolic engineering and the study of human disease. Reactome uses manually-curated human pathways to electronically infer equivalent events in 20 other species. The Species Comparison tool allows users to compare the predicted model organism pathways with those of human to find pathways conserved (or not) between both species.

Necessary Resources

Hardware

Computer capable of supporting a Web browser and an Internet connection

Software

Any modern Web browser such as Firefox, Safari, Chrome and Internet Explorer will work to display Reactome web pages.

  1. Point the browser to the Reactome home page at http://www.reactome.org.
  2. In the sidebar of the home page, click the “Compare Species” button to launch the data selection page for the Species Comparison Analysis.
  3. On the “Species Comparison” page is a selection tool that reveals a drop-down list of species. Select species “Mus musculus” from the drop-down menu and click the “Apply” button. After a few minutes, a table of results entitled “Species Comparison” will appear.
    • The “Species Comparison” results are presented as a sortable table that can be downloaded for further analysis or record keeping. The table contains one row for each Reactome pathway. The columns represent: i) pathway name, ii) the species used for comparison with human, iii) number of proteins in the human pathway, iv) number of proteins inferred to exist in the comparison species, v) graphic representing the ratio of values in column 3 and 4, and vi) a view button that launches the Pathway Browser and displays the relevant pathway diagram.
  4. Click at the head of the column labeled “% in other species”. The table rows should reorder so that the pathways with the greatest overlap between mouse and human are at the top.
  5. Scroll down the results page and click the “View” button for the “Double-Strand Break Repair” pathway to launch the Pathway Browser in a new window, as is shown in Figure 8.7.14.
    Figure 8.7.14
    The pathway browser displaying the results for the comparison of human and mouse Double-Strand Break Repair pathways.
    • Be sure the web browser is configured to see pop-ups for Reactome otherwise the pathway browser will not launch.
  6. At the top-left of the pathway diagram panel is the navigation and zoom tool. Click on the second highest circle to zoom out and use the arrows to scroll about the pathway diagram (the mouse wheel also zooms).
    • Twenty two yellow colored entities are visible in the pathway diagram. These are pathway entities conserved between both species. Grey colored entities indicate that inference was not possible, used for small molecules and genomic objects that have no UniProt entry. The black colored entities represent complexes. Blue colored entities (not shown in Figure 8.7.14) indicate the protein is only known in human and that no ortholog could be found in mouse.
  7. Click on the highest circle to zoom in an then “Mouse-over” the “gamma-H2AX:NBS1 complex at the site of double-strand break” entity, right click the entity and select “Display Participating Molecules”. A popup should appear, with a grid of yellow colored squares inside it, representing complex components common to both species.
    • “Mousing-over” the yellow colored boxes of the “gamma-H2AX:NBS1 complex at the site of double-strand break” entity will display the names of the individual protein components of the complex.

COMMENTARY

Background Information

The Reactome project is a collaboration between the Ontario Institute for Cancer Research, Cold Spring Harbor Laboratory, New York University Medical Center and the European Bioinformatics Institute, and aims to collect structured information on all the biological pathways in the human (Joshi-Tope et al., 2003 [see Internet Resources for online version of this paper], Croft et al., 2011). The project is building its database by inviting faculty-level laboratory researchers to contribute a pathway or sub-pathway to the database. To achieve this, contributors are instructed on the use of a specialized piece of authoring software and are assisted in their work by a staff of curators based at the four institutions. After authoring, each pathway is checked for consistency both manually and automatically and then sent to one or more external peer reviewers. The pathway is published to the Web when all internal and external peer review is satisfactory. In many ways, the project resembles a review journal, except that its output is a database rather than a series of papers.

Reactome uses a simple scheme for describing biological pathways in which all molecular interactions are defined as reactions. A reaction takes a series of inputs and transforms them into a series of outputs, where inputs and outputs are any type of molecular compound. For example, the reaction in which proinsulin is cleaved to form the α and β chains takes as its input proinsulin, and produces the insulin α and β polypeptides.

Representing biology as a set of molecular reactions turns out to have broad expressive power, but sometimes the results are disorienting. For example, the reaction in which insulin binds to the insulin receptor takes as its inputs extracellular insulin and the extracellular portion of the insulin receptor, and produces as its output the complex of insulin and its receptor, which, in Reactome, is represented as a distinct molecular entity. The reaction by which extracellular glucose is transported into the cytosol transforms extracellular D-glucose into intracellular D-glucose. Hence, a search of Reactome for “D-glucose” will find both D-glucose (intracellular cytosolic) and D-glucose (extracellular).

In addition to inputs and outputs, Reactome reactions have a discrete set of additional attributes. For those reactions that are mediated by catalysts, the catalyst enzyme and its activity are noted. Reactions are also annotated using the cellular compartment in which they occur. While Reactome does not pretend to be a definitive source of information on the cellular location of macromolecules, its data model is set up to work smoothly with future databases of subcellular localization; information on the subcellular location of macromolecules will help automated path-prediction software distinguish plausible pathways from impossible ones. Finally, each reaction is supported by literature citations, either those reporting experiments performed directly in the human system, or those performed on model systems when there is high-quality protein similarity data to suggest that the same reaction is likely to occur in humans.

In order to assist with the comprehensibility of the resource, the reactions are annotated with text narratives and illustrations, and are organized into a series of discrete goal-driven pathways.

Reactome is related to several other pathway databases, but has distinct methodologies and aims. The Human Protein Reference Database (HPRD; Peri et al., 2003) is also a hand-curated database of biological pathways. The HPRD focus, however, is to annotate individual proteins and their physical and genetic interactions. HPRD contains information derived from large-scale screening studies as well as individual papers that report pairwise interactions. A result of this methodology is that many of the interactions found in HPRD are speculative and subject to change. Reactome takes a much more conservative approach; it represents far fewer molecular interactions than HPRD does, but they are more likely to be correct and less subject to revision.

HumanCyc, NCI-PID, Panther Pathways and INOH (Krieger et al., 2004, Schaefer et al., 2009, Mi et al., 2010, http://www.inoh.org) are reaction centric pathway databases that are similar to Reactome, although the user interface and underlying database technology are quite different in detail. HumanCyc primarily focuses on intermediate metabolism, whereas Panther, NCI-PID and INOH emphasize signaling pathways. These databases allow their pathway data, but not their source code or software, to be used and redistributed freely.

The Kyoto Encyclopedia of Genes and Genomes, or KEGG (Kanehisa et al., 2004) features an extensive set of biological pathway charts. Like HumanCyc, KEGG focuses on intermediate metabolism rather than higher-level pathways. Its data model differs fundamentally from Reactome’s by representing the motivating force of all reactions in the form of catalyst activities via Enzyme Commission EC numbers. Because there is not a one-to-one mapping between EC activity and polypeptide, it can be problematic to relate a protein represented in SwissProt to a reaction represented in KEGG.

Finally, the BioCarta project (http://www.biocarta.com) represents human biology as a series of colorful high-resolution diagrams. Unlike Reactome or the other projects mentioned earlier, these diagrams are the end product of the project; there is no underlying database. The focus of BioCarta is to be an education and visualization tool, rather than to support data mining and pattern discovery.

Wikipathways (Pico et al., 2008) is a community-driven pathway database, built upon the foundations of Wikipedia, that allows community members to freely contribute and edit pathway diagrams. The data model underlying these pathway diagrams is not as well developed as in Reactome, and represents the molecular entities participating in a pathway as a simple list of names.

The Reactome database is far from complete. At the time this module was written, Reactome covered about 25% of the human genome, a number conservatively estimated by dividing the number of human SwissProt entries that take part in Reactome reactions by the total number of human entries in the entire SwissProt database. Because all of the other pathway databases mentioned here are also incomplete, the biologist faces the daunting task of visiting each of these sites in an attempt to fill in the holes in one database’s coverage with information from the others. The BioPAX project (http://www.biopax.org) has improved this situation by creating a standardized file format for representing biological pathways and reactions. Reactome and many of the other pathway databases have committed to exporting their data in BioPAX format. This has enabled databases to exchange pathways and to co-curate data, thereby accelerating the rate in which the gaps in pathway knowledge are closed.

Reactome is a fully open access and open-source project. All the software developed for use in Reactome is available for download and redistribution, and the data itself is available in a variety of formats. The Download link on the Reactome Web site provides instructions for obtaining data and software.

The Reactome dataset is available as relational database tables in a format compatible with MySQL (http//www.mysql.com; UNIT 9.2) and as files compatible with the Protégé-2000 knowledgebase editor (http://protege.stanford.edu) and available as tab-delimited text, BioPAX, SBML (http://www.sbml.org) and PSI-MITAB (http://www.psidev.info) files.

Footnotes

Internet Resources

http://www.biocarta.com

The Biocarta human pathways project.

http://www.biopax.org

BioPAX: Biological Pathways Exchange. Standardizing the file format for representing biological pathways.

http://www.inoh.org

INOH: Integrating Network Objects with Hierarchies

http://www.reactome.org

The Reactome home page.

http://www.psidev.info

PSI-MITAB: Proteomics Standards Initiative-Molecular Interactions. Defining community standards for molecular interaction data representation.

http://www.sbml.org

SBML: Systems Biology Markup Language. Standardizing the file format for representing models of biological pathways.

http://www.reactome.org/gk_symposium.pdf

Online version of Joshi-Tope et al. (2003).

Literature Cited

  • Croft D, O'Kelly G, Wu G, Haw R, Gillespie M, Matthews L, Caudy M, Garapati P, Gopinath G, Jassal B, Jupe S, Kalatskaya I, Mahajan S, May B, Ndegwa N, Schmidt E, Shamovsky V, Yung C, Birney E, Hermjakob H, D'Eustachio P, Stein L. Reactome: a database of reactions, pathways and biological processes. Nucleic Acids Res. 2011;39:D691–D697. [PMC free article] [PubMed]
  • Joshi-Tope G, Vastrik I, Gopinath GR, Matthews L, Schmidt E, Gillespie M, D’Eustachio P, Jassal B, Lewis S, Wu G, Birney E, Stein L. The Genome Knowledgebase: A Resource for Biologists and Bioinformaticists. Cold Spring Harbor, N.Y.: Cold Spring Harbor Symposia on Quantitative Biology LXVIII:237–244. Cold Spring Harbor Laboratory Press; 2003. [PubMed]
  • Kanehisa M, Goto S, Kawashima S, Okuno Y, Hattori M. The KEGG resource for deciphering the genome. Nucleic Acids Res. 2004;32:D277–D280. [PMC free article] [PubMed]
  • Krieger CJ, Zhang P, Mueller LA, Wang A, Paley S, Arnaud M, Pick J, Rhee SY, Karp PD. MetaCyc: A multiorganism database of metabolic pathways and enzymes. Nucleic Acids Res. 2004;32:D438–D442. [PMC free article] [PubMed]
  • Mi H, Dong Q, Muruganujan A, Gaudet P, Lewis S, Thomas PD. PANTHER version 7: improved phylogenetic trees, orthologs and collaboration with the Gene Ontology Consortium. Nucleic Acids Res. 2009;38:D204–D210. [PMC free article] [PubMed]
  • Peri S, Navarro JD, Amanchy R, Kristiansen TZ, Jonnalagadda CK, Surendranath V, Niranjan V, Muthusamy B, Gandhi TK, Gronborg M, Ibarrola N, Deshpande N, Shanker K, Shivashankar HN, Rashmi BP, Ramya MA, Zhao Z, Chandrika KN, Padma N, Harsha HC, Yatish AJ, Kavitha MP, Menezes M, Choudhury DR, Suresh S, Ghosh N, Saravana R, Chandran S, Krishna S, Joy M, Anand SK, Madavan V, Joseph A, Wong GW, Schiemann WP, Constantinescu SN, Huang L, Khosravi-Far R, Steen H, Tewari M, Ghaffari S, Blobe GC, Dang CV, Garcia JG, Pevsner J, Jensen ON, Roepstorff P, Deshpande KS, Chinnaiyan AM, Hamosh A, Chakravarti A, Pandey A. Development of human protein reference database as an initial platform for approaching systems biology in humans. Genome Res. 2003;10:2363–2371. [PubMed]
  • Pico AR, Kelder T, van Iersel MP, Hanspers K, Conklin BR, Evelo C. WikiPathways: pathway editing for the people. PLoS Biol. 2008;22:e184. [PMC free article] [PubMed]
  • Schaefer CF, Anthony K, Krupa S, Buchoff J, Day M, Hannay T, Buetow KH. PID: the Pathway Interaction Database. Nucleic Acids Res. 2008;37:D674–D679. [PMC free article] [PubMed]