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UniProt

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(Redirected fromTrEMBL)
Not to be confused withUniPro.
UniProt
Content
DescriptionUniProtis theUniversalProtein resource, a central repository ofproteindata created by combining the Swiss-Prot, TrEMBL and PIR-PSDdatabases.
Data types
captured		Protein annotation
OrganismsAll
Contact
Research centerEMBL-EBI,UK;SIB,Switzerland;PIR,US.
Primary citationUniProt Consortium[1]
Access
Data formatCustom flat file,FASTA,GFF,RDF,XML.
Websitewww.uniprot.org
www.uniprot.org/news/
Download URLwww.uniprot.org/downloads& for downloading complete data setsftp.uniprot.org
Web serviceURLYes –JAVAAPIsee infohere&RESTsee infohere
Tools
WebAdvanced search,BLAST,ClustalO, bulk retrieval/download, ID mapping
Miscellaneous
LicenseCreative CommonsAttribution-NoDerivs
VersioningYes
Data release
frequency		8 weeks
Curation policyYes – manual and automatic. Rules for automatic annotation generated by database curators and computational algorithms.
Bookmarkable
entities		Yes – both individual protein entries and searches

UniProtis a freely accessible database ofprotein sequenceand functional information, many entries being derived fromgenome sequencing projects.It contains a large amount of information about the biological function of proteins derived from the research literature. It is maintained by the UniProt consortium, which consists of several Europeanbioinformaticsorganisations and a foundation fromWashington, DC,USA.

The UniProt consortium

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The UniProt consortium comprises theEuropean Bioinformatics Institute(EBI), theSwiss Institute of Bioinformatics(SIB), and theProtein Information Resource(PIR). EBI, located at theWellcome Trust Genome Campusin Hinxton, UK, hosts a large resource of bioinformatics databases and services. SIB, located in Geneva, Switzerland, maintains theExPASy(Expert Protein Analysis System) servers that are a central resource for proteomics tools and databases. PIR, hosted by the National Biomedical Research Foundation (NBRF) at the Georgetown University Medical Center in Washington, DC, US, is heir to the oldest protein sequence database,Margaret Dayhoff's Atlas of Protein Sequence and Structure, first published in 1965.[2]In 2002, EBI, SIB, and PIR joined forces as the UniProt consortium.[3]

The roots of the UniProt databases

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Each consortium member is heavily involved in protein database maintenance and annotation. Until recently, EBI and SIB together produced the Swiss-Prot and TrEMBL databases, while PIR produced the Protein Sequence Database (PIR-PSD).[4][5][6]These databases coexisted with differingprotein sequencecoverage and annotation priorities.

Swiss-Prot was created in 1986 byAmos Bairochduring his PhD and developed by theSwiss Institute of Bioinformaticsand subsequently developed byRolf Apweilerat theEuropean Bioinformatics Institute.[7][8][9]Swiss-Prot aimed to provide reliable protein sequences associated with a high level of annotation (such as the description of the function of a protein, itsdomainstructure,post-translational modifications,variants, etc.), a minimal level ofredundancyand high level of integration with other databases. Recognizing that sequence data were being generated at a pace exceeding Swiss-Prot's ability to keep up, TrEMBL (Translated EMBL Nucleotide Sequence Data Library) was created to provide automated annotations for those proteins not in Swiss-Prot. Meanwhile, PIR maintained the PIR-PSD and related databases, includingiProClass,a database of protein sequences and curated families.

The consortium members pooled their overlapping resources and expertise, and launched UniProt in December 2003.[10]

Organization of the UniProt databases

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UniProt provides four core databases: UniProtKB (with sub-parts Swiss-Prot and TrEMBL), UniParc, UniRef and Proteome.

UniProtKB

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UniProt Knowledgebase (UniProtKB) is a protein database partially curated by experts, consisting of two sections: UniProtKB/Swiss-Prot (containing reviewed, manually annotated entries) and UniProtKB/TrEMBL (containing unreviewed, automatically annotated entries).[11]As of 22 February 2023,release "2023_01" of UniProtKB/Swiss-Prot contains 569,213 sequence entries (comprising 205,728,242 amino acids abstracted from 291,046 references) and release "2023_01" of UniProtKB/TrEMBL contains 245,871,724 sequence entries (comprising 85,739,380,194 amino acids).[12]

UniProtKB/Swiss-Prot

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UniProtKB/Swiss-Prot is a manually annotated, non-redundant protein sequence database. It combines information extracted from scientific literature andbiocurator-evaluated computational analysis. The aim of UniProtKB/Swiss-Prot is to provide all known relevant information about a particular protein. Annotation is regularly reviewed to keep up with current scientific findings. The manual annotation of an entry involves detailed analysis of the protein sequence and of the scientific literature.[13]

Sequences from the samegeneand the samespeciesare merged into the same database entry. Differences between sequences are identified, and their cause documented (for examplealternative splicing,natural variation,incorrectinitiationsites, incorrectexonboundaries,frameshifts,unidentified conflicts). A range of sequence analysis tools is used in the annotation of UniProtKB/Swiss-Prot entries. Computer-predictions are manually evaluated, and relevant results selected for inclusion in the entry. These predictions include post-translational modifications,transmembrane domainsandtopology,signal peptides,domain identification, andprotein familyclassification.[13][14]

Relevant publications are identified by searching databases such asPubMed.The full text of each paper is read, and information is extracted and added to the entry. Annotation arising from the scientific literature includes, but is not limited to:[10][13][14]

Annotated entries undergo quality assurance before inclusion into UniProtKB/Swiss-Prot. When new data becomes available, entries are updated.

UniProtKB/TrEMBL

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UniProtKB/TrEMBL contains high-quality computationally analyzed records, which are enriched with automatic annotation. It was introduced in response to increased dataflow resulting from genome projects, as the time- and labour-consuming manual annotation process of UniProtKB/Swiss-Prot could not be broadened to include all available protein sequences.[10]The translations of annotated coding sequences in theEMBL-Bank/GenBank/DDBJ nucleotide sequence databaseare automatically processed and entered in UniProtKB/TrEMBL. UniProtKB/TrEMBL also contains sequences fromPDB,and from gene prediction, includingEnsembl,RefSeqandCCDS.[15]Since 22 July 2021 it also includes structures predicted withAlphaFold2.[16]

UniParc

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UniProt Archive (UniParc) is a comprehensive and non-redundant database, which contains all the protein sequences from the main, publicly available protein sequence databases.[17]Proteins may exist in several different source databases, and in multiple copies in the same database. In order to avoid redundancy, UniParc stores each unique sequence only once. Identical sequences are merged, regardless of whether they are from the same or different species. Each sequence is given a stable and unique identifier (UPI), making it possible to identify the same protein from different source databases. UniParc contains only protein sequences, with no annotation. Database cross-references in UniParc entries allow further information about the protein to be retrieved from the source databases. When sequences in the source databases change, these changes are tracked by UniParc and history of all changes is archived.

Source databases

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Currently UniParc contains protein sequences from the following publicly available databases:

UniRef

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The UniProt Reference Clusters (UniRef) consist of three databases of clustered sets of protein sequences from UniProtKB and selected UniParc records.[20]The UniRef100 database combines identical sequences and sequence fragments (from anyorganism) into a single UniRef entry. The sequence of a representative protein, theaccession numbersof all the merged entries and links to the corresponding UniProtKB and UniParc records are displayed. UniRef100 sequences are clustered using the CD-HITalgorithmto build UniRef90 and UniRef50.[20][21]Each cluster is composed of sequences that have at least 90% or 50% sequence identity, respectively, to the longest sequence. Clustering sequences significantly reduces database size, enabling faster sequence searches.

UniRef is available from theUniProt FTP site.

Funding

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UniProt is funded by grants from theNational Human Genome Research Institute,theNational Institutes of Health(NIH), theEuropean Commission,the Swiss Federal Government through the Federal Office of Education and Science,NCI-caBIG,and the US Department of Defense.[11]

References

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  1. ^UniProt, Consortium. (January 2015)."UniProt: a hub for protein information".Nucleic Acids Research.43(Database issue): D204–12.doi:10.1093/nar/gku989.PMC4384041.PMID25348405.
  2. ^Dayhoff, Margaret O. (1965).Atlas of protein sequence and structure.Silver Spring, Md: National Biomedical Research Foundation.
  3. ^"2002 Release: NHGRI Funds Global Protein Database".National Human Genome Research Institute (NHGRI).Archived fromthe originalon 24 September 2015.Retrieved14 April2018.
  4. ^O'Donovan, C.; Martin, M. J.; Gattiker, A.; Gasteiger, E.; Bairoch, A.; Apweiler, R. (2002)."High-quality protein knowledge resource: SWISS-PROT and TrEMBL".Briefings in Bioinformatics.3(3): 275–284.doi:10.1093/bib/3.3.275.PMID12230036.
  5. ^Wu, C. H.; Yeh, L. S.; Huang, H.; Arminski, L.; Castro-Alvear, J.; Chen, Y.; Hu, Z.; Kourtesis, P.; Ledley, R. S.; Suzek, B. E.; Vinayaka, C. R.; Zhang, J.; Barker, W. C. (2003)."The Protein Information Resource".Nucleic Acids Research.31(1): 345–347.doi:10.1093/nar/gkg040.PMC165487.PMID12520019.
  6. ^Boeckmann, B.; Bairoch, A.; Apweiler, R.; Blatter, M. C.; Estreicher, A.; Gasteiger, E.; Martin, M. J.; Michoud, K.; O'Donovan, C.; Phan, I.; Pilbout, S.; Schneider, M. (2003)."The SWISS-PROT protein knowledgebase and its supplement TrEMBL in 2003".Nucleic Acids Research.31(1): 365–370.doi:10.1093/nar/gkg095.PMC165542.PMID12520024.
  7. ^Bairoch, A.; Apweiler, R. (1996)."The SWISS-PROT protein sequence data bank and its new supplement TREMBL".Nucleic Acids Research.24(1): 21–25.doi:10.1093/nar/24.1.21.PMC145613.PMID8594581.
  8. ^Bairoch, A. (2000)."Serendipity in bioinformatics, the tribulations of a Swiss bioinformatician through exciting times!".Bioinformatics.16(1): 48–64.doi:10.1093/bioinformatics/16.1.48.PMID10812477.
  9. ^Séverine Altairac, "Naissance d’une banque de données: Interview du prof. Amos Bairoch".Protéines à la Une,August 2006.ISSN1660-9824.
  10. ^abcApweiler, R.; Bairoch, A.; Wu, C. H. (2004). "Protein sequence databases".Current Opinion in Chemical Biology.8(1): 76–80.doi:10.1016/j.cbpa.2003.12.004.PMID15036160.
  11. ^abUniprot, C. (2009)."The Universal Protein Resource (UniProt) in 2010".Nucleic Acids Research.38(Database issue): D142–D148.doi:10.1093/nar/gkp846.PMC2808944.PMID19843607.
  12. ^"UniProtKB/Swiss-Prot Release 2023_01 statistics".web.expasy.org.Retrieved31 March2023.
  13. ^abc"How do we manually annotate a UniProtKB entry?".UniProt.September 21, 2011. Archived fromthe originalon Dec 13, 2013.Retrieved14 April2018.
  14. ^abApweiler, R.; Bairoch, A.; Wu, C. H.; Barker, W. C.; Boeckmann, B.; Ferro, S.; Gasteiger, E.; Huang, H.; Lopez, R.; Magrane, M.; Martin, M. J.; Natale, D. A.; o’Donovan, C.; Redaschi, N.; Yeh, L. S. (2004)."UniProt: The Universal Protein knowledgebase".Nucleic Acids Research.32(90001): 115D–1119.doi:10.1093/nar/gkh131.PMC308865.PMID14681372.
  15. ^"Where do the UniProtKB protein sequences come from?".UniProt.September 21, 2011. Archived fromthe originalon Dec 15, 2013.Retrieved14 April2018.
  16. ^Hassabis, Demis (22 July 2022)."Putting the power of AlphaFold into the world's hands".Deepmind.Archivedfrom the original on 24 July 2021.Retrieved24 July2021.
  17. ^Leinonen, R.; Diez, F. G.; Binns, D.; Fleischmann, W.; Lopez, R.; Apweiler, R. (2004)."UniProt archive".Bioinformatics.20(17): 3236–3237.doi:10.1093/bioinformatics/bth191.PMID15044231.Archived(PDF)from the original on Mar 30, 2024.
  18. ^"Protein Research Foundation".
  19. ^ftp://ftp.isrec.isb-sib.ch/pub/databases/trome[permanent dead link]
  20. ^abSuzek, B. E.; Huang, H.; McGarvey, P.; Mazumder, R.; Wu, C. H. (2007). "UniRef: Comprehensive and non-redundant UniProt reference clusters".Bioinformatics.23(10): 1282–1288.doi:10.1093/bioinformatics/btm098.PMID17379688.
  21. ^Li, W.; Jaroszewski, L.; Godzik, A. (2001). "Clustering of highly homologous sequences to reduce the size of large protein databases".Bioinformatics.17(3): 282–283.doi:10.1093/bioinformatics/17.3.282.PMID11294794.
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