Skip to content
2000
  1. Home
  2. A-Z Publications
  3. Current Indian Science
  4. Volume 2, Issue 1
  5. Article
Volume 2, Issue 1
  • ISSN: 2210-299X
  • E-ISSN: 2210-3007
file format pdf download PDF
side by side viewer icon HTML

Abstract

The technological advances in mass spectrometry and associated computational tools have enabled the development of proteome atlases and comprehensive catalogs of proteome snapshots that have gradually transformed biomedical research. These proteome catalogs in specific biological contexts, which focused initially on model organisms, have now expanded their scope to encompass diverse organisms, tissues, and experimental conditions. These atlases, such as the Human Protein Atlas (HPA), Peptide Atlas, and Global Proteome Machine Database (GPMDB), . provide invaluable insights into protein expression, subcellular localization, interactions, modifications, and functions. They aid in understanding biological processes, identifying disease biomarkers, and discovering novel therapeutic targets. Despite their potential, proteome atlases face challenges like data completeness, integration with other omics data, and ethical considerations. Addressing these challenges is vital for further progress. Proteome atlases serve as indispensable resources, driving biomedical discovery and innovation.

© 2024 The Author(s). Published by Bentham Science Publisher.
This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Loading

Article metrics loading...

/content/journals/cis/10.2174/012210299X320402240715065917
2024-07-22
2025-03-01

  • From This Site

    /content/journals/cis/10.2174/012210299X320402240715065917
    dcterms_title,dcterms_subject,pub_keyword
    -contentType:Contributor -contentType:Concept -contentType:Institution
    10
    5
The full text of this item is not currently available.

References

  1. DeutschE.W. LamH. AebersoldR. PeptideAtlas: A resource for target selection for emerging targeted proteomics workflows.EMBO Rep.20089542943410.1038/embor.2008.5618451766
     [Google Scholar]
  2. KusebauchU. CampbellD.S. DeutschE.W. ChuC.S. SpicerD.A. BrusniakM.Y. SlagelJ. SunZ. StevensJ. GrimesB. ShteynbergD. HoopmannM.R. BlattmannP. RatushnyA.V. RinnerO. PicottiP. CarapitoC. HuangC.Y. KapousouzM. LamH. TranT. DemirE. AitchisonJ.D. SanderC. HoodL. AebersoldR. MoritzR.L. Human SRMAtlas: A resource of targeted assays to quantify the complete human proteome.Cell2016166376677810.1016/j.cell.2016.06.04127453469
     [Google Scholar]
  3. LamK.H.B. FaustK. YinR. FialaC. DiamandisP. The brain protein atlas: A conglomerate of proteomics datasets of human neural tissue.Proteomics20222223-24220012710.1002/pmic.20220012735971647
     [Google Scholar]
  4. ThulP.J. LindskogC. The human protein atlas: A spatial map of the human proteome.Protein Sci.201827123324410.1002/pro.330728940711
     [Google Scholar]
  5. UhlénM. BjörlingE. AgatonC. SzigyartoC.A.K. AminiB. AndersenE. AnderssonA.C. AngelidouP. AsplundA. AsplundC. BerglundL. BergströmK. BrumerH. CerjanD. EkströmM. ElobeidA. ErikssonC. FagerbergL. FalkR. FallJ. ForsbergM. BjörklundM.G. GumbelK. HalimiA. HallinI. HamstenC. HanssonM. HedhammarM. HerculesG. KampfC. LarssonK. LindskogM. LodewyckxW. LundJ. LundebergJ. MagnussonK. MalmE. NilssonP. ÖdlingJ. OksvoldP. OlssonI. ÖsterE. OttossonJ. PaavilainenL. PerssonA. RiminiR. RockbergJ. RunesonM. SivertssonÅ. SköllermoA. SteenJ. StenvallM. SterkyF. StrömbergS. SundbergM. TegelH. TourleS. WahlundE. WaldénA. WanJ. WernérusH. WestbergJ. WesterK. WrethagenU. XuL.L. HoberS. PonténF. A human protein atlas for normal and cancer tissues based on antibody proteomics.Mol. Cell. Proteomics20054121920193210.1074/mcp.M500279‑MCP20016127175
     [Google Scholar]
  6. BockC. BoutrosM. CampJ.G. ClarkeL. CleversH. KnoblichJ.A. LiberaliP. RegevA. RiosA.C. StegleO. StunnenbergH.G. TeichmannS.A. TreutleinB. VriesR.G.J. The organoid cell atlas.Nat. Biotechnol.2021391131710.1038/s41587‑020‑00762‑x33384458
     [Google Scholar]
  7. YadavA.K. BanerjeeS.K. DasB. ChaudharyK. Editorial: Systems biology and omics approaches for understanding complex disease biology.Front. Genet.20221389681810.3389/fgene.2022.89681835495146
     [Google Scholar]
  8. TolaniP. GuptaS. YadavK. AggarwalS. YadavA.K. Big data, integrative omics and network biology.Adv. Protein Chem. Struct. Biol.202112712716010.1016/bs.apcsb.2021.03.00634340766
     [Google Scholar]
  9. AdhikariS. NiceE.C. DeutschE.W. LaneL. OmennG.S. PenningtonS.R. PaikY.K. OverallC.M. CorralesF.J. CristeaI.M. Van EykJ.E. UhlénM. LindskogC. ChanD.W. BairochA. WaddingtonJ.C. JusticeJ.L. LaBaerJ. RodriguezH. HeF. KostrzewaM. PingP. GundryR.L. StewartP. SrivastavaS. SrivastavaS. NogueiraF.C.S. DomontG.B. VandenbrouckY. LamM.P.Y. WennerstenS. VizcainoJ.A. WilkinsM. SchwenkJ.M. LundbergE. BandeiraN. Marko-VargaG. WeintraubS.T. PineauC. KusebauchU. MoritzR.L. AhnS.B. PalmbladM. SnyderM.P. AebersoldR. BakerM.S. A high-stringency blueprint of the human proteome.Nat. Commun.2020111530110.1038/s41467‑020‑19045‑933067450
     [Google Scholar]
  10. SmithL.M. AgarJ.N. Chamot-RookeJ. DanisP.O. GeY. LooJ.A. Paša-TolićL. TsybinY.O. KelleherN.L. The Human Proteoform Project: Defining the human proteome.Sci. Adv.2021746eabk073410.1126/sciadv.abk073434767442
     [Google Scholar]
  11. CraigR. CortensJ.P. BeavisR.C. Open source system for analyzing, validating, and storing protein identification data.J. Proteome Res.2004361234124210.1021/pr049882h15595733
     [Google Scholar]
  12. HuangQ. SzklarczykD. WangM. SimonovicM. von MeringC. PaxDb 5.0: Curated protein quantification data suggests adaptive proteome changes in yeasts.Mol. Cell. Proteomics2023221010064010.1016/j.mcpro.2023.10064037659604
     [Google Scholar]
  13. ChoiM. CarverJ. ChivaC. TzourosM. HuangT. TsaiT.H. PullmanB. BernhardtO.M. HüttenhainR. TeoG.C. Perez-RiverolY. MuntelJ. MüllerM. GoetzeS. PavlouM. VerschuerenE. WollscheidB. NesvizhskiiA.I. ReiterL. DunkleyT. SabidóE. BandeiraN. VitekO. MassIVE.quant: A community resource of quantitative mass spectrometry–based proteomics datasets.Nat. Methods2020171098198410.1038/s41592‑020‑0955‑032929271
     [Google Scholar]
  14. BoutetE. LieberherrD. TognolliM. SchneiderM. BansalP. BridgeA.J. PouxS. BougueleretL. XenariosI. UniProtKB/swiss-prot, the manually annotated section of the uniprot knowledgebase: How to use the entry view.Methods Mol. Biol.20161374235410.1007/978‑1‑4939‑3167‑5_226519399
     [Google Scholar]
  15. Zahn-ZabalM. MichelP.A. GateauA. NikitinF. SchaefferM. AudotE. GaudetP. DuekP.D. TeixeiraD. Rech de LavalV. SamarasingheK. BairochA. LaneL. The neXtProt knowledgebase in 2020: Data, tools and usability improvements.Nucleic Acids Res.202048D1D328D33431724716
     [Google Scholar]
  16. Dyring-AndersenB. LøvendorfM.B. CosciaF. SantosA. MøllerL.B.P. ColaçoA.R. NiuL. BzorekM. DollS. AndersenJ.L. ClarkR.A. SkovL. TeunissenM.B.M. MannM. Spatially and cell-type resolved quantitative proteomic atlas of healthy human skin.Nat. Commun.2020111558710.1038/s41467‑020‑19383‑833154365
     [Google Scholar]
  17. RieckmannJ.C. GeigerR. HornburgD. WolfT. KvelerK. JarrossayD. SallustoF. Shen-OrrS.S. LanzavecchiaA. MannM. MeissnerF. Social network architecture of human immune cells unveiled by quantitative proteomics.Nat. Immunol.201718558359310.1038/ni.369328263321
     [Google Scholar]
  18. HornbeckP.V. ZhangB. MurrayB. KornhauserJ.M. LathamV. SkrzypekE. PhosphoSitePlus, 2014: Mutations, PTMs and recalibrations.Nucleic Acids Res.201543D1D512D52010.1093/nar/gku126725514926
     [Google Scholar]
  19. AggarwalS. The language of posttranslational modifications and deciphering it from proteomics data.Transcription and Translation in Health and Disease. GargM. SethiG. PandeyA.K. Cambridge, MassachusettsAcademic Press202310913610.1016/B978‑0‑323‑99521‑4.00012‑X
     [Google Scholar]
  20. AggarwalS. TolaniP. GuptaS. YadavA.K. Posttranslational modifications in systems biology.Adv. Protein Chem. Struct. Biol.20211279312610.1016/bs.apcsb.2021.03.00534340775
     [Google Scholar]
  21. MinguezP. LetunicI. ParcaL. Garcia-AlonsoL. DopazoJ. Huerta-CepasJ. BorkP. PTMcode v2: A resource for functional associations of post-translational modifications within and between proteins.Nucleic Acids Res.201543D1D494D50210.1093/nar/gku108125361965
     [Google Scholar]
  22. AggarwalS. BanerjeeS.K. TalukdarN.C. YadavA.K. Post-translational modification crosstalk and hotspots in sirtuin interactors implicated in cardiovascular diseases.Front. Genet.20201135610.3389/fgene.2020.0035632425973
     [Google Scholar]
/content/journals/cis/10.2174/012210299X320402240715065917
Loading
What are Proteome Atlases good for?
Curr. Indian Sci. 2, e2210299X320402 (2024); https://doi.org/10.2174/012210299X320402240715065917
/content/journals/cis/10.2174/012210299X320402240715065917
/content/journals/cis/10.2174/012210299X320402240715065917
Loading

Data & Media loading...


  • Article Type:     Research Article
Keyword(s): Biomarkers; Drug target; Interactions; Mass spectrometry; Proteoforms; Proteome atlas; Systems biology; Therapeutics

Most Cited Most Cited RSS feed

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error
Please enter a valid_number test