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Tissue-based map of the human proteome
KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology.ORCID iD: 0000-0002-4858-8056
KTH, Centres, Science for Life Laboratory, SciLifeLab.ORCID iD: 0000-0003-0198-7137
KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology.
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2015 (English)In: Science, ISSN 0036-8075, E-ISSN 1095-9203, Vol. 347, no 6220, p. 1260419-Article in journal (Refereed) Published
Abstract [en]

Resolving the molecular details of proteome variation in the different tissues and organs of the human body will greatly increase our knowledge of human biology and disease. Here, we present a map of the human tissue proteome based on an integrated omics approach that involves quantitative transcriptomics at the tissue and organ level, combined with tissue microarray-based immunohistochemistry, to achieve spatial localization of proteins down to the single-cell level. Our tissue-based analysis detected more than 90% of the putative protein-coding genes. We used this approach to explore the human secretome, the membrane proteome, the druggable proteome, the cancer proteome, and the metabolic functions in 32 different tissues and organs. All the data are integrated in an interactive Web-based database that allows exploration of individual proteins, as well as navigation of global expression patterns, in all major tissues and organs in the human body.

Place, publisher, year, edition, pages
2015. Vol. 347, no 6220, p. 1260419-
Keywords [en]
isoprotein, membrane protein, protein, proteome, tumor protein
National Category
Biological Sciences
Identifiers
URN: urn:nbn:se:kth:diva-160035DOI: 10.1126/science.1260419ISI: 000348225800036PubMedID: 25613900Scopus ID: 2-s2.0-84920269464OAI: oai:DiVA.org:kth-160035DiVA, id: diva2:788319
Funder
Science for Life Laboratory - a national resource center for high-throughput molecular bioscienceKnut and Alice Wallenberg Foundation
Note

QC 20150216

Available from: 2015-02-13 Created: 2015-02-13 Last updated: 2024-03-15Bibliographically approved
In thesis
1. Towards a deeper understanding of the human brain
Open this publication in new window or tab >>Towards a deeper understanding of the human brain
2018 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Identifying the proteome variation in different parts of the body provides fundamental molecular details, enabling further findings and mapping of tissue specific proteins. By combining quantitative transcriptomics with qualitative antibody based proteomics, the Human Protein Atlas (HPA) project aims to protein profile each human protein-coding gene. Genes with varying expression levels in the different tissue types are categorized as tissue elevated in one tissue compared to others, thus connecting genes to potential tissue specific functions. This thesis focuses on the most complex organ in the human body, the brain. With its billions of neurons specifically organized and interconnected, the ability of not only controlling the body but also responsible for higher cognitive functions, the brain is still not fully understood.

In my search for brain important proteins, genes were classified at different stages based on expression levels. In Paper I and II the transcriptome of cerebral cortex was compared with peripheral organs to classify genes with elevated expression in the brain. Brain expression information was expanded by including external data (GTEx and FANTOM5) into the analysis, in Paper III. Thereafter, in Paper IV, the three datasets (HPA, GTEx and FANTOM5) were aligned and combined, enabling a consensus classification with an improved representation of the brain complexity. The most recent classification provided whole body gene expression profiles and out of the 19,670 protein-coding genes, 2,501 were expressed at elevated levels in the brain compared to the other tissue types. Twelve individual regions represented the brain as an organ, and were further analyzed and compared for regional classification of gene expression. One thousand genes showed regional variation in expression level, thus classified as regionally elevated within the brain. Interestingly, less than 500 of the genes classified as brain elevated on the whole body level, and were also regionally elevated in the brain. Many genes with regionally variable expression within the brain showed higher expression in a peripheral organ than in the brain when comparing whole body expression. Based on elevated expression in the brain or brain regions, more than 3,000 genes were suggested to be of high importance to the brain.

In addition, this high-throughput approach to combine transcriptomics and protein profiles in tissues and cells further generated new knowledge in several different other aspects: better understanding of uncharacterized and “missing proteins” (Paper III), validation of an antibody improving classification of pituitary adenoma (Paper V) and in Paper VI the possibility to explore cancer specific expression in relation to clinical data and normal tissue expression.

There are multiple diseases of the brain that are poorly understood on both a cellular and molecular level. While my work mainly focused on identifying and understanding the molecular organization of the normal brain, the ultimate goal of mapping and studying the normal expression baseline is to understand the molecular aspects of disease and identify ways to prevent, treat and cure diseases.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2018. p. 83
Series
TRITA-CBH-FOU ; 50
Keywords
Brain, organization, RNA, classification, mapping, proteins, antibodies
National Category
Medical Biotechnology (with a focus on Cell Biology (including Stem Cell Biology), Molecular Biology, Microbiology, Biochemistry or Biopharmacy)
Research subject
Biotechnology
Identifiers
urn:nbn:se:kth:diva-235670 (URN)978-91-7729-983-7 (ISBN)
Public defence
2018-11-15, Gard aulan, Nobels väg 18, Solna, 10:00 (English)
Opponent
Supervisors
Note

QC 20181018

Available from: 2018-10-18 Created: 2018-10-17 Last updated: 2022-06-26Bibliographically approved

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Uhlén, MathiasFagerberg, LinnHallström, Björn MOksvold, PerSivertsson, ÅsaSjöstedt, EvelinaLundberg, EmmaSzigyarto, Cristina Al-KhaliliOdeberg, JacobTakanen, Jenny OttossonHober, SophiaAlm, ToveBerling, HolgerTegel, HannaRockberg, JohanNilsson, PeterSchwenk, Jochen MHamsten, Maricavon Feilitzen, KalleForsberg, MattiasPersson, LukasJohansson, FredricZwahlen, Martin
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