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Publications (6 of 6) Show all publications
Sjöstedt, E., Sivertsson, Å., Norradin, F. H., Katona, B., Näsström, Å., Vuu, J., . . . Lindskog, C. (2018). Integration of Transcriptomics and Antibody-Based Proteomics for Exploration of Proteins Expressed in Specialized Tissues. Journal of Proteome Research, 17(12), 4127-4137
Open this publication in new window or tab >>Integration of Transcriptomics and Antibody-Based Proteomics for Exploration of Proteins Expressed in Specialized Tissues
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2018 (English)In: Journal of Proteome Research, ISSN 1535-3893, E-ISSN 1535-3907, Vol. 17, no 12, p. 4127-4137Article in journal (Refereed) Published
Abstract [en]

A large portion of human proteins are referred to as missing proteins, defined as protein-coding genes that lack experimental data on the protein level due to factors such as temporal expression, expression in tissues that are difficult to sample, or they actually do not encode functional proteins. In the present investigation, an integrated omics approach was used for identification and exploration of missing proteins. Transcriptomics data from three different sourcesthe Human Protein Atlas (HPA), the GTEx consortium, and the FANTOM5 consortiumwere used as a starting point to identify genes selectively expressed in specialized tissues. Complementing the analysis with profiling on more specific tissues based on immunohistochemistry allowed for further exploration of cell-type-specific expression patterns. More detailed tissue profiling was performed for >300 genes on complementing tissues. The analysis identified tissue-specific expression of nine proteins previously listed as missing proteins (POU4F1, FRMD1, ARHGEF33, GABRG1, KRTAP2-1, BHLHE22, SPRR4, AVPR1B, and DCLK3), as well as numerous proteins with evidence of existence on the protein level that previously lacked information on spatial resolution and cell-type- specific expression pattern. We here present a comprehensive strategy for identification of missing proteins by combining transcriptomics with antibody-based proteomics. The analyzed proteins provide interesting targets for organ-specific research in health and disease.

Place, publisher, year, edition, pages
American Chemical Society (ACS), 2018
Keywords
missing proteins, transcriptomics, proteomics, protein localization, immunohistochemistry, antibodies, tissue profiling
National Category
Medical Biotechnology (with a focus on Cell Biology (including Stem Cell Biology), Molecular Biology, Microbiology, Biochemistry or Biopharmacy) Biological Sciences
Research subject
Biotechnology
Identifiers
urn:nbn:se:kth:diva-236474 (URN)10.1021/acs.jproteome.8b00406 (DOI)000452930000010 ()30272454 (PubMedID)2-s2.0-85055105364 (Scopus ID)
Note

QC 20181018

Available from: 2018-10-17 Created: 2018-10-17 Last updated: 2019-01-11Bibliographically approved
Uhlén, M., Zhang, C., Lee, S., Sjöstedt, E., Fagerberg, L., Bidkhori, G., . . . Ponten, F. (2017). A pathology atlas of the human cancer transcriptome. Science, 357(6352), 660-+
Open this publication in new window or tab >>A pathology atlas of the human cancer transcriptome
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2017 (English)In: Science, ISSN 0036-8075, E-ISSN 1095-9203, Vol. 357, no 6352, p. 660-+Article in journal (Refereed) Published
Abstract [en]

Cancer is one of the leading causes of death, and there is great interest in understanding the underlying molecular mechanisms involved in the pathogenesis and progression of individual tumors. We used systems-level approaches to analyze the genome-wide transcriptome of the protein-coding genes of 17 major cancer types with respect to clinical outcome. A general pattern emerged: Shorter patient survival was associated with up-regulation of genes involved in cell growth and with down-regulation of genes involved in cellular differentiation. Using genome-scale metabolic models, we show that cancer patients have widespread metabolic heterogeneity, highlighting the need for precise and personalized medicine for cancer treatment. All data are presented in an interactive open-access database (www.proteinatlas.org/pathology) to allow genome-wide exploration of the impact of individual proteins on clinical outcomes.

Place, publisher, year, edition, pages
American Association for the Advancement of Science, 2017
National Category
Medical Biotechnology
Identifiers
urn:nbn:se:kth:diva-214334 (URN)10.1126/science.aan2507 (DOI)000407793600028 ()2-s2.0-85028362951 (Scopus ID)
Funder
Swedish Cancer SocietyScience for Life Laboratory - a national resource center for high-throughput molecular bioscienceKnut and Alice Wallenberg FoundationSwedish Research Council
Note

QC 20170913

Available from: 2017-09-13 Created: 2017-09-13 Last updated: 2018-10-17Bibliographically approved
Sjöstedt, E., Bollerslev, J., Mulder, J., Lindskog, C., Ponten, F. & Casar-Borota, O. (2017). A specific antibody to detect transcription factor T-Pit: a reliable marker of corticotroph cell differentiation and a tool to improve the classification of pituitary neuroendocrine tumours [Letter to the editor]. Acta Neuropathologica, 134(4), 675-677
Open this publication in new window or tab >>A specific antibody to detect transcription factor T-Pit: a reliable marker of corticotroph cell differentiation and a tool to improve the classification of pituitary neuroendocrine tumours
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2017 (English)In: Acta Neuropathologica, ISSN 0001-6322, E-ISSN 1432-0533, Vol. 134, no 4, p. 675-677Article in journal, Letter (Refereed) Published
Place, publisher, year, edition, pages
SPRINGER, 2017
National Category
Neurosciences
Identifiers
urn:nbn:se:kth:diva-214869 (URN)10.1007/s00401-017-1768-9 (DOI)000409369000012 ()2-s2.0-85027889508 (Scopus ID)
Note

QC 20171024

Available from: 2017-10-24 Created: 2017-10-24 Last updated: 2018-10-17Bibliographically approved
Sialana, F. J., Gulyassy, P., Majek, P., Sjöstedt, E., Kis, V., Muller, A. C., . . . Lubec, G. (2016). Mass spectrometric analysis of synaptosomal membrane preparations for the determination of brain receptors, transporters and channels. Proteomics, 16(22), 2911-2920
Open this publication in new window or tab >>Mass spectrometric analysis of synaptosomal membrane preparations for the determination of brain receptors, transporters and channels
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2016 (English)In: Proteomics, ISSN 1615-9853, E-ISSN 1615-9861, Vol. 16, no 22, p. 2911-2920Article in journal (Refereed) Published
Abstract [en]

The molecular composition of synaptic signal transduction machineries shapes synaptic neurotransmission. The repertoire of receptors, transporters and channels (RTCs) comprises major signaling events in the brain. RTCs are conventionally studied by candidate immunohistochemistry and biochemistry, which are low throughput with resolution greatly affected by available immunoreagents and membrane interference. Therefore, a comprehensive resource of synaptic brain RTCs is still lacking. In particular, studies on the detergent-soluble synaptosomal fraction, known to contain transporters and channels, are limited. We, therefore, performed sub-synaptosomal fractionation of rat cerebral cortex, followed by trypsin/chymotrypsin sequential digestion of a detergent-soluble synaptosomal fraction and a postsynaptic density preparation, stable-isotope tryptic peptide labeling and liquid chromatography mass spectrometry. Based on the current study, a total of 4784 synaptic proteins were submitted to the ProteomExchange database (PXD001948), including 274 receptors, 394 transporters/channels and 1377 transmembrane proteins. Function-based classification assigned 1781 proteins as probable drug targets with 834 directly linked to brain disorders. The analytical approach identified 499 RTCs that are not listed in the largest, curated database for synaptosomal proteins (SynProt). This is a threefold RTC increase over all other data collected to date. Taken together, we present a protein discovery resource that can serve as a benchmark for future molecular interrogation of synaptic connectivity.

Place, publisher, year, edition, pages
WILEY-BLACKWELL, 2016
Keywords
Animal proteomics, Channels, Membrane, Receptors, Transporters
National Category
Medical Biotechnology
Identifiers
urn:nbn:se:kth:diva-242606 (URN)10.1002/pmic.201600234 (DOI)000389219200010 ()27759936 (PubMedID)2-s2.0-84996503285 (Scopus ID)
Note

QC 20190226

Available from: 2019-02-26 Created: 2019-02-26 Last updated: 2019-08-21Bibliographically approved
Zieba, A., Sjöstedt, E., Olovsson, M., Fagerberg, L., Hallström, B. M., Oskarsson, L., . . . Ponten, F. (2015). The Human Endometrium-Specific Proteome Defined by Transcriptomics and Antibody-Based Profiling. Omics, 19(11), 659-668
Open this publication in new window or tab >>The Human Endometrium-Specific Proteome Defined by Transcriptomics and Antibody-Based Profiling
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2015 (English)In: Omics, ISSN 1536-2310, E-ISSN 1557-8100, Vol. 19, no 11, p. 659-668Article in journal (Refereed) Published
Abstract [en]

The human uterus includes the complex endometrial mucosa, the endometrium that undergoes dynamic, hormone-dependent alterations throughout the life of fertile females. Here we have combined a genome-wide transcriptomics analysis with immunohistochemistry-based protein profiling to analyze gene expression patterns in the normal endometrium. Human endometrial tissues from five women were used for deep sequencing (RNA-Seq). The mRNA and protein expression data from the endometrium were compared to 31 (RNA) and 44 (protein) other normal tissue types, to identify genes with elevated expression in the endometrium and to localize the expression of corresponding proteins at a cellular resolution. Based on the expression levels of transcripts, we could classify all putative human protein coding genes into categories defined by expression patterns and found altogether 101 genes that showed an elevated pattern of expression in the endometrium, with only four genes showing more than five-fold higher expression levels in the endometrium compared to other tissues. In conclusion, our analysis based on transcriptomics and antibody-based protein profiling reports here comprehensive lists of genes with elevated expression levels in the endometrium, providing important starting points for a better molecular understanding of human reproductive biology and disease.

Place, publisher, year, edition, pages
MARY ANN LIEBERT, INC, 2015
National Category
Medical Biotechnology
Identifiers
urn:nbn:se:kth:diva-243643 (URN)10.1089/omi.2015.0115 (DOI)000364547500001 ()26488136 (PubMedID)
Note

QC 20190304

Available from: 2019-03-04 Created: 2019-03-04 Last updated: 2019-05-17Bibliographically approved
Sjöstedt, E., Fagerberg, L., Mitsios, N., Adori, C., Oksvold, P., Limiszewka, A., . . . Mulder, J.The transcriptomic landscape of mammalian brain.
Open this publication in new window or tab >>The transcriptomic landscape of mammalian brain
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(English)Manuscript (preprint) (Other academic)
National Category
Neurosciences Medical Biotechnology
Research subject
Biotechnology; Medical Technology
Identifiers
urn:nbn:se:kth:diva-236079 (URN)
Note

QC 20181018

Available from: 2018-10-15 Created: 2018-10-15 Last updated: 2018-10-18Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-0327-7377

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