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  • 1
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    Proteomics. Tissue-based map of the human proteome (2015)
    American Association for the Advancement of Science (AAAS)
    Details
    Publication Date: 2015-01-24
    Description: 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.〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Uhlen, Mathias -- Fagerberg, Linn -- Hallstrom, Bjorn M -- Lindskog, Cecilia -- Oksvold, Per -- Mardinoglu, Adil -- Sivertsson, Asa -- Kampf, Caroline -- Sjostedt, Evelina -- Asplund, Anna -- Olsson, IngMarie -- Edlund, Karolina -- Lundberg, Emma -- Navani, Sanjay -- Szigyarto, Cristina Al-Khalili -- Odeberg, Jacob -- Djureinovic, Dijana -- Takanen, Jenny Ottosson -- Hober, Sophia -- Alm, Tove -- Edqvist, Per-Henrik -- Berling, Holger -- Tegel, Hanna -- Mulder, Jan -- Rockberg, Johan -- Nilsson, Peter -- Schwenk, Jochen M -- Hamsten, Marica -- von Feilitzen, Kalle -- Forsberg, Mattias -- Persson, Lukas -- Johansson, Fredric -- Zwahlen, Martin -- von Heijne, Gunnar -- Nielsen, Jens -- Ponten, Fredrik -- New York, N.Y. -- Science. 2015 Jan 23;347(6220):1260419. doi: 10.1126/science.1260419.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Science for Life Laboratory, KTH-Royal Institute of Technology, SE-171 21 Stockholm, Sweden. Department of Proteomics, KTH-Royal Institute of Technology, SE-106 91 Stockholm, Sweden. Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, DK-2970 Horsholm, Denmark. mathias.uhlen@scilifelab.se. ; Science for Life Laboratory, KTH-Royal Institute of Technology, SE-171 21 Stockholm, Sweden. ; Science for Life Laboratory, KTH-Royal Institute of Technology, SE-171 21 Stockholm, Sweden. Department of Proteomics, KTH-Royal Institute of Technology, SE-106 91 Stockholm, Sweden. ; Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, SE-751 85 Uppsala, Sweden. ; Department of Chemical and Biological Engineering, Chalmers University of Technology, SE-412 96 Gothenburg, Sweden. ; Science for Life Laboratory, KTH-Royal Institute of Technology, SE-171 21 Stockholm, Sweden. Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, SE-751 85 Uppsala, Sweden. ; Leibniz Research Centre for Working Environment and Human Factors (IfADo) at Dortmund TU, D-44139 Dortmund, Germany. ; Lab Surgpath, Mumbai, India. ; Department of Proteomics, KTH-Royal Institute of Technology, SE-106 91 Stockholm, Sweden. ; Science for Life Laboratory, Department of Neuroscience, Karolinska Institute, SE-171 77 Stockholm, Sweden. ; Center for Biomembrane Research, Department of Biochemistry and Biophysics, Stockholm University, Stockholm, Sweden. ; Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, DK-2970 Horsholm, Denmark. Department of Chemical and Biological Engineering, Chalmers University of Technology, SE-412 96 Gothenburg, Sweden.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/25613900" target="_blank"〉PubMed〈/a〉
    Keywords: Alternative Splicing ; Cell Line ; *Databases, Protein ; Female ; Genes ; Genetic Code ; Humans ; Internet ; Male ; Membrane Proteins/genetics/metabolism ; Mitochondrial Proteins/genetics/metabolism ; Neoplasms/genetics/metabolism ; Protein Array Analysis ; Protein Isoforms/genetics/metabolism ; Proteome/genetics/*metabolism ; Tissue Distribution ; Transcription, Genetic
    Print ISSN: 0036-8075
    Electronic ISSN: 1095-9203
    Topics: Biology , Chemistry and Pharmacology , Computer Science , Medicine , Natural Sciences in General , Physics
    Published by American Association for the Advancement of Science (AAAS)
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  • 2
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    Exclusive Enteral Nutrition: Clinical Effects and Changes in Mucosal Cytokine Profile in Pediatric New Inflammatory Bowel Disease (2019)
    Molecular Diversity Preservation International
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    Publication Date: 2019-02-15
    Description: Exclusive Enteral Nutrition (EEN) is the first-line treatment in children with Crohn’s disease (CD) for induction of remission. However, the mode of action remains conjectural. The aim of this study was to investigate whether the effect of EEN is paralleled by changes in the mucosal cytokine profiles (MCP). Twelve children with new onset inflammatory bowel disease (IBD) received induction treatment with a polymeric EEN. We assessed clinical, endoscopic and histologic scoring before and after EEN. Twelve colonic cytokines were analyzed by Polymerase Chain Reaction (PCR) in six of the IBD patients at onset and after EEN as well as in six non-IBD control children at the diagnostic colonoscopy. Twelve children completed 6 weeks of EEN, except from one child who completed 4 weeks. At the control colonoscopy, 83% were in complete clinical remission. Changes were found in the MCPs of individual patients after EEN. In particular, children with IBD showed significantly higher values of Interleukin (IL)-12β (p = 0.008) and IL-23α (p = 0.02) compared to non-IBD controls at the diagnostic colonoscopy. Furthermore, an overall change in proinflammatory cytokines was noted in the IBD-group after treatment. Further studies are warranted to understand the role of EEN in MCP.
    Electronic ISSN: 2072-6643
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Process Engineering, Biotechnology, Nutrition Technology
    Published by Molecular Diversity Preservation International
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  • 3
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    A pathology atlas of the human cancer transcriptome (2017)
    American Association for the Advancement of Science (AAAS)
    In: Science
    Details
    Publication Date: 2017-08-18
    Description: 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.
    Keywords: Genetics, Medicine, Diseases, Online Only
    Print ISSN: 0036-8075
    Electronic ISSN: 1095-9203
    Topics: Biology , Chemistry and Pharmacology , Geosciences , Computer Science , Medicine , Natural Sciences in General , Physics
    Published by American Association for the Advancement of Science (AAAS)
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  • 4
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    A comprehensive comparison of RNA-Seq-based transcriptome analysis from reads to differential gene expression and cross-comparison with microarrays: a case study in Saccharomyces cerevisiae (2012)
    Oxford University Press
    Details
    Publication Date: 2012-11-04
    Description: RNA-seq, has recently become an attractive method of choice in the studies of transcriptomes, promising several advantages compared with microarrays. In this study, we sought to assess the contribution of the different analytical steps involved in the analysis of RNA-seq data generated with the Illumina platform, and to perform a cross-platform comparison based on the results obtained through Affymetrix microarray. As a case study for our work we, used the Saccharomyces cerevisiae strain CEN.PK 113-7D, grown under two different conditions (batch and chemostat). Here, we asses the influence of genetic variation on the estimation of gene expression level using three different aligners for read-mapping (Gsnap, Stampy and TopHat) on S288c genome, the capabilities of five different statistical methods to detect differential gene expression (baySeq, Cuffdiff, DESeq, edgeR and NOISeq) and we explored the consistency between RNA-seq analysis using reference genome and de novo assembly approach. High reproducibility among biological replicates (correlation ≥0.99) and high consistency between the two platforms for analysis of gene expression levels (correlation ≥0.91) are reported. The results from differential gene expression identification derived from the different statistical methods, as well as their integrated analysis results based on gene ontology annotation are in good agreement. Overall, our study provides a useful and comprehensive comparison between the two platforms (RNA-seq and microrrays) for gene expression analysis and addresses the contribution of the different steps involved in the analysis of RNA-seq data.
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
    Published by Oxford University Press
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  • 5
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    Complementing tissue characterization by integrating transcriptome profiling from the Human Protein Atlas and from the FANTOM5 consortium (2015)
    Oxford University Press
    Details
    Publication Date: 2015-08-18
    Description: Understanding the normal state of human tissue transcriptome profiles is essential for recognizing tissue disease states and identifying disease markers. Recently, the Human Protein Atlas and the FANTOM5 consortium have each published extensive transcriptome data for human samples using Illumina-sequenced RNA-Seq and Heliscope-sequenced CAGE. Here, we report on the first large-scale complex tissue transcriptome comparison between full-length versus 5'-capped mRNA sequencing data. Overall gene expression correlation was high between the 22 corresponding tissues analyzed ( R 〉 0.8). For genes ubiquitously expressed across all tissues, the two data sets showed high genome-wide correlation (91% agreement), with differences observed for a small number of individual genes indicating the need to update their gene models. Among the identified single-tissue enriched genes, up to 75% showed consensus of 7-fold enrichment in the same tissue in both methods, while another 17% exhibited multiple tissue enrichment and/or high expression variety in the other data set, likely dependent on the cell type proportions included in each tissue sample. Our results show that RNA-Seq and CAGE tissue transcriptome data sets are highly complementary for improving gene model annotations and highlight biological complexities within tissue transcriptomes. Furthermore, integration with image-based protein expression data is highly advantageous for understanding expression specificities for many genes.
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
    Published by Oxford University Press
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  • 6
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    A subcellular map of the human proteome (2017)
    American Association for the Advancement of Science (AAAS)
    In: Science
    Details
    Publication Date: 2017-05-26
    Description: Resolving the spatial distribution of the human proteome at a subcellular level can greatly increase our understanding of human biology and disease. Here we present a comprehensive image-based map of subcellular protein distribution, the Cell Atlas, built by integrating transcriptomics and antibody-based immunofluorescence microscopy with validation by mass spectrometry. Mapping the in situ localization of 12,003 human proteins at a single-cell level to 30 subcellular structures enabled the definition of the proteomes of 13 major organelles. Exploration of the proteomes revealed single-cell variations in abundance or spatial distribution and localization of about half of the proteins to multiple compartments. This subcellular map can be used to refine existing protein-protein interaction networks and provides an important resource to deconvolute the highly complex architecture of the human cell.
    Keywords: Biochemistry, Online Only
    Print ISSN: 0036-8075
    Electronic ISSN: 1095-9203
    Topics: Biology , Chemistry and Pharmacology , Geosciences , Computer Science , Medicine , Natural Sciences in General , Physics
    Published by American Association for the Advancement of Science (AAAS)
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