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  • 1.
    Alm, Tove
    et al.
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    von Feilitzen, Kalle
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Lundberg, Emma
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Sivertsson, Åsa
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Uhlén, Mathias
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    A Chromosome-Centric Analysis of Antibodies Directed toward the Human Proteome Using Antibodypedia2014In: Journal of Proteome Research, ISSN 1535-3893, E-ISSN 1535-3907, Vol. 13, no 3, p. 1669-1676Article in journal (Refereed)
    Abstract [en]

    Antibodies are crucial for the study of human proteins and have been defined as one of the three pillars in the human chromosome-centric Human Proteome Project (CHPP). In this article the chromosome-centric structure has been used to analyze the availability of antibodies as judged by the presence within the portal Antibodypedia, a database designed to allow comparisons and scoring of publicly available antibodies toward human protein targets. This public database displays antibody data from more than one million antibodies toward human protein targets. A summary of the content in this knowledge resource reveals that there exist more than 10 antibodies to over 70% of all the putative human genes, evenly distributed over the 24 human chromosomes. The analysis also shows that at present, less than 10% of the putative human protein-coding genes (n = 1882) predicted from the genome sequence lack antibodies, suggesting that focused efforts from the antibody-based and mass spectrometry-based proteomic communities should be encouraged to pursue the analysis of these missing proteins. We show that Antibodypedia may be used to track the development of available and validated antibodies to the individual chromosomes, and thus the database is an attractive tool to identify proteins with no or few antibodies yet generated.

  • 2. Backvall, H.
    et al.
    Stromberg, S.
    Gustafsson, Anna
    KTH, Superseded Departments, Biotechnology.
    Asplund, A.
    Sivertsson, Åsa
    KTH, Superseded Departments, Biotechnology.
    Lundeberg, Joakim
    KTH, Superseded Departments, Biotechnology.
    Ponten, F.
    Mutation spectra of epidermal p53 clones adjacent to basal cell carcinoma and squamous cell carcinoma2004In: Experimental dermatology, ISSN 0906-6705, E-ISSN 1600-0625, Vol. 13, no 10, p. 643-650Article in journal (Refereed)
    Abstract [en]

    Foci of normal keratinocytes overexpressing p53 protein are frequently found in normal human skin. Such epidermal p53 clones are common in chronically sun-exposed skin and have been suggested to play a role in skin cancer development. In the present study, we have analyzed the prevalence of p53 mutations in epidermal p53 clones from normal skin surrounding basal cell carcinoma (BCC) and squamous cell carcinoma (SCC). Using laser-assisted microdissection, 37 epidermal p53 clones adjacent to BCC (21) and SCC (16) were collected. Genetic analysis was performed using a multiplex/nested polymerase chain reaction followed by direct DNA sequencing of p53 exons 2-11. In total, 21 of 37 analyzed p53 clones consisted of p53-mutated keratinocytes. The identified mutations were located in p53 exons 4-8, corresponding to the sequence-specific DNA-binding domain. All mutations were missense, and 78% displayed a typical ultraviolet signature. The frequency of p53 mutations was similar in skin adjacent to BCC compared to SCC. The presented data confirm and extend previous knowledge on the genetic background of epidermal p53 clones. The mutation spectra found in epidermal p53 clones resemble that of non-melanoma skin cancer. Approximately, 40% of the epidermal p53 clones lacked an underlying p53 mutation, suggesting that other genetic events in genes up- or downstream of the p53 gene can generate foci of normal keratinocytes overexpressing p53 protein.

  • 3.
    Berglund, Lisa
    et al.
    KTH, School of Biotechnology (BIO).
    Björling, Erik
    KTH, School of Biotechnology (BIO).
    Gry, Marcus
    KTH, School of Biotechnology (BIO).
    Asplund, Anna
    Uppsala Univ, Rudbeck laboratory.
    Al-Khalili Szigyarto, Cristina
    KTH, School of Biotechnology (BIO).
    Persson, Anja
    KTH, School of Biotechnology (BIO).
    Ottoson, Jenny
    KTH, School of Biotechnology (BIO).
    Wernérus, Henrik
    KTH, School of Biotechnology (BIO).
    Nilsson, Peter
    KTH, School of Biotechnology (BIO).
    Sivertsson, Åsa
    KTH, School of Biotechnology (BIO).
    Wester, Kenneth
    Uppsala Univ, Rudbeck laboratory.
    Kampf, Caroline
    Uppsala Univ, Rudbeck laboratory.
    Hober, Sophia
    KTH, School of Biotechnology (BIO).
    Pontén, Fredrik
    Uppsala Univ, Rudbeck laboratory.
    Uhlén, Mathias
    KTH, School of Biotechnology (BIO).
    Generation of validated antibodies towards the human proteomeArticle in journal (Other academic)
    Abstract [en]

    Here we show the results from a large effort to generate antibodies towards the human proteome. A high-throughput strategy was developed based on cloning and expression of antigens as recombitant protein epitope signature tags (PrESTs) Affinity purified polyclonal antibodies were generated, followed by validation by protein microarrays, Western blotting and microarray-based immunohistochemistry. PrESTs were selected based on sequence uniqueness relative the proteome and a bioinformatics analysis showed that unique antigens can be found for at least 85% of the proteome using this general strategy. The success rate from antigen selection to validated antibodies was 31%, and from protein to antibody 55%. Interestingly, membrane-bound and soluble proteins performed equally and PrEST lengths between 75 and 125 amino acids were found to give the highest yield of validated antibodies. Multiple antigens were selected for many genes and the results suggest that specific antibodies can be systematically generated to most human proteibs.

  • 4.
    Berglund, Lisa
    et al.
    KTH, School of Biotechnology (BIO).
    Björling, Erik
    KTH, School of Biotechnology (BIO).
    Jonasson, Kalle
    KTH, School of Biotechnology (BIO).
    Rockberg, Johan
    KTH, School of Biotechnology (BIO).
    Fagerberg, Linn
    KTH, School of Biotechnology (BIO).
    Al-Khalili Szigyarto, Cristina
    KTH, School of Biotechnology (BIO).
    Sivertsson, Åsa
    KTH, School of Biotechnology (BIO).
    Uhlén, Mathias
    KTH, School of Biotechnology (BIO).
    A whole-genome bioinformatics approach to selection of antigens for systematic antibody generation2008In: Proteomics, ISSN 1615-9853, E-ISSN 1615-9861, Vol. 8, no 14, p. 2832-2839Article in journal (Refereed)
    Abstract [en]

    Here, we present an antigen selection strategy based on a whole-genome bioinformatics approach, which is facilitated by an interactive visualization tool displaying protein features from both public resources and in-house generated data. The web-based bioinformatics platform has been designed for selection of multiple, non-overlapping recombinant protein epitope signature tags by display of predicted information relevant for antigens, including domain- and epitope sized sequence similarities to other proteins, transmembrane regions and signal peptides. The visualization tool also displays shared and exclusive protein regions for genes with multiple splice variants. A genome-wide analysis demonstrates that antigens for approximately 80% of the human protein-coding genes can be selected with this strategy.

  • 5.
    Berglund, Lisa
    et al.
    KTH, School of Biotechnology (BIO), Proteomics.
    Björling, Erik
    KTH, School of Biotechnology (BIO), Proteomics.
    Oksvold, Per
    KTH, School of Biotechnology (BIO), Proteomics.
    Fagerberg, Linn
    KTH, School of Biotechnology (BIO), Proteomics.
    Al-Khalili Szigyarto, Cristina
    KTH, School of Biotechnology (BIO), Proteomics.
    Persson, Anja
    KTH, School of Biotechnology (BIO), Proteomics.
    Ottosson, Jenny
    KTH, School of Biotechnology (BIO), Proteomics.
    Wernérus, Henrik
    KTH, School of Biotechnology (BIO), Proteomics.
    Nilsson, Peter
    KTH, School of Biotechnology (BIO), Proteomics.
    Lundberg, Emma
    KTH, School of Biotechnology (BIO), Proteomics.
    Sivertsson, Åsa
    KTH, School of Biotechnology (BIO), Proteomics.
    Hober, Sophia
    KTH, School of Biotechnology (BIO), Proteomics.
    Uhlén, Mathias
    KTH, School of Biotechnology (BIO), Proteomics.
    et al.,
    A genecentric human protein atlas for expression profiles based on antibodies2008In: Molecular & Cellular Proteomics, ISSN 1535-9476, Vol. 7, no 10, p. 2019-2027Article in journal (Refereed)
    Abstract [en]

    An attractive path forward in proteomics is to experimentally annotate the human protein complement of the genome in a genecentric manner. Using antibodies, it might be possible to design protein-specific probes for a representative protein from every protein-coding gene and to subsequently use the antibodies for systematical analysis of cellular distribution and subcellular localization of proteins in normal and disease tissues. A new version (4.0) of the Human Protein Atlas has been developed in a genecentric manner with the inclusion of all human genes and splice variants predicted from genome efforts together with a visualization of each protein with characteristics such as predicted membrane regions, signal peptide, and protein domains and new plots showing the uniqueness (sequence similarity) of every fraction of each protein toward all other human proteins. The new version is based on tissue profiles generated from 6120 antibodies with more than five million immunohistochemistry-based images covering 5067 human genes, corresponding to similar to 25% of the human genome. Version 4.0 includes a putative list of members in various protein classes, both functional classes, such as kinases, transcription factors, G-protein-coupled receptors, etc., and project-related classes, such as candidate genes for cancer or cardiovascular diseases. The exact antigen sequence for the internally generated antibodies has also been released together with a visualization of the application-specific validation performed for each antibody, including a protein array assay, Western blot analysis, immunohistochemistry, and, for a large fraction, immunofluorescence-based confocal microscopy. New search functionalities have been added to allow complex queries regarding protein expression profiles, protein classes, and chromosome location. The new version of the protein atlas thus is a resource for many areas of biomedical research, including protein science and biomarker discovery.

  • 6. Colwill, Karen
    et al.
    Nilsson, Peter
    KTH, School of Biotechnology (BIO), Proteomics.
    Sundberg, Mårten
    KTH, School of Biotechnology (BIO), Proteomics.
    Sjöberg, Ronald
    KTH, School of Biotechnology (BIO), Proteomics.
    Sivertsson, Åsa
    KTH, School of Biotechnology (BIO), Proteomics.
    Schwenk, Jochen M
    KTH, School of Biotechnology (BIO), Proteomics.
    Ottosson Takanen, Jenny
    KTH, School of Biotechnology (BIO), Proteomics.
    Hober, Sophia
    KTH, School of Biotechnology (BIO), Proteomics.
    Uhlén, Mathias
    KTH, School of Biotechnology (BIO), Proteomics.
    Gräslund, Susanne
    et, al.
    A roadmap to generate renewable protein binders to the human proteome2011In: Nature Methods, ISSN 1548-7091, E-ISSN 1548-7105, Vol. 8, no 7, p. 551-8Article in journal (Refereed)
    Abstract [en]

    Despite the wealth of commercially available antibodies to human proteins, research is often hindered by their inconsistent validation, their poor performance and the inadequate coverage of the proteome. These issues could be addressed by systematic, genome-wide efforts to generate and validate renewable protein binders. We report a multicenter study to assess the potential of hybridoma and phage-display technologies in a coordinated large-scale antibody generation and validation effort. We produced over 1,000 antibodies targeting 20 SH2 domain proteins and evaluated them for potency and specificity by enzyme-linked immunosorbent assay (ELISA), protein microarray and surface plasmon resonance (SPR). We also tested selected antibodies in immunoprecipitation, immunoblotting and immunofluorescence assays. Our results show that high-affinity, high-specificity renewable antibodies generated by different technologies can be produced quickly and efficiently. We believe that this work serves as a foundation and template for future larger-scale studies to create renewable protein binders.

  • 7.
    Edfors, Fredrik
    et al.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Hober, Andreas
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Linderbäck, Klas
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Maddalo, Gianluca
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Azimi, Alireza
    Karolinska Inst, Karolinska Univ Hosp, Dept Oncol Pathol, SE-17177 Stockholm, Sweden..
    Sivertsson, Åsa
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Tegel, Hanna
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Hober, Sophia
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Al-Khalili Szigyarto, Cristina
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Fagerberg, Linn
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    von Feilitzen, Kalle
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Oksvold, Per
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Lindskog, Cecilia
    Uppsala Univ, Dept Immunol Genet & Pathol, SE-75185 Uppsala, Sweden..
    Forsström, Björn
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Uhlén, Mathias
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science. KTH, Centres, Science for Life Laboratory, SciLifeLab. Biosustainabil, DK-2970 Horsholm, Denmark..
    Enhanced validation of antibodies for research applications2018In: Nature Communications, ISSN 2041-1723, E-ISSN 2041-1723, Vol. 9, article id 4130Article in journal (Refereed)
    Abstract [en]

    There is a need for standardized validation methods for antibody specificity and selectivity. Recently, five alternative validation pillars were proposed to explore the specificity of research antibodies using methods with no need for prior knowledge about the protein target. Here, we show that these principles can be used in a streamlined manner for enhanced validation of research antibodies in Western blot applications. More than 6,000 antibodies were validated with at least one of these strategies involving orthogonal methods, genetic knockdown, recombinant expression, independent antibodies, and capture mass spectrometry analysis. The results show a path forward for efforts to validate antibodies in an application-specific manner suitable for both providers and users.

  • 8.
    Edfors, Fredrik
    et al.
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Linderbäck, Klas
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology.
    Sivertsson, Åsa
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Danielsson, Frida
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Fagerberg, Linn
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Lundberg, Emma
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Alm, Tove
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Forsström, Björn
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Uhlén, Mathias
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab. Technical University of Denmark, Denmark.
    Validation of antibodies for Western blot applications using orthogonal methodsManuscript (preprint) (Other academic)
    Abstract [en]

    There is a great need for standardized validation methods for antibody specificity and selectivity. Here, we describe the use of orthogonal methods in which the specificity of an antibody in a particular application is determined based on correlation of protein abundance across several samples using an antibody-independent method. We show that pair-wise correlation between orthogonal samples can be used to score the specificity of antibodies in a standardized manner using a test panel of human cell lines. Here, we investigated two independent methods for validation of antibodies in Western blot applications, namely transcriptomics and targeted proteomics and we show that the two methods yield similar, but not identical results. The orthogonal methods can also be used to investigate on- and off- target binding for antibodies with multiple bands in the Western blot assay. In conclusion, orthogonal methods for antibody validation provide an attractive strategy for systematic validation of antibodies in a quantitative manner. 

  • 9.
    Fagerberg, Linn
    et al.
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Hallström, Björn M.
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Oksvold, Per
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Kampf, C.
    Djureinovic, D.
    Odeberg, Jacob
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Habuka, Masato
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Tahmasebpoor, S.
    Danielsson, A.
    Edlund, K.
    Asplund, A.
    Sjöstedt, E.
    Lundberg, E.
    Szigyarto, Cristina Al-Khalili
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Skogs, Marie
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Ottosson Takanen, J.
    Berling, H.
    Tegel, Hanna
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology.
    Mulder, J.
    Nilsson, Peter
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Schwenk, Jochen M.
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Lindskog, C.
    Danielsson, Frida
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Mardinoglu, A.
    Sivertsson, Åsa
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Von Feilitzen, Kalle
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology.
    Forsberg, Mattias
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Zwahlen, Martin
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Olsson, I.
    Navani, S.
    Huss, Mikael
    Nielsen, Jens
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Pontén, F.
    Uhlén, Mathias
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Analysis of the human tissue-specific expression by genome-wide integration of transcriptomics and antibody-based proteomics2014In: Molecular & Cellular Proteomics, ISSN 1535-9476, E-ISSN 1535-9484, Vol. 13, no 2, p. 397-406Article in journal (Refereed)
    Abstract [en]

    Global classification of the human proteins with regards to spatial expression patterns across organs and tissues is important for studies of human biology and disease. Here, we used a quantitative transcriptomics analysis (RNA-Seq) to classify the tissue-specific expression of genes across a representative set of all major human organs and tissues and combined this analysis with antibody- based profiling of the same tissues. To present the data, we launch a new version of the Human Protein Atlas that integrates RNA and protein expression data corresponding to 80% of the human protein-coding genes with access to the primary data for both the RNA and the protein analysis on an individual gene level. We present a classification of all human protein-coding genes with regards to tissue-specificity and spatial expression pattern. The integrative human expression map can be used as a starting point to explore the molecular constituents of the human body.

  • 10.
    Fagerberg, Linn
    et al.
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Oksvold, Per
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Skogs, Marie
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Älgenäs, C.
    Lundberg, Emma
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Pontén, F.
    Sivertsson, Åsa
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Odeberg, Jacob
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Klevebring, Daniel
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Kampf, C.
    Asplund, A.
    Sjöstedt, E.
    Al-Khalili Szigyarto, C.
    Edqvist, P. -H
    Olsson, I.
    Rydberg, U.
    Hudson, P.
    Ottosson Takanen, J.
    Berling, H.
    Björling, Lisa
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Tegel, Hanna
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology.
    Rockberg, J.
    Nilsson, Peter
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Navani, S.
    Jirström, K.
    Mulder, J.
    Schwenk, Jochen M.
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Zwahlen, Martin
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Hober, Sophia
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Forsberg, Mattias
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Von Feilitzen, Kalle
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Uhlén, Mathias
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Contribution of antibody-based protein profiling to the human chromosome-centric proteome project (C-HPP)2013In: Journal of Proteome Research, ISSN 1535-3893, E-ISSN 1535-3907, Vol. 12, no 6, p. 2439-2448Article in journal (Refereed)
    Abstract [en]

    A gene-centric Human Proteome Project has been proposed to characterize the human protein-coding genes in a chromosome-centered manner to understand human biology and disease. Here, we report on the protein evidence for all genes predicted from the genome sequence based on manual annotation from literature (UniProt), antibody-based profiling in cells, tissues and organs and analysis of the transcript profiles using next generation sequencing in human cell lines of different origins. We estimate that there is good evidence for protein existence for 69% (n = 13985) of the human protein-coding genes, while 23% have only evidence on the RNA level and 7% still lack experimental evidence. Analysis of the expression patterns shows few tissue-specific proteins and approximately half of the genes expressed in all the analyzed cells. The status for each gene with regards to protein evidence is visualized in a chromosome-centric manner as part of a new version of the Human Protein Atlas (www.proteinatlas.org).

  • 11. Gremel, Gabriela
    et al.
    Djureinovic, Dijana
    Niinivirta, Marjut
    Laird, Alexander
    Ljungqvist, Oscar
    Johannesson, Henrik
    Bergman, Julia
    Edqvist, Per-Henrik
    Navani, Sanjay
    Khan, Naila
    Patil, Tushar
    Sivertsson, Åsa
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Uhlén, Mathias
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Harrison, David J.
    Ullenhag, Gustav J.
    Stewart, Grant D.
    Ponten, Fredrik
    A systematic search strategy identifies cubilin as independent prognostic marker for renal cell carcinoma2017In: BMC Cancer, ISSN 1471-2407, E-ISSN 1471-2407, Vol. 17, article id 9Article in journal (Refereed)
    Abstract [en]

    Background: There is an unmet clinical need for better prognostic and diagnostic tools for renal cell carcinoma (RCC). Methods: Human Protein Atlas data resources, including the transcriptomes and proteomes of normal and malignant human tissues, were searched for RCC-specific proteins and cubilin (CUBN) identified as a candidate. Patient tissue representing various cancer types was constructed into a tissue microarray (n = 940) and immunohistochemistry used to investigate the specificity of CUBN expression in RCC as compared to other cancers. Two independent RCC cohorts (n = 181; n = 114) were analyzed to further establish the sensitivity of CUBN as RCC-specific marker and to explore if the fraction of RCCs lacking CUBN expression could predict differences in patient survival. Results: CUBN was identified as highly RCC-specific protein with 58% of all primary RCCs staining positive for CUBN using immunohistochemistry. In venous tumor thrombi and metastatic lesions, the frequency of CUBN expression was increasingly lost. Clear cell RCC (ccRCC) patients with CUBN positive tumors had a significantly better prognosis compared to patients with CUBN negative tumors, independent of T-stage, Fuhrman grade and nodal status (HR 0.382, CI 0.203-0.719, P = 0.003). Conclusions: CUBN expression is highly specific to RCC and loss of the protein is significantly and independently associated with poor prognosis. CUBN expression in ccRCC provides a promising positive prognostic indicator for patients with ccRCC. The high specificity of CUBN expression in RCC also suggests a role as a new diagnostic marker in clinical cancer differential diagnostics to confirm or rule out RCC.

  • 12.
    Habuka, Masato
    et al.
    KTH, Centres, Science for Life Laboratory, SciLifeLab. Karolinska University Hospital, Sweden .
    Fagerberg, Linn
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Hallström, Björn M.
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Kampf, Caroline
    Edlund, Karolina
    Sivertsson, Åsa
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Yamamoto, Tadashi
    Pontén, Fredrik
    Uhlén, Mathias
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Odeberg, Jacob
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab. Karolinska University Hospital, Sweden.
    The Kidney Transcriptome and Proteome Defined by Transcriptomics and Antibody-Based Profiling2014In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 9, no 12, p. e116125-Article in journal (Refereed)
    Abstract [en]

    To understand renal functions and disease, it is important to define the molecular constituents of the various compartments of the kidney. Here, we used comparative transcriptomic analysis of all major organs and tissues in the human body, in combination with kidney tissue micro array based immunohistochemistry, to generate a comprehensive description of the kidney-specific transcriptome and proteome. A special emphasis was placed on the identification of genes and proteins that were elevated in specific kidney subcompartments. Our analysis identified close to 400 genes that had elevated expression in the kidney, as compared to the other analysed tissues, and these were further subdivided, depending on expression levels, into tissue enriched, group enriched or tissue enhanced. Immunohistochemistry allowed us to identify proteins with distinct localisation to the glomeruli (n=11), proximal tubules (n=120), distal tubules (n=9) or collecting ducts (n=8). Among the identified kidney elevated transcripts, we found several proteins not previously characterised or identified as elevated in kidney. This description of the kidney specific transcriptome and proteome provides a resource for basic and clinical research to facilitate studies to understand kidney biology and disease.

  • 13.
    Lindskog, Mats
    et al.
    KTH, School of Biotechnology (BIO).
    Berglund, L.
    Persson, Anja
    KTH, School of Biotechnology (BIO).
    Sivertsson, Åsa
    KTH, School of Biotechnology (BIO).
    Uhlén, Mathias
    KTH, School of Biotechnology (BIO).
    Al-Khalili Szigyarto, Cristina
    KTH, School of Biotechnology (BIO).
    Design of protein epitope signature tags for antibody-based proteomicsManuscript (Other academic)
  • 14.
    Lundqvist, Magnus
    et al.
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology.
    Edfors, Fredrik
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology.
    Sivertsson, Åsa
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology.
    Hallström, Björn M
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology.
    Hudson, Elton P.
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Tegel, Hanna
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology.
    Holmberg, Anders
    Uhlén, Mathias
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Rockberg, Johan
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology.
    Solid-phase cloning for high-throughput assembly of single and multiple DNA parts2015In: Nucleic Acids Research, ISSN 0305-1048, E-ISSN 1362-4962, Vol. 43, no 7, article id e49Article in journal (Refereed)
    Abstract [en]

    We describe solid-phase cloning (SPC) for high-throughput assembly of expression plasmids. Our method allows PCR products to be put directly into a liquid handler for capture and purification using paramagnetic streptavidin beads and conversion into constructs by subsequent cloning reactions. We present a robust automated protocol for restriction enzyme based SPC and its performance for the cloning of >60 000 unique human gene fragments into expression vectors. In addition, we report on SPC-based single-strand assembly for applications where exact control of the sequence between fragments is needed or where multiple inserts are to be assembled. In this approach, the solid support allows for head-to-tail assembly of DNA fragments based on hybridization and polymerase fill-in. The usefulness of head-to-tail SPC was demonstrated by assembly of >150 constructs with up to four DNA parts at an average success rate above 80%. We report on several applications for SPC and we suggest it to be particularly suitable for high-throughput efforts using laboratory workstations.

  • 15.
    Sjöberg, Ronald
    et al.
    KTH, School of Biotechnology (BIO), Proteomics (closed 20130101).
    Sundberg, Mårten
    KTH, School of Biotechnology (BIO), Proteomics (closed 20130101).
    Gundberg, Anna
    KTH, School of Biotechnology (BIO).
    Sivertsson, Åsa
    KTH, School of Biotechnology (BIO).
    Schwenk, Jochen M.
    KTH, School of Biotechnology (BIO).
    Uhlén, Mathias
    KTH, School of Biotechnology (BIO), Proteomics (closed 20130101).
    Nilsson, Peter
    KTH, School of Biotechnology (BIO), Proteomics (closed 20130101).
    Validation of affinity reagents using antigen microarrays2011In: New Biotechnology, ISSN 1871-6784, E-ISSN 1876-4347, Vol. 29, no 5, p. 555-563Article in journal (Refereed)
    Abstract [en]

    There is a need for standardised validation of affinity reagents to determine their binding selectivity and specificity. This is of particular importance for systematic efforts that aim to cover the human proteome with different types of binding reagents. One such international program is the SH2-consortium, which was formed to generate a complete set of renewable affinity reagents to the SH2-domain containing human proteins. Here, we describe a microarray strategy to validate various affinity reagents, such as recombinant single-chain antibodies, mouse monoclonal antibodies and antigen-purified polyclonal antibodies using a highly multiplexed approach. An SH2-specific antigen microarray was designed and generated, containing more than 6000 spots displayed by 14 identical subarrays each with 406 antigens, where 105 of them represented SH2-domain containing proteins. Approximately 400 different affinity reagents of various types were analysed on these antigen microarrays carrying antigens of different types. The microarrays revealed not only very detailed specificity profiles for all the binders, but also showed that overlapping target sequences of spotted antigens were detected by off-target interactions. The presented study illustrates the feasibility of using antigen microarrays for integrative, high-throughput validation of various types of binders and antigens.

  • 16.
    Sjöstedt, Evelina
    et al.
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Systems Biology.
    Sivertsson, Åsa
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Systems Biology.
    Norradin, Feria Hikmet
    Department of Immunology, Genetics and Pathology, Uppsala University.
    Katona, Borbala
    Department of Immunology, Genetics and Pathology, Uppsala University.
    Näsström, Åsa
    Rudbeck Laboratory, Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, Sweden.
    Vuu, Jimmy
    Department of Immunology, Genetics and Pathology, Uppsala university.
    Kesti, Dennis
    Department of Immunology, Genetics and Pathology, Uppsala University.
    Oksvold, Per
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Edqvist, Per-Henrik
    Department of Immunology, Genetics and Pathology, Uppsala University.
    Olsson, Ingmarie
    Department of Immunology, Genetics and Pathology, Uppsala University.
    Uhlén, Mathias
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Systems Biology.
    Lindskog, Cecilia
    Department of Immunology, Genetics and Pathology, Uppsala University.
    Integration of Transcriptomics and Antibody-Based Proteomics for Exploration of Proteins Expressed in Specialized Tissues2018In: Journal of Proteome Research, ISSN 1535-3893, E-ISSN 1535-3907, Vol. 17, no 12, p. 4127-4137Article in journal (Refereed)
    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.

  • 17.
    Stadler, Charlotte
    et al.
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Fagerberg, Linn
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Sivertsson, Åsa
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Oksvold, Per
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Zwahlen, Martin
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Hallström, Björn M.
    Lundberg, Emma
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Uhlén, Mathias
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    RNA- and Antibody-Based Profiling of the Human Proteome with Focus on Chromosome 192014In: Journal of Proteome Research, ISSN 1535-3893, E-ISSN 1535-3907, Vol. 13, no 4, p. 2019-2027Article in journal (Refereed)
    Abstract [en]

    An important part of the Human Proteome Project is to characterize the protein complement of the genome with antibody-based profiling. Within the framework of this effort, a new version 12 of the Human Protein Atlas (www.proteinatlas.org) has been launched, including transcriptomics data for 27 tissues and 44 cell lines to complement the protein expression data from antibody-based profiling. Besides the extensive addition of transcriptomics data, the Human Protein Atlas now contains antibody-based protein profiles for 82% of the 20 329 putative protein-coding genes. The comprehensive data resulting from RNA-seq analysis and antibody-based profiling performed within the Human Protein Atlas as well as information from UniProt were used to generate evidence summary scores for each of the 20 329 genes, of which 94% now have experimental evidence at least at transcript level. The evidence scores for all individual genes are displayed with regards to both RNA- and antibody-based protein profiles, including chromosome-centric visualizations. An analysis of the human chromosome 19 shows that similar to 43% of the genes are expressed at the transcript level in all 27 tissues analyzed, suggesting a "house-keeping" function, while 12% of the genes show a more tissue-specific pattern with enriched expression in one of the analyzed tissues only.

  • 18.
    Szigyarto, C. Al-Khalili
    et al.
    KTH, Superseded Departments (pre-2005), Biotechnology.
    Berglund, L.
    KTH, Superseded Departments (pre-2005), Biotechnology.
    Sivertsson, Åsa
    KTH, Superseded Departments (pre-2005), Biotechnology.
    Lindskog, M.
    KTH, Superseded Departments (pre-2005), Biotechnology.
    Rockberg, J.
    KTH, Superseded Departments (pre-2005), Biotechnology.
    Westberg, J.
    KTH, Superseded Departments (pre-2005), Biotechnology.
    Agaton, L.
    KTH, Superseded Departments (pre-2005), Biotechnology.
    Persson, A.
    KTH, Superseded Departments (pre-2005), Biotechnology. Royal Inst Technol, Dept Mol Biotechnol, Stockholm, Sweden..
    Uhlén, Mathias
    KTH, Superseded Departments (pre-2005), Biotechnology.
    Statistics of protein epitope signature tag design within the Swedish human proteom resource2004In: Molecular & Cellular Proteomics, ISSN 1535-9476, E-ISSN 1535-9484, Vol. 3, no 10, p. S91-S91Article in journal (Other academic)
  • 19.
    Thul, Peter J.
    et al.
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Åkesson, Lovisa
    KTH, School of Biotechnology (BIO). KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Wiking, Mikaela
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Mahdessian, Diana
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Geladaki, A.
    Ait Blal, Hammou
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Alm, Tove L.
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Asplund, A.
    Björk, Lars
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Breckels, L. M.
    Bäckström, Anna
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Danielsson, Frida
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Fagerberg, Linn
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Fall, Jenny
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Gatto, L.
    Gnann, Christian
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Hober, Sophia
    KTH, School of Biotechnology (BIO), Protein Technology.
    Hjelmare, Martin
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Johansson, Fredric
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Lee, Sunjae
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Lindskog, C.
    Mulder, J.
    Mulvey, C. M.
    Nilsson, Peter
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Oksvold, Per
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Rockberg, Johan
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology.
    Schutten, Rutger
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Schwenk, Jochen M.
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Sivertsson, Åsa
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Sjöstedt, E.
    Skogs, Marie
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Stadler, Charlotte
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Sullivan, Devin P.
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Tegel, Hanna
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology.
    Winsnes, Casper F.
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Zhang, Cheng
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Zwahlen, Martin
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Mardinoglu, Adil
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Pontén, F.
    von Feilitzen, Kalle
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Lilley, K. S.
    Uhlén, Mathias
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology.
    Lundberg, Emma
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology.
    A subcellular map of the human proteome2017In: Science, ISSN 0036-8075, E-ISSN 1095-9203, Vol. 356, no 6340, article id 820Article in journal (Refereed)
    Abstract [en]

    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.

  • 20.
    Uhlén, Mathias
    et al.
    KTH, School of Biotechnology (BIO), Proteomics (closed 20130101).
    Björling, Erik
    KTH, School of Biotechnology (BIO).
    Agaton, Charlotta
    KTH, School of Biotechnology (BIO).
    Al-Khalili Szigyarto, Cristina
    KTH, School of Biotechnology (BIO).
    Amini, Bahram
    KTH, School of Biotechnology (BIO).
    Andersen, Elisabet
    Uppsala Univ, Rudbeck Lab, Dept Genet & Pathol.
    Andersson, Ann-Catrin
    Uppsala Univ, Rudbeck Lab, Dept Genet & Pathol.
    Angelidou, Pia
    KTH, School of Biotechnology (BIO).
    Asplund, Anna
    Uppsala Univ, Rudbeck Lab, Dept Genet & Pathol.
    Asplund, Caroline
    KTH, School of Biotechnology (BIO).
    Berglund, Lisa
    KTH, School of Biotechnology (BIO).
    Bergström, Kristina
    KTH, School of Biotechnology (BIO).
    Brumer, Harry
    KTH, School of Biotechnology (BIO).
    Cerjan, Dijana
    Uppsala Univ, Rudbeck Lab, Dept Genet & Pathol.
    Ekström, Marica
    KTH, School of Biotechnology (BIO).
    Elobeid, Adila
    Uppsala Univ, Rudbeck Lab, Dept Genet & Pathol.
    Eriksson, Cecilia
    KTH, School of Biotechnology (BIO).
    Fagerberg, Linn
    KTH, School of Biotechnology (BIO).
    Falk, Ronny
    KTH, School of Biotechnology (BIO).
    Fall, Jenny
    KTH, School of Biotechnology (BIO).
    Forsberg, Mattias
    KTH, School of Biotechnology (BIO).
    Gry Björklund, Marcus
    KTH, School of Biotechnology (BIO).
    Gumbel, Kristoffer
    Uppsala Univ, Rudbeck Lab, Dept Genet & Pathol.
    Halimi, Asif
    KTH, School of Biotechnology (BIO).
    Hallin, Inga
    Uppsala Univ, Rudbeck Lab, Dept Genet & Pathol.
    Hamsten, Carl
    KTH, School of Biotechnology (BIO), Proteomics (closed 20130101).
    Hansson, Marianne
    KTH, School of Biotechnology (BIO).
    Hedhammar, My
    KTH, School of Biotechnology (BIO).
    Hercules, Görel
    Uppsala Univ, Rudbeck Lab, Dept Genet & Pathol.
    Kampf, Caroline
    Uppsala Univ, Rudbeck Lab, Dept Genet & Pathol.
    Larsson, Karin
    KTH, School of Biotechnology (BIO).
    Lindskog, Mats
    KTH, School of Biotechnology (BIO).
    Lodewyckx, Wald
    KTH, School of Biotechnology (BIO).
    Lund, Jan
    KTH, School of Biotechnology (BIO).
    Lundeberg, Joakim
    KTH, School of Biotechnology (BIO).
    Magnusson, Kristina
    Uppsala Univ, Rudbeck Lab, Dept Genet & Pathol.
    Malm, Erik
    KTH, School of Biotechnology (BIO).
    Nilsson, Peter
    KTH, School of Biotechnology (BIO).
    Ödling, Jenny
    KTH, School of Biotechnology (BIO).
    Oksvold, Per
    KTH, School of Biotechnology (BIO).
    Olsson, Ingmarie
    Uppsala Univ, Rudbeck Lab, Dept Genet & Pathol.
    Öster, Emma
    KTH, School of Biotechnology (BIO).
    Ottosson, Jenny
    KTH, School of Biotechnology (BIO).
    Paavilainen, Linda
    Uppsala Univ, Rudbeck Lab, Dept Genet & Pathol.
    Persson, Anja
    KTH, School of Biotechnology (BIO), Proteomics (closed 20130101).
    Rimini, Rebecca
    KTH, School of Biotechnology (BIO).
    Rockberg, Johan
    KTH, School of Biotechnology (BIO).
    Runeson, Marcus
    Uppsala Univ, Rudbeck Lab, Dept Genet & Pathol.
    Sivertsson, Åsa
    KTH, School of Biotechnology (BIO).
    Sköllermo, Anna
    KTH, School of Biotechnology (BIO).
    Steen, Johanna
    KTH, School of Biotechnology (BIO).
    Stenvall, Maria
    KTH, School of Biotechnology (BIO).
    Sterky, Fredrik
    KTH, School of Biotechnology (BIO).
    Strömberg, Sara
    Uppsala Univ, Rudbeck Lab, Dept Genet & Pathol.
    Sundberg, Mårten
    KTH, School of Biotechnology (BIO).
    Tegel, Hanna
    KTH, School of Biotechnology (BIO).
    Tourle, Samuel
    KTH, School of Biotechnology (BIO).
    Wahlund, Eva
    Uppsala Univ, Rudbeck Lab, Dept Genet & Pathol.
    Waldén, Annelie
    KTH, School of Biotechnology (BIO).
    Wan, Jinghong
    KTH, School of Biotechnology (BIO), Molecular Biotechnology (closed 20130101).
    Wernérus, Henrik
    KTH, School of Biotechnology (BIO), Proteomics (closed 20130101).
    Westberg, Joakim
    KTH, School of Biotechnology (BIO).
    Wester, Kenneth
    Uppsala Univ, Rudbeck Lab, Dept Genet & Pathol.
    Wrethagen, Ulla
    KTH, School of Biotechnology (BIO).
    Xu, Lan Lan
    KTH, School of Biotechnology (BIO).
    Hober, Sophia
    KTH, School of Biotechnology (BIO), Proteomics (closed 20130101).
    Pontén, Fredrik
    Uppsala Univ, Rudbeck Lab, Dept Genet & Pathol.
    A human protein atlas for normal and cancer tissues based on antibody proteomics2005In: Molecular & Cellular Proteomics, ISSN 1535-9476, E-ISSN 1535-9484, Vol. 4, no 12, p. 1920-1932Article in journal (Refereed)
    Abstract [en]

    Antibody-based proteomics provides a powerful approach for the functional study of the human proteome involving the systematic generation of protein-specific affinity reagents. We used this strategy to construct a comprehensive, antibody-based protein atlas for expression and localization profiles in 48 normal human tissues and 20 different cancers. Here we report a new publicly available database containing, in the first version, similar to 400,000 high resolution images corresponding to more than 700 antibodies toward human proteins. Each image has been annotated by a certified pathologist to provide a knowledge base for functional studies and to allow queries about protein profiles in normal and disease tissues. Our results suggest it should be possible to extend this analysis to the majority of all human proteins thus providing a valuable tool for medical and biological research.

  • 21.
    Uhlén, Mathias
    et al.
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology.
    Fagerberg, Linn
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Hallström, Björn M
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology.
    Lindskog, Cecilia
    Oksvold, Per
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Mardinoglu, Adil
    Sivertsson, Åsa
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Kampf, Caroline
    Sjöstedt, Evelina
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Asplund, Anna
    Olsson, IngMarie
    Edlund, Karolina
    Lundberg, Emma
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Navani, Sanjay
    Szigyarto, Cristina Al-Khalili
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology.
    Odeberg, Jacob
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Djureinovic, Dijana
    Takanen, Jenny Ottosson
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology.
    Hober, Sophia
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology.
    Alm, Tove
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Edqvist, Per-Henrik
    Berling, Holger
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology.
    Tegel, Hanna
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology.
    Mulder, Jan
    Rockberg, Johan
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology.
    Nilsson, Peter
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Schwenk, Jochen M
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Hamsten, Marica
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology.
    von Feilitzen, Kalle
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Forsberg, Mattias
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Persson, Lukas
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Johansson, Fredric
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Zwahlen, Martin
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    von Heijne, Gunnar
    Nielsen, Jens
    Pontén, Fredrik
    Tissue-based map of the human proteome2015In: Science, ISSN 0036-8075, E-ISSN 1095-9203, Vol. 347, no 6220, p. 1260419-Article in journal (Refereed)
    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.

  • 22.
    Uhlén, Mathias
    et al.
    KTH, School of Biotechnology (BIO), Proteomics (closed 20130101). KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Oksvold, Per
    KTH, School of Biotechnology (BIO), Proteomics (closed 20130101).
    Älgenäs, Cajsa
    KTH, School of Biotechnology (BIO), Proteomics (closed 20130101).
    Hamsten, Carl
    KTH, School of Biotechnology (BIO), Proteomics (closed 20130101).
    Fagerberg, Linn
    KTH, School of Biotechnology (BIO), Proteomics (closed 20130101).
    Klevebring, Daniel
    Department of Medical Epidemiology, Karolinska Institute.
    Lundberg, Emma
    KTH, School of Biotechnology (BIO), Proteomics (closed 20130101). KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Odeberg, Jacob
    KTH, School of Biotechnology (BIO), Proteomics (closed 20130101). KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Pontén, Fredrik
    Kondo, Tadashi
    Sivertsson, Åsa
    KTH, School of Biotechnology (BIO), Proteomics (closed 20130101).
    Antibody-based Protein Profiling of the Human Chromosome 212012In: Molecular & Cellular Proteomics, ISSN 1535-9476, E-ISSN 1535-9484, Vol. 11, no 3Article in journal (Refereed)
    Abstract [en]

    A Human Proteome Project has been proposed to create a knowledgebased resource based on a systematical mapping of all human proteins, chromosome by chromosome, in a gene-centric manner. With this background, we here describe the systematic analysis of chromosome 21 using an antibody-based approach for protein profiling using both confocal microscopy and immunohistochemistry, complemented with transcript profiling using next generation sequencing data. We also describe a new approach for protein isoform analysis using a combination of antibody-based probing and isoelectric focusing. The analysis has identified several genes on chromosome 21 with no previous evidence on the protein level and the isoform analysis indicates that a large fraction of human proteins have multiple isoforms. A chromosome-wide matrix is presented with status for all chromosome 21 genes regarding subcellular localization, tissue distribution and molecular characterization of the corresponding proteins. The path to generate a chromosome-specific resource, including integrated data from complementary assay platforms, such as mass spectrometry and gene tagging analysis, is discussed.

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