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  • 1.
    Andrade, Jorge
    et al.
    KTH, School of Biotechnology (BIO), Gene Technology.
    Andersen, Malin
    KTH, School of Biotechnology (BIO), Gene Technology.
    Berglund, Lisa
    KTH, School of Biotechnology (BIO), Proteomics.
    Odeberg, Jacob
    KTH, School of Biotechnology (BIO), Gene Technology.
    Applications of grid computing in genetics and proteomics2007In: Applied Parallel Computing: State Of The Art In Scientific Computing / [ed] Kagstrom, B; Elmroth, E; Dongarra, J; Wasniewski, J, 2007, Vol. 4699, p. 791-798Conference paper (Refereed)
    Abstract [en]

    The potential for Grid technologies in applied bioinformatics is largely unexplored. We have developed a model for solving computationally demanding bioinformatics tasks in distributed Grid environments, designed to ease the usability for scientists unfamiliar with Grid computing. With a script-based implementation that uses a strategy of temporary installations of databases and existing executables on remote nodes at submission, we propose a generic solution that do not rely on predefined Grid runtime environments and that can easily be adapted to other bioinformatics tasks suitable for parallelization. This implementation has been successfully applied to whole proteome sequence similarity analyses and to genome-wide genotype simulations, where computation time was reduced from years to weeks. We conclude that computational Grid technology is a useful resource for solving high compute tasks in genetics and proteomics using existing algorithms.

  • 2.
    Andrade, Jorge
    et al.
    KTH, School of Biotechnology (BIO), Gene Technology.
    Berglund, Lisa
    KTH, School of Biotechnology (BIO), Gene Technology.
    Uhlén, Mathias
    KTH, School of Biotechnology (BIO), Gene Technology.
    Odeberg, Jacob
    KTH, School of Biotechnology (BIO), Gene Technology.
    Using Grid Technology for Computationally Intensive Applied Bioinformatics Analyses2006In: In Silico Biology, ISSN 1386-6338, Vol. 6, no 6, p. 495-504Article in journal (Refereed)
    Abstract [en]

    For several applications and algorithms used in applied bioinformatics, a bottle neck in terms of computational time may arise when scaled up to facilitate analyses of large datasets and databases. Re-codification, algorithm modification or sacrifices in sensitivity and accuracy may be necessary to accommodate for limited computational capacity of single work stations. Grid computing offers an alternative model for solving massive computational problems by parallel execution of existing algorithms and software implementations. We present the implementation of a Grid-aware model for solving computationally intensive bioinformatic analyses exemplified by a blastp sliding window algorithm for whole proteome sequence similarity analysis, and evaluate the performance in comparison with a local cluster and a single workstation. Our strategy involves temporary installations of the BLAST executable and databases on remote nodes at submission, accommodating for dynamic Grid environments as it avoids the need of predefined runtime environments (preinstalled software and databases at specific Grid-nodes). Importantly, the implementation is generic where the BLAST executable can be replaced by other software tools to facilitate analyses suitable for parallelisation. This model should be of general interest in applied bioinformatics. Scripts and procedures are freely available from the authors.

  • 3.
    Berglund, Lisa
    KTH, School of Biotechnology (BIO), Proteomics.
    Selection of antigens for antibody-based proteomics2008Doctoral thesis, comprehensive summary (Other scientific)
    Abstract [en]

    The human genome is predicted to contain ~20,500 protein-coding genes. The encoded proteins are the key players in the body, but the functions and localizations of most proteins are still unknown. Antibody-based proteomics has great potential for exploration of the protein complement of the human genome, but there are antibodies only to a very limited set of proteins. The Human Proteome Resource (HPR) project was launched in August 2003, with the aim to generate high-quality specific antibodies towards the human proteome, and to use these antibodies for large-scale protein profiling in human tissues and cells.

    The goal of the work presented in this thesis was to evaluate if antigens can be selected, in a high-throughput manner, to enable generation of specific antibodies towards one protein from every human gene. A computationally intensive analysis of potential epitopes in the human proteome was performed and showed that it should be possible to find unique epitopes for most human proteins. The result from this analysis was implemented in a new web-based visualization tool for antigen selection. Predicted protein features important for antigen selection, such as transmembrane regions and signal peptides, are also displayed in the tool. The antigens used in HPR are named protein epitope signature tags (PrESTs). A genome-wide analysis combining different protein features revealed that it should be possible to select unique, 50 amino acids long PrESTs for ~80% of the human protein-coding genes.

    The PrESTs are transferred from the computer to the laboratory by design of PrEST-specific PCR primers. A study of the success rate in PCR cloning of the selected fragments demonstrated the importance of controlled GC-content in the primers for specific amplification. The PrEST protein is produced in bacteria and used for immunization and subsequent affinity purification of the resulting sera to generate mono-specific antibodies. The antibodies are tested for specificity and approved antibodies are used for tissue profiling in normal and cancer tissues. A large-scale analysis of the success rates for different PrESTs in the experimental pipeline of the HPR project showed that the total success rate from PrEST selection to an approved antibody is 31%, and that this rate is dependent on PrEST length. A second PrEST on a target protein is somewhat less likely to succeed in the HPR pipeline if the first PrEST is unsuccessful, but the analysis shows that it is valuable to select several PrESTs for each protein, to enable generation of at least two antibodies, which can be used to validate each other.

  • 4.
    Berglund, Lisa
    et al.
    KTH, School of Biotechnology (BIO).
    Andrade, Jorge
    KTH, School of Biotechnology (BIO).
    Odeberg, Jacob
    KTH, School of Biotechnology (BIO).
    Uhlén, Mathias
    KTH, School of Biotechnology (BIO).
    The epitope space of the human proteome2008In: Protein Science, ISSN 0961-8368, E-ISSN 1469-896X, Vol. 17, no 4, p. 606-613Article in journal (Refereed)
    Abstract [en]

    In the post-genome era, there is a great need for protein-specific affinity reagents to explore the human proteome. Antibodies are suitable as reagents, but generation of antibodies with low cross-reactivity to other human proteins requires careful selection of antigens. Here we show the results from a proteomewide effort to map linear epitopes based on uniqueness relative to the entire human proteome. The analysis was based on a sliding window sequence similarity search using short windows (8, 10, and 12 amino acid residues). A comparison of exact string matching (Hamming distance) and a heuristic method (BLAST) was performed, showing that the heuristic method combined with a grid strategy allows for whole proteome analysis with high accuracy and feasible run times. The analysis shows that it is possible to find unique antigens for a majority of the human proteins, with relatively strict rules involving low sequence identity of the possible linear epitopes. The implications for human antibody-based proteomics efforts are discussed.

  • 5.
    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.

  • 6.
    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.

  • 7.
    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.

  • 8.
    Berglund, Lisa
    et al.
    KTH, School of Biotechnology (BIO).
    Persson, Anja
    KTH, School of Biotechnology (BIO).
    Uhlén, Mathias
    KTH, School of Biotechnology (BIO).
    Primer design for high-throughput PCR cloningArticle in journal (Other academic)
  • 9.
    Fagerberg, Linn
    et al.
    KTH, School of Biotechnology (BIO), Proteomics.
    Jonasson, Kalle
    KTH, School of Biotechnology (BIO), Proteomics.
    von Heijne, Gunnar
    Uhlén, Mathias
    KTH, School of Biotechnology (BIO), Proteomics.
    Berglund, Lisa
    KTH, School of Biotechnology (BIO), Proteomics.
    Prediction of the human membrane proteome2010In: Proteomics, ISSN 1615-9853, E-ISSN 1615-9861, Vol. 10, no 6, p. 1141-1149Article in journal (Refereed)
    Abstract [en]

    Membrane proteins are key molecules in the cell, and are important targets for pharmaceutical drugs. Few three-dimensional structures of membrane proteins have been obtained, which makes computational prediction of membrane proteins crucial for studies of these key molecules. Here, seven membrane protein topology prediction methods based on different underlying algorithms, such as hidden Markov models, neural networks and support vector machines, have been used for analysis of the protein sequences from the 21 416 annotated genes in the human genome. The number of genes coding for a protein with predicted cc-helical transmembrane region(s) ranged from 5508 to 7651, depending on the method used. Based on a majority decision method, we estimate 5539 human genes to code for membrane proteins, corresponding to approximately 26% of the human protein-coding genes. The largest fraction of these proteins has only one predicted transmembrane region, but there are also many proteins with seven predicted transmembrane regions, including the G-protein coupled receptors. A visualization tool displaying the topologies suggested by the eight prediction methods, for all predicted membrane proteins, is available on the public Human Protein Atlas portal (www.proteinatlas.org).

  • 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.
    Jonasson, Kalle
    et al.
    KTH, School of Biotechnology (BIO), Proteomics (closed 20130101).
    Berglund, Lisa
    KTH, School of Biotechnology (BIO), Proteomics (closed 20130101).
    Uhlén, Mathias
    KTH, School of Biotechnology (BIO), Proteomics (closed 20130101).
    The 6th HUPO Antibody Initiative (HAI) workshop: Sharing data about affinity reagents and other recent developments2010In: Proteomics, ISSN 1615-9853, E-ISSN 1615-9861, Vol. 10, no 11, p. 2066-2068Article in journal (Refereed)
    Abstract [en]

    The Human Antibody Initiative (HAI) aims to promote and facilitate the use of antibodies for proteomics research. The 6th workshop for the HUPO Antibody Initiative (HAI) held in September 2009 was co-chaired by Michael Snyder and Mathias Uhlen and discussed several aspects of antibody production, their validation, and attempts to standardise this process, in particular, when subsequently described in the literature. An update on the progress of the Human Protein Atlas was also presented to the attendees.

  • 12.
    Larsson, Karin
    et al.
    KTH, School of Biotechnology (BIO), Proteomics.
    Eriksson, Cecilia
    KTH, School of Biotechnology (BIO), Proteomics.
    Schwenk, Jochen. M.
    KTH, School of Biotechnology (BIO), Proteomics.
    Berglund, Lisa
    KTH, School of Biotechnology (BIO), Proteomics.
    Hober, Sophia
    KTH, School of Biotechnology (BIO), Proteomics.
    Uhlén, Mattias
    KTH, School of Biotechnology (BIO), Proteomics.
    Characterization of PrEST-based antibodies towards human Cytokeratin-172009In: JIM - Journal of Immunological Methods, ISSN 0022-1759, E-ISSN 1872-7905, Vol. 342, p. 20-32Article in journal (Refereed)
    Abstract [en]

    Antibody-based proteomics efforts depend on validated antibodies to ensure correct annotation of analyzed proteins. We have previously argued that a low sequence identity to other proteins is a key feature for antigens used in antibody generation. Thus, a major challenge for whole-proteome studies is how to address families of highly sequence related proteins within the context of generating specific antibodies. In this study, two non-overlapping parts of human Cytokeratin-17, a protein belonging to the intermediate filament family of highly sequence-related proteins, were selected as a model system to study the specificity and cross reactivity of antibodies generated towards such a target. These recombinantly produced Protein Epitope Signature Tags (PrESTs) were immunized in five rabbits each and the batch-to-batch variations in the obtained immune responses were studied by mapping of linear epitopes using synthetic overlapping peptides. The obtained results showed a similar but not identical immune response in the respective antibody groups with a limited number of epitopes being identified. Immunohistochemical analysis of the affinity purified monospecific antibodies on tissue micro arrays resulted in a general recognition of human cytokeratins for all analyzed binders whereas antibodies identified as binding to the most unique parts of the PrESTs showed the most Cytokeratin-17 like staining. The data presented here support the strategy to use sequence identity scores as the main criteria for antigen selection but also indicate the possibility to instead produce a single antibody recognizing a defined group of proteins when the intended targets overall sequence identity score is too high. This type of group-specific antibodies would be an important tool for antibody-based projects aiming for a complete coverage of the human proteome.

  • 13.
    Pontén, Fredrik
    et al.
    Department of Genetics and Pathology, The Rudbeck Laboratory, Uppsala University.
    Gry, Marcus
    KTH, School of Biotechnology (BIO), Proteomics.
    Björling, Erik
    KTH, School of Biotechnology (BIO), Proteomics.
    Berglund, Lisa
    KTH, School of Biotechnology (BIO), Proteomics.
    Al-Khalili Szigyarto, Cristina
    KTH, School of Biotechnology (BIO), Proteomics.
    Lundberg, Emma
    KTH, School of Biotechnology (BIO), Proteomics.
    Andersson-Svahn, Helene
    KTH, School of Biotechnology (BIO), Proteomics.
    Asplund, Anna
    Department of Genetics and Pathology, The Rudbeck Laboratory, Uppsala University.
    Hober, Sophia
    KTH, School of Biotechnology (BIO), Proteomics.
    Kampf, Caroline
    Department of Genetics and Pathology, The Rudbeck Laboratory, Uppsala University.
    Nilsson, Kenneth
    Department of Genetics and Pathology, The Rudbeck Laboratory, Uppsala University.
    Nilsson, Peter
    KTH, School of Biotechnology (BIO), Proteomics.
    Ottosson, Jenny
    KTH, School of Biotechnology (BIO), Proteomics.
    Persson, Anja
    KTH, School of Biotechnology (BIO), Proteomics.
    Wernérus, Henrik
    KTH, School of Biotechnology (BIO), Proteomics.
    Wester, Kenneth
    Department of Genetics and Pathology, The Rudbeck Laboratory, Uppsala University.
    Uhlén, Mathias
    KTH, School of Biotechnology (BIO), Proteomics.
    Ubiquitous protein expression in human cells, tissues and organsManuscript (Other academic)
  • 14.
    Ståhl, Patrik L.
    et al.
    KTH, School of Biotechnology (BIO), Gene Technology.
    Stranneheim, Hanrik
    KTH, School of Biotechnology (BIO), Gene Technology.
    Asplund, Anna
    Berglund, Lisa
    KTH, School of Biotechnology (BIO), Proteomics.
    Pontén, Fredrik
    Lundeberg, Joakim
    KTH, School of Biotechnology (BIO), Gene Technology.
    Sun‐induced Missense Mutations Are Extensively Accumulated and Tolerated in Phenotypically Intact Stem Cell Compartments of Human SkinArticle in journal (Refereed)
    Abstract [en]

    Here we demonstrate that intermittently sun‐exposed human skin contains an extensive number of phenotypically intact stem cell compartments bearing missense mutations in the p53 tumor suppressor gene. Deep sequencing of sun‐exposed and shielded microdissected skin from mid‐life individuals revealed that persistent p53 mutations had accumulated in 14% of all epidermal cells, with no apparent signs of a growth advantage of the affected cell compartments. Furthermore, 6% of the mutated epidermal cells encoded a truncated protein. The abundance of these events, not taking into account intron mutations and mutations in other genes that also may have functional implications, suggests an extensive tolerance of human cells to severe genetic alterations caused by ultraviolet light, with an estimated annual rate of accumulation of approximately 35,000 new persistent protein altering p53 mutations in sun exposed skin of a human individual.

  • 15.
    Ståhl, Patrik L.
    et al.
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Biotechnology (BIO), Gene Technology.
    Stranneheim, Henrik
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Biotechnology (BIO), Gene Technology.
    Asplund, Anna
    Berglund, Lisa
    KTH, School of Biotechnology (BIO), Proteomics (closed 20130101). KTH, School of Biotechnology (BIO), Centres, Albanova VinnExcellence Center for Protein Technology, ProNova.
    Pontén, Fredrik
    Lundeberg, Joakim
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Biotechnology (BIO), Gene Technology.
    Sun-Induced Nonsynonymous p53 Mutations Are Extensively Accumulated and Tolerated in Normal Appearing Human Skin2011In: Journal of Investigative Dermatology, ISSN 0022-202X, E-ISSN 1523-1747, Vol. 131, no 2, p. 504-508Article in journal (Refereed)
    Abstract [en]

    Here we demonstrate that intermittently sun-exposed human skin contains an extensive number of phenotypically intact cell compartments bearing missense and nonsense mutations in the p53 tumor suppressor gene. Deep sequencing of sun-exposed and shielded microdissected skin from mid-life individuals revealed that persistent p53 mutations had accumulated in 14% of all epidermal cells, with no apparent signs of a growth advantage of the affected cell compartments. Furthermore, 6% of the mutated epidermal cells encoded a truncated protein. The abundance of these events, not taking into account intron mutations and mutations in other genes that also may have functional implications, suggests an extensive tolerance of human cells to severe genetic alterations caused by UV light, with an estimated annual rate of accumulation of similar to 35,000 new persistent protein-altering p53 mutations in sun-exposed skin of a human individual.

  • 16.
    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.

  • 17.
    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).
    Fagerberg, Linn
    KTH, School of Biotechnology (BIO), Proteomics (closed 20130101).
    Lundberg, Emma
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Biotechnology (BIO), Proteomics (closed 20130101).
    Jonasson, Kalle
    KTH, School of Biotechnology (BIO), Proteomics (closed 20130101).
    Forsberg, Mattias
    KTH, School of Biotechnology (BIO), Proteomics (closed 20130101).
    Zwahlen, Martin
    KTH, School of Biotechnology (BIO), Proteomics (closed 20130101).
    Kampf, Caroline
    Uppsala Univ, Rudbeck Lab, Dept Genet & Pathol.
    Wester, Kenneth
    Uppsala Univ, Rudbeck Lab, Dept Genet & Pathol.
    Hober, Sophia
    KTH, School of Biotechnology (BIO), Proteomics (closed 20130101).
    Wernérus, Henrik
    KTH, School of Biotechnology (BIO), Proteomics (closed 20130101).
    Björling, Lisa
    KTH, School of Biotechnology (BIO), Proteomics (closed 20130101).
    Pontén, Fredrik
    Uppsala Univ, Rudbeck Lab, Dept Genet & Pathol.
    Towards a knowledge-based Human Protein Atlas2010In: Nature Biotechnology, ISSN 1087-0156, E-ISSN 1546-1696, Vol. 28, no 12, p. 1248-1250Article in journal (Refereed)
  • 18.
    Älgenäs, Cajsa
    et al.
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology.
    Agaton, Charlotta
    Fagerberg, Linn
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Asplund, Anna
    Björling, Lisa
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Björling, Erik
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology.
    Kampf, Caroline
    Lundberg, Emma
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Nilsson, Peter
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Persson, Anja
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology.
    Wester, Kenneth
    Pontén, Fredrik
    Wernerus, Henrik
    Uhlén, Mathias
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Ottosson Takanen, Jenny
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology.
    Hober, Sophia
    KTH, School of Biotechnology (BIO), Protein Technology.
    Antibody performance in western blot applications is context- dependent2014In: Biotechnology Journal, ISSN 1860-6768, E-ISSN 1860-7314, Vol. 9, no 3, p. 435-445Article in journal (Refereed)
    Abstract [en]

    An important concern for the use of antibodies in various applications, such as western blot (WB) or immunohistochemistry (IHC), is specificity. This calls for systematic validations using well-designed conditions. Here, we have analyzed 13000 antibodies using western blot with lysates from human cell lines, tissues, and plasma. Standardized stratification showed that 45% of the antibodies yielded supportive staining, and the rest either no staining (12%) or protein bands of wrong size (43%). A comparative study of WB and IHC showed that the performance of antibodies is application-specific, although a correlation between no WB staining and weak IHC staining could be seen. To investigate the influence of protein abundance on the apparent specificity of the antibody, new WB analyses were performed for 1369 genes that gave unsupportive WBs in the initial screening using cell lysates with overexpressed full-length proteins. Then, more than 82% of the antibodies yielded a specific band corresponding to the full-length protein. Hence, the vast majority of the antibodies (90%) used in this study specifically recognize the target protein when present at sufficiently high levels. This demonstrates the context- and application-dependence of antibody validation and emphasizes that caution is needed when annotating binding reagents as specific or cross-reactive. WB is one of the most commonly used methods for validation of antibodies. Our data implicate that solely using one platform for antibody validation might give misleading information and therefore at least one additional method should be used to verify the achieved data.

1 - 18 of 18
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