Change search
Refine search result
1 - 19 of 19
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Rows per page
  • 5
  • 10
  • 20
  • 50
  • 100
  • 250
Sort
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
Select
The maximal number of hits you can export is 250. When you want to export more records please use the Create feeds function.
  • 1.
    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.

  • 2. Bergström, Jonas P.
    et al.
    Gry, Marcus
    Lengqvist, Johan
    Lindberg, Johan
    Schwenk, Jochen
    KTH, School of Biotechnology (BIO), Proteomics (closed 20130101). KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Nilsson, Peter
    KTH, School of Biotechnology (BIO), Proteomics (closed 20130101). KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Drobin, Kimi
    KTH, School of Biotechnology (BIO), Proteomics (closed 20130101). KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Watkins, Paul B.
    Schuppe Koistinen, Ina
    Novel DILI biomarkers for prediction of acetaminophen-induced human hepatotoxicity2012In: Toxicology Letters, ISSN 0378-4274, E-ISSN 1879-3169, Vol. 211, p. S76-S76Article in journal (Other academic)
  • 3.
    Fagerberg, Linn
    et al.
    KTH, School of Biotechnology (BIO), Proteomics.
    Stromberg, Sara
    El-Obeid, Adila
    Gry, Marcus
    KTH, School of Biotechnology (BIO), Proteomics.
    Nilsson, Kenneth
    Uhlén, Mathias
    KTH, School of Biotechnology (BIO), Proteomics.
    Ponten, Fredrik
    Asplund, Anna
    Large-Scale Protein Profiling in Human Cell Lines Using Antibody-Based Proteomics2011In: Journal of Proteome Research, ISSN 1535-3893, E-ISSN 1535-3907, Vol. 10, no 9, p. 4066-4075Article in journal (Refereed)
    Abstract [en]

    Human cancer cell lines grown in vitro are frequently used to decipher basic cell biological phenomena and to also specifically study different forms of cancer. Here we present the first large-scale study of protein expression patterns in cell lines using an antibody-based proteomics approach. We analyzed the expression pattern of 5436 proteins in 45 different cell lines using hierarchical clustering, principal component analysis, and two-group comparisons for the identification of differentially expressed proteins. Our results show that immunohistochemically determined protein profiles can categorize cell lines into groups that overall reflect the tumor tissue of origin and that hematological cell lines appear to retain their protein profiles to a higher degree than cell lines established from solid tumors. The two-group comparisons reveal well-characterized proteins as well as previously unstudied proteins that could be of potential interest for further investigations. Moreover, multiple myeloma cells and cells of myeloid origin were found to share a protein profile, relative to the protein profile of lymphoid leukemia and lymphoma cells, possibly reflecting their common dependency of bone marrow microenvironment. This work also provides an extensive list of antibodies, for which high-resolution images as well as validation data are available on the Human Protein Atlas (www.proteinatlas.org), that are of potential use in cell line studies.

  • 4.
    Fagerberg, Linn
    et al.
    KTH, School of Biotechnology (BIO), Proteomics.
    Strömberg, Sara
    El-Obeid, Adila
    Gry, Marcus
    KTH, School of Biotechnology (BIO), Proteomics.
    Nilsson, Kenneth
    Uhlén, Mathias
    KTH, School of Biotechnology (BIO), Proteomics.
    Ponten, Fredrik
    Adplund, Anna
    The Global Protein Expression Pattern in Human Cell LinesManuscript (preprint) (Other academic)
    Abstract [en]

    Human cancer cell lines grown in vitro are frequently used to decipher basic cell biological phenomena but also to specifically study different forms of cancer. Here we present the first large-scale study of protein expression patterns in cell lines using an antibody-based proteomics approach. We analyzed the expression pattern of 5436 proteins in 45 different cell lines using hierarchical clustering, principal component analysis and two-group comparisons for the identification of differentially expressed proteins. The results show that protein profiles of cell lines, as determined using immunohistochemistry, allow for a hierarchical clustering that overall reflects tumor tissues of origin. Hematological cell lines appear to retain their protein profiles to a higher degree than cell lines established from solid tumors, resulting in a clustering that well reflects progenitor cell types. The discrepancy may reflect different levels of in vitro induced alterations in adherent and suspension grown cell lines, respectively. In addition, multiple myeloma cells and cells of myeloid origin were found to share a protein profile, relative the protein profile of lymphoid leukemia and lymphoma cells, possibly reflecting their common dependency of bone marrow microenvironment.

     

  • 5.
    Gry, Marcus
    KTH, School of Biotechnology (BIO), Proteomics.
    Global expression analysis of human cells and tissues using antibodies2008Doctoral thesis, comprehensive summary (Other scientific)
    Abstract [en]

    To construct a complete map of the human proteome landscape is a vital part of the total understanding of the human body. Such a map could enrich the mankind to the extent that many severe diseases could be fully understood and hence could be treated with appropriate methods.

    In this study, immunohistochemical (IHC) data from ~6000 proteins, 65 cell types in 48 tissues and 47 cell lines has been used to investigate the human proteome regarding protein expression and localization. In order to analyze such a large data set, different statistical methods and algorithms has been applied and by using these tools, interesting features regarding the proteome was found. By using all available IHC data from 65 cell types in 48 tissues, it was found that the amount of tissue specific protein expression was surprisingly small, and the general impression from the analysis is that almost all proteins are present at all times in the cellular environment. Rather than tissue specific protein expression, the localization and minor concentration fluctuations of the proteins in the cell is responsible for molecular interaction and tissue specific cellular behavior. However, if a quarter of all proteins are used to distinguish different tissues types, there are a proportion of proteins that have certain expression profiles, which defines clusters of tissues of the same kind and embryonic origin.

    The estimation of expression levels using IHC is a labor-intensive method, which suffers from large variation between manual annotators. An automated image software tool was developed to circumvent this problem. The automated image software was shown to be more robust then manual annotators, and the quantification of expressed protein levels of the stained imaged was in the same range as the manual annotations.

    A more thorough investigation of the stained image estimations made by the automated software revield a significant correlation between the estimated protein expression and the cell size parameters provided by the automated software. To make it feasible to compare protein expression levels across different cell lines, without the cell line size bias, a normalization procedure was implemented and evaluated. It was found that when the normalization procedure was applied to the protein expression data, the correlation between protein expression values and cell size was minimized, and hence comparisons between cell lines regarding protein expression is possible.

    In addition, using the normalized protein expression data, an analysis to investigate the degree of correlation between mRNA levels and proteins for 1065 gene products was performed. By using two individual microarray data sets for estimation of RNA levels, and normalized protein data measured by the automated software as estimation of the protein levels, a mean correlation of ~0.3 for was found. This result indicates that a significant proportion of the manufactured antibodies, when used in IHC setup, are indeed an accurate measurement of protein expression levels.

    By using antibodies directed towards human proteins, plasma samples were investigated regarding metabolic dysfunctions. Since plasma is a complex sample, an optimization regarding protocol for quantification of expressed proteins was made. By using certain characteristics within the dataset, and by using a suspension bead microarray, the protocol could be evaluated. Expected characteristics within the dataset were found in the subsequent analysis, which showed that the protocol was functional. Using the same experimental outline will facilitate future applications, e.g. biomarker discovery. 

  • 6.
    Gry, Marcus
    et al.
    KTH, School of Biotechnology (BIO), Proteomics (closed 20130101). Uppsala University, Sweden.
    Oksvold, Per
    KTH, School of Biotechnology (BIO), Proteomics (closed 20130101).
    Pontén, F.
    Uhlén, Mathias
    KTH, School of Biotechnology (BIO), Proteomics (closed 20130101). KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Tissue-specific protein expression in human cells, tissues and organs2010In: Journal of Proteomics & Bioinformatics, ISSN 0974-276X, E-ISSN 0974-276X, Vol. 3, no 10, p. 286-293Article in journal (Refereed)
    Abstract [en]

    An important part of understanding human biology is the study of tissue-specific expression both at the gene and protein level. In this study, the analysis of tissue specific protein expression was performed based on tissue micro array data available on the public Human Protein Atlas database (www.proteinatlas.org). An analysis of human proteins, corresponding to approximately one third of the protein-encoding genes, was carried out in 65 human tissues and cell types. The spatial distribution and relative abundance of 6,678 human proteins, were analyzed in different cell populations from various organs and tissues in the human body using unsupervised methods, such as hierarchical clustering and principal component analysis, as well as with supervised methods (Breiman, 2001). Well-known markers, such as neuromodulin for the central nervous system, keratin 20 for gastrointestinal tract and CD45 for hematopoietic cells, were identified as tissue-specific. Proteins expressed in a tissue-specific manner were identified for cells in all of the investigated tissues, including the central nervous system, hematopoietic system, squamous epithelium, mesenchymal cells and cells from the gastrointestinal tract. Several proteins not yet associated with tissue-specificity were identified, providing starting points for further studies to explore tissue-specific functions. This includes proteins with no known function, such as ZNF509 expressed in CNS and C1orf201 expressed in the gastro-intestinal tract. In general, the majority of the gene products are expressed in a ubiquitous manner and few proteins are detected exclusively in cells from a particular tissue class, as exemplified by less than 1% of the analyzed proteins found only in the brain.

  • 7.
    Gry, Marcus
    et al.
    KTH, School of Biotechnology (BIO), Proteomics.
    Rimini, Rebecca
    KTH, School of Biotechnology (BIO), Proteomics.
    Strömberg, Sara
    Department of Genetics and Pathology, Rudbeck Laboratory, Uppsala University Hospital.
    Asplund, Anna
    Department of Genetics and Pathology, Rudbeck Laboratory, Uppsala University Hospital.
    Pontén, Fredrik
    Department of Genetics and Pathology, Rudbeck Laboratory, Uppsala University Hospital.
    Uhlén, Mathias
    KTH, School of Biotechnology (BIO), Proteomics.
    Nilsson, Peter
    KTH, School of Biotechnology (BIO), Proteomics.
    Correlations between RNA and protein expression profiles in 23 human cell lines2009In: BMC Genomics, ISSN 1471-2164, E-ISSN 1471-2164, Vol. 10Article in journal (Refereed)
    Abstract [en]

    Background: The Central Dogma of biology holds, in famously simplified terms, that DNA makes RNA makes proteins, but there is considerable uncertainty regarding the general, genome-wide correlation between levels of RNA and corresponding proteins. Therefore, to assess degrees of this correlation we compared the RNA profiles (determined using both cDNA- and oligo-based microarrays) and protein profiles (determined immunohistochemically in tissue microarrays) of 1066 gene products in 23 human cell lines. Results: A high mean correlation coefficient (0.52) was obtained from the pairwise comparison of RNA levels determined by the two platforms. Significant correlations, with correlation coefficients exceeding 0.445, between protein and RNA levels were also obtained for a third of the specific gene products. However, the correlation coefficients between levels of RNA and protein products of specific genes varied widely, and the mean correlations between the protein and corresponding RNA levels determined using the cDNA- and oligo-based microarrays were 0.25 and 0.20, respectively. Conclusion: Significant correlations were found in one third of the examined RNA species and corresponding proteins. These results suggest that RNA profiling might provide indirect support to antibodies’ specificity, since whenever a evident correlation between the RNA and protein profiles exists, this can sustain that the antibodies used in the immunoassay recognized their cognate antigens.

  • 8.
    Klevebring, Daniel
    et al.
    KTH, School of Biotechnology (BIO), Gene Technology.
    Gry, Marcus
    KTH, School of Biotechnology (BIO), Gene Technology.
    Lindberg, Johan
    KTH, School of Biotechnology (BIO), Gene Technology.
    Eidefors, Anna
    Lundeberg, Joakim
    KTH, School of Biotechnology (BIO), Gene Technology.
    Automation of cDNA Synthesis and Labelling Improves Reproducibility2009In: Journal of Biomedicine and Biotechnology, ISSN 1110-7243, E-ISSN 1110-7251, Vol. 2009, p. 396808-Article in journal (Refereed)
    Abstract [en]

    Background. Several technologies, such as in-depth sequencing and microarrays, enable large-scale interrogation of genomes and transcriptomes. In this study, we asses reproducibility and throughput by moving all laboratory procedures to a robotic workstation, capable of handling superparamagnetic beads. Here, we describe a fully automated procedure for cDNA synthesis and labelling for microarrays, where the purification steps prior to and after labelling are based on precipitation of DNA on carboxylic acid-coated paramagnetic beads. Results. The fully automated procedure allows for samples arrayed on a microtiter plate to be processed in parallel without manual intervention and ensuring high reproducibility. We compare our results to a manual sample preparation procedure and, in addition, use a comprehensive reference dataset to show that the protocol described performs better than similar manual procedures. Conclusions. We demonstrate, in an automated gene expression microarray experiment, a reduced variance between replicates, resulting in an increase in the statistical power to detect differentially expressed genes, thus allowing smaller differences between samples to be identified. This protocol can with minor modifications be used to create cDNA libraries for other applications such as in-depth analysis using next-generation sequencing technologies.

  • 9.
    Lundberg, Emma
    et al.
    KTH, School of Biotechnology (BIO), Proteomics.
    Gry, Marcus
    KTH, School of Biotechnology (BIO), Proteomics.
    Oksvold, Per
    KTH, School of Biotechnology (BIO), Proteomics.
    Kononen, Juha
    Beecher Instruments, Sun Prairie, WI USA.
    Andersson-Svahn, Helene
    KTH, School of Biotechnology (BIO), Proteomics.
    Pontén, Fredrik
    Uppsala Univ, Rudbeck Lab, Dept Genet & Pathol.
    Uhlén, Mathias
    KTH, School of Biotechnology (BIO), Proteomics.
    Asplund, Anna
    Uppsala Univ, Rudbeck Lab, Dept Genet & Pathol.
    The correlation between cellular size and protein expression levels: Normalization for global protein profiling2008In: Journal of Proteomics, ISSN 1874-3919, Vol. 71, no 4, p. 448-460Article in journal (Refereed)
    Abstract [en]

    An automated image analysis system was used for protein quantification of 1862 human proteins in 47 cancer cell lines and 12 clinical cell samples using cell microarrays and immunohistochemistry. The analysis suggests that most proteins are expressed in a cell size dependent manner, and that normalization is required for comparative protein quantification in order to correct for the inherent bias of cell size and systematic ambiguities associated with immunohistochemistry. Two reference standards were evaluated, and normalized protein expression values were found to allow for protein profiling across a panel of morphologically diverse cells, revealing putative patterns of over- and underexpression. Using this approach, proteins with stable expression as well as cell-line specific expression were identified. The results demonstrate the value of large-scale, automated proteome analysis using immunohistochemistry in revealing functional correlations and establishing methods to interpret and mine proteomic data.

  • 10.
    Lundberg, Emma
    et al.
    KTH, School of Biotechnology (BIO).
    Gry, Marcus
    KTH, School of Biotechnology (BIO).
    Uhlén, Mathias
    KTH, School of Biotechnology (BIO).
    et al.,
    Tissue specific expression of the transcription factor SATB2 in colorectal carcinoma2008Article in journal (Other academic)
  • 11. Magnusson, Kristina
    et al.
    de Wit, Meike
    Brennan, Donal J.
    Johnson, Louis B.
    Mcgee, Sharon F.
    Lundberg, Emma
    KTH, School of Biotechnology (BIO), Proteomics.
    Naicker, Kirsha
    Klinger, Rut
    Kampf, Caroline
    Asplund, Anna
    Wester, Kenneth
    Gry, Marcus
    KTH, School of Biotechnology (BIO), Proteomics.
    Bjartell, Anders
    Gallagher, William M.
    Rexhepaj, Elton
    Kilpinen, Sami
    Kallioniemi, Olli-Pekka
    Belt, Eric
    Goos, Jeroen
    Meijer, Gerrit
    Birgisson, Helgi
    Glimelius, Bengt
    Borrebaeck, Carl A. K.
    Navani, Sanjay
    Uhlén, Mathias
    KTH, School of Biotechnology (BIO), Proteomics.
    O'Connor, Darran P.
    Jirström, Karin
    Ponten, Fredrik
    SATB2 in Combination With Cytokeratin 20 Identifies Over 95% of all Colorectal Carcinomas2011In: American Journal of Surgical Pathology, ISSN 0147-5185, E-ISSN 1532-0979, Vol. 35, no 7, p. 937-948Article in journal (Refereed)
    Abstract [en]

    The special AT-rich sequence-binding protein 2 (SATB2), a nuclear matrix-associated transcription factor and epigenetic regulator, was identified as a tissue type-specific protein when screening protein expression patterns in human normal and cancer tissues using an antibody-based proteomics approach. In this respect, the SATB2 protein shows a selective pattern of expression and, within cells of epithelial lineages, SATB2 expression is restricted to glandular cells lining the lower gastrointestinal tract. The expression of SATB2 protein is primarily preserved in cancer cells of colorectal origin, indicating that SATB2 could function as a clinically useful diagnostic marker to distinguish colorectal cancer (CRC) from other types of cancer. The aim of this study was to further explore and validate the specific expression pattern of SATB2 as a clinical biomarker and to compare SATB2 with the well-known cytokeratin 20 (CK20). Immunohistochemistry was used to analyze the extent of SATB2 expression in tissue microarrays with tumors from 9 independent cohorts of patients with primary and metastatic CRCs (n = 1882). Our results show that SATB2 is a sensitive and highly specific marker for CRC with distinct positivity in 85% of all CRCs, and that SATB2 and/or CK20 was positive in 97% of CRCs. In conclusion, the specific expression of SATB2 in a large majority of CRCs suggests that SATB2 can be used as an important complementary tool for the differential diagnosis of carcinoma of unknown primary origin.

  • 12.
    Mikus, Maria
    et al.
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology.
    Drobin, Kimi
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology.
    Gry, Marcus
    KTH.
    Bachmann, J.
    Lindberg, J.
    Yimer, G.
    Aklillu, E.
    Makonnen, E.
    Aderaye, G.
    Roach, J.
    Fier, I.
    Kampf, C.
    Göpfert, J.
    Perazzo, H.
    Poynard, T.
    Stephens, C.
    Andrade, R. J.
    Lucena, M. I.
    Arber, N.
    Uhlén, Mattias
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology.
    Watkins, P. B.
    Schwenk, Jochen M
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology.
    Nilsson, P. Anders
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology.
    Schuppe-Koistinen, I.
    Elevated levels of circulating CDH5 and FABP1 in association with human drug-induced liver injury2016In: Liver international (Print), ISSN 1478-3223, E-ISSN 1478-3231, Vol. 37, no 1, p. 132-140Article in journal (Refereed)
    Abstract [en]

    Background & Aims: The occurrence of drug-induced liver injury (DILI) is a major issue in all phases of drug development. To identify novel biomarker candidates associated with DILI, we utilised an affinity proteomics strategy, where antibody suspension bead arrays were applied to profile plasma and serum samples from human DILI cases and controls. Methods: An initial screening was performed using 4594 randomly selected antibodies, representing 3450 human proteins. Resulting candidate proteins together with proposed DILI biomarker candidates generated a DILI array of 251 proteins for subsequent target analysis and verifications. In total, 1196 samples from 241 individuals across four independent cohorts were profiled: healthy volunteers receiving acetaminophen, patients with human immunodeficiency virus and/or tuberculosis receiving treatment, DILI cases originating from a wide spectrum of drugs, and healthy volunteers receiving heparins. Results: We observed elevated levels of cadherin 5, type 2 (CDH5) and fatty acid-binding protein 1 (FABP1) in DILI cases. In the two longitudinal cohorts, CDH5 was elevated already at baseline. FABP1 was elevated after treatment initiation and seemed to respond more rapidly than alanine aminotransferase (ALT). The elevations were verified in the DILI cases treated with various drugs. In the heparin cohort, CDH5 was stable over time whereas FABP1 was elevated. Conclusions: These results suggest that CDH5 may have value as a susceptibility marker for DILI. FABP1 was identified as a biomarker candidate with superior characteristics regarding tissue distribution and kinetics compared to ALT but likely with limited predictive value for the development of severe DILI. Further studies are needed to determine the clinical utility of the proposed markers. © 2016 John Wiley & Sons A/S.

  • 13. Ponten, Fredrik
    et al.
    Gry, Marcus
    KTH, School of Biotechnology (BIO), Proteomics.
    Fagerberg, Linn
    KTH, School of Biotechnology (BIO), Proteomics.
    Lundberg, Emma
    KTH, School of Biotechnology (BIO), Proteomics.
    Asplund, Anna
    Berglund, Lisa
    KTH, School of Biotechnology (BIO), Proteomics.
    Oksvold, Per
    KTH, School of Biotechnology (BIO), Proteomics.
    Björling, Erik
    KTH, School of Biotechnology (BIO), Proteomics.
    Hober, Sophia
    KTH, School of Biotechnology (BIO), Proteomics.
    Kampf, Caroline
    Navani, Sanjay
    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
    Uhlén, Mathias
    KTH, School of Biotechnology (BIO), Proteomics.
    A global view of protein expression in human cells, tissues, and organs2009In: Molecular Systems Biology, ISSN 1744-4292, E-ISSN 1744-4292, Vol. 5Article in journal (Refereed)
    Abstract [en]

    Defining the protein profiles of tissues and organs is critical to understanding the unique characteristics of the various cell types in the human body. In this study, we report on an anatomically comprehensive analysis of 4842 protein profiles in 48 human tissues and 45 human cell lines. A detailed analysis of over 2 million manually annotated, high-resolution, immunohistochemistry- based images showed a high fraction (>65%) of expressed proteins in most cells and tissues, with very few proteins (<2%) detected in any single cell type. Similarly, confocal microscopy in three human cell lines detected expression of more than 70% of the analyzed proteins. Despite this ubiquitous expression, hierarchical clustering analysis, based on global protein expression patterns, shows that the analyzed cells can be still subdivided into groups according to the current concepts of histology and cellular differentiation. This study suggests that tissue specificity is achieved by precise regulation of protein levels in space and time, and that different tissues in the body acquire their unique characteristics by controlling not which proteins are expressed but how much of each is produced. Molecular Systems Biology 5: 337; published online 22 December 2009; doi:10.1038/msb.2009.93

  • 14.
    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)
  • 15.
    Rimini, Rebecca
    et al.
    KTH, School of Biotechnology (BIO), Proteomics.
    Schwenk, Jochen M.
    KTH, School of Biotechnology (BIO), Proteomics.
    Sundberg, Marten
    Sjöberg, Ronald
    Klevebring, Daniel
    Gry, Marcus
    KTH, School of Biotechnology (BIO), Proteomics.
    Uhlén, Mathias
    KTH, School of Biotechnology (BIO), Proteomics.
    Nilsson, Peter
    KTH, School of Biotechnology (BIO), Proteomics.
    Validation of serum protein profiles by a dual antibody array approach2009Article in journal (Refereed)
    Abstract [en]

    In recent years, affinity-based technologies have become important tools for serum profiling to uncover protein expression patterns linked to disease state or therapeutic effects. In this study, we describe a path towards the production of an antibody microarray to allow protein profiling of biotinylated human serum samples with reproducible sensitivity in the picomolar range. With the availability of growing numbers of affinity reagents, protein profiles are to be validated in efficient manners and we describe a cross-platform strategy based on data concordance with a suspension bead array to interrogate the identical set of antibodies with the same cohort of serum samples. Comparative analysis enabled to screen for high-performing antibodies, which were displaying consistent results across the two platforms and targeting known serum components. Moreover, data processing methods such as sample referencing and normalization were evaluated for their effects on inter-platform agreement. Our work suggests that mutual validation of protein expression profiles using alternative microarray platforms holds great potential in becoming an important and valuable component in affinity-based high-throughput proteomic screenings as it allows to narrow down the number of discovered targets prior to orthogonal, uniplexed validation approaches.

  • 16.
    Schwenk, Jochen M.
    et al.
    KTH, School of Biotechnology (BIO), Proteomics.
    Gry, Marcus
    KTH, School of Biotechnology (BIO), Proteomics.
    Rimini, Rebecca
    KTH, School of Biotechnology (BIO), Proteomics.
    Uhlén, Mathias
    KTH, School of Biotechnology (BIO), Proteomics.
    Nilsson, Peter
    KTH, School of Biotechnology (BIO), Proteomics.
    Antibody suspension bead arrays within serum proteomics2008In: Journal of Proteome Research, ISSN 1535-3893, E-ISSN 1535-3907, Vol. 7, no 8, p. 3168-3179Article in journal (Refereed)
    Abstract [en]

    Antibody microarrays offer a powerful tool to screen for target proteins in complex samples. Here, we describe an approach for systematic analysis of serum, based on antibodies and using color-coded beads for the creation of antibody arrays in suspension. This method, adapted from planar antibody arrays, offers a fast, flexible, and multiplexed procedure to screen larger numbers of serum samples, and no purification steps are required to remove excess labeling substance. The assay system detected proteins down to lower picomolar levels with dynamic ranges over 3 orders of magnitude. The feasibility of this workflow was shown in a study with more than 200 clinical serum samples tested for 20 serum proteins.

  • 17.
    Strömberg, Sara
    et al.
    Department of Genetics and Pathology, Rudbeck Laboratory, Uppsala University.
    Gry Björklund, Marcus
    KTH, School of Biotechnology (BIO), Proteomics.
    Asplund, Caroline
    KTH, School of Biotechnology (BIO), Proteomics.
    Sköllermo, Anna
    KTH, School of Biotechnology (BIO), Proteomics.
    Persson, Anja
    KTH, School of Biotechnology (BIO), Proteomics.
    Wester, Kenneth
    Department of Genetics and Pathology, Rudbeck Laboratory, Uppsala University.
    Kampf, Caroline
    Department of Genetics and Pathology, Rudbeck Laboratory, Uppsala University.
    Nilsson, Peter
    KTH, School of Biotechnology (BIO), Proteomics.
    Andersson, Ann-Catrin
    Department of Genetics and Pathology, Rudbeck Laboratory, Uppsala University.
    Uhlén, Mathias
    KTH, School of Biotechnology (BIO), Proteomics.
    Kononen, Juha
    Beecher Instruments, Sun Prairie, WI, United States.
    Pontén, Fredrik
    Department of Genetics and Pathology, Rudbeck Laboratory, Uppsala University.
    Asplund, Anna
    Department of Genetics and Pathology, Rudbeck Laboratory, Uppsala University.
    A high-throughput strategy for protein profiling in cell microarrays using automated image analysis2007In: Proteomics, ISSN 1615-9853, E-ISSN 1615-9861, Vol. 7, no 13, p. 2142-2150Article in journal (Refereed)
    Abstract [en]

    Advances in antibody production render a growing supply of affinity reagents for immunohistochemistry (IHC), and tissue microarray (TMA) technologies facilitate simultaneous analysis of protein expression in a multitude of tissues. However, collecting validated IHC data remains a bottleneck problem, as the standard method is manual microscopical analysis. Here we present a high-throughput strategy combining IHC on a recently developed cell microarray with a novel, automated image-analysis application (TMAx). The software was evaluated on 200 digital images of IHC-stained cell spots, by comparing TMAx annotation with manual annotation performed by seven human experts. A high concordance between automated and manual annotation of staining intensity and fraction of IHC-positive cells was found. in a limited study, we also investigated the possibility to assess the correlation between mRNA and protein levels, by using TMAx output results for relative protein quantification and quantitative real-time PCR for the quantification of corresponding transcript levels. In conclusion, automated analysis of immunohistochemically stained in vitro-cultured cells in a microarray format can be used for high-throughput protein profiling, and extraction of RNA from the same cell lines provides a basis for comparing transcription and protein expression on a global scale.

  • 18.
    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.

  • 19.
    Zajac, Pawel
    et al.
    KTH, School of Biotechnology (BIO), Gene Technology.
    Pettersson, Erik
    KTH, School of Biotechnology (BIO), Gene Technology.
    Gry, Marcus
    KTH, School of Biotechnology (BIO), Gene Technology.
    Lundeberg, Joakim
    KTH, School of Biotechnology (BIO), Gene Technology.
    Ahmadian, Afshin
    KTH, School of Biotechnology (BIO), Gene Technology.
    Expression profiling of signature gene sets with trinucleotide threading2008In: Genomics, ISSN 0888-7543, E-ISSN 1089-8646, Vol. 9, no 2, p. 209-217Article in journal (Refereed)
    Abstract [en]

    In recent years, studies have shown that expression profiling of carefully chosen intermediary gene sets, comprising approximately 10 to 100 genes, can convey the most relevant information compared to much more complex whole-genome studies. In this paper, we present a novel method suitable for expression profiling of moderate gene sets in a large number of samples. The assay implements the parallel amplification features of the trinucleotide threading technique (TnT), which encompasses linear transcript-based DNA thread formation in conjunction with exponential multiplexed thread amplification. The amplifications bestow the method with high sensitivity. The TnT procedure together with thread detection, relying on thread-specific primer extension followed by hybridization to universal tag arrays, allows for three distinction levels, thus offering high specificity. Additionally, the assay is easily automated and flexible. A gene set, comprising 18 protein epitope signature tags from the Swedish Human Protein Atlas program, was analyzed with the TnT-based approach and the data were compared with those generated by both real-time PCR and genome-wide cDNA arrays, with the highest correlation observed between TnT and real-time PCR. Taken together, expression profiling with trinucleotide threading represents a reliable approach for studies of intermediary gene sets.

1 - 19 of 19
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf