E-PROT-44
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ABSTRACT:
PROVIDER: E-PROT-44 | ExpressionAtlas | 2022-01-10
REPOSITORIES: ExpressionAtlas
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Project description:Uhlén2015 - Human tissue-based proteome metabolic network - salivary gland
Human salivary gland specific proteome metabolic network
This model is described in the article:
Tissue-based map of the human proteome
Uhlén M, Fagerberg L, Hallström BM, Lindskog C, Oksvold P, Mardinoglu A, Sivertsson Å, Kampf C, Sjöstedt E, Asplund A, Olsson I, Edllund K, Lundberg E, Navani S, Szigyarto AC, Odeberg J, Djureinovic D, Takanen JO, Hober S, Alm T, Edqvist P, Berlin H, Tegel H, Mulder J, Rockberg J, Nilsson P, Schwenk JM, Hamsten M, von Feilitzen K, Forsberg M, Persson L, Johansson F, Zwahlen M, von Heijne G, Nielsen J, Pontén F.
Science 2015 January; 347(6220)
Abstract:
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.
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2015-01-28 | MODEL1411240013 | BioModels
Project description:Proteomic analysis of human anterior pituitary gland
2022-01-06 | E-PROT-33 | ExpressionAtlas
Project description:Eccrine sweat gland is an exocrine gland that is involved in the secretion of sweat for control of temperature. Malfunction of the sweat glands can result in disorders such as miliaria, hyperhidrosis and bromhidrosis. In addition, lack of reabsorption of Cl- ions from reabsorptive duct of eccrine sweat gland is a major feature of cystic fibrosis. Understanding the proteome of eccrine sweat glands is important for understanding the physiology of sweat formation. In spite of this, no systematic transcriptome or proteome analysis of eccrine sweat glands has yet been reported. To this end, we isolated eccrine sweat glands by microdissecting them from human skin and performed both RNA-seq and proteome analysis. In total, ~138,000 transcripts and ~6,100 proteins were identified. The proteome data showed the enrichment in protein digestion/absorption and salivary secretion, while the transcriptome data did not show any enrichment for a specific pathway. This study also enabled us to confirm 2 missing proteins. Integrating RNA-seq and proteomic data allowed us to identify 7 peptides from 5 novel genes. Most of the novel proteins were from short open reading frames (sORFs) suggesting that many sORFs still remain to be annotated in the human genome. The peptides mapping to the missing or novel proteins were validated by analyzing synthetic peptides. This study provides the first integrated analysis of the transcriptome and proteome of the human eccrine sweat gland and should become an invaluable resource to biomedical research community for studying sweat glands in physiology and disease.
2018-07-31 | GSE117885 | GEO
Project description:Proteomics characterization of human colon and rectal cancer
2021-05-25 | E-PROT-23 | ExpressionAtlas
Project description:The availability of human genome sequence has transformed biomedical research over the past decade. However, an equivalent map for the human proteome with direct measurements of proteins and peptides was lacking. To this end, Akhilesh Pandey's lab reported a draft map of the human proteome based on high resolution Fourier transform mass spectrometry-based proteomics technology, which included an in-depth proteomic profiling of 30 histologically normal human samples including 17 adult tissues, 7 fetal tissues and 6 purified primary hematopoietic cells ( http://dx.doi.org/10.1038/nature13302 ). The profiling resulted in identification of proteins encoded by greater than 17,000 genes accounting for ~84% of the total annotated protein-coding genes in humans. This large human proteome catalog (available as an interactive web-based resource at http://www.humanproteomemap.org) complements available human genome and transcriptome data to accelerate biomedical research in health and disease. Pandey's lab and collaborators request that those considering use of this primary dataset for commercial purposes contact pandey@jhmi.edu. The full details of this study can be found in the PRIDE database: www.ebi.ac.uk/pride/archive/projects/PXD000561/. This ArrayExpress entry represents a top level summary of the metadata only which formed the basis of the reanalysis performed by Joyti Choudhary's team ( jc4@sanger.ac.uk ), results of which are presented in the Expression Atlas at EMBL-EBI : http://www.ebi.ac.uk/gxa/experiments/E-PROT-1.
2015-03-10 | E-PROT-1 | biostudies-arrayexpress
Project description:Human infection with Mycobacterium tuberculosis results in a continuum of ill-defined, clinical manifestations with stable latent M. tuberculosis infection (LTBI) and severe active disease at the ends. Identifying different states of infection is of importance to tuberculosis (TB) control since risk of developing active disease varies among different asymptomatic states while infectiousness varies among patients with different bacterial burden. We investigated changes in proteome-scale antibody responses during disease progression in a non-human primate model of tuberculosis. We probed M. tuberculosis proteome microarrays with serial sera collected from three infection-outcome groups (active, reactivation, and latent). We found that each infection outcome is associated with characteristic changes in the antibody levels and number of antigenic targets, which suggested an association between antibody responses and bacillary burden. Additional proteome-scale serological profiling of > 400 human TB suspects established that antibody responses are positively associated with bacterial load. Thus tuberculosis-specific antibody levels and number of antigenic targets increases with disease progression. To investigate antibody responses during the course of infection, we probed M. tuberculosis proteome microarrays with serial sera collected from experimentally infected cynomolgus macaques. Based on infection outcome, the macaques were grouped into three classes; A) active disease (n = 4), B) latent infection (n=5) and C) reactivation disease (n = 5). Note that the macaques in the reactivation class developed signs of disease spontaneously without any experimental intervention. For each animal, we tested one pre-infection time point and approximately ten post-infection time points at one-month intervals.
2012-07-05 | E-GEOD-30721 | biostudies-arrayexpress
Project description:Proteome of the Human Corpus Callosum and Anterior Temporal Lobe
2022-01-07 | E-PROT-42 | ExpressionAtlas
Project description:A deep proteome and transcriptome abundance atlas of 29 healthy human tissues
2021-05-25 | E-PROT-29 | ExpressionAtlas
Project description:Proteome Landscapes of the Human Colorectal Mucosa, and its Adenoma and Cancer
2023-06-21 | E-PROT-104 | ExpressionAtlas
Project description:Canine mammary gland tumors can be used as predictive models for human breast cancer. There are several types of microRNAs common in human breast cancer and canine mammary gland tumors. The functions of microRNAs in canine mammary gland tumors are not well understood. In the present study, we compared the characterization of microRNA expression in two-dimensional and three-dimensional canine mammary gland tumor cell models. The expression of microRNA-210 in the three-dimensional-SNP cells was 10.19 times higher than that in the two-dimensional-SNP cells.
2022-07-07 | GSE203410 | GEO