ArticleNature communications2017
Application of bio-orthogonal proteome labeling to cell transplantation and heterochronic parabiosis.
Article in Nature communications, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 40 papers.
What it found
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Who cites it
40 citing papers in PubMed, 70 citations in OpenAlex.
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Corrections and comments
- Erratum issued
- Erratum issued
Authors and funding
9 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Studies of heterochronic parabiosis demonstrated that with age, the composition of the circulatory milieu changes in ways that broadly inhibit tissue regenerative capacity. In addition, local tissue niches have age-specific influences on their resident stem cells. Here we use bio-orthogonal proteome labeling for detecting in vivo proteins present only in transplanted myoblasts, but not in host tissue, and proteins exclusive to one young mouse and transferred during parabiosis to its old partner. We use a transgenic mouse strain that ubiquitously expresses a modified tRNA methionine synthase, metRS, which preferentially incorporates the methionine surrogate azido-nor-leucine (ANL) into newly generated proteins. Using click chemistry and a modified antibody array to detect ANL-labeled proteins, we identify several 'young' systemic factors in old regenerating muscle of the heterochronic parabiotic partners. Our approach enables the selective profiling of mammalian proteomes in mixed biological environments such as cell and tissue transplantation, apheresis or parabiosis.Clarifying the source of proteins in mixed biological environments, such as after transplantation or parabiosis, remains a challenge. Here, the authors address this need with a mouse strain that incorporates a methionine derivate into proteins, allowing for their detection using click chemistry and antibody arrays.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.