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Dynamic tracking and identification of tissue-specific secretory proteins in the circulation of live mice

Secretory proteins are an essential component of interorgan communication networks that regulate animal physiology. Current approaches for identifying secretory proteins from specific cell and tissue types are largely limited to in vitro or ex vivo models which often fail to recapitulate in vivo bio...

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Detalles Bibliográficos
Autores principales: Kim, Kwang-eun, Park, Isaac, Kim, Jeesoo, Kang, Myeong-Gyun, Choi, Won Gun, Shin, Hyemi, Kim, Jong-Seo, Rhee, Hyun-Woo, Suh, Jae Myoung
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8410947/
https://www.ncbi.nlm.nih.gov/pubmed/34471136
http://dx.doi.org/10.1038/s41467-021-25546-y
Descripción
Sumario:Secretory proteins are an essential component of interorgan communication networks that regulate animal physiology. Current approaches for identifying secretory proteins from specific cell and tissue types are largely limited to in vitro or ex vivo models which often fail to recapitulate in vivo biology. As such, there is mounting interest in developing in vivo analytical tools that can provide accurate information on the origin, identity, and spatiotemporal dynamics of secretory proteins. Here, we describe iSLET (in situ Secretory protein Labeling via ER-anchored TurboID) which selectively labels proteins that transit through the classical secretory pathway via catalytic actions of Sec61b-TurboID, a proximity labeling enzyme anchored in the ER lumen. To validate iSLET in a whole-body system, we express iSLET in the mouse liver and demonstrate efficient labeling of liver secretory proteins which could be tracked and identified within circulating blood plasma. Furthermore, proteomic analysis of the labeled liver secretome enriched from liver iSLET mouse plasma is highly consistent with previous reports of liver secretory protein profiles. Taken together, iSLET is a versatile and powerful tool for studying spatiotemporal dynamics of secretory proteins, a valuable class of biomarkers and therapeutic targets.