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

Kwang-eun Kim, Isaac Park, Jeesoo Kim, Myeong-Gyun Kang, Won Gun Choi, Hyemi Shin, Jong-Seo Kim (), Hyun-Woo Rhee () and Jae Myoung Suh ()
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Kwang-eun Kim: Graduate School of Medical Science and Engineering, KAIST
Isaac Park: Seoul National University
Jeesoo Kim: Center for RNA Research, Institute for Basic Science
Myeong-Gyun Kang: Seoul National University
Won Gun Choi: Graduate School of Medical Science and Engineering, KAIST
Hyemi Shin: Graduate School of Medical Science and Engineering, KAIST
Jong-Seo Kim: Center for RNA Research, Institute for Basic Science
Hyun-Woo Rhee: Seoul National University
Jae Myoung Suh: Graduate School of Medical Science and Engineering, KAIST

Nature Communications, 2021, vol. 12, issue 1, 1-9

Abstract: Abstract 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.

Date: 2021
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DOI: 10.1038/s41467-021-25546-y

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