Nature CommunicationsBioengineeringPeer-reviewed journal article
In Vivo Metabolic Tagging and Targeting of Circulating Red Blood Cells
Yusheng Liu, Yizun WangiD, Kyungwon KoiD, Yuan Liu, Haiyi Huang, Yueji WangiD, Jiadiao ZhouiD, Dhyanesh BaskaraniD, Joonsu HaniD, Rimsha Bhatta, Daniel C. NguyeniD, Cecília LealiD, Matthew R. Berry, Fan LamiD, Hua WangiD
Abstract
Engineering red blood cells (RBCs) has been widely explored for drug delivery, imaging, vaccination, and other applications. However, effective strategies to directly engineer RBCs in vivo still do not exist. Here, for the first time, we report successful metabolic glycan labeling of RBCs in vivo. We demonstrate that systemically administered azido-sugars can metabolically label circulating RBCs with azido groups in the form of glycoproteins and glycolipids, with contributions from the labeling of both mature RBCs in the bloodstream and RBC precursor cells in the bone marrow. The RBC labeling efficiency can be improved by optimizing the choice and dose and dosing frequency of azido-sugars. The surface azido tags on RBCs can persist for >42 days in mice (nearly the lifespan of mouse RBCs), in sharp contrast to azido tags on leukocytes in the blood and cells in healthy tissues that decay to undetectable levels within 3 days. This in vivo RBC labeling technology does not induce any noticeable toxicity to RBCs, leukocytes, and healthy tissues. We further demonstrate that azido-labeled RBCs can covalently capture dibenzocyclooctyne-bearing cargos in vivo via click chemistry, prolonging the blood circulation of cargos from typical hours to >35 days. In a few examples, we show that the unprecedented RBC tagging and targeting technology can improve the fluorescence imaging of blood vessels and tumor tissues, enable long-term magnetic resonance imaging of brain vasculatures with one dose of gadolinium agent, and enhance the pharmacokinetics of drugs such as insulin.
- organism: mouse
- assay: proteomics
- research focus: drug response / drug discovery
- research focus: imputation
- approach: experimental assay
- Citations
- 3
- FWCI
- 5.26
- Field percentile
- top 5%
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