Herbal decoctosome is a novel form of medicine
Traditionally, herbal medicine is consumed by drinking decoctions produced by boiling herbs with water. The functional components of the decoction are heat stable. Small RNAs (sRNAs) were reported as a new class of functional components in decoctions. However, the mechanisms by which sRNAs survive heat treatment of the decoction and enter cells are unclear. Previous studies showed that plant-derived exosome-like nanoparticles (ELNs), which we call botanosomes, could deliver therapeutic reagents in vivo. Here, we report that heat-stable decoctosomes (ELNs) from decoctions have more therapeutic effects than the decoctions in vitro and demonstrate therapeutic efficacy in vivo. Furthermore, sRNAs, such as HJT-sRNA-m7 and PGY-sRNA-6, in the decoctosome exhibit potent anti-fibrosis and anti-inflammatory effects, respectively. Decoctosome is comprised of lipids, chemical compounds, proteins, and sRNAs. A medical decoctosome mimic is called bencaosome. A single lipid sphinganine (d22:0) identified in the decoctosome was mixed and heated with the synthesized sRNAs to form the simplest bencaosome. This simple bencaosome structure was identified by critical micelle concentration (cmc) assay that sRNAs coassembled with sphinganine (d22:0) to form the lipid layers of vesicles. The heating process facilitates co-assembly of sRNAs and sphinganine (d22:0) until a steady state is reached. The artificially produced sphinganine-HJT-sRNA-m7 and sphinganine- PGY-sRNA-6 bencaosomes could ameliorate bleomycin-induced lung fibrosis and poly(I:C)-induced lung inflammation, respectively, following oral administration in mice. Our study not only demonstrates that the herbal decoctosome may represent a combinatory remedy in precision medicine but also provides an effective oral delivery route for nucleic acid therapy. Keywords: bencaosome; decoctosome; sphinganine.
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基因水平:PCR Array、RT-PCR、PCR、单细胞测序
蛋白水平:MSD、Luminex、CBA、Elispot、Antibody Array、ELISA、Sengenics
细胞水平:细胞染色、细胞分选、细胞培养、细胞功能
组织水平:空间多组学、多重荧光免疫组化、免疫组化、免疫荧光
数据分析:流式数据分析、组化数据分析、多因子数据分析
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