journal article·2022-12Open access

Systemic and single cell level responses to 1 nm size biomaterials demonstrate distinct biological effects revealed by multi-omics atlas

Tao Zhang, Tingyun Lei, Ruojin Yan, Bo Zhou, Chunmei Fan, Yanyan Zhao, Shasha Yao, Haihua Pan, Yangwu Chen, Bingbing Wu, Yuwei Yang, Lijuan Hu, Shen Gu, Xiaoyi Chen, Fangyuan Bao, Yu Li, Hanqi Xie, Ruikang Tang, Xiao Chen, Zi Yin

Abstract

Although ultra-small nanoclusters (USNCs, < 2 nm) have immense application capabilities in biomedicine, the investigation on body-wide organ responses towards USNCs is scant. Here, applying a novel strategy of single-cell mass cytometry combined with Nano Genome Atlas of multi-tissues, we systematically evaluate the interactions between the host and calcium phosphate (CaP) USNCs at the organism level. Combining single-cell mass cytometry, and magnetic luminex assay results, we identify dynamic immune responses to CaP USNCs at the single cell resolution. The innate immune is initially activated and followed by adaptive immune activation, as evidenced by dynamic immune cells proportions. Furthermore, using Nano Genome Atlas of multi-tissues, we uncover CaP USNCs induce stronger activation of the immune responses in the cartilage and subchondral bone among the five local tissues while promote metabolic activities in the liver and kidney. Moreover, based on the immunological response profiles, histological evaluation of major organs and local tissue, and a body-wide transcriptomics, we demonstrate that CaP USNCs are not more hazardous than the Food and Drug Administration-approved CaP nanoparticles after 14 days of injection. Our findings provide valuable information on the future clinical applications of USNCs and introduce an innovative strategy to decipher the whole body response to implants.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Advanced Nanomaterials in Catalysis · Single-cell and spatial transcriptomics · Extracellular vesicles in disease

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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