Nanocarrier imaging at single-cell resolution across entire mouse bodies with deep learning

Abstract;

🔹Efficient and accurate nanocarrier development for targeted drug delivery is hindered by a lack of methods to analyze its cell-level biodistribution across whole organisms. Here we present Single Cell Precision Nanocarrier Identification (SCP-Nano), an integrated experimental and deep learning pipeline to comprehensively quantify the targeting of nanocarriers throughout the whole mouse body at single-cell resolution.

🔹SCP-Nano reveals the tissue distribution patterns of lipid nanoparticles (LNPs) after different injection routes at doses as low as 0.0005 mg kg−1—far below the detection limits of conventional whole body imaging techniques. We demonstrate that intramuscularly injected LNPs carrying SARS-CoV-2 spike mRNA reach heart tissue, leading to proteome changes, suggesting immune activation and blood vessel damage.

🔹SCP-Nano generalizes to various types of nanocarriers, including liposomes, polyplexes, DNA origami and adeno-associated viruses (AAVs), revealing that an AAV2 variant transduces adipocytes throughout the body. SCP-Nano enables comprehensive three-dimensional mapping of nanocarrier distribution throughout mouse bodies with high sensitivity and should accelerate the development of precise and safe nanocarrier-based therapeutics.

a, Scheme of SCP-Nano—a pipeline for mapping and quantifying the biodistribution of any fluorescently labeled nanocarrier throughout the entire mouse body with single-cell resolution and high sensitivity. b,c, Bioluminescence imaging (ventral) 6 h after intravenous injection of 0.5 mg kg−1 (b) and 0.0005 mg kg−1 (c) of luciferase mRNA-carrying LNPs. d–f, Whole body light sheet imaging of mice intravenously injected with 0.0005 mg kg−1 Alexa Fluor 647–labeled EGFP mRNA-carrying LNPs and cleared with our refined DISCO clearing methods. This approach enables the visualization of mRNA delivery throughout the entire mouse body, including the liver (e) and spleen (f), at cellular resolution. g–m, Visualization of whole mouse body LNPs after intranasal delivery of 0.0005 mg kg−1: maximum intensity projection (g) and single optical slice views (h–l); representative individual optical slices of the lung (m).

Result

High-resolution, whole body biodistribution imaging
Conventional bioluminescence imaging, a common whole body imaging technique, has identified luciferase expression after LNP-based delivery of its mRNA at high injection doses (0.5 mg kg−1) with high contrast at the organ level (Fig. 1b). However, signal contrast drops drastically at low doses typically used, for example, for mRNA vaccines (0.0005 mg kg−1)

To visualize LNP distribution with higher sensitivity and resolution, we generated LNPs based on the clinically approved MC3-ionizable lipid23 carrying EGFP mRNA—tagged with Alexa fluorescent dyes (Alexa 647 or Alexa 750).

a, Flowchart of the SCP-Nano pipeline. b, Customized 3D U-Net architecture of the SCP-Nano deep learning segmentation model. c, Comparison of the F1 (instance Dice) scores of SCP-Nano segmentation model with other models. d, Comparison of Imaris and SCP-Nano prediction accuracy using liver images. e, Illustration of the entire nanoparticle prediction pipeline. After obtaining the whole body dataset via light sheet microscopy, we used VR glasses for organ annotation, followed by the application of our SCP-Nano analysis algorithm to quantify the LNP distribution in the whole body. Example images are from the lung. Compared to the ground truth data, our algorithm accurately detects all different sizes of delivery events in the lung. f, Raw data of LNP distribution in the liver and instance-separated multicolor segmentation obtained by SCP-Nano. Each color represents a separate delivery event as predicted by the model. g, Continuous segmented slice views demonstrate single-cell segmentation.

a, Density heatmaps of the distribution of LNP-delivered mRNA applied using different routes (0.0005 mg kg−1 in each case). b, Raw projection images (left) and density heatmaps of selected organs. Arrows point to intra-organ delivery hotspots. c, Organ-level quantification of mRNA delivery events across key organs for different application routes using the SCP-Nano deep learning algorithm (n = 3 mice per group, mean ± s.d.). d, Quantification of mRNA delivery events in lymph nodes of intramuscularly injected mice. i.m., intramuscular; i.v., intravenous; LN, lymph node.