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Luciano Hoeher

Helmholtz Zentrum München

Publishes on Single-cell and spatial transcriptomics, Cell Image Analysis Techniques, Advanced biosensing and bioanalysis techniques. 15 papers and 409 citations.

15Publications
409Total Citations

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Top publicationsby citations

Whole-body cellular mapping in mouse using standard IgG antibodies
Hongcheng Mai, Jie Luo, Luciano Hoeher et al.|Nature Biotechnology|2023
Cited by 118Open Access

Whole-body imaging techniques play a vital role in exploring the interplay of physiological systems in maintaining health and driving disease. We introduce wildDISCO, a new approach for whole-body immunolabeling, optical clearing and imaging in mice, circumventing the need for transgenic reporter animals or nanobody labeling and so overcoming existing technical limitations. We identified heptakis(2,6-di-O-methyl)-β-cyclodextrin as a potent enhancer of cholesterol extraction and membrane permeabilization, enabling deep, homogeneous penetration of standard antibodies without aggregation. WildDISCO facilitates imaging of peripheral nervous systems, lymphatic vessels and immune cells in whole mice at cellular resolution by labeling diverse endogenous proteins. Additionally, we examined rare proliferating cells and the effects of biological perturbations, as demonstrated in germ-free mice. We applied wildDISCO to map tertiary lymphoid structures in the context of breast cancer, considering both primary tumor and metastases throughout the mouse body. An atlas of high-resolution images showcasing mouse nervous, lymphatic and vascular systems is accessible at http://discotechnologies.org/wildDISCO/atlas/index.php .

Immune-mediated denervation of the pineal gland underlies sleep disturbance in cardiac disease
Cited by 81Open Access

Disruption of the physiologic sleep-wake cycle and low melatonin levels frequently accompany cardiac disease, yet the underlying mechanism has remained enigmatic. Immunostaining of sympathetic axons in optically cleared pineal glands from humans and mice with cardiac disease revealed their substantial denervation compared with controls. Spatial, single-cell, nuclear, and bulk RNA sequencing traced this defect back to the superior cervical ganglia (SCG), which responded to cardiac disease with accumulation of inflammatory macrophages, fibrosis, and the selective loss of pineal gland-innervating neurons. Depletion of macrophages in the SCG prevented disease-associated denervation of the pineal gland and restored physiological melatonin secretion. Our data identify the mechanism by which diurnal rhythmicity in cardiac disease is disturbed and suggest a target for therapeutic intervention.

Virtual reality-empowered deep-learning analysis of brain cells
Doris Kaltenecker, Rami Al-Maskari, Moritz Negwer et al.|Nature Methods|2024
Cited by 36Open Access

Abstract Automated detection of specific cells in three-dimensional datasets such as whole-brain light-sheet image stacks is challenging. Here, we present DELiVR, a virtual reality-trained deep-learning pipeline for detecting c-Fos + cells as markers for neuronal activity in cleared mouse brains. Virtual reality annotation substantially accelerated training data generation, enabling DELiVR to outperform state-of-the-art cell-segmenting approaches. Our pipeline is available in a user-friendly Docker container that runs with a standalone Fiji plugin. DELiVR features a comprehensive toolkit for data visualization and can be customized to other cell types of interest, as we did here for microglia somata, using Fiji for dataset-specific training. We applied DELiVR to investigate cancer-related brain activity, unveiling an activation pattern that distinguishes weight-stable cancer from cancers associated with weight loss. Overall, DELiVR is a robust deep-learning tool that does not require advanced coding skills to analyze whole-brain imaging data in health and disease.

Nanocarrier imaging at single-cell resolution across entire mouse bodies with deep learning
Jie Luo, Müge Molbay, Ying Chen et al.|Nature Biotechnology|2025
Cited by 31Open Access

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.