Physics of exotic nuclei
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Spotiphy enables single-cell spatial whole transcriptomics across an entire section
Spatial transcriptomics (ST) has advanced our understanding of tissue regionalization by enabling the visualization of gene expression within whole-tissue sections, but current approaches remain plagued by the challenge of achieving single-cell resolution without sacrificing whole-genome coverage. Here we present Spotiphy (spot imager with pseudo-single-cell-resolution histology), a computational toolkit that transforms sequencing-based ST data into single-cell-resolved whole-transcriptome images. Spotiphy delivers the most precise cellular proportions in extensive benchmarking evaluations. Spotiphy-derived inferred single-cell profiles reveal astrocyte and disease-associated microglia regional specifications in Alzheimer’s disease and healthy mouse brains. Spotiphy identifies multiple spatial domains and alterations in tumor–tumor microenvironment interactions in human breast ST data. Spotiphy bridges the information gap and enables visualization of cell localization and transcriptomic profiles throughout entire sections, offering highly informative outputs and an innovative spatial analysis pipeline for exploring complex biological systems.
Cellpose3: one-click image restoration for improved cellular segmentation
Generalist methods for cellular segmentation have good out-of-the-box performance on a variety of image types; however, existing methods struggle for images that are degraded by noise, blurring or undersampling, all of which are common in microscopy. We focused the development of Cellpose3 on addressing these cases and here we demonstrate substantial out-of-the-box gains in segmentation and image quality for noisy, blurry and undersampled images. Unlike previous approaches that train models to restore pixel values, we trained Cellpose3 to output images that are well segmented by a generalist segmentation model, while maintaining perceptual similarity to the target images. Furthermore, we trained the restoration models on a large, varied collection of datasets, thus ensuring good generalization to user images. We provide these tools as ‘one-click’ buttons inside the graphical interface of Cellpose as well as in the Cellpose API.
Optical sorting: past, present and future
Optical sorting combines optical tweezers with diverse techniques, including optical spectrum, artificial intelligence (AI) and immunoassay, to endow unprecedented capabilities in particle sorting. In comparison to other methods such as microfluidics, acoustics and electrophoresis, optical sorting offers appreciable advantages in nanoscale precision, high resolution, non-invasiveness, and is becoming increasingly indispensable in fields of biophysics, chemistry, and materials science. This review aims to offer a comprehensive overview of the history, development, and perspectives of various optical sorting techniques, categorised as passive and active sorting methods. To begin, we elucidate the fundamental physics and attributes of both conventional and exotic optical forces. We then explore sorting capabilities of active optical sorting, which fuses optical tweezers with a diversity of techniques, including Raman spectroscopy and machine learning. Afterwards, we reveal the essential roles played by deterministic light fields, configured with lens systems or metasurfaces, in the passive sorting of particles based on their varying sizes and shapes, sorting resolutions and speeds. We conclude with our vision of the most promising and futuristic directions, including AI-facilitated ultrafast and bio-morphology-selective sorting. It can be envisioned that optical sorting will inevitably become a revolutionary tool in scientific research and practical biomedical applications.
The cellular and molecular cardiac tissue responses in human inflammatory cardiomyopathies after SARS-CoV-2 infection and COVID-19 vaccination
Myocarditis, characterized by inflammatory cell infiltration, can have multiple etiologies, including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection or, rarely, mRNA-based coronavirus disease 2019 (COVID-19) vaccination. The underlying cellular and molecular mechanisms remain poorly understood. In this study, we performed single-nucleus RNA sequencing on left ventricular endomyocardial biopsies from patients with myocarditis unrelated to COVID-19 (Non-COVID-19), after SARS-CoV-2 infection (Post-COVID-19) and after COVID-19 vaccination (Post-Vaccination). We identified distinct cytokine expression patterns, with interferon-γ playing a key role in Post-COVID-19, and upregulated IL16 and IL18 expression serving as a hallmark of Post-Vaccination myocarditis. Although myeloid responses were similar across all groups, the Post-Vaccination group showed a higher proportion of CD4+ T cells, and the Post-COVID-19 group exhibited an expansion of cytotoxic CD8+ T and natural killer cells. Endothelial cells showed gene expression changes indicative of vascular barrier dysfunction in the Post-COVID-19 group and ongoing angiogenesis across all groups. These findings highlight shared and distinct mechanisms driving myocarditis in patients with and without a history of SARS-CoV-2 infection or vaccination.
Droplet-based high-throughput 3D genome structure mapping of single cells with simultaneous transcriptomics
Single-cell three-dimensional (3D) genome techniques have advanced our understanding of cell-type-specific chromatin structures in complex tissues, yet current methodologies are limited in cell throughput. Here we introduce a high-throughput single-cell Hi-C (dscHi-C) approach and its transcriptome co-assay (dscHi-C-multiome) using droplet microfluidics. Using dscHi-C, we investigate chromatin structural changes during mouse brain aging by profiling 32,777 single cells across three developmental stages (3 months, 12 months, and 23 months), yielding a median of 78,220 unique contacts. Our results show that genes with significant structural changes are enriched in pathways related to metabolic process and morphology change in neurons, and innate immune response in glial cells, highlighting the role of 3D genome organization in physiological brain aging. Furthermore, our multi-omics joint assay, dscHi-C-multiome, enables precise cell type identification in the adult mouse brain and uncovers the intricate relationship between genome architecture and gene expression. Collectively, we developed the sensitive, high-throughput dscHi-C and its multi-omics derivative, dscHi-C-multiome, demonstrating their potential for large-scale cell atlas studies in development and disease.
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