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Imaging cellular activity across all organs reveals body-wide circuits

Ruetten, Virginie M. S.; Zheng, Wei; Siwanowicz, Igor; Mensh, Brett D.; Eddison, Mark; Hu, Amy; Chi, Yunfeng; Lemire, Andrew L.; Guo, Caiying; Kadobianskyi, Mykola; Renz, Marc; Lelek-Greskovic, Sara; He, Yisheng; Close, Kari; Ihrke, Gudrun; Dev, Aparna; Petruncio, Alyson; Wan, Yinan; Zhang, Rongwei; Fishman, Mark C.; Engert, Florian; Judkewitz, Benjamin; Rubinov, Mikail; Keller, Philipp J.; Satou, Chie; Yu, Guoqiang; Tillberg, Paul W.; Sahani, Maneesh; Ahrens, Misha B. (2026).泭.泭Nature.泭

Animals depend on coordinated activity among cells and organs to respond to challenges such as danger, food, and infection. However, researchers have lacked a way to observe cellular activity across the whole body in real time. Here, the researchers developed WHOLISTIC, an imaging method that combines fluorescence microscopy, machine learning, and calcium sensors to track cellular activity throughout a living vertebrate body within seconds. Using zebrafish, WHOLISTIC revealed previously unknown responses in cartilage and brain-protective tissues, rhythmic activity in the kidneys, coordination between muscles and organs, and brainstem-controlled changes in blood flow. Combined with optogenetics, which uses light to control specific cells, the method also allowed researchers to investigate cause-and-effect relationships between the brain and body. WHOLISTIC therefore provides a powerful way to study how cells and organs work together and may help identify new biological mechanisms and therapeutic targets.

Fig. 1: WHOLISTIC imaging of intracellular calcium dynamics across the body.

a, Schematic of WHOLISTIC.泭b, Transgenic zebrafish (7 days post-fertilization) expressing GCaMP7f pancellularly (Tg(ubi:tTA;TRE:GCaMP7f)), imaged with spinning-disk confocal microscopy; samples were mounted laterally for visceral access.泭c, Annotated 3D anatomical model of young zebrafish derived from whole-body expansion microscopy��(WB-ExM)��data.泭d, Single fluorescence channel enables identification of organs and tissues via distinct visual textures (enlarged examples).泭e, Volumetric imaging acquisition paradigm with typical acquisition parameters. Fluorescence intensity variations reflect changes in intracellular calcium. Images covering an area of 800���弮m���� 600���弮m are acquired in steps of approximately 9���弮m, spanning a depth of approximately 130���弮m using a ��20 0.75���NA objective.泭f, Registration workflow using multiscale iterative estimation of local motion fields.泭g, Registration results. Overlay of recording at the start (green) and 1���h into the experiment (magenta; top). The insets show myocytes and gut epithelium before (bottom left) and after (bottom right) registration.泭h, Dual-colour imaging (pancellular GCaMP plus membrane-targeted RFP; left), and example tissue (right), showing a 3D model and an enlarged view of the anterior part of pronephric kidney (glomerulus (G) and proximal tubules: descending limb (DL) and ascending limb (AL)).泭i, Cellular-scale segmentation (constrained non-negative matrix factorization). The inset shows an enlarged view of the segmentation results for the kidney nephron (1,265 cellular fragments).泭j, Coherence-based spectral clustering. The inset shows an enlarged view of clustering results for the kidney nephron (11 functional tissue ensembles).泭k, Nephron clusters ordered by time to first calcium activity peak within a burst (left), and raster of cellular activity within a single nephric burst, grouped by functional compartment and ordered within compartments using Rastermap (right). a.u., arbitrary units.泭l, Body-wide cellular activity raster ordered using Rastermap. On the right, a spectral cluster assignment is shown for some of the major organ groups. For visualization purposes, a random subset of 50 cells per cluster was included in the plot to reduce density of the figure, which was then ordered by Rastermap.泭m, Population-level dynamics. Mean activity of example functional tissue ensembles showing distinct dynamic profiles: high-frequency (for example, neurons and muscles), slower-evolving (for example, nephric tissue), tonic bistable (for example, sympathetic ganglion) and oscillatory (for example, enteric tissue) activity.

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