Prisca Liberali

Bulk transcriptome and proteome correlate only modestly, but this has not been investigated in the same cell or across cell-state changes. Here we introduce a scalable technology that quantifies thousands of proteins and transcripts in the same cell, separating RNA from protein by tip-based C18 capture and pairing full-length RNA sequencing with latest-generation mass spectrometry. In HeLa cells, transcript and protein abundances agree on the broad ranking within a cell (r = 0.45), but do not co-vary across the population (r = 0.038). In pluripotency transitions, only a third of matched transcripts and proteins change synchronously, yet the transcription factors defining each state stay tightly co-regulated. Transcript variance is several-fold larger than protein variance, reflecting transcriptional bursting and mRNA sampling noise. The proteome is thus the stable, low-noise definition of cell state, while the transcriptome marks cellular transitions; consequently, the proteome defines cell-state from far fewer cells.

Cells operate as networks of proteins, membranes, condensates and compartments, each sensing and displaying distinct intracellular mechanical properties. However, cells also sense, adapt and respond to manifold mechanical properties of the environment, including adhesion, tension, stiffness, shear, viscoelasticity, plasticity, pressure and confinement. By gauging these properties at various timescales and across nano to macro length scales, cellular systems alter their collective responses. The field of mechanobiology aims to elucidate how cellular systems such as tissues, organoids or organs perceive, respond to and influence mechanical cues, and how these impact physiological processes including homeostasis, growth, division, differentiation, movement, development, adaptation and apoptosis. This Perspective highlights challenges within mechanobiology that must be systematically tackled to advance exploration and deepen our understanding of the mechanical attributes of intricate multicellular organisms. Such understanding necessitates the engineering of multicellular models as reference systems, the development of new tools to rigorously quantify and manipulate mechanical properties from the nanoscale to macroscale and theoretical frameworks to decode mechanobiological complexities. Ultimately, addressing these challenges will improve the analysis, monitoring and prediction of mechanobiological processes across molecular, multicellular and organismal scales, thus advancing mechanodiagnostics and mechanomedicine.

The rapid growth in microscopy data volume, dimensionality, and diversity urgently calls for scalable and reproducible analysis frameworks. While efforts on the open OME-Zarr format have helped standardize the storage of large microscopy datasets, solutions for standardized processing are still lacking. Here, we introduce two complementary contributions to address this gap: 1) the Fractal task specification, defining OME-Zarr processing units that can interoperate across computational environments and workflow engines, and 2) the Fractal platform, using this specification to enable scalable and modular OME-Zarr-native analysis workflows. We demonstrate their use across diverse biological research data, including terabyte-scale multiplexed, volumetric, and time-lapse imaging. In a clinical setting, we show that Fractal workflows achieve near-identical quantification of millions of cells across independent deployments, demonstrating the reproducibility required for translational applications. With its growing community of contributors, the Fractal ecosystem provides a foundation for FAIR microscopy image analysis relying on open file formats.

Cell growth and division must be coordinated to maintain a stable cell size, but how this coordination is implemented in multicellular tissues remains unclear. In unicellular eukaryotes, autonomous cell size control mechanisms couple cell growth and division with little extracellular input. However, in multicellular tissues we do not know if autonomous cell size control mechanisms operate the same way or whether cell growth and cell cycle progression are separately controlled by cell-extrinsic signals. Here, we address this question by tracking single epidermal stem cells growing in the mouse ear. We find that a cell-autonomous size control mechanism, dependent on the RB pathway, sets the timing of S phase entry based on the cell’s current size. Cell-extrinsic variations in the cellular microenvironment affect cell growth rates but not this autonomous coupling. Our work reassesses long-standing models of cell cycle regulation in complex animal tissues and identifies cell-autonomous size control as a critical mechanism regulating cell division.

Imaging techniques are an important and growing source of scientific data, but the many different standards and file formats for representing and storing such data make streamlined analysis and data sharing cumbersome. To address this issue, the imaging community has recently developed an open and flexible file format specification (OME-NGFF) (Moore et al., 2021) and a concrete implementation using the Zarr file format (OME-Zarr) (Moore et al., 2023), which is increasingly adopted as the way to store and share multidimensional bioimaging data.

Human pluripotent stem cells and tissue-resident fetal and adult stem cells can generate epithelial tissues of endodermal origin in vitro that recapitulate aspects of developing and adult human physiology. Here, we integrate single-cell transcriptomes from 218 samples covering organoids and other models of diverse endoderm-derived tissues to establish an initial version of a human endoderm-derived organoid cell atlas. The integration includes nearly one million cells across diverse conditions, data sources and protocols. We compare cell types and states between organoid models and harmonize cell annotations through mapping to primary tissue counterparts. Focusing on the intestine and lung, we provide examples of mapping data from new protocols and show how the atlas can be used as a diverse cohort to assess perturbations and disease models. The human endoderm-derived organoid cell atlas makes diverse datasets centrally available and will be valuable to assess fidelity, characterize perturbed and diseased states, and streamline protocol development.

Reproducible pattern and form generation during embryogenesis is poorly understood. Intestinal organoid morphogenesis involves a number of mechanochemical regulators such as cell-type-specific cytoskeletal forces and osmotically driven lumen volume changes. It is unclear how these forces are coordinated in time and space to ensure robust morphogenesis. Here we show how mechanosensitive feedback on cytoskeletal tension gives rise to morphological bistability in a minimal model of organoid morphogenesis. In the model, lumen volume changes can impact the epithelial shape via both direct mechanical and indirect mechanosensitive mechanisms. We find that both bulged and budded crypt states are possible and dependent on the history of volume changes. We test key modelling assumptions via biophysical and pharmacological experiments to demonstrate how bistability can explain experimental observations, such as the importance of the timing of lumen shrinkage and robustness of the final morphogenetic state to mechanical perturbations. This suggests that bistability arising from feedback between cellular tensions and fluid pressure could be a general mechanism that coordinates multicellular shape changes in developing systems.

Tissue regeneration relies on the ability of cells to undergo de novo patterning. While tissue patterning has been viewed as the transition from initially identical un-patterned cells to an arrangement of different cell types, recent evidence suggests that initial heterogeneities between cells modulate tissue-scale pattern formation. Yet, how such heterogeneities arise and, thereafter, regulate cell type emergence in a population of cells is poorly understood. Using in vivo and in vitro mouse regenerative systems, we identify a critical tissue density that is required to induce heterogeneous inactivation of the mechanosensor YAP1. Experimental and biophysical approaches demonstrate that YAP1 cell-to-cell heterogeneity pre-patterns the first cell fate decision, via both chromatin remodelling and a supracellular feedback between FOXA1 and Delta-Notch signalling. This feedback motif induces cell fate bistability endowing memory to the system and the maintenance of patterns during homeostasis. These findings reveal a generalisable framework in which transient cell-to-cell heterogeneity, regulated by tissue-scale properties, serves as a critical control parameter for the emergence of cell fate and stable patterning during regeneration.