Biology subjects

Cairoli, A.

Publications and source records attributed to Cairoli, A..

4 recordsLinked to original sources

bioRxiv2024

Growth compensation upon changes in tissue size in the Drosophila abdomen

Attaining the appropriate size during development is essential for the function of animal tissues and organs. Robust tissue size control implies the existence of compensatory mechanisms that allow developing systems to recover from growth perturbations. However, the difficulty of directly observing normal or compensatory developmental growth means we have little understanding of the cellular behaviours that confer robustness to tissue size control. Here, we study how growth perturbations affect proliferation kinetics and the timing of growth termination of Drosophila histoblasts, the progenitors that give rise to the adult abdominal epidermis. Histoblasts undergo extensive growth and proliferation during the pupal stage, which is accessible for long-term live-imaging and precise quantitative analysis. By manipulating cell number or volume prior to the pupal growth phase, we changed the starting size of the abdomen primordium, then observed how the histoblasts adapted to these changes by altering their growth dynamics. We show that, upon a decrease in starting tissue size, the histoblasts compensate by extending their temporal proliferative window, undergoing additional cell cycles, as well as increasing their apical area to maximise coverage of the abdominal surface. When initial tissue size is increased, the histoblasts undergo fewer division cycles and arrest proliferation earlier than normal. Thus, the proliferative window of this tissue is flexible enough to buffer for changes in tissue size. Our data also suggest that the histoblasts sense both spatial and temporal cues to arrest their growth at the appropriate time and ensure accurate tissue size control.

developmental biology↗

bioRxiv2024

Spherical Phenotype Clustering

Phenotypic screening experiments produce many microscope images of cells under diverse perturbations, with biologically significant responses often subtle or difficult to identify visually. A central challenge is to extract image representations that distinguish activity from controls and group phenotypically similar perturbations. In this work we propose new adaptations of contrastive loss functions that incorporate experimental metadata as learned class vectors, and a geometrically inspired variant, called SPC, where class vectors are confined to the unit sphere and updated only by attractive terms (allowing more overlap of phenotypically similar classes). The approach is tested on two popular benchmarking datasets, BBBC021 and RxRx3-core; and we also evaluate performance on uncurated screens of HaCaT cells to gauge effectiveness in a realistic use-case scenario. We find we outperform prior methods across the three datasets and on a wide array of metrics measuring phenotype grouping, biological recall, drug-target interaction and mechanism-of-action inference. We also show we maintain this improved performance compared to models over 10x larger in parameter count, and that SPC can be used as an effective fine-tuning technique. The method is easy to implement and is well suited to settings with limited data or compute resources.

bioinformatics↗

bioRxiv2024

Patient-derived lymphomoids preserve the tumor architecture and allow to assess response to therapies in lymphoma

The efficacy of anti-cancer therapies depends on the genomic composition of the tumor, its microenvironment, spatial organization, and intra-tumor heterogeneity. B cell lymphomas are a heterogeneous group of tumors emerging from B cells at different stages of differentiation and exhibiting tumor-specific interactions with the tumor microenvironment. Thus, to measure response to therapy in lymphoma, it is critical to preserve the tumor composition and functional interactions among immune cells. Here, we developed a platform to maintain small fragments of human lymphoma tissue in culture for several days and use them to test response to therapies. We collected 25 patient samples representative of different lymphoma subtypes and established ex vivo tissue fragments that retained histological, cellular, and molecular characteristics of the original tissue, here referred to as lymphomoids. Using lymphomoids, we tested sensitivity to several clinically approved small molecule inhibitors in parallel and examined tissue remodeling upon treatment. Importantly, when this information was available, we showed that sensitivity to therapy observed in lymphomoids was consistent with patients response in the clinic. Lymphomoids are an innovative tool to assess treatment efficacy in clinically relevant contexts and could be used to uncover novel aspects of lymphoma biology.

cancer biology↗

bioRxiv2022

Model of inverse bleb growth explains giant vacuole dynamics during cell mechanoadaptation

Cells can withstand hostile environmental conditions manifest as large mechanical forces such as pressure gradients and/or shear stresses by dynamically changing their shape. Such conditions are realized in the Schlemms canal of the eye where endothelial cells that cover the inner vessel wall are subjected to the hydrodynamic pressure gradients exerted by the aqueous humor outflow. These cells form fluid-filled dynamic outpouchings of their basal membrane called giant vacuoles. The inverse of giant vacuoles are reminiscent of cellular blebs, extracellular cytoplasmic protrusions triggered by local temporary disruption of the contractile actomyosin cortex. Inverse blebbing has been first observed experimentally during sprouting angiogenesis, but its underlying physical mechanisms are poorly understood. Here, we identify giant vacuole formation as inverse blebbing and formulate a biophysical model of this process. Our model elucidates how cell membrane mechanical properties affect the morphology and dynamics of giant vacuoles and predicts coarsening akin to Ostwald ripening between multiple invaginating vacuoles. Our results are in qualitative agreement with observations from the formation of giant vacuoles during perfusion experiments. Our model not only elucidates the biophysical mechanisms driving inverse blebbing and giant vacuole dynamics, but also identifies universal features of the cellular response to pressure loads that are relevant to many experimental contexts. Significance statementHuman Schlemms canal endothelial cells in physiological conditions are subjected to a pressure gradient caused by the flow of aqueous humor in the basal-to-apical direction across the endothelium leading to the formation of cellular outpouchings called giant vacuoles. The physical mechanisms regulating giant vacuole formation are unknown. By describing giant vacuoles as inward blebs, we formulate a model of their growth and collapse that captures the characteristic features observed experimentally. Our theory reveals that the abrupt increase in surface tension caused by membrane stretching, which is required to accommodate the large areal strains locally induced by inward blebbing, limits giant vacuole growth. The model also predicts a competition between multiple invaginating vacuoles in which big vacuoles win over small vacuoles.

biophysics↗