Cancer-on-a-chip model shows that the adenomatous polyposis coli mutation impairs T cell engagement and killing of cancer spheroids.

Evaluating the ability of cytotoxic T lymphocytes (CTLs) to eliminate tumor cells is crucial, for instance, to predict the efficiency of cell therapy in personalized medicine. However, the destruction of a tumor by CTLs involves CTL migration in the extra-tumoral environment, accumulation on the tumor, antigen recognition, and cooperation in killing the cancer cells. Therefore, identifying the limiting steps in this complex process requires spatio-temporal measurements of different cellular events over long periods. Here, we use a cancer-on-a-chip platform to evaluate the impact of adenomatous polyposis coli (APC) mutation on CTL migration and cytotoxicity against 3D tumor spheroids. The APC mutated CTLs are found to have a reduced ability to destroy tumor spheroids compared with control cells, even though APC mutants migrate in the extra-tumoral space and accumulate on the spheroids as efficiently as control cells. Once in contact with the tumor however, mutated CTLs display reduced engagement with the cancer cells, as measured by a metric that distinguishes different modes of CTL migration. Realigning the CTL trajectories around localized killing cascades reveals that all CTLs transition to high engagement in the 2 h preceding the cascades, which confirms that the low engagement is the cause of reduced cytotoxicity. Beyond the study of APC mutations, this platform offers a robust way to compare cytotoxic cell efficiency of even closely related cell types, by relying on a multiscale cytometry approach to disentangle complex interactions and to identify the steps that limit the tumor destruction.

Griottes: a generalist tool for network generation from segmented tissue images.

BACKGROUND: Microscopy techniques and image segmentation algorithms have improved dramatically this decade, leading to an ever increasing amount of biological images and a greater reliance on imaging to investigate biological questions. This has created a need for methods to extract the relevant information on the behaviors of cells and their interactions, while reducing the amount of computing power required to organize this information. RESULTS: This task can be performed by using a network representation in which the cells and their properties are encoded in the nodes, while the neighborhood interactions are encoded by the links. Here, we introduce Griottes, an open-source tool to build the "network twin" of 2D and 3D tissues from segmented microscopy images. We show how the library can provide a wide range of biologically relevant metrics on individual cells and their neighborhoods, with the objective of providing multi-scale biological insights. The library's capacities are demonstrated on different image and data types. CONCLUSIONS: This library is provided as an open-source tool that can be integrated into common image analysis workflows to increase their capacities.

Apical size and deltaA expression predict adult neural stem cell decisions along lineage progression.

The maintenance of neural stem cells (NSCs) in the adult brain depends on their activation frequency and division mode. Using long-term intravital imaging of NSCs in the zebrafish adult telencephalon, we reveal that apical surface area and expression of the Notch ligand DeltaA predict these NSC decisions. deltaA-negative NSCs constitute a bona fide self-renewing NSC pool and systematically engage in asymmetric divisions generating a self-renewing deltaAneg daughter, which regains the size and behavior of its mother, and a neurogenic deltaApos daughter, eventually engaged in neuronal production following further quiescence-division phases. Pharmacological and genetic manipulations of Notch, DeltaA, and apical size further show that the prediction of activation frequency by apical size and the asymmetric divisions of deltaAneg NSCs are functionally independent of Notch. These results provide dynamic qualitative and quantitative readouts of NSC lineage progression in vivo and support a hierarchical organization of NSCs in differently fated subpopulations.

Spatiotemporal dynamics of cytokines expression dictate fetal liver hematopoiesis.

During embryogenesis, yolk-sac and intra-embryonic-derived hematopoietic progenitors, comprising the precursors of adult hematopoietic stem cells, converge into the fetal liver. With a new staining strategy, we defined all non-hematopoietic components of the fetal liver and found that hepatoblasts are the major producers of hematopoietic growth factors. We identified mesothelial cells, a novel component of the stromal compartment, producing Kit ligand, a major hematopoietic cytokine. A high-definition imaging dataset analyzed using a deep-learning based pipeline allowed the unambiguous identification of hematopoietic and stromal populations, and enabled determining a neighboring network composition, at the single cell resolution. Throughout active hematopoiesis, progenitors preferentially associate with hepatoblasts, but not with stellate or endothelial cells. We found that, unlike yolk sac-derived progenitors, intra-embryonic progenitors respond to a chemokine gradient created by CXCL12-producing stellate cells. These results revealed that FL hematopoiesis is a spatiotemporal dynamic process, defined by an environment characterized by low cytokine concentrations.