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Biology subjects

Gadd, V. L.

Publications and source records attributed to Gadd, V. L..

2 recordsLinked to original sources

Single-cell morphological tracking of liver cell states to identify small-molecule modulators of liver differentiation

Alternative therapeutic strategies are urgently required to treat liver disease, which is responsible for 2 million deaths anually. By combining Cell Painting, a morphological profiling assay that captures diverse cellular states, with the bi-potent HepaRG(R) liver progenitor cell line, we have developed a high-throughput, single-cell technique, to track liver cell fate and map small-molecule induced changes using a morphological atlas of bi-lineage liver cell differentiation. To our knowledge this is the first-time single-cell trajectory inference has been applied to image-based Cell Painting data and leveraged for drug screening. The overarching goal of this new method is to aid research into understanding liver cell regeneration mechanisms and facilitate the development of cell-based and small-molecule therapies. Using this approach, we have identified a class of small-molecule SRC family kinase inhibitors that promote differentiation of HepaRG(R) single-cells towards the hepatocyte-like lineage and promotes differentiation of primary human hepatic progenitor cells towards a hepatocyte-like phenotype in vitro.

cell biology↗

Utilising an in silico model to predict outcomes in senescence-driven acute liver injury

Currently liver transplantation is the only treatment option for liver disease, but organ availability cannot meet demand and transplant recipients require lifelong immunosuppression. The identification of alternative treatments, e.g. cell therapies, able to tip resolution of injury from inflammation to regeneration requires an understanding of the host response to the degree of injury. We adopt a combined in vivo-in silico approach and develop a mathematical model of acute liver disease able to predict the host response to injury. We utilise the Mdm2fl/fl mouse model together with a single Cre induction through intravenous injection of the hepatotropic Adeno-associated Virus Serotype 8 Cre (AAV8.Cre) to model acute liver injury. We derive a complementary ordinary differential equation model to capture the dynamics of the key cell players in the injury response together with the extracellular matrix. We show that the mathematical model is able to predict the host response to moderate injury via qualitative comparison of the model predictions with the experimental data. We then use the model to predict the host response to mild and severe injury, and test these predictions in vivo, obtaining good qualitative agreement.

cell biology↗