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Biology subjects

Loy, J.

Publications and source records attributed to Loy, J..

2 recordsLinked to original sources

TLR5 drives metabolic dysfunction-associated steatohepatitis through lipid- and flagellin-induced hepatocyte injury signalling

Liver fibrosis is a strong predictor of clinical outcomes in metabolic dysfunction-associated steatohepatitis (MASH). Fibrosis is a consequence of persistent liver cell injury and inflammation in which Toll-like receptors (TLRs) play a key initiating role. Here we test the hypothesis that TLR5 is involved in the development of MASH and fibrosis using a combination of clinical data from multiple independent patient cohorts, single cell liver transcriptomics and human in vitro and ex vivo models. Hepatic TLR5 expression, but not TLR2 or TLR4, is associated with liver fibrosis and mortality. Plasma levels of TLR5s cognate ligand flagellin are increased in MASH with advanced fibrosis and fall with liver disease improvement. Mechanistically, we identify two parallel TLR5-mediated routes to hepatocyte injury: one elicited by flagellin and the other indirectly by lipid injury. Furthermore, hepatocyte TLR5 inhibition abrogates paracrine activation of hepatic stellate cells to suppress collagen production. This is also seen ex vivo in patient-derived precision-cut liver slices where TLR5 inhibition significantly reduces lipid-induced collagen deposition. These findings reveal a new role for TLR5 signalling, specifically in the development of advanced MASH fibrosis and may offer a novel disease-specific therapeutic approach.

molecular biology↗

Synthetic microbial sensing and biosynthesis of amaryllidaceae alkaloids

A major challenge to achieving industry-scale biomanufacturing of therapeutic alkaloids is the slow process of biocatalyst engineering. Amaryllidaceae alkaloids, such as the Alzheimers medication galantamine, are complex plant secondary metabolites with recognized therapeutic value. Due to their difficult synthesis they are regularly sourced by extraction and purification from low-yielding plants, including the wild daffodil Narcissus pseudonarcissus. Engineered biocatalytic methods have the potential to stabilize the supply chain of amaryllidaceae alkaloids. Here, we propose a highly efficient biosensor-AI technology stack for biocatalyst development, which we apply to engineer amaryllidaceae alkaloid production in Escherichia coli. Directed evolution is used to develop a highly sensitive (EC50= 20 uM) and specific biosensor for the key amaryllidaceae alkaloid branchpoint 4-OMethylnorbelladine. A machine learning model (MutComputeX) was subsequently developed and used to generate activity-enriched variants of a plant methyltransferase, which were rapidly screened with the biosensor. Functional enzyme variants were identified that yielded a 60% improvement in product titer, 17-fold reduced remnant substrate, and 3-fold lower off-product regioisomer formation.

synthetic biology↗