Frazer, I. H. | bioRxiv Science

bioRxiv2024

A rational approach for the targeted discovery and characterisation of microbiome-derived therapeutics

The human gut microbiome is intrinsically involved in health and disease, representing a wealth of untapped therapeutic potential. Here, we demonstrate the utility and potential of a metagenome guided, large cohort-based approach for the rational selection of live biotherapeutics from the human gut. We applied this approach to Inflammatory Bowel Disease (IBD), identifying several lead candidates that were significantly depleted in individuals with IBD compared to healthy controls. Their therapeutic potential was assessed in preclinical models of IBD where they improved markers of disease pathology by reducing inflammation and promoting mucosal healing and wound repair. All leads had excellent safety profiles in silico and in vitro, and several additionally presented favourable manufacturing properties, supporting their progression into clinical trials. We believe that this rational approach will be generalisable to any disease state with underlying microbiome aetiology and will expedite the development of novel microbiome-derived therapeutics to improve human health.

microbiology↗

bioRxiv2020

Spatial analysis of ligand-receptor interactions in skin cancer at genome-wide and single-cell resolution

The ability to study cancer-immune cell communication across the whole tumor section without tissue dissociation is needed for cancer immunotherapies, to understand molecular mechanisms and to discover potential druggable targets. In this work, we developed a powerful experimental and analytical toolbox to enable genome-wide scale discovery and targeted validation of cellular communication. We assessed the utilities of five sequencing and imaging technologies to study cancer tissue, including single-cell RNA sequencing and Spatial Transcriptomic (measuring over >20,000 genes), RNA In Situ Hybridization (multiplex 4-12 genes), digital droplet PCR, and Opal multiplex protein staining (4-9 proteins). To spatially integrate multimodal data, we developed a computational method called STRISH that can automatically scan across the whole tissue section for local expression of gene and/or protein markers to recapitulate an interaction landscape across the whole tissue. We evaluated the unique ability of this toolbox to discover and validate cell-cell interaction in situ through in-depth analysis of two types of cancer, basal cell carcinoma and squamous cell carcinoma, which account for over 70% of cancer cases. We expect that the approach described here will be widely applied to discover and validate ligand receptor interaction in different types of solid cancer tumors.

cancer biology↗