Development of metagenomics-based diagnostics of infectious diseases (360G-Wellcome-206478_Z_17_Z)

During this fellowship I will use high throughput sequencing (HTS) and novel analytical methods to develop a framework for the investigation and diagnosis of infectious diseases. The focus will be on complex and difficult to diagnose diseases, such as encephalitis and meningitis, where pathogen detection rates remain poor. I will first optimise my existing Bayesian mixture model approach1–7 to ensure its wider application to a range of infections and suspected pathogens. I will then analyse metagenomic RNA-seq data from brain biopsy, cerebrospinal fluid (CSF) and whole blood samples towards pathogen detection. For selected samples where the cause of the disease is known, I will investigate whether host transcript signatures can distinguish infectious or autoimmune encephalitis, motivated by successes in other infectious diseases8–12. I hypothesize that diagnosis will benefit from the joint analysis of pathogen and host genomic data. A distinct but related problem is to characterize single pathogen mixed infections and to better understand their effect on disease phenotype and severity. This proposal goes beyond diagnostics to provide a platform for discovery research including novel virulence determinants, tropism, association of genotype and phenotype, description of novel pathogens, host gene expression patterns and characterization of co-infections and mixed infections.