Metrology, the study of measurement, is an emerging concept within molecular diagnosis of infection. Metrology promotes high-quality, reproducible data to be used in clinical management of infection, through characterisation of technical error and measurement harmonisation. This influences measurement accuracy, which has implications for setting thresholds between healthy and disease states, monitoring disease progression, and establishing cures. This thesis examines the placing of metrology in molecular diagnosis of infectious diseases. Sources of experimental error in advanced methodologies – dPCR and MALDI-TOF MS – that can influence measurement accuracy for RNA, DNA and protein biomarkers were investigated for HIV-1, methicillin-resistant Staphylococcus spp and organisms associated with hospital transmission. Measurement error introduced at different stages of a method can directly impact upon clinical results. A 30% bias was introduced between dPCR and qPCR quantification of HIV-1 DNA in clinical samples, owing to instability in the qPCR calibration material. In addition, experimental variability was found to influence classification of protein profiles which can limit the resolution of MALDI-TOF MS for strain typing bacteria. This thesis also addresses the prospective role of these advanced methods in supporting accurate clinical measurements. dPCR offers precise measurements of RNA and DNA targets and could be used to support qPCR, or for value assignment of reference materials to harmonise inter-laboratory results. MALDI-TOF MS demonstrated potential for strain typing Acinetobacter baumannii; results correlated with epidemiological data and WGS, although were not consistent with reference typing. Further work should examine the extent to which MALDI-TOF MS can support or replace contemporary strain typing methods for identifying nosocomial outbreaks. Molecular approaches possess a crucial role in the detection, quantification and characterisation of pathogens, and are invaluable tools for managing emerging diseases. Supporting accuracy and reproducibility in molecular measurements could help to strengthen diagnostic efforts, streamline clinical pathways and provide overall benefit to patient care
