Case Report: Genetic evolution of Burkholderia pseudomallei during treatment leading to antibiotic resistance and disease relapse – a case report.
Evans TJ., Keeratipusana C., Douangnouvong A., Phimolsarnnousith V., Sengdatka D., Chang K., Phommasone K., Chewapreecha C., Ashley EA., Batty EM.
Background Melioidosis is a significant yet neglected cause of sepsis in tropical regions, particularly in southeast Asia, with poor clinical outcomes. It is a growing threat with an expanding global footprint. The causative organism, Burkholderia pseudomallei, is intrinsically resistant to most first-line empiric antibiotic regimens, but acquired resistance to recommended antibiotics for this infection is uncommon. Nonetheless, the genetic determinants of resistance in this species remain poorly elucidated. Case presentation A 60-year-old farmer presented in septic shock to a hospital in Laos, and B. pseudomallei was grown from blood cultures. Following initial antibiotic treatment with meropenem and co-trimoxazole, his infection relapsed. Several subsequent B. pseudomallei isolates from the patient were resistant to multiple antibiotics, and whole genome sequencing demonstrated that this phenotype was associated with a novel 54-kb genomic deletion. This deletion, on chromosome 1, includes the 5’ end of amrR – which encodes a regulator of an efflux pump known to be important in conferring meropenem resistance – as well as 46 other genes, some of which have not been characterised. Treatment was targeted to the new antibiogram, requiring a further prolonged intravenous course and second-line oral eradication therapy. The patient made a full recovery. Conclusions Mutations in Burkholderia pseudomallei lead to increased virulence and drug resistance. Repeat microbiological sampling of patients who do not make clinical improvement as anticipated is essential, with repeat full antimicrobial susceptibility testing on subsequent isolates. Characterisation of drug-resistant mutants is required to understand mechanisms of resistance and to predict phenotypes from whole genome sequencing.