Back

Geographic microevolution of Mycobacterium ulcerans sustains Buruli ulcer extension, Australia

Saad, J.; Hammoudi, N.; Zgheib, R.; Anani, H.; Drancourt, M.

2020-11-04 evolutionary biology
10.1101/2020.11.03.366435 bioRxiv
Show abstract

The reason why severe cases of Buruli ulcers caused by Mycobacterium ulcerans are emerging in some South Australia counties has not been determined. In this study, we measured the diversity of M. ulcerans complex whole genome sequences (WGS) and reported a marker of this diversity. Using this marker as a probe, we compared WGS diversity in Buruli ulcer-epidemic South Australia counties versus non-epidemic Australian counties and further refined comparisons at the level of counties where severe Buruli ulcer cases have been reported. Analyzing 218 WGS (35 complete and 183 reconstructed WGS, including 174 Australian WGS) yielded 15 M. ulcerans complex genotypes, including three genotypes specific to Australia and one genotype specific to South Australia. A 1,068-bp PPE family protein gene exhibiting genotype-specific sequence variations was employed to further probe 13 minority clones hidden in sequence reads. The repartition of these clones significantly differed between South Australia and the rest of Australia. In addition, a significantly higher prevalence of 3/13 clones was observed in South Australia counties of the Mornington Peninsula, Melbourne and Bellarine Peninsula than in other South Australia counties. The data presented in this report suggest that the microevolution of three M. ulcerans complex clones drove the emergence of severe Buruli ulcer cases in some South Australia counties. Sequencing one specific PPE gene served to efficiently probe M. ulcerans complex clones. Further functional studies may balance the environmental adaptation and virulence of these clones.

Matching journals

The top 8 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.