A deep sequencing tool for partitioning clearance rates following antimalarial treatment in polyclonal infections

BACKGROUND AND OBJECTIVES: Current tools struggle to detect drug-resistant malaria parasites when infections contain multiple parasite clones, which is the norm in high transmission settings in Africa. Our aim was to develop and apply an approach for detecting resistance that overcomes the challenges of polyclonal infections without requiring a genetic marker for resistance. METHODOLOGY: Clinical samples from patients treated with artemisinin combination therapy were collected from Tanzania and Cambodia. By deeply sequencing a hypervariable locus, we quantified the relative abundance of parasite subpopulations (defined by haplotypes of that locus) within infections and revealed evolutionary dynamics during treatment. Slow clearance is a phenotypic, clinical marker of artemisinin resistance; we analyzed variation in clearance rates within infections by fitting parasite clearance curves to subpopulation data. RESULTS: In Tanzania, we found substantial variation in clearance rates within individual patients. Some parasite subpopulations cleared as slowly as resistant parasites observed in Cambodia. We evaluated possible explanations for these data, including resistance to drugs. Assuming slow clearance was a stable phenotype of subpopulations, simulations predicted that modest increases in their frequency could substantially increase time to cure. CONCLUSIONS AND IMPLICATIONS: By characterizing parasite subpopulations within patients, our method can detect rare, slow clearing parasites in vivo whose phenotypic effects would otherwise be masked. Since our approach can be applied to polyclonal infections even when the genetics underlying resistance are unknown, it could aid in monitoring the emergence of artemisinin resistance. Our application to Tanzanian samples uncovers rare subpopulations with worrying phenotypes for closer examination

The adaptation of the plant pathogen Pseudomonas syringae onto the novel host Arabidopsis thaliana through experimental evolution

The bacterial plant pathogen Pseudomonas syringae is a highly diverse species complex that can infect and cause disease on a wide range of hosts. Despite this broad host range, individual strains of P. syringae are highly host specific. In this thesis, we used in planta serial passaging to experimentally evolve twelve independent lineages of P. syringae pathovar phaseolicola (Pph) 1448A, a bean pathogen, on the novel host Arabidopsis thaliana (Arabidopsis), with the goal of characterizing the early adaptive steps towards host adaptation. Twelve hypermutating lineages of Pph 1448A were constructed for this experiment to increase the evolvability of lineages, and to efficiently study mutations associated with adaptation towards Arabidopsis. After eighty days of passaging on the novel host, lineage 7 has shown a significant gain in fitness on Arabidopsis. Population sequencing of this lineage may provide novel insights into the adaptive processes underlying host specificity in P. syringae.M.Sc

Evaluating colour in concept diagrams

This paper is the first to establish the impact of colour on users’ ability to interpret the informational content of concept diagrams, a logic designed for ontology engineering. Motivation comes from results for Euler diagrams, which form a fragment of concept diagrams: manipulating curve colours affects user performance. In particular, using distinct curve colours yields significant performance benefits in Euler diagrams. Naturally, one would expect to obtain similar empirical results for concept diagrams, since colour is a graphical feature to which we are perceptually sensitive. Thus, this paper sets out to test this expectation by conducting a crowdsourced empirical study involving 261 participants. Our study suggests that manipulating curve colours no longer yields significant performance differences in this syntactically richer logic. Consequently, when using colour to visually group syntactic elements with common semantic properties, we ask how different do the elements’ shapes need to be in order for there to be significant performance benefits arising from using colours