Candida Infection Biology – fungal armoury, battlefields ... - FINSysB

Poster number: 43
Genetic code ambiguity accelerates evolution of drug
resistance in Candida albicans
Tobias Weil, Ana R. Bezerra, João Simões and Manuel A. S. Santos
Department of Biology – CESAM, University of Aveiro, 3810-193 Aveiro, Portugal.
The opportunistic fungal pathogen Candida albicans has evolved to survive within
human hosts where it can cause serious diseases in immunocompromised patients.
The emergence of drug-resistant C. albicans strains has become a severe clinical
problem and the mechanisms of fungal drug resistance are still poorly understood.
In the present study we are testing the hypothesis that mRNA mistranslation is
relevant for the evolution of drug resistance. A characteristic feature of C. albicans
biology is the reassignment of the leucine CUG codon to serine. Remarkably, the
serine tRNA that decodes the CUG codons is aminoacylated in vivo with both serine
(3%) and leucine (97%). Such tRNA ambiguity is incorporated into proteins and
creates a statistical proteome. It is not yet clear whether proteome variation is
relevant for C. albicans parthogenesis, however, the potential of CUG ambiguity to
alter cell wall proteins and remodel surface antigens may help C. albicans evading
the immune system and gain advantages in terms of drug resistance. To determine
whether increasing mistranslation levels have important implications for C. albicans
drug resistance we have constructed a series of C. albicans strains that mistranslate
leucine CUG codons as serine at a rate up to 65% and exposed them to azoles,
which are commonly used to treat patients with fungal infections. Interestingly,
these strains developed drug resistance quite rapidly confirming our hypothesis
that mistranslation is indeed relevant for drug resistance. We are now applying in
vivo approaches combined with systems biology techniques based on gene
expression profiling with microarrays and deep genome sequencing in order to
identify novel putative drug target genes and pathways.
Acknowledgements: TW is supported by the European FP7 framework programme
SYBARIS.
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