Abstract
In many microbes rapid mutation of highly mutable contingency genes continually replenishes a pool of variant alleles from which the most suitable are selected, assisting in rapid adaptation and evasion of the immune response. In some contingency genes mutability is achieved through DNA repeats within the coding region. The fungal human pathogen
Candida albicans
has 2600 repeat-containing ORFs. For those investigated (
ALS
genes,
HYR1, HYR2, CEK1, RLM1
) many protein variants with differing amino acid repeat regions exist, as expected for contingency genes. However, specific alleles dominate in different clades, which is unexpected if allele variation is used for short-term adaptation. Generation of new alleles of repeat-containing
C. albicans
ORFs has never been observed directly. Here we present evidence for restrictions on the emergence of new alleles in a highly mutable
C. albicans
repeat-containing ORF,
PNG2
, encoding a putative secreted or cell surface glycoamidase. In laboratory cultures new
PNG2
alleles arose at a rate of 2.8×10
−5
(confidence interval 3.3×10
−6
−9. 9×10
−5
) per cell per division, comparable to rates measured for contingency genes. Among 80 clinical isolates 17 alleles of different length and 23 allele combinations were distinguishable; sequence differences between repeat regions of identical size suggest the existence of 36 protein variants. Specific allele combinations predominated in different genetic backgrounds, as defined by DNA fingerprinting and multilocus sequence typing. Given the
PNG2
mutation rate, this is unexpected, unless in different genetic backgrounds selection favors different alleles. Specific alleles or allele combinations were not preferentially associated with
C. albicans
isolates from particular body sites or geographical regions. Our results suggest that the mutability of
PNG2
is not used for short-term adaptation or evasion of the immune system. Nevertheless the large number of alleles observed indicates that mutability of
PNG2
may assist
C. albicans
strains from different genetic backgrounds optimize their interaction with the host in the long term.