Fitness trade-offs restrict the evolution of resistance to amphotericin B

The rarity of clinical drug resistance to the antifungal amphotericin B is explained by the extreme costs that resistance mutations impose upon stress responses and virulence factors.

The evolution of drug resistance in microbial pathogens provides a paradigm for investigating evolutionary dynamics with important consequences for human health. Candida albicans, the leading fungal pathogen of humans, rapidly evolves resistance to two major antifungal classes, the triazoles and echinocandins. In contrast, resistance to the third major antifungal used in the clinic, amphotericin B (AmB), remains extremely rare despite 50 years of use as monotherapy. We sought to understand this long-standing evolutionary puzzle. We used whole genome sequencing of rare AmB-resistant clinical isolates as well as laboratory-evolved strains to identify and investigate mutations that confer AmB resistance in vitro. Resistance to AmB came at a great cost. Mutations that conferred resistance simultaneously created diverse stresses that required high levels of the molecular chaperone Hsp90 for survival, even in the absence of AmB. This requirement stemmed from severe internal stresses caused by the mutations, which drastically diminished tolerance to external stresses from the host. AmB-resistant mutants were hypersensitive to oxidative stress, febrile temperatures, and killing by neutrophils and also had defects in filamentation and tissue invasion. These strains were avirulent in a mouse infection model. Thus, the costs of evolving resistance to AmB limit the emergence of this phenotype in the clinic. Our work provides a vivid example of the ways in which conflicting selective pressures shape evolutionary trajectories and illustrates another mechanism by which the Hsp90 buffer potentiates the emergence of new phenotypes. Developing antibiotics that deliberately create such evolutionary constraints might offer a strategy for limiting the rapid emergence of drug resistance.

The evolution of drug resistance in human pathogens is considered an inevitable consequence of the selective pressures imposed by antimicrobial drugs. Yet resistance to one antifungal drug, amphotericin B (AmB), remains extremely rare despite decades of widespread use. Here we explore the biological mechanisms underlying this conundrum. By examining natural and experimental populations of Candida albicans, we identify multiple mutations that confer resistance to AmB in vitro. As with the evolution of resistance to other antifungals, we find that the chaperone protein Hsp90 is involved in enabling the evolution of resistance to AmB. We also discover, however, that mutations that confer AmB resistance impose massive costs on other aspects of fungal pathogenicity; strains that are resistant to AmB are hypersensitive to attack by the host immune system and are unable to invade and damage host tissue. Thus, the evolution of resistance to AmB is restricted by a tradeoff between tolerance of the drug and the ability to cause disease. We propose that developing new antibiotics for which resistance presents such dire tradeoffs may be a promising strategy to prevent the evolution of resistance.

HLA-A, -B, -C, and -DRB1 allele and haplotype frequencies distinguish Eastern European Americans from the general European American population

Sequence-based typing was used to identify human leukocyte antigen (HLA)-A, -B, -C, and -DRB1 alleles from 558 consecutively recruited US volunteers with Eastern European ancestry for an unrelated hematopoietic stem cell registry. Four of 31 HLA-A alleles, 29 HLA-C alleles, 59 HLA-B alleles, and 42 HLA-DRB1 alleles identified (A*0325, B*440204, Cw*0332, and *0732N) are novel. The HLA-A*02010101g allele was observed at a frequency of 0.28. Two-, three-, and four-locus haplotypes were estimated using the expectation-maximization algorithm. The highest frequency extended haplotypes (A*010101g-Cw*070101g-B*0801g-DRB1*0301 and A*03010101g-Cw*0702-B*0702-DRB1*1501) were observed at frequencies of 0.04 and 0.03, respectively. Linkage disequilibrium values (Dij') of the constituent two-locus haplotypes were highly significant for both extended haplotypes (P values were less than 8 x 10(-10)) but were consistently higher for the more frequent haplotype. Balancing selection was inferred to be acting on all the four loci, with the strongest evidence of balancing selection observed for the HLA-C locus. Comparisons of the A-C-B haplotypes and DRB1 frequencies in this population with those for African, European, and western Asian populations showed high degrees of identity with Czech, Polish, and Slovenian populations and significant differences from the general European American population.

PyPop update--a software pipeline for large-scale multilocus population genomics

Population genetic statistics from multilocus genotype data inform our understanding of the patterns of genetic variation and their implications for evolutionary studies, generally, and human disease studies in particular. In any given population one can estimate haplotype frequencies, identify deviation from Hardy-Weinberg equilibrium, test for balancing or directional selection, and investigate patterns of linkage disequilibrium. Existing software packages are oriented primarily toward the computation of such statistics on a population-by-population basis, not on comparisons among populations and across different statistics. We developed PyPop (Python for Population Genomics) to facilitate the analyses of population genetic statistics across populations and the relationships among different statistics within and across populations. PyPop is an open-source framework for performing large-scale population genetic analyses on multilocus genotype data. It computes the statistics described above, among others. PyPop deploys a standard Extensible Markup Language (XML) output format and can integrate the results of multiple analyses on various populations that were performed at different times into a common output format that can be read into a spreadsheet. The XML output format allows PyPop to be embedded as part of a larger analysis pipeline. Originally developed to analyze the highly polymorphic genetic data of the human leukocyte antigen region of the human genome, PyPop has applicability to any kind of multilocus genetic data. It is the primary analysis platform for analyzing data collected for the Anthropological component of the 13th and 14th International Histocompatibility Workshops. PyPop has also been successfully used in studies by our group, with collaborators, and in publications by several independent research teams.