Evolutionary dynamics of methicillin-resistant Staphylococcus aureus within a healthcare system

BackgroundIn the past decade, several countries have seen gradual replacement of endemic multi-resistant healthcare-associated methicillin-resistant Staphylococcus aureus (MRSA) with clones that are more susceptible to antibiotic treatment. One example is Singapore, where MRSA ST239, the dominant clone since molecular profiling of MRSA began in the mid-1980s, has been replaced by ST22 isolates belonging to EMRSA-15, a recently emerged pandemic lineage originating from Europe.ResultsWe investigated the population structure of MRSA in Singaporean hospitals spanning three decades, using whole genome sequencing. Applying Bayesian phylogenetic methods we report that prior to the introduction of ST22, the ST239 MRSA population in Singapore originated from multiple introductions from the surrounding region; it was frequently transferred within the healthcare system resulting in a heterogeneous hospital population. Following the introduction of ST22 around the beginning of the millennium, this clone spread rapidly through Singaporean hospitals, supplanting the endemic ST239 population. Coalescent analysis revealed that although the genetic diversity of ST239 initially decreased as ST22 became more dominant, from 2007 onwards the genetic diversity of ST239 began to increase once more, which was not associated with the emergence of a sub-clone of ST239. Comparative genomic analysis of the accessory genome of the extant ST239 population identified that the Arginine Catabolic Mobile Element arose multiple times, thereby introducing genes associated with enhanced skin colonization into this population.ConclusionsOur results clearly demonstrate that, alongside clinical practice and antibiotic usage, competition between clones also has an important role in driving the evolution of nosocomial pathogen populations.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-015-0643-z) contains supplementary material, which is available to authorized users.     

Selection of haplotype variables from a high-density marker map for genomic prediction

Background

Using haplotype blocks as predictors rather than individual single nucleotide polymorphisms (SNPs) may improve genomic predictions, since haplotypes are in stronger linkage disequilibrium with the quantitative trait loci than are individual SNPs. It has also been hypothesized that an appropriate selection of a subset of haplotype blocks can result in similar or better predictive ability than when using the whole set of haplotype blocks. This study investigated genomic prediction using a set of haplotype blocks that contained the SNPs with large effects estimated from an individual SNP prediction model. We analyzed protein yield, fertility and mastitis of Nordic Holstein cattle, and used high-density markers (about 770k SNPs). To reach an optimum number of haplotype variables for genomic prediction, predictions were performed using subsets of haplotype blocks that contained a range of 1000 to 50 000 main SNPs.

Results

The use of haplotype blocks improved the prediction reliabilities, even when selection focused on only a group of haplotype blocks. In this case, the use of haplotype blocks that contained the 20 000 to 50 000 SNPs with the highest effect was sufficient to outperform the model that used all individual SNPs as predictors (up to 1.3 % improvement in prediction reliability for mastitis, compared to individual SNP approach), and the achieved reliabilities were similar to those using all haplotype blocks available in the genome data (from 0.6 % lower to 0.8 % higher reliability).

Conclusions

Haplotype blocks used as predictors can improve the reliability of genomic prediction compared to the individual SNP model. Furthermore, the use of a subset of haplotype blocks that contains the main SNP effects from genomic data could be a feasible approach to genomic prediction in dairy cattle, given an increase in density of genotype data available. The predictive ability of the models that use a subset of haplotype blocks was similar to that obtained using either all haplotype blocks or all individual SNPs, with the benefit of having a much lower computational demand.     

Differential Virulence of Candida glabrata Glycosylation Mutants

The fungus Candida glabrata is an important and increasingly common pathogen of humans, particularly in immunocompromised hosts. Despite this, little is known about the attributes that allow this organism to cause disease or its interaction with the host immune system. However, in common with other fungi, the cell wall of C. glabrata is the initial point of contact between the host and pathogen, and as such, it is likely to play an important role in mediating interactions and hence virulence. Here, we show both through genetic complementation and polysaccharide structural analyses that C. glabrata ANP1, MNN2, and MNN11 encode functional orthologues of the respective Saccharomyces cerevisiae mannosyltransferases. Furthermore, we show that deletion of the C. glabrata Anp1, Mnn2, and Mnn11 mannosyltransferases directly affects the structure of the fungal N-linked mannan, in line with their predicted functions, and this has implications for cell wall integrity and consequently virulence. C. glabrata anp1 and mnn2 mutants showed increased virulence, compared with wild-type (and mnn11) cells. This is in contrast to Candida albicans where inactivation of genes involved in mannan biosynthesis has usually been linked to an attenuation of virulence. In the long term, a better understanding of the attributes that allow C. glabrata to cause disease will provide insights that can be adopted for the development of novel therapeutic and diagnostic approaches.     

Fertility Defects in Mice Expressing the L68Q Variant of Human Cystatin C: A ROLE FOR AMYLOID IN MALE INFERTILITY*

Hereditary cystatin C amyloid angiopathy is an autosomal dominant disorder in which a variant form of cystatin C (L68Q) readily forms amyloid deposits in cerebral arteries in affected individuals resulting in early death. L68Q protein deposits in human cystatin C amyloid angiopathy patients have also been found in tissues outside of the brain including the testis, suggesting possible effects on fertility. Heterozygous transgenic mice (L68Q) that express the human L68Q variant of cystatin C under the control of the mouse cystatin C promoter were unable to generate offspring, suggesting the presence of L68Q cystatin C amyloid affected sperm function. In vitro studies showed that epididymal spermatozoa from L68Q mice were unable to fertilize oocytes and exhibited poor sperm motility. Furthermore, spermatozoa from L68Q mice exhibited reduced cell viability compared with wild type (WT) spermatozoa and often were detected in large agglutinated clumps. Examination of the epididymal fluid and spermatozoa from L68Q mice showed increased levels and distinct forms of cystatin C amyloid that were not present in WT mice. The addition of epididymal fluid from L68Q mice to WT spermatozoa resulted in a recapitulation of the L68Q phenotype in that WT spermatozoa showed reduced cell viability and motility compared with WT spermatozoa incubated in epididymal fluid from WT mice. L68Q epididymal fluid that was depleted of cystatin C amyloids, however, did not impair the motility of WT spermatozoa. Taken together these studies suggest that amyloids in the epididymal fluid can be cytotoxic to the maturing spermatozoa resulting in male infertility.     

Genomic prediction of genetic merit using LD-based haplotypes in the Nordic Holstein population

Background

A haplotype approach to genomic prediction using high density data in dairy cattle as an alternative to single-marker methods is presented. With the assumption that haplotypes are in stronger linkage disequilibrium (LD) with quantitative trait loci (QTL) than single markers, this study focuses on the use of haplotype blocks (haploblocks) as explanatory variables for genomic prediction. Haploblocks were built based on the LD between markers, which allowed variable reduction. The haploblocks were then used to predict three economically important traits (milk protein, fertility and mastitis) in the Nordic Holstein population.

Results

The haploblock approach improved prediction accuracy compared with the commonly used individual single nucleotide polymorphism (SNP) approach. Furthermore, using an average LD threshold to define the haploblocks (LD≥0.45 between any two markers) increased the prediction accuracies for all three traits, although the improvement was most significant for milk protein (up to 3.1 % improvement in prediction accuracy, compared with the individual SNP approach). Hotelling’s t-tests were performed, confirming the improvement in prediction accuracy for milk protein. Because the phenotypic values were in the form of de-regressed proofs, the improved accuracy for milk protein may be due to higher reliability of the data for this trait compared with the reliability of the mastitis and fertility data. Comparisons between best linear unbiased prediction (BLUP) and Bayesian mixture models also indicated that the Bayesian model produced the most accurate predictions in every scenario for the milk protein trait, and in some scenarios for fertility.

Conclusions

The haploblock approach to genomic prediction is a promising method for genomic selection in animal breeding. Building haploblocks based on LD reduced the number of variables without the loss of information. This method may play an important role in the future genomic prediction involving while genome sequences.