Prediction of Staphylococcus aureus antimicrobial resistance by whole-genome sequencing

Whole-genome sequencing (WGS) could potentially provide a single platform for extracting all the information required to predict an organism’s phenotype. However, its ability to provide accurate predictions has not yet been demonstrated in large independent studies of specific organisms. In this study, we aimed to develop a genotypic prediction method for antimicrobial susceptibilities. The whole genomes of 501 unrelated Staphylococcus aureus isolates were sequenced, and the assembled genomes were interrogated using BLASTn for a panel of known resistance determinants (chromosomal mutations and genes carried on plasmids). Results were compared with phenotypic susceptibility testing for 12 commonly used antimicrobial agents (penicillin, methicillin, erythromycin, clindamycin, tetracycline, ciprofloxacin, vancomycin, trimethoprim, gentamicin, fusidic acid, rifampin, and mupirocin) performed by the routine clinical laboratory. We investigated discrepancies by repeat susceptibility testing and manual inspection of the sequences and used this information to optimize the resistance determinant panel and BLASTn algorithm. We then tested performance of the optimized tool in an independent validation set of 491 unrelated isolates, with phenotypic results obtained in duplicate by automated broth dilution (BD Phoenix) and disc diffusion. In the validation set, the overall sensitivity and specificity of the genomic prediction method were 0.97 (95% confidence interval [95% CI], 0.95 to 0.98) and 0.99 (95% CI, 0.99 to 1), respectively, compared to standard susceptibility testing methods. The very major error rate was 0.5%, and the major error rate was 0.7%. WGS was as sensitive and specific as routine antimicrobial susceptibility testing methods. WGS is a promising alternative to culture methods for resistance prediction in S. aureus and ultimately other major bacterial pathogens.

Sequentially testing for a gene-drug interaction in a genomewide analysis

Assaying a large number of genetic markers from patients in clinical trials is now possible in order to tailor drugs with respect to efficacy. The statistical methodology for analysing such massive data sets is challenging. The most popular type of statistical analysis is to use a univariate test for each genetic marker, once all the data from a clinical study have been collected. This paper presents a sequential method for conducting an omnibus test for detecting gene-drug interactions across the genome, thus allowing informed decisions at the earliest opportunity and overcoming the multiple testing problems from conducting many univariate tests. We first propose an omnibus test for a fixed sample size. This test is based on combining F-statistics that test for an interaction between treatment and the individual single nucleotide polymorphism (SNP). As SNPs tend to be correlated, we use permutations to calculate a global p-value. We extend our omnibus test to the sequential case. In order to control the type I error rate, we propose a sequential method that uses permutations to obtain the stopping boundaries. The results of a simulation study show that the sequential permutation method is more powerful than alternative sequential methods that control the type I error rate, such as the inverse-normal method. The proposed method is flexible as we do not need to assume a mode of inheritance and can also adjust for confounding factors. An application to real clinical data illustrates that the method is computationally feasible for a large number of SNPs. Copyright (c) 2007 John Wiley & Sons, Ltd.

Changes in in vitro susceptibility of influenza A H3N2 viruses to a neuraminidase inhibitor drug during evolution in the human host

Objectives: Influenza A H3N2 viruses isolated recently have characteristic receptor binding properties that may decrease susceptibility to neuraminidase inhibitor drugs. A panel of clinical isolates and recombinant viruses generated by reverse genetics were characterized and tested for susceptibility to zanamivir. Methods: Plaque reduction assays and neuraminidase enzyme inhibition assays were used to assess susceptibility to zanamivir. Receptor binding properties of the viruses were characterized by differential agglutination of red blood cells (RBCs) from different species. Sequence analysis of the haemagglutinin (HA) and neuraminidase (NA) genes was carried out. Results: Characterization of a panel of H3N2 clinical isolates from 1968 to 2000 showed a gradual decrease in agglutination of chicken and guinea pig RBCs over time, although all isolates could agglutinate turkey RBCs equally. Sequence analysis of the HA and NA genes identified mutations in conserved residues of the HA1 receptor binding site, in particular Leu-226 --> Ile-226/Val-226, and modification of potential glycosylation site motifs. This may be indicative of changes in virus binding to sialic acid (SA) receptors in recent years. Although recent isolates had reduced susceptibility to zanamivir in MDCK cell based plaque reduction assays, no difference was found in an NA enzyme-inhibition assay. Assays with recombinant isogenic viruses showed that the recent HA, but not the NA, conferred reduced susceptibility to zanamivir. Conclusion: This study demonstrates that recent clinical isolates of influenza A H3N2 virus no longer agglutinate chicken RBCs, but despite significant receptor binding changes as a result of changes in HA, there was little variation in sensitivity of the NA to zanamivir.

Proanthocyanidins inhibit Ascaris suum glutathione-S-transferase activity and increase susceptibility of larvae to levamisole and ivermectin in vitro

Proanthocyanidins (PAC) are a class of plant secondary metabolites commonly found in the diet that have shown potential to control gastrointestinal nematode infections. The anti-parasitic mechanism(s) of PAC remain obscure, however the protein-binding properties of PAC suggest that disturbance of key enzyme functions may be a potential mode of action. Glutathione-S-transferases (GSTs) are essential for parasite detoxification and have been investigated as drug and vaccine targets. Here, we show that purified PAC strongly inhibit the activity of both recombinant and native GSTs from the parasitic nematode Ascaris suum. As GSTs are involved in detoxifying xenobiotic substances within the parasite, we hypothesised that this inhibition may render parasites hyper-susceptible to anthelmintic drugs. Migration inhibition assays with A. suum larvae demonstrated that the potency of levamisole (LEV) and ivermectin (IVM) were significantly increased in the presence of PAC purified from pine bark (4.6-fold and 3.2-fold reduction in IC50 value for LEV and IVM, respectively). Synergy analysis revealed that the relationship between PAC and LEV appeared to be synergistic in nature, suggesting a specific enhancement of LEV activity, whilst the relationship between PAC and IVM was additive rather than synergistic, suggesting independent actions. Our results demonstrate that these common dietary compounds may increase the efficacy of synthetic anthelmintic drugs in vitro, and also suggest one possible mechanism for their well-known anti-parasitic activity.