Capturing the cloud of diversity reveals complexity and heterogeneity of MRSA carriage, infection and transmission.

Genome sequencing is revolutionizing clinical microbiology and our understanding of infectious diseases. Previous studies have largely relied on the sequencing of a single isolate from each individual. However, it is not clear what degree of bacterial diversity exists within, and is transmitted between individuals. Understanding this 'cloud of diversity' is key to accurate identification of transmission pathways. Here, we report the deep sequencing of methicillin-resistant Staphylococcus aureus among staff and animal patients involved in a transmission network at a veterinary hospital. We demonstrate considerable within-host diversity and that within-host diversity may rise and fall over time. Isolates from invasive disease contained multiple mutations in the same genes, including inactivation of a global regulator of virulence and changes in phage copy number. This study highlights the need for sequencing of multiple isolates from individuals to gain an accurate picture of transmission networks and to further understand the basis of pathogenesis.Thanks to Dr Alex O’Neill, University of Leeds and Dr Matthew Ellington, Public Health England for provision of RN4220 and RN4200mutS. We thank the core sequencing and informatics team at the Wellcome Trust Sanger Institute for sequencing of the isolates described in this study. This work was supported by a Medical Research Council Partnership grant (G1001787/1) held between the Department of Veterinary Medicine, University of Cambridge (M.A.H.), the School of Clinical Medicine, University of Cambridge (S.J.P.), the Moredun Research Institute, and the Wellcome Trust Sanger Institute (J.P. and S.J.P). S.J.P. receives support from the NIHR Cambridge Biomedical Research Centre. M.T.G.H., S.R.H. and J.P. were funded by Wellcome Trust grant no. 098051. G.G.R.M. was funded by an MRC studentship.This is the final version of the article. It first appeared from Nature Publishing Group via http://dx.doi.org/10.1038/ncomms756

Interleukin-32 Promotes Osteoclast Differentiation but Not Osteoclast Activation

Background: Interleukin-32 (IL-32) is a newly described cytokine produced after stimulation by IL-2 or IL-18 and IFN-γ. IL-32 has the typical properties of a pro-inflammatory mediator and although its role in rheumatoid arthritis has been recently reported its effect on the osteoclastogenesis process remains unclear. Methodology/principal findings: In the present study, we have shown that IL-32 was a potent modulator of osteoclastogenesis in vitro, whereby it promoted the differentiation of osteoclast precursors into TRAcP+ VNR+ multinucleated cells expressing specific osteoclast markers (up-regulation of NFATc1, OSCAR, Cathepsin K), but it was incapable of inducing the maturation of these multinucleated cells into bone-resorbing cells. The lack of bone resorption in IL-32-treated cultures could in part be explain by the lack of F-actin ring formation by the multinucleated cells generated. Moreover, when IL-32 was added to PBMC cultures maintained with soluble RANKL, although the number of newly generated osteoclast was increased, a significant decrease of the percentage of lacunar resorption was evident suggesting a possible inhibitory effect of this cytokine on osteoclast activation. To determine the mechanism by which IL-32 induces such response, we sought to determine the intracellular pathways activated and the release of soluble mediators in response to IL-32. Our results indicated that compared to RANKL, IL-32 induced a massive activation of ERK1/2 and Akt. Moreover, IL-32 was also capable of stimulating the release of IL-4 and IFN-γ, two known inhibitors of osteoclast formation and activation. Conclusions/significance: This is the first in vitro report on the complex role of IL-32 on osteoclast precursors. Further clarification on the exact role of IL-32 in vivo is required prior to the development of any potential therapeutic approach

Mapping the Environmental Fitness Landscape of a Synthetic Gene Circuit

Gene expression actualizes the organismal phenotypes encoded within the genome in an environment-dependent manner. Among all encoded phenotypes, cell population growth rate (fitness) is perhaps the most important, since it determines how well-adapted a genotype is in various environments. Traditional biological measurement techniques have revealed the connection between the environment and fitness based on the gene expression mean. Yet, recently it became clear that cells with identical genomes exposed to the same environment can differ dramatically from the population average in their gene expression and division rate (individual fitness). For cell populations with bimodal gene expression, this difference is particularly pronounced, and may involve stochastic transitions between two cellular states that form distinct sub-populations. Currently it remains unclear how a cell population's growth rate and its subpopulation fractions emerge from the molecular-level kinetics of gene networks and the division rates of single cells. To address this question we developed and quantitatively characterized an inducible, bistable synthetic gene circuit controlling the expression of a bifunctional antibiotic resistance gene in Saccharomyces cerevisiae. Following fitness and fluorescence measurements in two distinct environments (inducer alone and antibiotic alone), we applied a computational approach to predict cell population fitness and subpopulation fractions in the combination of these environments based on stochastic cellular movement in gene expression space and fitness space. We found that knowing the fitness and nongenetic (cellular) memory associated with specific gene expression states were necessary for predicting the overall fitness of cell populations in combined environments. We validated these predictions experimentally and identified environmental conditions that defined a “sweet spot” of drug resistance. These findings may provide a roadmap for connecting the molecular-level kinetics of gene networks to cell population fitness in well-defined environments, and may have important implications for phenotypic variability of drug resistance in natural settings