Human cytomegalovirus immediate-early 1 protein rewires upstream STAT3 to downstream STAT1 signaling switching an IL6-type to an IFNγ-like response

MN and CP were supported by the Wellcome Trust (www.wellcome.ac.uk) Institutional Strategic Support Fund and CP was supported by the Deutsche Forschungsgemeinschaft (PA 815/2-1; www.dfg.de).The human cytomegalovirus (hCMV) major immediate-early 1 protein (IE1) is best known for activating transcription to facilitate viral replication. Here we present transcriptome data indicating that IE1 is as significant a repressor as it is an activator of host gene expression. Human cells induced to express IE1 exhibit global repression of IL6- and oncostatin M-responsive STAT3 target genes. This repression is followed by STAT1 phosphorylation and activation of STAT1 target genes normally induced by IFNγ. The observed repression and subsequent activation are both mediated through the same region (amino acids 410 to 445) in the C-terminal domain of IE1, and this region serves as a binding site for STAT3. Depletion of STAT3 phenocopies the STAT1-dependent IFNγ-like response to IE1. In contrast, depletion of the IL6 receptor (IL6ST) or the STAT kinase JAK1 prevents this response. Accordingly, treatment with IL6 leads to prolonged STAT1 instead of STAT3 activation in wild-type IE1 expressing cells, but not in cells expressing a mutant protein (IE1dl410-420) deficient for STAT3 binding. A very similar STAT1-directed response to IL6 is also present in cells infected with a wild-type or revertant hCMV, but not an IE1dl410-420 mutant virus, and this response results in restricted viral replication. We conclude that IE1 is sufficient and necessary to rewire upstream IL6-type to downstream IFNγ-like signaling, two pathways linked to opposing actions, resulting in repressed STAT3- and activated STAT1-responsive genes. These findings relate transcriptional repressor and activator functions of IE1 and suggest unexpected outcomes relevant to viral pathogenesis in response to cytokines or growth factors that signal through the IL6ST-JAK1-STAT3 axis in hCMV-infected cells. Our results also reveal that IE1, a protein considered to be a key activator of the hCMV productive cycle, has an unanticipated role in tempering viral replication.Publisher PDFPeer reviewe

ISSN exercise & sport nutrition review: research & recommendations

Sports nutrition is a constantly evolving field with hundreds of research papers published annually. For this reason, keeping up to date with the literature is often difficult. This paper is a five year update of the sports nutrition review article published as the lead paper to launch the JISSN in 2004 and presents a well-referenced overview of the current state of the science related to how to optimize training and athletic performance through nutrition. More specifically, this paper provides an overview of: 1.) The definitional category of ergogenic aids and dietary supplements; 2.) How dietary supplements are legally regulated; 3.) How to evaluate the scientific merit of nutritional supplements; 4.) General nutritional strategies to optimize performance and enhance recovery; and, 5.) An overview of our current understanding of the ergogenic value of nutrition and dietary supplementation in regards to weight gain, weight loss, and performance enhancement. Our hope is that ISSN members and individuals interested in sports nutrition find this review useful in their daily practice and consultation with their clients

Methodological challenges to multivariate syndromic surveillance: a case study using Swiss animal health data

BACKGROUND In an era of ubiquitous electronic collection of animal health data, multivariate surveillance systems (which concurrently monitor several data streams) should have a greater probability of detecting disease events than univariate systems. However, despite their limitations, univariate aberration detection algorithms are used in most active syndromic surveillance (SyS) systems because of their ease of application and interpretation. On the other hand, a stochastic modelling-based approach to multivariate surveillance offers more flexibility, allowing for the retention of historical outbreaks, for overdispersion and for non-stationarity. While such methods are not new, they are yet to be applied to animal health surveillance data. We applied an example of such stochastic model, Held and colleagues' two-component model, to two multivariate animal health datasets from Switzerland. RESULTS In our first application, multivariate time series of the number of laboratories test requests were derived from Swiss animal diagnostic laboratories. We compare the performance of the two-component model to parallel monitoring using an improved Farrington algorithm and found both methods yield a satisfactorily low false alarm rate. However, the calibration test of the two-component model on the one-step ahead predictions proved satisfactory, making such an approach suitable for outbreak prediction. In our second application, the two-component model was applied to the multivariate time series of the number of cattle abortions and the number of test requests for bovine viral diarrhea (a disease that often results in abortions). We found that there is a two days lagged effect from the number of abortions to the number of test requests. We further compared the joint modelling and univariate modelling of the number of laboratory test requests time series. The joint modelling approach showed evidence of superiority in terms of forecasting abilities. CONCLUSIONS Stochastic modelling approaches offer the potential to address more realistic surveillance scenarios through, for example, the inclusion of times series specific parameters, or of covariates known to have an impact on syndrome counts. Nevertheless, many methodological challenges to multivariate surveillance of animal SyS data still remain. Deciding on the amount of corroboration among data streams that is required to escalate into an alert is not a trivial task given the sparse data on the events under consideration (e.g. disease outbreaks)