Tularemia is caused by the category A biodefense agent Francisella tularensis. This bacterium is associated with diverse environments and a plethora of arthropod and mammalian hosts. How F. tularensis adapts to these different conditions, particularly the eukaryotic intracellular environment in which it replicates, is poorly understood. Here, we demonstrate that the polyamines spermine and spermidine are environmental signals that alter bacterial stimulation of host cells. Genomewide analysis showed that F. tularensis LVS undergoes considerable changes in gene expression in response to spermine. Unexpectedly, analysis of gene expression showed that multiple members of two classes of Francisella insertion sequence (IS) elements, ISFtu1 and ISFtu2, and the genes adjacent to these elements were induced by spermine. Spermine was sufficient to activate transcription of these IS elements and of nearby genes in broth culture and in macrophages. Importantly, the virulent strain of F. tularensis, Schu S4, exhibited similar phenotypes of cytokine induction and gene regulation in response to spermine. Distinctions in gene expression changes between Schu S4 and LVS at one orthologous locus, however, correlated with differences in IS element location. Our results indicate that spermine and spermidine are novel triggers to alert F. tularensis of its eukaryotic host environment. The results reported here also identify an unexpected mechanism of gene regulation controlled by a spermine-responsive promoter contained within IS elements. Different arrangements of these mobile genetic elements among Francisella strains may contribute to virulence by conveying new expression patterns for genes from different strains.
Wireless sensor networks link the physical and digital worlds enabling both surveillance as well as scientific exploration. In both cases, on-line detection of interesting events can be accomplished with continuous queries (CQs) in a Data Stream Management System (DSMS). However, the qualityof-service requirements of detecting these events are different for different monitoring applications. The CQs for detecting anomalous events (e.g., fire, flood) have stricter response time requirements over CQs which are for logging and keeping statistical information of physical phenomena. In this work, we are proposing the Continuous Query Class (CQC) scheduler, a new scheduling policy which employs two-level scheduling that is able to handle different ranks of CQ classes. It provides the lowest response times for classes of critical CQs, while at the same time keeping reasonable response times for the other classes down the rank. We have implemented CQC in the AQSIOS prototype DSMS and evaluated it against existing scheduling policies under different workloads.
Amazon, Google, and IBM now sell cloud computing services. We consider the setting of a for-profit business selling data stream monitoring/management services and we investigate auction-based mechanisms for admission control of continuous queries. When submitting a query, each user also submits a bid of how much she will commit to paying for that query to run. The admission control auction mechanism then determines which queries to admit, and how much to charge each user in a way that maximizes system revenue while incentivizing users to use the system honestly. Specifically, we require that each user maximizes her payoff by bidding her true value of having her query run. We further consider the requirement that the mechanism be sybil-immune, that is, that no user can increase her payoff by submitting queries that she does not value. The main combinatorial challenges come from the difficulty of effectively taking advantage of the shared processing between queries. We design several payment mechanisms and experimentally evaluate them. We describe the provable game theoretic characteristics of each mechanism alongside its performance with respect to maximizing profit, total user payoff, and rate of admission, showing what tradeoffs may be in store for implementers.
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