Latent herpesvirus infection arms NK cells
ABSTRACT Natural killer (NK) cells were identified by their ability to kill target cells without previous sensitization. However, without an antecedent "arming" event, NK cells can recognize, but are not equipped to kill, target cells. How NK cells become armed in vivo in healthy hosts is unclear. Because latent herpesviruses are highly prevalent and alter multiple aspects of host immunity, we hypothesized that latent herpesvirus infection would arm NK cells. Here we show that NK cells from mice latently infected with Murid herpesvirus 4 (MuHV-4) were armed as evidenced by increased granzyme B protein expression, cytotoxicity, and interferon-gamma production. NK-cell arming occurred rapidly in the latently infected host and did not require acute viral infection. Furthermore, NK cells armed by latent infection protected the host against a lethal lymphoma challenge. Thus, the immune environment created by latent herpesvirus infection provides a mechanism whereby host NK-cell function is enhanced in vivo.
- SourceAvailable from: Amy Pedersen
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- "Either this immunomodulation or latency-associated innate immune activation, as shown for MuHV-4 in laboratory mice (Barton et al., 2007), could underlie the survival cost observed here. For example, although a state of heightened immune activation has been shown to protect against bacterial challenge and lethal lymphoma in laboratory mice (Barton et al., 2007; White et al., 2010), it could be costly in the wild. Immune activation may reduce resources available for other important physiological functions or cause immunopathology (Eraud et al., 2005; Bertrand et al., 2006; Hanssen, 2006). "
ABSTRACT: Rodent gammaherpesviruses have become important models for understanding human herpesvirus diseases. In particular, interactions between murid herpesvirus 4 and Mus musculus (a non-natural host species) have been extensively studied under controlled laboratory conditions. However, several fundamental aspects of murine gammaherpesvirus biology are not well understood, including how these viruses are transmitted from host to host, and their impacts on host fitness under natural conditions. Here, we investigate the epidemiology of a gammaherpesvirus in free-living wood mice (Apodemus sylvaticus) and bank voles (Myodes glareolus) in a 2-year longitudinal study. Wood mouse herpesvirus (WMHV) was the only herpesvirus detected and occurred frequently in wood mice and also less commonly in bank voles. Strikingly, WMHV infection probability was highest in reproductively active, heavy male mice. Infection risk also showed a repeatable seasonal pattern, peaking in spring and declining through the summer. We show that this seasonal decline can be at least partly attributed to reduced recapture of WMHV-infected adults. These results suggest that male reproductive behaviours could provide an important natural route of transmission for these viruses. They also suggest that gammaherpesvirus infection may have significant detrimental effects in wild hosts, questioning the view that these viruses have limited impacts in natural, co-evolved host species.Journal of General Virology 08/2012; 93(Pt 11):2447-56. DOI:10.1099/vir.0.044826-0 · 3.53 Impact Factor
- "EBV is able to reroute the TNF receptor family signaling pathway (Izumi and Kieff, 1997; Le Clorennec et al., 2008; Liebowitz, 1998; Mosialos et al., 1995). Such interactions favor EBV persistence, yet EBV latency may also provide mutualistic benefit to its hosts as an immune adjuvant (White et al., 2010), protecting against lethal Listeria monocytogenes and Yersinia pestis infections (Barton et al., 2007). Over a host's lifetime, incompletely characterized stimuli occasionally induce EBV to emerge from latency and initiate a lytic state via sequential expression of genes responsible for replication and whole virion assembly. "
Article: Microbiome and Malignancy[Show abstract] [Hide abstract]
ABSTRACT: Current knowledge is insufficient to explain why only a proportion of individuals exposed to environmental carcinogens or carrying a genetic predisposition to cancer develop disease. Clearly, other factors must be important, and one such element that has recently received attention is the human microbiome, the residential microbes including Bacteria, Archaea, Eukaryotes, and viruses that colonize humans. Here, we review principles and paradigms of microbiome-related malignancy, as illustrated by three specific microbial-host interactions. We review the effects of the microbiota on local and adjacent neoplasia, present the estrobolome model of distant effects, and discuss the complex interactions with a latent virus leading to malignancy. These are separate facets of a complex biology interfacing all the microbial species we harbor from birth onward toward early reproductive success and eventual senescence.Cell host & microbe 10/2011; 10(4):324-35. DOI:10.1016/j.chom.2011.10.003 · 12.19 Impact Factor
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ABSTRACT: A novel approach called generalized adaptive wavelet neural network based on resemblance coefficient (GAWNN-RC) is proposed to extract the most discriminatory information from radar emitter signals and to recognize different radar emitter signals with different intra-pulse modulation laws In this work. Because a weighted linear combination of dilated and translated replica of a mother wavelet can approximate a radar emitter signal in frequency domain and the weights, dilation and translation parameters can be estimated adaptively to minimize an approximation error in a least mean square sense, generalized adaptive wavelets (GAW) can be used to extract the most important features of radar emitter signals. Aiming at the characteristics of radar emitter signals, GAW is introduced to extract features for the first time. But there are three problems in GAW representation: (1) it is difficult to obtain the globally optimal solution using gradient descent algorithm (GDA) because GDA is very sensitive to initial values and drops into sub-optimum easily; (2) there are many difficulties in classifier design because the dimension of feature vector is too large; (3) multiple solutions exist in GAW representation, which is not considered in existing methods. So quantum evolutionary algorithm (QEA) and resemblance coefficient method are proposed to solve the problems effectively. Moreover, QEA and neural network (NN) are combined to design classifiers. Finally, 6 typical radar emitter signals are chosen to make the experiment of feature extraction and recognition. Experimental results show that high accurate recognition rate can be achieved and unknown radar emitter signals are also distinguished accurately, which indicates that the introduced approach is feasible and effective.Intelligent Control, 2004. Proceedings of the 2004 IEEE International Symposium on; 10/2004