Project description:Himanshu Manchanda, Nora Seidel, Andi Krumbholz, Andreas Sauerbrei, Michaela Schmidtke & Reinhard Guthke. Within-host influenza dynamics: a small-scale mathematical modeling approach. Biosystems 118 (2014).
The emergence of new influenza viruses like the pandemic H1N1 influenza A virus in 2009 (A(H1N1)pdm09) with unpredictable difficulties in vaccine coverage and established antiviral treatment protocols emphasizes the need of new murine models to prove the activity of novel antiviral compounds in vivo. The aim of the present study was to develop a small-scale mathematical model based on easily attainable experimental data to explain differences in influenza kinetics induced by different virus strains in mice. To develop a three-dimensional ordinary differential equation model of influenza dynamics, the following variables were included: (i) viral pathogenicity (P), (ii) antiviral immune defense (D), and (iii) inflammation due to pro-inflammatory response (I). Influenza virus-induced symptoms (clinical score S) in mice provided the basis for calculations of P and I. Both, mono- and biphasic course of mild to severe influenza induced by three clinical A(H1N1)pdm09 strains and one European swine H1N2 virus were comparatively and quantitatively studied by fitting the mathematical model to the experimental data. The model hypothesizes reasons for mild and severe influenza with mono- as well as biphasic course of disease. According to modeling results, the second peak of the biphasic course of infection is caused by inflammation. The parameters (i) maximum primary pathogenicity, (ii) viral infection rate, and (iii) rate of activation of the immune system represent most important parameters that quantitatively characterize the different pattern of virus-specific influenza kinetics.
Project description:To clarify the underlying mechanism that regulates the response of iron metabolism to influenza A virus infection, we analyzed gene expression profiles in mouse, bone marrow-derived macrophages (BMDMs) infected with H7N9 virus. In addition, We also analysed the chemokine, inflammation, innate-immunity, lipid-metabolism, transcription mRNA level by micrroarray. So, we gain the global transcriptional response in the BMDMs of mice infected with H7N9 virus.
Project description:Engrams are considered to be substrates for memory storage, and the functional dysregulation of the engrams leads to cognition impairment.However, the cellular basis for these maladaptive changes lead to the forgetting of memories remains unclear. Here we found that the expression of autophagy protein 7 (Atg7) mRNA was dramatically upregulated in aged DG engrams, and led to the forgetting of contextual fear memory and the activation of surrounding microglia.To determine mechanism by which autophagy in DG engrams activates the surrounding microglia, mice were co-injected AAV-RAM-Cre either with AAV-Dio-Atg7-Flag or AAV-Dio- EYFP in dorsal dentate gyrus to overexpress ATG7 in the DG memory engrams. Microglia were separated using magnetic-activated cell sorting and subjected to RNA-Seq in dorsal hippocampus .Bioinformatics analysis shown overexpression of Atg7 in dorsal DG memory engrams caused an increase in the expression of Tlr2 in the surrounding microglia.Depletion of Toll-like receptor 2/4 (TLR2/4) in DG microglia prohibited excessive microglial activation and synapse elimination induced by the overexpression of ATG7 in DG engrams, and thus prevented forgetting. Furthermore, the expression of Rac1, a Rho-GTPases which regulates active forgetting in both fly and mice, was upregulated in aged engrams. Optogentic activation of Rac1 in DG engrams promoted the autophagy of the engrams, the activation of microglia, and the forgetting of fear memory. Invention of the Atg7 expression and microglia activation attenuated forgetting induced by activation of Rac1 in DG engrams. Together, our findings revealed autophagy-dependent synapse elimination of DG engrams by microglia as a novel forgetting mechanism.
