Project description:Transcriptomic comparison of 5 cell types during lethal and non-lethal influenza infection and further use of these signatures in a top-down systems analysis investigating the relative pathogenic contributions of direct viral damage to lung epithelium vs. dysregulated immunity during lethal influenza infection. For acutely lethal influenza infections, the relative pathogenic contributions of direct viral damage to lung epithelium vs. dysregulated immunity remain unresolved. Here, we take a top-down systems approach to this question. Multigene transcriptional signatures from infected lungs suggested that elevated activation of inflammatory signaling networks distinguished lethal from sublethal infections. Flow cytometry and gene expression analysis involving isolated cell subpopulations from infected lungs showed that neutrophil influx largely accounted for the predictive transcriptional signature. Automated imaging analysis together with these gene expression and flow data identified a chemokine-driven feed-forward circuit involving pro-inflammatory neutrophils potently driven by poorly contained lethal viruses. Consistent with these data, attenuation but not ablation of the neutrophil-driven response increased survival without changing viral spread. These findings establish the primacy of damaging innate inflammation in at least some forms of influenza-induced lethality and provide a roadmap for the systematic dissection of infection-associated pathology.
Project description:Identification of biological processes that distinguish lethal from non-lethal influenza infection and further use of these signatures in a top-down systems analysis investigating the relative pathogenic contributions of direct viral damage to lung epithelium vs. dysregulated immunity to during lethal influenza infection. For acutely lethal influenza infections, the relative pathogenic contributions of direct viral damage to lung epithelium vs. dysregulated immunity remain unresolved. Here, we take a top-down systems approach to this question. Multigene transcriptional signatures from infected lungs suggested that elevated activation of inflammatory signaling networks distinguished lethal from sublethal infections. Flow cytometry and gene expression analysis involving isolated cell subpopulations from infected lungs showed that neutrophil influx largely accounted for the predictive transcriptional signature. Automated imaging analysis together with these gene expression and flow data identified a chemokine-driven feed-forward circuit involving pro-inflammatory neutrophils potently driven by poorly contained lethal viruses. Consistent with these data, attenuation but not ablation of the neutrophil-driven response increased survival without changing viral spread. These findings establish the primacy of damaging innate inflammation in at least some forms of influenza-induced lethality and provide a roadmap for the systematic dissection of infection-associated pathology.
Project description:Transcriptomic comparison of 5 cell types during lethal and non-lethal influenza infection and further use of these signatures in a top-down systems analysis investigating the relative pathogenic contributions of direct viral damage to lung epithelium vs. dysregulated immunity during lethal influenza infection. For acutely lethal influenza infections, the relative pathogenic contributions of direct viral damage to lung epithelium vs. dysregulated immunity remain unresolved. Here, we take a top-down systems approach to this question. Multigene transcriptional signatures from infected lungs suggested that elevated activation of inflammatory signaling networks distinguished lethal from sublethal infections. Flow cytometry and gene expression analysis involving isolated cell subpopulations from infected lungs showed that neutrophil influx largely accounted for the predictive transcriptional signature. Automated imaging analysis together with these gene expression and flow data identified a chemokine-driven feed-forward circuit involving pro-inflammatory neutrophils potently driven by poorly contained lethal viruses. Consistent with these data, attenuation but not ablation of the neutrophil-driven response increased survival without changing viral spread. These findings establish the primacy of damaging innate inflammation in at least some forms of influenza-induced lethality and provide a roadmap for the systematic dissection of infection-associated pathology. Multiple mice were either sham infected, infected with the seasonal H1N1 influenza A virus TX91 (10^6PFU), or infected with various sublethal or lethal doses of the mouse pathogenic H1N1 strain PR8. Lung tissues were collected at 48h or 72h post infection. 5 different cell types were purified by flow sorting from lungs of individual animals and then processed to yield total RNA that was used for microarray analysis. The dataset contains 75 microarrays covering 25 experimental conditions with 3 biological replicates. This dataset is linked to a dataset containing 138 microarrays of whole lungs covering 20 experimental conditions.
Project description:Identification of biological processes that distinguish lethal from non-lethal influenza infection and further use of these signatures in a top-down systems analysis investigating the relative pathogenic contributions of direct viral damage to lung epithelium vs. dysregulated immunity to during lethal influenza infection. For acutely lethal influenza infections, the relative pathogenic contributions of direct viral damage to lung epithelium vs. dysregulated immunity remain unresolved. Here, we take a top-down systems approach to this question. Multigene transcriptional signatures from infected lungs suggested that elevated activation of inflammatory signaling networks distinguished lethal from sublethal infections. Flow cytometry and gene expression analysis involving isolated cell subpopulations from infected lungs showed that neutrophil influx largely accounted for the predictive transcriptional signature. Automated imaging analysis together with these gene expression and flow data identified a chemokine-driven feed-forward circuit involving pro-inflammatory neutrophils potently driven by poorly contained lethal viruses. Consistent with these data, attenuation but not ablation of the neutrophil-driven response increased survival without changing viral spread. These findings establish the primacy of damaging innate inflammation in at least some forms of influenza-induced lethality and provide a roadmap for the systematic dissection of infection-associated pathology. Multiple mice were either sham infected, infected with the seasonal H1N1 influenza A virus TX91 (10^6PFU), or infected with various sublethal or lethal doses of the mouse pathogenic H1N1 strain PR8. Lung tissues were collected at various time points (24h, 48h, 72h and 240h post infection) and processed to yield whole lung RNA that was used for microarray analysis. The dataset contains 138 microarrays covering 20 experimental conditions with 7 biological replicates each. As an exception, the alternative non-infectious control condition (Alum treatment) contains 5 biological replicates. This dataset is linked to a dataset comparing the transcriptomes of 5 different cell types isolated from individual lungs of influenza A-infected or control animals (contains 75 microarrays covering 25 experimental conditions).
Project description:Maintaining an appropriate balance between excitation and inhibition is critical for information processing in cortical neurons. It is known that cortical neurons receive widely disparate levels of excitation. To ensure efficient coding, they are capable of cell-autonomously adjusting the inhibition they receive to the individual levels of excitatory input, but the underlying mechanisms are not understood.
The article associated with this data shows that Ste20-like kinase (SLK) in cortical neurons mediates cell-autonomous regulation of excitation-inhibition balance in the thalamocortical feed-forward circuit, but not in the feed-back circuit. The parallel reaction monitoring data here supports the link between activity, SLK phosphorylation and function.
Project description:Prior to generation of microarray data for a Top-down Systems analysis of influenza A infection, we evaluated the degree and origin of technical variation in gene expression microarray data from mouse lungs and compared this to inter-animal variation. Technical variation in these microarray data in the context of inter-animal variation supported a choice of biological rather than technical replicates.
Project description:Induction of vast transcriptional programs is a central event of innate host responses to viral infections. Here we report a unique transcriptional program with potent antiviral activity, driven by E74-like ETS transcription factor 1 (ELF1). Using high-content microscopy to quantify viral infection over time, we found that ELF1 inhibits eight diverse RNA and DNA viruses uniquely at multi-cycle replication. Elf1 deficiency results in enhanced susceptibility to influenza A virus infections in mice. ELF1 does not feed-forward to induce interferons, and ELF1’s antiviral effect is not abolished by the absence of STAT1 or by inhibition of JAK phosphorylation. Accordingly, comparative expression analyses by RNAseq revealed that the ELF1 transcriptional program is distinct from interferon signatures. Thus, ELF1 provides an additional layer of the innate host response, independent from the action of type I interferons.
Project description:Systems vaccinology has emerged as an interdisciplinary field that combines systems wide measurements and network and predictive modeling applied to vaccinology. Here we used the systems vaccinology approach to study the molecular mechanisms underlying the innate responses to the trivalent inactivated influenza (TIV) and live attenuated influenza (LAIV) vaccination in humans, and to identify early gene signatures that predict the magnitude of the antibody responses to influenza vaccination.
Project description:Systems vaccinology has emerged as an interdisciplinary field that combines systems wide measurements and network and predictive modeling applied to vaccinology. Here we used the systems vaccinology approach to study the molecular mechanisms underlying the innate responses to the trivalent inactivated influenza (TIV) and live attenuated influenza (LAIV) vaccination in humans, and to identify early gene signatures that predict the magnitude of the antibody responses to influenza vaccination.
Project description:Systems vaccinology has emerged as an interdisciplinary field that combines systems wide measurements and network and predictive modeling applied to vaccinology. Here we used the systems vaccinology approach to study the molecular mechanisms underlying the innate responses to the trivalent inactivated influenza (TIV) and live attenuated influenza (LAIV) vaccination in humans, and to identify early gene signatures that predict the magnitude of the antibody responses to influenza vaccination.