Search bioRxiv⌕ Search

Biology subjects

Stegemann-Koniszewski, S.

Publications and source records attributed to Stegemann-Koniszewski, S..

2 recordsLinked to original sources

Epigenetic changes and serotype-specific interferon-responses of lung epithelial cells in late post-influenza pneumococcal pneumonia

Pneumococcal infection following influenza A virus (IAV) pneumonia is a synergistic complication with high mortality. IAV modulates host antibacterial responses and invasiveness of pneumococcal serotypes and is an important pathogenic factor 2. Yet, serotype-specifc immediate-early responses of the IAV-perturbed alveolar epithelium have not been adressed. We analyzed gene transcription in alveolar type II epithelial cells (AECII) from mice infected with IAV and/or one of three S. pneumoniae (S.pn.) serotypes of varying invasiveness (4 > 7F > 19F). IAV, 14 days post infection, rendered the lung susceptible to invasive S.pn. infection with serotype 4 and the mildly invasive 7F but not 19F. Only 7F secondary infection induced exacerbated cytokine/chemokine responses. IAV/7F infection induced superior protein expression of type I and II interferons, exceeding that in IAV/serotype 4 infection. Inference of a scale-free-like ARACNE gene co-expression network revealed interferon-response network modules. Network-mapping unfolded S.pn. serotype-specific transcriptional network responses/usage. Secondary S.pn. infection abrogated the IAV-induced pneumocyte proliferative configuration and IAV infection rendered the transcriptional response to 7F comparable to that of serotype 4. This related to network genes correlating with the expression of two master regulators of interferon responses: Irf7 and Stat1. Epigenetic ATAC-seq analysis of AECII in resolved IAV infection identified enhanced expression of ARACNE network genes Hist1h2bf, Igtp, Mki67, Rasl10b, H2-Q6 and H2-Q7 to be associated with increased chromatin accessability at promoter regions. We show that AECII retain a sustained IAV-associated transcriptional configuration with epigenetic involvement that serotype-specifically affects proliferation and intensifies the AECII transcriptional response, mainly to interferons, in S.pn. infection.

immunology↗

Tracking influenza a virus infection in the lung from hematological data with machine learning

The tracking of pathogen burden and host responses with minimal-invasive methods during respiratory infections is central for monitoring disease development and guiding treatment decisions. Utilizing a standardized murine model of respiratory Influenza A virus (IAV) infection, we developed and tested different supervised machine learning models to predict viral burden and immune response markers, i.e. cytokines and leukocytes in the lung, from hematological data. We performed independently in vivo infection experiments to acquire extensive data for training and testing purposes of the models. We show here that lung viral load, neutrophil counts, cytokines like IFN-{gamma} and IL-6, and other lung infection markers can be predicted from hematological data. Furthermore, feature analysis of the models shows that blood granulocytes and platelets play a crucial role in prediction and are highly involved in the immune response against IAV. The proposed in silico tools pave the path towards improved tracking and monitoring of influenza infections and possibly other respiratory infections based on minimal-invasively obtained hematological parameters.

microbiology↗