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ABSTRACT The tracking of pathogen burden and host responses with minimally 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 of the models. We show here that lung viral load, neutrophil counts, cytokines (such as gamma interferon [IFN-γ] and interleukin 6 [IL-6]), and other lung infection markers can be predicted from hematological data. Furthermore, feature analysis of the models showed 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 toward improved tracking and monitoring of influenza virus infections and possibly other respiratory infections based on minimally invasively obtained hematological parameters. IMPORTANCE During the course of respiratory infections such as influenza, we do have a very limited view of immunological indicators to objectively and quantitatively evaluate the outcome of a host. Methods for monitoring immunological markers in a host’s lungs are invasive and expensive, and some of them are not feasible to perform. Using machine learning algorithms, we show for the first time that minimally invasively acquired hematological parameters can be used to infer lung viral burden, leukocytes, and cytokines following influenza virus infection in mice. The potential of the framework proposed here consists of a new qualitative vision of the disease processes in the lung compartment as a noninvasive tool.

ABSTRACT Influenza A virus (IAV) periodically causes substantial morbidity and mortality in the human population. In the lower lung, the primary targets for IAV replication are type II alveolar epithelial cells (AECII), which are increasingly recognized for their immunological potential. So far, little is known about their reaction to IAV and their contribution to respiratory antiviral immunity in vivo. Therefore, we characterized the AECII response during early IAV infection by analyzing transcriptional regulation in cells sorted from the lungs of infected mice. We detected rapid and extensive regulation of gene expression in AECII following in vivo IAV infection. The comparison to transcriptional regulation in lung tissue revealed a strong contribution of AECII to the respiratory response. IAV infection triggered the expression of a plethora of antiviral factors and immune mediators in AECII with a high prevalence for interferon-stimulated genes. Functional pathway analyses revealed high activity in pathogen recognition, immune cell recruitment, and antigen presentation. Ultimately, our analyses of transcriptional regulation in AECII and lung tissue as well as interferon I/III levels and cell recruitment indicated AECII to integrate signals provided by direct pathogen recognition and surrounding cells. Ex vivo analysis of AECII proved a powerful tool to increase our understanding of their role in respiratory immune responses, and our results clearly show that AECII need to be considered a part of the surveillance and effector system of the lower respiratory tract. IMPORTANCE In order to confront the health hazard posed by IAV, we need to complete our understanding of its pathogenesis. AECII are primary targets for IAV replication in the lung, and while we are beginning to understand their importance for respiratory immunity, the in vivo AECII response during IAV infection has not been analyzed. In contrast to studies addressing the response of AECII infected with IAV ex vivo, we have performed detailed gene transcriptional profiling of AECII isolated from the lungs of infected mice. Thereby, we have identified an exceptionally rapid and versatile response to IAV infection that is shaped by pathogen-derived as well as microenvironment-derived signals and aims at the induction of antiviral measures and the recruitment and activation of immune cells. In conclusion, our study presents AECII as active players in antiviral defense in vivo that need to be considered part of the sentinel and effector immune system of the lung.