RESUMEN
Antiviral immune mediators, including interferons and their downstream effectors, are critical for host defense yet can become detrimental when uncontrolled. Here, we identify a macrophage-mediated anti-inflammatory mechanism that limits type I interferon (IFN-I) responses. Specifically, we found that cellular stress and pathogen recognition induce Oncostatin M (OSM) production by macrophages. OSM-deficient mice succumbed to challenge with influenza or a viral mimic due to heightened IFN-I activation. Macrophage-derived OSM restricted excessive IFN-I production by lung epithelial cells following viral stimulation. Furthermore, reconstitution of OSM in the respiratory tract was sufficient to protect mice lacking macrophage-derived OSM against morbidity, indicating the importance of local OSM production. This work reveals a host strategy to dampen inflammation in the lung through the negative regulation of IFN-I by macrophages.
RESUMEN
Noncoding RNAs are integral to a wide range of biological processes, including translation, gene regulation, host-pathogen interactions and environmental sensing. While genomics is now a mature field, our capacity to identify noncoding RNA elements in bacterial and archaeal genomes is hampered by the difficulty of de novo identification. The emergence of new technologies for characterizing transcriptome outputs, notably RNA-seq, are improving noncoding RNA identification and expression quantification. However, a major challenge is to robustly distinguish functional outputs from transcriptional noise. To establish whether annotation of existing transcriptome data has effectively captured all functional outputs, we analysed over 400 publicly available RNA-seq datasets spanning 37 different Archaea and Bacteria. Using comparative tools, we identify close to a thousand highly-expressed candidate noncoding RNAs. However, our analyses reveal that capacity to identify noncoding RNA outputs is strongly dependent on phylogenetic sampling. Surprisingly, and in stark contrast to protein-coding genes, the phylogenetic window for effective use of comparative methods is perversely narrow: aggregating public datasets only produced one phylogenetic cluster where these tools could be used to robustly separate unannotated noncoding RNAs from a null hypothesis of transcriptional noise. Our results show that for the full potential of transcriptomics data to be realized, a change in experimental design is paramount: effective transcriptomics requires phylogeny-aware sampling.