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Anekalla, K.

Publications and source records attributed to Anekalla, K..

2 recordsLinked to original sources

Influenza-induced activation of recruited alveolar macrophages during the early inflammatory phase drives lung injury and lethality

Severe respiratory virus infections initiate a robust host immune response that contributes to disease severity. Immunomodulatory strategies that limit virus-initiated inflammation are of critical importance. In this study, we compared the host response to influenza A virus (IAV) infection in susceptible animals (wild-type, WT) to resilient mice (Vimentin-/- mice). We identified distinct gene expression patterns in recruited monocyte-derived alveolar macrophages (MoAMs) associated with three phases (Infiltrating, Early Inflammatory, Late Inflammatory) that evolve in sequence over the course of IAV infection. We report a core set of pro-inflammatory genes involved in the WT MoAM Early Inflammatory response that is suppressed in Vim-/- MoAMs. Moreover, we identify CEBPB, Jun-AP1, and IRF transcriptions factors as regulators of this attenuated inflammatory response. We performed causal experiments using bone-marrow chimeras to credential that Vim-/- MoAMs with suppressed pro-inflammatory genes confer protection from influenza-induced mortality in WT susceptible mice. Taken together, these data support the notion that vimentin plays a causal role in determining the pro-inflammatory function of recruited MoAMs and drives IAV-induced lung injury.

immunology↗

Aging is associated with a systemic length-driven transcriptome imbalance

Aging manifests itself through a decline in organismal homeostasis and a multitude of cellular and physiological functions1. Efforts to identify a common basis for vertebrate aging face many challenges; for example, while there have been documented changes in the expression of many hundreds of mRNAs, the results across tissues and species have been inconsistent2. We therefore analyzed age-resolved transcriptomic data from 17 mouse organs and 51 human organs using unsupervised machine learning3-5 to identify the architectural and regulatory characteristics most informative on the differential expression of genes with age. We report a hitherto unknown phenomenon, a systemic age-dependent length-driven transcriptome imbalance that for older organisms disrupts the homeostatic balance between short and long transcript molecules for mice, rats, killifishes, and humans. We also demonstrate that in a mouse model of healthy aging, length-driven transcriptome imbalance correlates with changes in expression of splicing factor proline and glutamine rich (Sfpq), which regulates transcriptional elongation according to gene length6. Furthermore, we demonstrate that length-driven transcriptome imbalance can be triggered by environmental hazards and pathogens. Our findings reinforce the picture of aging as a systemic homeostasis breakdown and suggest a promising explanation for why diverse insults affect multiple age-dependent phenotypes in a similar manner.

systems biology↗