Boyaka, P. N. | bioRxiv Science

bioRxiv2025

AI-based decoding of long covid cognitive impairments in mice using automated behavioral system and comparative transcriptomic analysis

Long COVID (LC) following SARS-CoV-2 infection affects millions of individuals world-wide and manifests with a variety of symptoms including cognitive dysfunction also known as "brain fog". This is characterized by difficulties in executive functions, planning, decision-making, working memory, impairments in complex attention, loss of ability to learn new skills and perform sophisticated brain tasks. No effective treatment options currently exist for LC-related cognitive dysfunction. Here, we use the IntelliCage, which is an automated tracking system of cognitive functions, following SARS-CoV-2 infection in mice, measuring the ability of each mouse within a group to perform tasks that mimic complex human behaviors, such as planning, decision-making, cognitive flexibility, and working memory. Artificial intelligence and machine learning analyses of the tracking data classified LC mice into distinct behavioral categories from non-infected control mice, permitting precise identification and quantification of complex cognitive dysfunction in a controlled, replicable manner. Importantly, we find that brains from LC mice with cognitive dysfunction exhibit transcriptomic alterations similar to those observed in humans suffering from LC-related cognitive impairments, including altered expression of genes involved in learning, executive functions, synaptic functions, neurotransmitters and memory. Together, our findings establish a validated murine model and an automated unbiased approach to study LC-related cognitive dysfunction for the first time, and providing a valuable tool for screening potential treatments and therapeutic interventions.

neuroscience↗

bioRxiv2018

Is IκBζ constitutively expressed in mammalian airway epithelium?

I{kappa}B{zeta} is a transcriptional factor induced primarily in immune cells upon Toll-like receptor (TLR) activation that drives important cytokine responses. Recent studies have demonstrated constitutive I{kappa}B{zeta} expression in the epithelial cells of mouse skin and eyes, possibly reflecting the activation of TLRs by pathogen-associated molecular patterns (PAMPs). In this context, another mucosal surface, the lung epithelium, may not be as actively exposed to the external environment as the skin and the conjunctiva, especially since the lower lung airways are typically conceived to be sterile. Whether I{kappa}B{zeta} expression in the lungs is constitutive or induced remains largely unexplored. This is especially important since I{kappa}B{zeta} has been shown to promote the expression of protective cytokine and antimicrobial peptide responses, supporting a role for I{kappa}B{zeta} in lung host defense. We hence evaluated I{kappa}B{zeta} expression in airway epithelia of both humans and mice using immunostaining with antiserum raised against recombinant I{kappa}B{zeta} in our laboratory. We observed positive signal in the nuclei of ciliated epithelial cells lining the central airways. Airway cells of gnotobiotic mice also stained positive, suggesting that I{kappa}B{zeta} expression does not require induction by bacterial PAMPs. Unexpectedly, we also observed staining in the lung epithelia of I{kappa}B{zeta} knockout mice, indicating possible false positive signals from our immunohistochemistry experiments. In this context, 2D gel analysis followed by mass spectrometry revealed that our I{kappa}B{zeta} antiserum also detected a nuclear protein lamin B1. Nevertheless, immunoblotting tissue homogenates from gnotobiotic mouse lungs and primary human airway epithelial cells showed the appropriate 86 kDa band for I{kappa}B{zeta}. Together, these results demonstrate constitutive I{kappa}B{zeta} expression in airway epithelium, suggesting that lung epithelial cells may depend upon I{kappa}B{zeta} expression for airway protection.

immunology↗