Back

Dysregulated neuroimmune interactions and sustained type I interferon signaling after human immunodeficiency virus type 1 infection of human iPSC derived microglia and cerebral organoids

Boreland, A. J.; Stillitano, A. C.; Lin, H.; Abbo, Y.; Hart, R. P.; Jiang, P.; Pang, Z. P.; Rabson, A. B.

2023-10-25 neuroscience
10.1101/2023.10.25.563950 bioRxiv
Show abstract

Human immunodeficiency virus type-1 (HIV-1) associated neurocognitive disorder (HAND) affects up to half of HIV-1 positive patients with long term neurological consequences, including dementia. There are no effective therapeutics for HAND because the pathophysiology of HIV-1 induced glial and neuronal functional deficits in humans remains enigmatic. To bridge this knowledge gap, we established a model simulating HIV-1 infection in the central nervous system using human induced pluripotent stem cell (iPSC) derived microglia combined with sliced neocortical organoids. Upon incubation with two replication-competent macrophage-tropic HIV-1 strains (JRFL and YU2), we observed that microglia not only became productively infected but also exhibited inflammatory activation. RNA sequencing revealed a significant and sustained activation of type I interferon signaling pathways. Incorporating microglia into sliced neocortical organoids extended the effects of aberrant type I interferon signaling in a human neural context. Collectively, our results illuminate the role of persistent type I interferon signaling in HIV-1 infected microglial in a human neural model, suggesting its potential significance in the pathogenesis of HAND. Highlights of the workO_LIHIV-1 productively infects iPSC-derived microglia and triggers inflammatory activation. C_LIO_LIHIV-1 infection of microglia results in sustained type I interferon signaling. C_LIO_LIMicroglia infected by HIV-1 incorporate into sliced neocortical organoids with persistent type I interferon signaling and disease risk gene expression. C_LI

Matching journals

The top 5 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.