Back

The role of ER exit sites in maintaining P-body organization and transmitting ER stress response during Drosophila melanogaster oogenesis

Milano, S. N.; Bayer, L. V.; Ko, J. J.; Casella, C. E.; Bratu, D. P.

2024-07-05 cell biology Community evaluation
10.1101/2024.07.03.601952 bioRxiv
Show abstract

Processing bodies (P-bodies) are cytoplasmic membrane-less organelles which host multiple mRNA processing events. While the fundamental principles of P-body organization are beginning to be elucidated in vitro, a nuanced understanding of how their assembly is regulated in vivo remains elusive. Here, we investigate the potential link between ER exit sites and P-bodies in Drosophila melanogaster egg chambers. Employing a combination of live and super-resolution imaging, we found that P-bodies associated with ER exit sites are larger and less mobile than cytoplasmic P-bodies, indicating that they constitute a distinct class of P-bodies which are more mature than their cytoplasmic counterparts. Moreover, we demonstrate that altering the composition of ER exit sites has differential effects on core P-body proteins (Me31B, Cup, and Trailer Hitch) suggesting a potential role for ER exit sites in P-body organization. We further show that in the absence of ER exit sites, P-body integrity is compromised and the stability and translational repression efficiency of the maternal mRNA, oskar, are reduced. Finally, we show that ER stress is communicated to P-bodies via ER exit sites, highlighting the pivotal role of ER exit sites as a bridge between membrane-bound and membrane-less organelles in ER stress response. Together, our data unveils the significance of ER exit sites not only in governing P-body organization, but also in facilitating inter-organellar communication during stress, potentially bearing implications for a variety of disease pathologies.

Matching journals

The top 7 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.