Back

LetA defines a structurally distinct transporter family involved in lipid trafficking

Santarossa, C. C.; Li, Y.; Yousef, S.; Hasdemir, H. S.; Rodriguez, C. C.; Haase, M. B.; Baek, M.; Coudray, N.; Pavek, J. G.; Focke, K. N.; Silverberg, A. L.; Bautista, C.; Yeh, J.; Marty, M.; Baker, D.; Tajkhorshid, E.; Ekiert, D. C.; Bhabha, G.

2025-03-22 biophysics
10.1101/2025.03.21.644421 bioRxiv
Show abstract

Membrane transport proteins translocate diverse cargos, ranging from small sugars to entire proteins, across cellular membranes. A few structurally distinct protein families have been described that account for most of the known membrane transport processes. However, many membrane proteins with predicted transporter functions remain uncharacterized. We determined the structure of E. coli LetAB, a phospholipid transporter involved in outer membrane integrity, and found that LetA adopts a distinct architecture that is structurally and evolutionarily unrelated to known transporter families. LetA functions as a pump at one end of a ~225 [A] long tunnel formed by its binding partner, MCE protein LetB, creating a pathway for lipid transport between the inner and outer membranes. Unexpectedly, the LetA transmembrane domains adopt a fold that is evolutionarily related to the eukaryotic tetraspanin family of membrane proteins, including TARPs and claudins. LetA has no detectable homology to known transport proteins, and defines a new class of membrane transporters. Through a combination of deep mutational scanning, molecular dynamics simulations, AlphaFold-predicted alternative states, and functional studies, we present a model for how the LetA-like family of membrane transporters may use energy from the proton-motive force to drive the transport of lipids across the bacterial cell envelope.

Matching journals

The top 2 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.