Structure of the Respiratory Syncytial Virus Polymerase Complex

Abstract

Graphical AbstractHighlights d Cryo-EM structure of RSV L bound by tetrameric RSV P solved to 3.2 Å d P tetramer adopts an asymmetric tentacular arrangement when bound to L d L priming loop adopts elongation-compatible state without PRNTase-RdRp separation d Structure rationalizes escape from small-molecule antivirals SUMMARY Numerous interventions are in clinical development for respiratory syncytial virus (RSV) infection, including small molecules that target viral transcription and replication. These processes are catalyzed by a complex comprising the RNA-dependent RNA polymerase (L) and the tetrameric phosphoprotein (P). RSV P recruits multiple proteins to the polymerase complex and, with the exception of its oligomerization domain, is thought to be intrinsically disordered. Despite their critical roles in RSV transcription and replication, structures of L and P have remained elusive. Here, we describe the 3.2-Å cryo-EM structure of RSV L bound to tetrameric P. The structure reveals a striking tentacular arrangement of P, with each of the four monomers adopting a distinct conformation. The structure also rationalizes inhibitor escape mutants and mutations observed in live-attenuated vaccine candidates. These results provide a framework for determining the molecular underpinnings of RSV replication and transcription and should facilitate the design of effective RSV inhibitors.

Structure of a rabies virus polymerase complex from electron cryo-microscopy

“…This closed conformation appears to represent the L protein poised for initiation at the 3' end of the genome or anti-genome. Comparison with structures of two recently published pneumovirus L-P complexes (Gilman et al, 2019) (Pan et al, submitted) as well as with that of a VSV L-P reconstruction determined at 3.0 Å resolution (Jenni, et al, submitted) suggests that replication and transcription have alternative priming configurations and alternative product exit sites.…”

“…and of two recently published pneumovirus L-P complexes((Gilman et al, 2019) andPan et al, submitted), suggests a mechanism for switching between replication and transcription, with alternative priming configurations and alternative sites for product exit.The "priming loop" (residues 1170 to 1186 in the CAP domain) projects into the RdRp catalytic cavity, closing off a channel that connects it with the catalytic cavity of the CAP domain. Model building in the homologous VSV L-P complex shows that an initiating nucleotide would stack on a tryptophan (W1167), corresponding to residue W1180 in RABV L, at the tip of the projecting loop (Jenni et al, submitted).…”

“…Mutation of this residue compromises end initiation, but not internal initiation or capping.Elongation beyond formation of the initial dinucleotide requires that the priming loop retract into the CAP catalytic cavity. The recent pneumovirus L-P structures show just such a retracted configuration(Gilman et al, 2019) and Pan et al, submitted. A nascent transcript can then pass across the retracted loop.…”

Non-uniform refinement: Adaptive regularization improves single particle cryo-EM reconstruction

“…Indeed, it has been already been successful in helping to resolve a number of interesting new structures. Examples include a structure of FACT manipulating the nucleasome [19], multiple conformations of an ABC exporter [14], mTORC1 docked on the lysosome [24], the respiratory syncytial virus polymerase complex [9], a GPCR-G protein-β-arrestin megacomplex [20], and MERS-CoV/SARS-CoV with neutralizing antibodies [32]. An updated non-uniform refinement algorithm implementation, as described in this work, will be released in an upcoming version of cryoSPARC (www.cryosparc.com).…”

MicrographCleaner: a python package for cryo-EM micrograph cleaning using deep learning

“…Nevertheless, despite these developments, conventional particle pickers are still the preferred choice in recent publications (Gilman et al, 2019;Hiraizumi et al, 2019;Jain et al, 2019;Molina et al, 2019;Stone et al, 2019;Yan et al, 2019). Although it is likely that deep learning particle pickers will become increasingly popular, they are not perfect and different situations will require different approaches, so conventional particle pickers, especially those based on templates, will probably remain popular.…”