Cryo-EM structures of the human INO80 chromatin-remodeling complex

Abstract

Access to chromatin for processes such as DNA repair and transcription requires the sliding of nucleosomes along DNA. The multi-subunit INO80 chromatin remodelling complex has a particular role in DNA repair. Here we present the cryo electron microscopy structures of the active core complex of human INO80 at 9.6 Å with portions at 4.1 Å resolution along with reconstructions of combinations of subunits. Together these structures reveal the architecture of the INO80 complex, including Ino80 and actin-related proteins, which is assembled around a single Tip49a (RUVBL1) and Tip49b (RUVBL2) AAA+ heterohexamer. An unusual spoked-wheel structural domain of the Ino80 subunit is engulfed by this heterohexamer and the intimate association of this Ino80 domain with the heterohexamer is at the core of the complex. We also identify a cleft in RUVBL1 and RUVBL2, which forms a major interaction site for partner proteins and likely communicates partner-interactions with its nucleotide binding sites.

Structure and dynamics of the yeast SWR1-nucleosome complex

“…As shown previously (21,22), and in common with the related INO80 complex (23), the SWR1 complex contains a single heterohexamer of the RuvBL proteins (Fig. 1B) that serves as a scaffold around which many of the other subunits are assembled (Movie 1).…”

RPAP3 provides a flexible scaffold for coupling HSP90 to the human R2TP co-chaperone complex

“…Since RPAP3 residues 430–665 bind the RUVBL ring without affecting the dodecameric assembly of RUVBL1–RUVBL2, our data suggest that the RPAP3 region that binds PIH1D1 together with PIH1D1 itself are responsible for these effects, likely because it locates within the DII-domain face of the RUVBL ring, as in yeast 24 . This is the side of the RUVBL ring where most protein interactions have been described in other complexes that contain a RUVBL1–RUVBL2 hexamer, such as INO80 31 . These experiments do not discard that RPAP3 alone could be sufficient to disrupt the RUVBL1–RUVBL2 dodecamer.…”

Deep Consensus, a deep learning-based approach for particle pruning in cryo-electron microscopy

“…Nevertheless, the set of false-positive particles that are selected by these automatic methods is non-negligible, typically ranging from 10% to more than 25% (Zhu et al, 2004). As a consequence, it is common practice in the field to perform several pruning steps (Razi et al, 2017;Aramayo et al, 2018) in which a combination of algorithmic approaches such as particle sorting (Vargas et al, 2013) or two-dimensional classification (de la Rosa-Trevín et al, 2013;Scheres, 2012;Kimanius et al, 2016;Yang et al, 2012) are employed together with manual intervention in order to rule out false-positive particles.…”