Shifra Lansky Lab

Transient receptor potential (TRP) channels are a large, eukaryotic ion channel superfamily that control diverse physiological functions, and therefore are attractive drug targets ^1–5. More than 210 structures from more than 20 different TRP channels have been determined, and all are tetramers ⁴. Despite this wealth of structures, many aspects concerning TRPV channels remain poorly understood, including the pore-dilation phenomenon, whereby prolonged activation leads to increased conductance, permeability to large ions and loss of rectification ^6,7. Here, we used high-speed atomic force microscopy (HS-AFM) to analyse membrane-embedded TRPV3 at the single-molecule level and discovered a pentameric state. HS-AFM dynamic imaging revealed transience and reversibility of the pentamer in dynamic equilibrium with the canonical tetramer through membrane diffusive protomer exchange. The pentamer population increased upon diphenylboronic anhydride (DPBA) addition, an agonist that has been shown to induce TRPV3 pore dilation. On the basis of these findings, we designed a protein production and data analysis pipeline that resulted in a cryogenic-electron microscopy structure of the TRPV3 pentamer, showing an enlarged pore compared to the tetramer. The slow kinetics to enter and exit the pentameric state, the increased pentamer formation upon DPBA addition and the enlarged pore indicate that the pentamer represents the structural correlate of pore dilation. We thus show membrane diffusive protomer exchange as an additional mechanism for structural changes and conformational variability. Overall, we provide structural evidence for a non-canonical pentameric TRP-channel assembly, laying the foundation for new directions in TRP channel research.

AbnA is an extracellular GH43 α-L-arabinanase from Geobacillus stearothermophilus, a key bacterial enzyme in the degradation and utilization of arabinan. We present herein its full-length crystal structure, revealing the only ultra-multimodular architecture and the largest structure to be reported so far within the GH43 family. Additionally, the structure of AbnA appears to contain two domains belonging to new uncharacterized carbohydrate-binding module (CBM) families. Three crystallographic conformational states are determined for AbnA, and this conformational flexibility is thoroughly investigated further using the “integrative structure determination” approach, integrating molecular dynamics, metadynamics, normal mode analysis, small angle X-ray scattering, dynamic light scattering, cross-linking, and kinetic experiments to reveal large functional conformational changes for AbnA, involving up to ~100 Å movement in the relative positions of its domains. The integrative structure determination approach demonstrated here may apply also to the conformational study of other ultra-multimodular proteins of diverse functions and structures.

Understanding structural dynamics of biomolecules at the single-molecule level is vital to advancing our knowledge of molecular mechanisms. Currently, there are few techniques that can capture dynamics at the sub-nanometre scale and in physiologically relevant conditions. Atomic force microscopy (AFM)¹ has the advantage of analysing unlabelled single molecules in physiological buffer and at ambient temperature and pressure, but its resolution limits the assessment of conformational details of biomolecules². Here we present localization AFM (LAFM), a technique developed to overcome current resolution limitations. By applying localization image reconstruction algorithms³ to peak positions in high-speed AFM and conventional AFM data, we increase the resolution beyond the limits set by the tip radius, and resolve single amino acid residues on soft protein surfaces in native and dynamic conditions. LAFM enables the calculation of high-resolution maps from either images of many molecules or many images of a single molecule acquired over time, facilitating single-molecule structural analysis. LAFM is a post-acquisition image reconstruction method that can be applied to any biomolecular AFM dataset.