Structural Information, Resolution, and Noise in High-Resolution Atomic Force Microscopy Topographs

AFM has developed into a powerful tool in structural biology, providing topographs of proteins under close-to-native conditions and featuring an outstanding signal/noise ratio. However, the imaging mechanism exhibits particularities: fast and slow scan axis represent two independent image acquisition axes. Additionally, unknown tip geometry and tip-sample interaction render the contrast transfer function nondefinable. Hence, the interpretation of AFM topographs remained difficult. How can noise and distortions present in AFM images be quantified? How does the number of molecule topographs merged influence the structural information provided by averages? What is the resolution of topographs? Here, we find that in high-resolution AFM topographs, many molecule images are only slightly disturbed by noise, distortions, and tip-sample interactions. To identify these high-quality particles, we propose a selection criterion based on the internal symmetry of the imaged protein. We introduce a novel feature-based resolution analysis and show that AFM topographs of different proteins contain structural information beginning at different resolution thresholds: 10 Å (AqpZ), 12 Å (AQP0), 13 Å (AQP2), and 20 Å (light-harvesting-complex-2). Importantly, we highlight that the best single-molecule images are more accurate molecular representations than ensemble averages, because averaging downsizes the z-dimension and “blurs” structural details.Abbreviations: 2D, two-dimensional; 3D, three-dimensional; ACV, auto-correlation value; AFM, atomic force microscopy; AQP0, aquaporin-0; AQP2, aquaporin-2; AqpZ, aquaporin-Z; bR, bacteriorhodopsin; CCV, cross-correlation value; CTF, contrast transfer function; DPR, differential phase residual; EM, electron microscopy; FRC, Fourier ring correlation; FSC, Fourier shell correlation; IS, internal symmetry; LH2, light-harvesting-complex 2; RMSD, root mean-square deviation; SD, standard deviation; SNR, signal/noise ratio; SSNR, spectral signal/noise ratio     

BAmSA: Visualising transmembrane regions in protein complexes using biotinylated amphipols and electron microscopy

Membrane protein (MP) complexes play key roles in all living cells. Their structural characterisation is hampered by difficulties in purifying and crystallising them. Recent progress in electron microscopy (EM) have revolutionised the field, not only by providing higher-resolution structures for previously characterised MPs but also by yielding first glimpses into the structure of larger and more challenging complexes, such as bacterial secretion systems. However, the resolution of pioneering EM structures may be difficult and their interpretation requires clues regarding the overall organisation of the complexes. In this context, we present BAmSA, a new method for localising transmembrane (TM) regions in MP complexes, using a general procedure that allows tagging them without resorting to neither genetic nor chemical modification. Labels bound to TM regions can be visualised directly on raw negative-stain EM images, on class averages, or on three-dimensional reconstructions, providing a novel strategy to explore the organisation of MP complexes.