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Copyright © 2009 Biophysical Society All rights reserved.
Biophysical Journal, Volume 96, Issue 9, 3822-3831, 6 May 2009


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

Peter FechnerThomas BoudierStéphanie Mangenot§Szymon JaroslawskiJames N. Sturgis and Simon ScheuringGo To Corresponding Author 

Institut Curie, Équipe Institut National de la Santé et de la Recherche Médicale Avenir, 75248 Paris, France
UPR-9027 Laboratoire d'Ingénierie des Systèmes Macromoléculaires, Institut de Microbiologie de la Méditerranée, Centre National de la Recherche Scientifique–Aix-Marseille Université, 13402 Marseille, France
§ Université Paris-Sud, 91405 Orsay, France
Institut de Biologie Intégrative, Institut Fédératif de Recherche 83, Université Pierre et Marie Curie, Paris, France

Corresponding author


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.