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Abstract Membrane proteins play critical roles in disease and in the disposition of many pharmaceuticals. A prime example is P-glycoprotein (Pgp) which moves a diverse range of drugs across membranes and out of the cell before a therapeutic payload can be delivered. Conventional structural biology methods have provided a valuable framework for comprehending the complex conformational changes underlying Pgp function, which also includes ATPase activity, but the lack of real-time information hinders understanding. Atomic force microscopy (AFM) is a single-molecule technique that is well-suited for studying active membrane proteins in bilayers and is poised to advance the field beyond static snapshots. After verifying Pgp activity in surface-support bilayers, we used kymograph analysis in conjunction with AFM imaging and simulations to study structural transitions at the 100 ms timescale. Though kymographs are frequently employed to boost temporal resolution, the limitations of the method have not been well characterized, especially for sparse non-crystalline distributions of pharmaceutically relevant membrane proteins like Pgp. Common experimental challenges are analyzed, including protein orientation, instrument noise, and drift. Surprisingly, a lateral drift of 75% of the protein dimension leads to only a 12% probability of erroneous state transition detection; average dwell time error achieves a maximum value of 6%. Rotational drift of proteins like Pgp, with azimuthally-dependent maximum heights, can lead to artifactual transitions. Torsional constraints can alleviate this potential pitfall. Confidence in detected transitions can be increased by adding conformation-altering ligands such as non-hydrolysable analogs. Overall, the data indicate that AFM kymographs are a viable method to access conformational dynamics for Pgp, but generalizations of the method should be made with caution.
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Atomic force microscope kymograph analysis: A case study of two membrane proteins
Kymograph analysis is employed across the biological atomic force microscopy (AFM) community to boost temporal resolution. The method is well suited for revealing protein dynamics at the single molecule level in near-native conditions. Yet, kymograph analysis comes with limitations that depend on several factors including protein geometry and instrumental drift. This work focuses on conformational dynamics of difficult-to-study sparse distributions of membrane proteins. We compare and contrast AFM kymograph analysis for two proteins, one of which (SecDF) exhibits conformational dynamics primarily in the vertical direction (normal to the membrane surface) and the other (Pgp) exhibits a combination of lateral dynamics and vertical motion. Common experimental issues are analyzed including translational and rotational drift. Conformational transition detection is evaluated via kymograph simulations followed by state detection algorithms. We find that kymograph analysis is largely robust to lateral drift. Displacement of the AFM line scan trajectory away from the protein center of mass by a few nanometers, roughly half of the molecule diameter, does not significantly affect transition detection nor generate undue dwell time errors. On the other hand, for proteins like Pgp that exhibit significant azimuthal maximum height dependence, rotational drift can potentially produce artifactual transitions. Measuring the height of a membrane protein protrusion is generally superior to measurement of width, confirming intuition based on vertical resolution superiority. In low signal-to-noise scenarios, common state detection algorithms struggle with transition detection as opposed to infinite hidden Markov models. AFM kymography represents a valuable addition to the membrane biophysics toolkit; continued hardware and software improvements are poised to expand the method’s impact in the field.
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- Award ID(s):
- 2122027
- PAR ID:
- 10522339
- Publisher / Repository:
- Elsevier
- Date Published:
- Journal Name:
- Methods
- Volume:
- 223
- Issue:
- C
- ISSN:
- 1046-2023
- Page Range / eLocation ID:
- 83 to 94
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1016/j.ymeth.2024.01.013
