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Atomic Force Microscopy (AFM) can create images of biomolecules under near-native conditions but suffers from limited lateral resolution due to the finite AFM tip size and recording frequency. The recently developed Localization Atomic Force Microscopy or LAFM (Heath et al., Nature 594, 385 (2021)) enhances lateral resolution by reconstructing peak positions in AFM image stacks, but it is less effective for flexible proteins with multiple conformations. Here we introduce an unsupervised deep learning algorithm that simultaneously registers and clusters images by protein conformation, thus making LAFM applicable to more flexible proteins. Using simulated AFM images from molecular dynamics simulations of the SecYEG translocon as a model membrane protein system, we demonstrate improved resolution for individual protein conformations. This work represents a step towards a more general LAFM algorithm that can handle biological macromolecules with multiple distinct conformational states such as SecYEG. Author summaryAtomic Force Microscopy (AFM) enables high-resolution imaging of biomolecules under near-native conditions but faces lateral resolution limits due to the finite AFM tip size and recording frequency. The recently developed Localization Atomic Force Microscopy (LAFM) method addresses this by reconstructing peak positions from AFM image stacks, achieving almost atomic resolution for rigid proteins like bacteriorhodopsin (Heath et al., Nature 594, 385 (2021)). However, flexible membrane proteins with dynamic conformations, such as the SecYEG translocon, which exhibits large and highly mobile cytoplasmic loops, lead to non-physical smearing in standard LAFM reconstructions. Here, we present a computational framework combining unsupervised deep clustering and LAFM to enhance the lateral resolution of AFM images of flexible membrane proteins. Our neural network algorithm (i) groups AFM images into conformationally homogeneous clusters and (ii) registers images within each cluster. Applying LAFM separately to these clusters minimizes smearing artifacts, yielding high-resolution reconstructions for distinct conformations. We validate this approach using synthetic AFM images generated from all-atom molecular dynamics simulations of SecYEG in a solvated POPE lipid bilayer. This advancement extends LAFM’s utility to encompass conformationally diverse membrane proteins. 

Physical interactions between polypeptide chains and lipid membranes underlie critical cellular processes. Yet, despite fundamental importance, key mechanistic aspects of these interactions remain elusive. Bulk experiments have revealed a linear relationship between free energy and peptide chain length in a model system, but does this linearity extend to the interaction strength and to the kinetics of lipid binding? To address these questions, we utilized a combination of coarse-grained molecular dynamics (CG MD) simulations, analytical modeling, and atomic force microscopy (AFM)-based single molecule force spectroscopy. Following previous bulk experiments, we focused on interactions between short hydrophobic peptides (WLn, n = 1, ..., 5) with 1-palmitoyl-2-oleoyl-glycero-3-phosphocholine (POPC) bilayers, a simple system that probes peptide primary structure effects. Potentials of mean force extracted from CG MD recapitulated the linearity of free energy with the chain length. Simulation results were quantitatively connected to bulk biochemical experiments via a single scaling factor of order unity, corroborating the methodology. Additionally, CG MD revealed an increase in the distance to the transition state, a result that weakens the dependence of the dissociation force on the peptide chain length. AFM experiments elucidated rupture force distributions and, through modeling, intrinsic dissociation rates. Taken together, the analysis indicates a rupture force plateau in the WLn−POPC system, suggesting that the final rupture event involves the last 2 or 3 residues. In contrast, the linear dependence on chain length was preserved in the intrinsic dissociation rate. This study advances the understanding of peptide−lipid interactions and provides potentially useful insights for the design of peptides with tailored membrane-interacting properties. 

The efficacy of many cancer drugs is hindered by P-glycoprotein (Pgp), a cellular pump that removes drugs from cells. To improve chemotherapy, drugs capable of evading Pgp must be developed. Despite similarities in structure, vinca alkaloids (VAs) show disparate Pgp-mediated efflux ratios. ATPase activity and binding affinity studies show at least two binding sites for the VAs: high- and low-affinity sites that stimulate and inhibit the ATPase activity rate, respectively. The affinity for ATP from the ATPase kinetics curve for vinblastine (VBL) at the high-affinity site was 2- and 9-fold higher than vinorelbine (VRL) and vincristine (VCR), respectively. Conversely, VBL had the highest Km (ATP) for the low-affinity site. The dissociation constants (KDs) determined by protein fluorescence quenching were in the order VBL < VRL< VCR. The order of the KDs was reversed at higher substrate concentrations. Acrylamide quenching of protein fluorescence indicate that the VAs, either at 10 mM or 150 mM, predominantly maintain Pgp in an open-outward conformation. When 3.2 mM AMPPNP was present, 10 mM of either VBL, VRL, or VCR cause Pgp to shift to an open-outward conformation, while 150 mM of the VAs shifted the conformation of Pgp to an intermediate orientation, between opened inward and open-outward. However, the conformational shift induced by saturating AMPPNP and VCR condition was less than either VBL or VRL in the presence of AMPPNP. At 150 mM, atomic force microscopy (AFM) revealed that the VAs shift Pgp population to a predominantly open-inward conformation. Additionally, STDD NMR studies revealed comparable groups in VBL, VRL, and VCR are in contact with the protein during binding. Our results, when coupled with VAs-microtubule structure-activity relationship studies, could lay the foundation for developing next-generation VAs that are effective as anti-tumor agents. A model that illustrates the intricate process of Pgp-mediated transport of the VAs is presented. 

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. 

Candida albicans is a commensal fungus that can cause epithelial infections and life-threatening invasive candidiasis. The fungus secretes candidalysin (CL), a peptide that causes cell damage and immune activation by permeation of epithelial membranes. The mechanism of CL action involves strong peptide assembly into polymers in solution. The free ends of linear CL polymers can join, forming loops that become pores upon binding to membranes. CL polymers constitute a therapeutic target for candidiasis, but little is known about CL self-assembly in solution. Here, we examine the assembly mechanism of CL in the absence of membranes using complementary biophysical tools, including a new fluorescence polymerization assay, mass photometry, and atomic force microscopy. We observed that CL assembly is slow, as tracked with the fluorescent marker C-laurdan. Single-molecule methods showed that CL polymerization involves a convolution of four processes. Self-assembly begins with the formation of a basic subunit, thought to be a CL octamer that is the polymer seed. Polymerization proceeds via the addition of octamers, and as polymers grow they can curve and form loops. Alternatively, secondary polymerization can occur and cause branching. Interplay between the different rates determines the distribution of CL particle types, indicating a kinetic control mechanism. This work elucidates key physical attributes underlying CL self-assembly which may eventually evoke pharmaceutical development. 

Ice Lithography (IL) is a new technique for electron beam lithography that employs conformal ices (i.e., solid phase condensed gasses) as sacrificial resist layers for lithographic processes on a variety of sample types. The completely dry in-situ processing inherent in IL allows for high precision patterning of delicate and organic surfaces such as atomic force microscope (AFM) tips and proteins. In this talk I will present an overview of the capabilities of the MU IL instrument and describe our recent work, which is centered on pushing ice species beyond water. Amorphous H2O ice is a material that has been well characterized in the astrophysics community but has received little attention from the nanotechnology field. It is a positive resist that requires large critical doses (about 2C/cm^2 for 200nm thick ice). The alcohols (ethanol, methanol and isopropanol) are attractive candidates to complement water ice. They are negative phase resists which exhibit lower critical dose (0.2C/cm^2 for 200nm thick ice) requirements than water ice. We are exploring the use of alcohol resists in conjunction with Reactive Ion Etching (RIE) for accurate modification of small, delicate, structures such as AFM tips. We are also interested in characterizing the residual material from alcohol ices after exposure to the electron beam which can be achieved through several methods including Electron Energy Loss Spectroscopy (EELS) and simulations such as the high energy chemistry program GEANT-4. 

Abstract The fundamental molecules of life are polymers. Prominent examples include nucleic acids and proteins, both of which exhibit a large array of mechanical properties and three-dimensional shapes. The bending rigidity of individual polymers is quantified by the persistence length. The shape of a polymer, dictated by the topology of the polymer backbone, a line trace through the center of the polymer along the contour path, is also an important characteristic. Common biomolecular architectures include linear, cyclic (ring-like), and branched structures; combinations of these can also exist, as in complex polymer networks. Determination of persistence length and shape are largely informative to polymer function and stability in biological environments. Here we demonstratePersistence lengthShapePolymer (PS Poly), a near-fully automated algorithm designed to obtain polymer persistence length and shape from single molecule images obtained in physiologically relevant fluid conditions via atomic force microscopy. The algorithm, which involves image reduction via skeletonization followed by end point and branch point detection, is capable of rapidly analyzing thousands of polymers with subpixel precision. Algorithm outputs were verified by analysis of deoxyribonucleic acid, a very well characterized macromolecule. The method was further demonstrated by application to candidalysin, a recently discovered and complex virulence factor fromCandida albicans. Candidalysin forms polymers of highly variable shape and contour length and represents the first peptide toxin identified in a human fungal pathogen. PS Poly is a robust and general algorithm. It can be used to extract fundamental information about polymer backbone stiffness, shape, and more generally, polymerization mechanisms. 

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.