Single-molecule orientation-localization microscopy: Applications and approaches

Abstract

Single-molecule orientation-localization microscopy (SMOLM) builds upon super-resolved localization microscopy by imaging orientations and rotational dynamics of individual molecules in addition to their positions. This added dimensionality provides unparalleled insights into nanoscale biophysical and biochemical processes, including the organization of actin networks, movement of molecular motors, conformations of DNA strands, growth and remodeling of amyloid aggregates, and composition changes within lipid membranes. In this review, we discuss recent innovations in SMOLM and cover three key aspects: (1) biophysical insights enabled by labeling strategies that endow fluorescent probes to bind to targets with orientation specificity; (2) advanced imaging techniques that leverage the physics of light-matter interactions and estimation theory to encode orientation information with high fidelity into microscope images; and (3) computational methods that ensure accurate and precise data analysis and interpretation, even in the presence of severe shot noise. Additionally, we compare labeling approaches, imaging hardware, and publicly available analysis software to aid the community in choosing the best SMOLM implementation for their specific biophysical application. Finally, we highlight future directions for SMOLM, such as the development of probes with improved photostability and specificity, the design of “smart” adaptive hardware, and the use of advanced computational approaches to handle large, complex datasets. This review underscores the significant current and potential impact of SMOLM in deepening our understanding of molecular dynamics, paving the way for future breakthroughs in the fields of biophysics, biochemistry, and materials science.

Keywords: biophysical chemistry and spectroscopy; fluorescence; physical chemistry; single-molecule dichroism; single-molecule fluorescence anisotropy.

Figure 1.

Representative labeling techniques in SMOLM. (a) Alexa Fluor 488-phalloidin conjugate labeling an actin filament (F-actin) (adapted from Rimoli et al., 2022). (b) Position and orientation of bis-((N-iodoacetyl)piperazinyl) sulfonerhodamine (BSR) on the kinesin protein structure (adapted from Sosa et al., 2001). (c) B-form double-stranded DNA internally labeled with covalently attached Cy3 and Cy5 dyes (adapted from Mortensen et al., 2015). (d) Concept of molecular tension DNA probes (adapted from Brockman et al., 2018). (e) Molecular rotors transiently bind to amyloid fibrils (adapted from Sarkar et al., 2023). (f) SYTOX orange dye intercalating within λ-DNA (adapted from Backer et al., 2016). (g) 1,1′-Dioctadecyl-3,3,3′,3′-Tetramethylindocarbocyanine perchlorate (DiI) and merocyanine 540 (MC540) bound to gel- and fluid-like supported lipid bilayers, respectively (adapted from Lu et al., 2020).

Figure 2.

Imaging protein assemblies using SMOLM. (a) Polar-dSTORM imaging of actin stress fibers labeled with Alexa Fluor 488, Atto 633, and Alexa Fluor 647. Colors indicate the polarization factor P, equivalent here to linear dichroism LD, superimposed on grayscale dSTORM images (adapted from Valades Cruz et al., 2016). (b) Representative raw and hue-saturation-value (HSV) images of phalloidin-AF488 and phalloidin-AF647 bound to actin in fixed HeLa cells and distributions of the average degree of linear polarization (DoLP) for both fluorophores. Hue: angle of linear polarization (AoLP); saturation: DoLP; value: brightness (adapted from Bruggeman et al., 2024). (c) 4polar-STORM imaging of actin filament organization in fixed U2OS cells with color-coded wobbling angles δ (Alexa Fluor 488-phalloidin-labeled F-actin; adapted from Rimoli et al., 2022). The zoomed-in regions (1–4) show the (top) STORM and (bottom) 4polar-STORM images; lines indicate orientation, and colors represent wobble angles. (d) TAB SMOLM images of amyloid fibrils transiently labeled with LDS722, color-coded by (left) polar angle $\theta$ (rad) and (middle) wobble angle $\Omega$ (sr). The polar angle histogram reveals two distinct binding modes (adapted from Sarkar et al., 2023). (e) Visualization of growing and decaying amyloid-beta fibrils using (top) SMLM and (bottom) SMOLM with lines color-coded according to Nile blue orientation (adapted from Sun et al., 2024). (f) SMOLM images and orientation distributions for representative KFE8^L, KFE8^D, and Aβ42 fibrils (adapted from Zhou et al., 2024a). In each figure, Nile red orientations are plotted and color-coded relative to the long axis ( $u_x$) of each fiber.

Figure 3.

Imaging nucleic-acid structures and flexibility using SMOLM. (a) DNA helical winding of a scaffold strand (gray) and ssDNA staple (red line) labeled with a fluorophore (red dot), and orientation distributions of ATTO 647N and ATTO 643 within DNA origami structures 1 and 2 (adapted from Hübner et al., 2021). (b) (top) AFM and (bottom) three SMOLM views of Cy5 orientations within 4-arm Holliday Junction complexes (HJs) with interduplex angles of 60°, 90°, and 120° (adapted from Cervantes-Salguero et al., 2024). Mean orientations of populations and subpopulations are denoted by red and blue arrows, respectively. (c) Controlled orientations of doubly linked Cy3 and Cy5 molecules within DNA origami structures featuring different numbers of missing base pairs (adapted from Adamczyk et al., 2022). (d) (top left) Diagram and (bottom) SMOLM image of a plectoneme formed by a single supercoiled DNA molecule and distribution of SYTOX orange orientations along a typical individual strand aligned along the $x$-axis (adapted from Hulleman et al., 2021). Colors represent azimuthal orientations (top right) Typical orientation distribution of a supercoiled strand before it twists around itself. (e) Histograms of fluorescence polarization of DNA intercalators under stretching forces of 3, 7, and 35 pN (left to right) above the onset of the overstretching transition, along with illustrations of tilted intercalators (adapted from Backer et al., 2019).

Figure 4.

Imaging lipid membranes using SMOLM. (a) Distribution of polar angle ( $\theta$) and wobble angles ( $\alpha$ along the polar direction and $\beta$ perpendicular to the polar direction) of Nile red (NR) within DPPC bilayers with and without cholesterol (adapted from Ding and Lew, 2021). (b) SMOLM images of NR before and after successive sphingomyelinase (SMase) treatments reveal compositional changes within the liquid-ordered (Lo) domain and minor changes in domain size and shape during the treatment (adapted from Lu et al., 2020). (c) Nanodomains within SLBs sensed by transiently binding NR molecules using the raPol microscope (adapted from Zhang et al., 2022). (Left) localization density per 100 × 100 nm² in the azimuthally polarized channel; (middle) polar angle $\theta$ (deg); (right) wobble angle $\Omega$ (sr). (d) Orientations of Nile red (NR) transiently bound to spherical supported lipid bilayers (SLBs) after a 7-day incubation (left) without and (right) with Aβ42 monomers (adapted from Zhang et al., 2023). Localizations are color-coded by (top) polar angle $\theta$ (deg) and (bottom) wobble angle $\Omega (\mathrm{sr})$. All images are lateral ($xy$) views unless otherwise marked. (e) SMOLM images of an HEK-293T cell. Localizations are (left) color-coded by and (right) oriented along azimuthal angle $\varphi$ (deg). (Right) Zoomed image of the boxed region at left, color-coded by wobble angle $\Omega (\mathrm{sr})$. The inset histogram shows the distribution of the measured wobble angle within the regions marked by yellow and white boxes (adapted from Zhang et al., 2023).

Figure 5.

(a) Molecular orientation represented by a unit vector $\mu ={\left[{\mu }_x,{\mu }_y,{\mu }_z\right]}^{⊺}={[\sin \theta \cos \varphi ,\sin \theta \sin \varphi ,\cos \theta ]}^{⊺}$. The wobble is modeled as a hard-edged cone with cone solid angle $\Omega$ (b) Excitation light in typical SMOLM. A Kohler lens (KL) is used to produce a collimated illumination beam above the objective lens (OL). The absorption probability is a function of the angle between the absorption dipole moment ${\mu }_{\mathrm{abs}}$ and the excitation optical field ${\mathit{E}}_{\mathrm{ex}}$ (green arrows). The absorption probability is maximized if ${\mu }_{\mathrm{abs}}$ is parallel to ${\mathit{E}}_{\mathrm{ex}}$. Colorbar: normalized absorption probability. (c) Depolarization, i.e., a non-zero angle between ${\mu }_{\mathrm{abs}}$ and ${\mu }_{\mathrm{em}}$ caused by rotation during the fluorescence lifetime between the absorption and emission events. (d) Depolarization caused by energy transfer between chromophores of a YOYO-1. (e,f) Anisotropic rotational diffusion models for SMs. (e) Cone half angles $\alpha$ and $\beta$ represent the area within which the molecule can wobble, and (f) $\psi$ describes the preferred direction of the wobble.

Figure 6.

Schematic diagram of dipole emitters (a) within a medium of matched RI and (b) near the RI interface between the sample ( $n_2$) and lens immersion medium ( $n_1$). The objective lens captures a pseudo-spherical wave ( ${\mathit{E}}_{\mathrm{ff}}$ and ${\mathit{E}}_{\mathrm{ff},3}$) and converts it to a pseudo-plane wave ( ${\mathit{E}}_{\mathrm{BFP}}$). Useful unit vectors, angles, and lengths for the derivation in this section are labeled in the figure. (c) Positions of a dipole emitter relative to the RI interface ( $z_{\mathrm{SM}}$) and the nominal focal plane ( $z_f$). (d-f) Representative intensity distributions at the BFP for SMs with orientations of (i) $\theta =0^{°}$, (ii) $[\theta ,\varphi ]=[{45}^{°},{90}^{°}]$, and (iii) $[\theta ,\varphi ]=[{90}^{°},{90}^{°}]$ when (d) the sample RI matches that of the lens immersion medium (1.515) and when the sample RI is (e) $n_2=1.33$ and (f) $n_2=1$. The numerical aperture is NA = 1.4. Colorbar: normalized intensity.

Figure 7.

Representative images of recently developed and widely used dipole spread functions (DSFs). (a) Principle of a fluorescence microscope with polarized detection using a polarizing beamsplitter (PBS). An objective lens (OL) is placed at one focal length away from the dipole emitter. The tube lenses (TL1, TL2) perform optical Fourier transforms on the field at the back focal plane (BFP) modulated by an optical component represented by a 2 × 2 complex tensor $\mathit{J}(u,v)$ and create the DSF at the detector plane. Images for molecules with various orientations and wobble using the (b) standard DSF (i) unpolarized and focused (Mortensen et al., 2010), (ii) polarized and focused (Ding et al., 2020), (iii) unpolarized and defocused (Böhmer and Enderlein, 2003), (c) double-helix DSF, (d) multi-spot DSFs (i–iv) quadrated (Backer et al., 2013), bisected (Backer et al., 2014), tri-spot (Zhang et al., 2018), duo-spot (Lu et al., 2020 DSFs), (e) vortex DSF (Ding and Lew, 2021; Hulleman et al., 2021), (f) radially and azimuthally polarized (raPol) standard DSF (Zhang et al., 2022), (g) pixOL (Wu et al., 2022a), and (h) CHIDO (Curcio et al., 2020). (j) Images from eight channels of the multi-view-reflector (MVR) microscope (Zhang et al., 2023). Molecule with (1) $[\theta ,\varphi ]=[{90}^{°},0^{°}]$, (2) $[\theta ,\varphi ]=[{90}^{°},{90}^{°}]$, (3) $\theta =0^{°}$, and (4) $[\theta ,\varphi ]=[{45}^{°},0^{°}]$. (5) Isotropic emitter. Purple: in-focus molecules; green: molecules defocused by (b) 500 nm and (c–h) 200 nm. Color bar: normalized intensity; scale bar: 500 nm.

Figure 8.

(a, b) Schematic of a polarization-sensitive 4f imaging system appended to the detection path of a fluorescence microscope for modulating the phase at the back focal plane (BFP) using a spatial light modulator (SLM). (a) After separating the $x$ (red) and $y$ (blue) polarized fluorescence using a polarizing beamsplitter (PBS), light is guided towards a pyramid mirror and (b) reflected upwards towards the SLM. Both $x$ and $y$-polarized BFP are positioned at the same area on the SLM. Arrows on the phase mask represent the light polarization on the SLM. Both imaging channels are collected using camera C1. (c) Schematic of the raMVR microscope. After turning radially and azimuthally polarized fluorescence to $x$- and $y$-polarized light using a variable wave plate (VaWP) and a vortex wave plate (VWP), a PBS and two sets of pyramid mirrors separate lights into eight detection channels, captured by cameras C1 and C2.

Figure 9.

Best-possible precisions, given by the square root of the Cramér-Rao lower bound, of measuring SM position and orientation in (a–d) thin and (e–h) thick samples using various SMOLM techniques. For thin samples, we report precisions of (a) the average orientation $\mu$, (b) wobble angle $\Omega$, (c) 2D position $x$, and (d) combined precision for orientational second moments $\mathit{m}$ and 2D position $x$ as a function of nominal focal plane position $z_f$. All SMs are positioned at $z=0$ nm (at the glass-media interface). For thick samples, we report precisions of (e) average orientation $\mu$, (f) wobble angle $\Omega$, (g) 3D position $\mathit{r}$, and (h) combined precision for orientational second moments $\mathit{m}$ and 3D position $\mathit{r}$ as a function of molecular position $z$. The nominal focal plane is set at $z_f=1200\mathrm{nm}$. For all simulations, we assume that the sample has a refractive index $n_2=1.33$ (equal to that of water) and that 5000 signal photons and 40 background photons per pixel total across all channels are collected. See (Zhang and Lew, 2021b) for details on how each quantity is defined and calculated.

Figure 10.

Workflow of detection and estimation algorithms in SMOLM. (a) A raw fluorescence image can be processed using (i) an SM detection algorithm. (ii) The detected SM images can be fitted to the forward imaging model using an MLE; a reconstruction of the raw image using the fit parameters is shown in (iii). (b) The image can also be fitted to the forward imaging model using a sparsity-promoting MLE (reconstruction shown in (b)), or (c) through a (i) convolutional neural network that generates an (ii) upsampled stack representing the position and orientation of SMs. The final output of these algorithms is a list of SM positions and orientations.