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1. Fundamental limits of measuring single-molecule rotational mobility

   https://doi.org/10.1117/12.2506712  

   Zhang, Oumeng; Lew, Matthew D. (February 2019, Proc. SPIE 10884, Single Molecule Spectroscopy and Superresolution Imaging XII)

   Various methods exist for measuring molecular orientation, thereby providing insight into biochemical activities at nanoscale. Since fluorescence intensity and not electric field is detected, these methods are limited to measuring even-order moments of molecular orientation. However, any measurement noise, for example photon shot noise, will result in nonzero measurements of any of these even-order moments, thereby causing rotationally-free molecules to appear to be partially constrained. Here, we build a model to quantify measurement errors in rotational mobility. Our theoretical framework enables scientists to choose the optimal single-molecule orientation measurement technique for any desired measurement accuracy and photon budget. 

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2. Six-dimensional single-molecule imaging with isotropic resolution using a multi-view reflector microscope

   https://doi.org/10.1038/s41566-022-01116-6  

   Zhang, Oumeng; Guo, Zijian; He, Yuanyuan; Wu, Tingting; Vahey, Michael D.; Lew, Matthew D. (December 2022, Nature Photonics)

   Imaging of both the positions and orientations of single fluorophores, termed single-molecule orientation-localization microscopy, is a powerful tool for the study of biochemical processes. However, the limited photon budget associated with single-molecule fluorescence makes high-dimensional imaging with isotropic, nanoscale spatial resolution a formidable challenge. Here we realize a radially and azimuthally polarized multi-view reflector (raMVR) microscope for the imaging of the three-dimensional (3D) positions and 3D orientations of single molecules, with precisions of 10.9 nm and 2.0° over a 1.5-μm depth range. The raMVR microscope achieves 6D super-resolution imaging of Nile red molecules transiently bound to lipid-coated spheres, accurately resolving their spherical morphology, despite refractive-index mismatch. By observing the rotational dynamics of Nile red, raMVR images also resolve the infiltration of lipid membranes by amyloid-beta oligomers without covalent labelling. Finally, we demonstrate 6D imaging of cell membranes, where the orientations of specific fluorophores reveal heterogeneity in membrane fluidity. With its nearly isotropic 3D spatial resolution and orientation measurement precision, we expect the raMVR microscope to enable 6D imaging of molecular dynamics within biological and chemical systems with exceptional detail. 

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3. SpotClean adjusts for spot swapping in spatial transcriptomics data

   https://doi.org/10.1038/s41467-022-30587-y  

   Ni, Zijian; Prasad, Aman; Chen, Shuyang; Halberg, Richard B.; Arkin, Lisa M.; Drolet, Beth A.; Newton, Michael A.; Kendziorski, Christina (December 2022, Nature Communications)

   Abstract Spatial transcriptomics is a powerful and widely used approach for profiling the gene expression landscape across a tissue with emerging applications in molecular medicine and tumor diagnostics. Recent spatial transcriptomics experiments utilize slides containing thousands of spots with spot-specific barcodes that bind RNA. Ideally, unique molecular identifiers (UMIs) at a spot measure spot-specific expression, but this is often not the case in practice due to bleed from nearby spots, an artifact we refer to as spot swapping. To improve the power and precision of downstream analyses in spatial transcriptomics experiments, we propose SpotClean, a probabilistic model that adjusts for spot swapping to provide more accurate estimates of gene-specific UMI counts. SpotClean provides substantial improvements in marker gene analyses and in clustering, especially when tissue regions are not easily separated. As demonstrated in multiple studies of cancer, SpotClean improves tumor versus normal tissue delineation and improves tumor burden estimation thus increasing the potential for clinical and diagnostic applications of spatial transcriptomics technologies. 

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4. Small Rotations, Big Effects: Lessons from Water Adsorption in NU-1000

   https://doi.org/10.1021/acs.jpcc.4c06889  

   Formalik, Filip; Mazur, Bartosz; Joodaki, Faramarz; Kuchta, Bogdan; Snurr, Randall Q (February 2025, The Journal of Physical Chemistry C)

   In this study, the adsorption mechanism of water in the metal–organic framework NU-1000 was investigated using molecular simulations. The simulations predict a significant impact of small changes in terminal aquo ligand orientation on the shape and pressure of the condensation step in the water adsorption isotherm. The analysis revealed that the rotational mobility of aquo ligands, often neglected in computational studies, can shift the condensation step by up to 20% in the relative humidity scale. By examining adsorption modes and interaction sites, it was demonstrated that configurational changes in the Zr6O8 node affect water adsorption significantly and can change the nature of the interactions from hydrophobic to hydrophilic. We propose a robust approach to account for these changes in simulations, achieving good agreement with experimental results. This work underscores the necessity of considering local, molecular flexibility in water adsorption simulations to avoid mischaracterization of MOFs’ water adsorption properties. 

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5. Dense Super-Resolution Imaging of Molecular Orientation Via Joint Sparse Basis Deconvolution and Spatial Pooling

   https://doi.org/10.1109/isbi.2019.8759444  

   Mazidi, Hesam; King, Eshan S.; Zhang, Oumeng; Nehorai, Arye; Lew, Matthew D. (April 2019, 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019))

   In single-molecule super-resolution microscopy, engineered point-spread functions (PSFs) are designed to efficiently encode new molecular properties, such as 3D orientation, into complex spatial features captured by a camera. To fully benefit from their optimality, algorithms must estimate multi-dimensional parameters such as molecular position and orientation in the presence of PSF overlap and model-experiment mismatches. Here, we present a novel joint sparse deconvolution algorithm based on the decomposition of fluorescence images into six basis images that characterize molecular orientation. The proposed algorithm exploits a group-sparsity structure across these basis images and applies a pooling strategy on corresponding spatial features for robust simultaneous estimates of the number, brightness, 2D position, and 3D orientation of fluorescent molecules. We demonstrate this method by imaging DNA transiently labeled with the intercalating dye YOYO-1. Imaging the position and orientation of each molecule reveals orientational order and disorder within DNA with nanoscale spatial precision. 

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