Contact

  • Academic
    arroy@stanford.edu
    University - Student Department: Chemistry Position: Graduate

Additional Info

  • Mail Code: 5080

All Publications

  • Multi-color super-resolution imaging to study human coronavirus RNA during cellular infection. bioRxiv : the preprint server for biology Wang, J., Han, M., Roy, A. R., Wang, H., Mockl, L., Zeng, L., Moerner, W. E., Qi, L. S. 2022

    Abstract

    The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the third human coronavirus within 20 years that gave rise to a life-threatening disease and the first to reach pandemic spread. To make therapeutic headway against current and future coronaviruses, the biology of coronavirus RNA during infection must be precisely understood. Here, we present a robust and generalizable framework combining high-throughput confocal and super-resolution microscopy imaging to study coronavirus infection at the nanoscale. Employing the model human coronavirus HCoV-229E, we specifically labeled coronavirus genomic RNA (gRNA) and double-stranded RNA (dsRNA) via multicolor RNA-immunoFISH and visualized their localization patterns within the cell. The exquisite resolution of our approach uncovers a striking spatial organization of gRNA and dsRNA into three distinct structures and enables quantitative characterization of the status of the infection after antiviral drug treatment. Our approach provides a comprehensive framework that supports investigations of coronavirus fundamental biology and therapeutic effects.

    View details for DOI 10.1101/2021.06.09.447760

    View details for PubMedID 34127974

  • Multi-color super-resolution imaging to study human coronavirus RNA during cellular infection. Cell reports methods Wang, J., Han, M., Roy, A. R., Wang, H., Möckl, L., Zeng, L., Moerner, W. E., Qi, L. S. 2022: 100170

    Abstract

    The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the third human coronavirus within 20 years that gave rise to a life-threatening disease and the first to reach pandemic spread. To make therapeutic headway against current and future coronaviruses, the biology of coronavirus RNA during infection must be precisely understood. Here, we present a robust and generalizable framework combining high-throughput confocal and super-resolution microscopy imaging to study coronavirus infection at the nanoscale. Employing the model human coronavirus HCoV-229E, we specifically labeled coronavirus genomic RNA (gRNA) and double-stranded RNA (dsRNA) via multicolor RNA-immunoFISH and visualized their localization patterns within the cell. The 20nm resolution achieved by of our approach uncovers a striking spatial organization of gRNA and dsRNA into three distinct structures and enables quantitative characterization of the status of the infection after antiviral drug treatment. Our approach provides a comprehensive imaging framework that will enable future investigations of coronavirus fundamental biology and therapeutic effects.

    View details for DOI 10.1016/j.crmeth.2022.100170

    View details for PubMedID 35128513

    View details for PubMedCentralID PMC8806145

  • Exploring Cell Surface-Nanopillar Interactions with 3D Super-Resolution Microscopy. ACS nano Roy, A. R., Zhang, W., Jahed, Z., Tsai, C. T., Cui, B., Moerner, W. E. 2021

    Abstract

    Plasma membrane topography has been shown to strongly influence the behavior of many cellular processes such as clathrin-mediated endocytosis, actin rearrangements, and others. Recent studies have used three-dimensional (3D) nanostructures such as nanopillars to imprint well-defined membrane curvatures (the "nano-bio interface"). In these studies, proteins and their interactions were probed by two-dimensional fluorescence microscopy. However, the low resolution and limited axial detail of such methods are not optimal to determine the relative spatial position and distribution of proteins along a 100 nm-diameter object, which is below the optical diffraction limit. Here, we introduce a general method to explore the nanoscale distribution of proteins at the nano-bio interface with 10-20 nm precision using 3D single-molecule super-resolution (SR) localization microscopy. This is achieved by combining a silicone-oil immersion objective and 3D double-helix point spread function microscopy. We carefully adjust the objective to minimize spherical aberrations between quartz nanopillars and the cell. To validate the 3D SR method, we imaged the 3D shape of surface-labeled nanopillars and compared the results with electron microscopy measurements. Turning to transmembrane-anchored labels in cells, the high quality 3D SR reconstructions reveal the membrane tightly wrapping around the nanopillars. Interestingly, the cytoplasmic protein AP-2 involved in clathrin-mediated endocytosis accumulates along the nanopillar above a specific threshold of 1/R (the reciprocal of the radius) membrane curvature. Finally, we observe that AP-2 and actin preferentially accumulate at positive Gaussian curvature near the pillar caps. Our results establish a general method to investigate the nanoscale distribution of proteins at the nano-bio interface using 3D SR microscopy.

    View details for DOI 10.1021/acsnano.1c05313

    View details for PubMedID 34582687

  • Deep learning in single-molecule microscopy: fundamentals, caveats, and recent developments [Invited]. Biomedical optics express Mockl, L., Roy, A. R., Moerner, W. E. 2020; 11 (3): 1633–61

    Abstract

    Deep learning-based data analysis methods have gained considerable attention in all fields of science over the last decade. In recent years, this trend has reached the single-molecule community. In this review, we will survey significant contributions of the application of deep learning in single-molecule imaging experiments. Additionally, we will describe the historical events that led to the development of modern deep learning methods, summarize the fundamental concepts of deep learning, and highlight the importance of proper data composition for accurate, unbiased results.

    View details for DOI 10.1364/BOE.386361

    View details for PubMedID 32206433

  • Quantitative super-resolution microscopy of the mammalian glycocalyx Mockl, L., Pedram, K., Roy, A., Krishnan, V., Gustavsson, A., Dorigo, O., Bertozzi, C., Moerner, W. AMER CHEMICAL SOC. 2019

    View details for Web of Science ID 000525055501242

  • Accurate and rapid background estimation in single-molecule localization microscopy using the deep neural network BGnet. Proceedings of the National Academy of Sciences of the United States of America Möckl, L. n., Roy, A. R., Petrov, P. N., Moerner, W. E. 2019

    Abstract

    Background fluorescence, especially when it exhibits undesired spatial features, is a primary factor for reduced image quality in optical microscopy. Structured background is particularly detrimental when analyzing single-molecule images for 3-dimensional localization microscopy or single-molecule tracking. Here, we introduce BGnet, a deep neural network with a U-net-type architecture, as a general method to rapidly estimate the background underlying the image of a point source with excellent accuracy, even when point-spread function (PSF) engineering is in use to create complex PSF shapes. We trained BGnet to extract the background from images of various PSFs and show that the identification is accurate for a wide range of different interfering background structures constructed from many spatial frequencies. Furthermore, we demonstrate that the obtained background-corrected PSF images, for both simulated and experimental data, lead to a substantial improvement in localization precision. Finally, we verify that structured background estimation with BGnet results in higher quality of superresolution reconstructions of biological structures.

    View details for DOI 10.1073/pnas.1916219117

    View details for PubMedID 31871202

  • Quantitative Super-Resolution Microscopy of the Mammalian Glycocalyx. Developmental cell Möckl, L. n., Pedram, K. n., Roy, A. R., Krishnan, V. n., Gustavsson, A. K., Dorigo, O. n., Bertozzi, C. R., Moerner, W. E. 2019

    Abstract

    The mammalian glycocalyx is a heavily glycosylated extramembrane compartment found on nearly every cell. Despite its relevance in both health and disease, studies of the glycocalyx remain hampered by a paucity of methods to spatially classify its components. We combine metabolic labeling, bioorthogonal chemistry, and super-resolution localization microscopy to image two constituents of cell-surface glycans, N-acetylgalactosamine (GalNAc) and sialic acid, with 10-20 nm precision in 2D and 3D. This approach enables two measurements: glycocalyx height and the distribution of individual sugars distal from the membrane. These measurements show that the glycocalyx exhibits nanoscale organization on both cell lines and primary human tumor cells. Additionally, we observe enhanced glycocalyx height in response to epithelial-to-mesenchymal transition and to oncogenic KRAS activation. In the latter case, we trace increased height to an effector gene, GALNT7. These data highlight the power of advanced imaging methods to provide molecular and functional insights into glycocalyx biology.

    View details for DOI 10.1016/j.devcel.2019.04.035

    View details for PubMedID 31105009