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Ultrafast data mining of molecular assemblies in multiplexed high-density super-resolution images

Author

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  • Yandong Yin

    (New York University School of Medicine)

  • Wei Ting Chelsea Lee

    (New York University School of Medicine)

  • Eli Rothenberg

    (New York University School of Medicine)

Abstract

Multicolor single-molecule localization super-resolution microscopy has enabled visualization of ultrafine spatial organizations of molecular assemblies within cells. Despite many efforts, current approaches for distinguishing and quantifying such organizations remain limited, especially when these are contained within densely distributed super-resolution data. In theory, higher-order correlation such as the Triple-Correlation function is capable of obtaining the spatial configuration of individual molecular assemblies masked within seemingly discorded dense distributions. However, due to their enormous computational cost such analyses are impractical, even for high-end computers. Here, we developed a fast algorithm for Triple-Correlation analyses of high-content multiplexed super-resolution data. This algorithm computes the probability density of all geometric configurations formed by every triple-wise single-molecule localization from three different channels, circumventing impractical 4D Fourier Transforms of the entire megapixel image. This algorithm achieves 102-folds enhancement in computational speed, allowing for high-throughput Triple-Correlation analyses and robust quantification of molecular complexes in multiplexed super-resolution microscopy.

Suggested Citation

  • Yandong Yin & Wei Ting Chelsea Lee & Eli Rothenberg, 2019. "Ultrafast data mining of molecular assemblies in multiplexed high-density super-resolution images," Nature Communications, Nature, vol. 10(1), pages 1-7, December.
    • Handle: RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-018-08048-2
    DOI: 10.1038/s41467-018-08048-2
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    Cited by:

    1. Sameera Vipat & Dipika Gupta & Sagun Jonchhe & Hele Anderspuk & Eli Rothenberg & Tatiana N. Moiseeva, 2022. "The non-catalytic role of DNA polymerase epsilon in replication initiation in human cells," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
    2. Aina Maria Mas & Enrique Goñi & Igor Ruiz de los Mozos & Aida Arcas & Luisa Statello & Jovanna González & Lorea Blázquez & Wei Ting Chelsea Lee & Dipika Gupta & Álvaro Sejas & Shoko Hoshina & Alexandr, 2023. "ORC1 binds to cis-transcribed RNAs for efficient activation of replication origins," Nature Communications, Nature, vol. 14(1), pages 1-19, December.
    3. Kate E. Coleman & Yandong Yin & Sarah Kit Leng Lui & Sarah Keegan & David Fenyo & Duncan J. Smith & Eli Rothenberg & Tony T. Huang, 2022. "USP1-trapping lesions as a source of DNA replication stress and genomic instability," Nature Communications, Nature, vol. 13(1), pages 1-19, December.
    4. Liana Goehring & Sarah Keegan & Sudipta Lahiri & Wenxin Xia & Michael Kong & Judit Jimenez-Sainz & Dipika Gupta & Ronny Drapkin & Ryan B. Jensen & Duncan J. Smith & Eli Rothenberg & David Fenyö & Tony, 2024. "Dormant origin firing promotes head-on transcription-replication conflicts at transcription termination sites in response to BRCA2 deficiency," Nature Communications, Nature, vol. 15(1), pages 1-18, December.

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