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Multicolor fluorescent imaging by space-constrained computational hyperspectral imaging

Yina Wang, Bin Yang, Siyu Feng, Veronica Pessino, Bo Huang
doi: https://doi.org/10.1101/458869
Yina Wang
1Department of Pharmaceutical Chemistry, University of California in San Francisco, San Francisco, CA 94143, USA
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Bin Yang
1Department of Pharmaceutical Chemistry, University of California in San Francisco, San Francisco, CA 94143, USA
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Siyu Feng
2The UC Berkeley-UCSF Graduate Program in Bioengineering, San Francisco, CA 94143, USA
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Veronica Pessino
1Department of Pharmaceutical Chemistry, University of California in San Francisco, San Francisco, CA 94143, USA
3Graduate Program of Biophysics, University of California, San Francisco, San Francisco, CA 94143, USA
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Bo Huang
1Department of Pharmaceutical Chemistry, University of California in San Francisco, San Francisco, CA 94143, USA
4Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, CA 94143, USA
5Chan Zuckerberg Biohub, San Francisco, CA 94158, USA
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  • For correspondence: bo.huang@ucsf.edu
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Abstract

Hyperspectral imaging is a powerful technique to simultaneously study multiple fluorophore labels with overlapping emissions. Here we present a computational hyperspectral imaging method, which uses the sample spatial fluorescence information as a reconstruction constraint. Our method addresses both the under-sampling issue of compressive hyperspectral imaging and the low throughput issue of scanning hyperspectral imaging. With simulated and experimental data, we have demonstrated the superior reconstruction precision of our method in two and three-color imaging. We have experimentally validated this method in differentiating cellular structures labeled with two red-colored fluorescent proteins, tdTomato and mCherry, which have highly overlapping emission spectra. Our method has the advantage of totally free wavelength choice and can also be combined with conventional filter-based sequential multi-color imaging to further expand the choices of probes.

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Posted November 01, 2018.
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Multicolor fluorescent imaging by space-constrained computational hyperspectral imaging
Yina Wang, Bin Yang, Siyu Feng, Veronica Pessino, Bo Huang
bioRxiv 458869; doi: https://doi.org/10.1101/458869
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Multicolor fluorescent imaging by space-constrained computational hyperspectral imaging
Yina Wang, Bin Yang, Siyu Feng, Veronica Pessino, Bo Huang
bioRxiv 458869; doi: https://doi.org/10.1101/458869

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