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High-Resolution Imaging of Single-Cell Behaviors in 3D Bacterial Biofilms using Lattice-Light Sheet Microscopy and Deep Learning-Based Image Processing

Published online by Cambridge University Press:  30 July 2021

Ji Zhang ,
Yibo Wang ,
Mingxing Zhang ,
Alecia Achimovich ,
Jie Wang ,
Scott Acton  and
Andreas Gahlmann
Ji Zhang
Affiliation:
University of Virginia, United States
Yibo Wang
Affiliation:
University of Virginia, United States
Mingxing Zhang
Affiliation:
University of Virginia, United States
Alecia Achimovich
Affiliation:
University of Virginia, United States
Jie Wang
Affiliation:
University of Virginia, United States
Scott Acton
Affiliation:
University of Virginia, United States
Andreas Gahlmann
Affiliation:
University of Virginia, CHARLOTTESVILLE, Virginia, United States

Abstract

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Type
From Images to Insights: Working with Large Multi-modal Data in Cell Biological Imaging
Information
Microscopy and Microanalysis , Volume 27 , Supplement S1 , August 2021 , pp. 3038 - 3040
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Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press on behalf of the Microscopy Society of America

References

Chen, B.C., et al. Lattice light-sheet microscopy: imaging molecules to embryos at high spatiotemporal resolution. Science 346, 1257998 (2014).CrossRefGoogle ScholarPubMed
Li, D., et al. Extended-resolution structured illumination imaging of endocytic and cytoskeletal dynamics. Science 349, aab3500 (2015).Google ScholarPubMed
Yang, B., et al. Epi-illumination SPIM for volumetric imaging with high spatial-temporal resolution. Nat Methods 16, 501-504 (2019).Google ScholarPubMed
Voleti, V., et al. Real-time volumetric microscopy of in vivo dynamics and large-scale samples with SCAPE 2.0. Nat Methods 16, 1054-1062 (2019).Google ScholarPubMed
Zhang, M., et al. Non-invasive single-cell morphometry in living bacterial biofilms. Nature Communications 11, 6151 (2020).CrossRefGoogle ScholarPubMed
Çiçek, Ö., Abdulkadir, A., Lienkamp, S.S., Brox, T. & Ronneberger, O. 3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation. 424-432 (Springer International Publishing, Cham, 2016).Google Scholar
Stringer, C., Wang, T., Michaelos, M. & Pachitariu, M. Cellpose: a generalist algorithm for cellular segmentation. Nat Methods 18, 100-106 (2021).CrossRefGoogle ScholarPubMed
Yan, J., Sharo, A.G., Stone, H.A., Wingreen, N.S. & Bassler, B.L. Vibrio cholerae biofilm growth program and architecture revealed by single-cell live imaging. Proc Natl Acad Sci U S A 113, E5337-5343 (2016).Google ScholarPubMed
Reyer, M.A., McLean, E.L., Chennakesavalu, S. & Fei, J. An Automated Image Analysis Method for Segmenting Fluorescent Bacteria in Three Dimensions. Biochemistry 57, 209-215 (2018).CrossRefGoogle ScholarPubMed
Hartmann, R., et al. Emergence of three-dimensional order and structure in growing biofilms. Nature Physics 15, 251-256 (2019).Google ScholarPubMed
Kroos, L. Highly Signal-Responsive Gene Regulatory Network Governing Myxococcus Development. Trends Genet 33, 3-15 (2017).Google ScholarPubMed
Lee, C.K., et al. Multigenerational memory and adaptive adhesion in early bacterial biofilm communities. Proc Natl Acad Sci U S A (2018).Google ScholarPubMed