Fluorescence and SEM correlative microscopy for nanomanipulation of subcellular structures

被引:0
|
作者
Zheng Gong
Brandon K Chen
Jun Liu
Chao Zhou
Dave Anchel
Xiao Li
Ji Ge
David P Bazett-Jones
Yu Sun
机构
[1] Advanced Micro and Nanosystems Laboratory,
[2] University of Toronto,undefined
[3] Toronto,undefined
[4] ON M5S 3G8,undefined
[5] Canada,undefined
[6] State Key Laboratory of Intelligent Control and Management of Complex Systems,undefined
[7] Institute of Automation,undefined
[8] Chinese Academy of Sciences,undefined
[9] The Genetics and Genome Biology Program,undefined
[10] the Hospital for Sick Children,undefined
[11] Toronto,undefined
[12] ON M5G 1X8,undefined
[13] Canada,undefined
来源
关键词
correlative microscopy; fluorescence; image correlation; nanomanipulation; SEM; subcellular structures;
D O I
暂无
中图分类号
学科分类号
摘要
Nanomanipulation under scanning electron microscopy (SEM) enables direct interactions of a tool with a sample. We recently developed a nanomanipulation technique for the extraction and identification of DNA contained within sub-nuclear locations of a single cell nucleus. In nanomanipulation of sub-cellular structures, a key step is to identify targets of interest through correlating fluorescence and SEM images. The DNA extraction task must be conducted with low accelerating voltages resulting in low imaging resolutions. This is imposed by the necessity of preserving the biochemical integrity of the sample. Such poor imaging conditions make the identification of nanometer-sized fiducial marks difficult. This paper presents an affine scale-invariant feature transform (ASIFT) based method for correlating SEM images and fluorescence microscopy images. The performance of the image correlation approach under different noise levels and imaging magnifications was quantitatively evaluated. The optimal mean absolute error (MAE) of correlation results is 68±34 nm under standard conditions. Compared with manual correlation by skilled operators, the automated correlation approach demonstrates a speed that is higher by an order of magnitude. With the SEM-fluorescence image correlation approach, targeted DNA was successfully extracted via nanomanipulation under SEM conditions.
引用
收藏
页码:e224 / e224
相关论文
共 50 条
  • [1] Fluorescence and SEM correlative microscopy for nanomanipulation of subcellular structures
    Gong, Zheng
    Chen, Brandon K.
    Liu, Jun
    Zhou, Chao
    Anchel, Dave
    Li, Xiao
    Ge, Ji
    Bazett-Jones, David P.
    Sun, Yu
    [J]. LIGHT-SCIENCE & APPLICATIONS, 2014, 3 : e224 - e224
  • [2] Fluorescence and SEM correlative microscopy for nanomanipulation of subcellular structures
    Gong, Zheng
    Chen, Brandon K.
    Liu, Jun
    Zhou, Chao
    Anchel, Dave
    Li, Xiao
    Ge, Ji
    Bazett-Jones, David P.
    Sun, Yu
    [J]. Light: Science and Applications, 2014, 3 (11):
  • [3] Fluorescence and SEM correlative microscopy for nanomanipulation of subcellular structures
    Gong, Zheng
    Chen, Brandon K.
    Liu, Jun
    Zhou, Chao
    Anchel, Dave
    Li, Xiao
    Ge, Ji
    Bazett-Jones, David P.
    Sun, Yu
    [J]. Light: Science and Applications, 2014, 3
  • [4] Fluorescence and SEM correlative microscopy for nanomanipulation of subcellular structures
    [J]. Bazett-Jones, David P. (david.bazett-jones@sickkids.ca), 1600, Nature Publishing Group (03):
  • [5] Correlative Microscopy for Nanomanipulation of Sub-Cellular Structures
    Gong, Z.
    Chen, B. K.
    Liu, J.
    Zhou, C.
    Anchel, D.
    Li, X.
    Bazett-Jones, D. P.
    Sun, Y.
    [J]. 2014 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA), 2014, : 5209 - 5214
  • [6] Motion estimation of subcellular structures from fluorescence microscopy images
    Vallmitjana, A.
    Civera-Tregon, A.
    Hoenicka, J.
    Palau, F.
    Benitez, R.
    [J]. 2017 39TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC), 2017, : 4419 - 4422
  • [7] Segmentation and quantification of subcellular structures in fluorescence microscopy images using Squassh
    Aurélien Rizk
    Grégory Paul
    Pietro Incardona
    Milica Bugarski
    Maysam Mansouri
    Axel Niemann
    Urs Ziegler
    Philipp Berger
    Ivo F Sbalzarini
    [J]. Nature Protocols, 2014, 9 : 586 - 596
  • [8] Automated recognition of patterns characteristic of subcellular structures in fluorescence microscopy images
    Boland, MV
    Markey, MK
    Murphy, RF
    [J]. CYTOMETRY, 1998, 33 (03): : 366 - 375
  • [9] Deep localization of subcellular protein structures from fluorescence microscopy images
    Muhammad Tahir
    Saeed Anwar
    Ajmal Mian
    Abdul Wahab Muzaffar
    [J]. Neural Computing and Applications, 2022, 34 : 5701 - 5714
  • [10] Segmentation and quantification of subcellular structures in fluorescence microscopy images using Squassh
    Rizk, Aurelien
    Paul, Gregory
    Incardona, Pietro
    Bugarski, Milica
    Mansouri, Maysam
    Niemann, Axel
    Ziegler, Urs
    Berger, Philipp
    Sbalzarini, Ivo F.
    [J]. NATURE PROTOCOLS, 2014, 9 (03) : 586 - 596