Back

Unraveling cellular complexity with unlimited multiplexed super-resolution imaging

Schueder, F.; Rivera-Molina, F.; Su, M.; Kidd, P.; Rothman, J. E.; Toomre, D.; Bewersdorf, J.

2023-05-18 cell biology
10.1101/2023.05.17.541061 bioRxiv
Show abstract

Mapping the intricate spatial relationships between the many different molecules inside a cell is essential to understanding cellular functions in all their complexity. Super-resolution fluorescence microscopy offers the required spatial resolution but struggles to reveal more than four different targets simultaneously. Exchanging labels in subsequent imaging rounds for multiplexed imaging extends this number but is limited by its low throughput. Here we present a novel imaging method for rapid multiplexed super-resolution microscopy of a nearly unlimited number of molecular targets by leveraging fluorogenic labeling in conjunction with Transient Adapter-mediated switching for high-throughput DNA-PAINT (FLASH-PAINT). We demonstrate the cell biological versatility of FLASH-PAINT in mammalian cells in four applications: i) mapping nine proteins in a single mammalian cell, ii) elucidating the functional organization of primary cilia by nine-target imaging, iii) revealing the changes in proximity of twelve different targets in unperturbed and dissociated Golgi stacks and iv) investigating inter-organelle contacts at 3D super-resolution.

Matching journals

The top 3 journals account for 50% of the predicted probability mass.

1
Nature Communications
○ 5641 papers in training set
Top 6%
22.7%
Similar papers in this journal
2
Nature Methods
○ 385 papers in training set
Top 0.4%
18.8%
Similar papers in this journal
3
Cell
○ 431 papers in training set
Top 0.2%
12.1%
Similar papers in this journal
50% of probability mass above
4
Nature Biotechnology
○ 172 papers in training set
Top 0.8%
5.2%
Similar papers in this journal
5
Science Advances
● 1243 papers in training set
Top 6%
4.9%
Similar papers in this journal
6
Nature Cell Biology
○ 118 papers in training set
Top 0.9%
3.3%
7
Journal of Cell Biology
● 392 papers in training set
Top 2%
2.7%
8
Science
● 477 papers in training set
Top 4%
2.5%
9
Proceedings of the National Academy of Sciences
● 2444 papers in training set
Top 20%
2.5%
10
eLife
● 5828 papers in training set
Top 42%
2.4%
11
Communications Biology
○ 993 papers in training set
Top 10%
2.2%
12
Nature Chemical Biology
○ 119 papers in training set
Top 2%
1.4%
13
Cell Systems
○ 201 papers in training set
Top 3%
1.4%
14
Cell Reports
○ 1498 papers in training set
Top 22%
1.1%
15
Angewandte Chemie International Edition
○ 93 papers in training set
Top 1%
1.1%
16
Molecular Cell
○ 350 papers in training set
Top 4%
1.0%
17
Journal of the American Chemical Society
● 217 papers in training set
Top 2%
1.0%
18
Nature Materials
○ 28 papers in training set
Top 0.4%
1.0%
19
Nature
○ 645 papers in training set
Top 9%
1.0%
20
Cell Reports Methods
○ 165 papers in training set
Top 3%
0.9%
21
Developmental Cell
○ 196 papers in training set
Top 4%
0.9%
22
Nano Letters
● 71 papers in training set
Top 1%
0.9%
23
iScience
○ 1154 papers in training set
Top 40%
0.6%
24
Advanced Science
○ 286 papers in training set
Top 10%
0.6%
25
Light: Science & Applications
○ 16 papers in training set
Top 0.3%
0.6%

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.