Back

Measuring the co-localization and dynamics of mobile proteins in live cells undergoing signaling responses

Shelby, S. A.; Shaw, T. R.; Veatch, S. L.

2022-10-17 biophysics
10.1101/2022.10.17.511423 bioRxiv
Show abstract

ii.Summary/AbstractSingle molecule imaging in live cells enables the study of protein interactions and dynamics as they participate in signaling processes. When combined with fluorophores that stochastically transition between fluorescent and reversible dark states, as in super-resolution localization imaging, labeled molecules can be visualized in single cells over time. This improvement in sampling enables the study of extended cellular responses at the resolution of single molecule localization. This chapter provides optimized experimental and analytical methods used to quantify protein interactions and dynamics within the membranes of adhered live cells. Importantly, the use of pair-correlation functions resolved in both space and time allows researchers to probe interactions between proteins on biologically relevant distance and time-scales, even though fluorescence localization methods typically require long times to assemble well-sampled reconstructed images. We describe an application of this approach to measure protein interactions in B cell receptor signaling and include sample analysis code for post-processing of imaging data. These methods are quantitative, sensitive, and broadly applicable to a range of signaling systems.

Matching journals

The top 7 journals account for 50% of the predicted probability mass.

1
Biophysical Journal
○ 631 papers in training set
Top 0.6%
11.8%
Similar papers in this journal
2
PLOS ONE
● 5266 papers in training set
Top 21%
7.8%
Similar papers in this journal
3
Methods
○ 34 papers in training set
Top 0.1%
7.8%
Similar papers in this journal
4
Biomedical Optics Express
● 95 papers in training set
Top 0.2%
7.8%
Similar papers in this journal
5
Nature Protocols
○ 33 papers in training set
Top 0.1%
6.7%
Similar papers in this journal
6
Biophysical Reports
○ 37 papers in training set
Top 0.1%
5.4%
7
Scientific Reports
○ 3612 papers in training set
Top 23%
4.3%
50% of probability mass above
8
Journal of Visualized Experiments
● 34 papers in training set
Top 0.2%
4.0%
9
eLife
● 5828 papers in training set
Top 36%
3.2%
10
Molecular Biology of the Cell
● 311 papers in training set
Top 1%
3.2%
11
ACS Photonics
● 13 papers in training set
Top 0.1%
2.6%
12
Journal of Microscopy
○ 20 papers in training set
Top 0.1%
2.4%
13
Optics Express
● 26 papers in training set
Top 0.1%
2.4%
14
Protein Science
○ 246 papers in training set
Top 2%
2.1%
15
Nature Methods
○ 385 papers in training set
Top 4%
2.1%
16
Biological Imaging
◐ 15 papers in training set
Top 0.2%
1.3%
17
PLOS Computational Biology
● 1863 papers in training set
Top 17%
1.1%
18
BMC Methods
○ 15 papers in training set
Top 0.1%
1.1%
19
Wellcome Open Research
○ 67 papers in training set
Top 0.8%
1.1%
20
Biology Open
● 156 papers in training set
Top 3%
1.0%
21
Cell Reports Methods
○ 165 papers in training set
Top 3%
1.0%
22
Analytical Biochemistry
○ 26 papers in training set
Top 0.5%
0.8%
23
npj Imaging
○ 12 papers in training set
Top 0.2%
0.8%
24
The Journal of Physical Chemistry B
● 167 papers in training set
Top 2%
0.8%
25
Talanta
○ 14 papers in training set
Top 0.4%
0.6%
26
BMC Bioinformatics
○ 457 papers in training set
Top 6%
0.6%
27
Proceedings of the National Academy of Sciences
● 2444 papers in training set
Top 45%
0.6%
28
Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences
● 12 papers in training set
Top 0.2%
0.6%
29
Nature Communications
○ 5641 papers in training set
Top 59%
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.