Back

Principles of in situ protein sequencing: expansion microscopy-adapted Edman degradation and amino acid recognition

Mitchell, C. M.; Tavana, S. Z.; Peng, J.; Wang, H.; Shi, J.; Zhang, C.; Evgeniou, L.; Domecillo, M.; Wang, S.; Estandian, D. M.; Choueiri, A. G.; Wong, E.; Dohadwala, S.; Polizzi, N.; Kiessling, L. L.; Boyden, E. S.

2026-01-30 biochemistry
10.64898/2026.01.29.702630 bioRxiv
Show abstract

The ability to map protein identity, with resolution sufficient to infer interactions, would support analysis of how proteins work together, or malfunction, in biological processes and diseases. Although several emerging technologies aim towards single-molecule protein sequencing, they require proteins to be removed from the nanoscale spatial context of cells and tissues. Expansion microscopy (ExM) has facilitated a diversity of chemical analyses by isotropically separating molecules throughout a specimen after permeation via a charged hydrogel, followed by gel swelling. Here, we adapt key protein sequencing steps - Edman degradation and amino acid recognition - to the ExM gel context. Using testbed peptides in ExM gels, we show that N-terminal amino acids can be recognized over multiple cycles of in-gel Edman degradation. These results establish principles of in situ protein sequencing and provide a framework for future in situ protein sequencing developments, including the development of higher specificity and affinity amino acid binders.

Matching journals

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

1
Nature Communications
○ 5641 papers in training set
Top 0.5%
42.3%
Similar papers in this journal
2
Journal of the American Chemical Society
● 217 papers in training set
Top 0.6%
6.2%
Similar papers in this journal
3
Analytical Chemistry
● 218 papers in training set
Top 0.7%
5.5%
Similar papers in this journal
50% of probability mass above
4
Nature Chemical Biology
○ 119 papers in training set
Top 0.4%
5.5%
Similar papers in this journal
5
eLife
● 5828 papers in training set
Top 26%
4.8%
Similar papers in this journal
6
Proceedings of the National Academy of Sciences
● 2444 papers in training set
Top 16%
3.2%
7
Molecular & Cellular Proteomics
183 papers in training set
Top 0.9%
2.1%
8
Advanced Science
○ 286 papers in training set
Top 4%
1.9%
9
Cell
○ 431 papers in training set
Top 6%
1.7%
10
Science Advances
● 1243 papers in training set
Top 21%
1.7%
11
Cell Reports Methods
○ 165 papers in training set
Top 2%
1.5%
12
Communications Chemistry
○ 48 papers in training set
Top 0.6%
1.5%
13
ACS Chemical Biology
● 167 papers in training set
Top 2%
1.1%
14
Angewandte Chemie International Edition
○ 93 papers in training set
Top 1%
1.1%
15
ACS Nano
● 113 papers in training set
Top 2%
1.1%
16
Nature Methods
○ 385 papers in training set
Top 6%
1.1%
17
Communications Biology
○ 993 papers in training set
Top 24%
1.1%
18
Nucleic Acids Research
◐ 1281 papers in training set
Top 12%
1.0%
19
Chemical Science
● 73 papers in training set
Top 2%
0.8%
20
Nature Biotechnology
○ 172 papers in training set
Top 4%
0.8%
21
Angewandte Chemie
○ 15 papers in training set
Top 0.2%
0.8%
22
JACS Au
● 43 papers in training set
Top 1.0%
0.6%
23
Nature Chemistry
○ 42 papers in training set
Top 1%
0.6%
24
Journal of Biological Chemistry
○ 690 papers in training set
Top 11%
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.