Back

In vivo spatial coordination with synthetic paracrine signaling

Luo, K.;Ma, Y.;Li, H.;Li, H.;Swift, M.;Dalleska, N.;Farooq, A.;Criado-Hidalgo, E.;Liu, A.;Shapiro, M.;Elowitz, M.

2026-06-29 Synthetic Biology
10.64898/2026.06.26.734902 bioRxiv
Show abstract

The immune system uses paracrine signaling to spatially confine potent responses such as inflammation. A bio-orthogonal synthetic paracrine system could enable engineering of analogous multicellular circuits in which different cell types coordinate their functions in a spatially organized fashion. Here, using the plant hormone auxin as a bio-orthogonal chemical signal, we introduce programmable paracrine circuits that distribute sensing and effector functions to different cell types to spatially restrict responses in mouse xenografts. Cells engineered to express auxin biosynthetic genes generated auxin-dense regions with tunable length scales in vivo. This localized signaling ability enabled design of a multicellular sentinel-effector system, in which THP-1 sentinel cells conditionally produce auxin in regions expressing the tumor-specific antigen EGFRvIII, and Jurkat effector cells respond by locally modulating the activity of a chimeric antigen receptor (CAR). This two-cell type system was able to achieve localized activation of engineered effector cells in vivo. These results establish a foundation for engineering multicellular therapeutic systems that focus responses in specific tissue contexts or disease sites.

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

1
Nature Communications
○ 5641 papers in training set
Top 9%
18.4%
Similar papers in this journal
2
eLife
● 5828 papers in training set
Top 9%
11.0%
Similar papers in this journal
3
Cell
○ 431 papers in training set
Top 0.8%
6.7%
Similar papers in this journal
4
Science Advances
● 1243 papers in training set
Top 3%
6.7%
Similar papers in this journal
5
Nature
○ 645 papers in training set
Top 3%
6.2%
Similar papers in this journal
6
Proceedings of the National Academy of Sciences
● 2444 papers in training set
Top 11%
4.3%
50% of probability mass above
7
Nature Methods
○ 385 papers in training set
Top 3%
3.4%
8
Science
● 477 papers in training set
Top 2%
3.4%
9
Nature Biotechnology
○ 172 papers in training set
Top 1%
3.2%
10
Nature Chemical Biology
○ 119 papers in training set
Top 0.8%
3.2%
11
Nature Biomedical Engineering
○ 47 papers in training set
Top 0.4%
3.2%
12
Cell Reports
○ 1498 papers in training set
Top 15%
2.4%
13
Molecular Cell
○ 350 papers in training set
Top 3%
2.1%
14
Cell Systems
○ 201 papers in training set
Top 3%
1.5%
15
The EMBO Journal
○ 309 papers in training set
Top 4%
1.5%
16
Nature Cell Biology
○ 118 papers in training set
Top 2%
1.3%
17
Molecular Systems Biology
○ 162 papers in training set
Top 2%
1.1%
18
Journal of Cell Biology
● 392 papers in training set
Top 3%
1.1%
19
iScience
○ 1154 papers in training set
Top 32%
1.0%
20
Nature Metabolism
○ 69 papers in training set
Top 2%
1.0%
21
Advanced Science
○ 286 papers in training set
Top 9%
0.8%
22
Developmental Cell
○ 196 papers in training set
Top 5%
0.6%
23
Cell Reports Methods
○ 165 papers in training set
Top 4%
0.6%
24
Nature Genetics
○ 286 papers in training set
Top 5%
0.6%
25
Cancer Cell
○ 42 papers in training set
Top 1%
0.6%
26
EMBO Reports
○ 263 papers in training set
Top 8%
0.6%
27
Nature Immunology
○ 79 papers in training set
Top 2%
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.