Back

The REFLEX system enables in vivo identification of perivascular angiogenic macrophages in the heart

Sato, T.; Isagawa, T.; Kawakami, T.; Hosokawa, S.; Ito, M.; Sawaki, D.; Sato, S.; Nakagama, Y.; Ono, K.; Ariunbold, C.-E.; Pham, T. T.; Tanaka, R.; Kurozumi, A.; Semba, H.; Wake, M.; Minatsuki, S.; Higashikuni, Y.; Suzuki, N.; Asagiri, M.; Harada, H.; Stockmann, C.; Hirota, Y.; Kido, Y.; Kubota, Y.; Kohro, T.; Kuchimaru, T.; Manabe, I.; Komuro, I.; Takeda, N.

2026-01-30 cell biology
10.64898/2026.01.27.702189 bioRxiv
Show abstract

Direct identification of physically interacting cells in vivo remains challenging because conventional interactome analyses infer signaling partners from transcriptomes and cannot reveal which cells are in direct contact. In pressure-overload induced cardiac remodeling, VEGF-A plays a central role in the maintenance of vascular integrity and cardiac function. However, the cell type which produces VEGF-A and how the VEGF-A peptide is delivered to vascular endothelial cells remains unclear. Here, we developed a genetically encoded platform that combines REFLEX mice with HUNTERuni-seq, enabling unbiased detection and transcriptional profiling of the cells that physically interact with vascular endothelial cells. The REFLEX and HUNTERuni-seq approach identified subpopulations of Vegfa positive macrophages which we named perivascular angiogenic macrophages (PVAMs). Although the amount of VEGF-A in PVAMs is small, loss of VEGF-A in PVAMs impaired angiogenesis and systolic function during pressure overload. We additionally show that direct contact between PVAMs and endothelial cells is critical for the delivery of VEGF-A to endothelial cells. Conventional interactome analysis predicted that cardiomyocytes as dominant sources of VEGF-A in the heart. However, cardiomyocyte Vegfa deletion had no effect on capillary density nor systolic function in a model of heart failure. These results suggest that VEGF-A signaling does not rely on free diffusion through the interstitium and that cellular proximity and physical contact between PVAMs and endothelial cells are the key determinants of effective signal delivery. Together, these findings establish REFLEX and HUNTERuni-seq as a versatile platform for uncovering biologically critical cell-to-cell interactions and provide new insight into intercellular communication in pathological tissue contexts.

Matching journals

The top 5 journals account for 50% of the predicted probability mass.

1
Developmental Cell
168 papers in training set
Top 0.3%
22.6%
2
Nature Cardiovascular Research
28 papers in training set
Top 0.1%
10.1%
3
Nature Communications
4913 papers in training set
Top 21%
9.2%
4
Cell Reports
1338 papers in training set
Top 6%
6.8%
5
Circulation
66 papers in training set
Top 0.8%
4.3%
50% of probability mass above
6
eLife
5422 papers in training set
Top 25%
3.6%
7
Molecular Cell
308 papers in training set
Top 4%
3.6%
8
Cell Systems
167 papers in training set
Top 4%
3.1%
9
Science Translational Medicine
111 papers in training set
Top 2%
2.1%
10
Cell
370 papers in training set
Top 9%
2.1%
11
Nature Cell Biology
99 papers in training set
Top 2%
2.1%
12
Circulation Research
39 papers in training set
Top 0.6%
1.9%
13
Science Advances
1098 papers in training set
Top 14%
1.9%
14
PLOS Biology
408 papers in training set
Top 10%
1.7%
15
EMBO reports
136 papers in training set
Top 3%
1.5%
16
Nucleic Acids Research
1128 papers in training set
Top 13%
1.3%
17
JCI Insight
241 papers in training set
Top 5%
1.2%
18
iScience
1063 papers in training set
Top 23%
1.1%
19
Science
429 papers in training set
Top 17%
1.0%
20
Advanced Science
249 papers in training set
Top 15%
1.0%
21
Proceedings of the National Academy of Sciences
2130 papers in training set
Top 40%
1.0%
22
Cell Stem Cell
57 papers in training set
Top 2%
1.0%
23
Nature
575 papers in training set
Top 14%
0.9%
24
Cell Reports Medicine
140 papers in training set
Top 6%
0.9%
25
Development
440 papers in training set
Top 3%
0.8%
26
Scientific Reports
3102 papers in training set
Top 78%
0.6%
27
Cardiovascular Research
33 papers in training set
Top 1%
0.6%
28
The EMBO Journal
267 papers in training set
Top 6%
0.6%