Back

Rapid catecholamine trafficking regulates neutrophil functions and neutrophil-platelet interactions

Mohr, J. M.; Schmitz, A.; Dinarvand, M.; Sangeetha, S.; Hill, B. F.; Wulfert, F.; Neubert, E.; Shumanska, M.; Kaushik, S.; Kartaschew, L.; Bogeski, I.; Daniel, J.; Jung, S.; Eble, J.; Erpenbeck, L.; Kruss, S.

2025-01-28 immunology
10.1101/2025.01.27.634021 bioRxiv
Show abstract

Neutrophils are key effector cells of the innate immune system that respond to small signaling molecules regulating immune responses. For a long time, similarities between neuronal and immune cells have been discussed. Here, we show that human neutrophils rapidly take up, package and use catecholamine neurotransmitters such as dopamine or epinephrine via the machinery known from neurons. Uptake and release of catecholamines as well as trafficking and packaging into MPO/VMAT2-positive primary vesicles is visualized with false fluorescent neurotransmitters. We also directly image the fast (> 10 s) and transient release of catecholamines from neutrophils with near infrared fluorescent nanosensors. Serotonin or activated platelets trigger calcium (Ca2+) signaling and consequently exocytosis of catecholamines. They reduce NET-formation but increase platelet aggregation. Thus, we establish similarities between neurons and neutrophils and identify a paracrine neutrophil-platelet feedback loop relevant for inflammatory and coagulatory conditions.

Matching journals

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

1
Proceedings of the National Academy of Sciences
● 2444 papers in training set
Top 0.4%
26.9%
Similar papers in this journal
2
Science Advances
● 1243 papers in training set
Top 0.1%
18.8%
Similar papers in this journal
3
eLife
● 5828 papers in training set
Top 15%
7.4%
Similar papers in this journal
50% of probability mass above
4
Nano Letters
● 71 papers in training set
Top 0.2%
5.6%
Similar papers in this journal
5
Nature Communications
○ 5641 papers in training set
Top 29%
4.9%
Similar papers in this journal
6
Cell
○ 431 papers in training set
Top 3%
3.3%
7
iScience
○ 1154 papers in training set
Top 6%
3.3%
8
ACS Nano
● 113 papers in training set
Top 0.7%
3.3%
9
Communications Biology
○ 993 papers in training set
Top 12%
1.9%
10
Nature Chemical Biology
○ 119 papers in training set
Top 1%
1.8%
11
PNAS Nexus
◐ 159 papers in training set
Top 2%
1.4%
12
Journal of the American Chemical Society
● 217 papers in training set
Top 2%
1.4%
13
Advanced Science
○ 286 papers in training set
Top 6%
1.1%
14
Small
○ 78 papers in training set
Top 1%
1.1%
15
Cell Reports
○ 1498 papers in training set
Top 25%
1.0%
16
ACS Central Science
● 71 papers in training set
Top 1%
1.0%
17
Advanced Materials
○ 56 papers in training set
Top 0.9%
1.0%
18
Cell Reports Methods
○ 165 papers in training set
Top 3%
1.0%
19
PLOS Biology
● 486 papers in training set
Top 11%
0.9%
20
Journal of Biological Chemistry
○ 690 papers in training set
Top 9%
0.9%
21
mBio
● 833 papers in training set
Top 11%
0.9%
22
Scientific Reports
○ 3612 papers in training set
Top 76%
0.6%
23
ChemBioChem
○ 55 papers in training set
Top 1%
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.