Back

Cytosolic Proliferating Cell Nuclear Antigen (PCNA) interacts with S100A8 and controls an inflammatory subset of neutrophils in COVID-19

Formiga, R.; Pesenti, L.; Ladjemi, M. Z.; Andrieu, M.; Many, S.; Karunanithy, V.; Bailly, K.; Dhote, T.; Starick, M.; Lummertz da Rocha, E.; Puig Lombardi, E.; Frachet, P.; Granger, V.; de Chaisemartin, L.; Chollet-Martin, S.; Mouthon, L.; Spiller, F.; Hosmalin, A.; Hurtado-Nedelec, M.; Martin, C.; Pene, F.; Burgel, P.-R.; Tourneur, L.; Witko-Sarsat, V.

2022-10-13 infectious diseases
10.1101/2022.10.12.22280984 medRxiv
Show abstract

Neutrophils are key players in the hyperinflammatory response upon SARS-CoV-2 infection. We have previously described that cytosolic proliferating cell nuclear antigen (PCNA) controls neutrophil survival and NADPH oxidase-dependent ROS production. We here show that both PCNA and S100A8 expression and interaction were elevated in neutrophils from patients with COVID-19 compared to healthy donors and this was correlated with disease severity. Increased PCNA expression was accompanied by a decreased apoptosis and increased NADPH-oxidase activity in neutrophils from COVID-19 patients compared to healthy donors. These effects, as well as the interaction between PCNA and S100A8, were potently counteracted by T2 amino alcohol (T2AA), a PCNA inhibitor, demonstrating that the PCNA scaffold orchestrated neutrophil activation. Notably, the interaction between PCNA-S100A8 was more intense in the CD16high-CD62Llow activated neutrophil subset. We propose that PCNA-S100A8 complex acts as potential driver for neutrophil dysregulation in COVID-19 and show for the first time that the PCNA scaffold is a decisive component of both neutrophil activation and heterogeneity.

Matching journals

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

1
JCI Insight
● 277 papers in training set
Top 0.2%
12.7%
Similar papers in this journal
2
Frontiers in Immunology
○ 638 papers in training set
Top 0.8%
12.7%
Similar papers in this journal
3
Journal of Leukocyte Biology
◐ 42 papers in training set
Top 0.1%
7.9%
Similar papers in this journal
4
Journal of Clinical Investigation
● 179 papers in training set
Top 0.7%
5.5%
Similar papers in this journal
5
Cell Death & Disease
147 papers in training set
Top 0.4%
5.5%
6
Life Science Alliance
● 285 papers in training set
Top 0.4%
5.5%
Similar papers in this journal
7
Scientific Reports
○ 3612 papers in training set
Top 19%
4.8%
50% of probability mass above
8
iScience
○ 1154 papers in training set
Top 4%
4.0%
9
Cell Death Discovery
○ 58 papers in training set
Top 0.2%
3.2%
10
Nature Communications
○ 5641 papers in training set
Top 40%
2.4%
11
International Journal of Molecular Sciences
○ 494 papers in training set
Top 6%
2.1%
12
eBioMedicine
○ 183 papers in training set
Top 2%
2.1%
13
Haematologica
● 25 papers in training set
Top 0.3%
2.1%
14
Clinical & Translational Immunology
○ 22 papers in training set
Top 0.1%
1.7%
15
Cell Reports
○ 1498 papers in training set
Top 21%
1.4%
16
Free Radical Biology and Medicine
○ 36 papers in training set
Top 0.4%
1.3%
17
The FASEB Journal
○ 194 papers in training set
Top 4%
1.1%
18
Signal Transduction and Targeted Therapy
○ 30 papers in training set
Top 0.4%
1.1%
19
eLife
● 5828 papers in training set
Top 59%
1.1%
20
Journal of Hematology & Oncology
○ 10 papers in training set
Top 0.2%
1.1%
21
PLOS Pathogens
● 820 papers in training set
Top 9%
0.9%
22
Cell Reports Medicine
○ 153 papers in training set
Top 5%
0.8%
23
Theranostics
● 37 papers in training set
Top 1%
0.8%
24
Blood Advances
● 62 papers in training set
Top 1%
0.8%
25
EMBO Molecular Medicine
○ 95 papers in training set
Top 2%
0.8%
26
Nature Immunology
○ 79 papers in training set
Top 2%
0.6%
27
The Journal of Immunology
◐ 166 papers in training set
Top 3%
0.6%
28
Clinical Immunology
○ 21 papers in training set
Top 0.4%
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.