Back

SARS-CoV-2 infection studies in lung organoids identify TSPAN8 as novel mediator

Hysenaj, L.; Little, S.; Kulhanek, K. R.; Gbenedio, O.; Rodriguez, L.; Shen, A.; Lone, J.-C.; Lupin-Jimenez, L. C.; Bonser, L.; Serwas, N. K.; Bahl, K.; Mick, E.; Li, J. Z.; Ding, V.; Matsumoto, S.; Maishan, M. l.; Fragiadakis, G.; Jablons, D. M.; Langelier, C. R.; Matthay, M.; Ott, M.; Sil, A.; Krummel, M.; Combes, A. J.; Erle, D. M.; Kratz, J. R.; Roose, J. P.

2021-06-02 microbiology
10.1101/2021.06.01.446640 bioRxiv
Show abstract

SARS coronavirus-2 (SARS-CoV-2) is causing a global pandemic with large variation in COVID-19 disease spectrum. SARS-CoV-2 infection requires host receptor ACE2 on lung epithelium, but epithelial underpinnings of variation are largely unknown. We capitalized on comprehensive organoid assays to report remarkable variation in SARS-CoV-2 infection rates of lung organoids from different subjects. Tropism is highest for TUBA- and MUC5AC-positive organoid cells, but levels of TUBA-, MUC5A-, or ACE2-positive cells do not predict infection rate. We identify surface molecule Tetraspanin 8 (TSPAN8) as novel mediator of SARS-CoV-2 infection, which is not downregulated by this specific virus. TSPAN8 levels, prior to infection, strongly correlate with infection rate and TSPAN8-blocking antibodies diminish SARS-CoV-2 infection. We propose TSPAN8 as novel functional biomarker and potential therapeutic target for COVID-19.

Matching journals

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

1
Nature Communications
○ 5641 papers in training set
Top 3%
30.3%
Similar papers in this journal
2
Cell Reports
○ 1498 papers in training set
Top 4%
7.7%
Similar papers in this journal
3
Cell
○ 431 papers in training set
Top 1%
6.1%
Similar papers in this journal
4
Nature
○ 645 papers in training set
Top 3%
5.3%
Similar papers in this journal
5
eLife
● 5828 papers in training set
Top 25%
5.0%
Similar papers in this journal
50% of probability mass above
6
Proceedings of the National Academy of Sciences
● 2444 papers in training set
Top 11%
4.7%
7
Science Advances
● 1243 papers in training set
Top 9%
3.9%
8
iScience
○ 1154 papers in training set
Top 5%
3.9%
9
Cell Reports Medicine
○ 153 papers in training set
Top 2%
2.4%
10
Cell Systems
○ 201 papers in training set
Top 3%
1.7%
11
Science
● 477 papers in training set
Top 6%
1.6%
12
Cell Stem Cell
○ 62 papers in training set
Top 1%
1.6%
13
eBioMedicine
○ 183 papers in training set
Top 3%
1.5%
14
Communications Biology
○ 993 papers in training set
Top 18%
1.4%
15
Cell Research
○ 51 papers in training set
Top 0.8%
1.3%
16
Cell Host & Microbe
126 papers in training set
Top 2%
1.3%
17
Signal Transduction and Targeted Therapy
○ 30 papers in training set
Top 0.4%
1.1%
18
The EMBO Journal
○ 309 papers in training set
Top 5%
1.1%
19
EMBO Reports
○ 263 papers in training set
Top 6%
1.0%
20
Science Immunology
● 88 papers in training set
Top 2%
1.0%
21
Scientific Reports
○ 3612 papers in training set
Top 74%
0.8%
22
Developmental Cell
○ 196 papers in training set
Top 4%
0.8%
23
Nature Microbiology
○ 155 papers in training set
Top 3%
0.8%
24
Nature Genetics
○ 286 papers in training set
Top 6%
0.6%
25
Nature Medicine
○ 125 papers in training set
Top 5%
0.6%
26
Nature Biotechnology
○ 172 papers in training set
Top 5%
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.