Back

H3N2 influenza virus tropism shifts to glycan receptors on tracheal ciliated cells

Kikuchi, C.; Antonopoulos, A.; Wang, S.; Biyasheva, A.; Chien, Y.-C.; Bharat, A.; McBride, R.; Nycholat, C. M.; Thompson, A. J.; Dell, A.; Khoo, K.-H.; Schleimer, R.; Haslam, S. M.; Paulson, J. C.

2025-09-13 microbiology
10.1101/2025.09.12.675939 bioRxiv
Show abstract

Human H3N2 influenza viruses, introduced during the 1968 pandemic, have evolved to recognize human-type sialic acid-containing receptors (Neu5Ac2-6Gal) extended with at least three LacNAc (Gal{beta}1-4GlcNAc) repeats. To investigate this restriction in the context of virus attachment to the airway epithelium, we comprehensively analyzed the glycome of human nasal and tracheal epithelial cells. Using a synthetic N-glycan library that reflects the structural diversity of the human airway glycome, we found that only bi-antennary N-glycans with extended human-type receptors on at least one branch serve as receptors for the recent H3 hemagglutinins (HAs). Such receptors are found on tracheal epithelium but are deficient in nasal epithelium. Immunofluorescence analysis on human trachea reveals that recent H3 HAs preferentially attach to ciliated cells, consistent with single-cell RNA sequencing analysis indicating that these cells express glycosyltransferases that produce extended glycan chains. These findings suggest that H3N2 viruses have developed a tropism for tracheal ciliated cells. (146 words)

Matching journals

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

1
Nature Communications
○ 5641 papers in training set
Top 8%
19.0%
Similar papers in this journal
2
Cell
○ 431 papers in training set
Top 0.1%
13.3%
Similar papers in this journal
3
Cell Reports
○ 1498 papers in training set
Top 0.7%
13.3%
Similar papers in this journal
4
PNAS Nexus
◐ 159 papers in training set
Top 0.1%
4.2%
Similar papers in this journal
5
Science Advances
● 1243 papers in training set
Top 8%
4.2%
Similar papers in this journal
50% of probability mass above
6
Proceedings of the National Academy of Sciences
● 2444 papers in training set
Top 15%
3.3%
7
Science
● 477 papers in training set
Top 2%
3.3%
8
Journal of Virology
● 499 papers in training set
Top 2%
2.5%
9
mBio
● 833 papers in training set
Top 6%
2.5%
10
Journal of the American Chemical Society
● 217 papers in training set
Top 1%
2.2%
11
iScience
○ 1154 papers in training set
Top 15%
2.0%
12
Cell Chemical Biology
○ 94 papers in training set
Top 0.7%
1.8%
13
Immunity
○ 67 papers in training set
Top 0.9%
1.7%
14
PLOS Biology
● 486 papers in training set
Top 4%
1.7%
15
eLife
● 5828 papers in training set
Top 54%
1.5%
16
Cell Host & Microbe
126 papers in training set
Top 2%
1.2%
17
PLOS Pathogens
● 820 papers in training set
Top 7%
1.2%
18
Cell Reports Medicine
○ 153 papers in training set
Top 3%
1.2%
19
ACS Central Science
● 71 papers in training set
Top 1%
1.2%
20
Communications Biology
○ 993 papers in training set
Top 23%
1.1%
21
Signal Transduction and Targeted Therapy
○ 30 papers in training set
Top 0.4%
1.1%
22
Glycobiology
◐ 35 papers in training set
Top 0.2%
1.0%
23
Nature Microbiology
○ 155 papers in training set
Top 3%
1.0%
24
Science Translational Medicine
● 127 papers in training set
Top 3%
0.9%
25
Nature Chemical Biology
○ 119 papers in training set
Top 3%
0.9%
26
eBioMedicine
○ 183 papers in training set
Top 6%
0.9%
27
Angewandte Chemie
○ 15 papers in training set
Top 0.2%
0.9%
28
Journal of Proteome Research
● 234 papers in training set
Top 2%
0.6%
29
Nature
○ 645 papers in training set
Top 11%
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.