A spatial sequencing atlas of age-induced changes in the lung during influenza infection

地图集(解剖学) 生物 肺部感染 进化生物学 计算生物学 地图学 病毒学 地理 医学 古生物学 内科学
作者
Moujtaba Y. Kasmani,Paytsar Topchyan,Ashley K. Brown,Ryan Brown,Xiaopeng Wu,Yao Chen,Achia Khatun,Donia Alson,Yue Wu,Robert T. Burns,Chien‐Wei Lin,Matthew Kudek,Jie Sun,Weiguo Cui
出处
期刊:Nature Communications [Springer Nature]
卷期号:14 (1) 被引量:5
标识
DOI:10.1038/s41467-023-42021-y
摘要

Abstract Influenza virus infection causes increased morbidity and mortality in the elderly. Aging impairs the immune response to influenza, both intrinsically and because of altered interactions with endothelial and pulmonary epithelial cells. To characterize these changes, we performed single-cell RNA sequencing (scRNA-seq), spatial transcriptomics, and bulk RNA sequencing (bulk RNA-seq) on lung tissue from young and aged female mice at days 0, 3, and 9 post-influenza infection. Our analyses identified dozens of key genes differentially expressed in kinetic, age-dependent, and cell type-specific manners. Aged immune cells exhibited altered inflammatory, memory, and chemotactic profiles. Aged endothelial cells demonstrated characteristics of reduced vascular wound healing and a prothrombotic state. Spatial transcriptomics identified novel profibrotic and antifibrotic markers expressed by epithelial and non-epithelial cells, highlighting the complex networks that promote fibrosis in aged lungs. Bulk RNA-seq generated a timeline of global transcriptional activity, showing increased expression of genes involved in inflammation and coagulation in aged lungs. Our work provides an atlas of high-throughput sequencing methodologies that can be used to investigate age-related changes in the response to influenza virus, identify novel cell-cell interactions for further study, and ultimately uncover potential therapeutic targets to improve health outcomes in the elderly following influenza infection.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
大幅提高文件上传限制,最高150M (2024-4-1)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
1秒前
小木子发布了新的文献求助10
3秒前
shinysparrow应助hulala采纳,获得10
4秒前
Song发布了新的文献求助10
4秒前
4秒前
淡淡的靳完成签到,获得积分10
4秒前
小蘑菇应助huangjing采纳,获得10
5秒前
6秒前
小张同学读研版完成签到,获得积分10
9秒前
杨yang发布了新的文献求助10
10秒前
13秒前
浙江嘉兴完成签到,获得积分10
13秒前
wanci应助千万别取这个名采纳,获得20
14秒前
14秒前
Atan完成签到,获得积分10
15秒前
huangjing完成签到,获得积分10
16秒前
ZZ应助自信傲柔采纳,获得10
16秒前
脑洞疼应助小杰采纳,获得10
16秒前
17秒前
三横一竖发布了新的文献求助10
18秒前
李健应助科研通管家采纳,获得10
19秒前
李爱国应助科研通管家采纳,获得10
19秒前
寻寻觅觅呢应助科研通管家采纳,获得100
19秒前
Hello应助科研通管家采纳,获得10
19秒前
搜集达人应助科研通管家采纳,获得10
19秒前
小二郎应助科研通管家采纳,获得10
19秒前
19秒前
123发布了新的文献求助10
19秒前
20秒前
22秒前
huangjing发布了新的文献求助10
22秒前
颜路完成签到,获得积分10
22秒前
23秒前
白子完成签到,获得积分10
23秒前
24秒前
24秒前
27秒前
Mike001发布了新的文献求助10
27秒前
11发布了新的文献求助10
28秒前
之桃完成签到,获得积分10
28秒前
高分求助中
Manual of Clinical Microbiology, 4 Volume Set (ASM Books) 13th Edition 1000
Sport in der Antike 800
Aspect and Predication: The Semantics of Argument Structure 666
De arte gymnastica. The art of gymnastics 600
少脉山油柑叶的化学成分研究 530
Berns Ziesemer - Maos deutscher Topagent: Wie China die Bundesrepublik eroberte 500
Stephen R. Mackinnon - Chen Hansheng: China’s Last Romantic Revolutionary (2023) 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 有机化学 工程类 生物化学 纳米技术 物理 内科学 计算机科学 化学工程 复合材料 遗传学 基因 物理化学 催化作用 电极 光电子学 量子力学
热门帖子
关注 科研通微信公众号,转发送积分 2411420
求助须知:如何正确求助?哪些是违规求助? 2106309
关于积分的说明 5322753
捐赠科研通 1833814
什么是DOI,文献DOI怎么找? 913812
版权声明 560875
科研通“疑难数据库(出版商)”最低求助积分说明 488598