Single‐cell and bulk transcriptomic sequencing reveals tryptophan metabolism‐linked biomarkers of obesity

转录组 生物 脂肪组织 基因 免疫系统 基因表达谱 色氨酸 肥胖 基因表达 计算生物学 犬尿氨酸 色氨酸代谢 炎症 基因调控网络 发起人 下调和上调 遗传学 生物信息学 基因表达调控 单变量 RNA序列 细胞 逻辑回归 生物标志物 免疫学 分子生物学 白色脂肪组织 转录因子 单变量分析
作者
Yiyi Zhang,Bo Peng,Hui Zhou,Hui Zhou
出处
期刊:FEBS Journal [Wiley]
标识
DOI:10.1111/febs.70628
摘要

Obesity remains a major public health challenge, and the contribution of tryptophan metabolism to obesity-associated inflammation remains incompletely understood. Here, we integrated bulk transcriptomic and single-cell RNA sequencing datasets from the Gene Expression Omnibus (GSE25401, GSE217007, GSE166047, and GSE176171) with a curated set of tryptophan metabolism-related genes. Weighted gene co-expression network analysis and differential expression analysis identified 95 differentially expressed tryptophan metabolism-related genes. Protein-protein interaction analysis, univariate logistic regression, and machine-learning models including random forest, support vector machine, and generalized linear model prioritized five biomarkers: SPI1, ITGB2, CD86, CYBB, and TLR8. All five genes were upregulated in obesity and were enriched in immune-related pathways. Single-cell analysis identified major adipose tissue cell populations and showed that SPI1, CD86, CYBB, and TLR8 were predominantly expressed in monocytes, whereas ITGB2 was enriched in natural killer cells. Immune infiltration analysis further supported close associations between these biomarkers and obesity-related immune dysregulation. RT-qPCR validation confirmed increased expression of ITGB2, CD86, and SPI1 in adipose tissue from obese individuals, whereas CYBB and TLR8 were not significantly different between groups. Together, these findings identify tryptophan metabolism-linked biomarkers associated with obesity and suggest that their main translational relevance may lie in stratifying or targeting obesity-associated secondary inflammation.
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
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
爱吃芹菜小炒的寻梦人完成签到,获得积分20
1秒前
zzzzzyq完成签到 ,获得积分10
1秒前
1秒前
惠鹏飞发布了新的文献求助10
1秒前
1秒前
1秒前
CodeCraft应助CC0113采纳,获得10
2秒前
孙梦涵完成签到,获得积分10
2秒前
科研通AI6.4应助CC0113采纳,获得10
2秒前
乱红完成签到 ,获得积分10
2秒前
科研通AI6.4应助CC0113采纳,获得10
2秒前
小马甲应助听雨落声采纳,获得10
3秒前
SciGPT应助pamper采纳,获得10
3秒前
3秒前
薯条完成签到,获得积分10
3秒前
万能图书馆应助纪洪森采纳,获得10
4秒前
wanci应助科研通管家采纳,获得10
4秒前
我是老大应助科研通管家采纳,获得10
5秒前
研友_VZG7GZ应助科研通管家采纳,获得10
5秒前
上官若男应助科研通管家采纳,获得10
5秒前
FashionBoy应助科研通管家采纳,获得10
5秒前
情怀应助YMC采纳,获得10
5秒前
5秒前
充电宝应助科研通管家采纳,获得10
5秒前
5秒前
丘比特应助科研通管家采纳,获得10
6秒前
隐形曼青应助科研通管家采纳,获得10
6秒前
深情安青应助梨花采纳,获得10
6秒前
orixero应助科研通管家采纳,获得10
6秒前
6秒前
所所应助科研通管家采纳,获得10
6秒前
komorebi发布了新的文献求助10
6秒前
思源应助科研通管家采纳,获得10
6秒前
GU发布了新的文献求助10
6秒前
完美世界应助九耳兔采纳,获得10
6秒前
赘婿应助科研通管家采纳,获得10
6秒前
Hello应助GaYa采纳,获得10
7秒前
天天快乐应助科研通管家采纳,获得30
7秒前
7秒前
Ava应助科研通管家采纳,获得10
7秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Essentials of Carbohydrate Chemistry and Biochemistry, 4th Edition 800
Organizational Behavior 510
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
CLSI VET01S-2024 Performance Standards for Antimicrobial Disk and Dilution Susceptibility Tests for Bacteria Isolated From Animals (7th Ed) 500
A Case Study on Hotels as Noncongregate Emergency Living Accommodations for Returning Citizens 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 计算机科学 化学工程 工程类 有机化学 物理 复合材料 生物化学 内科学 细胞生物学 基因 遗传学 免疫学 冶金 光电子学 癌症研究
热门帖子
关注 科研通微信公众号,转发送积分 7764817
求助须知:如何正确求助?哪些是违规求助? 9309121
关于积分的说明 20309262
捐赠科研通 7349614
什么是DOI,文献DOI怎么找? 3314612
关于科研通互助平台的介绍 2463990
邀请新用户注册赠送积分活动 2328915