The Role of Fucose-Containing Glycan Motifs Across Taxonomic Kingdoms

作者
Luc Thomès,Daniel Bojar
出处
期刊:Frontiers in Molecular Biosciences [Frontiers Media]
卷期号:8: 755577-755577 被引量:26
标识
DOI:10.3389/fmolb.2021.755577
摘要

The extraordinary diversity of glycans leads to large differences in the glycomes of different kingdoms of life. Yet, while most monosaccharides are solely found in certain taxonomic groups, there is a small set of monosaccharides with widespread distribution across nearly all domains of life. These general monosaccharides are particularly relevant for glycan motifs, as they can readily be used by commensals and pathogens to mimic host glycans or hijack existing glycan recognition systems. Among these, the monosaccharide fucose is especially interesting, as it frequently presents itself as a terminal monosaccharide, primed for interaction with proteins. Here, we analyze fucose-containing glycan motifs across all taxonomic kingdoms. Using a hereby presented large species-specific glycan dataset and a plethora of methods for glycan-focused bioinformatics and machine learning, we identify characteristic as well as shared fucose-containing glycan motifs for various taxonomic groups, demonstrating clear differences in fucose usage. Even within domains, fucose is used differentially based on an organism’s physiology and habitat. We particularly highlight differences in fucose-containing motifs between vertebrates and invertebrates. With the example of pathogenic and non-pathogenic Escherichia coli strains, we also demonstrate the importance of fucose-containing motifs in molecular mimicry and thereby pathogenic potential. We envision that this study will shed light on an important class of glycan motifs, with potential new insights into the role of fucosylated glycans in symbiosis, pathogenicity, and immunity.

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
Anonymous举报月月求助涉嫌违规
刚刚
刚刚
bulingbuling完成签到 ,获得积分10
1秒前
xzx发布了新的文献求助10
2秒前
3秒前
5秒前
5秒前
科研通AI6.2应助掏粪男孩采纳,获得10
6秒前
xx发布了新的文献求助10
6秒前
orixero应助浙理小祝采纳,获得10
6秒前
生而追梦不止完成签到,获得积分0
6秒前
前进发布了新的文献求助10
7秒前
Dr_Shi完成签到,获得积分10
10秒前
10秒前
上官若男应助kalcspin采纳,获得10
11秒前
科研通AI6.4应助辛勤秋双采纳,获得10
12秒前
自由抽屉发布了新的文献求助10
13秒前
14秒前
兴奋的天蓉完成签到 ,获得积分10
14秒前
111完成签到 ,获得积分10
15秒前
科研通AI6.4应助璐璐采纳,获得10
16秒前
16秒前
16秒前
曾丸子发布了新的文献求助10
17秒前
17秒前
大知闲闲应助shinn采纳,获得10
18秒前
悦耳雪巧完成签到 ,获得积分10
19秒前
科研通AI6.4应助掏粪男孩采纳,获得30
19秒前
赘婿应助LQ采纳,获得30
19秒前
乾巧发布了新的文献求助10
19秒前
19秒前
科研通AI6.4应助Qawsed采纳,获得10
20秒前
小蛋发布了新的文献求助10
21秒前
英俊的一笑完成签到 ,获得积分10
22秒前
浙理小祝发布了新的文献求助10
22秒前
大胆半双完成签到,获得积分10
22秒前
24秒前
guz完成签到,获得积分10
24秒前
26秒前
爆米花应助个性的薯片采纳,获得10
26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
An Introduction to Foreign Language Learning and Teaching 750
China Pluperfect I: Epistemology of Past and Outside in Chinese Art 520
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
Cosmos as Art Object: Studies in Plato's Timaeus and Other Dialogues 500
What is the Future of Psychotherapy in Digital Age? Technology, AI Bots, and Psychotherapy after Covid 444
煤炭地下气化渗流燃烧方法的研究 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7632002
求助须知:如何正确求助?哪些是违规求助? 9206365
关于积分的说明 19744385
捐赠科研通 7201289
什么是DOI,文献DOI怎么找? 3274729
关于科研通互助平台的介绍 2436616
邀请新用户注册赠送积分活动 2271356