清晨好,您是今天最早来到科研通的研友!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您科研之路漫漫前行!

Toolbox Accelerating Glycomics (TAG): Improving Large-Scale Serum Glycomics and Refinement to Identify SALSA-Modified and Rare Glycans

作者
Nobuaki Miura,Hisatoshi Hanamatsu,Ikuko Yokota,Keiko Akasaka‐Manya,Hiroshi Manya,Tamao Endo,Yasuro Shinohara,Jun‐ichi Furukawa
出处
期刊:International Journal of Molecular Sciences [Multidisciplinary Digital Publishing Institute]
卷期号:23 (21): 13097-13097 被引量:3
标识
DOI:10.3390/ijms232113097
摘要

Glycans are involved in many fundamental cellular processes such as growth, differentiation, and morphogenesis. However, their broad structural diversity makes analysis difficult. Glycomics via mass spectrometry has focused on the composition of glycans, but informatics analysis has not kept pace with the development of instrumentation and measurement techniques. We developed Toolbox Accelerating Glycomics (TAG), in which glycans can be added manually to the glycan list that can be freely designed with labels and sialic acid modifications, and fast processing is possible. In the present work, we improved TAG for large-scale analysis such as cohort analysis of serum samples. The sialic acid linkage-specific alkylamidation (SALSA) method converts differences in linkages such as α2,3- and α2,6-linkages of sialic acids into differences in mass. Glycans modified by SALSA and several structures discovered in recent years were added to the glycan list. A routine to generate calibration curves has been implemented to explore quantitation. These improvements are based on redefinitions of residues and glycans in the TAG List to incorporate information on glycans that could not be attributed because it was not assumed in the previous version of TAG. These functions were verified through analysis of purchased sera and 74 spectra with linearity at the level of R2 > 0.8 with 81 estimated glycan structures obtained including some candidate of rare glycans such as those with the N,N’-diacetyllactosediamine structure, suggesting they can be applied to large-scale analyses.

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
lee发布了新的文献求助10
1分钟前
安详的迎丝完成签到 ,获得积分10
1分钟前
1分钟前
lee发布了新的文献求助10
1分钟前
1分钟前
七七完成签到 ,获得积分10
1分钟前
1分钟前
yhtsyy完成签到 ,获得积分10
2分钟前
包容谷雪发布了新的文献求助10
2分钟前
Xu发布了新的文献求助30
2分钟前
思源应助不要太辣辣辣辣采纳,获得10
2分钟前
晴空万里完成签到 ,获得积分10
2分钟前
做实验的猫应助Kolia采纳,获得10
3分钟前
一剑白完成签到 ,获得积分10
3分钟前
3分钟前
叁月二完成签到 ,获得积分10
3分钟前
嘻嘻哈哈应助Kolia采纳,获得10
3分钟前
lee发布了新的文献求助10
3分钟前
3分钟前
Gordon_2020完成签到,获得积分10
3分钟前
且听风吟发布了新的文献求助10
3分钟前
酷波er应助Gordon_2020采纳,获得10
3分钟前
3分钟前
lee发布了新的文献求助10
3分钟前
3分钟前
且听风吟完成签到,获得积分10
3分钟前
cdercder应助Kolia采纳,获得10
3分钟前
cdercder应助Kolia采纳,获得10
4分钟前
drhkc完成签到,获得积分10
4分钟前
5分钟前
脑洞疼应助Dima采纳,获得10
5分钟前
lee发布了新的文献求助10
5分钟前
5分钟前
5分钟前
Dima发布了新的文献求助10
5分钟前
5分钟前
lee发布了新的文献求助10
5分钟前
Dima完成签到,获得积分10
5分钟前
5分钟前
lee发布了新的文献求助10
6分钟前
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
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
Practical Process Research and Development 500
Discerning Saints: Moralization of Intrinsic Motivation and Selective Prosociality at Work 500
Handbuch Trainingswissenschaft – Trainingslehre 500
Additive Manufacturing Design and Applications (ASM Handbook, Volume 24A) 500
Exploring Entrepreneurial Psychology Through AI 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 7585933
求助须知:如何正确求助?哪些是违规求助? 9164225
关于积分的说明 19612008
捐赠科研通 7166788
什么是DOI,文献DOI怎么找? 3266627
关于科研通互助平台的介绍 2431638
邀请新用户注册赠送积分活动 2258336