Current status of MALDI-TOF mass spectrometry in clinical microbiology

质谱法 临床微生物学 鉴定(生物学) 基质辅助激光解吸/电离 分析物 样品制备 色谱法 微生物学 计算生物学 化学
作者
Tsung Yun Hou,Chuan Chiang-Ni,Shih Hua Teng
出处
期刊:Journal of Food and Drug Analysis [The Journal of Food and Drug Analysis (JFDA), Food and Drug Administration, Taiwan (TFDA)]
卷期号:27 (2): 404-414 被引量:155
标识
DOI:10.1016/j.jfda.2019.01.001
摘要

Mass spectrometry (MS) is a type of analysis used to determine what molecules make up a sample, based on the mass spectrum that are created by the ions. Mass spectrometers are able to perform traditional target analyte identification and quantitation; however, they may also be used within a clinical setting for the rapid identification of bacteria. The causative agent in sepsis is changed over time, and clinical decisions affecting the management of infections are often based on the outcomes of bacterial identification. Therefore, it is essential that such identifications are performed quickly and interpreted correctly. Matrix-assisted laser desorption/ionization-time of flight (MALDI-TOF) mass spectrometer is one of the most popular MS instruments used in biology, due to its rapid and precise identification of genus and species of an extensive range of Gram-negative and -positive bacteria. Microorganism identification by Mass spectrometry is based on identifying a characteristic spectrum of each species and then matched with a large database within the instrument. The present review gives a contemporary perspective on the challenges and opportunities for bacterial identification as well as a written report of how technological innovation has advanced MS. Future clinical applications will also be addressed, particularly the use of MALDI-TOF MS in the field of microbiology for the identification and the analysis of antibiotic resistance.
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
wang完成签到 ,获得积分10
2秒前
cy发布了新的文献求助10
3秒前
3秒前
yanaftdl完成签到,获得积分20
4秒前
Endlessway应助敏感绫萱采纳,获得10
4秒前
科研通AI2S应助何文军采纳,获得10
5秒前
wanci应助121314wld采纳,获得10
6秒前
玫瑰遇上奶油完成签到,获得积分10
7秒前
科研通AI2S应助乐观师采纳,获得10
7秒前
紫色奶萨完成签到,获得积分10
8秒前
8秒前
威武鸽子完成签到,获得积分10
8秒前
哇哇卡哇发布了新的文献求助10
10秒前
别管发布了新的文献求助10
10秒前
紫金之巅完成签到 ,获得积分10
11秒前
11秒前
11秒前
111完成签到,获得积分20
12秒前
令狐晓博完成签到,获得积分0
13秒前
搜集达人应助xkyasc采纳,获得10
13秒前
科研通AI2S应助田柾国采纳,获得10
14秒前
15秒前
科研通AI2S应助斯文谷秋采纳,获得10
15秒前
zz完成签到,获得积分10
15秒前
lin完成签到 ,获得积分10
16秒前
16秒前
NexusExplorer应助Esfuerzo采纳,获得10
16秒前
mengbo完成签到,获得积分10
17秒前
敏感绫萱完成签到,获得积分10
17秒前
pp陶发布了新的文献求助10
17秒前
邓豪完成签到 ,获得积分10
17秒前
18秒前
食梦貊完成签到 ,获得积分10
18秒前
我爱学习发布了新的文献求助10
19秒前
充电宝应助酸菜采纳,获得10
19秒前
nana完成签到,获得积分10
19秒前
文艺灯泡完成签到,获得积分10
21秒前
完美世界应助pp陶采纳,获得10
22秒前
23秒前
高分求助中
A new species of Velataspis (Hemiptera Coccoidea Diaspididae) from tea in Assam 500
Sarcolestes leedsi Lydekker, an ankylosaurian dinosaur from the Middle Jurassic of England 500
Machine Learning for Polymer Informatics 500
《关于整治突出dupin问题的实施意见》(厅字〔2019〕52号) 500
2024 Medicinal Chemistry Reviews 480
Women in Power in Post-Communist Parliaments 450
Geochemistry, 2nd Edition 地球化学经典教科书第二版 401
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 基因 遗传学 催化作用 物理化学 免疫学 量子力学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 3217943
求助须知:如何正确求助?哪些是违规求助? 2867202
关于积分的说明 8155265
捐赠科研通 2534052
什么是DOI,文献DOI怎么找? 1366768
科研通“疑难数据库(出版商)”最低求助积分说明 644865
邀请新用户注册赠送积分活动 617880