Bioinformatics-based strategies for rapid microorganism identification by mass spectrometry

被引:0
|
作者
Demirev, PA
Feldman, AB
Lin, JS
机构
[1] Johns Hopkins Univ, Appl Phys Lab, Res & Technol Dev Ctr, Bioinformat Sect, Laurel, MD 20703 USA
[2] Johns Hopkins Univ, Appl Phys Lab, Res & Technol Dev Ctr, Syst & Informat Sci Grp, Laurel, MD 20703 USA
来源
JOHNS HOPKINS APL TECHNICAL DIGEST | 2004年 / 25卷 / 01期
关键词
D O I
暂无
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
We review approaches for microorganism identification that exploit the wealth of information in constantly expanding proteome databases. Masses of an organism's protein biomarkers are experimentally determined and matched against sequence-derived masses of proteins, found together with their source organisms in proteome databases. The source organisms are ranked according to the matches, resulting in microorganism identification. Statistical analysis of proteome uniqueness across organisms in a database enables evaluation of the probability of false identifications based on protein mass assignments alone. Biomarkers likely to be observed can be identified based solely on microbial genome sequence information. Protein identification methodologies allow assignment of detected proteins to specific microorganisms and, by extension, allow identification of the microorganism from which those proteins originate.
引用
收藏
页码:27 / 37
页数:11
相关论文
共 50 条
  • [41] Bioinformatics-based Identification of Ferroptosis-related Genes and their Diagnostic Value in Gestational Diabetes Mellitus
    Lv, Xiaomei
    An, Yujun
    ENDOCRINE METABOLIC & IMMUNE DISORDERS-DRUG TARGETS, 2024, 24 (14) : 1611 - 1621
  • [42] Bioinformatics-Based Identification of a circRNA-miRNA-mRNA Axis in Esophageal Squamous Cell Carcinomas
    Wang, Zhaojun
    Li, Haifeng
    Li, Fajun
    Su, Xin
    Zhang, Junhang
    JOURNAL OF ONCOLOGY, 2020, 2020
  • [43] Bioinformatics-based identification and validation of hub genes associated with aging in patients with coronary artery disease
    Zhang, Wangmeng
    Zhao, Minmin
    Xin, Li
    Qi, Ximei
    Cao, Ping
    Wang, Jiyan
    Li, Xin
    AGING-US, 2023, 15 (24): : 14830 - 14844
  • [44] A bioinformatics-based approach for the prediction and identification of novel proteins potentially involved in phosphorylation signalling pathways
    Ahn, SK
    INTERNATIONAL JOURNAL OF MOLECULAR MEDICINE, 2003, 12 (03) : 391 - 397
  • [45] Bioinformatics-based identification of GH12 endoxyloglucanases in citrus-pathogenic Penicillium spp
    Li, Kai
    Barrett, Kristian
    Agger, Jane W.
    Zeuner, Birgitte
    Meyer, Anne S.
    ENZYME AND MICROBIAL TECHNOLOGY, 2024, 178
  • [46] The application of bioinformatics to mass spectrometry
    Appel, RD
    Bairoch, A
    PROTEOMICS, 2002, 2 (10) : 1363 - 1364
  • [47] Mass spectrometry-based proteomics strategies for protease cleavage site identification
    van den Berg, Bart H. J.
    Tholey, Andreas
    PROTEOMICS, 2012, 12 (4-5) : 516 - 529
  • [48] Bioinformatics-Based Identification of Methylated-Differentially Expressed Genes and Related Pathways in Gastric Cancer
    Li, Hao
    Liu, Jing-wei
    Liu, Shuang
    Yuan, Yuan
    Sun, Li-ping
    DIGESTIVE DISEASES AND SCIENCES, 2017, 62 (11) : 3029 - 3039
  • [49] Bioinformatics-Based Identification of Candidate Genes from QTLs Associated with Cell Wall Traits in Populus
    Priya Ranjan
    Tongming Yin
    Xinye Zhang
    Udaya C. Kalluri
    Xiaohan Yang
    Sara Jawdy
    Gerald A. Tuskan
    BioEnergy Research, 2010, 3 : 172 - 182
  • [50] Bioinformatics-Based Identification of Candidate Genes from QTLs Associated with Cell Wall Traits in Populus
    Ranjan, Priya
    Yin, Tongming
    Zhang, Xinye
    Kalluri, Udaya C.
    Yang, Xiaohan
    Jawdy, Sara
    Tuskan, Gerald A.
    BIOENERGY RESEARCH, 2010, 3 (02) : 172 - 182