Development and application of functional gene arrays for microbial community analysis

被引:12
|
作者
He, Z. L. [1 ]
Van Nostrand, J. D. [1 ]
Wu, L. Y. [1 ]
Zhou, J. Z. [1 ]
机构
[1] Univ Oklahoma, Dept Bot & Microbiol, Inst Environm Genom, Norman, OK 73019 USA
关键词
microarray; application; function gene marker; microbial community;
D O I
10.1016/S1003-6326(09)60004-2
中图分类号
TF [冶金工业];
学科分类号
0806 ;
摘要
Functional gene markers can provide important information about functional gene diversity and potential activity of microbial communities. Although microarray technology has been successfully applied to study gene expression for pure cultures, simple, and artificial microbial communities, adapting such a technology to analyze complex microbial communities still presents a lot of challenges in terms of design, sample preparation, and data analysis. This work is focused on the development and application of functional gene arrays (FGAs) to target key functional gene markers for microbial community studies. A few key issues specifically related to FGAs, such as oligonucleotide probe design, nucleic acid extraction and purification, data analysis, specificity, sensitivity, and quantitative capability are discussed in detail. Recent studies have demonstrated that FGAs can provide specific, sensitive, and potentially quantitative information about microbial communities from a variety of natural environments and controlled ecosystems. This technology is expected to revolutionize the analysis of microbial communities, and link microbial structure to ecosystem functioning.
引用
收藏
页码:1319 / 1327
页数:9
相关论文
共 50 条
  • [31] Sulfadiazine degradation in soils: Dynamics, functional gene, antibiotic resistance genes and microbial community
    Chen, Jianfei
    Jiang, Xinshu
    Tong, Tianli
    Miao, Sun
    Huang, Jun
    Xie, Shuguang
    SCIENCE OF THE TOTAL ENVIRONMENT, 2019, 691 : 1072 - 1081
  • [32] Microbial community analysis
    White, DC
    ENVIRONMENTAL MICROBIOLOGY, 2002, 4 (01) : 13 - 14
  • [33] Microbial Community Analysis with Ribosomal Gene Fragments from Shotgun Metagenomes
    Guo, Jiarong
    Cole, James R.
    Zhang, Qingpeng
    Brown, C. Titus
    Tiedje, James M.
    APPLIED AND ENVIRONMENTAL MICROBIOLOGY, 2016, 82 (01) : 157 - 166
  • [34] Considerations for the development and application of control materials to improve metagenomic microbial community profiling
    Jim F. Huggett
    Thomas Laver
    Sasithon Tamisak
    Gavin Nixon
    Denise M. O’Sullivan
    Ramnath Elaswarapu
    David J. Studholme
    Carole A. Foy
    Accreditation and Quality Assurance, 2013, 18 : 77 - 83
  • [35] Development and application of a fatty acid based microbial community structure similarity index
    Werker, A
    Hall, E
    ENVIRONMETRICS, 2002, 13 (04) : 347 - 363
  • [36] Application of Methodology for Microbial Community Analysis to Gas-Phase Biofilters
    Lee, Eun-Hee
    Park, Hyunjung
    Jo, Yun-Seong
    Ryu, Hee Wook
    Cho, Kyung-Suk
    KOREAN CHEMICAL ENGINEERING RESEARCH, 2010, 48 (02): : 147 - 156
  • [37] Considerations for the development and application of control materials to improve metagenomic microbial community profiling
    Huggett, Jim F.
    Laver, Thomas
    Tamisak, Sasithon
    Nixon, Gavin
    O'Sullivan, Denise M.
    Elaswarapu, Ramnath
    Studholme, David J.
    Foy, Carole A.
    ACCREDITATION AND QUALITY ASSURANCE, 2013, 18 (02) : 77 - 83
  • [38] Microbial Community Predicts Functional Stability of Microbial Fuel Cells
    Lesnik, Keaton Larson
    Cai, Wenfang
    Liu, Hong
    ENVIRONMENTAL SCIENCE & TECHNOLOGY, 2020, 54 (01) : 427 - 436
  • [39] Selective capture of transcribed sequences in the functional gene analysis of microbial pathogens
    Wang, Yang
    Yi, Li
    Wang, Shaohui
    Lu, Chengping
    Ding, Chan
    APPLIED MICROBIOLOGY AND BIOTECHNOLOGY, 2014, 98 (24) : 9983 - 9992
  • [40] Selective capture of transcribed sequences in the functional gene analysis of microbial pathogens
    Yang Wang
    Li Yi
    Shaohui Wang
    Chengping Lu
    Chan Ding
    Applied Microbiology and Biotechnology, 2014, 98 : 9983 - 9992