The next wave in metabolome analysis

被引:173
作者
Nielsen, J [1 ]
Oliver, S
机构
[1] Tech Univ Denmark, BioCtr DTU, Ctr Microbial Biotechnol, DK-2800 Lyngby, Denmark
[2] Univ Manchester, Fac Life Sci, Manchester M13 9PT, Lancs, England
关键词
D O I
10.1016/j.tibtech.2005.08.005
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
The metabolome of a cell represents the amplification and integration of signals from other functional genomic levels, such as the transcriptome and the proteome. Although this makes metabolomics a useful tool for the high-throughput analysis of phenotypes, the lack of a direct connection to the genome makes it difficult to interpret metabolomic data. Nevertheless, functional genomics has produced examples of the use of metabolomics to elucidate the phenotypes of otherwise silent mutations. Despite several successes, we believe that future metabolomic studies must focus on the accurate measurement of the concentrations of unambiguously identified metabolites. The research community must develop databases of metabolite concentrations in cells that are grown in several well-defined conditions if metabolomic data are to be integrated meaningfully with data from the other levels of functional-genomic analysis and to make a significant contribution to systems biology.
引用
收藏
页码:544 / 546
页数:3
相关论文
共 22 条
[1]   High-throughput classification of yeast mutants for functional genomics using metabolic footprinting [J].
Allen, J ;
Davey, HM ;
Broadhurst, D ;
Heald, JK ;
Rowland, JJ ;
Oliver, SG ;
Kell, DB .
NATURE BIOTECHNOLOGY, 2003, 21 (06) :692-696
[2]   Metabolome analysis:: the potential of in vivo labeling with stable isotopes for metabolite profiling [J].
Birkemeyer, C ;
Luedemann, A ;
Wagner, C ;
Erban, A ;
Kopka, J .
TRENDS IN BIOTECHNOLOGY, 2005, 23 (01) :28-33
[3]   Integrating high-throughput and computational data elucidates bacterial networks [J].
Covert, MW ;
Knight, EM ;
Reed, JL ;
Herrgard, MJ ;
Palsson, BO .
NATURE, 2004, 429 (6987) :92-96
[4]   Combining genomics, metabolome analysis, and biochemical modelling to understand metabolic networks [J].
Fiehn, O .
COMPARATIVE AND FUNCTIONAL GENOMICS, 2001, 2 (03) :155-168
[5]   Genome-scale reconstruction of the Saccharomyces cerevisiae metabolic network [J].
Förster, J ;
Famili, I ;
Fu, P ;
Palsson, BO ;
Nielsen, J .
GENOME RESEARCH, 2003, 13 (02) :244-253
[6]   Metabolomics by numbers: acquiring and understanding global metabolite data [J].
Goodacre, R ;
Vaidyanathan, S ;
Dunn, WB ;
Harrigan, GG ;
Kell, DB .
TRENDS IN BIOTECHNOLOGY, 2004, 22 (05) :245-252
[7]   Chemical derivatization and mass spectral libraries in metabolic profiling by GC/MS and LC/MS/MS [J].
Halket, JM ;
Waterman, D ;
Przyborowska, AM ;
Patel, RKP ;
Fraser, PD ;
Bramley, PM .
JOURNAL OF EXPERIMENTAL BOTANY, 2005, 56 (410) :219-243
[8]   Integration of transcriptomics and metabolomics for understanding of global responses to nutritional stresses in Arabidopsis thaliana [J].
Hirai, MY ;
Yano, M ;
Goodenowe, DB ;
Kanaya, S ;
Kimura, T ;
Awazuhara, M ;
Arita, M ;
Fujiwara, T ;
Saito, K .
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2004, 101 (27) :10205-10210
[9]   A proposed framework for the description of plant metabolomics experiments and their results [J].
Jenkins, H ;
Hardy, N ;
Beckmann, M ;
Draper, J ;
Smith, AR ;
Taylor, J ;
Fiehn, O ;
Goodacre, R ;
Bino, RJ ;
Hall, R ;
Kopka, J ;
Lane, GA ;
Lange, BM ;
Liu, JR ;
Mendes, P ;
Nikolau, BJ ;
Oliver, SG ;
Paton, NW ;
Rhee, S ;
Roessner-Tunali, U ;
Saito, K ;
Smedsgaard, J ;
Sumner, LW ;
Wang, T ;
Walsh, S ;
Wurtele, ES ;
Kell, DB .
NATURE BIOTECHNOLOGY, 2004, 22 (12) :1601-1606
[10]  
KEIGHTLEY PD, 1987, GENETICS, V117, P319