Validation of a more sensitive method for using spotted oligonucleotide DNA microarrays for functional genomics studies on bacterial communities
Identifieur interne : 003251 ( Main/Curation ); précédent : 003250; suivant : 003252Validation of a more sensitive method for using spotted oligonucleotide DNA microarrays for functional genomics studies on bacterial communities
Auteurs : Vincent J. Denef [Belgique, États-Unis] ; Joonhong Park [États-Unis] ; Jorge L. M. Rodrigues [États-Unis] ; Tamara V. Tsoi [États-Unis] ; Syed A. Hashsham [États-Unis] ; James M. Tiedje [États-Unis]Source :
- Environmental Microbiology [ 1462-2912 ] ; 2003-10.
Descripteurs français
- KwdFr :
- MESH :
English descriptors
- KwdEn :
- MESH :
- genetics : Bacteria.
- methods : Oligonucleotide Array Sequence Analysis.
- Teeft :
- Appl, Appl envir microbiol, Appl environ microbiol, Background levels, Bacterial gdnas, Biodegradation, Environmental, Blackwell publishing, Brown protocol, Cdna microarrays, Consistent results, Control probe, Data analysis, Denef, Detection limit, Direct incorporation, East lansing, Ecology, Envir, Environ, Environ microbiol, Environmental community, Environmental microbiology, Enzymatic incorporation, Epoxysilane substrates, Error bars, Experimental replicates, Functional genes, Functional oligo arrays, Gdna, Gene, Genes ohbb, Genome, Bacterial, Genomic, Genomics, Genomics technology support facility, Higher amounts, Hybridization, Hybridization mixture, Hybridization signal, Hybridization signals, Incorporation, Labelling, Labelling hybridizations, Labelling methods, Labelling reactions, Lambda, Linear relationship, Local background, Lower number, Michigan state university, Microarray, Microarray fabrication optimization, Microarray slide, Microarray technology, Microarrays, Microbial, Microbial communities, Microbial community, Microbial diversity, Microbial ecology, Microbiol, Microbiology, Microcosm hybridizations, Mineral medium, Mouse gdna, Multicopy genes, Negative control, Negative controls, Negative effects, Nucleic acids, Oligonucleotide, Oligonucleotide microarrays, Oligonucleotide probes, Optimal probe category, Optimization, Optimized, Optimized method, Optimized protocol, Other substrates, Perkin elmer, Plasmid, Poly substrates, Polychlorinated biphenyls, Printing buffer, Probe, Probe categories, Probe category, Probe category codes, Probe length, Probe level, Probe sequence, Probequant columns, Product mixture, Protocol, Quantitative detection, Recombinant strains, Replicates, Rha1, Same slide, Santo domingo, Sediment, Sensitivity and Specificity, Sensitivity study, Sequence information, Signal intensities, Signal intensity, Signal steps, Simultaneous monitoring, Soil Microbiology, Soil community, Standard error, Ste3, Superaldehyde, Superaldehyde substrates, Target concentrations, Tiedje, Total community, Unique combination.
Abstract
Spotted oligonucleotide microarrays potentially offer a wide scope of applications for microbial ecology, especially as they improve the flexibility of design and the specificity of detection compared to PCR product based microarrays. Sensitivity, however, was expected to be problematic, as studies with the more sensitive PCR‐based cDNA microarrays indicate that only genes from populations contributing to more than 5% of the community DNA can be detected. We evaluated several parameters to increase sensitivity and then tested applicability for bacterial functional genomics. The optimal parameters were the use of 5′‐C6‐amino‐modified 70‐mers printed on CMT‐GAPS II substrates at a 40 µM concentration combined with the use of Tyramide Signal Amplification labelling. This protocol allowed detection of single copy genes belonging to an organism contributing to 1% or more of the total community. To demonstrate its application, we detected the specific aromatic oxygenase genes in a soil community degrading polychlorinated biphenyls (PCBs). This increase in sensitivity is important if oligonucleotide microarrays are to be used for simultaneous monitoring of a range of functions performed by different microorganisms in the environment.
Url:
DOI: 10.1046/j.1462-2920.2003.00490.x
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qualifier="methods" xml:lang="en"><term>Oligonucleotide Array Sequence Analysis</term></keywords><keywords scheme="Teeft" xml:lang="en"><term>Appl</term><term>Appl envir microbiol</term><term>Appl environ microbiol</term><term>Background levels</term><term>Bacterial gdnas</term><term>Biodegradation, Environmental</term><term>Blackwell publishing</term><term>Brown protocol</term><term>Cdna microarrays</term><term>Consistent results</term><term>Control probe</term><term>Data analysis</term><term>Denef</term><term>Detection limit</term><term>Direct incorporation</term><term>East lansing</term><term>Ecology</term><term>Envir</term><term>Environ</term><term>Environ microbiol</term><term>Environmental community</term><term>Environmental microbiology</term><term>Enzymatic incorporation</term><term>Epoxysilane substrates</term><term>Error bars</term><term>Experimental replicates</term><term>Functional genes</term><term>Functional oligo arrays</term><term>Gdna</term><term>Gene</term><term>Genes ohbb</term><term>Genome, Bacterial</term><term>Genomic</term><term>Genomics</term><term>Genomics technology support facility</term><term>Higher amounts</term><term>Hybridization</term><term>Hybridization mixture</term><term>Hybridization signal</term><term>Hybridization signals</term><term>Incorporation</term><term>Labelling</term><term>Labelling hybridizations</term><term>Labelling methods</term><term>Labelling reactions</term><term>Lambda</term><term>Linear relationship</term><term>Local background</term><term>Lower number</term><term>Michigan state university</term><term>Microarray</term><term>Microarray fabrication optimization</term><term>Microarray slide</term><term>Microarray technology</term><term>Microarrays</term><term>Microbial</term><term>Microbial communities</term><term>Microbial community</term><term>Microbial diversity</term><term>Microbial ecology</term><term>Microbiol</term><term>Microbiology</term><term>Microcosm hybridizations</term><term>Mineral 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domingo</term><term>Sediment</term><term>Sensitivity and Specificity</term><term>Sensitivity study</term><term>Sequence information</term><term>Signal intensities</term><term>Signal intensity</term><term>Signal steps</term><term>Simultaneous monitoring</term><term>Soil Microbiology</term><term>Soil community</term><term>Standard error</term><term>Ste3</term><term>Superaldehyde</term><term>Superaldehyde substrates</term><term>Target concentrations</term><term>Tiedje</term><term>Total community</term><term>Unique combination</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Dépollution biologique de l'environnement</term><term>Génome bactérien</term><term>Génomique</term><term>Microbiologie du sol</term><term>Sensibilité et spécificité</term><term>Séquençage par oligonucléotides en batterie</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Spotted oligonucleotide microarrays potentially offer a wide scope of applications for microbial ecology, especially as they improve the flexibility of design and the specificity of detection compared to PCR product based microarrays. Sensitivity, however, was expected to be problematic, as studies with the more sensitive PCR‐based cDNA microarrays indicate that only genes from populations contributing to more than 5% of the community DNA can be detected. We evaluated several parameters to increase sensitivity and then tested applicability for bacterial functional genomics. The optimal parameters were the use of 5′‐C6‐amino‐modified 70‐mers printed on CMT‐GAPS II substrates at a 40 µM concentration combined with the use of Tyramide Signal Amplification labelling. This protocol allowed detection of single copy genes belonging to an organism contributing to 1% or more of the total community. To demonstrate its application, we detected the specific aromatic oxygenase genes in a soil community degrading polychlorinated biphenyls (PCBs). This increase in sensitivity is important if oligonucleotide microarrays are to be used for simultaneous monitoring of a range of functions performed by different microorganisms in the environment.</div></front></TEI></record>Pour manipuler ce document sous Unix (Dilib)
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