Abstract
Functional gene arrays, like the GeoChip, allow for the study of tens of thousands of genes in a single assay. The GeoChip array (5.0) contains probes for genes involved in geochemical cycling (N, C, S, and P), metal homeostasis, stress response, organic contaminant degradation, antibiotic resistance, secondary metabolism, and virulence factors as well as genes specific for fungi, protists, and viruses. Here, we briefly describe GeoChip design strategies (gene selection and probe design) and discuss minimum quantity and quality requirements for nucleic acids. We then provide detailed protocols for amplification, labeling, and hybridization of samples to the GeoChip.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Amann RI, Ludwig W, Schleifer KH (1995) Phylogenetic identification and in situ detection of individual microbial cells without cultivation. Microbiol Rev 59:143–169
Furhman JA, Campbell L (1998) Marine ecology: microbial microdiversity. Nature 393:410–411
Whitman WB, Coleman DC, Wiebe WJ (1998) Prokaryotes: the unseen majority. Proc Natl Acad Sci U S A 95:6578–6583
Wu L, Thompson DK, Li G et al (2001) Development and evaluation of functional gene arrays for detection of selected genes in the environment. Appl Environ Microbiol 67:5780–5790
He Z, Gentry TJ, Schadt CW et al (2007) GeoChip: a comprehensive microarray for investigating biogeochemical, ecological and environmental processes. ISME J 1:67–77
He Z, Deng Y, Van Nostrand JD et al (2010) GeoChip 3.0 as a high-throughput tool for analyzing microbial community composition, structure and functional activity. ISME J 4:1167–1179
Tu Q, Yu H, He Z et al (2014) GeoChip 4: a functional gene arrays-based high throughput environmental technology for microbial community analysis. Mol Ecol Resour 14:914–928
He Z, Wu LY, Li XY et al (2005) Empirical establishment of oligonucleotide probe design criteria. Appl Environ Microbiol 71:3753–3760
Liebich J, Schadt CW, Chong SC et al (2006) Improvement of oligonucleotide probe design criteria for functional gene microarrays in environmental applications. Appl Environ Microbiol 72:1688–1691
Li X, He Z, Zhou J (2005) Selection of optimal oligonucleotide probes for microarrays using multiple criteria, global alignment and parameter estimation. Nucleic Acids Res 33:6114–6123
Ning J, Liebich J, Kästner M et al (2009) Different influences of DNA purity indices and quantity on PCR-based DGGE and functional gene microarray in soil microbial community study. Appl Microbiol Biotechnol 82:983–993
NanoDrop (2007) 260/280 and 260/230 Ratios NanoDrop® ND-1000 and ND-8000 8-Sample Spectrophotometers. Technical Support Bulletin T009
Liang Y, He Z, Wu L et al (2010) Development of a common oligonucleotide reference standard (CORS) for microarray data normalization and comparison across different microbial communities. Appl Environ Microbiol 76:1088–1094
Xie J, Wu L, Van Nostrand JD et al (2012) Improvements on environmental DNA extraction and purification procedures for matagenomic analysis. J Cent South Univ 19:3055–3063
Wu L, Liu X, Schadt CW et al (2006) Microarray-based analysis of submicrogram quantities of microbial community DNAs by using whole-community genome amplification. Appl Environ Microbiol 72:4931–4941
Gao H, Yang ZK, Gentry TJ et al (2007) Microarray-based analysis of microbial community RNAs by whole-community RNA amplification. Appl Environ Microbiol 73:563–571
Zhang K, Martiny AC, Reppas NB et al (2006) Sequencing genomes from single cells by polymerase cloning. Nat Biotechnol 24:680–686
Khan AU, Mei YH, Wilson T (1992) A proposed function for spermine and spermidine: protection of replicating DNA against damage by singlet oxygen. Proc Natl Acad Sci U S A 89:11426–11427
Marceau AH (2012) Functions of single-strand DNA-binding proteins in DNA replication, recombination, and repair. Methods Mol Biol 922:1–21
Agilent (2012) Agilent Oligonucleotide Array-Based CGH for Genomic DNA Analysis. Version 3.4, July 2012. Agilent Technologies
Deng Y, He Z (2014) Microarray data analysis. In: He Z (ed) Microarrays: current technology, innovations and applications. Caister Academic Press, Norwich, UK, http://www.horizonpress.com/microarrays2
Luo Y, Hui D, Zhang D (2006) Elevated CO2 stimulates net accumulations of carbon and nitrogen in land ecosystems: a meta-analysis. Ecology 87:53–63
ter Braak CJF (1986) Canonical correspondence analysis: a new eigenvector technique for multivariate direct gradient analysis. Ecology 67:1167–1179
Legendre P, Anderson MJ (1999) Distance-based redundancy analysis: testing multi-species responses in multi-factorial ecological experiments. Ecol Monogr 69:1–24
Økland RH, Eilertsen O (1994) Canonical correspondence analysis with variation partitioning: some comments and an application. J Veg Sci 5:117–126
Ramette A, Tiedje JM (2007) Multiscale responses of microbial life in spatial distance and environmental heterogeneity in a patchy ecosystem. Proc Natl Acad Sci U S A 104:2761–2766
Sambrook J, Russell DW (2001) Molecular cloning a laboratory manual, vol 1. Cold Spring Harbor Laboratory Press, Cold Spring Harbor, NY
Fare TL, Coffey EM, Dai H (2003) Effects of atmospheric ozone on microarray data quality. Anal Chem 75:4672–4675
Branham WS, Melvin CD, Han T et al (2007) Elimination of laboratory ozone leads to a dramatic improvement in the reproducibility of microarray gene expression measurements. BMC Biotechnol 7:8
Byerly S, Sundin K, Raja R et al (2009) Effects of ozone exposure during microarray posthybridization washes and scanning. J Mol Diagn 11:590–597
Acknowledgement
Efforts for writing this Chapter were supported by the Department of Energy’s Carbon Cycling program (DE-SC0004601 and DE-SC0010715).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer Science+Business Media New York
About this protocol
Cite this protocol
Van Nostrand, J.D., Yin, H., Wu, L., Yuan, T., Zhou, J. (2016). Hybridization of Environmental Microbial Community Nucleic Acids by GeoChip. In: Martin, F., Uroz, S. (eds) Microbial Environmental Genomics (MEG). Methods in Molecular Biology, vol 1399. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-3369-3_11
Download citation
DOI: https://doi.org/10.1007/978-1-4939-3369-3_11
Published:
Publisher Name: Humana Press, New York, NY
Print ISBN: 978-1-4939-3367-9
Online ISBN: 978-1-4939-3369-3
eBook Packages: Springer Protocols