GeoChip 3.0 as a high-throughput tool for analyzing microbial community composition, structure and functional activity View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2010-09

AUTHORS

Zhili He, Ye Deng, Joy D Van Nostrand, Qichao Tu, Meiying Xu, Christopher L Hemme, Xingyuan Li, Liyou Wu, Terry J Gentry, Yifeng Yin, Jost Liebich, Terry C Hazen, Jizhong Zhou

ABSTRACT

A new generation of functional gene arrays (FGAs; GeoChip 3.0) has been developed, with approximately 28 000 probes covering approximately 57 000 gene variants from 292 functional gene families involved in carbon, nitrogen, phosphorus and sulfur cycles, energy metabolism, antibiotic resistance, metal resistance and organic contaminant degradation. GeoChip 3.0 also has several other distinct features, such as a common oligo reference standard (CORS) for data normalization and comparison, a software package for data management and future updating and the gyrB gene for phylogenetic analysis. Computational evaluation of probe specificity indicated that all designed probes would have a high specificity to their corresponding targets. Experimental analysis with synthesized oligonucleotides and genomic DNAs showed that only 0.0036-0.025% false-positive rates were observed, suggesting that the designed probes are highly specific under the experimental conditions examined. In addition, GeoChip 3.0 was applied to analyze soil microbial communities in a multifactor grassland ecosystem in Minnesota, USA, which showed that the structure, composition and potential activity of soil microbial communities significantly changed with the plant species diversity. As expected, GeoChip 3.0 is a high-throughput powerful tool for studying microbial community functional structure, and linking microbial communities to ecosystem processes and functioning. More... »

PAGES

1167

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/ismej.2010.46

DOI

http://dx.doi.org/10.1038/ismej.2010.46

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1053592340

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/20428223


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