Microbial Ecology

, Volume 53, Issue 3, pp 371–383 | Cite as

High-Density Universal 16S rRNA Microarray Analysis Reveals Broader Diversity than Typical Clone Library When Sampling the Environment

  • Todd Z. DeSantis
  • Eoin L. Brodie
  • Jordan P. Moberg
  • Ingrid X. Zubieta
  • Yvette M. Piceno
  • Gary L. Andersen


Molecular approaches aimed at detection of a broad-range of prokaryotes in the environment routinely rely on classifying heterogeneous 16S rRNA genes amplified by polymerase chain reaction (PCR) using primers with broad specificity. The general method of sampling and categorizing DNA has been to clone then sequence the PCR products. However, the number of clones required to adequately catalog the majority of taxa in a sample is unwieldy. Alternatively, hybridizing target sequences to a universal 16S rRNA gene microarray may provide a more rapid and comprehensive view of prokaryotic community composition. This study investigated the breadth and accuracy of a microarray in detecting diverse 16S rRNA gene sequence types compared to clone-and-sequencing using three environmental samples: urban aerosol, subsurface soil, and subsurface water. PCR products generated from universal 16S rRNA gene-targeted primers were classified by using either the clone-and-sequence method or by hybridization to a novel high-density microarray of 297,851 probes complementary to 842 prokaryotic subfamilies. The three clone libraries comprised 1391 high-quality sequences. Approximately 8% of the clones could not be placed into a known subfamily and were considered novel. The microarray results confirmed the majority of clone-detected subfamilies and additionally demonstrated greater amplicon diversity extending into phyla not observed by the cloning method. Sequences matching operational taxonomic units within the phyla Nitrospira, Planctomycetes, and TM7, which were uniquely detected by the array, were verified with specific primers and subsequent amplicon sequencing. Subfamily richness detected by the array corresponded well with nonparametric richness predictions extrapolated from clone libraries except in the water community where clone-based richness predictions were greatly exceeded. It was concluded that although the microarray is unreliable in identifying novel prokaryotic taxa, it reveals greater diversity in environmental samples than sequencing a typically sized clone library. Furthermore, the microarray allowed samples to be rapidly evaluated with replication, a significant advantage in studies of microbial ecology.


Clone Library Accumulation Curve Probe Pair Amplicon Pool Nonparametric Richness Estimator 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The authors wish to thank Dr. Phil Hugenholtz and Dr. Paul Richardson of the Joint Genome Institute for assistance in constructing the clone libraries. We acknowledge the expert technical assistance of Sonya Murray, Richard Phan, Mark Rojas, and Ramine Cromartie-Thornton. Computational support was provided through the Virtual Institute for Microbial Stress and Survival ( This work was performed under the auspices of the US Department of Energy by the University of California, Lawrence Berkeley National Laboratory under Contract No. DE-AC02-05CH11231, and was funded in part by the Department of Homeland Security under grant number HSSCHQ04X00037 and in part by the Department of Energy, Environmental Remediation Sciences Program (ERSP) and the Genomics: GTL program.


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Copyright information

© Springer Science+Business Media, Inc. 2007

Authors and Affiliations

  • Todd Z. DeSantis
    • 1
    • 2
  • Eoin L. Brodie
    • 1
  • Jordan P. Moberg
    • 1
  • Ingrid X. Zubieta
    • 1
  • Yvette M. Piceno
    • 1
  • Gary L. Andersen
    • 1
    • 2
  1. 1.Lawrence Berkeley National LaboratoryCenter for Environmental BiotechnologyBerkeleyUSA
  2. 2.Lawrence Berkeley National LaboratoryVirtual Institute for Microbial Stress and SurvivalBerkeleyUSA

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