Accurately quantifying low-abundant targets amid similar sequences by revealing hidden correlations in oligonucleotide microarray data

Luisa A. Marcelino, Vadim Backman, Andres Donaldson, Claudia Steadman, Janelle R. Thompson, Sarah Pacocha Preheim, Cynthia Lien, Eelin Lim, Daniele Veneziano, Martin F. Polz*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

27 Scopus citations

Abstract

Microarrays have enabled the determination of how thousands of genes are expressed to coordinate function within single organisms. Yet applications to natural or engineered communities where different organisms interact to produce complex properties are hampered by theoretical and technological limitations. Here we describe a general method to accurately identify low-abundant targets in systems containing complex mixtures of homologous targets. We combined an analytical predictor of nonspecific probe-target interactions (cross-hybridization) with an optimization algorithm that iteratively deconvolutes true probe-target signal from raw signal affected by spurious contributions (cross-hybridization, noise, background, and unequal specific hybridization response). The method was capable of quantifying, with unprecedented specificity and accuracy, ribosomal RNA (rRNA) sequences in artificial and natural communities. Controlled experiments with spiked rRNA into artificial and natural communities demonstrated the accuracy of identification and quantitative behavior over different concentration ranges. Finally, we illustrated the power of this methodology for accurate detection of low-abundant targets in natural communities. We accurately identified Vibrio taxa in coastal marine samples at their natural concentrations (<0.05% of total bacteria), despite the high potential for cross-hybridization by hundreds of different coexisting rRNAs, suggesting this methodology should be expandable to any microarray platform and system requiring accurate identification of low-abundant targets amid pools of similar sequences.

Original languageEnglish (US)
Pages (from-to)13629-13634
Number of pages6
JournalProceedings of the National Academy of Sciences of the United States of America
Volume103
Issue number37
DOIs
StatePublished - Sep 12 2006

Keywords

  • Cross-hybridization
  • Free energy
  • Microbial ecology
  • Optimization algorithm
  • rRNA

ASJC Scopus subject areas

  • General

Fingerprint Dive into the research topics of 'Accurately quantifying low-abundant targets amid similar sequences by revealing hidden correlations in oligonucleotide microarray data'. Together they form a unique fingerprint.

Cite this