School of Biological Sciences, University of Queensland, St. Lucia, Queensland 4072, Australia.
Appl Environ Microbiol. 2010 Nov;76(21):7161-70. doi: 10.1128/AEM.03108-09. Epub 2010 Sep 17.
Functional attributes of microbial communities are difficult to study, and most current techniques rely on DNA- and rRNA-based profiling of taxa and genes, including microarrays containing sequences of known microorganisms. To quantify gene expression in environmental samples in a culture-independent manner, we constructed an environmental functional gene microarray (E-FGA) consisting of 13,056 mRNA-enriched anonymous microbial clones from diverse microbial communities to profile microbial gene transcripts. A new normalization method using internal spot standards was devised to overcome spotting and hybridization bias, enabling direct comparisons of microarrays. To evaluate potential applications of this metatranscriptomic approach for studying microbes in environmental samples, we tested the E-FGA by profiling the microbial activity of agricultural soils with a low or high flux of N₂O. A total of 109 genes displayed expression that differed significantly between soils with low and high N₂O emissions. We conclude that mRNA-based approaches such as the one presented here may complement existing techniques for assessing functional attributes of microbial communities.
微生物群落的功能属性很难研究,目前大多数技术都依赖于基于 DNA 和 rRNA 的分类群和基因分析,包括包含已知微生物序列的微阵列。为了在非培养的方式下定量环境样本中的基因表达,我们构建了一个由来自不同微生物群落的 13056 个富含 mRNA 的匿名微生物克隆组成的环境功能基因微阵列(E-FGA),以分析微生物基因转录本。我们设计了一种新的使用内部点标准的归一化方法,以克服点样和杂交偏倚,从而能够直接比较微阵列。为了评估这种宏转录组学方法在研究环境样品中微生物的潜在应用,我们通过对 N₂O 通量低或高的农业土壤中的微生物活性进行分析,测试了 E-FGA。共有 109 个基因的表达在低 N₂O 排放和高 N₂O 排放土壤之间存在显著差异。我们得出结论,基于 mRNA 的方法,如本文所述的方法,可能会补充现有的评估微生物群落功能属性的技术。