Neufeld Josh D, Mohn William W, de Lorenzo Victor
Department of Microbiology and Immunology, University of British Columbia, 300-6174 University Boulevard, Vancouver, British Columbia, Canada, V6T 1Z3.
Environ Microbiol. 2006 Jan;8(1):126-40. doi: 10.1111/j.1462-2920.2005.00875.x.
Microarray technology was used to characterize and compare hexachlorocyclohexane (HCH) contaminated soils from Spain. A library of 2,290 hypervariable 16S rRNA gene sequences was prepared with serial analysis of ribosomal sequence tags (SARST) from a composite of contaminated and uncontaminated soils. By designing hybridization probes specific to the 100 most abundant ribosomal sequence tags (RSTs) in the composite library, the RST array was designed to be habitat-specific and predicted to monitor the most abundant polymerase chain reaction (PCR)-amplified phylotypes in the individual samples. The sensitivity and specificity of the RST array was tested with a series of pure culture-specific probes and hybridized with labelled soil PCR products to generate hybridization patterns for each soil. Sequencing of prominent bands in denaturing gradient gel electrophoresis (DGGE) fingerprints derived from these soils provided a means by which we successfully confirmed the habitat-specific array design and validated the bulk of the probe signals. Non-metric multidimensional scaling revealed correlations between probe signals and soil physicochemical parameters. Among the strongest correlations to total HCH contamination were probe signals corresponding to unknown Gamma Proteobacteria, potential pollutant-degrading phylotypes, and several organisms with acid-tolerant phenotypes. The strongest correlations to alpha-HCH were probe signals corresponding to the genus Sphingomonas, which contains known HCH degraders. This suggests that the population detected was enriched in situ by HCH contamination and may play a role in HCH degradation. Other environmental parameters were also likely instrumental in shaping community composition in these soils. The results highlight the power of habitat-specific microarrays for comparing complex microbial communities.
利用微阵列技术对来自西班牙的六氯环己烷(HCH)污染土壤进行表征和比较。通过对受污染和未受污染土壤的混合物进行核糖体序列标签的序列分析(SARST),构建了一个包含2290个高变16S rRNA基因序列的文库。通过设计针对混合文库中100个最丰富的核糖体序列标签(RST)的杂交探针,RST阵列被设计成栖息地特异性的,并预计可监测各个样本中最丰富的聚合酶链反应(PCR)扩增系统型。用一系列纯培养特异性探针测试了RST阵列的敏感性和特异性,并与标记的土壤PCR产物杂交,以生成每种土壤的杂交模式。对这些土壤变性梯度凝胶电泳(DGGE)指纹图谱中突出条带的测序提供了一种方法,通过该方法我们成功地证实了栖息地特异性阵列设计并验证了大部分探针信号。非度量多维标度分析揭示了探针信号与土壤理化参数之间的相关性。与总六氯环己烷污染相关性最强的是对应于未知γ-变形菌、潜在污染物降解系统型以及几种具有耐酸表型的生物的探针信号。与α-六氯环己烷相关性最强的是对应于鞘氨醇单胞菌属的探针信号,该属包含已知的六氯环己烷降解菌。这表明检测到的种群因六氯环己烷污染而在原位富集,可能在六氯环己烷降解中发挥作用。其他环境参数也可能对这些土壤中群落组成的形成起到了作用。结果突出了栖息地特异性微阵列在比较复杂微生物群落方面的强大功能。