Dunman P M, Mounts W, McAleese F, Immermann F, Macapagal D, Marsilio E, McDougal L, Tenover F C, Bradford P A, Petersen P J, Projan S J, Murphy E
Wyeth Research, 401 N. Middletown Rd., Pearl River, NY 10965, USA.
J Clin Microbiol. 2004 Sep;42(9):4275-83. doi: 10.1128/JCM.42.9.4275-4283.2004.
Understanding the relatedness of strains within a bacterial species is essential for monitoring reservoirs of antimicrobial resistance and for epidemiological studies. Pulsed-field gel electrophoresis (PFGE), ribotyping, and multilocus sequence typing are commonly used for this purpose. However, these techniques are either nonquantitative or provide only a limited estimation of strain relatedness. Moreover, they cannot extensively define the genes that constitute an organism. In the present study, 21 oxacillin-resistant Staphylococcus aureus (ORSA) isolates, representing eight major ORSA lineages, and each of the seven strains for which the complete genomic sequence is publicly available were genotyped using a novel GeneChip-based approach. Strains were also subjected to PFGE and ribotyping analysis. GeneChip results provided a higher level of discrimination among isolates than either ribotyping or PFGE, although strain clustering was similar among the three techniques. In addition, GeneChip signal intensity cutoff values were empirically determined to provide extensive data on the genetic composition of each isolate analyzed. Using this technology it was shown that strains could be examined for each element represented on the GeneChip, including virulence factors, antimicrobial resistance determinants, and agr type. These results were validated by PCR, growth on selective media, and detailed in silico analysis of each of the sequenced genomes. Collectively, this work demonstrates that GeneChips provide extensive genotyping information for S. aureus strains and may play a major role in epidemiological studies in the future where correlating genes with particular disease phenotypes is critical.
了解细菌物种内菌株的相关性对于监测抗菌药物耐药性储存库和进行流行病学研究至关重要。脉冲场凝胶电泳(PFGE)、核糖体分型和多位点序列分型通常用于此目的。然而,这些技术要么是非定量的,要么仅提供有限的菌株相关性估计。此外,它们无法广泛定义构成生物体的基因。在本研究中,使用基于新型基因芯片的方法对代表八个主要耐苯唑西林金黄色葡萄球菌(ORSA)谱系的21株ORSA分离株以及七株完整基因组序列可公开获得的菌株中的每一株进行基因分型。菌株还进行了PFGE和核糖体分型分析。基因芯片结果在分离株之间提供了比核糖体分型或PFGE更高水平的区分,尽管三种技术之间的菌株聚类相似。此外,通过经验确定基因芯片信号强度截止值,以提供关于所分析的每个分离株遗传组成的广泛数据。使用该技术表明,可以检查基因芯片上代表的每个元件的菌株,包括毒力因子、抗菌药物耐药决定簇和agr类型。这些结果通过PCR、在选择性培养基上的生长以及对每个测序基因组的详细计算机分析进行了验证。总体而言,这项工作表明基因芯片为金黄色葡萄球菌菌株提供了广泛的基因分型信息,并且在未来将基因与特定疾病表型相关联至关重要的流行病学研究中可能发挥主要作用。