Bittar Fadi, Richet Hervé, Dubus Jean-Christophe, Reynaud-Gaubert Martine, Stremler Nathalie, Sarles Jacques, Raoult Didier, Rolain Jean-Marc
Unité de Recherche sur les Maladies Infectieuses et Tropicales Emergentes, CNRS-IRD, UMR 6236, Faculté de Médecine et de Pharmacie, Université de la Méditerranée, Marseille, France.
PLoS One. 2008 Aug 6;3(8):e2908. doi: 10.1371/journal.pone.0002908.
There is strong evidence that culture-based methods detect only a small proportion of bacteria present in the respiratory tracts of cystic fibrosis (CF) patients.
METHODOLOGY/PRINCIPAL FINDINGS: Standard microbiological culture and phenotypic identification of bacteria in sputa from CF patients have been compared to molecular methods by the use of 16S rDNA amplification, cloning and sequencing. Twenty-five sputa from CF patients were cultured that yield 33 isolates (13 species) known to be pathogens during CF. For molecular cloning, 760 clones were sequenced (7.2+/-3.9 species/sputum), and 53 different bacterial species were identified including 16 species of anaerobes (30%). Discrepancies between culture and molecular data were numerous and demonstrate that accurate identification remains challenging. New or emerging bacteria not or rarely reported in CF patients were detected including Dolosigranulum pigrum, Dialister pneumosintes, and Inquilinus limosus.
CONCLUSIONS/SIGNIFICANCE: Our results demonstrate the complex microbial community in sputa from CF patients, especially anaerobic bacteria that are probably an underestimated cause of CF lung pathology. Metagenomic analysis is urgently needed to better understand those complex communities in CF pulmonary infections.
有充分证据表明,基于培养的方法仅能检测出囊性纤维化(CF)患者呼吸道中存在的一小部分细菌。
方法/主要发现:通过使用16S rDNA扩增、克隆和测序,将CF患者痰液中细菌的标准微生物培养和表型鉴定与分子方法进行了比较。对25份CF患者的痰液进行培养,得到33株分离菌(13个菌种),这些分离菌在CF期间被认为是病原体。对于分子克隆,对760个克隆进行了测序(每份痰液7.2±3.9个菌种),鉴定出53种不同的细菌物种,包括16种厌氧菌(30%)。培养数据与分子数据之间存在许多差异,这表明准确鉴定仍然具有挑战性。检测到了在CF患者中未报告或很少报告的新出现的细菌,包括嗜麦芽窄食单胞菌、肺炎戴阿李斯特菌和栖居菌。
结论/意义:我们的结果表明CF患者痰液中的微生物群落复杂,尤其是厌氧菌,它们可能是CF肺部病理的一个被低估的原因。迫切需要进行宏基因组分析,以更好地了解CF肺部感染中的这些复杂群落。