BACKGROUND It is now possible to comprehensively characterize the microbiota of the lungs using culture-independent, sequencing-based assays. Several sample types have been used to investigate the lung microbiota, each presenting specific challenges for preparation and analysis of microbial communities. Bronchoalveolar lavage fluid (BALF) enables the identification of microbiota specific to the lower lung but commonly has low bacterial density, increasing the risk of false-positive signal from contaminating DNA. The objectives of this study were to investigate the extent of contamination across a range of sample densities representative of BALF and identify features of contaminants that facilitate their removal from sequence data and aid in the interpretation of BALF sample 16S sequencing data. RESULTS Using three mock communities across a range of densities ranging from 8E+ 02 to 8E+ 09 16S copies/ml, we assessed taxonomic accuracy and precision by 16S rRNA gene sequencing and the proportion of reads arising from contaminants. Sequencing accuracy, precision, and the relative abundance of mock community members decreased with sample input density, with a significant drop-off below 8E+ 05 16S copies/ml. Contaminant OTUs were commonly inversely correlated with sample input density or not reproduced between technical replicates. Removal of taxa with these features or physical concentration of samples prior to sequencing improved both sequencing accuracy and precision for samples between 8E+ 04 and 8E+ 06 16S copies/ml. For the lowest densities, below 8E+ 03 16S copies/ml BALF, accuracy and precision could not be significantly improved using these approaches. Using clinical BALF samples across a large density range, we observed that OTUs with features of contaminants identified in mock communities were also evident in low-density BALF samples. CONCLUSION Relative abundance data and community composition generated by 16S sequencing of BALF samples across the range of density commonly observed in this sample type should be interpreted in the context of input sample density and may be improved by simple pre- and post-sequencing steps for densities above 8E+ 04 16S copies/ml.

中文翻译：

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人类支气管肺泡灌洗液的微生物群分析优化。

背景技术现在有可能使用与培养无关的，基于测序的测定法全面表征肺的微生物群。几种样本类型已被用于调查肺微生物群，每种样本对微生物群落的制备和分析提出了特殊的挑战。支气管肺泡灌洗液（BALF）可以识别下肺特有的微生物群，但通常细菌密度低，从而增加了污染DNA产生假阳性信号的风险。这项研究的目的是调查代表BALF的各种样品密度范围内的污染程度，并确定有助于从序列数据中去除污染物并帮助解释BALF样品16S测序数据的污染物特征。结果使用密度从8E + 02到8E + 09 16S拷贝/ ml范围内的三个模拟社区，我们通过16S rRNA基因测序以及由污染物引起的读数比例评估了分类学的准确性和精密度。测序的准确性，准确性和模拟群体成员的相对丰度随着样品输入密度的降低而降低，低于8E + 05 16S拷贝/ ml时显着下降。污染物的OTU通常与样品输入密度成反比，或者在技术复制之间未复制。在测序之前去除具有这些特征或样品的物理浓度的分类单元，可以提高8E + 04和8E + 06 16S拷贝/ ml之间样品的测序准确性和精密度。对于最低密度，低于8E + 03 16S拷贝/ ml BALF，使用这些方法无法显着提高准确性和精度。使用大密度范围内的临床BALF样本，我们观察到在低密度BALF样本中也存在在模拟群落中识别出的具有污染物特征的OTU。结论应在输入样本密度的背景下解释在此样本类型中通常观察到的密度范围内，通过BALF样本的16S测序生成的相对丰度数据和群落组成，并且可以通过简单的测序前和测序后的密度步骤来改善高于8E + 04 16S拷贝/ ml。