Identification of limiting factors essential for phylogenetic analysis of low biomass microbiota samples.. Refinement of 16S rRNA gene analysis for low-biomass samples

Background: High-throughput phylogenetic 16S rRNA gene analysis has permitted to thoroughly delve into microbial community complexity and to understand host-microbiota interactions in health and disease. The analysis comprises sample collection and storage, genomic DNA extraction, 16S rRNA gene amplification, high-throughput amplicon sequencing and bioinformatic analysis. Low biomass microbiota samples (e.g. biopsies, tissue swabs and lavages) are receiving increasing attention, but optimal standardization for analysis of low biomass samples has yet to be developed. Here we tested the lower bacterial concentration required to perform 16S rRNA gene analysis using three different DNA extraction protocols, three different mechanical lysing series and two different PCR protocols. Methods: A mock microbiota community standard and low biomass samples (108, 107, 106, 105 and 104 microbes) from two healthy donor stools were employed to assess optimal sample processing for 16S rRNA gene analysis using paired-end Illumina MiSeq technology.Results: Three DNA extraction protocols tested in our study performed similar with regards to representing microbiota composition, but extraction yield was better for silica columns compared to bead absorption and chemical precipitation. Furthermore, increasing mechanical lysing time and repetition did ameliorate the representation of bacterial composition. The most influential factor enabling appropriate representation of microbiota composition remains sample biomass. Indeed, bacterial densities below 106 cells resulted in loss of sample identity based on cluster analysis for all tested protocols. Finally, we excluded DNA extraction bias using a genomic DNA standard, which revealed that a semi-nested PCR protocol represented microbiota composition better than classical PCR.Conclusions: Based on our results, starting material concentration is an important limiting factor, highlighting the need to adapt protocols for dealing with low biomass samples. Our study suggests that the use of prolonged mechanical lysing, silica membrane DNA isolation and a semi-nested PCR protocol improve the analysis of low biomass samples. Using the improved protocol we report a lower limit of 106 bacteria per sample for robust and reproducible microbiota analysis.

研究背景：高通量系统发育16S rRNA基因（16S rRNA gene）分析技术，已实现对微生物群落复杂性的深入解析，并助力阐明健康与疾病状态下宿主-菌群互作机制。该分析流程涵盖样本采集与保存、基因组DNA提取、16S rRNA基因扩增、高通量扩增子测序及生物信息学分析。低生物量微生物组样本（low biomass microbiota samples，如活检样本、组织拭子及灌洗液）正受到越来越多的关注，但目前仍缺乏适用于此类样本的标准化分析流程。本研究针对16S rRNA基因分析所需的最低细菌浓度展开测试，共采用3种DNA提取方案、3套机械裂解程序及2种PCR扩增方案。
研究方法：本研究以模拟微生物群落标准品（mock microbiota community standard）及2名健康志愿者粪便来源的梯度低生物量样本（菌量分别为10^8、10^7、10^6、10^5及10^4个微生物）为研究对象，基于双端Illumina MiSeq（paired-end Illumina MiSeq）测序技术，评估适用于16S rRNA基因分析的最优样本处理流程。
研究结果：本研究测试的3种DNA提取方案在菌群组成表征效果上整体相近，但硅胶柱法的提取产量优于磁珠吸附法与化学沉淀法。此外，延长机械裂解时长并增加裂解次数，可改善细菌组成的表征效果。影响菌群组成准确表征的最关键因素仍为样本生物量。经聚类分析证实，对于所有测试方案而言，当细菌密度低于10^6个/样本时，样本的群落特征信息会丢失。最后，本研究通过基因组DNA标准品排除了DNA提取环节的偏倚，结果显示半巢式PCR方案在菌群组成表征效果上优于常规PCR。
研究结论：基于本研究结果，起始样本浓度是影响分析效果的重要限制因素，这凸显了针对低生物量样本优化实验方案的必要性。本研究表明，采用延长机械裂解步骤、硅胶膜法DNA提取及半巢式PCR方案，可提升低生物量样本的微生物组分析效果。经优化后的实验方案，本研究确定其用于稳定且可重复的微生物组分析的最低样本菌量阈值为10^6个/样本。