微生物组研究的规模越来越大,以检测环境因素对我们肠道微生物组的潜在小影响,或者微生物组对我们健康的影响。因此,需要快速和可重复的DNA分离方法来处理成千上万的粪便样本。我们使用Chemagic360化学和磁性分离模块I(MSMI)仪器比较了两种样品防腐剂和四种不同的预处理方案,以找到从数千个粪便样品中分离DNA的最佳方法。预处理包括珠子跳动,以管和板格式处理样品,和蛋白酶K孵育。最佳方法提供了足够的高质量DNA产量而没有污染。三个人类粪便样本(成人,高级,和婴儿)提取了技术副本。提取包括阴性对照(OMNIgeneGUT,DNA/RNA屏蔽液,和化学裂解缓冲液1)以检测交叉污染和ZymoBIOMICS肠道微生物组标准作为阳性对照,以模拟人类肠道微生物组和评估提取方法的敏感性。所有样品均使用ChemagicDNAStool200H96试剂盒(PerkinElmer,芬兰)。样品收集在两种防腐剂中,OMNIgeneGUT和DNA/RNA屏蔽液。使用Qubit荧光计测量DNA数量,使用凝胶电泳的DNA纯度和质量,以及基于16SrRNA基因的V3V4和V4区域测序的分类学特征。珠打增加细菌多样性。最大的增加是在布劳特氏菌属中检测到的,双歧杆菌,和Ruminococus.防腐剂显示细菌丰度的微小差异。V3V4和V4区域之间的轮廓差异很大,多样性样本较低。阴性对照显示来自粪便样品中丰富的属的迹象。肠道标准和粪便样本的技术重复显示低变化。所选择的分离方案包括来自制造商的推荐步骤以及珠打浆。发现珠子跳动对于检测难以溶解的细菌是必要的。该方案在不同粪便重复和ZymoBIOMICS肠道微生物组标准中的DNA产量方面是可重复的。96格式的MSM1仪器和预处理提供了自动化和处理大型样品收集的可能性。两种防腐剂在样品处理方面都是可行的,并且在分类特征上具有低变化。16SrRNA靶区域对细菌谱的组成具有高度影响。
目的:下一代测序(NGS)是一种广泛使用的用于确定肠道菌群组成的方法。由于个体之间肠道微生物群组成的差异,微生物组研究已扩展到大型人群研究,以最大程度地检测对微生物-宿主相互作用的小影响。因此,对快速可靠的微生物分析的需求不断增加,使高通量96格式DNA提取的优化整合为基于NGS的下游应用。然而,实验方案容易出现样本收集和存储的偏差和错误,DNA提取,引物选择和测序,和生物信息学分析。方法学偏见可能导致微生物组概况的差异,导致使用不同协议的研究和实验室之间的差异。为了提高测量的一致性和可信度,微生物组分析方法的标准化已经在许多领域得到认可。
Microbiome studies are becoming larger in size to detect the potentially small effect that environmental factors have on our gut microbiomes, or that the microbiome has on our health. Therefore, fast and reproducible DNA isolation methods are needed to handle thousands of fecal samples. We used the Chemagic 360 chemistry and Magnetic Separation Module I (MSMI) instrument to compare two sample preservatives and four different pre-treatment protocols to find an optimal method for DNA isolation from thousands of fecal samples. The pre-treatments included bead beating, sample handling in tube and plate format, and proteinase K incubation. The optimal method offers a sufficient yield of high-quality DNA without contamination. Three human fecal samples (adult, senior, and infant) with technical replicates were extracted. The extraction included negative controls (OMNIgeneGUT, DNA/RNA shield fluid, and Chemagic Lysis Buffer 1) to detect cross-contamination and ZymoBIOMICS Gut Microbiome Standard as a positive control to mimic the human gut microbiome and assess sensitivity of the extraction method. All samples were extracted using Chemagic DNA Stool 200 H96 kit (PerkinElmer, Finland). The samples were collected in two preservatives, OMNIgeneGUT and DNA/RNA shield fluid. DNA quantity was measured using Qubit-fluorometer, DNA purity and quality using gel electrophoresis, and taxonomic signatures with 16S rRNA gene-based sequencing with V3V4 and V4 regions. Bead beating increased bacterial diversity. The largest increase was detected in gram-positive genera Blautia, Bifidobacterium, and Ruminococcus. Preservatives showed minor differences in bacterial abundances. The profiles between the V3V4 and V4 regions differed considerably with lower diversity samples. Negative controls showed signs from genera abundant in fecal samples. Technical replicates of the Gut Standard and stool samples showed low variation. The selected isolation protocol included recommended steps from manufacturer as well as bead beating. Bead beating was found to be necessary to detect hard-to-lyse bacteria. The protocol was reproducible in terms of DNA yield among different stool replicates and the ZymoBIOMICS Gut Microbiome Standard. The MSM1 instrument and pre-treatment in a 96-format offered the possibility of automation and handling of large sample collections. Both preservatives were feasible in terms of sample handling and had low variation in taxonomic signatures. The 16S rRNA target region had a high impact on the composition of the bacterial profile.
OBJECTIVE: Next-generation sequencing (NGS) is a widely used method for determining the composition of the gut microbiota. Due to the differences in the gut microbiota composition between individuals, microbiome studies have expanded into large population studies to maximize detection of small effects on microbe-host interactions. Thus, the demand for a rapid and reliable microbial profiling is continuously increasing, making the optimization of high-throughput 96-format DNA extraction integral for NGS-based downstream applications. However, experimental protocols are prone to bias and errors from sample collection and storage, to DNA extraction, primer selection and sequencing, and bioinformatics analyses. Methodological bias can contribute to differences in microbiome profiles, causing variability across studies and laboratories using different protocols. To improve consistency and confidence of the measurements, the standardization of microbiome analysis methods has been recognized in many fields.