Institute for Digestive Research, Lithuanian University of Health Sciences, Kaunas 44307, Lithuania.
Department of Gastroenterology, Hepatology and Infectious Diseases, Otto-von-Guericke University Hospital, Magdeburg 39120, Germany.
World J Gastroenterol. 2023 Feb 21;29(7):1202-1218. doi: 10.3748/wjg.v29.i7.1202.
and the stomach microbiome play a crucial role in gastric carcinogenesis, and detailed characterization of the microbiome is necessary for a better understanding of the pathophysiology of the disease. There are two common modalities for microbiome analysis: DNA (16S rRNA gene) and RNA (16S rRNA transcript) sequencing. The implications from the use of one or another sequencing approach on the characterization and comparability of the mucosal microbiome in gastric cancer (GC) are poorly studied.
To characterize the microbiota of GC using 16S rRNA gene and its transcript and determine difference in the bacterial composition.
In this study, 316 DNA and RNA samples extracted from 105 individual stomach biopsies were included. The study cohort consisted of 29 healthy control individuals and 76 patients with GC. Gastric tissue biopsy samples were collected from damaged mucosa and healthy mucosa at least 5 cm from the tumor tissue. From the controls, healthy stomach mucosa biopsies were collected. From all biopsies RNA and DNA were extracted. RNA was reverse transcribed into cDNA. V1-V2 region of bacterial 16S rRNA gene from all samples were amplified and sequenced on an Illumina MiSeq platform. Bray-Curtis algorithm was used to construct sample-similarity matrices abundances of taxonomic ranks in each sample type. For significant differences between groups permutational multivariate analysis of variance and Mann-Whitney test followed by false-discovery rate test were used.
Microbial analysis revealed that only a portion of phylotypes (18%-30%) overlapped between microbial profiles obtained from DNA and RNA samples. Detailed analysis revealed differences between GC and controls depending on the chosen modality, identifying 17 genera at the DNA level and 27 genera at the RNA level. Ten of those bacteria were found to be different from the control group at both levels. The key taxa showed congruent results in various tests used; however, differences in 7 bacteria taxa were found uniquely only at the DNA level, and 17 uniquely only at the RNA level. Furthermore, RNA sequencing was more sensitive for detecting differences in bacterial richness, as well as differences in the relative abundance of and according to the type of GC. In each study group (control, tumor, and tumor adjacent) were found differences between DNA and RNA bacterial profiles.
Comprehensive microbial study provides evidence for the effect of choice of sequencing modality on the microbiota profile, as well as on the identified differences between case and control.
胃微生物组和胃黏膜微生物组在胃癌的发生发展中起着至关重要的作用,详细描述微生物组对于更好地了解疾病的病理生理学非常必要。目前有两种常用的微生物组分析方法:DNA(16S rRNA 基因)和 RNA(16S rRNA 转录本)测序。然而,这两种测序方法对胃癌(GC)黏膜微生物组的特征描述和可比性的影响还研究甚少。
使用 16S rRNA 基因及其转录本对 GC 中的微生物组进行特征描述,并确定细菌组成的差异。
本研究纳入了从 105 个体胃活检组织中提取的 316 个 DNA 和 RNA 样本。研究队列包括 29 名健康对照个体和 76 名 GC 患者。从肿瘤组织至少 5cm 以外的损伤黏膜和健康黏膜采集胃组织活检样本。从对照组中采集健康胃黏膜活检样本。从所有活检组织中提取 RNA 和 DNA。将 RNA 逆转录为 cDNA。对所有样本的细菌 16S rRNA 基因的 V1-V2 区进行扩增,并在 Illumina MiSeq 平台上进行测序。使用 Bray-Curtis 算法构建样本相似性矩阵,以表示每种样本类型中分类等级的丰度。采用置换多元方差分析和曼-惠特尼检验(Mann-Whitney test)对组间差异进行分析,同时使用错误发现率检验(false-discovery rate test)对结果进行校正。
微生物分析表明,只有部分(18%-30%)菌落在 DNA 和 RNA 样本中获得的微生物图谱中重叠。详细分析显示,GC 和对照组之间存在差异,这种差异取决于所选的模式,在 DNA 水平上鉴定出 17 个属,在 RNA 水平上鉴定出 27 个属。其中 10 种细菌在两个水平上与对照组均存在差异。关键分类群在各种测试中均显示出一致的结果;然而,有 7 种细菌仅在 DNA 水平上存在差异,17 种细菌仅在 RNA 水平上存在差异。此外,RNA 测序在检测细菌丰富度的差异以及根据 GC 类型检测 属和 属的相对丰度的差异方面更为敏感。在每个研究组(对照组、肿瘤组和肿瘤旁组织组)中,都发现了 DNA 和 RNA 细菌图谱之间的差异。
全面的微生物研究为测序模式对微生物组谱的影响以及病例与对照组之间确定的差异提供了证据。