Meroni Gabriele, Pace Fabio, Grossi Enzo, Casini Valentina, Drago Lorenzo
Laboratory of Clinical Microbiology, Department of Biomedical Science for Health, University of Milan, Milan, Italy.
UOC Gastroenterology and Digestive Endoscopy, Bolognini Hospital, Seriate, Italy.
New Microbiol. 2020 Jan;43(1):22-27. Epub 2020 Mar 1.
The gut microbiota is a complex and dynamic ecosystem with a strong influence on the host's health. Several factors can modify the gut's bacterial composition, often leading to the onset of intestinal dysbiosis. Therefore, it is essential not only to evaluate the quantitative bacterial changes occurring in the human microbiota but also to characterize relationships existing among all the microorganisms. This study aimed to evaluate the impact of bowel cleansing on the fecal microbiota network by highlighting differences between fecal microflora before and after colonoscopy, and luminal samples during colonoscopy. Fecal and luminal samples, previously analyzed by mean of Next-Generation Sequencing (NGS) for their bacterial abundance, were further processed by a method based on Artificial Neural Network (ANN) architecture. The bowel lavage had a strong effect on the intestinal microbiota network, leading to significant changes in the distribution of different bacterial hubs potentially involved in the microbiota homeostasis. Furthermore, the fecal and luminal microbiota showed a different bacterial network, characterized by distinct microbial hubs. In particular, the latter seemed to be rich in potentially pathogenic bacteria which, in physiological conditions, are counteracted by fecal microorganisms.
肠道微生物群是一个复杂且动态的生态系统，对宿主健康有重大影响。多种因素可改变肠道细菌组成，常导致肠道生态失调的发生。因此，不仅要评估人类微生物群中发生的细菌数量变化，还要描述所有微生物之间存在的关系，这至关重要。本研究旨在通过突出结肠镜检查前后粪便微生物群以及结肠镜检查期间管腔样本之间的差异，评估肠道清洁对粪便微生物群网络的影响。先前通过下一代测序（NGS）分析其细菌丰度的粪便和管腔样本，采用基于人工神经网络（ANN）架构的方法进行进一步处理。肠道灌洗对肠道微生物群网络有强烈影响，导致可能参与微生物群稳态的不同细菌枢纽分布发生显著变化。此外，粪便和管腔微生物群显示出不同的细菌网络，其特征是有不同的微生物枢纽。特别是，后者似乎富含潜在致病细菌，在生理条件下，这些细菌会被粪便微生物抵消。
