背景:随着抗生素的广泛使用,他们的副作用受到了更多的关注。我们特别关注抗生素对儿童身体的影响。因此,我们分析了抗生素治疗后儿童肠道菌群的特征性变化,以更深入地探讨抗生素相关疾病的发病机制,为诊断和治疗提供依据。
方法:我们在珠海西区招募了28名支气管肺炎患儿,中国,并根据抗生素类型分为三个治疗组。我们在抗生素治疗前和治疗后3-5天采集了儿童的粪便样本。16SrRNA基因测序用于分析抗生素治疗对儿童肠道菌群的影响。连续非参数数据表示为中值并使用Wilcoxon秩和检验进行分析。
结果:虽然α多样性分析发现在短期抗生素治疗后,儿童肠道菌群的平均丰度没有显著变化,β多样性分析表明,即使在短期抗生素治疗后,儿童肠道微生物群的组成和多样性也发生了显著变化。我们还发现,美洛西林舒巴坦可以抑制变形杆菌的生长,拟杆菌,和Verrucomicrobia,头孢曲松钠抑制Verrucomicrobia和拟杆菌,阿奇霉素抑制梭菌,放线菌,变形杆菌,和Verrucomicrobia。我们进一步在属水平上进行了比较分析,发现每组中的簇明显不同。最后,我们发现阿奇霉素对肠道微生物群的代谢功能影响最大,其次是头孢曲松,美洛西林舒巴坦治疗后肠道菌群代谢过程无明显变化。
结论:抗生素治疗显著影响儿童肠道菌群的多样性,即使在短期抗生素治疗后。不同种类的抗生素主要影响不同的微生物群,导致代谢功能的变化。同时,我们确定了一系列在抗生素治疗后显著不同的肠道微生物群.这些微生物群可以用作生物标志物,为诊断和治疗抗生素相关疾病提供额外的基础。
BACKGROUND: With the widespread use of antibiotics, more attention has been paid to their side effects. We paid extra attention to the impact of antibiotics on children\'s bodies. Therefore, we analyzed the characteristic changes in the gut microbiota of children after antibiotic treatment to explore the pathogenesis of antibiotic-associated diseases in more depth and to provide a basis for diagnosis and treatment.
METHODS: We recruited 28 children with bronchopneumonia in the western district of Zhuhai,
China, and divided them into three treatment groups based on antibiotic type. We took stool samples from children before and 3-5 days after antibiotic treatment. 16S rRNA gene sequencing was used to analyze the effects of antibiotic therapy on the gut microbiota of children. Continuous nonparametric data are represented as median values and analyzed using the Wilcoxon rank-sum test.
RESULTS: While alpha diversity analysis found no significant changes in the mean abundance of the gut microbiota of children after a short course of antibiotic treatment, beta diversity analysis demonstrated significant changes in the composition and diversity of the gut microbiota of children even after a short course of antibiotic therapy. We also found that meloxicillin sulbactam can inhibit the growth of Proteobacteria, Bacteroidetes, and Verrucomicrobia, ceftriaxone inhibits Verrucomicrobia and Bacteroides, and azithromycin inhibits Fusobacteria, Actinobacteria, Proteobacteria, and Verrucomicrobia. We further performed a comparative analysis at the genus level and found significantly different clusters in each group. Finally, we found that azithromycin had the greatest effect on the metabolic function of intestinal microbiota, followed by ceftriaxone, and no significant change in the metabolic process of intestinal microbiota after meloxicillin sulbactam treatment.
CONCLUSIONS: Antibiotic treatment significantly affects the diversity of intestinal microbiota in children, even after a short course of antibiotic treatment. Different classes of antibiotics affect diverse microbiota primarily, leading to varying alterations in metabolic function. Meanwhile, we identified a series of intestinal microbiota that differed significantly after antibiotic treatment. These groups of microbiota could be used as biomarkers to provide an additional basis for diagnosing and treating antibiotic-associated diseases.