婴儿年龄与肠道携带的抗性基因成反比,反映了生命早期微生物碳水化合物代谢的变化

IF 23.7 Q1 MICROBIOLOGY
iMeta Pub Date : 2024-01-31 DOI:10.1002/imt2.169
Xinming Xu, Qingying Feng, Tao Zhang, Yunlong Gao, Qu Cheng, Wanqiu Zhang, Qinglong Wu, Ke Xu, Yucan Li, Nhu Nguyen, Diana H. Taft, David A. Mills, Danielle G. Lemay, Weiyun Zhu, Shengyong Mao, Anyun Zhang, Kelin Xu, Jinxin Liu
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引用次数: 0

摘要

婴儿肠道微生物组越来越被认为是抗生素耐药性基因的储存库,但婴儿肠道耐药性基因组的组装及其影响因素在很大程度上仍不为人所知。我们对来自 6 个国家 963 名婴儿的 4132 个元基因组中的耐药性基因组进行了鉴定,共观察到 4285 个耐药性基因。健康婴儿(N = 272)的固有抗性基因组模式可分为两个阶段:多化合物抗性阶段(0-7 个月)和四环素-莫匹罗星-β-内酰胺为主的阶段(8-14 个月)。微生物分类解释了健康婴儿肠道耐药基因组的 40.7%,其中埃希氏菌(25.5%)携带的耐药基因最多。在对所有可用婴儿(N = 963)进行的进一步分析中,我们发现年龄是对抗药性基因组影响最大的因素,并且与头 3 年的总体抗药性呈负相关(p < 0.001)。利用随机森林方法,一组 34 个抗性基因可用于预测年龄(R2 = 68.0%)。通过微生物宿主推断分析,我们推断婴儿抗药性基因组的形成与年龄有关,这是肠道微生物组变化的结果,主要是由不同类群中不成比例地携带抗药性基因的类群的变化所驱动的(例如,大肠埃希菌比其他类群更频繁地携带抗药性基因)。我们进行了元基因组功能剖析和元基因组组装基因组分析,结果表明肠道抗性基因组的发展是由微生物碳水化合物代谢的变化驱动的,婴儿期对类杆菌的碳水化合物活性酶的需求增加,而对假单胞菌的需求减少。重要的是,我们观察到获得性抗性基因随着时间的推移而增加,这与发育中的婴儿肠道微生物组中横向基因转移增加有关。总之,婴儿年龄与抗菌素耐药性基因水平呈负相关,这反映了肠道微生物组的组成发生了变化,而这种变化很可能是由生命早期微生物碳水化合物代谢需求的变化所驱动的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Infant age inversely correlates with gut carriage of resistance genes, reflecting modifications in microbial carbohydrate metabolism during early life

Infant age inversely correlates with gut carriage of resistance genes, reflecting modifications in microbial carbohydrate metabolism during early life

The infant gut microbiome is increasingly recognized as a reservoir of antibiotic resistance genes, yet the assembly of gut resistome in infants and its influencing factors remain largely unknown. We characterized resistome in 4132 metagenomes from 963 infants in six countries and 4285 resistance genes were observed. The inherent resistome pattern of healthy infants (N = 272) could be distinguished by two stages: a multicompound resistance phase (Months 0–7) and a tetracycline-mupirocin-β-lactam-dominant phase (Months 8–14). Microbial taxonomy explained 40.7% of the gut resistome of healthy infants, with Escherichia (25.5%) harboring the most resistance genes. In a further analysis with all available infants (N = 963), we found age was the strongest influencer on the resistome and was negatively correlated with the overall resistance during the first 3 years (p < 0.001). Using a random-forest approach, a set of 34 resistance genes could be used to predict age (R2 = 68.0%). Leveraging microbial host inference analyses, we inferred the age-dependent assembly of infant resistome was a result of shifts in the gut microbiome, primarily driven by changes in taxa that disproportionately harbor resistance genes across taxa (e.g., Escherichia coli more frequently harbored resistance genes than other taxa). We performed metagenomic functional profiling and metagenomic assembled genome analyses whose results indicate that the development of gut resistome was driven by changes in microbial carbohydrate metabolism, with an increasing need for carbohydrate-active enzymes from Bacteroidota and a decreasing need for Pseudomonadota during infancy. Importantly, we observed increased acquired resistance genes over time, which was related to increased horizontal gene transfer in the developing infant gut microbiome. In summary, infant age was negatively correlated with antimicrobial resistance gene levels, reflecting a composition shift in the gut microbiome, likely driven by the changing need for microbial carbohydrate metabolism during early life.

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