Sub-MIC antibiotics influence the microbiome, resistome and structure of riverine biofilm communities.
Sub-MIC antibiotics influence the microbiome, resistome and structure of riverine biofilm communities.
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亚最低抑菌浓度的抗生素影响河流生物膜群落的微生物组、耐药基因组和结构。
DOI：
10.3389/fmicb.2023.1194952
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发表时间：
2023
影响因子：
5.2
通讯作者：
中科院分区：
文献类型：
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作者：
抗生素的次最小抑菌浓度（sub-MIC）对水生环境的影响尚未完全了解。在这里，我们探索这些影响，采用一个复制的缩影系统与河水喂养的生物膜群落连续暴露在8周的时间内，以低于MIC的曝光（1/10，1/50，和1/100 MIC）的混合常见的抗生素（环丙沙星，链霉素，土霉素）。使用结构-功能方法，需要显微镜和宏基因组技术，揭示了微生物组，耐药基因组，代谢组和功能预测的细节生物膜进行了检查。还对三种常用的微生物组和耐药基因组数据库进行了比较。在亚MIC抗生素处理之间观察到生物膜结构的差异，细胞外聚合物和自养生物（藻类和蓝藻）和原生动物生物量总体减少，特别是在1/10亚MIC条件下。虽然宏基因组学分析表明，微生物多样性在亚MIC 1/10抗生素处理时最低，但耐药基因组多样性在亚MIC 1/50时最高。这项研究还指出了基准分析工具和仔细选择参考数据库的重要性，因为不同方法检测到的抗菌素耐药基因（ARG）身份和丰度存在差异。最终，在亚MIC暴露生物膜中检测到的最多的ARG是对氨基糖苷类、四环素类、β-内酰胺类、磺胺类和甲氧苄啶产生耐药性的ARG。微生物组和耐药组特征的共同出现一致地显示了变形菌属和氨基糖苷类ARG之间的关系。我们的研究结果支持这样的假设，即持续暴露于亚MIC抗生素促进了河流生物膜群落中抗生素耐药性的传播和流行，并改变了整体微生物群落的代谢功能。
The effects of sub-minimum inhibitory concentrations (sub-MICs) of antibiotics on aquatic environments is not yet fully understood. Here, we explore these effects by employing a replicated microcosm system fed with river water where biofilm communities were continuously exposed over an eight-week period to sub-MIC exposure (1/10, 1/50, and 1/100 MIC) to a mix of common antibiotics (ciprofloxacin, streptomycin, and oxytetracycline). Biofilms were examined using a structure–function approach entailing microscopy and metagenomic techniques, revealing details on the microbiome, resistome, virulome, and functional prediction. A comparison of three commonly used microbiome and resistome databases was also performed. Differences in biofilm architecture were observed between sub-MIC antibiotic treatments, with an overall reduction of extracellular polymeric substances and autotroph (algal and cyanobacteria) and protozoan biomass, particularly at the 1/10 sub-MIC condition. While metagenomic analyses demonstrated that microbial diversity was lowest at the sub-MIC 1/10 antibiotic treatment, resistome diversity was highest at sub-MIC 1/50. This study also notes the importance of benchmarking analysis tools and careful selection of reference databases, given the disparity in detected antimicrobial resistance genes (ARGs) identity and abundance across methods. Ultimately, the most detected ARGs in sub-MICs exposed biofilms were those that conferred resistance to aminoglycosides, tetracyclines, β-lactams, sulfonamides, and trimethoprim. Co-occurrence of microbiome and resistome features consistently showed a relationship between Proteobacteria genera and aminoglycoside ARGs. Our results support the hypothesis that constant exposure to sub-MICs antibiotics facilitate the transmission and promote prevalence of antibiotic resistance in riverine biofilms communities, and additionally shift overall microbial community metabolic function.
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影响因子：
7.7
作者：
Beghini F;McIver LJ;Blanco-Míguez A;Dubois L;Asnicar F;Maharjan S;Mailyan A;Manghi P;Scholz M;Thomas AM;Valles-Colomer M;Weingart G;Zhang Y;Zolfo M;Huttenhower C;Franzosa EA;Segata N
通讯作者：
Segata N
影响因子：
4.5
作者：
Baharoglu Z;Bikard D;Mazel D
通讯作者：
Mazel D
影响因子：
5.2
作者：
Chonova, Teofana;Kurmayer, Rainer;Bouchez, Agnes
通讯作者：
Bouchez, Agnes
影响因子：
4.6
作者：
Couto N;Schuele L;Raangs EC;Machado MP;Mendes CI;Jesus TF;Chlebowicz M;Rosema S;Ramirez M;Carriço JA;Autenrieth IB;Friedrich AW;Peter S;Rossen JW
通讯作者：
Rossen JW
DOI：
10.1093/jac/dkaa345
发表时间：
2020-12-01
期刊：
The Journal of antimicrobial chemotherapy
影响因子：
--
作者：
Bortolaia V;Kaas RS;Ruppe E;Roberts MC;Schwarz S;Cattoir V;Philippon A;Allesoe RL;Rebelo AR;Florensa AF;Fagelhauer L;Chakraborty T;Neumann B;Werner G;Bender JK;Stingl K;Nguyen M;Coppens J;Xavier BB;Malhotra-Kumar S;Westh H;Pinholt M;Anjum MF;Duggett NA;Kempf I;Nykäsenoja S;Olkkola S;Wieczorek K;Amaro A;Clemente L;Mossong J;Losch S;Ragimbeau C;Lund O;Aarestrup FM
通讯作者：
Aarestrup FM