Simulating the Influence of Conjugative-Plasmid Kinetic Values on the Multilevel Dynamics of Antimicrobial Resistance in a Membrane Computing Model.
Simulating the Influence of Conjugative-Plasmid Kinetic Values on the Multilevel Dynamics of Antimicrobial Resistance in a Membrane Computing Model.
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DOI：
10.1128/aac.00593-20
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发表时间：
2020-07-22
影响因子：
4.9
通讯作者：
Baquero F
中科院分区：
文献类型：
--
作者：
Campos M;San Millán Á;Sempere JM;Lanza VF;Coque TM;Llorens C;Baquero F
含有抗生素抗性基因的细菌质粒对于抗生素抗性的传播至关重要。已知质粒的动力学值不同，即接合率、与相关质粒的拷贝数不相容性导致的分离率以及复制过程中的随机丢失率。它们在降低适应性和补偿质粒成本的补偿突变频率方面对细胞的成本也有所不同。然而，我们不知道这些值的变化如何影响质粒及其抗性基因在复杂生态系统（例如微生物群）中的成功。含有抗生素抗性基因的细菌质粒对于抗生素抗性的传播至关重要。已知质粒的动力学值不同，即接合率、与相关质粒的拷贝数不相容性导致的分离率以及复制过程中的随机丢失率。它们在降低适应性和补偿质粒成本的补偿突变频率方面对细胞的成本也有所不同。然而，我们不知道这些值的变化如何影响质粒及其抗性基因在复杂生态系统（例如微生物群）中的成功。基因在质粒中，质粒在细胞中，细胞在宿主体内的细菌群体和微生物群中，宿主在医院的人类社区或处于不同程度的交叉定植和抗生素暴露下的社区中。质粒动力学的差异可能会对抗生素耐药性的全球传播产生影响。新的膜计算方法有助于预测这些后果。在我们的模拟中，至少 10−3 的接合频率会影响带有抗性质粒的菌株的优势。如果宿主菌株能够维持相似质粒的两个拷贝，就会出现不同抗生素耐药性的共存。 10−4 或 10−5 的质粒丢失率或≥0.06 的质粒适应性成本有利于位于最丰富物种中的质粒。补偿性突变对质粒适应度成本的有益影响与高突变频率（10−3 至 10−5）的成本成正比。该计算模型的结果清楚地表明质粒动力学的变化如何改变医院环境中抗生素耐药性的整个群体生态。
Bacterial plasmids harboring antibiotic resistance genes are critical in the spread of antibiotic resistance. It is known that plasmids differ in their kinetic values, i.e., conjugation rate, segregation rate by copy number incompatibility with related plasmids, and rate of stochastic loss during replication. They also differ in cost to the cell in terms of reducing fitness and in the frequency of compensatory mutations compensating plasmid cost. However, we do not know how variation in these values influences the success of a plasmid and its resistance genes in complex ecosystems, such as the microbiota. Bacterial plasmids harboring antibiotic resistance genes are critical in the spread of antibiotic resistance. It is known that plasmids differ in their kinetic values, i.e., conjugation rate, segregation rate by copy number incompatibility with related plasmids, and rate of stochastic loss during replication. They also differ in cost to the cell in terms of reducing fitness and in the frequency of compensatory mutations compensating plasmid cost. However, we do not know how variation in these values influences the success of a plasmid and its resistance genes in complex ecosystems, such as the microbiota. Genes are in plasmids, plasmids are in cells, and cells are in bacterial populations and microbiotas, which are inside hosts, and hosts are in human communities at the hospital or the community under various levels of cross-colonization and antibiotic exposure. Differences in plasmid kinetics might have consequences on the global spread of antibiotic resistance. New membrane computing methods help to predict these consequences. In our simulation, conjugation frequency of at least 10−3 influences the dominance of a strain with a resistance plasmid. Coexistence of different antibiotic resistances occurs if host strains can maintain two copies of similar plasmids. Plasmid loss rates of 10−4 or 10−5 or plasmid fitness costs of ≥0.06 favor plasmids located in the most abundant species. The beneficial effect of compensatory mutations for plasmid fitness cost is proportional to this cost at high mutation frequencies (10−3 to 10−5). The results of this computational model clearly show how changes in plasmid kinetics can modify the entire population ecology of antibiotic resistance in the hospital setting.