Modeling the Biodegradation of Bacterial Community Assembly Linked Antibiotics in River Sediment Using a Deterministic Stochastic Combined Model
Modeling the Biodegradation of Bacterial Community Assembly Linked Antibiotics in River Sediment Using a Deterministic Stochastic Combined Model
复制标题
使用确定性随机组合模型模拟河流沉积物中细菌群落组装相关抗生素的生物降解
DOI：
10.1021/acs.est.6b01573
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发表时间：
2016
影响因子：
11.4
通讯作者：
Jing Wang
中科院分区：
文献类型：
--
作者：
Wenlong Zhang;Yi Li;Chao Wang;Peifang Wang;Jun Hou;Zhongbo Yu;Lihua Niu;Linqiong Wang;Jing Wang
为了解细菌群落组装与抗生素组装联用生物降解的相互作用，建立了一个包含Monod动力学、Logistic动力学和随机项的模型框架来描述河流沉积物中细菌群落组装联用磺胺甲恶唑（SMX）的生物降解.模拟结果表明，SMX的生物降解受确定性过程和随机性过程的共同控制，其相对重要性取决于SMX的浓度。根据不同的过程，获得了SMX在实验河流沉积物中生物降解的阈值浓度（即，20 μg/kg）。较高浓度的SMX（>20 μg/kg）通过生态位分化促进了抗生素降解菌在微生物群落中的驯化，从而导致SMX的特异性微生物代谢。相比之下，较低的SMX引入浓度（<20 μg/kg）不能导致确定性过程的显著增加，并导致SMX通过共存微生物的共代谢而被生物降解。该模型可以被认为是一个有用的工具，以改善水环境保护和修复技术。
To understand the interaction between bacterial community assembly and the assembly linked antibiotics biodegradation, a unique model framework containing a Monod kinetic, a logistic kinetic, and a stochastic item was established to describe the biodegradation of bacterial community assembly linked sulfamethoxazole (SMX) in river sediment. According to the modeling results, both deterministic and stochastic processes driving bacterial population variations played important roles in controlling SMX biodegradation, and the relative importance depended on the in situ concentration of SMX. A threshold concentration of SMX, which was biodegraded in the experimental river sediment depending on different processes, was obtained (i.e., 20 μg/kg). The higher introduced concentration of SMX (>20 μg/kg) was found to promote the acclimation of antibiotic degradation bacteria in microbial community through niche differentiation, which resulted in the specific microbial metabolization of SMX. In contrast, the lower introduced concentration of SMX (<20 μg/kg) was not able to lead to a significant increase of deterministic processes and resulted in the biodegradation of SMX through co-metabolism by the coexisting microorganisms. The developed model can be considered a useful tool for improving the technologies of water environmental protection and remediation.