The experimental determination of reliable biodegradation rates for mono-aromatics towards evaluating QSBR models.
The experimental determination of reliable biodegradation rates for mono-aromatics towards evaluating QSBR models.
复制标题
通过实验确定单芳烃的可靠生物降解率，以评估 QSBR 模型。
DOI：
10.1016/j.watres.2019.05.075
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发表时间：
2019
期刊：
影响因子：
12.8
通讯作者：
Acharya K
中科院分区：
文献类型：
--
作者：
Acharya K
定量结构生物降解关系（QSBRs）是一种预测化学品生物降解性的工具。这项工作的目的是产生可靠的单芳香族化学品的生物降解数据，以评估和验证以前开发的QSBRs模型。开发了一种稳健的生物降解测试方法来估计特定的底物利用率，该底物利用率用作纯培养物中化学品生物降解率的替代指标。选择了五种具有代表性的单芳香族化学品，这些化学品具有广泛的生物降解性。在接种有已知降解剂的分批反应器中对每种化学品进行好氧生物降解实验。随着时间的推移，化学去除，降解生长和CO2生产进行了监测。采用全碳质量平衡模型对实验数据进行了解释，并确定了每种化学品的Monod动力学参数（Y、Ks、qmax和μmax）。此外，化学计量方程的测试化学品的好氧矿化。理论上估计的生物量和CO2产量与实验观察到的相似; 35%（s.d ± 8%）的回收底物碳转化为生物量，65%（s.d ± 8%）矿化为CO2。实验确定的特定底物利用率，qmax和qmax/Ks，在高和低底物浓度，分别表示，和一阶生物降解速率常数预测由以前的QSBR研究之间观察到显着的相关性。类似地，qmax与先前QSBR研究中表征化学品结构的选定分子描述符之间的相关性也是显著的。这些结果表明，QSBR模型可以是可靠的和强大的优先化学品半衰期监管筛选的目的。
Quantitative Structure Biodegradation Relationships (QSBRs) are a tool to predict the biodegradability of chemicals. The objective of this work was to generate reliable biodegradation data for mono-aromatic chemicals in order to evaluate and verify previously developed QSBRs models. A robust biodegradation test method was developed to estimate specific substrate utilization rates, which were used as a proxy for biodegradation rates of chemicals in pure culture. Five representative mono-aromatic chemicals were selected that spanned a wide range of biodegradability. Aerobic biodegradation experiments were performed for each chemical in batch reactors seeded with known degraders. Chemical removal, degrader growth and CO2production were monitored over time. Experimental data were interpreted using a full carbon mass balance model, and Monod kinetic parameters (Y, Ks, qmaxand μmax) for each chemical were determined. In addition, stoichiometric equations for aerobic mineralization of the test chemicals were developed. The theoretically estimated biomass and CO2yields were similar to those experimentally observed; 35% (s.d ± 8%) of the recovered substrate carbon was converted to biomass, and 65% (s.d ± 8%) was mineralised to CO2. Significant correlations were observed between the experimentally determined specific substrate utilization rates, as represented by qmaxand qmax/Ks, at high and low substrate concentrations, respectively, and the first order biodegradation rate constants predicted by a previous QSBR study. Similarly, the correlation between qmaxand selected molecular descriptors characterizing the chemicals structure in a previous QSBR study was also significant. These results suggest that QSBR models can be reliable and robust in prioritising chemical half-lives for regulatory screening purposes.
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