通过弥合微生物生长动力学和微生物种群动态,建立对活化泥微生物群的预测性理解
Zhang Cheng1, Weibo Xia1, Sean McKelvey1,2
1Department of Civil & Environmental Engineering, Temple University, 1947 N. 12th Street, Philadelphia, Pennsylvania 19122, United States.
Environmental science & technology
|October 6, 2025
概括
一种新的混合建模方法通过将微生物生长动力学与人口动力学联系起来来增强微生物组预测. 这种方法提高了活性污泥系统的准确性,为微生物生态提供了洞察力.
科学领域:
- 微生物生态学 微生物生态学
- 生物信息学是一种生物信息学.
- 环境微生物学 环境微生物学
背景情况:
- 目前的微生物组建模方法在预测准确性方面存在局限性.
- 了解微生物种群动态对于生态洞察至关重要.
研究的目的:
- 开发一种新的混合建模方法,整合微生物生长动力学和人口动态.
- 提高在活性污泥系统中对微生物群的预测性理解.
主要方法:
- 使用了466个活性污泥样本和数据转化技术.
- 应用贝叶斯网络和拓数据分析以识别微生物协会和基石种群.
- 使用活性泥微生物数据库 (MiDAS) 和人工神经网络验证的模型推断.
主要成果:
- 在42个核心群体中,36个表现出稳定的动态 (接近于零).
- 结合微生物动力学参数的混合模型提高了预测准确性 (布雷-库蒂斯相似性为0.70与0.66).
- 确定了基石种群和依赖时间的微生物相互作用.
结论:
- 拟议的混合建模框架为微生物组分析提供了一种灵活和潜在的可适应方法.
- 这种方法增强了自然系统中依赖时间的数据的预测能力.
- 这些发现有助于更深入地了解工程系统中的微生物生态学.
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