Integrating Multiple Bacterial Phenotypes and Bayesian Network for Analyzing Health Risks of Pathogens in Plastisphere.
Anal Chem
; 96(28): 11374-11382, 2024 Jul 16.
Article
em En
| MEDLINE
| ID: mdl-38949233
ABSTRACT
Plastic pollution represents a critical threat to soil ecosystems and even humans, as plastics can serve as a habitat for breeding and refuging pathogenic microorganisms against stresses. However, evaluating the health risk of plastispheres is difficult due to the lack of risk factors and quantification model. Here, DNA sequencing, single-cell Raman-D2O labeling, and transformation assay were used to quantify key risk factors of plastisphere, including pathogen abundance, phenotypic resistance to various stresses (antibiotic and pesticide), and ability to acquire antibiotic resistance genes. A Bayesian network model was newly introduced to integrate these three factors and infer their causal relationships. Using this model, the risk of pathogen in the plastisphere is found to be nearly 3 magnitudes higher than that in free-living state. Furthermore, this model exhibits robustness for risk prediction, even in the absence of one factor. Our framework offers a novel and practical approach to assessing the health risk of plastispheres, contributing to the management of plastic-related threats to human health.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Teorema de Bayes
Limite:
Humans
Idioma:
En
Revista:
Anal Chem
Ano de publicação:
2024
Tipo de documento:
Article
País de afiliação:
China