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Updated: Jul 4, 2025
Author Spotlight: Understanding and Detecting Environmental Antimicrobial Resistance by Combining Culture-Based Techniques and Genomics
Published on: July 19, 2024
Predictive statistical models for monitoring antimicrobial resistance spread in the environment using Apis mellifera
Ilaria Resci1, Laura Zavatta2, Silvia Piva3
1Research Centre for Agriculture and Environment (CREA-AA), Council for Agricultural Research and Agricultural Economics Analysis, Via di Corticella 133, 40128 Bologna, Italy; Department of Veterinary Sciences, University of Bologna, Via Tolara di Sopra, 43, 40064 Ozzano Dell'Emilia (BO), Italy.
Abstract:
The rise of antimicrobial resistance (AMR) is one of the most relevant problems for human and animal health. According to One Health Approach, it is important to regulate the use of antimicrobials and monitor the spread of AMR in the environment as well. Apis mellifera (L. 1758) colonies were used as bioindicators thanks to their physical and behavioural characteristics. During their foraging flights, bees can intercept small particles, including atmospheric particulate matter, etc., and also microorganisms. To date, the antimicrobial surveillance network is limited to the sanitary level but lacks into environmental context. This study aimed to evaluate the use of A. mellifera colonies distributed throughout the Emilia-Romagna region (Italy) as indicators of environmental antimicrobial-resistant bacteria. This was performed by creating a statistical predictive model that establishes correlations between environmental characteristics and the likelihood of isolating specific bacterial genera and antimicrobial-resistant strains. A total of 608 strains were isolated and tested for susceptibility to 19 different antimicrobials. Aztreonam-resistant strains were significantly related to environments with sanitary structures, agricultural areas and wetlands, while urban areas present a higher probability of trimethoprim/sulfamethoxazole-resistant strains isolation. Concerning genera, environments with sanitary structures and wetlands are significantly related to the genera Proteus spp., while the Escherichia spp. strains can be probably isolated in industrial environments. The obtained models showed maximum values of Models Accuracy and robustness (R2) of 55 % and 24 %, respectively. The results indicate the efficacy of utilizing A. mellifera colonies as valuable bioindicators for estimating the prevalence of AMR in environmentally disseminated bacteria. This survey can be considered a good basis for the development of further studies focused on monitoring both sanitary and animal pathology, creating a specific network in the environments of interest.
Insights
Honey bees (Apis mellifera) can monitor environmental antimicrobial resistance (AMR). Researchers linked bee-collected bacteria to specific environments, aiding AMR surveillance beyond human and animal health sectors.
Area of Science:
- Environmental microbiology
- One Health approach
- Antimicrobial resistance (AMR) surveillance
Background:
- Antimicrobial resistance (AMR) poses a significant threat to human and animal health.
- Environmental monitoring of AMR is crucial, complementing existing sanitary surveillance.
- Honey bees (Apis mellifera) serve as effective bioindicators due to their foraging behavior.
Purpose of the Study:
- To assess the utility of Apis mellifera colonies for monitoring environmental antimicrobial-resistant bacteria.
- To develop a predictive model correlating environmental factors with bacterial isolation and AMR prevalence.
- To establish a baseline for a broader environmental AMR surveillance network.
Main Methods:
- Deployment of Apis mellifera colonies across the Emilia-Romagna region, Italy.
- Isolation and antimicrobial susceptibility testing of 608 bacterial strains against 19 antimicrobials.
- Statistical modeling to correlate environmental characteristics with specific bacterial genera and resistant strains.
Main Results:
- Aztreonam-resistant strains linked to sanitary areas, agricultural land, and wetlands.
- Trimethoprim/sulfamethoxazole-resistant strains more probable in urban environments.
- Proteus spp. associated with sanitary structures and wetlands; Escherichia spp. with industrial areas.
- Predictive models achieved up to 55% accuracy and 24% robustness (R²).
Conclusions:
- Apis mellifera colonies are effective bioindicators for estimating environmental AMR prevalence.
- The study provides a foundation for integrated environmental and health-focused AMR monitoring.
- Developing a dedicated environmental AMR surveillance network is recommended.
