Predictive statistical models for monitoring antimicrobial resistance spread in the environment using Apis mellifera (L. 1758) colonies

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.

Keywords: Antimicrobial resitance; Environment; Honey bee; Monitoring; Resistant bacteria; Surveillance.