Using the wax moth larva Galleria mellonella infection model to detect emerging bacterial pathogens.

Climate change, changing farming practices, social and demographic changes and rising levels of antibiotic resistance are likely to lead to future increases in opportunistic bacterial infections that are more difficult to treat. Uncovering the prevalence and identity of pathogenic bacteria in the environment is key to assessing transmission risks. We describe the first use of the Wax moth larva Galleria mellonella, a well-established model for the mammalian innate immune system, to selectively enrich and characterize pathogens from coastal environments in the South West of the UK. Whole-genome sequencing of highly virulent isolates revealed amongst others a Proteus mirabilis strain carrying the Salmonella SGI1 genomic island not reported from the UK before and the recently described species Vibrio injenensis hitherto only reported from human patients in Korea. Our novel method has the power to detect bacterial pathogens in the environment that potentially pose a serious risk to public health.

Trace levels of sewage effluent are sufficient to increase class 1 integron prevalence in freshwater biofilms without changing the core community.

Most river systems are impacted by sewage effluent. It remains unclear if there is a lower threshold to the concentration of sewage effluent that can significantly change the structure of the microbial community and its mobile genetic elements in a natural river biofilm. We used novel in situ mesocosms to conduct replicated experiments to study how the addition of low-level concentrations of sewage effluent (nominally 2.5 ppm) affects river biofilms in two contrasting Chalk river systems, the Rivers Kennet and Lambourn (high/low sewage impact, respectively). 16S sequencing and qPCR showed that community composition was not significantly changed by the sewage effluent addition, but class 1 integron prevalence (Lambourn control 0.07% (SE ± 0.01), Lambourn sewage effluent 0.11% (SE ± 0.006), Kennet control 0.56% (SE ± 0.01), Kennet sewage effluent 1.28% (SE ± 0.16)) was significantly greater in the communities exposed to sewage effluent than in the control flumes (ANOVA, F = 5.11, p = 0.045) in both rivers. Furthermore, the difference in integron prevalence between the Kennet control (no sewage effluent addition) and Kennet sewage-treated samples was proportionally greater than the difference in prevalence between the Lambourn control and sewage-treated samples (ANOVA (interaction between treatment and river), F = 6.42, p = 0.028). Mechanisms that lead to such differences could include macronutrient/biofilm or phage/bacteria interactions. Our findings highlight the role that low-level exposure to complex polluting mixtures such as sewage effluent can play in the spread of antibiotic resistance genes. The results also highlight that certain conditions, such as macronutrient load, might accelerate spread of antibiotic resistance genes.