Acute and long-term effects of antibiotics commonly used in laboratory animal medicine on the fecal microbiota

Abstract

Biomedical research relies on the use of animal models, and the animals used in those models receive medical care, including antibiotics for brief periods of time to treat conditions such as dermatitis, fight wounds, and suspected bacterial pathogens of unknown etiology. As many mouse model phenotypes are sensitive to changes in the gut microbiota, our goal was to examine the effect of antibiotics commonly administered to mice. Therefore, four treatment groups (subcutaneous enrofloxacin for 7 days, oral enrofloxacin for 14 days, oral trimethoprim-sulfamethoxazole for 14 days, and topical triple antibiotic ointment for 14 days) alongside a fifth control group receiving no treatment (n = 12/group) were included in our study. Fecal samples were collected prior to treatment, immediately after two weeks of exposure, and four weeks after cessation of treatment, and subjected to 16S rRNA library sequencing. The entire experimental design was replicated in mice from two different suppliers. As expected, several treatments including enrofloxacin and triple antibiotic ointment substantially decreased the amount of DNA recovered from fecal material, as well as the microbial richness. Notably, many of these effects were long-lasting with diminished gut microbiota (GM) richness four weeks following exposure, in both substrains of mice. Trimethoprim-sulfamethoxazole induced minimal to no discernible changes in the taxonomic composition beyond that seen in control mice. Collectively, these data highlight the need to consider the impact on GM of brief and seemingly routine use of antibiotics in the clinical care of research animals.

The gut microbiome of laboratory mice: considerations and best practices for translational research

“…For example, C57BL/6 mice harboring the GM of a wild mouse are extremely resistant to antibiotic-induced changes when compared to traditional SPF mice with either a Jackson or Taconic-origin GM (Rosshart et al 2019) (both comparably sparse SPF microbiomes). In contrast, the relatively low and high richness GM observed in mice from Jackson and Envigo appear to respond very similarly to several commonly used antibiotics (Korte et al 2020). While it might not be intuitive that antibiotic exposure would go unnoticed, or at least unappreciated, scenarios for such influences include exposure to tetracycline (Yin et al 2015) or doxycycline (Boynton et al 2017) to induce or silence gene expression, or the use of topical triple antibiotic ointment by veterinary care staff to treat fight wounds or dermatitis, which is subsequently ingested during grooming (Korte et al 2020).…”

“…In contrast, the relatively low and high richness GM observed in mice from Jackson and Envigo appear to respond very similarly to several commonly used antibiotics (Korte et al 2020). While it might not be intuitive that antibiotic exposure would go unnoticed, or at least unappreciated, scenarios for such influences include exposure to tetracycline (Yin et al 2015) or doxycycline (Boynton et al 2017) to induce or silence gene expression, or the use of topical triple antibiotic ointment by veterinary care staff to treat fight wounds or dermatitis, which is subsequently ingested during grooming (Korte et al 2020). It should also be noted that, despite a lack of appreciable effect on the GM as characterized using 16S rRNA amplicon sequencing, antibiotics may nonetheless affect model phenotypes via GM-independent mechanisms or changes in the GM below the resolution of current methods.…”

“…Regarding factors capable of influencing the GM of laboratory animals, the list continues to grow and includes source of the animals (Hirayama et al 1990;Hufeldt et al 2010;, diet (Org et al 2015;Ericsson et al 2018), caging (Ericsson et al 2018;Lundberg et al 2017), bedding (Ericsson et al 2018;Bidot et al 2018), water treatment (Bidot et al 2018), transportation (Montonye et al 2018;Ma et al 2012), housing density (Bogatyrev et al 2020;Basson et al 2020), sex (Org et al 2016;Kozik et al 2017), genetics (Hufeldt et al 2010;Hildebrand et al 2013;Kovacs et al 2011) and a wide range of antibiotics and other pharmacological agents (Korte et al 2020;Zhao et al 2020;Yin et al 2015;Boynton et al 2017). It should be noted that differences (or changes) in the composition of the GM, typically assessed via 16S rRNA amplicon sequencing, do not necessitate differences (or changes) in the function of those bacterial communities or model phenotypes.…”

“…It is a common member of the fecal microbiota in mice from many sources and is cultivable and available through the ATCC (BAA-835 and BAA-2869), lending itself to controlled experimentation. As it is frequently not affected by antibiotics (Korte et al 2020), it may proliferate in the context of antibiotic pressures and exert an increased effect on the host phenotype (Hansen et al 2012). In addition to L. murinus and L. intestinalis (presumably of ASF origin), several other Lactobacillus spp.…”

Reduced housing density improves statistical power of murine gut microbiota studies

“…One such variable that has gained considerable attention over the last couple of decades is the gut microbiome. In the context of mouse models, factors such as differing husbandry practices ( Ericsson et al, 2018 ; Bidot et al, 2018 ), different animal sources ( Ericsson et al, 2015 ; Hufeldt et al, 2010 ), and the use of antimicrobials ( Korte et al, 2020 ) can significantly alter the microbiome and affect the results of a study ( Hart et al, 2017 ; Moskowitz et al, 2019 ; Denning et al, 2011 ). While assessing differences within the microbiome in murine studies has become critical to understanding its influence on human health and disease susceptibility, it is important to understand the treatment effect size in the context of the inherent within-group variability, both of which may be altered by factors such as housing density.…”