Consideration of Gut Microbiome in Murine Models of Diseases

Abstract

The gut microbiome (GM), a complex community of bacteria, viruses, protozoa, and fungi located in the gut of humans and animals, plays significant roles in host health and disease. Animal models are widely used to investigate human diseases in biomedical research and the GM within animal models can change due to the impact of many factors, such as the vendor, husbandry, and environment. Notably, variations in GM can contribute to differences in disease model phenotypes, which can result in poor reproducibility in biomedical research. Variation in the gut microbiome can also impact the translatability of animal models. For example, standard lab mice have different pathogen exposure experiences when compared to wild or pet store mice. As humans have antigen experiences that are more similar to the latter, the use of lab mice with more simplified microbiomes may not yield optimally translatable data. Additionally, the literature describes many methods to manipulate the GM and differences between these methods can also result in differing interpretations of outcomes measures. In this review, we focus on the GM as a potential contributor to the poor reproducibility and translatability of mouse models of disease. First, we summarize the important role of GM in host disease and health through different gut–organ axes and the close association between GM and disease susceptibility through colonization resistance, immune response, and metabolic pathways. Then, we focus on the variation in the microbiome in mouse models of disease and address how this variation can potentially impact disease phenotypes and subsequently influence research reproducibility and translatability. We also discuss the variations between genetic substrains as potential factors that cause poor reproducibility via their effects on the microbiome. In addition, we discuss the utility of complex microbiomes in prospective studies and how manipulation of the GM through differing transfer methods can impact model phenotypes. Lastly, we emphasize the need to explore appropriate methods of GM characterization and manipulation.

Host Age Prediction from Fecal Microbiota Composition in Male C57BL/6J Mice

“…The western diet-fed animals also highlight that accurate age prediction is not possible for microbiotas dissimilar to our training set. Hence, a new training set would be required for the myriad of factors such as housing facilities and murine strain that influence gut microbiota heterogeneity ( 4 , 44 ).…”

Safety of a Novel Listeria monocytogenes-Based Vaccine Vector Expressing NcSAG1 (Neospora caninum Surface Antigen 1)

“…However, responses among individual mice of the same dose group varied, and not all mice developed immunity. External and internal factors such as those reported in humans ( Zimmermann and Curtis, 2019 ) and mice ( Franklin and Ericsson, 2017 ; Voelkl et al., 2020 ; Voelkl and Würbel, 2021 ; Zhang et al., 2021 ) (i.e. stress, microbiota diversity, variation in vaccination dose) may cause this variability and need to be further evaluated.…”

Role of Microbiota in Viral Infections and Pathological Progression

“…The causal relationships remain unclear, as viral infections can affect the microbiota. Therefore, animal models and in vitro experimental systems may also be useful tools in understanding these causal relationships and the underlying molecular mechanisms, which have been reviewed extensively elsewhere [ 216 , 217 ]. In addition, it is necessary to elucidate the molecular mechanism of the immune activation of secondary metabolites produced by bacteria and clarify the role of molecules such as extracellular vesicles [ 218 ], whose functions have recently been explained as communication tools among bacteria and between bacteria and host cells, in infectious diseases.…”