C57BL/6J (B6J) and C57BL/6N (B6N) mice are the most frequently used substrains in C57BL/6 (B6) inbred mice, serving as physiological models for in vivo studies and as background strains to build transgenic mice. However, the differences in metabolic phenotypes between B6J and B6N mice are not coherent, and genotypic differences in metabolically important tissues have not been well studied. The phenotypic differences between B6J and B6N substrains have often been attributed to the role of the nicotinamide nucleotide transhydrogenase (Nnt) gene, whereby B6J has a spontaneous missense mutation of Nnt. Nevertheless, phenotypic differences between the two cannot be explained by Nnt mutations alone, especially in metabolic traits. Therefore, we aimed to investigate the genetic cause of the phenotypic differences between B6J and B6N mice. Determining consistent genetic differences across multiple tissues involved in metabolic traits such as subcutaneous and visceral white adipose tissues, brown adipose tissue, skeletal muscle, liver, hypothalamus, and hippocampus, may help explain phenotypic differences in metabolism between the two substrains. We report candidate genes along with comparative data on body weight, tissue weight, blood components involved in metabolism, and energy balance of B6J and B6N mice. Insulin degrading enzyme, adenylosuccinate synthase 2, and ectonucleotide triphosphate diphosphohydrolase 4 were highly expressed in B6J mice compared with those in B6N mice, and Nnt, WD repeat and FYVE domain containing 1, and dynein light chain Tctex-type 1 were less expressed in B6J mice compared with those in B6N mice in all seven tissues. Considering the extremely wide use of both substrains and their critical importance in generating transgenic and knock-out models, these findings guide future research across several interrelated fields.

C57BL/6J (B6J) and C57BL/6N (B6N) mice are the most frequently used substrains in C57BL/6 (B6) inbred mice, serving as physiological models for in vivo studies and as background strains to build transgenic mice. However, little attention has been paid to the phenotypic differences between B6J and B6N mice, and they have often been attributed to mutations in the nicotinamide nucleotide transhydrogenase (Nnt) gene, which was found only in B6J. Nevertheless, phenotypic differences between the two that cannot be explained by Nnt mutations alone, especially in metabolic traits, indicate the presence of genetic variants associated with metabolism other than Nnt. We aimed to identify these genetic differences between B6J and B6N mice. Our results provide insights into differentially expressed genes (DEGs) in adipose tissues, skeletal muscle, liver, hypothalamus, and hippocampus, and phenotypic differences in metabolic traits between B6J and B6N. B6J mice had significantly lower body weight than B6N mice, regardless of a normal or high-fat diet. Blood insulin levels in B6J mice were significantly lower than those in B6N mice and glucose levels during dietary obesity were higher in B6J mice. Metabolic assessments revealed greater physical activity, less food intake, and higher energy expenditure in B6J mice than in B6N mice. Among the DEGs that were highly expressed in B6J mice compared to B6N mice, three genes—insulin degrading enzyme, adenylosuccinate synthase 2, and ectonucleotide triphosphate diphosphohydrolase 4—and the DEGs that had lower expression in B6J mice compared to B6N mice— Nnt , WD repeat and FYVE domain containing 1, and dynein light chain Tctex-type 1—were overlapped in all seven tissues. Our study provides insights into DEGs between B6J and B6N, which will be useful for substrain selection for mouse experiments, avoiding erroneous experimental results, and reviewing the results of studies that have used B6J, B6N, or mixed substrains.

We aimed to identify gut microbiota that influences body weight by elucidating the association with diets and host genes. Germ-free (GF) mice with and without fecal microbiota transplant (FMT) were fed a normal, high-carbohydrate, or high-fat diet. FMT mice exhibited greater total body weight; adipose tissue and liver weights; blood glucose, insulin, and total cholesterol levels; and oil droplet size than the GF mice, regardless of diet. However, the extent of weight gain and metabolic parameter levels associated with gut microbiota depended on the nutrients ingested. For example, a disaccharide- or polysaccharide-rich diet caused more weight gain than a monosaccharide-rich diet. An unsaturated fatty acid-rich diet had a greater microbial insulin-increasing effect than a saturated fatty acid-rich diet. Perhaps the difference in microbial metabolites produced from substances taken up by the host created metabolic differences. Therefore, we analyzed such dietary influences on gut microbiota, differentially expressed genes between GF and FMT mice, and metabolic factors, including body weight. The results revealed a correlation between increased weight gain, a fat-rich diet, increased Ruminococcaceae abundance, and decreased claudin 22 gene expression. These findings suggest that weight regulation might be possible through the manipulation of the gut microbiota metabolism using the host’s diet.

We aimed to identify gut microbiota that influences body weight by elucidating the association with diets and host genes. Germ-free (GF) mice with and without fecal microbiota transplant (FMT) were fed a normal, high-carbohydrate, or high-fat diet. FMT mice exhibited greater total body weight, adipose tissue and liver weights, blood glucose, insulin, and total cholesterol levels, and oil droplet size than the GF mice, regardless of diet. However, the extent of weight gain and metabolic parameter levels associated with gut microbiota depended on the nutrients ingested. For example, a disaccharide- or polysaccharide-rich diet caused more weight gain than a monosaccharide-rich diet. An unsaturated fatty acid-rich diet had a greater effect on increased insulin by microorganisms than a saturated fatty acid-rich diet. Perhaps the difference in microbial metabolites produced from substances taken up by the host created metabolic differences. Therefore, we analyzed such dietary influences on gut microbiota, differentially expressed genes between GF and FMT mice, and metabolic factors including body weight. The results revealed a correlation between increased weight gain, a fat-rich diet, increased Ruminococcaceae abundance, and decreased claudin 22 gene expression. Thus, prevention of claudin 22 downregulation by manipulating Ruminococcaceae metabolism may inhibit weight gain.