Niska-Blakie, J., Gopinathan, L., Low, K.N. et al. Knockout of the non-essential gene SUGCT creates diet-linked, age-related microbiome disbalance with a diabetes-like metabolic syndrome phenotype. Cell. Mol. Life Sci. (2019). https://doi.org/10.1007/s00018-019-03359-z
Abstract:
SUGCT (C7orf10) is a mitochondrial enzyme that synthesizes glutaryl-CoA from glutarate in tryptophan and lysine catabolism, but it has not been studied in vivo. Although mutations in Sugct lead to Glutaric Aciduria Type 3 disease in humans, patients remain largely asymptomatic despite high levels of glutarate in the urine. To study the disease mechanism, we generated SugctKO mice and uncovered imbalanced lipid and acylcarnitine metabolism in kidney in addition to changes in the gut microbiome. After SugctKO mice were treated with antibiotics, metabolites were comparable to WT, indicating that the microbiome affects metabolism in SugctKO mice. SUGCT loss of function contributes to gut microbiota dysbiosis, leading to age-dependent pathological changes in kidney, liver, and adipose tissue. This is associated with an obesity-related phenotype that is accompanied by lipid accumulation in kidney and liver, as well as “crown-like” structures in adipocytes. Furthermore, we show that the SugctKO kidney pathology is accelerated and exacerbated by a high-lysine diet. Our study highlights the importance of non-essential genes with no readily detectable early phenotype, but with substantial contributions to the development of age-related pathologies, which result from an interplay between genetic background, microbiome, and diet in the health of mammals.
License type:
http://creativecommons.org/licenses/by/4.0/
Funding Info:
Open access funding provided by Lund University. We thank Zakiah Talib for animal care and all past and current members of the Kaldis lab for support and discussions. We thank Roger Low for contributions at early project stages and Keng Hwee Neo for exploratory work and controls not included here. We thank Falicia Goh from Natural Product Research Laboratory in BII for the discussions about the analysis of the metabolomics data. We thank Norman Pavelka for discussions and Mark Lewandoski for the β-actin–Cre/Flpe mice. We acknowledge the technical expertise provided by the Advanced Molecular Pathology Laboratory at IMCB. Lino Tessarollo was supported by the Intramural Research Program of the NIH, National Cancer Institute, Center for Cancer Research. This work was supported by the Biomedical Research Council of A*STAR (Agency for Science, Technology and Research), Singapore, and in part by a Grant from the National Medical Research Council Singapore, NMRC (OFIRG15nov120), Natural Product Research Laboratory BMRC Transition Fund (H16/99/b0/004), and the National Research Foundation Singapore (NRF-CRP17-2017-06).