RESUMO
Metabolic profiling harbors the potential to better understand various disease entities such as cancer, diabetes, Alzheimer's, Parkinson's disease or COVID-19. To better understand such diseases and their intricate metabolic pathways in human studies, model animals are regularly used. There, standardized rearing conditions and uniform sampling strategies are prerequisites towards a successful metabolomic study that can be achieved through model organisms. Although metabolomic approaches have been employed on model organisms before, no systematic assessment of different conditions to optimize metabolite extraction across several organisms and sample types has been conducted. We address this issue using a highly standardized metabolic profiling assay analyzing 630 metabolites across three commonly used model organisms (Drosophila, mouse, and zebrafish) to find an optimal extraction protocol for various matrices. Focusing on parameters such as metabolite coverage, concentration and variance between replicates we compared seven extraction protocols. We found that the application of a combination of 75% ethanol and methyl tertiary-butyl ether (MTBE), while not producing the broadest coverage and highest concentrations, was the most reproducible extraction protocol. We were able to determine up to 530 metabolites in mouse kidney samples, 509 in mouse liver, 422 in zebrafish and 388 in Drosophila and discovered a core overlap of 261 metabolites in these four matrices. To enable other scientists to search for the most suitable extraction protocol in their experimental context and interact with this comprehensive data, we have integrated our data set in the open-source shiny app "MetaboExtract". Hereby, scientists can search for metabolites or compound classes of interest, compare them across the different tested extraction protocols and sample types as well as find reference concentration values.
RESUMO
OBJECTIVE: The molecular pathogenesis of late complications associated with type 2 diabetes mellitus (T2DM) is not yet fully understood. While high glucose levels indicated by increased HbA1c only poorly explain disease progression and late complications, a pro-inflammatory status, oxidative stress, and reactive metabolites generated by metabolic processes were postulated to be involved. Individuals with metabolic syndrome (MetS) frequently progress to T2DM, whereby 70% of patients with T2DM show non-alcoholic fatty liver disease (NAFLD), the hepatic manifestation of MetS, and insulin resistance (IR). Epidemiological studies have shown that T2DM and steatosis are associated with alterations in iron metabolism and hepatic iron accumulation. Excess free iron triggers oxidative stress and a switch towards a macrophage pro-inflammatory status. However, so far it remains unclear whether hepatic iron accumulation plays a causative role in the generation of IR and T2DM or whether it is merely a manifestation of altered hepatic metabolism. To address this open question, we generated and characterized a mouse model of T2DM with IR, steatosis, and iron overload. METHODS: Leprdb/db mice hallmarked by T2DM, IR and steatosis were crossed with Fpnwt/C326S mice with systemic iron overload to generate Leprdb/db/Fpnwt/C326S mice. The resulting progeny was characterized for major diabetic and iron-related parameters. RESULTS: We demonstrated that features associated with T2DM in Leprdb/db mice, such as obesity, steatosis, or IR, reduce the degree of tissue iron overload in Fpnwt/C326S mice, suggesting an 'iron resistance' phenotype. Conversely, we observed increased serum iron levels that strongly exceeded those in the iron-overloaded Fpnwt/C326S mice. Increased hepatic iron levels induced oxidative stress and lipid peroxidation and aggravated IR, as indicated by diminished IRS1 phosphorylation and AKT activation. Additionally, in the liver, we observed gene response patterns indicative of de novo lipogenesis and increased gluconeogenesis as well as elevated free glucose levels. Finally, we showed that iron overload in Leprdb/db/Fpnwt/C326S mice enhances microvascular complications observed in retinopathy, suggesting that iron accumulation can enhance diabetic late complications associated with the liver and the eye. CONCLUSION: Taken together, our data show that iron causes the worsening of symptoms associated with the MetS and T2DM. These findings imply that iron depletion strategies together with anti-diabetic drugs may ameliorate IR and diabetic late complications.