Environmental factors capable of broadly interfering with nutritional lifespan extension paradigms
Description
Despite being principally prescribed to treat type 2 diabetes, biguanides, especially metformin and phenformin, have been shown to extend lifespan and healthspan in preclinical models. While there have been conflicting results in studies involving rodents and humans, consistent evidence indicates metformin and phenformin's ability to significantly extend lifespan in C. elegans. We find that variation in agar from lot-to-lot or from different manufacturers influences metformin's ability to extend lifespan in diverse Caenorhabditis species. Using unbiased metabolomics and genetics, we traced the ability of certain agars to interfere with metformin-prompted lifespan extension to differences in glucose, dipeptide, and trace element levels. These compounds act directly in the worm, independently of the bacterial food source, preventing longevity through action downstream of longevity effectors skn-1 and AMPK. In contrast, phenformin prompts robust lifespan extension in the face of environmental changes and exhibits broad positive effects in aging across genetically diverse Caenorhabditis species. To begin to precisely identify candidate molecules that could interfere with metformin-prompted lifespan extension, we conducted an unbiased mass spectrometry analysis of small molecules in nematode growth media made with Bacto agar, Fisher Scientific agar, and agarose.
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MetaboAnalyst 6.0 package 65 was used for data analysis. Mass integration values for 17072 compounds from positive modes and 7977 compounds from negative modes were extracted from full-scan LC-MS/MS measurements of NGM agar plates, OP50-1 E. coli, and wild-type C. elegans, treated with vehicle, 4.5 mM phenformin, or 50 mM metformin, on NGM plates made of agarose, Fisher Scientific agar and Bacto agar. Compounds missing greater than 50% values were discarded. Missing and zero values in the data matrix were imputed via replacement with 1/5th of the minimum positive value for each variable. Compounds that do not vary more than 40% of the interquartile range across conditions are removed. Abundance values were subsequently filtered based on interquartile range and log10 transformed. Sum normalization was then performed, followed with division by the standard deviation of each variable (auto-scaling). Normalized abundance values for each metabolite were then extracted and assessed for statistical significance via one-way ANOVA followed by false discovery rate (FDR) control using the Benjamini-Hochberg method. Post hoc testing was then performed using Fisher’s LSD to evaluate pairwise comparison significance. Metabolites were considered differentially abundant in any one condition with an FDR controlled p-value <0.05. Metabolites in NGM agar plates made of agarose, Fisher Scientific agar and Bacto agar, treated with vehicle, 4.5 mM phenformin, or 50 mM metformin from positive and negative modes were visualized using a heatmap of Euclidean distance measurements, with Ward clustering of samples and normalized compound abundances included. Additional information can be found in the excel spreadsheet in the "Analysis Key" tab.
Institutions
- Harvard Medical School
- Massachusetts General Hospital
- Broad Institute