Abstract
In this paper we present an investigation of parental-diet-driven metabolic programming in offspring using a novel computational network analysis tool. The impact of high paternal carbohydrate intake on offsprings’ phospholipid and triglyceride metabolism in F1 and F2 generations is described. Detailed lipid profiles were acquired from F1 neonate (3 weeks), F1 adult (16 weeks) and F2 neonate offspring in serum, liver, brain, heart and abdominal adipose tissues by MS and NMR. Using a purpose-built computational tool for analysing both phospholipid and fat metabolism as a network, we characterised the number, type and abundance of lipid variables in and between tissues (Lipid Traffic Analysis), finding a variety of reprogrammings associated with paternal diet. These results are important because they describe the long-term metabolic result of dietary intake by fathers. This analytical approach is important because it offers unparalleled insight into possible mechanisms for alterations in lipid metabolism throughout organisms.
Highlights
In this paper we present an investigation of parental-diet-driven metabolic programming in offspring using a novel computational network analysis tool
A combination of orthogonal techniques, direct infusion mass spectrometry (DI-MS21,22) and phosphorus nuclear magnetic resonance (31P NMR23) was used to profile the lipidome. This approach, known as dual spectroscopy[22], was used to identify and verify the abundance of lipid classes between the two ionisation modes respectively (NMR data for each compartment shown in Supplementary Information) and identified up to 586 lipid variables in positive ionisation mode and up to 564 lipid variables in negative ionisation mode in liver, brain, heart and adipose homogenates and in serum
This study was motivated by the hypothesis that a higher carbohydrate, lower protein intake in the paternal grandsire diet influences the lipid metabolism of their offspring
Summary
In this paper we present an investigation of parental-diet-driven metabolic programming in offspring using a novel computational network analysis tool. Using a purpose-built computational tool for analysing both phospholipid and fat metabolism as a network, we characterised the number, type and abundance of lipid variables in and between tissues (Lipid Traffic Analysis), finding a variety of reprogrammings associated with paternal diet. These results are important because they describe the long-term metabolic result of dietary intake by fathers. The programming effects on de novo lipogenesis were expected to be focused on the offsprings’ liver, the products of lipid biosynthesis are typically distributed throughout the organism quickly, especially triglycerides (TG)[16] Testing this hypothesis, required a tool for analysing lipid metabolism and distribution systemically. These analyses represent the state-of-the-art in the characterisation of lipid metabolism across organs
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