Effect of Echium oil compared with marine oils on lipid profile and inhibition of hepatic steatosis in LDLr knockout mice

Abstract Background In an effort to identify new alternatives for long-chain n-3 polyunsaturated fatty acids (LC n-3 PUFA) supplementation, the effect of three sources of omega 3 fatty acids (algae, fish and Echium oils) on lipid profile and inflammation biomarkers was evaluated in LDL receptor knockout mice. Methods The animals received a high fat diet and were supplemented by gavage with an emulsion containing water (CON), docosahexaenoic acid (DHA, 42.89%) from algae oil (ALG), eicosapentaenoic acid (EPA, 19.97%) plus DHA (11.51%) from fish oil (FIS), and alpha-linolenic acid (ALA, 26.75%) plus stearidonic acid (SDA, 11.13%) from Echium oil (ECH) for 4 weeks. Results Animals supplemented with Echium oil presented lower cholesterol total and triacylglycerol concentrations than control group (CON) and lower VLDL than all of the other groups, constituting the best lipoprotein profile observed in our study. Moreover, the Echium oil attenuated the hepatic steatosis caused by the high fat diet. However, in contrast to the marine oils, Echium oil did not affect the levels of transcription factors involved in lipid metabolism, such as Peroxisome Proliferator Activated Receptor α (PPAR α) and Liver X Receptor α (LXR α), suggesting that it exerts its beneficial effects by a mechanism other than those observed to EPA and DHA. Echium oil also reduced N-6/N-3 FA ratio in hepatic tissue, which can have been responsible for the attenuation of steatosis hepatic observed in ECH group. None of the supplemented oils reduced the inflammation biomarkers. Conclusion Our results suggest that Echium oil represents an alternative as natural ingredient to be applied in functional foods to reduce cardiovascular disease risk factors.

Multimodality and flexibility of stochastic gene expression

We consider a general class of mathematical models for stochastic gene expression where the transcription rate is allowed to depend on a promoter state variable that can take an arbitrary (finite) number of values. We provide the solution of the master equations in the stationary limit, based on a factorization of the stochastic transition matrix that separates timescales and relative interaction strengths, and we express its entries in terms of parameters that have a natural physical and/or biological interpretation. The solution illustrates the capacity of multiple states promoters to generate multimodal distributions of gene products, without the need for feedback. Furthermore, using the example of a three states promoter operating at low, high, and intermediate expression levels, we show that using multiple states operons will typically lead to a significant reduction of noise in the system. The underlying mechanism is that a three-states promoter can change its level of expression from low to high by passing through an intermediate state with a much smaller increase of fluctuations than by means of a direct transition.