Plastic polarization of macrophage is involved in tumorigenesis. M1‐polarized macrophage mediates rapid inflammation, entity clearance and may also cause inflammation‐induced mutagenesis. M2‐polarized macrophage inhibits rapid inflammation but can promote tumour aggravation. ω‐3 long‐chain polyunsaturated fatty acid (PUFA)‐derived metabolites show a strong anti‐inflammatory effect because they can skew macrophage polarization from M1 to M2. However, their role in tumour promotive M2 macrophage is still unknown. Resolvin D1 and D2 (RvD1 and RvD2) are docosahexaenoic acid (DHA)‐derived docosanoids converted by 15‐lipoxygenase then 5‐lipoxygenase successively. We found that although dietary DHA can inhibit prostate cancer in vivo, neither DHA (10 μmol/L) nor RvD (100 nmol/L) can directly inhibit the proliferation of prostate cancer cells in vitro. Unexpectedly, in a cancer cell‐macrophage co‐culture system, both DHA and RvD significantly inhibited cancer cell proliferation. RvD1 and RvD2 inhibited tumour‐associated macrophage (TAM or M2d) polarization. Meanwhile, RvD1 and RvD2 also exhibited anti‐inflammatory effects by inhibiting LPS‐interferon (IFN)‐γ‐induced M1 polarization as well as promoting interleukin‐4 (IL‐4)‐mediated M2a polarization. These differential polarization processes were mediated, at least in part, by protein kinase A. These results suggest that regulation of macrophage polarization using RvDs may be a potential therapeutic approach in the management of prostate cancer.
Gut microbiota play important roles in host metabolism, especially in diabetes. However, why different diets lead to similar diabetic states despite being associated with different microbiota is not clear. Mice were fed two high-energy diets (HED) with the same energy density but different fat-to-sugar ratios to determine the associations between the microbiota and early-stage metabolic syndrome. The two diets resulted in different microbiota but similar diabetic states. Interestingly, the microbial gene profiles were not significantly different, and many common metabolites were identified, including l-aspartic acid, cholestan-3-ol (5β, 3α), and campesterol, which have been associated with lipogenesis and inflammation. Our study suggests that different metabolic-syndrome-inducing diets may result in different microbiota but similar microbiomes and metabolomes. This suggests that the metagenome and metabolome are crucial for the prognosis and pathogenesis of obesity and metabolic syndrome.
IMPORTANCE Various types of diet can lead to type 2 diabetes. The gut microbiota in type 2 diabetic patients are also different. So, two questions arise: whether there are any commonalities between gut microbiota induced by different pro-obese diets and whether these commonalities lead to disease. Here we found that high-energy diets with two different fat-to-sugar ratios can both cause obesity and prediabetes but enrich different gut microbiota. Still, these different gut microbiota have similar genetic and metabolite compositions. The microbial metabolites in common between the diets modulate lipid accumulation and macrophage inflammation in vivo and in vitro. This work suggests that studies that only use 16S rRNA amplicon sequencing to determine how the microbes respond to diet and associate with diabetic state are missing vital information.
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