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饮食调节免疫基因表达与功能性免疫反应之间的关系。

Diet modulates the relationship between immune gene expression and functional immune responses.

机构信息

School of Life Sciences, University of Lincoln, Brayford Pool, Lincoln, LN6 7TS, UK.

Lancaster Environment Centre, Lancaster University, Lancaster, LA1 4YQ, UK.

出版信息

Insect Biochem Mol Biol. 2019 Jun;109:128-141. doi: 10.1016/j.ibmb.2019.04.009. Epub 2019 Apr 5.

DOI:10.1016/j.ibmb.2019.04.009
PMID:30954680
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6527921/
Abstract

Nutrition is vital to health and the availability of resources has long been acknowledged as a key factor in the ability to fight off parasites, as investing in the immune system is costly. Resources have typically been considered as something of a "black box", with the quantity of available food being used as a proxy for resource limitation. However, food is a complex mixture of macro- and micronutrients, the precise balance of which determines an animal's fitness. Here we use a state-space modelling approach, the Geometric Framework for Nutrition (GFN), to assess for the first time, how the balance and amount of nutrients affects an animal's ability to mount an immune response to a pathogenic infection. Spodoptera littoralis caterpillars were assigned to one of 20 diets that varied in the ratio of macronutrients (protein and carbohydrate) and their calorie content to cover a large region of nutrient space. Caterpillars were then handled or injected with either live or dead Xenorhabdus nematophila bacterial cells. The expression of nine genes (5 immune, 4 non-immune) was measured 20 h post immune challenge. For two of the immune genes (PPO and Lysozyme) we also measured the relevant functional immune response in the hemolymph. Gene expression and functional immune responses were then mapped against nutritional intake. The expression of all immune genes was up-regulated by injection with dead bacteria, but only those in the IMD pathway (Moricin and Relish) were substantially up-regulated by both dead and live bacterial challenge. Functional immune responses increased with the protein content of the diet but the expression of immune genes was much less predictable. Our results indicate that diet does play an important role in the ability of an animal to mount an adequate immune response, with the availability of protein being the most important predictor of the functional (physiological) immune response. Importantly, however, immune gene expression responds quite differently to functional immunity and we would caution against using gene expression as a proxy for immune investment, as it is unlikely to be reliable indicator of the immune response, except under specific dietary conditions.

摘要

营养对于健康至关重要,资源的可获得性长期以来一直被认为是抵御寄生虫的关键因素,因为投资于免疫系统是有代价的。资源通常被视为一种“黑箱”,可用食物的数量被用作资源限制的替代物。然而,食物是一种复杂的宏量和微量营养素混合物,其精确平衡决定了动物的适应性。在这里,我们使用状态空间建模方法——营养几何框架(GFN),首次评估了营养物的平衡和数量如何影响动物对致病感染产生免疫反应的能力。我们将滨水粘虫幼虫分配到 20 种不同的饮食中,这些饮食在宏量营养素(蛋白质和碳水化合物)的比例及其热量含量上有所不同,以涵盖营养空间的大部分区域。然后,幼虫要么被处理,要么被注射活的或死的 Xenorhabdus nematophila 细菌细胞。在免疫挑战后 20 小时测量了 9 个基因(5 个免疫,4 个非免疫)的表达。对于两个免疫基因(PPO 和溶菌酶),我们还在血淋巴中测量了相关的功能性免疫反应。然后根据营养摄入情况对基因表达和功能性免疫反应进行映射。所有免疫基因的表达都因注射死细菌而被上调,但只有 IMD 途径(Moricin 和 Relish)中的基因被死细菌和活细菌挑战显著上调。功能性免疫反应随着饮食中蛋白质含量的增加而增加,但免疫基因的表达则不太可预测。我们的研究结果表明,饮食确实在动物产生足够免疫反应的能力方面起着重要作用,蛋白质的可获得性是功能性(生理)免疫反应的最重要预测因素。然而,重要的是,免疫基因表达对功能性免疫反应的反应截然不同,我们建议不要将基因表达作为免疫投资的替代物,因为它不太可能成为免疫反应的可靠指标,除非在特定的饮食条件下。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/77b6/6527921/e240f31bd2dd/gr7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/77b6/6527921/cb3d584824f9/fx1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/77b6/6527921/5fb10fc8b525/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/77b6/6527921/c74c47d026da/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/77b6/6527921/d051d9a72d06/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/77b6/6527921/da3446066398/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/77b6/6527921/47e56dfc7d97/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/77b6/6527921/b01e23538ce7/gr6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/77b6/6527921/e240f31bd2dd/gr7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/77b6/6527921/cb3d584824f9/fx1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/77b6/6527921/5fb10fc8b525/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/77b6/6527921/c74c47d026da/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/77b6/6527921/d051d9a72d06/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/77b6/6527921/da3446066398/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/77b6/6527921/47e56dfc7d97/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/77b6/6527921/b01e23538ce7/gr6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/77b6/6527921/e240f31bd2dd/gr7.jpg

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