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盲肠微生物演替及其与肉鸡营养代谢的明显关联。

Cecal Microbial Succession and Its Apparent Association with Nutrient Metabolism in Broiler Chickens.

机构信息

College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, People's Republic of China.

School of Basic Medical Sciences, Shaanxi University of Chinese Medicine, Xianyang, Shaanxi, People's Republic of China.

出版信息

mSphere. 2023 Jun 22;8(3):e0061422. doi: 10.1128/msphere.00614-22. Epub 2023 Apr 5.

DOI:10.1128/msphere.00614-22
PMID:37017520
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10286727/
Abstract

The chicken gut microbiota plays an influential role in nutrient absorption and metabolism. A clear picture of microbiota succession can enhance host nutrition and disease resistance. This study investigated the cecal microbiota succession of broilers between 3 and 42 days after hatching using 16S rRNA gene sequencing and analyzed its potential association with intestinal nutrient metabolism. Microbiota structure differed significantly at different time points depending on the microbiota alpha-diversity or beta-diversity. and promoted succession on days 3 to 7 and days 28 to 35, respectively. and maintained homeostasis on days 7 to 28 and days 35 to 42. , [], , and promoted succession on days 3 to 7; modified microbial composition on days 7 to 14; and regulated microbial structure from days 21 to 28. The microbiota structure was relatively stable on days 14 to 21 and days 28 to 35. Spearman's correlation analysis indicated a positive correlation between and villus height and crypt depth (0.01). and were correlated with propionate, butyrate, and valerate concentrations (0.01). was correlated with sodium-glucose cotransporters 1 and cationic amino acid transporter 1 expression (0.05). and were positively correlated with serum levels of total cholesterol, tryglucerides, and high- and low-density lipoprotein cholesterol (0.01). , , , and were correlated with serum VB6 levels (0.01). , , and were correlated with the moisture content of cecal contents (0.05). The identification of the microbiota in correlation with nutrient metabolism will promote microbial nutrition through microbiota intervention or nutritional regulation. The poultry industry has become a global leader in livestock farming over the past few decades. Poultry production has a large consumer market as an integrated industry producing high-protein foods. Establishing the association between microbiota and nutrient metabolism processes provides fresh insights for precise nutrient regulation. This study aimed to describe the development of cecal microbiota in broiler chickens throughout the production cycle and to assess the correlation of nutrient metabolism phenotypes with temporal changes in the microbiota. The results suggested that changes in cecal microbes with age partly explain changes in gut nutrient metabolic processes, and numerous microbes were significantly associated with the processes. Therefore, this study attempts to further find efficient ways of improving poultry production. One is to promote nutrient metabolism by identifying potential candidates for probiotics, and another is to foster the dominant colonization of the microbiota by regulating nutrient metabolism.

摘要

鸡肠道微生物群在营养吸收和代谢中起着重要作用。清晰的微生物群演替图可以增强宿主的营养和疾病抵抗力。本研究使用 16S rRNA 基因测序研究了孵化后 3 至 42 天肉鸡盲肠微生物群的演替,并分析了其与肠道营养代谢的潜在关联。根据微生物群 α多样性或β多样性,不同时间点的微生物群结构差异显著。和分别在第 3 至 7 天和第 28 至 35 天促进演替。和在第 7 至 28 天和第 35 至 42 天维持肠道内稳态。、、和在第 3 至 7 天促进演替;在第 7 至 14 天改变微生物组成;在第 21 至 28 天调节微生物结构。第 14 至 21 天和第 28 至 35 天,微生物群结构相对稳定。Spearman 相关性分析表明,与绒毛高度和隐窝深度呈正相关(0.01)。和与丙酸盐、丁酸盐和戊酸盐浓度呈正相关(0.01)。与钠-葡萄糖协同转运蛋白 1 和阳离子氨基酸转运蛋白 1 的表达呈正相关(0.05)。和与血清总胆固醇、甘油三酯、高密度脂蛋白胆固醇和低密度脂蛋白胆固醇浓度呈正相关(0.01)。、、和与血清 VB6 水平呈正相关(0.01)。、和与盲肠内容物的水分含量呈正相关(0.05)。与营养代谢相关的微生物群的鉴定将通过微生物群干预或营养调节来促进微生物的营养。几十年来,家禽业已成为畜牧业的全球领导者。家禽生产作为生产高蛋白食品的综合性产业,拥有庞大的消费市场。确定微生物群与营养代谢过程之间的关联为精确的营养调节提供了新的视角。本研究旨在描述肉鸡盲肠微生物群在整个生产周期中的发育情况,并评估营养代谢表型与微生物群随时间变化的相关性。结果表明,随年龄变化的盲肠微生物部分解释了肠道营养代谢过程的变化,许多微生物与这些过程显著相关。因此,本研究试图进一步寻找提高家禽生产效率的有效方法。一种方法是通过确定潜在的益生菌候选物来促进营养代谢,另一种方法是通过调节营养代谢来促进微生物群的优势定植。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f0d6/10286727/717fae32d83a/msphere.00614-22-f005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f0d6/10286727/0f0d9566b0a9/msphere.00614-22-f001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f0d6/10286727/ccc3d43e6c7c/msphere.00614-22-f004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f0d6/10286727/717fae32d83a/msphere.00614-22-f005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f0d6/10286727/0f0d9566b0a9/msphere.00614-22-f001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f0d6/10286727/abe9314de3f0/msphere.00614-22-f002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f0d6/10286727/c246bf4ac27e/msphere.00614-22-f003.jpg
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