| 摘要: |
| 为探讨不同代次雄性ICR小鼠生长发育与其肠道微生物的关系，本研究通过对16SrRNA基因V3~V4区测序，分析F0到F3代雄性ICR小鼠肠道菌群多样性和菌种组成。结果显示:1)从F0到F3代，组间微生物的Alpha多样性中的Chao1指数，Observed-species指数和香侬指数(Shannon)指数随代次积累显著降低(P<0.05)，Simpson指数无显著差异(P>0.05)。2)从F0到F3代的优势菌门均为厚壁菌门(Firmicutes)(F0、F1、F2和F3丰度分别为83.3%、79.0%、81.8%和90.3%)和拟杆菌门(Bacteroides)(F0、F1、F2和F3丰度分别为6.0%、5.1%、4.0%和3.2%)。3)F0，F1和F2代三组的优势菌属均为乳酸菌属(Lactobacillus)(F0、F1和F2丰度分别为83.1%、62.8%和38.2%)，但F3代的一些未确认分类的菌属占比较高，丰度约为45.3%；从F0到F3代在属水平上微生物组成上存在显著差异(P<0.05)，各组的乳酸菌属丰度随代次的积累显著降低(P<0.05)。4)对差异菌属进行了KEGG差异代谢通路预测，发现乙醛酸盐代谢、胰岛素信号通路、苯丙氨酸，色氨酸和酪氨酸生物合成途径，萜类化合物生物合成途径，肽聚糖生物合成和糖酵解糖异生作用在F3代中显著降低，表明F3代氨基酸合成、糖类代谢等多条基础代谢通路受损。综上，本研究基于微生物16SrRNA测序技术对ICR小鼠传代后肠道菌群变化进行了一系列分析和功能预测，发现微生物多样性发生改变，F0至F2代优势菌门未发生明显变化，但在F3代出现了较多的为确认分类菌属，并且在属水平上各组的乳酸菌属丰度随代次的积累显著降低，F3代氨基酸合成、糖类代谢等多条基础代谢通路受到影响。本研究有助于从肠道微生物与宿主间的相互作用角度解释ICR雄性小鼠传代后出现的体重偏低等现象产生的原因。 |
| 关键词: 肠道微生物 ICR雄性小鼠 16SrRNA测序 KEGG代谢通路预测 |
| DOI：10.11841/j.issn.1007-4333.2022.07.12 |
| 分类号: |
| 基金项目:国家自然科学基金项目(32072736) |
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| Analysis on the changes of intestinal microbiota in ICR mice after passage based on microbial 16SrRNA sequencing technology |
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ZHANG Luyao1,MENG Lin1,ZHUAN Qingrui2,FU Xiangwei2,3,HOU Yunpeng1*
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1.College of Biological Sciences/State Key Laboratories for Agrobiotechnology, China Agricultural University, Beijing 100193, China;2.College of Animal Science and Technology/Key Laboratory of Animal Genetics, Breeding and Reproduction, China Agricultural University, Beijing 100193, China;3.State Key Laboratory of Sheep Genetic Improvement and Healthy Breeding, Xinjiang Academy ofAgricultural and Reclamation Sciences, Shihezi 832000, China
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| Abstract: |
| To explore the relationship between the growth and development of male ICR mice of different generations and their intestinal microorganisms, the composition of microbial diversity in male ICR mice of F0 to F3 generations by sequencing the V3-V4 region of 16SrRNA gene was analyzed. The results showed that: 1)From F0 to F3 generations, the observed species index, Chao1 index and Shannon index significantly decreased with generation accumulation, but there was no significant difference in Simpson index(P>0. 05). 2)The two dominant bacteria phyla detected in all groups were Firmicutes(83. 3%, 79. 0%, 81. 8% and 90. 3% in F0, F1, F2 and F3 group)and Bacteroidetes(6. 0%, 5. 1%, 4. 0% and 3. 2% in F0, F1, F2 and F3 groups, respectively). 3)The dominant genera of Lactobacillus in F0, F1 and F2 groups were all Lactobacillus (83. 1%, 62. 8% and 38. 2% in F0, F1 and F2 groups, respectively). However, some unidentified genera of mice in F3 generation accounted for a relatively high proportion, accounting for 45. 3%. 4)At the genus level, the abundance of lactic acid bacteria in each group decreased significantly with the accumulation of generations(P<0. 05). In addition, this study predicted the KEGG differential metabolic pathway of different bacteria, glyoxalase metabolic insulin signaling pathway, the phenylalanine, tryptophan and tyrosine biosynthesis pathways, terpenoid biosynthesis pathways, peptidoglycan biosynthesis and glycolysis gluconeogenesis were significantly decreased in the F3 generation, indicating that several basic metabolic pathways such as amino acid synthesis and carbohydrate metabolism were impaired in the F3 generation. In summary, the changes of intestinal microbiota in ICR mice after passage were discovered based on microbial 16SrRNA sequencing technology. It was found that the microbial diversity decreased, with no significant changes in the dominant bacteria from F0 to F2 generations, but there were more confirmed classification bacteria in F3 generations, and the abundance of lactic acid bacteria in each group at the genus level decreased significantly with the accumulation of generations, and several basic metabolic pathways such as amino acid synthesis and sugar metabolism were affected in F3 generations. This study provided insights into explain the causes of low body weight in ICR mice generation accumulation from the perspective of host-microbe interactions. |
| Key words: gut microbes ICR male mice 16S rRNA sequencing prediction of KEGG metabolic pathway |
