利用Illumina MiSeq测序平台分析野生树鼩粪便微生物多样性
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摘要
目的应用高通量测序技术分析野生树鼩粪便菌群的结构与组成,为进一步开发利用这种新型实验动物奠定基础。方法在云南昆明野外捕捉3只野外成年雄性树鼩,采取粪便,用细菌16SrRNA通用引物扩增V3～V4区,采用Illumina MiSeq测序平台对树鼩粪便微生物进行研究。结果共测序获得181 657条有效序列与624个OTU,shannon稀释曲线证明此次测序量能够覆盖样本中的绝大部分物种。树鼩粪便中的细菌共鉴定出9个门、17个纲、31个目、56个科、124个属和172个种。其中,(1)优势门是厚壁菌门(Firmicutes)和拟杆菌门(Bacteroidetes),分别为68.38%和20.52%;(2)丰度最高的纲为为芽孢杆菌纲(Bacilli)54.81%和拟杆菌纲(Bacteroidia)20.52%;(3)乳杆菌目(Lactobacillales)和拟杆菌目(Bacteroidales)的丰度最高,为50.01%和20.52%;(4)优势菌科为链球菌科(Streptococcaceae)和普雷沃氏菌科(Prevotellaceae),为40.52%和12.13%;(5)乳杆菌属(Lactobacillus)和链球菌属(Streptococcus)的丰度最高,分别为20.03%和19.62%;(6)有益菌群如乳酸杆菌属、乳球菌属丰度相对较高,双歧杆菌属丰度较低,但在所检测样本中都含有;(7)16 s功能预测发现:氨基酸转运与代谢、碳水化合物转运与代谢等功能丰度较高。结论应用高通量测序技术,第一次较全面的检测了野生树鼩粪便菌群,野生树鼩粪便细菌组成具有丰富的多样性,其中还有许多未被分类鉴定且相对丰度较高的细菌,需要进一步研究。
Objective To analyze the structure and composition of the intestinal flora of the wild tree shrew using the Illumina MiSeq sequencing platform. Methods The feces of three wild tree shrews were collected and investigated for diversity using the Illumina MiSeq sequencing platform. Results In total, 181,657 sequences and 624 OTU were collected after sequencing. According to the Shannon-Wiener curve, the sequencing data were reliable for all bacteria of the samples. The bacteria in the tree shrew feces were from 9 phyla, 17 classes, 31 orders, 56 families, 124 genera, and 172 species. Among them, 1) Firmicutes and Bacteroidetes had the highest abundance, 68.38% and 20.52%, respectively. 2) The dominant classes were Bacilli and Bacteroidia, at 54.81% and 20.52%. 3) The abundance of Lactobacillales and Bacteroidales was higher, at 50.01% and 20.52%. 4) Dominant families were Streptococcaceae and Prevotellaceae, at 40.52% and 12.13%. 5) Lactobacillus and Streptococcus were dominant(20.03%, 19.62%). 6) Beneficial bacteria, such as Lactobacillus and Lactococcus, were relatively common, while Bifidobacterium was relatively rare. 7) 16 S functional prediction showed an abundance of functional genes, such as those involved in amino acid transport and metabolism, carbohydrate transport, and metabolism. Conclusions The composition of tree shrew fecal microbiota shows a rich diversity. Many bacteria that are relatively abundant remain unidentified, so further study is warranted.
Objective To analyze the structure and composition of the intestinal flora of the wild tree shrew using the Illumina MiSeq sequencing platform. Methods The feces of three wild tree shrews were collected and investigated for diversity using the Illumina MiSeq sequencing platform. Results In total, 181,657 sequences and 624 OTU were collected after sequencing. According to the Shannon-Wiener curve, the sequencing data were reliable for all bacteria of the samples. The bacteria in the tree shrew feces were from 9 phyla, 17 classes, 31 orders, 56 families, 124 genera, and 172 species. Among them, 1) Firmicutes and Bacteroidetes had the highest abundance, 68.38% and 20.52%, respectively. 2) The dominant classes were Bacilli and Bacteroidia, at 54.81% and 20.52%. 3) The abundance of Lactobacillales and Bacteroidales was higher, at 50.01% and 20.52%. 4) Dominant families were Streptococcaceae and Prevotellaceae, at 40.52% and 12.13%. 5) Lactobacillus and Streptococcus were dominant(20.03%, 19.62%). 6) Beneficial bacteria, such as Lactobacillus and Lactococcus, were relatively common, while Bifidobacterium was relatively rare. 7) 16 S functional prediction showed an abundance of functional genes, such as those involved in amino acid transport and metabolism, carbohydrate transport, and metabolism. Conclusions The composition of tree shrew fecal microbiota shows a rich diversity. Many bacteria that are relatively abundant remain unidentified, so further study is warranted.
引文
[1] 沈培清, 郑红, 刘汝文, 等. 中国树鼩实验动物化研究进展和展望[J]. 动物学研究, 2011, 32(1):109-114.Shen PQ, Zhen H, Liu RW, et al. Progress and prospect in research on laboratory tree shrew in China[J]. Zool Res, 2011, 32(1):109-114.
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[7] 王映纯, 金炜翔, 唐永明, 等. 健康树鼩肠道致病菌的调查[J]. 实验动物科学, 1988(2):43-49.Wang YC, Jin WX, Tang YM, et al. The survey of enteric pathogens in healthy tree shrew[J]. Lab Anim Sci,1988(2):43-49.
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[11] 赵晗旭. 不同野生动物肠道微生物多样性分析及功能初步研究[D]. 吉林农业大学, 2015.Zhao HX. Diversity and functional analysis of intestinal microflora in different wild animals[D]. Jilin Agricultural University, 2015.
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[13] Rinttil? T, Kassinen A, Malinen E, et al. Development of an extensive set of 16S rDNA-targeted primers for quantification of pathogenic and indigenous bacteria in faecal samples by real-time PCR[J]. J Appl Microbiol, 2010, 97(6):1166-1177.
[14] Kozich JJ, Westcott SL, Baxter NT, et al. Development of a dual-index sequencing strategy and curation pipeline for analyzing amplicon sequence data on the MiSeq Illumina sequencing platform. [J]. Appl Environ Microb, 2013, 79(17):5112-5120.
[15] Martin R, Nauta AJ, Ben AK, et al. Early life: gut microbiota and immune development in infancy[J]. Benef Microbes, 2010, 1(4):367-382.
[16] Torok VA, Allison GE, Percy NJ, et al. Influence of antimicrobial feed additives on broiler commensal posthatch gut microbiota development and performance. [J]. Appl Environ Microbiol, 2011, 77(10):3380-3390.
[17] Sergeant MJ, Constantinidou C, Cogan TA, et al. Extensive microbial and functional diversity within the chicken cecal microbiome[J]. PLoS One, 2014, 9(3):e91941.
[18] Sergeant MJ, Constantinidou C, Cogan T, et al. High-throughput sequencing of 16S rRNA gene amplicons: effects of extraction procedure, primer length and annealing temperature[J]. PLoS One, 2012, 7(5):e38094.
[19] Fu J, Liu H, Xing H, et al. Comparative analysis of glucuronidation of ethanol in tree shrews, rats and humans[J]. Xenobiotica, 2014, 44(12):1067-1073.
[20] Wang Z, Klipfell E, Bennett BJ, et al. Gut flora metabolism of phosphatidylcholine promotes cardiovascular disease[J]. Nature, 2011, 472(7341):57-63.
[2] 许凌, 范宇, 蒋学龙, 等. 树鼩进化分类地位的分子证据[J]. 动物学研究, 2013, 34(2):70-76.Xu L, Fan Y, Jiang XL, et al. Molecular evidence on the phylogenetic position of tree shrews[J]. Zool Res, 2013, 34(2):70-76.
[3] 沈培清, 刘美芳, 刘汝文, 等. 树鼩的应用和标准化产业化研究[J]. 实验动物科学, 2008, 25(1):49-52.Shen PQ, Liu MF, Liu RW, et al. Application and standardization industrialization of tree shrew[J]. Lab Anim Sci, 2008, 25(1):49-52.
[4] 高家红, 江勤芳, 罗志武, 等. 树鼩正常肠道细菌的培养分离鉴定及其药敏试验研究[J]. 中国比较医学杂志, 2009, 19(12):24-26.Gao JH, Jiang QF, Luo ZW, et al. Culture, isolation and identification of normal intestinal bacterial flora and their antibiotic susceptibility in tree shrew[J]. Chin J Comp Med,2009, 19(12):24-26.
[5] 刘丽君, 余柄廷, 胡凝珠, 等. 树鼩粪便细菌分离培养与鉴定[J]. 中国比较医学杂志, 2015(10):64-68.Liu LJ,Yu BT,Hu NZ, et al. Isolation, culture and identification of bacterial strains from tree shrews feces[J] Chin J Comp Med, 2015(10):64-68.
[6] 张才军, 施明, 陈芳,等. 中缅树鼠句常见病原菌的分离鉴定[J]. 中国病原生物学杂志, 2009(12):899-900.Zhang CJ, Shi M, Chen F, et al. Isolation and identification of common bacteria in tree shrews [J]. J Pathog Biol, 2009(12):899-900.
[7] 王映纯, 金炜翔, 唐永明, 等. 健康树鼩肠道致病菌的调查[J]. 实验动物科学, 1988(2):43-49.Wang YC, Jin WX, Tang YM, et al. The survey of enteric pathogens in healthy tree shrew[J]. Lab Anim Sci,1988(2):43-49.
[8] 邢进, 冯育芳, 付瑞, 等. 野生树鼩可培养细菌和真菌携带情况的调查[J]. 实验动物科学, 2012, 29(3):34-38.Xing J, Feng YF, Fu R, et al. The survey of culturable bacteria and fungi in wild tree shrews [J]. Lab Anim Sci, 2012, 29(3):34-38.
[9] Anders S, Pyl PT, Huber W. HTSeq-a Python framework to work with high-throughput sequencing data[J]. Bioinformatics, 2015, 31(2):166-169.
[10] Friedensohn S, Khan TA, Reddy ST. Advanced methodologies in high-throughput sequencing of immune repertoires [J]. Trends Biotechnol, 2017, 35(3):203-214.
[11] 赵晗旭. 不同野生动物肠道微生物多样性分析及功能初步研究[D]. 吉林农业大学, 2015.Zhao HX. Diversity and functional analysis of intestinal microflora in different wild animals[D]. Jilin Agricultural University, 2015.
[12] Ley RE, Lozupone CA, Hamady M, et al. Worlds within worlds: evolution of the vertebrate gut microbiota[J]. Nat Rev Microbiol, 2008, 6(10):776-788.
[13] Rinttil? T, Kassinen A, Malinen E, et al. Development of an extensive set of 16S rDNA-targeted primers for quantification of pathogenic and indigenous bacteria in faecal samples by real-time PCR[J]. J Appl Microbiol, 2010, 97(6):1166-1177.
[14] Kozich JJ, Westcott SL, Baxter NT, et al. Development of a dual-index sequencing strategy and curation pipeline for analyzing amplicon sequence data on the MiSeq Illumina sequencing platform. [J]. Appl Environ Microb, 2013, 79(17):5112-5120.
[15] Martin R, Nauta AJ, Ben AK, et al. Early life: gut microbiota and immune development in infancy[J]. Benef Microbes, 2010, 1(4):367-382.
[16] Torok VA, Allison GE, Percy NJ, et al. Influence of antimicrobial feed additives on broiler commensal posthatch gut microbiota development and performance. [J]. Appl Environ Microbiol, 2011, 77(10):3380-3390.
[17] Sergeant MJ, Constantinidou C, Cogan TA, et al. Extensive microbial and functional diversity within the chicken cecal microbiome[J]. PLoS One, 2014, 9(3):e91941.
[18] Sergeant MJ, Constantinidou C, Cogan T, et al. High-throughput sequencing of 16S rRNA gene amplicons: effects of extraction procedure, primer length and annealing temperature[J]. PLoS One, 2012, 7(5):e38094.
[19] Fu J, Liu H, Xing H, et al. Comparative analysis of glucuronidation of ethanol in tree shrews, rats and humans[J]. Xenobiotica, 2014, 44(12):1067-1073.
[20] Wang Z, Klipfell E, Bennett BJ, et al. Gut flora metabolism of phosphatidylcholine promotes cardiovascular disease[J]. Nature, 2011, 472(7341):57-63.