基于高通量测序技术测定普通棉耳狨猴粪便微生物多样性
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摘要
目的应用高通量测序技术分析普通棉耳狨猴粪便菌群的结构与组成,为进一步开发利用新型实验动物奠定基础。方法采集4只成年雄性普通棉耳狨猴粪便,用细菌16S rRNA通用引物扩增V3～V4区,采用Illumina MiSeq测序平台对普通棉耳狨猴粪便微生物进行研究。结果共测序获得315 511条有效序列与596个OTU。普通棉耳狨猴粪便中的细菌共鉴定出9个门、14个纲、26个目、50个科、82个属和64个种和226个OTU。其中,1)优势门是拟杆菌门(Bacteroidetes)和厚壁菌门(Firmicutes),平均含量分别为54. 52%和25. 39%2)丰度最高的纲为拟杆菌纲(Bacteroidia)和厌氧菌纲(Negativicutes),平均含量为54. 5%和17%。3)乳杆菌目(Lactobacillales)和拟杆菌目(Bacteroidales)的丰度最高,为50. 01%和20. 52%。4)普雷沃菌科(Prevotellaceae)和双歧杆菌科(Bifidobacteriaceae)所占丰度最高,平均含量分别为43. 14%和11. 33%。5)双歧杆菌属(Bifidobacterium)和拟杆菌属(Bacteroides)的丰度较高,平均含量分别为11. 33%11. 12%。6)有益菌群双歧杆菌属丰度较高,但在所检测样本中都含有。7)丰度最高的前10个种,归类为7个科、5个纲。这10个种占到33. 16%,其他53种总和仅占到0. 74%,其他未鉴定出菌种,且相对丰度还较高,需要进一步研究。8) PICRUSt功能预测分析:氨基酸转运等代谢功能和蛋白质翻译、折叠遗传信息处理功能丰度较高。结论应用高通量测序技术,较全面的检测了普通棉耳狨猴粪便菌群,普通棉耳狨猴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 intestinal flora in the common cotton-eared marmoset using the Illumina MiSeq sequencing platform. Methods Feces of the common cotton-eared marmoset were collected and investigated for microbial diversity using the Illumina MiSeq sequencing platform. Results In total,315511 sequences and 596 OTUs were obtained after sequencing. According to the Shannon-Wiener curve,the sequencing data were reliable for all bacteria in the samples. The bacteria in the common cotton-eared marmoset included 9 phyla,14 classes,26 orders,50 families,82 genera,and 64 species. Among them,Firmicutes and Bacteroidetes had the highest abundance( 54. 52% and 25. 39%,respectively). The dominant classes were Bacteroidia and Negativicutes at 54. 5% and17%,respectively. The abundance of Lactobacillales and Bacteroidales was higher at 50. 01% and 20. 52%,respectively.Dominant families were Prevotellaceae and Bifidobacteriaceae at 43. 14% and 11. 33% respectively. Lactobacillus and Streptococcus were dominant at 20. 03% and 19. 62%, respectively. The abundance of beneficial bacteria, such as Bifidobacterium,was high,which were found in samples. The top 10 species with the highest abundance were classified into seven families and five classes. These 10 species accounted for 33. 16%,and the other 53 species only accounted for0. 74%. Other species were not identified,and the abundance was relatively high,which require further study. PICRUSt functional prediction showed an abundance of functional genes such as those involved in amino acid transport and metabolism as well as genetic information processing. Conclusions The composition of fecal microbiota in common cottoneared marmoset has rich diversity. Many bacteria that are relatively abundant remain unidentified,and further study is warranted.
Objective To analyze the structure and composition of intestinal flora in the common cotton-eared marmoset using the Illumina MiSeq sequencing platform. Methods Feces of the common cotton-eared marmoset were collected and investigated for microbial diversity using the Illumina MiSeq sequencing platform. Results In total,315511 sequences and 596 OTUs were obtained after sequencing. According to the Shannon-Wiener curve,the sequencing data were reliable for all bacteria in the samples. The bacteria in the common cotton-eared marmoset included 9 phyla,14 classes,26 orders,50 families,82 genera,and 64 species. Among them,Firmicutes and Bacteroidetes had the highest abundance( 54. 52% and 25. 39%,respectively). The dominant classes were Bacteroidia and Negativicutes at 54. 5% and17%,respectively. The abundance of Lactobacillales and Bacteroidales was higher at 50. 01% and 20. 52%,respectively.Dominant families were Prevotellaceae and Bifidobacteriaceae at 43. 14% and 11. 33% respectively. Lactobacillus and Streptococcus were dominant at 20. 03% and 19. 62%, respectively. The abundance of beneficial bacteria, such as Bifidobacterium,was high,which were found in samples. The top 10 species with the highest abundance were classified into seven families and five classes. These 10 species accounted for 33. 16%,and the other 53 species only accounted for0. 74%. Other species were not identified,and the abundance was relatively high,which require further study. PICRUSt functional prediction showed an abundance of functional genes such as those involved in amino acid transport and metabolism as well as genetic information processing. Conclusions The composition of fecal microbiota in common cottoneared marmoset has rich diversity. Many bacteria that are relatively abundant remain unidentified,and further study is warranted.
引文
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[15] 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 Mi Seq illumina sequencing platform[J]. Appl Environ Microbiol,2013,79(17):5112-5120.
[16] 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.
[17]潘勇.肠道菌群与大肠癌发病风险的相关性研究[J].中国医学前沿杂志(电子版),2017,9(2):88-92.Pan Y. The study on the relationship between microbial community in intestine and colorectal cancer[J]. Chin J Front Med Sci(Elect Ver),2017,9(2):88-92.
[2] Zhang J,Chen SL,Li LB. Correlation between intestinal flora and serum inflammatory factors in patients with Crohn’s disease[J]. Eur Rev Med Pharmacol Sci,2017,21(21):4913-4917.
[3] Zhu H,Zeng D,Wang N,et al. Microbial community and diversity in the feces of Sichuan takin(Budorcas taxicolor tibetana)as revealed by Illumina Miseq sequencing and quantitative real-time PCR[J]. AMB Express, 2018, 8(1):68.
[4] Ramezani M,Hosseini SM,Fazeli SAS,et al. PCR-DGGE analysis of fungal community in manufacturing process of a traditional Iranian cheese[J]. Iran J Microbiol,2018,10(3):180-186.
[5] Bailey MT,Coe CL. Maternal separation disrupts the integrity of the intestinal microflora in infant rhesus monkeys[J]. Dev Psychobiol,2015,35(2):146-155.
[6] Jones CA, Duffy MK, Hoffman SA, et al. Vocalization development in common marmosets for neurodegenerative translational modeling[J]. Neurol Res,2018,40(4):303-311.
[7] Ash H,Smith TE,Knight S,et al. Measuring physiological stress in the common marmoset(Callithrix jacchus):Validation of a salivary cortisol collection and assay technique[J]. Physiol Behav,2018,185(3):14-22.
[8] Guo Z,Zhang J,Wang Z,et al. Intestinal microbiota distinguish gout patients from healthy humans[J]. Sci Rep, 2016,6:20602.
[9] Tang R,Wei Y,Li Y,et al. Gut microbial profile is altered in primary biliary cholangitis and partially restored after UDCA therapy[J]. Gut,2018,67(3):534-541.
[10] Hess M,Sczyrba A,Egan R,et al. Metagenomic discovery of biomass-degrading genes and genomes from cow rumen[J].Science,2011,331(6016):463-467.
[11] Perruzza L,Gargari G,Proietti M,et al. T Follicular helper cells promote a beneficial gut ecosystem for host metabolic homeostasis by sensing microbiota-derived extracellular ATP[J]. Cell Rep,2017,18(11):2566-2575.
[12]伊丽娜,刘学聪,蒋志刚.非人灵长类肠道菌群组成及影响因素[J].动物学杂志,2018(3). 53(3):479-494.Yi LN,Liu XC,Jiang ZG. Gut bacterial composition and its influencing factors of non-human primates[J]. Chin J Zool,2018(3). 53(3):479-494.
[13]朱乃军,项建梅,陈祖培,等.棉耳型狨猴肠道菌群的研究[J].中国比较医学杂志,1998(2):101-103.Zhu NJ,Xiang JM,Chen ZP,et al. Study on intestinal flora of Cotton-eared marmoset[J]. Chin J Comp Med,1998(2):101-103.
[14] RinttilT,Kassinen A,Malinen E,et al. Development of an extensive set of 16S r DNA-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.
[15] 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 Mi Seq illumina sequencing platform[J]. Appl Environ Microbiol,2013,79(17):5112-5120.
[16] 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.
[17]潘勇.肠道菌群与大肠癌发病风险的相关性研究[J].中国医学前沿杂志(电子版),2017,9(2):88-92.Pan Y. The study on the relationship between microbial community in intestine and colorectal cancer[J]. Chin J Front Med Sci(Elect Ver),2017,9(2):88-92.