基于16S rRNA基因序列对不同土壤细菌群落的差异性分析
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摘要
目的研究不同土壤细菌群落的结构和差异,探索16S rRNA基因测序技术在不同土壤鉴定中的有效性。方法采集上海市7个地区的土壤样本,提取土壤细菌基因组DNA,采用高通量测序技术对16S rRNA基因序列高变区片段进行测序,测序结果通过生物信息学软件量化或可视化后,比较分析草地、树林和沙滩3类土壤样本间细菌群落多样性和丰度的差异。结果草地、树林和沙滩土壤样本细菌群落的alpha多样性指数差异具有统计学意义,三类土壤细菌群落的物种相对丰度和多样性差异明显,草地土壤中酸杆菌门相对丰度较高,树林土壤中变形菌门相对丰度较高,沙滩土壤中放线菌门相对丰度较高。但人工草地、天然草地和工业区草地土壤细菌群落差异无统计学意义。结论基于16S rRNA基因序列测序可以有效区分不同类别土壤,该方法有望为刑事案件第一犯罪现场判读提供线索。
Objective To study the structure and differences of bacterial communities in different soils,and to explore the effectiveness of 16 S rRNA sequencing in identification of different soil. Methods Soil samples from 7 places in Shanghai were collected, then bacterial genomic DNA were extracted from them. The fragments of hypervariable region from 16 S rRNA sequences were sequenced with high-throughput sequencing techniques. The results were quantified or visualized with bioinformatics software. The differences in diversity and abundance among the three kinds of bacterial communities in soil samples from grassland, forests and beaches were compared and analyzed. Results The statistical differences that existed among the alpha diversity indexes of bacterial communities in soil samples of grassland, forests and beaches had statistical significance. The relative abundance and diversity of bacterial communities in these three kinds of soil were significantly different. Grassland soil had higher Acidobacteria abundance, forest soil had higher Proteobacteria abundance, beach soil had higher Actinobacteria abundance. However, the differences in soil bacterial communities in artificial grasslands, natural grasslands and industrial district grasslands did not have statistical significance. Conclusion 16 S rRNA sequencing can effectively distinguish different soils. This method may be able to provide clues for first crime scene inference in criminal cases.
Objective To study the structure and differences of bacterial communities in different soils,and to explore the effectiveness of 16 S rRNA sequencing in identification of different soil. Methods Soil samples from 7 places in Shanghai were collected, then bacterial genomic DNA were extracted from them. The fragments of hypervariable region from 16 S rRNA sequences were sequenced with high-throughput sequencing techniques. The results were quantified or visualized with bioinformatics software. The differences in diversity and abundance among the three kinds of bacterial communities in soil samples from grassland, forests and beaches were compared and analyzed. Results The statistical differences that existed among the alpha diversity indexes of bacterial communities in soil samples of grassland, forests and beaches had statistical significance. The relative abundance and diversity of bacterial communities in these three kinds of soil were significantly different. Grassland soil had higher Acidobacteria abundance, forest soil had higher Proteobacteria abundance, beach soil had higher Actinobacteria abundance. However, the differences in soil bacterial communities in artificial grasslands, natural grasslands and industrial district grasslands did not have statistical significance. Conclusion 16 S rRNA sequencing can effectively distinguish different soils. This method may be able to provide clues for first crime scene inference in criminal cases.
引文
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[23]王蕊,朱珂,李刚,等.东北丘陵区林地、耕地和草地土壤真菌群落代谢特征[J].农业环境科学学报,2018,37(9):1925-1932.
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[25]SENSABAUGH G F.Microbial community profiling for the characterisation of soil evidence:Forensic considerations[M]//RITZ K,DAWSON L,MILLER D.Criminal and environmental soil forensics.Dordrecht:Springer,2009:49-60.
[2]马海霞,张丽丽,孙晓萌,等.基于宏组学方法认识微生物群落及其功能[J].微生物学通报,2015,42(5):902-912.
[3]RUFFELL A.Forensic pedology,forensic geology,forensic geoscience,geoforensics and soil forensics[J].Forensic Sci Int,2010,202(1/2/3):9-12.
[4]SUENAGA H.Targeted metagenomics:a high-resolution metagenomics approach for specific gene clusters in complex microbial communities[J].Environ Microbiol,2012,14(1):13-22.
[5]CHAKRAVORTY S,HELB D,BURDAY M,et al.A detailed analysis of 16S ribosomal RNA gene segments for the diagnosis of pathogenic bacteria[J].J Microbiol Methods,2007,69(2):330-339.
[6]YANG B,WANG Y,QIAN P Y.Sensitivity and correlation of hypervariable regions in 16S rRNAgenes in phylogenetic analysis[J].BMC Bioinformatics,2016,17:135.
[7]国家环境保护总局.土壤环境监测技术规范:HJ/T166-2004[S].北京:中国标准出版社,2004.
[8]KHODAKOVA A S,SMITH R J,BURGOYNE L,et al.Random whole metagenomic sequencing for forensic discrimination of soils[J].PLoS One,2014,9(8):e104996.
[9]YOUNG J M,WEYRICH L S,BREEN J,et al.Predicting the origin of soil evidence:High throughput eukaryote sequencing and MIR spectroscopy applied to a crime scene scenario[J].Forensic Sci Int,2015,251:22-31.
[10]METCALF J L,XU Z Z,WEISS S,et al.Microbial community assembly and metabolic function during mammalian corpse decomposition[J].Science,2016,351(6269):158-162.
[11]JANSSEN P H.Identifying the dominant soil bacterial taxa in libraries of 16S rRNA and 16S rRNAgenes[J].Appl Environ Microbiol,2006,72(3):1719-1728.
[12]COURADEAU E,KARAOZ U,LIM H C,et al.Bacteria increase arid-land soil surface temperature through the production of sunscreens[J].Nat Commun,2016,7:10373.
[13]YANG B,WANG Y,QIAN P Y.Sensitivity and correlation of hypervariable regions in 16S rRNAgenes in phylogenetic analysis[J].BMC Bioinformatics,2016,17:135.
[14]JESMOK E M,HOPKINS J M,FORAN D R.Next-generation sequencing of the bacterial 16SrRNA gene for forensic soil comparison:A feasibility study[J].J Forensic Sci,2016,61(3):607-617.
[15]XU Z,HANSEN M A,HANSEN L H,et al.Bioinformatic approaches reveal metagenomic characterization of soil microbial community[J].PLoS One,2014,9(4):e93445.
[16]GARBEVA P,van VEEN J A,van ELSAS J D.Microbial diversity in soil:selection microbial populations by plant and soil type and implications for disease suppressiveness[J].Annu Rev Phytopathol,2004,42:243-270.
[17]PENG M,ZI X,WANG Q.Bacterial Community diversity of oil-contaminated soils assessed by high throughput sequencing of 16S rRNA genes[J].Int J Environ Res Public Health,2015,12(10):12002-12015.
[18]WILLIS K J,WHITTAKER R J.Ecology.Species diversity--scale matters[J].Science,2002,295(5558):1245-1248.
[19]周玉杰,李建华,张广宇,等.基于高通量测序的橡胶林土壤真菌多样性及群落组成分析[J].南方农业学报,2018,49(9):1729-1735.
[20]OLIVAS E S,GUERRERO J D M,SOBER M M,et al.Handbook of research on machine learning applications and trends:Algorithms,methods and techniques(VolumeⅡ)[M].Hershey:Information Science Reference(IGI Global),2009.
[21]LOZUPONE C A,HAMADY M,KELLEY S T,et al.Quantitative and qualitative beta diversity measures lead to different insights into factors that structure microbial communities[J].Appl Environ Microbiol,2007,73(5):1576-1585.
[22]MCHUGH T A,COMPSON Z,van GESTEL N,et al.Climate controls prokaryotic community composition in desert soils of the southwestern United States[J].FEMS Microbiol Ecol,2017,93(10).doi:10.1093/femsec/fix116.
[23]王蕊,朱珂,李刚,等.东北丘陵区林地、耕地和草地土壤真菌群落代谢特征[J].农业环境科学学报,2018,37(9):1925-1932.
[24]RAIESI F,ASADI E.Soil microbial activity and litter turnover in native grazed and ungrazed rangelands in a semiarid ecosystem[J].Biol Fert Soils,2006,43(1):76-82.
[25]SENSABAUGH G F.Microbial community profiling for the characterisation of soil evidence:Forensic considerations[M]//RITZ K,DAWSON L,MILLER D.Criminal and environmental soil forensics.Dordrecht:Springer,2009:49-60.