基于ITS2测序的中国四个城市灰尘样本地域推断研究  

Geographical Inference Study of Dust Samples From Four Cities in China Based on ITS2 Sequencing

作　　者：张文君 冯耀森 彭加金 冯凯[4] 邓晔[4] 康克莱 王乐 ZHANG Wen-Jun;FENG Yao-Sen;PENG Jia-Jin;FENG Kai;Deng Ye;KANG Ke-Lai;WANG Le(School of Forensic Medicine,Shanxi Medical University,Jinzhong 030600,China;Key Laboratory of Forensic Genetics of Ministry of Public Security,Institute of Forensic Science,Ministry of Public Security,Beijing 100038,China;School of Forensic Medicine,Kunming Medical University,Kunming 650500,China;CAS Key Laboratory of Environmental Biotechnology,Research Center for Eco-Environmental Sciences,Chinese Academy of Sciences,Beijing 100085,China)

机构地区：[1]山西医科大学法医学院,晋中030600 [2]公安部鉴定中心,法医遗传学公安部重点实验室,北京100038 [3]昆明医科大学法医学院,昆明650500 [4]中国科学院生态环境研究中心,中国科学院环境生物技术重点实验室,北京100085

出　　处：《生物化学与生物物理进展》2025年第4期970-981,共12页Progress In Biochemistry and Biophysics

基　　金：公安部鉴定中心基本科研业务费(2022JB022);公安部科技强警基础工作专项(2023JC14)资助。

摘　　要：目的 灰尘作为重要的微量物证检材,在法庭科学领域有极大的应用潜力,随着DNA测序技术的发展,越来越多的研究者开始关注灰尘中的微生物群落分布。不同地区灰尘中的微生物群落分布存在差异,利用灰尘中的微生物群落信息进行生物地理位置推断在法庭科学领域有重要意义。通过分析不同地区灰尘样本的微生物DNA,可以揭示该地区的微生物组成,从而推断该地区的生物地理位置。本研究旨在探索中国4个城市的真菌群落组成结构差异,评估基于真菌的内转录间隔区(internal transcribed spacer,ITS) 2区测序对灰尘样本进行生物地理位置推断的准确率,为公安实战基于环境DNA进行地域推断奠定基础。方法 使用通用引物5.8S-Fun/ITS4-Fun扩增真菌基因组的ITS2区,在Illumina MiSeq FGx平台进行测序。采用非度量多维标度分析(non-metric multidimensional scaling,NMDS)可视化样本之间的差异。使用相似性分析(analysis of similarities,ANOSIM)和多元方差分析(permutational multivariate analysis of variance,PERMANOVA)两种不同的非参数分析方法衡量样本间的群落差异程度。使用LDA Effect Size (LEfSe)分析筛选出不同城市间有显著差异的物种。使用微生物来源分析软件SourceTracker对灰尘样本进行生物地理位置来源推断。结果 北京、福州、昆明、乌鲁木齐4个城市的灰尘样本中,北京的物种丰富度最高,物种注释结果显示,4个城市的真菌群落物种组成结构和相对丰度有明显差异。NMDS结果显示,灰尘样本在多维空间中基于生物地理来源进行分组,同一城市的灰尘样本有明显的聚类现象,不同城市的灰尘样本在第一轴明显分开。ANOSIM和PERMANOVA结果也表明,4个城市间的真菌群落组成均具有显著差异,其中以福州和乌鲁木齐两个城市之间的差异最为明显。所有已知来源的灰尘样本的生物地理位置均被成功预测。结论 北京、福�Objective In the realm of forensic science,dust is a valuable type of trace evidence with immense potential for intricate investigations.With the development of DNA sequencing technologies,there is a heightened interest among researchers in unraveling the complex tapestry of microbial communities found within dust samples.Furthermore,striking disparities in the microbial community composition have been noted among dust samples from diverse geographical regions,heralding new possibilities for geographical inference based on microbial DNA analysis.The pivotal role of microbial community data from dust in geographical inference is significant,underscoring its critical importance within the field of forensic science.This study aims to delve deeply into the nuances of fungal community composition across the urban landscapes of Beijing,Fuzhou,Kunming,and Urumqi in China.It evaluates the accuracy of biogeographic inference facilitated by the internal transcribed spacer 2(ITS2)fungal sequencing while concurrently laying a robust foundation for the operational integration of environmental DNA into geographical inference mechanisms.Methods ITS2 region of the fungal genomes was amplified using universal primers known as 5.8S-Fun/ITS4-Fun,and the resulting DNA fragments were sequenced on the Illumina MiSeq FGx platform.Non-metric multidimensional scaling analysis(NMDS)was employed to visually represent the differences between samples,while analysis of similarities(ANOSIM)and permutational multivariate analysis of variance(PERMANOVA)were utilized to statistically evaluate the dissimilarities in community composition across samples.Furthermore,using Linear Discriminant Analysis Effect Size(LEfSe)analysis to identify and filter out species that exhibit significant differences between various cities.In addition,we leveraged SourceTracker to predict the geographic origins of the dust samples.Results Among the four cities of Beijing,Fuzhou,Kunming and Urumqi,Beijing has the highest species richness.The results of species annotatio

关 键 词：法庭科学 真菌 灰尘DNA 地域推断 高通量测序 

分 类 号：R89[医药卫生—法医学] Q938[医药卫生—临床医学] DF795.2[生物学—微生物学]