Zhiyong Liu (刘志勇) , Jiajun Liu (刘佳俊) , Jiaojiao Geng , Enlin Wu , Jianzhang Zhu , Bin Cong , Riga Wu , Hongyu Sun
{"title":"六种法医样本的超转录组学特征及其在体液/组织鉴定中的潜在应用:一项试点研究。","authors":"Zhiyong Liu (刘志勇) , Jiajun Liu (刘佳俊) , Jiaojiao Geng , Enlin Wu , Jianzhang Zhu , Bin Cong , Riga Wu , Hongyu Sun","doi":"10.1016/j.fsigen.2023.102978","DOIUrl":null,"url":null,"abstract":"<div><p><span><span>Microorganisms are potential markers for identifying body fluids (venous and menstrual blood, semen, saliva, and vaginal secretion) and skin tissue in forensic genetics<span><span>. Existing published studies have mainly focused on investigating microbial DNA by 16 S </span>rRNA<span> gene sequencing or metagenome<span><span> shotgun sequencing. We rarely find microbial </span>RNA<span> level investigations on common forensic body fluid/tissue. Therefore, the use of metatranscriptomics to characterize common forensic body fluids/tissue has not been explored in detail, and the potential application of metatranscriptomics in forensic science remains unknown. Here, we performed 30 </span></span></span></span></span>metatranscriptome<span> analyses on six types of common forensic sample from healthy volunteers by massively parallel sequencing. After quality control and host RNA filtering, a total of 345,300 unigenes were assembled from clean reads. Four kingdoms, 137 phyla, 267 classes, 488 orders, 985 families, 2052 genera, and 4690 species were annotated across all samples. Alpha- and beta-diversity and differential analysis were also performed. As a result, the saliva and skin groups demonstrated high alpha diversity (Simpson index), while the venous blood group exhibited the lowest diversity despite a high Chao1 index. Specifically, we discussed potential microorganism contamination and the “core </span></span>microbiome<span><span>,” which may be of special interest to forensic researchers. In addition, we implemented and evaluated artificial neural network (ANN), random forest (RF), and </span>support vector machine<span> (SVM) models for forensic body fluid/tissue identification (BFID) using genus- and species-level metatranscriptome profiles. The ANN and RF prediction models discriminated six forensic body fluids/tissue, demonstrating that the microbial RNA-based method could be applied to BFID. Unlike metagenomic research, metatranscriptomic analysis can provide information about active microbial communities; thus, it may have greater potential to become a powerful tool in forensic science for microbial-based individual identification. This study represents the first attempt to explore the application potential of metatranscriptome profiles in forensic science. Our findings help deepen our understanding of the microorganism community structure at the RNA level and are beneficial for other forensic applications of metatranscriptomics.</span></span></p></div>","PeriodicalId":50435,"journal":{"name":"Forensic Science International-Genetics","volume":null,"pages":null},"PeriodicalIF":3.2000,"publicationDate":"2023-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Metatranscriptomic characterization of six types of forensic samples and its potential application to body fluid/tissue identification: A pilot study\",\"authors\":\"Zhiyong Liu (刘志勇) , Jiajun Liu (刘佳俊) , Jiaojiao Geng , Enlin Wu , Jianzhang Zhu , Bin Cong , Riga Wu , Hongyu Sun\",\"doi\":\"10.1016/j.fsigen.2023.102978\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p><span><span>Microorganisms are potential markers for identifying body fluids (venous and menstrual blood, semen, saliva, and vaginal secretion) and skin tissue in forensic genetics<span><span>. Existing published studies have mainly focused on investigating microbial DNA by 16 S </span>rRNA<span> gene sequencing or metagenome<span><span> shotgun sequencing. We rarely find microbial </span>RNA<span> level investigations on common forensic body fluid/tissue. Therefore, the use of metatranscriptomics to characterize common forensic body fluids/tissue has not been explored in detail, and the potential application of metatranscriptomics in forensic science remains unknown. Here, we performed 30 </span></span></span></span></span>metatranscriptome<span> analyses on six types of common forensic sample from healthy volunteers by massively parallel sequencing. After quality control and host RNA filtering, a total of 345,300 unigenes were assembled from clean reads. Four kingdoms, 137 phyla, 267 classes, 488 orders, 985 families, 2052 genera, and 4690 species were annotated across all samples. Alpha- and beta-diversity and differential analysis were also performed. As a result, the saliva and skin groups demonstrated high alpha diversity (Simpson index), while the venous blood group exhibited the lowest diversity despite a high Chao1 index. Specifically, we discussed potential microorganism contamination and the “core </span></span>microbiome<span><span>,” which may be of special interest to forensic researchers. In addition, we implemented and evaluated artificial neural network (ANN), random forest (RF), and </span>support vector machine<span> (SVM) models for forensic body fluid/tissue identification (BFID) using genus- and species-level metatranscriptome profiles. The ANN and RF prediction models discriminated six forensic body fluids/tissue, demonstrating that the microbial RNA-based method could be applied to BFID. Unlike metagenomic research, metatranscriptomic analysis can provide information about active microbial communities; thus, it may have greater potential to become a powerful tool in forensic science for microbial-based individual identification. This study represents the first attempt to explore the application potential of metatranscriptome profiles in forensic science. 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Metatranscriptomic characterization of six types of forensic samples and its potential application to body fluid/tissue identification: A pilot study
Microorganisms are potential markers for identifying body fluids (venous and menstrual blood, semen, saliva, and vaginal secretion) and skin tissue in forensic genetics. Existing published studies have mainly focused on investigating microbial DNA by 16 S rRNA gene sequencing or metagenome shotgun sequencing. We rarely find microbial RNA level investigations on common forensic body fluid/tissue. Therefore, the use of metatranscriptomics to characterize common forensic body fluids/tissue has not been explored in detail, and the potential application of metatranscriptomics in forensic science remains unknown. Here, we performed 30 metatranscriptome analyses on six types of common forensic sample from healthy volunteers by massively parallel sequencing. After quality control and host RNA filtering, a total of 345,300 unigenes were assembled from clean reads. Four kingdoms, 137 phyla, 267 classes, 488 orders, 985 families, 2052 genera, and 4690 species were annotated across all samples. Alpha- and beta-diversity and differential analysis were also performed. As a result, the saliva and skin groups demonstrated high alpha diversity (Simpson index), while the venous blood group exhibited the lowest diversity despite a high Chao1 index. Specifically, we discussed potential microorganism contamination and the “core microbiome,” which may be of special interest to forensic researchers. In addition, we implemented and evaluated artificial neural network (ANN), random forest (RF), and support vector machine (SVM) models for forensic body fluid/tissue identification (BFID) using genus- and species-level metatranscriptome profiles. The ANN and RF prediction models discriminated six forensic body fluids/tissue, demonstrating that the microbial RNA-based method could be applied to BFID. Unlike metagenomic research, metatranscriptomic analysis can provide information about active microbial communities; thus, it may have greater potential to become a powerful tool in forensic science for microbial-based individual identification. This study represents the first attempt to explore the application potential of metatranscriptome profiles in forensic science. Our findings help deepen our understanding of the microorganism community structure at the RNA level and are beneficial for other forensic applications of metatranscriptomics.
期刊介绍:
Forensic Science International: Genetics is the premier journal in the field of Forensic Genetics. This branch of Forensic Science can be defined as the application of genetics to human and non-human material (in the sense of a science with the purpose of studying inherited characteristics for the analysis of inter- and intra-specific variations in populations) for the resolution of legal conflicts.
The scope of the journal includes:
Forensic applications of human polymorphism.
Testing of paternity and other family relationships, immigration cases, typing of biological stains and tissues from criminal casework, identification of human remains by DNA testing methodologies.
Description of human polymorphisms of forensic interest, with special interest in DNA polymorphisms.
Autosomal DNA polymorphisms, mini- and microsatellites (or short tandem repeats, STRs), single nucleotide polymorphisms (SNPs), X and Y chromosome polymorphisms, mtDNA polymorphisms, and any other type of DNA variation with potential forensic applications.
Non-human DNA polymorphisms for crime scene investigation.
Population genetics of human polymorphisms of forensic interest.
Population data, especially from DNA polymorphisms of interest for the solution of forensic problems.
DNA typing methodologies and strategies.
Biostatistical methods in forensic genetics.
Evaluation of DNA evidence in forensic problems (such as paternity or immigration cases, criminal casework, identification), classical and new statistical approaches.
Standards in forensic genetics.
Recommendations of regulatory bodies concerning methods, markers, interpretation or strategies or proposals for procedural or technical standards.
Quality control.
Quality control and quality assurance strategies, proficiency testing for DNA typing methodologies.
Criminal DNA databases.
Technical, legal and statistical issues.
General ethical and legal issues related to forensic genetics.