Department of Molecular Biomedical Sciences, North Carolina State University, 1060 William Moore Dr., Raleigh, NC, 27607, USA.
Department of Ecology and Evolutionary Biology, University of Colorado, 216 UCB, Boulder, CO, 80309-0216, USA; Cooperative Institute for Research in Environmental Sciences, University of Colorado, 216 UCB, Boulder, CO, 80309-0216, USA.
Forensic Sci Int. 2020 May;310:110250. doi: 10.1016/j.forsciint.2020.110250. Epub 2020 Mar 12.
The use of environmental trace material to aid criminal investigations is an ongoing field of research within forensic science. The application of environmental material thus far has focused upon a variety of different objectives relevant to forensic biology, including sample provenance (also referred to as sample attribution). The capability to predict the provenance or origin of an environmental DNA sample would be an advantageous addition to the suite of investigative tools currently available. A metabarcoding approach is often used to predict sample provenance, through the extraction and comparison of the DNA signatures found within different environmental materials, such as the bacteria within soil or fungi within dust. Such approaches are combined with bioinformatics workflows and statistical modelling, often as part of large-scale study, with less emphasis on the investigation of the adaptation of these methods to a smaller scale method for forensic use. The present work was investigating a small-scale approach as an adaptation of a larger metabarcoding study to develop a model for global sample provenance using fungal DNA signatures collected from dust swabs. This adaptation was to facilitate a standardized method for consistent, reproducible sample treatment, including bioinformatics processing and final application of resulting data to the available prediction model. To investigate this small-scale method, 76 DNA samples were treated as anonymous test samples and analyzed using the standardized process to demonstrate and evaluate processing and customized sequence data analysis. This testing included samples originating from countries previously used to train the model, samples artificially mixed to represent multiple or mixed countries, as well as outgroup samples. Positive controls were also developed to monitor laboratory processing and bioinformatics analysis. Through this evaluation we were able to demonstrate that the samples could be processed and analyzed in a consistent manner, facilitated by a relatively user-friendly bioinformatic pipeline for sequence data analysis. Such investigation into standardized analyses and application of metabarcoding data is of key importance for the future use of applied microbiology in forensic science.
利用环境痕量物质辅助刑事调查是法医学中一个不断发展的研究领域。迄今为止，环境物质的应用主要集中在与法医生物学相关的各种不同目标上，包括样本来源（也称为样本归因）。能够预测环境 DNA 样本的来源或起源将是对当前可用的一套调查工具的有利补充。通常使用宏条形码方法通过提取和比较不同环境物质（如土壤中的细菌或灰尘中的真菌）中的 DNA 特征来预测样本来源。这些方法与生物信息学工作流程和统计建模相结合，通常作为大规模研究的一部分，而较少关注这些方法对法医小范围应用的适应性的研究。本工作正在研究一种小规模方法，即将更大规模的宏条形码研究进行改编，以使用从灰尘拭子中收集的真菌 DNA 特征来开发全球样本来源模型。这种改编是为了方便一种标准化方法，以实现一致、可重复的样本处理，包括生物信息学处理和最终将结果数据应用于可用预测模型。为了研究这种小规模方法，76 个 DNA 样本被视为匿名测试样本，并使用标准化流程进行分析，以展示和评估处理和定制序列数据分析。该测试包括来自先前用于训练模型的国家的样本、代表多个或混合国家的人工混合样本以及外群样本。还开发了阳性对照来监测实验室处理和生物信息学分析。通过这种评估，我们能够证明可以以一致的方式处理和分析样本，这得益于相对用户友好的序列数据分析生物信息学管道。这种对标准化分析和宏条形码数据应用的研究对于未来在法医学中应用应用微生物学至关重要。
