Kim Sungmin, Lee Han Chul, Sim Jeong Eun, Park Su Jeong, Oh Hye Hyun
Forensic Genetics and Chemistry Division, Supreme Prosecutors' Office, 157 Banpo daero, Seocho gu, Seoul, 06590, Republic of Korea.
Genes Genomics. 2025 Jan;47(1):87-98. doi: 10.1007/s13258-024-01594-8. Epub 2024 Nov 6.
Identifying the origins of biological traces is critical for the reconstruction of crime scenes in forensic investigations. Traditional methods for body fluid identification rely on chemical, enzymatic, immunological, and spectroscopic techniques, which can be sample-consuming and depend on simple color-change reactions. However, these methods have limitations when residual samples are insufficient after DNA extraction.
This study aimed to develop a method for body fluid identification by leveraging bacterial DNA profiling to overcome the limitations of the conventional approaches.
Bacterial profiles were determined by sequencing the hypervariable region of the 16 S rRNA gene, using DNA metabarcoding of evidence collected from criminal cases. Amplicon sequence variants (ASVs) were analyzed to identify significant microbial patterns in different body fluid samples.
The bacterial profile-based method demonstrated high discriminatory power with a machine learning model trained using the naïve Bayes algorithm, achieving an accuracy of over 98% in classifying samples into one of four body fluid types: blood, saliva, vaginal secretion, and mixture traces of vaginal secretions and semen.
Bacterial profiling enhances the accuracy and robustness of body fluid identification in forensic analysis, providing a valuable alternative to traditional methods by utilizing DNA and microbial community data despite the uncontrollable conditions. This approach offers significant improvements in the classification accuracy and practical applicability in forensic investigations.
在法医调查中，确定生物痕迹的来源对于犯罪现场重建至关重要。传统的体液鉴定方法依赖于化学、酶学、免疫学和光谱技术，这些方法可能会消耗样本，并且依赖于简单的颜色变化反应。然而，当DNA提取后残留样本不足时，这些方法存在局限性。
本研究旨在开发一种利用细菌DNA谱分析的体液鉴定方法，以克服传统方法的局限性。
通过对16S rRNA基因的高变区进行测序来确定细菌谱，使用从刑事案件中收集的证据进行DNA宏条形码分析。分析扩增子序列变体（ASVs）以识别不同体液样本中的显著微生物模式。
基于细菌谱的方法在使用朴素贝叶斯算法训练的机器学习模型中显示出高鉴别力，在将样本分类为四种体液类型之一（血液、唾液、阴道分泌物以及阴道分泌物和精液的混合痕迹）时，准确率超过98%。
细菌谱分析提高了法医分析中体液鉴定的准确性和稳健性，尽管条件不可控，但通过利用DNA和微生物群落数据，为传统方法提供了一种有价值的替代方法。这种方法在法医调查中的分类准确性和实际适用性方面有显著提高。
