ABSTRACT
Metabarcoding through Next Generation Sequencing (NGS) has revolutionized environmental biological studies. The availability of this technical approach has opened the opportunity for a systematic implementation of fungal metabarcoding analysis in forensics, where standardized, sensitive and reproducible protocols are highly desirable. In the present paper, a pipeline including a semi-automated molecular protocol and user-friendly bioinformatics tools are applied to several kinds of environmental samples and forensic caseworks. The identification of fungi that characterize specific environments (like Aspergillus for indoor walls, or Penicillium, Debaryomices and Wickerhamomyces for food storage) can be informative for the provenance of samples. In some situations, fungal analysis cannot allow the identification of a defined environment but seems useful to cluster samples with similar provenance. Based on these considerations, fungal analysis can be included in a wider process of non-human DNA identification in order to provide clues on sample provenance.
Subject(s)
DNA Barcoding, Taxonomic , DNA, Fungal/genetics , Fungi/genetics , High-Throughput Nucleotide Sequencing/methods , Environmental Microbiology , Forensic Sciences , Principal Component Analysis , Sequence Analysis, DNA , SoftwareABSTRACT
The identification of vaginal fluids is crucial in forensic science. Several molecular protocols based on PCR amplification of mfDNA (microflora DNA) specific for vaginal bacteria are now available. Unfortunately mfDNA extraction and PCR reactions require manual optimization of several steps. The aim of present study was the verification of a partial automatization of vaginal fluids identification through two instruments widely diffused in forensic laboratories: EZ1 Advanced robot and Rotor Gene Q 5Plex HRM. Moreover, taking advantage of 5-plex thermocycler technology, the ForFluid kit performances were improved by expanding the mfDNA characterization panel with a new bacterial target for vaginal fluids and with an internal positive control (IPC) to monitor PCR inhibition. Results underlined the feasibility of a semi-automated extraction of mfDNA using a BioRobot and demonstrated the analytical improvements of the kit.
