NEW TOOL IN THE BELT - ENVIRONMENTAL DNA FOR THE ANALYSIS OF SOIL AND DUST

Soil and dust are often submitted to crime laboratories as trace evidence and can be used to link an individual to a crime scene or to determine provenance. Current methodologies that are applied to analyze these geologic materials aim to characterize their physical properties (e.g. color and pH) and inorganic components (e.g. mineral content), but sample size can limit these analyses. A supplemental method is needed to harness additional evidentiary information from geologic materials. DNA metabarcoding is a commonly used approach to identify the biological taxa present in various environmental samples by amplifying and sequencing short, yet informative, regions of the genome and is not restricted by sample amount. The goal of this research is to determine the utility and stability of environmental DNA (eDNA) associated with mock soil and dust evidence for sample-to-sample comparisons and determining sample origin. To achieve this, bacteria (16S), fungi (ITS1), arthropods (COI), and plants (ITS2, trnL) associated with each sample were characterized (n, 1026). An initial soil isolation study was performed to determine the most optimal approach (scrapping, swabbing and sonication) to remove soil from mock evidence for downstream eDNA analysis. Picking and scrapping of soil yielded the highest amount of DNA compared to swabbing (p = 0.0025) and sonication (p = 0.0068). Following the soil isolation study, five mock geologic evidence items were collected in triplicate monthly from an agricultural and urban location in North Carolina over a one-year period. Mock items included a) soil removed from t-shirts, boot soles, and trowels using the scrapping method, b) exposed dust collected from brick pavers, and c) dry dust from air filters. Libraries were generated using custom indexed primers that target each barcode region and were sequenced using the Illumina MiSeq. Raw sequencing reads were processed through a bioinformatic pipeline that removes primer sequences, identifies amplicon sequence variants (ASVs) via DADA2, and searches ASVs against GenBank for taxonomic identification. This presentation will focus on the experimental design and workflow and will include a preliminary assessment of temporal and spatial variables on the recovery of bacteria, fungi, arthropods, and plants from mock geologic evidence.