Microbes are ubiquitous organisms, and microbiomes (or communities of microbes) have important forensic applications. Analysis of microbial communities can be applied to human identification (from individuals’ specific microbial communities), body fluid identification (microbial community signatures), and postmortem interval estimations (microbial clocks). Many of these forensic microbiology applications are only possible due to the application of next generation sequencing (NGS).
NGS technologies generate millions of sequence reads that describe the microbial communities. However, the data generated from NGS are complex and we are just beginning to understand how to process and analyze microbial data for forensic application.
Pushing forensic microbiology forward into the criminal justice system will require standardization of pipelines, and other parameters associated with downstream forensic microbiology analysis. We assessed bioinformatic pipelines, and two other important parameters (normalization of sequence reads and sample size) for optimizing downstream analysis for forensic microbiology (Kaszubinski et al 2019).
From Kaszubinski et al (2019): In silico data error among pipelines.(A) Taxon output from each pipeline was compared to the taxonomic reference dataset available on mockrobiota. Taxa present in only the mockrobiota taxonomic reference = false negatives, while taxa present only in the pipeline outputs = false positives. (B–D) Abundance of taxa from pipeline output versus expected abundance of taxa based on reference dataset for each sample. (B) MG‐RAST, (C) mothur, and (D) QIIME2.
There are many interesting questions left to be answered about the postmortem microbiome and its application to forensics. Through a partnership with Dr. Eric Benbow, and Dr. Jen Pechal at MSU, we hope to answer questions about the general microbial community structure, while also building tools for future forensic applications.
Kasubinski, SF., J. Pechal, C. Schmidt, H. Jordan, M. Benbow, and M. Meek. 2019. Evaluating bioinformatic pipeline performance for forensic microbiome analysis. Journal of Forensic Sciences. https://doi.org/10.1111/1556-4029.14213