Body fluid identification is an important area of forensic casework as it aids in crime scene reconstruction. Nonetheless, accurate body fluid identification remains a challenge in forensic cases given the limitations of current identification methods. Recent human microbiome studies have shown the tissue-specificity of microbial communities, highlighting their potential utilization to distinguish body sites. In this project we investigate the robustness and accuracy of microbial forensic methods for body fluid identification, utilizing next-generation sequencing methods as well as machine-learning algorithms. In addition, we also explore the potential of microbiome data for individual identification.
Bioinformatics Group, Institute of Molecular Life Sciences
Applied Computational Genomics group, ZHAW School of Life Sciences and Facility Management
Dobay A, Haas C, Fucile G, Downey N, Morrison HG, Kratzer A, and Arora N (2019). Microbiome-based body fluid identification of samples exposed to indoor conditions. Forensic Science International Genetics, doi: https://doi.org/10.1016/j.fsigen.2019.02.010
Tackmann J, Arora N, Benedikt Schmidt TS, Matias Rodrigues JF, and von Mering C (2018). Ecologically informed microbial biomarkers and accurate classification of mixed and unmixed samples in an extensive cross-study of human body sites. BMC Microbiome 6: 192, https://doi.org/10.1186/s40168-018-0565-6