title: Microbiome Tools for Forensic Science.
abstract: Microbes are present at every crime scene and have been used as physical evidence for over a century. Advances in DNA sequencing and computational approaches have led to recent breakthroughs in the use of microbiome approaches for forensic science, particularly in the areas of estimating postmortem intervals (PMIs), locating clandestine graves, and obtaining soil and skin trace evidence. Low-cost, high-throughput technologies allow us to accumulate molecular data quickly and to apply sophisticated machine-learning algorithms, building generalizable predictive models that will be useful in the criminal justice system. In particular, integrating microbiome and metabolomic data has excellent potential to advance microbial forensics.
authors.affiliation: Department of Animal Sciences, Colorado State University, Fort Collins, CO ​80523, USA. Electronic address: Jessica.Metcalf@colostate.edu.
authors.forename: Jessica L
authors.initials: JL
authors.lastname: Metcalf
authors.affiliation: Department of Pediatrics, University of California, San Diego School of Medicine, La Jolla, CA 92093, USA.
authors.forename: Zhenjiang Z
authors.initials: ZZ
authors.lastname: Xu
authors.affiliation: Department of Pharmacology, University of California, San Diego, La Jolla, CA 92093, USA.
authors.forename: Amina
authors.initials: A
authors.lastname: Bouslimani
authors.affiliation: Department of Pediatrics, University of California, San Diego School of Medicine, La Jolla, CA 92093, USA; Department of Pharmacology, University of California, San Diego, La Jolla, CA 92093, USA; Collaborative Mass Spectrometry Innovation Center, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA 92093, USA; Center for Microbiome Innovation, Jacobs School of Engineering, University of California, San Diego, La Jolla, CA 92093, USA.
authors.forename: Pieter
authors.initials: P
authors.lastname: Dorrestein
authors.affiliation: Laboratory of Forensic Taphonomy, Forensic Sciences Unit, Division of Natural Sciences and Mathematics, Chaminade University of Honolulu, Honolulu, HI 96816, USA.
authors.forename: David O
authors.initials: DO
authors.lastname: Carter
authors.affiliation: Department of Pediatrics, University of California, San Diego School of Medicine, La Jolla, CA 92093, USA; Center for Microbiome Innovation, Jacobs School of Engineering, University of California, San Diego, La Jolla, CA 92093, USA; Department of Computer Science and Engineering, Jacobs School of Engineering, University of California San Diego, La Jolla, CA 92093, USA.
authors.forename: Rob
authors.initials: R
authors.lastname: Knight
mesh_terms: D000465:Algorithms; D000818:Animals; D044707:Forensic Sciences / Q000379:methods* / Q000639:trends; D059014:High-Throughput Nucleotide Sequencing; D006801:Humans; D000069550:Machine Learning; D064307:Microbiota
keywords: forensics; machine learning; metabolomic; microbiome; postmortem interval; trace evidence