Metaproteomic Characterization of Forensic Samples

preprint · SSRN Electronic Journal · 2022

preprint · SSRN Electronic Journal · 2022. Kristin H. Jarman et al. To date, the field of forensic proteomics has focused on the identification of specific target organisms…
Date 2022-06-16
Type preprint
Venue SSRN Electronic Journal
Publisher Elsevier BV (SSRN)
Contribution downstream-application
DOI 10.2139/ssrn.4135651
Citations (OpenAlex) 0

Abstract

To date, the field of forensic proteomics has focused on the identification of specific target organisms, tissues, or proteins in unknown source samples. Numerous published studies have demonstrated the ability of bottom-up proteomics to perform reliable and accurate unknown protein identification. However, to our knowledge, none of the published methods address the problem of a true protein-containing unknown, a sample where nothing is known a priori about its contents. In this work, we suggest how proteomics might be used to generate leads in an investigation. Specifically, we ask the question ‘can shotgun proteomics be used to reduce the list of potential protein sources in a true unknown’? To answer this question, we employ approaches developed for metaproteomics, a field of study concerned with characterizing proteins in complex, poorly characterized microbial communities. Our approach relies on de novo peptide sequencing followed by taxonomic assignment and statistical scoring to identify potential protein sources in a sample. We test our forensic metaproteomics workflow on 90 high-resolution LC-MS/MS datasets from a wide diversity of bacterial samples, along with 144 simulated mixtures constructed from these original datasets. Results show that this approach effectively isolates the protein sources in in our test datasets, suggesting that forensic metaproteomics may play a useful role in unknown sample characterization and lead generation.

Authors

  1. Kristin H. Jarman · Karius Inc., Pacific Northwest National Laboratory
  2. Sarah C. Jenson · Pacific Northwest National Laboratory
  3. Natalie C. Heller-Lamar · Pacific Northwest National Laboratory
  4. Dustin L. Crockett · Pacific Northwest National Laboratory
  5. Eric D. Merkley · Pacific Northwest National Laboratory

Methods and tools

  • PNNL forensic metaproteomic characterization: De novo peptide sequencing plus taxonomic assignment and statistical scoring to characterize protein sources in complex forensic samples: a precursor to the MARLOWE tool from the same PNNL group.

Cites (9)

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