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                            Library & Multimedia
 A predictive model for vertebrate bone identification from collagen using proteomic mass spectrometry
NCJ Number
              305077
Journal

*Scientific Reports* Volume: 11 Issue: 1 Dated: 2021
Author(s)
          Heyi Yang;
                        Erin R. Butler;
                        Samantha A. Monier;
                        Jennifer Teubl;
                        David Fenyö;
                        Beatrix Ueberheide;
                        Donald Siegel
Date Published

May 2021
Annotation
              Here we evaluate the causes of peptide sequence errors and propose an unbiased, probabilistic approach to determine the likelihood that a species is correctly identified from bone without relying on species-specific peptides.
Abstract
              Proteogenomics is an increasingly common method for species identification as it allows for rapid and inexpensive interrogation of an unknown organism’s proteome—even when the proteome is partially degraded. The proteomic method typically uses tandem mass spectrometry to survey all peptides detectable in a sample that frequently contains hundreds or thousands of proteins. Species identification is based on detection of a small numbers of species-specific peptides. Genetic analysis of proteins by mass spectrometry, however, is a developing field, and the bone proteome, typically consisting of only two proteins, pushes the limits of this technology. Nearly 20% of highly confident spectra from modern human bone samples identify non-human species when searched against a vertebrate database—as would be necessary with a fragment of unknown bone. These non-human peptides are often the result of current limitations in mass spectrometry or algorithm interpretation errors. Consequently, it is difficult to know if a “species-specific” peptide used to identify a sample is actually present in that sample. (Publisher abstract provided)
      
  
          Additional Details
Grant Number(s)
        2017-NE-BX-0003
                                2010-DN-BX-K192
                                2014-DN-BX-K014


  
  
        
  Agencies
        NIJ-Sponsored


  
  
        
  Award
        Development of a Proteomic Assay for Menstrual Blood, Vaginal Fluid and Species Identification
                                Identifying Individuals through Proteomic Analysis: A New Forensic Tool to Rapidly and Efficiently Identify Large Numbers of Fragmentary Human Remains
                                Bioinformatic Analaysis of Big Proteomic Data:  A New Forensic Tool to Identify Menstrual Blood & Body Fluid Mixtures
    
  
  
Date Published: May 1, 2021
    
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