Biochemist Glendon Parker examines a 250-year-old archaeological hair sample analyzed for human identification using protein markers from the hair. (Photo : Lawrence Livermore National Laboratory)
The first-ever biological identification method that exploits the information encoded in proteins of human hair has been developed by scientists from Lawrence Livermore National Laboratory (LLNL) and a Utah startup company.
The partners' groundbreaking technique provides a second science-based, statistically validated way to identify people and link individuals to evidence in addition to DNA profiling.
The new protein identification technique will offer another tool to law enforcement for crime scene investigations. It will also help archaeologists since the method has been able to detect protein in human hair over 250 years old.
Once the method is optimized, researchers believe they can use protein markers from a small number of human hairs, possibly as little as one, to distinguish an individual among the world's population.
"We are in a very similar place with protein-based identification to where DNA profiling was during the early days of its development," said LLNL chemist Brad Hart, director of the Lab's Forensic Science Center and co-author of a paper detailing the work.
"This method will be a game-changer for forensics, and while we've made a lot of progress toward proving it, there are steps to go before this new technique will be able to reach its full potential."
The work of LLNL scientists, a researcher with Utah-based Protein-Based Identification Technologies LLC and other collaborators is described in a paper published in PLOS ONE, a San Francisco-based peer reviewed online scientific journal.
In the PLOS ONE study, researchers examined male and female hair samples for 66 European-Americans, five African Americans, five Kenyans and six skeletal remains from the 1750s and 1850s, finding a total of 185 protein markers so far. Each person's number of hair protein markers, combined with their pattern of protein markers, is unique.
Using their current sample sizes, the researchers were able to find enough markers to provide a unique pattern for an individual that would distinguish that person among a population of one million.
The new method addresses a 2009 National Research Council report on forensic science that detailed the weaknesses of many current approaches and reported an urgent need for new science-based forensic methods.
"Nuclear DNA is the gold standard for human identification, but it is quite fragile," Hart said. "When the DNA molecule degrades from light, heat exposure or other environmental conditions, it becomes useless for identification."
Proteins are chemically more robust than nuclear DNA. That point was illustrated by the team's work as the researchers found protein markers in human hair from six skeletal remains taken from cemeteries in the greater London area dating back about 150 to 250 years.
In the research, the protein markers used by the scientists have been variants in the proteins resulting from amino acid substitutions that stem from DNA mutations, and are known as single amino acid polymorphisms (SAPs).
The team's research kicked into high gear in March 2013 when biochemist Glendon Parker, the inventor of the protein identification concept and then an associate professor at Utah Valley University, came to work at LLNL. Parker is the lead author of the PLOS ONE paper.
"Glendon's clever invention was to realize that the uniqueness of SAPs could be used to identify individual people, and the robustness of the technique relies on its link back to DNA," said Deon Anex, an LLNL chemist and co-author.
Although people do not inherit proteins, they do inherit the DNA that produces their proteins.
"As a result, there is a link between the protein markers that we find and a person's DNA. There are two reasons why this is particularly important: the DNA is unique to each individual and it is inherited from a person's parents," Anex said.
In addition to Hart, Parker and Anex, other LLNL researchers who have worked on the project are biochemist and postdoc Katelyn Mason, bioinformaticist Marisa Torres and biologists Bonnee Rubinfeld and Cheryl Strout.
The team's collaborators and advisers include researchers from seven universities: Utah Valley University, the University of Utah, Montana State University, the University of California, Davis, the University of Bradford in the United Kingdom, George Mason University and the University of Washington.
