Date of Award
Spring 6-1-2023
Document Type
Thesis
Degree Name
Master of Science (MS)
Department/Program
Forensic Science
Language
English
First Advisor or Mentor
Richard Li
Second Reader
Andrew Schweighardt
Third Advisor
Mark Desire
Abstract
In forensic science, DNA extraction can be a tedious and resource-intensive process. Extraction with Proteinase K is an industry standard but has its drawbacks, such as requiring multiple ionic detergents and washing steps. MicroGEM has developed a new enzyme called forensicGEM that is temperature-dependent and compatible with mesophilic enzymes, offering complete DNA extraction in about 20 minutes in a single tube, limiting contamination, loss of sample, and working time. ForensicGEM can extract DNA from highly degraded samples, potentially leading to more complete STR profiles. Highly degraded tissue and bone samples were collected and extracted with the forensicGEM kit, altering different parameters to assess the efficiency and potential uses of forensicGEM. The STR profiles of samples extracted with forensicGEM were compared to those extracted with a standard organic extraction. Half of the degraded samples extracted with forensicGEM had detectable DNA, with the highest success rate observed for bone samples. Success with bone profiling was notable given that there was much less sample input for forensicGEM (10 mg) compared to the organic extraction (2 g). The forensicGEM kit yielded a 22-locus and a 15-locus profile on two highly degraded samples from the 9/11 World Trade Center attacks. The bone preparation method of scraping yielded higher DNA quantities and better-quality profiles compared to samples treated with the standard method of milling. Future work will focus on further investigation of the bone scraping method and continued optimization of experimental parameters in the MicroGEM extraction protocol.
Recommended Citation
Vega, Falyn R., "Extraction of Challenging Forensic Samples Using the MicroGEM DNA Extraction Kit" (2023). CUNY Academic Works.
https://academicworks.cuny.edu/jj_etds/282
