Dulce Jimenez
Dulce Jimenez
Dulce Jimenez
Helios Scholar
School: Northern Arizona University
Hometown: Tucson, Arizona
Mentor: David Engelthaler, Ph.D.

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Whole genome library preparation kit comparison for next generation sequencing of Mycobacterium tuberculosis

Tuberculosis (TB) is an airborne infectious disease caused by Mycobacterium tuberculosis (Mtb) that primarily affects the lungs, but can disseminate throughout the entire body. Drug resistant TB is a major concern, especially since multidrug resistant (MDR) and extensively drug resistant (XDR) cases are increasing. Early detection of MDR or XDR is difficult with current diagnostics. Incorrect diagnosis of low-level drug resistant tuberculosis can lead to poor patient outcomes and community spread, since treatment using TB drugs without understanding an individual’s resistance profile typically selects for resistant populations.

TGen North is working with over 30 global collaborators including the Critical Path Institute to build the ReSeqTB database, the largest and most comprehensive global resource linking drug resistant tuberculosis to DNA mutations. In addition, TGen North is actively building diagnostic solutions using genomics technologies to quickly detect low-level resistant TB populations in clinical samples to help physicians correctly diagnose and treat patients. Once the ReSeqTB genome database is populated, we will be able to identify new resistance-conferring genes and incorporate them as additional targets into our rapid diagnostic solutions.

To mximize costs, sequence quality, and ultimately add the most genomes to the ReSeqTB database as possible, we tested two different library preparation methods for whole genome sequencing (Kapa Library Preparation kit versus NEB Ultra II DNA Preparation Kit). For our rapid diagnostic solutions, one major barrier to making targeted genome sequencing available in clinical laboratories is normalizing individual sample libraries using conventional qPCR methods. We tested an alternative library normalization method, SequalPrep, which has shown promise in previous tests. These results identify the relative performance limits of these two methods, as tests were conducted near the limit of detection for both.