An ultra-high throughput mutational spectrometer for human genetic diagnostics

Abstract

Discovering the genetic causes of common diseases may require scanning for mutations in all of the genes in a million people, a significant undertaking. Such discoveries would revolutionize biotechnology, potentially enabling simple genetic tests for risk and targeted preventative or therapeutic strategies. An increase in throughput of genetic analysis instrumentation by several orders of magnitude is essential to undertake such an ambitious task. In this thesis, progress will be presented towards the creation of such a "mutational spectrometer" instrument containing up to 10,000 capillary channels and enabled with subsystems for loading, separating, and detecting fluorescently-labeled DNA. Challenges include DNA manipulation, optical signal detection, macro/micro design integration, precision alignment and assembly, and thermal control. To manipulate DNA, we have utilized a bioMEMS design platform for interfacing to an array of separation channels that enables electrokinetic biomolecule loading, detection, and fraction collection in independent wells.

(cont.) Signal detection is accomplished by a sensitive (107 molecule limit-of-detection), scalable (to 10,000 independent channels), end-of-column fluorescence detection technology that accommodates tightly packed capillary arrays as required for ultra-high throughput electrophoretic separation. Capillary array assembly and constraint technologies have been developed for 2-D arrays containing as many as 10,000 replaceable capillaries. Thermal control requirements of 0.3 °C over the entire 10,000 channel array are met with a cross-flow water heat exchanger. Additional subsystems for forcing a viscous polymer matrix into the capillaries, and interfacing the capillary array to a fluid reservoir for electrophoresis have also been developed, as required. This work lays the foundation for the realization of a mutational spectrometer instrument that will enable population-wide pangenomic analyses to uncover the genetic causes of common diseases.