Date of Award

6-14-2019

Document Type

Thesis

Publisher

Santa Clara : Santa Clara University, 2019.

Degree Name

Master of Science (MS)

Department

Bioengineering

First Advisor

Maryam Mobed-Miremadi

Second Advisor

Ashley Kim

Abstract

Milkguard is an alginate-based biosensor developed to detect E. coli in human breast milk via the metabolism of X-gal (5-Bromo-4-Chloro-3-Indolyl β-D-Galactopyranoside) by β-galactosidase. In order to deconvolute metabolic reproducibility from scaling laws, the commercial enzyme β-galactosidase was used to mimic the biological function of the bacterial lac operon. Downscaling was explored as an optimization of the biosensor design based on numerical solutions to Fickian-based diffusion models. The characterization of large capsules (d ≅ 3 mm) and atomized microcapsules (d ≅ 300 ± 60 μm) yielded size-specific Michaelis-Menten constants. Small capsules (Km = 3.6 x 10-4 M; Vmax ’’ = 1.2 x 10-3) produced a significantly faster response time versus large capsules when loaded at a substrate concentration of 5 mg/mL (p = 7.7x 10-3 at 𝛼 = 0.01) and 2.5 mg/mL (p = 1.5 x 10-4 at 𝛼 < 0.001). Comparisons of effectiveness factors between small (η = 0.58) and large (η = 0.43) capsules indicates a lesser degree of diffusion limitations in small capsules. Large bootstrapping errors produced by nonlinear regression of Michaelis-Menten models for the capsules suggests that additional mechanisms to diffusion are involved in producing sensor response. A new sensor mechanism combining Fickian diffusion and experimental results is proposed and modeled numerically.

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