Publication Date
Fall 2019
Degree Type
Thesis
Degree Name
Master of Science (MS)
Department
Chemical and Materials Engineering
Advisor
Anand K. Ramasubramanian
Keywords
High-Throughput Screening, lab on a chip, Metagenomics
Subject Areas
Chemical engineering
Abstract
The growing prevalence of antibiotic resistance is one of the greatest challenges facing humankind today. The Centers for Disease Control and Prevention (CDC) have estimated that about 2 million people in the US each year develop an infection caused by antibiotic-resistant bacteria, and about 23,000 people die. To combat this growing crisis, efforts geared toward the discovery of novel compounds, such as antimicrobial peptides (AMPs), have spurred. However, current approaches for identification of such compounds have proven to be costly, time-consuming and ineffective. This problem underscores the need for a new approach, one that is fundamentally different from traditional methods both in the content of the library being screened and in the screening methodology. As a first demonstration of this approach, we have developed an E. coli chip – a novel, robust, high-density nano-culture platform – and an associated high-throughput screening methodology to successfully screen for cells containing genes that confer resistance to ampicillin from a soil metagenomic library. This platform offers several advantages over the current industry standard, a 96-well microplate platform, including miniaturization, automation, reduced amount and cost of reagents and process time. It eliminates the need for more than one round of screening thus potentially speeding up the antibiotic discovery process. Further, a single E. coli chip can replace the work of approximately seven 96-well plates. These advantages make this technology ideal for further applications, including screening for AMPs.
Recommended Citation
Tiongco, Richard Paul Manarin, "High-Throughput Screening of a Metagenomic Library Using a Novel E. Coli Chip for Discovery of Antibiotic Resistance Genes" (2019). Master's Theses. 5084.
DOI: https://doi.org/10.31979/etd.fh4k-65ww
https://scholarworks.sjsu.edu/etd_theses/5084