Rapid Antimicrobial Susceptibility Testing Based on Bacterial Motion Tracking

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Description
Antibiotic resistant bacteria are a worldwide epidemic threatening human survival. Antimicrobial susceptibility tests (ASTs) are important for confirming susceptibility to empirical antibiotics and detecting resistance in bacterial isolates. Current ASTs are based on bacterial culturing, which take 2-14 days to

Antibiotic resistant bacteria are a worldwide epidemic threatening human survival. Antimicrobial susceptibility tests (ASTs) are important for confirming susceptibility to empirical antibiotics and detecting resistance in bacterial isolates. Current ASTs are based on bacterial culturing, which take 2-14 days to complete depending on the microbial growth rate. Considering the high mortality and morbidity rates for most acute infections, such long time frames are clinically impractical and pose a huge risk to a patient's life. A faster AST will reduce morbidity and mortality rates, as well as help healthcare providers, administer narrow spectrum antibiotics at the earliest possible treatment stage.

In this dissertation, I developed a nonculture-based AST using an imaging and cell tracking technology. I track individual Escherichia coli O157:H7 (E. coli O157:H7) Uropathogenic Escherichia Coli (UPEC) cells, widely implicated in food-poisoning outbreaks and urinary tract infections respectively. Cells tethered to a surface are tracked on the nanometer scale, and phenotypic motion is correlated with bacterial metabolism. Antibiotic action significantly slows down motion of tethered bacterial cells, which is used to perform antibiotic susceptibility testing. Using this technology, the clinical minimum bactericidal concentration of an antibiotic against UPEC pathogens was calculated within 2 hours directly in urine samples as compared to 3 days using current gold standard tools.

Such technologies can make a tremendous impact to improve the efficacy and efficiency of infectious disease treatment. This has the potential to reduce the antibiotic mis-prescription steeply, which can drastically decrease the annual 2M+ hospitalizations and 23,000+ deaths caused due to antibiotic resistance bacteria along with saving billions of dollars to payers, patients, and hospitals.
Date Created
2017
Agent

Plasmonic Imaging of Protein Interactions With Single Bacterial Cells

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Description

Quantifying the interactions of bacteria with external ligands is fundamental to the understanding of pathogenesis, antibiotic resistance, immune evasion, and mechanism of antimicrobial action. Due to inherent cell-to-cell heterogeneity in a microbial population, each bacterium interacts differently with its environment.

Quantifying the interactions of bacteria with external ligands is fundamental to the understanding of pathogenesis, antibiotic resistance, immune evasion, and mechanism of antimicrobial action. Due to inherent cell-to-cell heterogeneity in a microbial population, each bacterium interacts differently with its environment. This large variability is washed out in bulk assays, and there is a need of techniques that can quantify interactions of bacteria with ligands at the single bacterium level. In this work, we present a label-free and real-time plasmonic imaging technique to measure the binding kinetics of ligand interactions with single bacteria, and perform statistical analysis of the heterogeneity. Using the technique, we have studied interactions of antibodies with single Escherichia coli O157:H7 cells and demonstrated a capability of determining the binding kinetic constants of single live bacteria with ligands, and quantify heterogeneity in a microbial population.

Date Created
2015-01-15
Agent