DEVELOPMENT OF A NOVEL NANOPORE-BASED SENSING TECHNOLOGY FOR NOROVIRUS DETECTION

Author

Minji Kim, University of Massachusetts AmherstFollow

Author ORCID Identifier

https://orcid.org/0000-0002-8926-9449

AccessType

Campus-Only Access for Five (5) Years

Document Type

dissertation

Degree Name

Doctor of Philosophy (PhD)

Degree Program

Food Science

Year Degree Awarded

2024

Month Degree Awarded

February

First Advisor

Matthew D. Moore

Second Advisor

Min Chen

Third Advisor

Lili He

Subject Categories

Biochemistry | Biophysics | Food Microbiology | Molecular Biology | Virology

Abstract

Human norovirus is one of the leading causes of foodborne illness and mortality. Although polymerase chain reaction (PCR) is considered a gold standard method for norovirus detection, it has limitations in terms of portability and detection time. In this degree research, we developed a nanopore sensor to overcome conventional detection methods, utilizing E.coli Outer membrane protein G (OmpG). To engineer the OmpG, we initially employed two peptides (Noro-1 and Noro-2) and three aptamers (M6-2, AG3, and APTL-1) from previous research^1–4. However, after testing their interaction with the target norovirus capsid P domain through fluorescence anisotropy and ITC, we found no affinity. Thus, we did not proceed with these ligands in further experiments. Next OmpG engineering strategy involved creating a library by scrambling the OmpG loop sequence. As a result, 0.1 % of the total population was in the flow cytometry P domain sort gate. Although we collected these sorted cells and attempted to grow them, they proved difficult to cultivate, and gene loss was observed. This indicated that the generated library was suboptimal for detecting the P domain. Hence, we decided to test ligand insertion into the OmpG loop for optimization, utilizing a FLAG tag with a glycine linker for spacing. We observed an OmpG construct containing an inserted FLAG sequence, showing strong interaction with anti-FLAG antibodies in flow cytometry. However, it could not translate molecular interactions into a readable signal in current recordings. We optimized the peptide presentation by replacing specific loop 6 sequences with the FLAG tag. This led to a construct capable of generating distinct signals when interacting with various anti-FLAG IgG antibodies, highlighting the importance of the binding motif’s location and length in OmpG loops for single current recording. This underscores the need to consider ligand location and loop length when generating a new OmpG construct. Rogers and coworkers found that 12-mer peptides of NV-O-R5-3 bind to the P domain of Norwalk virus virus-like particles⁵. To test whether the norovirus affinity peptides, Noro-1 and NV-OR5-3, bind to the P domain, surface-enhanced Raman spectroscopy (SERS) was used. The affinity peptide-labeled gold nanoparticles were incubated with 300 nM or 1 uM P domain each for 20 minutes at room temperature. Peptide Noro-1 labeled gold substrate did not generate any signal, while peptide NV-O-R5-3 labeled gold substrate displayed a unique peak at 750 cm^-1. This result confirms NV-O-R5-3’s interaction with the P domain for further experiments. Based on the SERS results, a new OmpG engineering strategy using peptide NV-O-R5-3 was employed. Preliminary data revealed unclear binding signals when NV-O-R5-3 replaced sequences in OmpG loop 6 due to the pore’s quiet characteristics in single-channel recording. To address this, we introduced recognition sites for TEV and thrombin at the N-terminus of NV-O-R5-3 to linearize the peptide. After purifying and refolding OmpG, loop cleavage occurred, and single molecular detection with the target norovirus P domain revealed a reduced frequency of irregular spikes, resulting in decreased occurrence of the pore’s closed state around 10 pA.

DOI

https://doi.org/10.7275/36154248

Recommended Citation

Kim, Minji, "DEVELOPMENT OF A NOVEL NANOPORE-BASED SENSING TECHNOLOGY FOR NOROVIRUS DETECTION" (2024). Doctoral Dissertations. 3058.
https://doi.org/10.7275/36154248 https://scholarworks.umass.edu/dissertations_2/3058

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This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.