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Rapid and dynamic detection of antimicrobial response of pathogenic bacteria using MZO nanostructure-modified quartz crystal microbalance
Descriptive
TitleInfo
Title
Rapid and dynamic detection of antimicrobial response of pathogenic bacteria using MZO nanostructure-modified quartz crystal microbalance
Name
(type = personal)
NamePart
(type = family)
Wu
NamePart
(type = given)
Yifan
NamePart
(type = date)
1993-
DisplayForm
Yifan Wu
Role
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(authority = RULIB)
author
Name
(type = personal)
NamePart
(type = family)
Lu
NamePart
(type = given)
Yicheng
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Yicheng Lu
Affiliation
Advisory Committee
Role
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(authority = RULIB)
chair
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Rutgers University
Role
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(authority = RULIB)
degree grantor
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School of Graduate Studies
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school
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Text
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theses
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2019
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2019-05
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2019
Language
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English
Abstract
Antimicrobial resistance (AMR) threatens the effective prevention and treatment of a constantly increasing range of infections caused by bacteria, parasites, viruses and fungi, and has caused a dramatic increase in infection-related deaths, such that it threatens to become the next world pandemic. We report a magnesium zinc oxide nanostructure (MZOnano) modified quartz crystal microbalance (QCM) biosensor for rapid and dynamic detection of AMR. The sensor consists of a QCM with MZOnano grown directly on the sensing electrode using metalorganic chemical vapor deposition (MOCVD). The MZOnano sensing surface offers high-sensitivity to various biological species through surface-wettability and morphology control. Combining advantages of MZOnano with the QCM dynamic impedance spectrum makes the biosensor well-suited for monitoring viscoelastic transitions during drug treatment compared to the conventional frequency shift signals from the QCM. Using the MZOnano-QCM, we demonstrated the dynamic real-time monitoring of culture growth and antimicrobial treatment effects on two clinically relevant bacterial strains: (1) Gram-positive strain Staphylococcus epidermidis and (2) Gram-negative strain Pseudomonas aeruginosa. The antimicrobial treatment response of each of the two bacterial strains using Ciprofloxacin as the drug, was rapidly and dynamically detected. The standard microbiological protocols and assays were performed to determine the optimal drug dosages and the minimum inhibitory concentration to serve as the benchmark for the data reported by the sensors. The sensor also demonstrated capability to rapidly (within 1.5 hours) detect dosage dependent response of the two bacterial strains in real time. The testing results from two clinically-relevant bacterial strains mentioned above demonstrate the capabilities of the MZOnano - QCM to sense both mass accumulation and viscoelastic transitions during cell growth and drug treatment. It is found that the viscoelastic transitions of the bacterial cells during drug treatment gives higher sensitivity to the data as compared to the frequency shift signals of the device.
Subject
(authority = local)
Topic
Magnesium zinc oxide
Subject
(authority = RUETD)
Topic
Electrical and Computer Engineering
Subject
(authority = ETD-LCSH)
Topic
Drug resistance in microorganisms
Subject
(authority = ETD-LCSH)
Topic
Biosensors
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Rutgers University Electronic Theses and Dissertations
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ETD_9637
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1 online resource (vi, 30 pages) : illustrations
Note
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M.S.
Note
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Includes bibliographical references
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School of Graduate Studies Electronic Theses and Dissertations
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rucore10001600001
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NjNbRU
Identifier
(type = doi)
doi:10.7282/t3-t057-h668
Genre
(authority = ExL-Esploro)
ETD graduate
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Rights
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The author owns the copyright to this work.
RightsHolder
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Name
FamilyName
Wu
GivenName
Yifan
Role
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Type
Permission or license
DateTime
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2019-04-10 15:30:57
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Name
Yifan Wu
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Affiliation
Rutgers University. School of Graduate Studies
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Author Agreement License
Detail
I hereby grant to the Rutgers University Libraries and to my school the non-exclusive right to archive, reproduce and distribute my thesis or dissertation, in whole or in part, and/or my abstract, in whole or in part, in and from an electronic format, subject to the release date subsequently stipulated in this submittal form and approved by my school. I represent and stipulate that the thesis or dissertation and its abstract are my original work, that they do not infringe or violate any rights of others, and that I make these grants as the sole owner of the rights to my thesis or dissertation and its abstract. I represent that I have obtained written permissions, when necessary, from the owner(s) of each third party copyrighted matter to be included in my thesis or dissertation and will supply copies of such upon request by my school. I acknowledge that RU ETD and my school will not distribute my thesis or dissertation or its abstract if, in their reasonable judgment, they believe all such rights have not been secured. I acknowledge that I retain ownership rights to the copyright of my work. I also retain the right to use all or part of this thesis or dissertation in future works, such as articles or books.
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2019-05-31
DateTime
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2019-11-30
Detail
Access to this PDF has been restricted at the author's request. It will be publicly available after November 30th, 2019.
Copyright
Status
Copyright protected
Availability
Status
Open
Reason
Permission or license
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2019-04-12T00:05:35
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