Dielectrophoresis assisted rapid, selective and single cell detection of antibiotic resistant bacteria with G-FETs
Abstract
Time-consuming, expensive and low sensitivity diagnostic methods used for monitoring bacterial infections lead to unnecessary or delays in prescription of the right antibiotic treatment. Determining an optimal clinical treatment requires rapid detection and identification of pathogenic bacteria and their sensitivity to specific antimicrobials. However, diagnostic devices that meet all of these criteria have proven elusive thus far. Graphene field effect transistors (G-FET) are a promising solution, since they are highly sensitive to chemical/biological modification, can have fast detection times and can be placed on different substrates. Here, by integrating specific peptide probes over G-FETs, we present a proof-of-concept study for species and strain specific label-free detection of clinical strains of pathogenic bacteria with high specificity and sensitivity. We found that pyrene-conjugated peptides immobilized on G-FETs were capable of detecting pathogenic Staphylococcus aureus at the single-cell level and discriminate against other gram-positive and gram-negative bacterial pathogens. A similar device was able to discriminate between antibiotic resistant and sensitive strains of Acinetobacter baumannii , suggesting that these devices can also be used for detecting antibiotic resistive pathogens. Furthermore, a new means of enhancing attachment, electric-field assisted binding, reduced the detection limit to 104 cells/ml and the detection time to below 5 minutes.more »
- Authors:
-
- Boston College, Chestnut Hill, MA (United States)
- Boston Univ., MA (United States)
- Publication Date:
- Research Org.:
- Boston College, Chestnut Hill, MA (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC), Basic Energy Sciences (BES). Materials Sciences & Engineering Division; National Institutes of Health (NIH); National Science Foundation (NSF); USDOE
- OSTI Identifier:
- 1780972
- Alternate Identifier(s):
- OSTI ID: 1603705
- Grant/Contract Number:
- SC0018675; R01-AI110724; U01-AI124302; R01-GM102735; R01-GM124231; DMR-1709987; BIO-1460628
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Biosensors and Bioelectronics
- Additional Journal Information:
- Journal Volume: 156; Journal ID: ISSN 0956-5663
- Publisher:
- Elsevier
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 77 NANOSCIENCE AND NANOTECHNOLOGY; Biosensors; G-FET; Peptide probes; Dielectrophoresis; Antibiotic resistance bacteria; Electrical detection
Citation Formats
Kumar, Narendra, Wang, Wenjian, Ortiz-Marquez, Juan C., Catalano, Matthew, Gray, Mason, Biglari, Nadia, Hikari, Kitadai, Ling, Xi, Gao, Jianmin, van Opijnen, Tim, and Burch, Kenneth S. Dielectrophoresis assisted rapid, selective and single cell detection of antibiotic resistant bacteria with G-FETs. United States: N. p., 2020.
Web. doi:10.1016/j.bios.2020.112123.
Kumar, Narendra, Wang, Wenjian, Ortiz-Marquez, Juan C., Catalano, Matthew, Gray, Mason, Biglari, Nadia, Hikari, Kitadai, Ling, Xi, Gao, Jianmin, van Opijnen, Tim, & Burch, Kenneth S. Dielectrophoresis assisted rapid, selective and single cell detection of antibiotic resistant bacteria with G-FETs. United States. https://doi.org/10.1016/j.bios.2020.112123
Kumar, Narendra, Wang, Wenjian, Ortiz-Marquez, Juan C., Catalano, Matthew, Gray, Mason, Biglari, Nadia, Hikari, Kitadai, Ling, Xi, Gao, Jianmin, van Opijnen, Tim, and Burch, Kenneth S. Thu .
"Dielectrophoresis assisted rapid, selective and single cell detection of antibiotic resistant bacteria with G-FETs". United States. https://doi.org/10.1016/j.bios.2020.112123. https://www.osti.gov/servlets/purl/1780972.
@article{osti_1780972,
title = {Dielectrophoresis assisted rapid, selective and single cell detection of antibiotic resistant bacteria with G-FETs},
author = {Kumar, Narendra and Wang, Wenjian and Ortiz-Marquez, Juan C. and Catalano, Matthew and Gray, Mason and Biglari, Nadia and Hikari, Kitadai and Ling, Xi and Gao, Jianmin and van Opijnen, Tim and Burch, Kenneth S.},
abstractNote = {Time-consuming, expensive and low sensitivity diagnostic methods used for monitoring bacterial infections lead to unnecessary or delays in prescription of the right antibiotic treatment. Determining an optimal clinical treatment requires rapid detection and identification of pathogenic bacteria and their sensitivity to specific antimicrobials. However, diagnostic devices that meet all of these criteria have proven elusive thus far. Graphene field effect transistors (G-FET) are a promising solution, since they are highly sensitive to chemical/biological modification, can have fast detection times and can be placed on different substrates. Here, by integrating specific peptide probes over G-FETs, we present a proof-of-concept study for species and strain specific label-free detection of clinical strains of pathogenic bacteria with high specificity and sensitivity. We found that pyrene-conjugated peptides immobilized on G-FETs were capable of detecting pathogenic Staphylococcus aureus at the single-cell level and discriminate against other gram-positive and gram-negative bacterial pathogens. A similar device was able to discriminate between antibiotic resistant and sensitive strains of Acinetobacter baumannii , suggesting that these devices can also be used for detecting antibiotic resistive pathogens. Furthermore, a new means of enhancing attachment, electric-field assisted binding, reduced the detection limit to 104 cells/ml and the detection time to below 5 minutes. Here, the combination of single step attachment, inexpensive production, rapid, selective and sensitive detection suggest G-FETs plus pyrene-conjugated peptides are a new platform for solving major challenges faced in point of care diagnostics to fight infectious diseases and antimicrobial resistance.},
doi = {10.1016/j.bios.2020.112123},
journal = {Biosensors and Bioelectronics},
number = ,
volume = 156,
place = {United States},
year = {Thu Feb 27 00:00:00 EST 2020},
month = {Thu Feb 27 00:00:00 EST 2020}
}
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