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Title: Machine learning enabled acoustic detection of sub-nanomolar concentration of trypsin and plasmin in solution

Abstract

Here, we demonstrate a machine learning enabled low-cost acoustic detection of protease which may find application in assuring quality and safety of dairy products, drug screening, molecular profiling, and disease diagnostics. A hydrophilic SiO2-coated quartz crystal microbalance (QCM) acts as a substrate to assemble α-, β-, and κ-casein layers (protease reporters) and as a transducer for measuring changes in frequency as casein is removed by protease. We demonstrate that α-, β-, and κ-caseins can form stable assembly on SiO2 from phosphate-buffered solution (PBS) solution. Exposure to protease results in cleaving of casein which changes the frequency of the 1st–11th odd harmonics of QCM. Monitoring β-casein cleavage allows ~0.2 nM detection of trypsin and ~0.5 nM detection of plasmin and enables differentiation between trypsin and plasmin after <2 min of protease exposure. The casein-coated QCM allows sub-nanomolar detection and classification of protease.

Authors:
 [1];  [2];  [1]; ORCiD logo [2]; ORCiD logo [2];  [1]; ORCiD logo [2]
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  1. Comenius Univ., Bratislava (Slovakia)
  2. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Basic Energy Sciences (BES)
OSTI Identifier:
1482462
Alternate Identifier(s):
OSTI ID: 1591683
Grant/Contract Number:  
AC05-00OR22725
Resource Type:
Accepted Manuscript
Journal Name:
Sensors and Actuators. B, Chemical
Additional Journal Information:
Journal Volume: 272; Journal Issue: C; Journal ID: ISSN 0925-4005
Publisher:
Elsevier
Country of Publication:
United States
Language:
English
Subject:
47 OTHER INSTRUMENTATION; Casein; Plasmin; Trypsin; Protease; QCM; Biosensor; Machine learning

Citation Formats

Tatarko, Marek, Muckley, Eric S., Subjakova, Veronika, Goswami, Monojoy, Sumpter, Bobby G., Hianik, Tibor, and Ivanov, Ilia N. Machine learning enabled acoustic detection of sub-nanomolar concentration of trypsin and plasmin in solution. United States: N. p., 2018. Web. doi:10.1016/j.snb.2018.05.100.
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Tatarko, Marek, Muckley, Eric S., Subjakova, Veronika, Goswami, Monojoy, Sumpter, Bobby G., Hianik, Tibor, & Ivanov, Ilia N. Machine learning enabled acoustic detection of sub-nanomolar concentration of trypsin and plasmin in solution. United States. doi:https://doi.org/10.1016/j.snb.2018.05.100
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Tatarko, Marek, Muckley, Eric S., Subjakova, Veronika, Goswami, Monojoy, Sumpter, Bobby G., Hianik, Tibor, and Ivanov, Ilia N. Sat . "Machine learning enabled acoustic detection of sub-nanomolar concentration of trypsin and plasmin in solution". United States. doi:https://doi.org/10.1016/j.snb.2018.05.100. https://www.osti.gov/servlets/purl/1482462.
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@article{osti_1482462,
title = {Machine learning enabled acoustic detection of sub-nanomolar concentration of trypsin and plasmin in solution},
author = {Tatarko, Marek and Muckley, Eric S. and Subjakova, Veronika and Goswami, Monojoy and Sumpter, Bobby G. and Hianik, Tibor and Ivanov, Ilia N.},
abstractNote = {Here, we demonstrate a machine learning enabled low-cost acoustic detection of protease which may find application in assuring quality and safety of dairy products, drug screening, molecular profiling, and disease diagnostics. A hydrophilic SiO2-coated quartz crystal microbalance (QCM) acts as a substrate to assemble α-, β-, and κ-casein layers (protease reporters) and as a transducer for measuring changes in frequency as casein is removed by protease. We demonstrate that α-, β-, and κ-caseins can form stable assembly on SiO2 from phosphate-buffered solution (PBS) solution. Exposure to protease results in cleaving of casein which changes the frequency of the 1st–11th odd harmonics of QCM. Monitoring β-casein cleavage allows ~0.2 nM detection of trypsin and ~0.5 nM detection of plasmin and enables differentiation between trypsin and plasmin after <2 min of protease exposure. The casein-coated QCM allows sub-nanomolar detection and classification of protease.},
doi = {10.1016/j.snb.2018.05.100},
journal = {Sensors and Actuators. B, Chemical},
number = C,
volume = 272,
place = {United States},
year = {2018},
month = {5}
}
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Journal Article:
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Publisher's Version of Record
DOI:  https://doi.org/10.1016/j.snb.2018.05.100
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Cited by: 2 works
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Figures / Tables:

Fig. 1 Fig. 1: Kinetics of casein adsorption and removal from SiO⁠2, as measured by frequency shift ($Δ$f) of 1st–11th odd harmonics of the QCM. Exposure and removal of $α$-casein (left panel), $β$-casein (middle panel), and κ-casein (right panel) are marked by the first and second vertical dashed lines respectively.
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Works referencing / citing this record:

Machine Learning‐Enabled Correlation and Modeling of Multimodal Response of Thin Film to Environment on Macro and Nanoscale Using “Lab‐on‐a‐Crystal”
journal, January 2020

  • Muckley, Eric S.; Collins, Liam; Srijanto, Bernadeta R.
  • Advanced Functional Materials, Vol. 30, Issue 10
  • DOI: 10.1002/adfm.201908010
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    Figures / Tables found in this record:

    Fig. 1 (p. 3)figure
    Fig. 2 (p. 4)figure
    Fig. 3 (p. 4)figure
    Fig. 4 (p. 6)figure
    Fig. 5 (p. 6)figure
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