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Quantitative assessment of automated purification and concentration of E. coli bacteria.
Fraticelli Guzmán, Nina Sara; Badawy, Mohamed W; Stockslager, Max A; Farrell, Michael L; van Zyl, Caitlin; Stewart, Seth; Hu, David L; Forest, Craig R.
Affiliation
  • Fraticelli Guzmán NS; George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA, United States.
  • Badawy MW; George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA, United States.
  • Stockslager MA; George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA, United States.
  • Farrell ML; Georgia Tech Research Institute, Georgia Institute of Technology, Atlanta, GA, United States.
  • van Zyl C; Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA.
  • Stewart S; George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA, United States.
  • Hu DL; George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA, United States; School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA.
  • Forest CR; George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA, United States; Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA. Electronic address: cforest@gatech.edu.
SLAS Technol ; 28(4): 251-257, 2023 08.
Article de En | MEDLINE | ID: mdl-36804174
ABSTRACT
Automated methods for rapidly purifying and concentrating bacteria from environmental interferents are needed in next-generation applications for anything from water purification to biological weapons detection. Though previous work has been performed by other researchers in this area, there is still a need to create an automated system that can both purify and concentrate target pathogens in a timely manner with readily available and replaceable components that could be easily integrated with a detection mechanism. Thus, the objective of this work was to design, build, and demonstrate the effectiveness of an automated system, the Automated Dual-filter method for Applied Recovery, or aDARE. aDARE uses a custom LABVIEW program that guides the flow of bacterial samples through a pair of size-based separation membranes to capture and elute the target bacteria. Using aDARE, we eliminated 95% of the interfering beads of a 5 mL-sample volume containing 107 CFU/mL of E. coli contaminated with 2 µm and 10 µm polystyrene beads at 106 beads/mL concentration., The target bacteria were concentrated to more than twice the initial concentration in 900 µL of eluent, resulting in an enrichment ratio for the target bacteria of 42 ± 13 in 5.5 min. These results show the feasibility and effectiveness of using size-based filtration membranes to purify and concentrate a target bacterium, in this case E. coli, in an automated system.
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Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Sujet principal: Bactéries / Escherichia coli Langue: En Journal: SLAS Technol Année: 2023 Type de document: Article Pays d'affiliation: États-Unis d'Amérique

Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Sujet principal: Bactéries / Escherichia coli Langue: En Journal: SLAS Technol Année: 2023 Type de document: Article Pays d'affiliation: États-Unis d'Amérique