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3D Nanodevice Detects Harmful Bacteria in Blood

By HospiMedica International staff writers
Posted on 09 Apr 2020
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Image: 3D nanodevice detects harmful bacteria in blood (Photo courtesy of RIT)
Image: 3D nanodevice detects harmful bacteria in blood (Photo courtesy of RIT)
A new study describes how a nanofluidic three-dimensional (3D) device stacked with magnetic beads can trap, concentrate, and retrieve E. coli from blood and plasma.

Developed at Rutgers University (Rutgers; Piscataway, NJ, USA), Tsinghua-UC Berkeley Shenzhen Institute (TBSI; China), the Rochester Institute of Technology (RIT; NY, USA), and other institutions, the inexpensive, transparent device is based on stacking magnetic beads with different sizes in order to create microscopic voids that can physically isolate bacteria. The sizes and ratio of the beads was calculated using computational fluid dynamics, 3D tomography technology, and machine learning, achieving a 86% capture efficiency with a flow rate of 50 μL/min.

By leveraging the high deformability of the device, E. coli samples can be retrieved from a bacterial suspension by applying a higher flow rate, followed by rapid magnetic separation. An on-chip 11-fold concentration factor can be achieved by inputting 1300 μL of the E. coli sample, and then concentrating it in 100 μL of buffer. The multiplexed, miniaturized, see-through device is easy to fabricate and operate, making it ideal for pathogen separation in both laboratory and in point-of-care (POC) settings. The study was published on January 15, 2020, in ACS Applied Materials & Interfaces.

“Drug-resistant bacteria have become a severe public health concern. Fortunately, this risk can be reduced via the correct use of prescriptions, and by avoiding unnecessary prescriptions, and over prescription of antibiotics,” concluded lead author Xinye Cen, PhD, of RIT, and colleagues. “In this regard, rapid isolation of the target bacteria from various samples is an essential step toward the identification of antibiotic resistance and providing early-treatment.”

Related Links:
Rutgers University
Tsinghua-UC Berkeley Shenzhen Institute
Rochester Institute of Technology

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