4.7 Article

A universal automated method for determining the bacteriostatic activity of nanomaterials

Journal

JOURNAL OF HAZARDOUS MATERIALS
Volume 413, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.jhazmat.2021.125320

Keywords

Multi-channel contactless conductometric sensor; Bacterial growth; Nanomaterials; Phenotypic antibiotic susceptibility testing; Universal method

Funding

  1. Key Project of the Natural Science Foundation of Shandong Province, China [ZR2020KB021]
  2. National Research and Development Program of China [2019YFD0900505, 2017YFE1015200]

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The researchers developed an automated method based on a sensor to monitor the growth kinetics of E. coli and S. aureus in different media, enabling direct determination of minimum inhibitory concentrations of nanomaterials against bacteria. This method is highlighted for its universality, simplicity, and affordability, offering possibilities for a powerful analytical platform in nanoscience research, particularly in assessing the ecotoxicity of nanomaterials.
The lack of analytical strategies to directly determine the bacteriostatic activity of nanomaterials in complex aqueous media (e.g., environmentally relevant scenarios) seriously hampers the harvest of reliable data for nanomaterial risk assessment. Here, we created an automated phenotypic method based on a developed multi-channel contactless conductometric sensor. Bacterial growth kinetics of E. coli and S. aureus were determined via on-line monitoring of conductivity changes in simple media (e.g., liquid LB broth) and complex media (e.g., relevant river water and seawater samples with diverse pH, salinity, conductivity, turbidity, chemical oxygen demand and total suspended solids). The high temporal resolution growth curves provide detailed information on the bacteria inhibition of the model nanomaterial - Au nanospheres, Au nanorods, Ag nanospheres and Ag nanocubes - at each growth stage, thus enabling users to directly obtain minimum inhibitory concentrations. The method highlights the advantages of universality, simplicity and affordability. It opens up possibilities for the development of a powerful analytical platform for researches in the field of nanoscience, e.g. to assess ecotoxicity of nanomaterials.

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