期刊
ENVIRONMENTAL SCIENCE & TECHNOLOGY
卷 55, 期 13, 页码 9119-9128出版社
AMER CHEMICAL SOC
DOI: 10.1021/acs.est.1c02552
关键词
surface-enhanced Raman spectroscopy; detection; metabolite; bacteria; virus
资金
- US National Science Foundation [OISE-1545756, CBET-2029911]
- NSF [1542100]
- Sustainable Nanotechnology Interdisciplinary Graduate Program (VTSuN IGEP) - Virginia Tech Graduate School
This study utilized surface-enhanced Raman spectroscopy (SERS) to detect bacterial metabolites for bacterial growth quantification and viral infection diagnosis. The time-dependent SERS signal of volatile metabolite and nonvolatile metabolites were detected in bacterial cultures. Multivariate analysis allowed for detection of viral infection with a prediction accuracy of 93% using SERS-based approach.
Bacterial metabolites are intermediate products of bacterial metabolism and their production reflects metabolic activity. Herein, we report the use of surface-enhanced Raman spectroscopy (SERS) for detection of both volatile and nonvolatile metabolites and the application of this approach for bacterial growth quantification and diagnosis of viral infection. The time-dependent SERS signal of the volatile metabolite dimethyl disulfide in the headspace above bacteria growing on an agar plate was detected and quantified. In addition, SERS signals arising from the plate reflected nutrient consumption and production of nonvolatile metabolites. The measurement of metabolite accumulation can be used for bacterial quantification. In the presence of bacteriophage virus, bacterial metabolism is suppressed, and the relative decrease in SERS intensity reflects the initial virus concentration. Using multivariate analysis, we detect viral infection with a prediction accuracy of 93%. Our SERS-based approach for metabolite production monitoring provides new insights toward viral infection diagnosis.
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