Infrared Spectroscopy Coupled with a Dispersion Model for Quantifying the Real-Time Dynamics of Kanamycin Resistance in Artificial Microbiota

Overusage of antibiotics leads to the widespread induction of antibiotic-resistance genes (ARGs). Developing an approach to allow real-time monitoring and fast prediction of ARGs dynamics in clinical or environmental samples has become an urgent matter. Vibrational spectroscopy is potentially an ideal technique for the characterization of the microbial composition of microbiota as it is nondestructive, high-throughput, and label-free. The present study included two strains without kanamycin-resistant-gene,<i> Mycobacterium vanbaalenii </i>PYR-1 (Myco) and<i> Escherichia coli </i>DH5α (<i>E.coli</i>), and one kanamycin-resistant strain <i>Acinetobacter baylyi</i> ADPWH_recA (ADP). The three control groups contained pure <i>M. vanbaalenii </i>PYR-1, <i>E. coli </i>DH5α and <i>A. baylyi</i> ADPWH_recA, respectively. The artificial microbiotas were prepared for both static (M1 to M5) and dynamic (M1 and M2) experiments by gently mixing the cells in the compositions. The <i>A. baylyi</i> ADPWH_recA ratios in static (M1 to M5) and dynamic (M1, M2) were 10%, 25%, 50%, 75%, 90% and 20%, 50% respectively. The tested exposure time points were 0, 4, 8, 12, 24hrs. This file contains raw and preprocessed data from the static and dynamic experiments. Raw spectra were preprocessed to correct problems associated with data acquisition and further multivariate approaches were applied to study the respective datasets. The preprocessing of the raw spectra was performed within MATLAB software, using an in-house-developed IRootLab toolbox (http://trevisanj.github.io/irootlab/). <br>