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. 2022 Sep 11;12(9):749.
doi: 10.3390/bios12090749.

Unraveling the Secrets of Colistin Resistance with Label-Free Raman Spectroscopy

Dimple Saikia  1 , Priyanka Jadhav  2   3 , Arti R Hole  2 , Chilakapati Murali Krishna  2   3 , Surya P Singh  1
Affiliations

Unraveling the Secrets of Colistin Resistance with Label-Free Raman Spectroscopy

Dimple Saikia et al. Biosensors (Basel). .

Abstract

The rise in number of infections from multidrug-resistant (MDR) Gram-negative microbes has led to an increase in the use of a variety of 'polymyxins' such as colistin. Even though colistin is known to cause minor nephro- and neuro-toxicity, it is still considered as last resort antibiotic for treating MDR infections. In this study, we have applied Raman spectroscopy to understand the differences among colistin sensitive and resistant bacterial strains at community level. We have successfully generated colistin resistant clones and verified the presence of resistance-causing MCR-1 plasmid. A unique spectral profile associated with specific drug concentration has been obtained. Successful delineation between resistant and sensitive cells has also been achieved via principal component analysis. Overall findings support the prospective utility of Raman spectroscopy in identifying anti-microbial resistance.

Keywords: Raman spectroscopy; antimicrobial resistance; colistin; microbiology; principal component analysis.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
MCR-1 transformed strains with different concentration of colistin (3.9, 5.0, 6.5, and 7.8 µg/mL).
Figure 2
Figure 2
(A) Agarose gel image showing the presence of the MCR-1 plasmid in resistant strains (~5081 bp) (B) Rapid polymyxin NP test based identification of colistin sensitive and resistant strains.
Figure 3
Figure 3
Growth pattern comparing sensitive and resistant strains.
Figure 4
Figure 4
Average Raman spectra from colistin sensitive and resistant bacterial cells collected from the log phase. The shaded area represents the standard deviation. Characteristic spectral bands are marked with an arrow.
Figure 5
Figure 5
(A) PCA-scatter plot between sensitive and cells resistant to colistin concentration of 3.9 and 5 µg/mL (B) Loading plot of PC1- and PC4 used for classification. (C) PCA-scatter plot between sensitive and cells resistant to colistin concentration of 6.5 and 7.8 µg/mL (D) Loading plot of PC1- and PC2 used for classification.
Figure 6
Figure 6
Morphological changes associated with induction of colistin resistance (3.9, 5.0, 6.5, and 7.8 ug/mL) analyzed using FESM.
See this image and copyright information in PMC

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