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

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.

Growth Kinetics Monitoring of Gram-Negative Pathogenic Microbes Using Raman Spectroscopy.

Optical density based measurements are routinely performed to monitor the growth of microbes. These measurements solely depend upon the number of cells and do not provide any information about the changes in the biochemical milieu or biological status. An objective information about these parameters is essential for evaluation of novel therapies and for maximizing the metabolite production. In the present study, we have applied Raman spectroscopy to monitor growth kinetics of three different pathogenic Gram-negative microbes Escherichia coli, Pseudomonas aeruginosa, and Acinetobacter baumannii. Spectral measurements were performed under 532 nm excitation with 5 seconds of exposure time. Spectral features suggest temporal changes in the "peptide" and "nucleic acid" content of cells under different growth stages. Using principal component analysis (PCA), successful discrimination between growth phases was also achieved. Overall, the findings are supportive of the prospective adoption of Raman based approaches for monitoring microbial growth.

Unique spectral markers discern recurrent Glioblastoma cells from heterogeneous parent population.

An inability to discern resistant cells from bulk tumour cell population contributes to poor prognosis in Glioblastoma. Here, we compared parent and recurrent cells generated from patient derived primary cultures and cell lines to identify their unique molecular hallmarks. Although morphologically similar, parent and recurrent cells from different samples showed variable biological properties like proliferation and radiation resistance. However, total RNA-sequencing revealed transcriptional landscape unique to parent and recurrent populations. These data suggest that global molecular differences but not individual biological phenotype could differentiate parent and recurrent cells. We demonstrate that Raman Spectroscopy a label-free, non-invasive technique, yields global information about biochemical milieu of recurrent and parent cells thus, classifying them into distinct clusters based on Principal-Component-Analysis and Principal-Component-Linear-Discriminant-Analysis. Additionally, higher lipid related spectral peaks were observed in recurrent population. Importantly, Raman spectroscopic analysis could further classify an independent set of naïve primary glioblastoma tumour tissues into non-responder and responder groups. Interestingly, spectral features from the non-responder patient samples show a considerable overlap with the in-vitro generated recurrent cells suggesting their similar biological behaviour. This feasibility study necessitates analysis of a larger cohort of naïve primary glioblastoma samples to fully envisage clinical utility of Raman spectroscopy in predicting therapeutic response.

Raman mapping of oral buccal mucosa: a spectral histopathology approach.

Oral cancer is one of the most common cancers worldwide. One-fifth of the world's oral cancer subjects are from India and other South Asian countries. The present Raman mapping study was carried out to understand biochemical variations in normal and malignant oral buccal mucosa. Data were acquired using WITec alpha 300R instrument from 10 normal and 10 tumors unstained tissue sections. Raman maps of normal sections could resolve the layers of epithelium, i.e. basal, intermediate, and superficial. Inflammatory, tumor, and stromal regions are distinctly depicted on Raman maps of tumor sections. Mean and difference spectra of basal and inflammatory cells suggest abundance of DNA and carotenoids features. Strong cytochrome bands are observed in intermediate layers of normal and stromal regions of tumor. Epithelium and stromal regions of normal cells are classified by principal component analysis. Classification among cellular components of normal and tumor sections is also observed. Thus, the findings of the study further support the applicability of Raman mapping for providing molecular level insights in normal and malignant conditions.