Hyperspectral Chemical Imaging of Single Bacterial Cell Structure by Raman Spectroscopy and Machine Learning

Giulia Barzan,Chiara Portesi,Alessio Sacco,Andrea Mario Rossi,Andrea Mario Giovannozzi,Luisa Mandrile

doi:10.3390/app11083409

Abstract

In this work, biomolecules, such as membrane proteins, lipids, and DNA, were identified and their spatial distribution was mapped within a single Escherichia coli cell by Raman hyperspectral imaging. Raman spectroscopy allows direct, nondestructive, rapid, and cost-effective analysis of biological samples, minimizing the sample preparation and without the need of chemical label or immunological staining. Firstly, a comparison between an air-dried and a freeze-dried cell was made, and the principal vibrational modes associated to the membrane and nucleic acids were identified by the bacterium’s Raman chemical fingerprint. Then, analyzing the Raman hyperspectral images by multivariate statistical analysis, the bacterium biological status was investigated at a subcellular level. Principal components analysis (PCA) was applied for dimensionality reduction of the spectral data, then spectral unmixing was performed by multivariate curve resolution–alternating least squares (MCR-ALS). Thanks to multivariate data analysis, the DNA segregation and the Z-ring formation of a replicating bacterial cell were detected at a sub-micrometer level, opening the way to real-time molecular analysis that could be easily applied on in vivo or ex vivo biological samples, avoiding long preparation and analysis process.

Highlights

Vibrational spectroscopy offers the opportunity for revolutionary innovation in the life sciences and shows high potential as a rapid, culture-independent, cost-effective, and label-free technique for the characterization of biological samples, compared to conventional time-consuming methods, such as microbiological and molecular techniques, which usually require expensive equipment, highly trained staff, and complicated sample preparation [1,2]
We investigated the cell status of a single E. coli cell, which was collected in its mid-exponential growth phase to explore the possibility of identifying different phases of the cell replication cycle thanks to the high resolution and molecular specificity offered by
2A(φ))ofE.biocomponents coli sample of an E. coli ATCC 8739 cell Raman imaging was performed on a randomly selected bacterial cell found in were compared to determine the different distribution of biological components, as isolated capa drop of E.imaging, coli within a concentration of 1 ×cells

Summary

Introduction

Vibrational spectroscopy offers the opportunity for revolutionary innovation in the life sciences and shows high potential as a rapid, culture-independent, cost-effective, and label-free technique for the characterization of biological samples, compared to conventional time-consuming methods, such as microbiological and molecular techniques, which usually require expensive equipment, highly trained staff, and complicated sample preparation [1,2]. Unlike infrared spectroscopy (FT-IR) [3], Raman spectroscopy is more suited for biological investigations because it allows real-time analysis of living samples in their natural environmental conditions [4], either dispersed in aqueous media or deposited on commercial microscope glass slides. Spectroscopic technology can generate an enormous amount of data in a short time, and due to the complexity of biological samples, Raman spectra raises several interpretation difficulties To overcome this issue , disciplines such as image processing, statistical analysis, chemometrics, machine learning, and computational intelligence techniques are needed [12,13]

Methods

Results

Conclusion