2021
DOI: 10.1002/jrs.6204
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Raman spectroscopy in cell biology and microbiology

Abstract: The Raman spectrum of living cells and microorganisms contains highly specific fingerprint‐like signatures, useful in unequivocally identifying different species and interpreting physiological and metabolic responses to environmental stressors. In situ Raman imaging with dedicated highly sensitive instruments can translate selected spectroscopic fingerprints into vivid snapshots of molecular species or specific physiological reactions. Time‐lapse experiments, crucial in characterizing growth‐dependent phenomen… Show more

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Cited by 111 publications
(101 citation statements)
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References 453 publications
(699 reference statements)
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“…The spectroscopic characteristics obtained on average spectra for both clades/treatments were then subjected to confirmation by means of further characterizations based on Raman mapping and imaging, according to protocols described in previous works (Pezzotti, 2021 ; Pezzotti et al, 2021 ).…”
Section: Resultsmentioning
confidence: 99%
“…The spectroscopic characteristics obtained on average spectra for both clades/treatments were then subjected to confirmation by means of further characterizations based on Raman mapping and imaging, according to protocols described in previous works (Pezzotti, 2021 ; Pezzotti et al, 2021 ).…”
Section: Resultsmentioning
confidence: 99%
“…This study is in line with our previous studies of variants of Influenza virus. [ 39 ] The Raman characteristics yield molecular‐scale information uniquely discriminating among different variants. Facilitating real‐time data access and exchange is an essential step in tracking variants and in estimating their spread and evolutionary mutation rate.…”
Section: Discussionmentioning
confidence: 99%
“…The computational work produced two important outcomes: (a) spectra could be screened automatically and an appropriate deconvolution could be suggested through finding the closest match with the experimentally collected spectrum through eq 1 , while additionally identifying the molecules/compounds primarily contributing to each sub-band, and (b) sub-bands having primarily single-reference-molecule sourced signal intensity (>90%) could be isolated. A number of reference spectra from basic molecules used in the above-described machine learning algorithm could be found in ref ( 112 ).…”
Section: Methodsmentioning
confidence: 99%