Metabolic fingerprinting of bacteria by fluorescence lifetime imaging microscopy

Abstract Bacterial populations exhibit a range of metabolic states influenced by their environment, intra- and interspecies interactions. The identification of bacterial metabolic states and transitions between them in their native environment promises to elucidate community behavior and stochastic...

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Main Authors: Arunima Bhattacharjee, Rupsa Datta, Enrico Gratton, Allon I. Hochbaum
Format: Article
Language:English
Published: Nature Publishing Group 2017-06-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-017-04032-w
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spelling doaj-087a549f5bbe4ca3b0cb8e42508fc0c62020-12-08T03:14:40ZengNature Publishing GroupScientific Reports2045-23222017-06-017111010.1038/s41598-017-04032-wMetabolic fingerprinting of bacteria by fluorescence lifetime imaging microscopyArunima Bhattacharjee0Rupsa Datta1Enrico Gratton2Allon I. Hochbaum3Department of Chemical Engineering and Materials Science, University of California, IrvineLaboratory for Fluorescence Dynamics, Department of Biomedical Engineering, University of California, IrvineLaboratory for Fluorescence Dynamics, Department of Biomedical Engineering, University of California, IrvineDepartment of Chemical Engineering and Materials Science, University of California, IrvineAbstract Bacterial populations exhibit a range of metabolic states influenced by their environment, intra- and interspecies interactions. The identification of bacterial metabolic states and transitions between them in their native environment promises to elucidate community behavior and stochastic processes, such as antibiotic resistance acquisition. In this work, we employ two-photon fluorescence lifetime imaging microscopy (FLIM) to create a metabolic fingerprint of individual bacteria and populations. FLIM of autofluorescent reduced nicotinamide adenine dinucleotide (phosphate), NAD(P)H, has been previously exploited for label-free metabolic imaging of mammalian cells. However, NAD(P)H FLIM has not been established as a metabolic proxy in bacteria. Applying the phasor approach, we create FLIM-phasor maps of Escherichia coli, Salmonella enterica serovar Typhimurium, Pseudomonas aeruginosa, Bacillus subtilis, and Staphylococcus epidermidis at the single cell and population levels. The bacterial phasor is sensitive to environmental conditions such as antibiotic exposure and growth phase, suggesting that observed shifts in the phasor are representative of metabolic changes within the cells. The FLIM-phasor approach represents a powerful, non-invasive imaging technique to study bacterial metabolism in situ and could provide unique insights into bacterial community behavior, pathology and antibiotic resistance with sub-cellular resolution.https://doi.org/10.1038/s41598-017-04032-w
collection DOAJ
language English
format Article
sources DOAJ
author Arunima Bhattacharjee
Rupsa Datta
Enrico Gratton
Allon I. Hochbaum
spellingShingle Arunima Bhattacharjee
Rupsa Datta
Enrico Gratton
Allon I. Hochbaum
Metabolic fingerprinting of bacteria by fluorescence lifetime imaging microscopy
Scientific Reports
author_facet Arunima Bhattacharjee
Rupsa Datta
Enrico Gratton
Allon I. Hochbaum
author_sort Arunima Bhattacharjee
title Metabolic fingerprinting of bacteria by fluorescence lifetime imaging microscopy
title_short Metabolic fingerprinting of bacteria by fluorescence lifetime imaging microscopy
title_full Metabolic fingerprinting of bacteria by fluorescence lifetime imaging microscopy
title_fullStr Metabolic fingerprinting of bacteria by fluorescence lifetime imaging microscopy
title_full_unstemmed Metabolic fingerprinting of bacteria by fluorescence lifetime imaging microscopy
title_sort metabolic fingerprinting of bacteria by fluorescence lifetime imaging microscopy
publisher Nature Publishing Group
series Scientific Reports
issn 2045-2322
publishDate 2017-06-01
description Abstract Bacterial populations exhibit a range of metabolic states influenced by their environment, intra- and interspecies interactions. The identification of bacterial metabolic states and transitions between them in their native environment promises to elucidate community behavior and stochastic processes, such as antibiotic resistance acquisition. In this work, we employ two-photon fluorescence lifetime imaging microscopy (FLIM) to create a metabolic fingerprint of individual bacteria and populations. FLIM of autofluorescent reduced nicotinamide adenine dinucleotide (phosphate), NAD(P)H, has been previously exploited for label-free metabolic imaging of mammalian cells. However, NAD(P)H FLIM has not been established as a metabolic proxy in bacteria. Applying the phasor approach, we create FLIM-phasor maps of Escherichia coli, Salmonella enterica serovar Typhimurium, Pseudomonas aeruginosa, Bacillus subtilis, and Staphylococcus epidermidis at the single cell and population levels. The bacterial phasor is sensitive to environmental conditions such as antibiotic exposure and growth phase, suggesting that observed shifts in the phasor are representative of metabolic changes within the cells. The FLIM-phasor approach represents a powerful, non-invasive imaging technique to study bacterial metabolism in situ and could provide unique insights into bacterial community behavior, pathology and antibiotic resistance with sub-cellular resolution.
url https://doi.org/10.1038/s41598-017-04032-w
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AT allonihochbaum metabolicfingerprintingofbacteriabyfluorescencelifetimeimagingmicroscopy
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