ArticleScientific reports2017
Metabolic fingerprinting of bacteria by fluorescence lifetime imaging microscopy.
Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
23 citing papers in PubMed.
- Real-time, high-resolution metabolic characterization of live bacteria using label-free optical metabolic imaging.NPJ biofilms and microbiomes · 2026Article
- Phasor-based FLIM analysis of NAD(P)H and FAD autofluorescence for label-free bacterial classification.Journal of biomedical optics · 2026Article
- New Application for the Early Detection of Wound Infections Using a Near-Infrared Fluorescence Device and Forward-Looking Thermal Camera.Diagnostics (Basel, Switzerland) · 2025Article
- Fluorescence Lifetime Imaging Detects Long-Lifetime Signal Associated with Reduced Pyocyanin at the Surface ofACS infectious diseases · 2025Article
- Label-free metabolic imaging ofFrontiers in cellular and infection microbiology · 2025Article
- Antibacterial activity and mechanisms of α-terpineol against foodborne pathogenic bacteria.Applied microbiology and biotechnology · 2023Article
- Probing organoid metabolism using fluorescence lifetime imaging microscopy (FLIM): The next frontier of drug discovery and disease understanding.Advanced drug delivery reviews · 2023Review
- Formation and emergent dynamics of spatially organized microbial systems.Interface focus · 2023Review
- Comprehensive Investigation of Parameters Influencing Fluorescence Lifetime Imaging Microscopy in Frequency- and Time-Domain Illustrated by Phasor Plot Analysis.International journal of molecular sciences · 2022Article
- Rapid species identification of pathogenic bacteria from a minute quantity exploiting three-dimensional quantitative phase imaging and artificial neural network.Light, science & applications · 2022Article
- Use of Flavin-Related Cellular Autofluorescence to Monitor Processes in Microbial Biotechnology.Microorganisms · 2022Article
- Fluorescence Lifetime Imaging Microscopy of Porphyrins inPharmaceutics · 2021Article
- Article
- Roadmap on emerging concepts in the physical biology of bacterial biofilms: from surface sensing to community formation.Physical biology · 2021Review
- Zinc limitation triggers anticipatory adaptations in Mycobacterium tuberculosis.PLoS pathogens · 2021Article
- FLIM data analysis based on Laguerre polynomial decomposition and machine-learning.Journal of biomedical optics · 2021Article
- Microglia activation visualization via fluorescence lifetime imaging microscopy of intrinsically fluorescent metabolic cofactors.Neurophotonics · 2020Article
- Quantitative High-Resolution Imaging of Live Microbial Cells at High Hydrostatic Pressure.Biophysical journal · 2020Article
- A Shift in Central Metabolism Accompanies Virulence Activation in Pseudomonas aeruginosa.mBio · 2020Article
- Machine Learning Methods for Fluorescence Lifetime Imaging (FLIM) Based Label-Free Detection of Microglia.Frontiers in neuroscience · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.