NAD+observational2020

Autofluorescence lifetime imaging of cellular metabolism: Sensitivity toward cell density, pH, intracellular, and intercellular heterogeneity.

Cytometry. Part A : the journal of the International Society for Analytical Cytology

confidence

Key findings

Review of autofluorescence lifetime imaging (FLIM) for NADH/FAD metabolism; no clinical or biological endpoints reported.

View source on PubMed (PMID 30296355) ↗

Sample size
Not reported
Population
Cellular samples (in vitro)
Dosing
Not reported
Duration
Not reported
Route
Not reported
Blinding
not_reported
Controls
none
Drug class
coenzyme
Full abstract

Autofluorescence imaging (AFI) has greatly accelerated in the last decade, way past its origins in detecting endogenous signals in biological tissues to identify differences between samples. There are many endogenous fluorescence sources of contrast but the most robust and widely utilized have been those associated with metabolism. The intrinsically fluorescent metabolic cofactors nicotinamide adenine dinucleotide (NAD+ /NADH) and flavin adenine dinucleotide (FAD/FADH2 ) have been utilized in a number of AFI applications including basic research, clinical, and pharmaceutical studies. Fluorescence lifetime imaging microscopy (FLIM) has emerged as one of the more powerful AFI tools for NADH and FAD characterization due to its unique ability to noninvasively detect metabolite bound and free states and quantitate cellular redox ratio. However, despite this widespread biological use, many standardization methods are still needed to extend FLIM-based AFI into a fully robust research and clinical diagnostic tools. FLIM is sensitive to a wide range of factors in the fluorophore microenvironment, and there are a number of analysis variables as well. To this end, there has been an emphasis on developing imaging standards and ways to make the image acquisition and analysis more consistent. However, biological conditions during FLIM-based AFI imaging are rarely considered as key sources of FLIM variability. Here, we present several experimental factors with supporting data of the cellular microenvironment such as confluency, pH, inter-/intracellular heterogeneity, and choice of cell line that need to be considered for accurate quantitative FLIM-based AFI measurement of cellular metabolism. © 2018 International Society for Advancement of Cytometry.

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