Timing and operating mode design for time-gated fluorescence lifetime imaging microscopy

Protein aggregation monitoring in cells under oxidative stress: a novel fluorescent probe based on a 7-azaindole-BODIPY derivative

The development of new fluorescent probes as molecular sensors is a critical step for the understanding of molecular mechanisms. BODIPY-based probes offer versatility due to their high fluorescence quantum yields, photostability, and tunable absorption/emission wavelengths. Here, we report the synthesis and evaluation of a novel 7-azaindole-BODIPY derivative to probe hydrophobic proteins as well as protein misfolding and aggregation. In organic solvents, this compound shows two efficiently interconverting emissive excited states. In aqueous environments, it forms molecular aggregates with unique photophysical properties. The complex photophysics of the 7-azaindole-BODIPY derivative was explored for sensing applications. In the presence of albumin, the compound is stabilized in hydrophobic protein regions, significantly increasing its fluorescence emission intensity and lifetime. Similar effects occur in the presence of protein aggregates but not with other macromolecules like pepsin, DNA, Ficoll 40, and coconut oil. Fluorescence lifetime imaging microscopy (FLIM) and two-photon fluorescence microscopy on breast (MCF-7) and lung (A549) cancer cells incubated with this compound display longer fluorescence lifetimes and higher emission intensity under oxidative stress. Synchrotron FTIR micro spectroscopy confirmed that the photophysical changes observed were due to protein misfolding and aggregation caused by the oxidative stress. These findings demonstrate that this compound can serve as a fluorescent probe to monitor protein misfolding and aggregation triggered by oxidative stress.

A Novel Fit-Flexible Fluorescence Soft Imager: Tri-Sensing of Intensity, Fall-Time, and Life Profile

Time-resolved fluorescence imaging techniques, like confocal fluorescence lifetime imaging microscopy, are powerful photonic instrumentation tools of modern science with diverse applications, including: biology, medicine, and chemistry. However, complexities of the systems, both at specimen and device levels, cause difficulties in quantifying soft biomarkers. To address the problems, we first aim to understand and model the underlying photophysics of fluorescence decay curves. For this purpose, we provide a set of mathematical functions, called "life models", fittable with the real temporal recordings of histogram of photon counts. For each model, an equivalent electrical circuit, called a "life circuit", is derived for explaining the whole process. In confocal endomicroscopy, the components of excitation laser, specimen, and fluorescence-emission signal as the histogram of photon counts are modelled by a power source, network of resistor-inductor-capacitor circuitry, and multimetre, respectively. We then design a novel pixel-level temporal classification algorithm, called a "fit-flexible approach", where qualities of "intensity", "fall-time", and "life profile" are identified for each point. A model selection mechanism is used at each pixel to flexibly choose the best representative life model based on a proposed Misfit-percent metric. A two-dimensional arrangement of the quantified information detects some kind of structural information. This approach showed a potential of separating microbeads from lung tissue, distinguishing the tri-sensing from conventional methods. We alleviated by 7% the error of the Misfit-percent for recovering the histograms on real samples than the best state-of-the-art competitor. Codes are available online.

Applications of machine learning in time-domain fluorescence lifetime imaging: a review

Many medical imaging modalities have benefited from recent advances in Machine Learning (ML), specifically in deep learning, such as neural networks. Computers can be trained to investigate and enhance medical imaging methods without using valuable human resources. In recent years, Fluorescence Lifetime Imaging (FLIm) has received increasing attention from the ML community. FLIm goes beyond conventional spectral imaging, providing additional lifetime information, and could lead to optical histopathology supporting real-time diagnostics. However, most current studies do not use the full potential of machine/deep learning models. As a developing image modality, FLIm data are not easily obtainable, which, coupled with an absence of standardisation, is pushing back the research to develop models which could advance automated diagnosis and help promote FLIm. In this paper, we describe recent developments that improve FLIm image quality, specifically time-domain systems, and we summarise sensing, signal-to-noise analysis and the advances in registration and low-level tracking. We review the two main applications of ML for FLIm: lifetime estimation and image analysis through classification and segmentation. We suggest a course of action to improve the quality of ML studies applied to FLIm. Our final goal is to promote FLIm and attract more ML practitioners to explore the potential of lifetime imaging.

Computational Photon Counting Using Multithreshold Peak Detection for Fast Fluorescence Lifetime Imaging Microscopy

Time-resolved photon counting methods have a finite bandwidth that restricts the acquisition speed of techniques like fluorescence lifetime imaging microscopy (FLIM). To enable faster imaging, computational methods can be employed to count photons when the output of a detector is directly digitized at a high sampling rate. Here, we present computational photon counting using a hybrid photodetector in conjunction with multithreshold peak detection to count instances where one or more photons arrive at the detector within the detector response time. This method can be used to distinguish up to five photon counts per digitized point, whereas previous demonstrations of computational photon counting on data acquired with photomultiplier tubes have only counted one photon at a time. We demonstrate in both freely moving C. elegans and a human breast cancer cell line undergoing apoptosis that this novel multithreshold peak detection method can accurately characterize the intensity and fluorescence lifetime of samples producing photon rates up to 223%, higher than previously demonstrated photon counting FLIM systems.

A Novel Quantum Dot-Based pH Probe for Long-Term Fluorescence Lifetime Imaging Microscopy Experiments in Living Cells

The use of two nanoparticles for quantitative pH measurements in live cells by means of fluorescence lifetime imaging microscopy (FLIM) is investigated here. These nanoparticles are based on CdSe/ZnS quantum dots (QDs), functionalized with N-acetylcysteine (CdSe/ZnS-A) and with a small peptide containing D-penicillamine and histidine (CdSe/ZnS-PH). CdSe/ZnS-A has tendency to aggregate and nonlinear pH sensitivity in a complex medium containing salts and macromolecules. On the contrary, CdSe/ZnS-PH shows chemical stability, low toxicity, efficient uptake in C3H10T1/2 cells, and good performance as an FLIM probe. CdSe/ZnS-PH also has key advantages over a recently reported probe based on a CdSe/ZnS QD functionalized with D-penicillamine (longer lifetimes and higher pH-sensitivity). A pH(±2σ) of 6.97 ± 0.14 was determined for C3H10T1/2 cells by FLIM employing this nanoprobe. In addition, the fluorescence lifetime signal remains nearly constant for C3H10T1/2 cells treated with CdSe/ZnS-PH for 24 h. These results show the promising applications of this nanoprobe to monitor the intracellular pH and cell state employing the FLIM technique.

Functionalized CdSe/ZnS Quantum Dots for Intracellular pH Measurements by Fluorescence Lifetime Imaging Microscopy

pH is an important biomarker for many human diseases and great efforts are being made to develop new pH probes for bioimaging and biomedical applications. Here, the use of three different CdSe/ZnS QDs, functionalized with d-penicillamine and small peptides, as pH probes for fluorescence lifetime imaging microscopy (FLIM) is investigated. The fluorescence pH sensitivity of the nanoparticles is analyzed in different experimental media: aqueous solution, synthetic intracellular medium, and mesenchymal C3H10T1/2 and tumoral SK-MEL-2 cell lines. Different experiments along with theoretical calculations are conducted to unravel the mechanisms causing pH sensitivity of the nanoparticles and the effect of the length and composition of the peripheral branches on their photophysical properties. Absolute intracellular pH values measured in live cells with FLIM using a fluorescent probe based on a QD are reported here for the first time (intracellular pH values of 7.0 and 7.1 for C3H10T1/2 and SK-MEL-2 cells, respectively). These fluorescent nanoprobes can also be used to distinguish between different types of cells in cocultures on the basis of their different fluorescence lifetimes in dissimilar intracellular environments.

Fluorescence lifetime imaging microscopy: fundamentals and advances in instrumentation, analysis, and applications

SIGNIFICANCE

Fluorescence lifetime imaging microscopy (FLIM) is a powerful technique to distinguish the unique molecular environment of fluorophores. FLIM measures the time a fluorophore remains in an excited state before emitting a photon, and detects molecular variations of fluorophores that are not apparent with spectral techniques alone. FLIM is sensitive to multiple biomedical processes including disease progression and drug efficacy.

AIM

We provide an overview of FLIM principles, instrumentation, and analysis while highlighting the latest developments and biological applications.

APPROACH

This review covers FLIM principles and theory, including advantages over intensity-based fluorescence measurements. Fundamentals of FLIM instrumentation in time- and frequency-domains are summarized, along with recent developments. Image segmentation and analysis strategies that quantify spatial and molecular features of cellular heterogeneity are reviewed. Finally, representative applications are provided including high-resolution FLIM of cell- and organelle-level molecular changes, use of exogenous and endogenous fluorophores, and imaging protein-protein interactions with Förster resonance energy transfer (FRET). Advantages and limitations of FLIM are also discussed.

CONCLUSIONS

FLIM is advantageous for probing molecular environments of fluorophores to inform on fluorophore behavior that cannot be elucidated with intensity measurements alone. Development of FLIM technologies, analysis, and applications will further advance biological research and clinical assessments.