Pathogen Detection Using Frequency Domain Fluorescent Lifetime Measurements

Probing Polarity and pH Sensitivity of Carbon Dots in Escherichia coli through Time-Resolved Fluorescence Analyses

Intracellular monitoring of pH and polarity is crucial for understanding cellular processes and functions. This study employed pH- and polarity-sensitive nanomaterials such as carbon dots (CDs) for the intracellular sensing of pH, polarity, and viscosity using integrated time-resolved fluorescence anisotropy (FA) imaging (TR-FAIM) and fluorescence lifetime (FLT) imaging microscopy (FLIM), thereby enabling comprehensive characterization. The functional groups on the surface of CDs exhibit sensitivity to changes in the microenvironment, leading to variations in fluorescence intensity (FI) and FLT according to pH and polarity. The FLT of CDs in aqueous solution changed gradually from 6.38 ± 0.05 ns to 8.03 ± 0.21 ns within a pH range of 2-8. Interestingly, a complex relationship of FI and FLT was observed during measurements of CDs with decreasing polarity. However, the FA and rotational correlation time (θ) increased from 0.062 ± 0.019 to 0.112 ± 0.023 and from 0.49 ± 0.03 ns to 2.01 ± 0.27 ns, respectively. This increase in FA and θ was attributed to the higher viscosity accompanying the decrease in polarity. Furthermore, CDs were found to bind to three locations in Escherichia coli: the cell wall, inner membrane, and cytoplasm, enabling intracellular characterization using FI and FA decay imaging. FLT provided insights into cytoplasmic pH (7.67 ± 0.48), which agreed with previous works, as well as the decrease in polarity in the cell wall and inner membrane. The CD aggregation was suspected in certain areas based on FA, and the θ provided information on cytoplasmic heterogeneity due to the aggregation and/or interactions with biomolecules. The combined TR-FAIM/FLIM system allowed for simultaneous monitoring of pH and polarity changes through FLIM and viscosity variations through TR-FAIM.

Simple and Robust Deep Learning Approach for Fast Fluorescence Lifetime Imaging

Fluorescence lifetime imaging (FLIM) is a powerful tool that provides unique quantitative information for biomedical research. In this study, we propose a multi-layer-perceptron-based mixer (MLP-Mixer) deep learning (DL) algorithm named FLIM-MLP-Mixer for fast and robust FLIM analysis. The FLIM-MLP-Mixer has a simple network architecture yet a powerful learning ability from data. Compared with the traditional fitting and previously reported DL methods, the FLIM-MLP-Mixer shows superior performance in terms of accuracy and calculation speed, which has been validated using both synthetic and experimental data. All results indicate that our proposed method is well suited for accurately estimating lifetime parameters from measured fluorescence histograms, and it has great potential in various real-time FLIM applications.

Classification of fluorescent anisotropy decay based on the distance approach in the frequency domain

Frequency-domain (FD) fluorometry is a widely utilized tool to probe unique features of complex biological structures, which may serve medical diagnostic purposes. The conventional data analysis approaches used today to extract the fluorescence intensity or fluorescence anisotropy (FA) decay data suffer from several drawbacks and are inherently limited by the characteristics and complexity of the decay models. This paper presents the squared distance (D²) technique, which categorized samples based on the direct frequency response data (FRD) of the FA decay. As such, it improves the classification ability of the FD measurements of the FA decay as it avoids any distortion that results from the challenged translation into time domain data. This paper discusses the potential use of the D² approach to classify biological systems. Mathematical formulation of D² technique adjusted to the FRD of the FA decay is described. In addition, it validates the D² approach using 2 simulated data sets of 6 groups with similar widely and closely spaced FA decay data as well as in experimental data of 4 samples of a fluorophore-solvent (fluorescein-glycerol) system. In the simulations, the classification accuracy was above 95% for all 6 groups. In the experimental data, the classification accuracy was 100%. The D² approach can help classify samples whose FA decay data are difficult to extract making FA in the FD a realistic diagnostic tool. The D² approach offers an advanced method for sorting biological samples with differences beyond the practical temporal resolution limit in a reliable and efficient manner based on the FRD of their time-resolved fluorescence measurements thereby achieving better diagnostic quality in a shorter time.

Carbon Dots-Based Logic Gates

Carbon dots (CDs)-based logic gates are smart nanoprobes that can respond to various analytes such as metal cations, anions, amino acids, pesticides, antioxidants, etc. Most of these logic gates are based on fluorescence techniques because they are inexpensive, give an instant response, and highly sensitive. Computations based on molecular logic can lead to advancement in modern science. This review focuses on different logic functions based on the sensing abilities of CDs and their synthesis. We also discuss the sensing mechanism of these logic gates and bring different types of possible logic operations. This review envisions that CDs-based logic gates have a promising future in computing nanodevices. In addition, we cover the advancement in CDs-based logic gates with the focus of understanding the fundamentals of how CDs have the potential for performing various logic functions depending upon their different categories.

In vivo study of metabolic dynamics and heterogeneity in brown and beige fat by label-free multiphoton redox and fluorescence lifetime microscopy

In this work, the metabolic characteristics of adipose tissues in live mouse model were investigated using a multiphoton redox ratio and fluorescence lifetime imaging technology. By analyzing the intrinsic fluorescence of metabolic coenzymes, we measured the optical redox ratios of adipocytes in vivo and studied their responses to thermogenesis. The fluorescence lifetime imaging further revealed changes in protein bindings of metabolic coenzymes in the adipocytes during thermogenesis. Our study uncovered significant heterogeneity in the cellular structures and metabolic characteristics of thermogenic adipocytes in brown and beige fat. Subgroups of brown and beige adipocytes were identified based on the distinct lipid size distributions, redox ratios, fluorescence lifetimes and thermogenic capacities. The results of our study show that this label-free imaging technique can shed new light on in vivo study of metabolic dynamics and heterogeneity of adipose tissues in live organisms.

Single-Photon, Time-Gated, Phasor-Based Fluorescence Lifetime Imaging through Highly Scattering Medium

Fluorescence lifetime imaging (FLI) is increasingly recognized as a powerful tool for biochemical and cellular investigations, including in vivo applications. Fluorescence lifetime is an intrinsic characteristic of any fluorescent dye which, to a large extent, does not depend on excitation intensity and signal level. In particular, it allows distinguishing dyes with similar emission spectra, offering additional multiplexing capabilities. However, in vivo FLI in the visible range is complicated by the contamination by (i) tissue autofluorescence, which decreases contrast, and by (ii) light scattering and absorption in tissues, which significantly reduce fluorescence intensity and modify the temporal profile of the signal. Here, we demonstrate how these issues can be accounted for and overcome, using a new time-gated single-photon avalanche diode array camera, SwissSPAD2, combined with phasor analysis to provide a simple and fast visual method for lifetime imaging. In particular, we show how phasor dispersion increases with increasing scattering and/or decreasing fluorescence intensity. Next, we show that as long as the fluorescence signal of interest is larger than the phantom autofluorescence, the presence of a distinct lifetime can be clearly identified with appropriate background correction. We use these results to demonstrate the detection of A459 cells expressing the fluorescent protein mCyRFP1 through highly scattering and autofluorescent phantom layers. These results showcase the possibility to perform FLI in challenging conditions, using standard, bright, visible fluorophore or fluorescence proteins.

The squared distance approach to frequency domain time-resolved fluorescence analysis

A frequency-domain (FD) analysis of fluorescence lifetime (FLT) is a unique and rapid method for cellular and intracellular classifications that can serve for medical diagnostics purposes. Nevertheless, its data analysis process demands nonlinear fitting algorithms that may distort the resolution of the FLT data and hence diminish the classification ability of the method. This research suggests a sample classification technique that is unaffected by the analysis process as it is based on the squared distance (D² ) between the raw frequency response data (FRD). In addition, it presents the theory behind this technique and its validation in two simulated data sets of six groups with similar widely and closely spaced FLT data as well as in experimental data of 43 samples from bacterial and viral infected and non-infected patients. In the two simulated tests, the classification accuracy was above 95% for all six groups. In the experimental data, the classification of 41 out of 43 samples matched earlier report and 29 out of 31 agreed with preliminary physician diagnosis. The D² approach has the potential to promote FD-time resolved fluorescence measurements as a medical diagnostic technique with high specifity and high sensitivity for many of today's conventional diagnostic procedures.