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

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.

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.

Toward absolute viability measurements for bacteria

We aim to develop a quantitative viability method that distinguishes individual quiescent from dead cells and is measured in time (ns) as a referenceable, comparable quantity. We demonstrate that fluorescence lifetime imaging of an anionic, fluorescent membrane voltage probe fulfills these requirements for Streptococcus mutans. A random forest machine-learning model assesses whether individual S. mutans can be correctly classified into their original populations: stationary phase (quiescent), heat killed and inactivated via chemical fixation. We compare the results to intensity using three models: lifetime variables (τ₁ , τ₂ and p₁ ), phasor variables (G, S) or all five variables, with the five variable models having the most accurate classification. This initial work affirms the potential for using fluorescence lifetime of a membrane voltage probe as a viability marker for quiescent bacteria, and future efforts on other bacterial species and fluorophores will help refine this approach.

Real-time fiber-based fluorescence lifetime imaging with synchronous external illumination: A new path for clinical translation

Time-correlated single photon counting is the "gold-standard" method for fluorescence lifetime measurements and has demonstrated potential for clinical deployment. However, the translation of the technology into clinic is hindered by the use of ultrasensitive detectors, which make the fluorescence acquisition impractical with bright lighting conditions such as in clinical settings. We address this limitation by interleaving periodic fluorescence detection with synchronous out-of-phase externally modulated light source, thus guaranteeing specimen illumination and a fluorescence signal free from bright background light upon temporal separation. Fluorescence lifetime maps are generated in real-time from single-point measurements by tracking a reference beam and using the phasor approach. We demonstrate the feasibility and practicality of this technique in a number of biological specimens, including real-time mapping of degraded articular cartilage. This method is compatible and can be integrated with existing clinical microscopic, endoscopic and robotic modalities, thus offering a new pathway towards label-free diagnostics and surgical guidance in a number of clinical applications.