Global analysis of time-resolved fluorescence microspectroscopy and applications in biomolecular studies

Understanding the properties of biomolecular networks is of central importance in life sciences. Optical microscopy has been very useful to determine the sub-cellular localisation of proteins but it cannot reveal whether proteins interact with one another. Micro-spectroscopic techniques (combining microscopy with spectroscopy) can provide direct information on molecular interactions and dynamic events involving biomolecules with minimal perturbation of cellular integrity and function and they are particularly useful for studying life cells. Over the last few years the spatial-temporal resolution and sensitivity of these techniques have improved considerably. Detecting protein-protein interactions within a biological cell can lead to a greater understanding of the key mechanisms that regulate the fundamental processes of the cell. However, analysis of fluorescence microspectroscopy data is not a trivial task. Well-designed data analysis techniques could significantly improve the interpretation of parameters and characteristics of photophysical processes in complex molecular systems. The most commonly used methods of time-resolved spectroscopic data analysis are, respectively, nonlinear least squares, deconvolution, global analysis and maximum entropy. These methods often lead to a good description of the data but do not necessarily provide physically relevant parameters. The aim of this thesis is to develop new multidimensional fluorescence analysis methods dedicated to improve the visualization and the quantitative analysis and physical interpretation of complex spectral, spatial and time-resolved data sets. <br/

Analysis of time-correlated single photon counting data:a comparative evaluation of deterministic and probabilistic approaches

We review various methods for analysing time-resolved fluorescence data acquired using the time-correlated single photon counting method in an attempt to evaluate their benefits and limitations. We have applied these methods to both experimental and simulated data. The relative merits of using deterministic approaches, such as the commonly used iterative reconvolution method, and probabilistic approaches, such as the smoothed exponential series method, the maximum entropy method and recently proposed basis pursuit denoising (compressed sensing) method, are outlined. In particular, we show the value of using multiple methods to arrive at the most appropriate choice of model. We show that the use of probabilistic analysis methods can indicate whether a discrete component or distribution analysis provides the better representation of the data

Air pollution source identification

The techniques available for source identification are reviewed: remote sensing, injected tracers, and pollutants themselves as tracers. The use of the large number of trace elements in the ambient airborne particulate matter as a practical means of identifying sources is discussed. Trace constituents are determined by sensitive, inexpensive, nondestructive, multielement analytical methods such as instrumental neutron activation and charged particle X-ray fluorescence. The application to a large data set of pairwise correlation, the more advanced pattern recognition-cluster analysis approach with and without training sets, enrichment factors, and pollutant concentration rose displays for each element is described. It is shown that elemental constituents are related to specific source types: earth crustal, automotive, metallurgical, and more specific industries. A field-ready source identification system based on time and wind direction resolved sampling is described

Fast fluorescence lifetime imaging and sensing via deep learning

Error on title page – year of award is 2023.Fluorescence lifetime imaging microscopy (FLIM) has become a valuable tool in diverse disciplines. This thesis presents deep learning (DL) approaches to addressing two major challenges in FLIM: slow and complex data analysis and the high photon budget for precisely quantifying the fluorescence lifetimes. DL's ability to extract high-dimensional features from data has revolutionized optical and biomedical imaging analysis. This thesis contributes several novel DL FLIM algorithms that significantly expand FLIM's scope. Firstly, a hardware-friendly pixel-wise DL algorithm is proposed for fast FLIM data analysis. The algorithm has a simple architecture yet can effectively resolve multi-exponential decay models. The calculation speed and accuracy outperform conventional methods significantly. Secondly, a DL algorithm is proposed to improve FLIM image spatial resolution, obtaining high-resolution (HR) fluorescence lifetime images from low-resolution (LR) images. A computational framework is developed to generate large-scale semi-synthetic FLIM datasets to address the challenge of the lack of sufficient high-quality FLIM datasets. This algorithm offers a practical approach to obtaining HR FLIM images quickly for FLIM systems. Thirdly, a DL algorithm is developed to analyze FLIM images with only a few photons per pixel, named Few-Photon Fluorescence Lifetime Imaging (FPFLI) algorithm. FPFLI uses spatial correlation and intensity information to robustly estimate the fluorescence lifetime images, pushing this photon budget to a record-low level of only a few photons per pixel. Finally, a time-resolved flow cytometry (TRFC) system is developed by integrating an advanced CMOS single-photon avalanche diode (SPAD) array and a DL processor. The SPAD array, using a parallel light detection scheme, shows an excellent photon-counting throughput. A quantized convolutional neural network (QCNN) algorithm is designed and implemented on a field-programmable gate array as an embedded processor. The processor resolves fluorescence lifetimes against disturbing noise, showing unparalleled high accuracy, fast analysis speed, and low power consumption.Fluorescence lifetime imaging microscopy (FLIM) has become a valuable tool in diverse disciplines. This thesis presents deep learning (DL) approaches to addressing two major challenges in FLIM: slow and complex data analysis and the high photon budget for precisely quantifying the fluorescence lifetimes. DL's ability to extract high-dimensional features from data has revolutionized optical and biomedical imaging analysis. This thesis contributes several novel DL FLIM algorithms that significantly expand FLIM's scope. Firstly, a hardware-friendly pixel-wise DL algorithm is proposed for fast FLIM data analysis. The algorithm has a simple architecture yet can effectively resolve multi-exponential decay models. The calculation speed and accuracy outperform conventional methods significantly. Secondly, a DL algorithm is proposed to improve FLIM image spatial resolution, obtaining high-resolution (HR) fluorescence lifetime images from low-resolution (LR) images. A computational framework is developed to generate large-scale semi-synthetic FLIM datasets to address the challenge of the lack of sufficient high-quality FLIM datasets. This algorithm offers a practical approach to obtaining HR FLIM images quickly for FLIM systems. Thirdly, a DL algorithm is developed to analyze FLIM images with only a few photons per pixel, named Few-Photon Fluorescence Lifetime Imaging (FPFLI) algorithm. FPFLI uses spatial correlation and intensity information to robustly estimate the fluorescence lifetime images, pushing this photon budget to a record-low level of only a few photons per pixel. Finally, a time-resolved flow cytometry (TRFC) system is developed by integrating an advanced CMOS single-photon avalanche diode (SPAD) array and a DL processor. The SPAD array, using a parallel light detection scheme, shows an excellent photon-counting throughput. A quantized convolutional neural network (QCNN) algorithm is designed and implemented on a field-programmable gate array as an embedded processor. The processor resolves fluorescence lifetimes against disturbing noise, showing unparalleled high accuracy, fast analysis speed, and low power consumption

Time-resolved FRET fluorescence spectroscopy of visible fluorescent protein pairs

Förster resonance energy transfer (FRET) is a powerful method for obtaining information about small-scale lengths between biomacromolecules. Visible fluorescent proteins (VFPs) are widely used as spectrally different FRET pairs, where one VFP acts as a donor and another VFP as an acceptor. The VFPs are usually fused to the proteins of interest, and this fusion product is genetically encoded in cells. FRET between VFPs can be determined by analysis of either the fluorescence decay properties of the donor molecule or the rise time of acceptor fluorescence. Time-resolved fluorescence spectroscopy is the technique of choice to perform these measurements. FRET can be measured not only in solution, but also in living cells by the technique of fluorescence lifetime imaging microscopy (FLIM), where fluorescence lifetimes are determined with the spatial resolution of an optical microscope. Here we focus attention on time-resolved fluorescence spectroscopy of purified, selected VFPs (both single VFPs and FRET pairs of VFPs) in cuvette-type experiments. For quantitative interpretation of FRET–FLIM experiments in cellular systems, details of the molecular fluorescence are needed that can be obtained from experiments with isolated VFPs. For analysis of the time-resolved fluorescence experiments of VFPs, we have utilised the maximum entropy method procedure to obtain a distribution of fluorescence lifetimes. Distributed lifetime patterns turn out to have diagnostic value, for instance, in observing populations of VFP pairs that are FRET-inactiv

High-sensitivity spectral fluorescence lifetime imaging for resolving spectroscopically overlapping species

The capability to resolve the contributions from spectroscopically overlapping fluorophores has enabled significant breakthroughs in cellular imaging. However, commercial microscopes for this purpose use analog light detection with least squares curve-fitting analysis and improvements in sensitivity are needed. To this end, a microscope has been constructed with high throughput and single-photon detection capability. The fluorescence is separated through use of a prism spectrometer or a series of dichroic mirrors into four spectral bands and detected using four single-photon avalanche diode (SPAD) detectors, which provide high-quantum efficiency in the red spectral region. The detectors are connected to a time-correlated single photon counting module to provide sub-nanosecond temporal resolution for distinguishing fluorophores with different fluorescence lifetimes. Maximum-likelihood (ML) methods have been developed for analyzing the temporally and spectrally resolved photon count data from the SPADs to find the contributions from different fluorescent species and from background. Commercially available SPADs exhibit a count-rate dependent time shift in the impulse response function, and hence the instrument incorporates custom modified SPADs with improved timing stability. Nevertheless, there is still some time shift, and hence the ML-analysis has been extended to include this as an adjustable parameter for each individual SPAD. Monte Carlo simulations have also been developed to enable studies of the number of photons needed to resolve specific fluorophores

Use of time-resolved fluorescence to monitor bioactive compounds in plant based foodstuffs

The study of compounds that exhibit antioxidant activity has recently received much interest in the food industry because of their potential health benefits. Most of these compounds are plant based, such as polyphenolics and carotenoids, and there is a need to monitor them from the field through processing and into the body. Ideally, a monitoring technique should be non-invasive with the potential for remote capabilities. The application of the phenomenon of fluorescence has proved to be well suited, as many plant associated compounds exhibit fluorescence. The photophysical behaviour of fluorescent molecules is also highly dependent on their microenvironment, making them suitable probes to monitor changes in pH, viscosity and polarity, for example. Time-resolved fluorescence techniques have recently come to the fore, as they offer the ability to obtain more information, coupled with the fact that the fluorescence lifetime is an absolute measure, while steady state just provides relative and average information. In this work, we will present illustrative time-resolved measurements, rather than a comprehensive review, to show the potential of time-resolved fluorescence applied to the study of bioactive substances. The aim is to help assess if any changes occur in their form, going from extraction via storage and cooking to the interaction with serum albumin, a principal blood transport protein

NANOSCALE INVESTIGATION OF NUCLEAR STRUCTURES BY TIME-RESOLVED MICROSCOPY

The eukaryotic cell nucleus is composed by heterogeneous biological structures, such as the nuclear envelope (NE) and chromatin. At a morphological level, chromatin organization and its interactions with nuclear structures, such as nuclear lamina (NL) and nuclear pore complex (NPC), are suggested to play an essential role in the regulation of gene activity, which involves the packaging of the genome into transcriptionally active and inactive sites, bound to healthy cell proliferation and maintenance. However, the processes governing the relation between nuclear structures and gene regulation are still unclear. For this reason, the advanced microscopy methods represent a powerful tool for imaging nuclear structures at the nanometer level, which is essential to understand the effect of nuclear interactions on genome function. The nanometer information may be achieved either through the advanced imaging techniques in combination with fluorescence spectroscopy or with the help of super-resolution methods, increasing the spatial resolution of the conventional optical microscopy. In this thesis, I implemented a double strategy based on a novel FLIM-FRET assay and super resolution SPLIT-STED method for the investigation of the chromatin organization and nuclear envelope components (lamins and NPC) at the nanoscale, in combination with the phasor analysis. The phasor approach can be applied to several fluorescence microscopy techniques abled to provide an image with an additional information in a third channel. Phasor plot is a graphical representation, which decodes the fluorescence dynamics encoded in the image, revealing a powerful tool for the data analysis in time-resolved imaging. The Chapter 1 of the thesis is characterized by an Introduction, which provides an overview on the chromatin organization at the nanoscale and the description of the several advanced fluorescence microscopy techniques used for its investigation. They are broadly divided into two main categories: the advanced imaging techniques, such as Fluorescence Correlation Spectroscopy (FCS), single particle tracking (SPT) and Fluorescence Recovery After Photobleaching (FRAP), Forster Resonance Energy Transfer (FRET) and Fluorescence Lifetime Imaging Microscopy (FLIM) and the super-resolution techniques, which include Stimulated Emission Depletion (STED), Structured Illumination Microscopy (SIM) and single molecule localization microscopy (SMLM). Following, Chapter 2 focus on the capabilities of the phasor approach in time-resolved microscopy, as a powerful tool for the analysis of the experimental data. After a description of the principles of time-domain and frequency-domain measurements, in this section are explained the rules of the phasor analysis and its applications in different fluorescence microscopy techniques. In Chapter 3, I present a FRET assay, based on the staining of the nuclei with two DNA-binding dyes (e.g. Hoechst 33342 and Syto Green 13) by using frequency-domain detection of FLIM and the phasor analysis in live interphase nuclei. I show that the FRET level strongly depends on the relative concentration of the two fluorophores. I describe a method to correct the values of FRET efficiency and demonstrate that, with this correction, the FLIM-FRET assay can be used to quantify variations of nanoscale chromatin compaction in live cells. In Chapter 4, the phasor analysis is employed to the improvement of the resolving power of the super-resolution STED microscopy. I describe a novel method to investigate nuclear structures at the nanometer level, known as SPLIT (Separation of Photons by Lifetime Tuning), developed by my group in last years. By using the phasor approach, the SPLIT technique decodes the variations of spectroscopic parameters of fluorophores, such as lifetime and fluorescence intensity, due to the effect of the modulated depletion power of the STED technique, increasing the resolving power. In this chapter, I develop the concept of the SPLIT method modulating the excitation pattern during the image acquisition to overcome its limitation linked to the photobleaching effect and the signal-to-noise ratio