Robust Bayesian Fluorescence Lifetime Estimation, Decay Model Selection and Instrument Response Determination for Low-Intensity FLIM Imaging

The promise and peril of comparing fluorescence lifetime in biology revealed by simulations

Signaling dynamics are crucial in biological systems, and biosensor-based real-time imaging has revolutionized their analysis. Fluorescence lifetime imaging microscopy (FLIM) excels over the widely used fluorescence intensity imaging by allowing the measurement of absolute signal levels, independent of sensor concentration. This capability enables the comparison of signaling dynamics across different animals, body regions, and timeframes. However, FLIM's advantage can be compromised by factors like autofluorescence in biological experiments. To address this, we introduce FLiSimBA, a flexible computational framework for realistic F luorescence Li fetime Sim ulation for B iological A pplications. Through simulations, we analyze the signal-to-noise ratios of fluorescence lifetime data, determining measurement uncertainty and providing necessary error bars for lifetime measurements. Furthermore, we challenge the belief that fluorescence lifetime is unaffected by sensor expression and establish quantitative limits to this insensitivity in biological applications. Additionally, we propose innovations, notably multiplexed dynamic imaging that combines fluorescence intensity and lifetime measurements. This innovation can transform the number of signals that can be simultaneously monitored, thereby enabling a systems approach in studying signaling dynamics. Thus, by incorporating diverse factors into our simulation framework, we uncover surprises, identify limitations, and propose advancements for fluorescence lifetime imaging in biology. This quantitative framework supports rigorous experimental design, facilitates accurate data interpretation, and paves the way for technological advancements in fluorescence lifetime imaging.

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.

Fluorescence Microscopy: a statistics-optics perspective

Fundamental properties of light unavoidably impose features on images collected using fluorescence microscopes. Modeling these features is ever more important in quantitatively interpreting microscopy images collected at scales on par or smaller than light's wavelength. Here we review the optics responsible for generating fluorescent images, fluorophore properties, microscopy modalities leveraging properties of both light and fluorophores, in addition to the necessarily probabilistic modeling tools imposed by the stochastic nature of light and measurement.

Predicting progression-free survival after systemic therapy in advanced head and neck cancer: Bayesian regression and model development

Background

Advanced head and neck squamous cell carcinoma (HNSCC) is associated with a poor prognosis, and biomarkers that predict response to treatment are highly desirable. The primary aim was to predict progression-free survival (PFS) with a multivariate risk prediction model.

Methods

Experimental covariates were derived from blood samples of 56 HNSCC patients which were prospectively obtained within a Phase 2 clinical trial (NCT02633800) at baseline and after the first treatment cycle of combined platinum-based chemotherapy with cetuximab treatment. Clinical and experimental covariates were selected by Bayesian multivariate regression to form risk scores to predict PFS.

Results

A 'baseline' and a 'combined' risk prediction model were generated, each of which featuring clinical and experimental covariates. The baseline risk signature has three covariates and was strongly driven by baseline percentage of CD33+CD14+HLADRhigh monocytes. The combined signature has six covariates, also featuring baseline CD33+CD14+HLADRhigh monocytes but is strongly driven by on-treatment relative change of CD8+ central memory T cells percentages. The combined model has a higher predictive power than the baseline model and was successfully validated to predict therapeutic response in an independent cohort of nine patients from an additional Phase 2 trial (NCT03494322) assessing the addition of avelumab to cetuximab treatment in HNSCC. We identified tissue counterparts for the immune cells driving the models, using imaging mass cytometry, that specifically colocalized at the tissue level and correlated with outcome.

Conclusions

This immune-based combined multimodality signature, obtained through longitudinal peripheral blood monitoring and validated in an independent cohort, presents a novel means of predicting response early on during the treatment course.

Funding

Daiichi Sankyo Inc, Cancer Research UK, EU IMI2 IMMUCAN, UK Medical Research Council, European Research Council (335326), Merck Serono. Cancer Research Institute, National Institute for Health Research, Guy's and St Thomas' NHS Foundation Trust and The Institute of Cancer Research.

Clinical trial number

NCT02633800.

A method for the fast and photon-efficient analysis of time-domain fluorescence lifetime image data over large dynamic ranges

Fluorescence lifetime imaging (FLIM) allows the quantification of sub-cellular processes in situ, in living cells. A number of approaches have been developed to extract the lifetime from time-domain FLIM data, but they are often limited in terms of speed, photon efficiency, precision or the dynamic range of lifetimes they can measure. Here, we focus on one of the best performing methods in the field, the centre-of-mass method (CMM), that conveys advantages in terms of speed and photon efficiency over others. In this paper, however, we identify a loss of photon efficiency of CMM for short lifetimes when background noise is present. We subsequently present a new development and generalization of CMM that provides for the rapid and accurate extraction of fluorescence lifetime over a large lifetime dynamic range. We provide software tools to simulate, validate and analyse FLIM data sets and compare the performance of our approach against the standard CMM and the commonly employed least-square minimization (LSM) methods. Our method features a better photon efficiency than standard CMM and LSM and is robust in the presence of background noise. The algorithm is applicable to any time-domain FLIM data set.

High Resolution Fluorescence Lifetime Maps from Minimal Photon Counts

Fluorescence lifetime imaging microscopy (FLIM) may reveal subcellular spatial lifetime maps of key molecular species. Yet, such a quantitative picture of life necessarily demands high photon budgets at every pixel under the current analysis paradigm, thereby increasing acquisition time and photodamage to the sample. Motivated by recent developments in computational statistics, we provide a direct means to update our knowledge of the lifetime maps of species of different lifetimes from direct photon arrivals, while accounting for experimental features such as arbitrary forms of the instrument response function (IRF) and exploiting information from empty laser pulses not resulting in photon detection. Our ability to construct lifetime maps holds for arbitrary lifetimes, from short lifetimes (comparable to the IRF) to lifetimes exceeding interpulse times. As our method is highly data efficient, for the same amount of data normally used to determine lifetimes and photon ratios, working within the Bayesian paradigm, we report direct blind unmixing of lifetimes with subnanosecond resolution and subpixel spatial resolution using standard raster scan FLIM images. We demonstrate our method using a wide range of simulated and experimental data.

Simple phasor-based deep neural network for fluorescence lifetime imaging microscopy

Fluorescence lifetime imaging microscopy (FLIM) is a powerful technique to probe the molecular environment of fluorophores. The analysis of FLIM images is usually performed with time consuming fitting methods. For accelerating this analysis, sophisticated deep learning architectures based on convolutional neural networks have been developed for restrained lifetime ranges but they require long training time. In this work, we present a simple neural network formed only with fully connected layers able to analyze fluorescence lifetime images. It is based on the reduction of high dimensional fluorescence intensity temporal decays into four parameters which are the phasor coordinates, the mean and amplitude-weighted lifetimes. This network called Phasor-Net has been applied for a time domain FLIM system excited with an 80 MHz laser repetition frequency, with negligible jitter and afterpulsing. Due to the restricted time interval of 12.5 ns, the training range of the lifetimes was limited between 0.2 and 3.0 ns; and the total photon number was lower than 106, as encountered in live cell imaging. From simulated biexponential decays, we demonstrate that Phasor-Net is more precise and less biased than standard fitting methods. We demonstrate also that this simple architecture gives almost comparable performance than those obtained from more sophisticated networks but with a faster training process (15 min instead of 30 min). We finally apply successfully our method to determine biexponential decays parameters for FLIM experiments in living cells expressing EGFP linked to mCherry and fused to a plasma membrane protein.

Histogram clustering for rapid time-domain fluorescence lifetime image analysis

We propose a histogram clustering (HC) method to accelerate fluorescence lifetime imaging (FLIM) analysis in pixel-wise and global fitting modes. The proposed method's principle was demonstrated, and the combinations of HC with traditional FLIM analysis were explained. We assessed HC methods with both simulated and experimental datasets. The results reveal that HC not only increases analysis speed (up to 106 times) but also enhances lifetime estimation accuracy. Fast lifetime analysis strategies were suggested with execution times around or below 30 μs per histograms on MATLAB R2016a, 64-bit with the Intel Celeron CPU (2950M @ 2GHz).

Bayesian Inference: The Comprehensive Approach to Analyzing Single-Molecule Experiments

Biophysics experiments performed at single-molecule resolution provide exceptional insight into the structural details and dynamic behavior of biological systems. However, extracting this information from the corresponding experimental data unequivocally requires applying a biophysical model. In this review, we discuss how to use probability theory to apply these models to single-molecule data. Many current single-molecule data analysis methods apply parts of probability theory, sometimes unknowingly, and thus miss out on the full set of benefits provided by this self-consistent framework. The full application of probability theory involves a process called Bayesian inference that fully accounts for the uncertainties inherent to single-molecule experiments. Additionally, using Bayesian inference provides a scientifically rigorous method of incorporating information from multiple experiments into a single analysis and finding the best biophysical model for an experiment without the risk of overfitting the data. These benefits make the Bayesian approach ideal for analyzing any type of single-molecule experiment.

FLIMJ: An open-source ImageJ toolkit for fluorescence lifetime image data analysis

In the field of fluorescence microscopy, there is continued demand for dynamic technologies that can exploit the complete information from every pixel of an image. One imaging technique with proven ability for yielding additional information from fluorescence imaging is Fluorescence Lifetime Imaging Microscopy (FLIM). FLIM allows for the measurement of how long a fluorophore stays in an excited energy state, and this measurement is affected by changes in its chemical microenvironment, such as proximity to other fluorophores, pH, and hydrophobic regions. This ability to provide information about the microenvironment has made FLIM a powerful tool for cellular imaging studies ranging from metabolic measurement to measuring distances between proteins. The increased use of FLIM has necessitated the development of computational tools for integrating FLIM analysis with image and data processing. To address this need, we have created FLIMJ, an ImageJ plugin and toolkit that allows for easy use and development of extensible image analysis workflows with FLIM data. Built on the FLIMLib decay curve fitting library and the ImageJ Ops framework, FLIMJ offers FLIM fitting routines with seamless integration with many other ImageJ components, and the ability to be extended to create complex FLIM analysis workflows. Building on ImageJ Ops also enables FLIMJ's routines to be used with Jupyter notebooks and integrate naturally with science-friendly programming in, e.g., Python and Groovy. We show the extensibility of FLIMJ in two analysis scenarios: lifetime-based image segmentation and image colocalization. We also validate the fitting routines by comparing them against industry FLIM analysis standards.

Direct Photon-by-Photon Analysis of Time-Resolved Pulsed Excitation Data using Bayesian Nonparametrics

Lifetimes of chemical species are typically estimated by either fitting time-correlated single-photon counting (TCSPC) histograms or phasor analysis from time-resolved photon arrivals. While both methods yield lifetimes in a computationally efficient manner, their performance is limited by choices made on the number of distinct chemical species contributing photons. However, the number of species is encoded in the photon arrival times collected for each illuminated spot and need not be set by hand a priori. Here, we propose a direct photon-by-photon analysis of data drawn from pulsed excitation experiments to infer, simultaneously and self-consistently, the number of species and their associated lifetimes from a few thousand photons. We do so by leveraging new mathematical tools within the Bayesian nonparametric. We benchmark our method for both simulated and experimental data for 1-4 species.

HER2-HER3 Heterodimer Quantification by FRET-FLIM and Patient Subclass Analysis of the COIN Colorectal Trial

BACKGROUND

The phase III MRC COIN trial showed no statistically significant benefit from adding the EGFR-target cetuximab to oxaliplatin-based chemotherapy in first-line treatment of advanced colorectal cancer. This study exploits additional information on HER2-HER3 dimerization to achieve patient stratification and reveal previously hidden subgroups of patients who had differing disease progression and treatment response.

METHODS

HER2-HER3 dimerization was quantified by fluorescence lifetime imaging microscopy in primary tumor samples from 550 COIN trial patients receiving oxaliplatin and fluoropyrimidine chemotherapy with or without cetuximab. Bayesian latent class analysis and covariate reduction was performed to analyze the effects of HER2-HER3 dimer, RAS mutation, and cetuximab on progression-free survival and overall survival (OS). All statistical tests were two-sided.

RESULTS

Latent class analysis on a cohort of 398 patients revealed two patient subclasses with differing prognoses (median OS = 1624 days [95% confidence interval [CI] = 1466 to 1816 days] vs 461 days [95% CI = 431 to 504 days]): Class 1 (15.6%) showed a benefit from cetuximab in OS (hazard ratio = 0.43, 95% CI = 0.25 to 0.76, P = .004). Class 2 showed an association of increased HER2-HER3 with better OS (hazard ratio = 0.64, 95% CI = 0.44 to 0.94, P = .02). A class prediction signature was formed and tested on an independent validation cohort (n = 152) validating the prognostic utility of the dimer assay. Similar subclasses were also discovered in full trial dataset (n = 1630) based on 10 baseline clinicopathological and genetic covariates.

CONCLUSIONS

Our work suggests that the combined use of HER dimer imaging and conventional mutation analyses will be able to identify a small subclass of patients (>10%) who will have better prognosis following chemotherapy. A larger prospective cohort will be required to confirm its utility in predicting the outcome of anti-EGFR treatment.

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.

Review: Clinical in vivo multiphoton FLIM tomography

Fluorescence Lifetime Imaging (FLIM) in life sciences based on ultrashort laser scanning microscopy and time-correlated single photon counting (TCSPC) started 30 years ago in Jena/East-Germany. One decade later, first two-photon FLIM images of a human finger were taken with a lab microscope based on a tunable femtosecond Ti:sapphire laser. In 2002/2003, first clinical non-invasive two-photon FLIM studies on patients with dermatological disorders were performed using a novel multiphoton tomograph. Current in vivo two-photon FLIM studies on human subjects are based on TCSPC and focus on (i) patients with skin inflammation and skin cancer as well as brain tumors, (ii) cosmetic research on volunteers to evaluate anti-ageing cremes, (iii) pharmaceutical research on volunteers to gain information on in situ pharmacokinetics, and (iv) space medicine to study non-invasively skin modifications on astronauts during long-term space flights. Two-photon FLIM studies on volunteers and patients are performed with multiphoton FLIM tomographs using near infrared femtosecond laser technology that provide rapid non-invasive and label-free intratissue autofluorescence biopsies with picosecond temporal resolution.

Nonparametric empirical Bayesian framework for fluorescence-lifetime imaging microscopy

Fluorescence lifetime imaging microscopy (FLIM) is a powerful imaging tool used to study the molecular environment of flurophores. In time domain FLIM, extracting lifetime from fluorophores signals entails fitting data to a decaying exponential distribution function. However, most existing techniques for this purpose need large amounts of photons at each pixel and a long computation time, thus making it difficult to obtain reliable inference in applications requiring either short acquisition or minimal computation time. In this work, we introduce a new nonparametric empirical Bayesian framework for FLIM data analysis (NEB-FLIM), leading to both improved pixel-wise lifetime estimation and a more robust and computationally efficient integral property inference. This framework is developed based on a newly proposed hierarchical statistical model for FLIM data and adopts a novel nonparametric maximum likelihood estimator to estimate the prior distribution. To demonstrate the merit of the proposed framework, we applied it on both simulated and real biological datasets and compared it with previous classical methods on these datasets.

High-resolution remote thermometry and thermography using luminescent low-dimensional tin-halide perovskites

Although metal-halide perovskites have recently revolutionized research in optoelectronics through a unique combination of performance and synthetic simplicity, their low-dimensional counterparts can further expand the field with hitherto unknown and practically useful optical functionalities. In this context, we present the strong temperature dependence of the photoluminescence lifetime of low-dimensional, perovskite-like tin-halides and apply this property to thermal imaging. The photoluminescence lifetimes are governed by the heat-assisted de-trapping of self-trapped excitons, and their values can be varied over several orders of magnitude by adjusting the temperature (up to 20 ns °C^-1). Typically, this sensitive range spans up to 100 °C, and it is both compound-specific and shown to be compositionally and structurally tunable from -100 to 110 °C going from [C(NH₂)₃]₂SnBr₄ to Cs₄SnBr₆ and (C₄N₂H₁₄I)₄SnI₆. Finally, through the implementation of cost-effective hardware for fluorescence lifetime imaging, based on time-of-flight technology, these thermoluminophores have been used to record thermographic videos with high spatial and thermal resolution.

Targeted fluorescence lifetime probes reveal responsive organelle viscosity and membrane fluidity

The only way to visually observe cellular viscosity, which can greatly influence biological reactions and has been linked to several human diseases, is through viscosity imaging. Imaging cellular viscosity has allowed the mapping of viscosity in cells, and the next frontier is targeted viscosity imaging of organelles and their microenvironments. Here we present a fluorescent molecular rotor/FLIM framework to image both organellar viscosity and membrane fluidity, using a combination of chemical targeting and organelle extraction. For demonstration, we image matrix viscosity and membrane fluidity of mitochondria, which have been linked to human diseases, including Alzheimer's Disease and Leigh's syndrome. We find that both are highly dynamic and responsive to small environmental and physiological changes, even under non-pathological conditions. This shows that neither viscosity nor fluidity can be assumed to be fixed and underlines the need for single-cell, and now even single-organelle, imaging.

Metabolic Profiling of Live Cancer Tissues Using NAD(P)H Fluorescence Lifetime Imaging

Altered metabolism is a hallmark of cancer, both resulting from and driving oncogenesis. The NAD and NADP redox couples play a key role in a large number of the metabolic pathways involved. In their reduced forms, NADH and NADPH, these molecules are intrinsically fluorescent. As the average time for fluorescence to be emitted following excitation by a laser pulse, the fluorescence lifetime, is exquisitely sensitive to changes in the local environment of the fluorophore, imaging the fluorescence lifetime of NADH and NADPH offers the potential for label-free monitoring of metabolic changes inside living tumors. Here, we describe the biological, photophysical, and methodological considerations required to establish fluorescence lifetime imaging (FLIM) of NAD(P)H as a routine method for profiling the metabolism of living cancer cells and tissues.

Measuring NDC80 binding reveals the molecular basis of tension-dependent kinetochore-microtubule attachments

Proper kinetochore-microtubule attachments, mediated by the NDC80 complex, are required for error-free chromosome segregation. Erroneous attachments are corrected by the tension dependence of kinetochore-microtubule interactions. Here, we present a method, based on fluorescence lifetime imaging microscopy and Förster resonance energy transfer, to quantitatively measure the fraction of NDC80 complexes bound to microtubules at individual kinetochores in living human cells. We found that NDC80 binding is modulated in a chromosome autonomous fashion over prometaphase and metaphase, and is predominantly regulated by centromere tension. We show that this tension dependency requires phosphorylation of the N-terminal tail of Hec1, a component of the NDC80 complex, and the proper localization of Aurora B kinase, which modulates NDC80 binding. Our results lead to a mathematical model of the molecular basis of tension-dependent NDC80 binding to kinetochore microtubules in vivo.

When a cell divides, each new cell that forms needs to contain a complete set of DNA, which is stored in structures called chromosomes. So first, the chromosomes duplicate, and the two copies are held together. A protein structure known as a kinetochore then forms on each copy of the chromosome. The kinetochores act as a pair of hands that pull the chromosome copies apart and toward opposite sides of the dividing cell. They do this by grabbing protein ‘ropes’ called microtubules that extend toward the chromosomes from each side of the cell.

Kinetochores grip the microtubule ropes more tightly when the connection is under greater tension. This helps the kinetochores to remain attached to the microtubules that will separate the chromosome copies while releasing the microtubules that would pull both copies to the same side. Previous research has shown that hundreds of finger-like structures made out of a protein group called NDC80 extend from each kinetochore ‘hand’ and attach to the microtubules. What remains a mystery is whether and how the NDC80 fingers grip the microtubules more tightly when tension is greater in cells.

Yoo et al. developed a technique for counting how many of the available NDC80 fingers of a single kinetochore are attached to microtubules within a living human cell. The new technique combines genetic engineering, fluorescence imaging and statistical methods to quantify the attachment of NDC80 to microtubules over time and space.

Yoo et al. found that more NDC80 bound to microtubules when there was greater tension. This relationship between binding and tension depends on an enzyme called Aurora B, which modifies the tip of each NDC80 finger and consequently changes the binding of NDC80 to microtubules. Yoo et al. further showed that Aurora B needs to be properly placed between two kinetochore hands to make NDC80-microtubule binding dependent on tension. Without this tension dependency, chromosomes could segregate unevenly into the newly formed cells – a problem that can lead to cancer, infertility and birth defects. The results presented by Yoo et al. therefore expand our understanding of how these diseases originate and may eventually help researchers to develop new treatments for them.

Quantitative Live Cell FLIM Imaging in Three Dimensions

In this chapter, the concept of fluorescence lifetime and its utility in quantitative live cell imaging will be introduced, along with methods to record and analyze FLIM data. Relevant applications in 3D tissue and live cell imaging, including multiplexed FLIM detection, will also be detailed.

Recent Advances in Fluorescence Lifetime Analytical Microsystems: Contact Optics and CMOS Time-Resolved Electronics

Fluorescence spectroscopy has become a prominent research tool with wide applications in medical diagnostics and bio-imaging. However, the realization of combined high-performance, portable, and low-cost spectroscopic sensors still remains a challenge, which has limited the technique to the laboratories. A fluorescence lifetime measurement seeks to obtain the characteristic lifetime from the fluorescence decay profile. Time-correlated single photon counting (TCSPC) and time-gated techniques are two key variations of time-resolved measurements. However, commercial time-resolved analysis systems typically contain complex optics and discrete electronic components, which lead to bulkiness and a high cost. These two limitations can be significantly mitigated using contact sensing and complementary metal-oxide-semiconductor (CMOS) implementation. Contact sensing simplifies the optics, whereas CMOS technology enables on-chip, arrayed detection and signal processing, significantly reducing size and power consumption. This paper examines recent advances in contact sensing and CMOS time-resolved circuits for the realization of fully integrated fluorescence lifetime measurement microsystems. The high level of performance from recently reported prototypes suggests that the CMOS-based contact sensing microsystems are emerging as sound technologies for application-specific, low-cost, and portable time-resolved diagnostic devices.

Noise-Corrected Principal Component Analysis of fluorescence lifetime imaging data

Fluorescence Lifetime Imaging (FLIM) is an attractive microscopy method in the life sciences, yielding information on the sample otherwise unavailable through intensity-based techniques. A novel Noise-Corrected Principal Component Analysis (NC-PCA) method for time-domain FLIM data is presented here. The presence and distribution of distinct microenvironments are identified at lower photon counts than previously reported, without requiring prior knowledge of their number or of the dye's decay kinetics. A noise correction based on the Poisson statistics inherent to Time-Correlated Single Photon Counting is incorporated. The approach is validated using simulated data, and further applied to experimental FLIM data of HeLa cells stained with membrane dye di-4-ANEPPDHQ. Two distinct lipid phases were resolved in the cell membranes, and the modification of the order parameters of the plasma membrane during cholesterol depletion was also detected. Noise-corrected Principal Component Analysis of FLIM data resolves distinct microenvironments in cell membranes of live HeLa cells.

Time-resolved spectroscopy at 19,000 lines per second using a CMOS SPAD line array enables advanced biophotonics applications

A SPAD-based line sensor fabricated in 130 nm CMOS technology capable of acquiring time-resolved fluorescence spectra (TRFS) in 8.3 milliseconds is presented. To the best of our knowledge, this is the fastest time correlated single photon counting (TCSPC) TRFS acquisition reported to date. The line sensor is an upgrade to our prior work and incorporates: i) parallelized interface from sensor to surrounding circuitry enabling high line rate to the PC (19,000 lines/s) and ii) novel time-gating architecture where detected photons in the OFF region are rejected digitally after the output stage of the SPAD. The time-gating architecture was chosen to avoid electrical transients on the SPAD high voltage supplies when gating is achieved by excess bias modulation. The time-gate has an adjustable location and time window width allowing the user to focus on time-events of interest. On-chip integrated center-of-mass (CMM) calculations provide efficient acquisition of photon arrivals and direct lifetime estimation of fluorescence decays. Furthermore, any of the SPC, TCSPC and on-chip CMM modes can be used in conjunction with the time-gating. The higher readout rate and versatile architecture greatly empower the user and will allow widespread applications across many techniques and disciplines. Here we focused on 3 examples of TRFS and time-gated Raman spectroscopy: i) kinetics of chlorophyll A fluorescence from an intact leaf; ii) kinetics of a thrombin biosensor FRET probe from quenched to fluorescence states; iii) ex vivo mouse lung tissue autofluorescence TRFS; iv) time-gated Raman spectroscopy of toluene at 3056 cm^-1 peak. To the best of our knowledge, we detect spectrally for the first time the fast rise in fluorescence lifetime of chlorophyll A in a measurement over single fluorescent transient.

Bridging length scales to measure polymer assembly

Time-resolvable quantitative measurements of polymer concentration are very useful to elucidate protein polymerization pathways. There are numerous techniques to measure polymer concentrations in purified protein solutions, but few are applicable in vivo. Here we develop a methodology combining microscopy and spectroscopy to overcome the limitations of both approaches for measuring polymer concentration in cells and cell extracts. This technique is based on quantifying the relationship between microscopy and spectroscopy measurements at many locations. We apply this methodology to measure microtubule assembly in tissue culture cells and Xenopus egg extracts using two-photon microscopy with FLIM measurements of FRET. We find that the relationship between FRET and two-photon intensity quantitatively agrees with predictions. Furthermore, FRET and intensity measurements change as expected with changes in acquisition time, labeling ratios, and polymer concentration. Taken together, these results demonstrate that this approach can quantitatively measure microtubule assembly in complex environments. This methodology should be broadly useful for studying microtubule nucleation and assembly pathways of other polymers.