Mapping diffusion in a living cell via the phasor approach

Segmented fluorescence correlation spectroscopy (FCS) on a commercial laser scanning microscope

Performing accurate Fluorescence Correlation Spectroscopy (FCS) measurements in cells can be challenging due to cellular motion or other intracellular processes. In this respect, it has recently been shown that analysis of FCS data in short temporal segments (segmented FCS) can be very useful to increase the accuracy of FCS measurements inside cells. Here, we demonstrate that segmented FCS can be performed on a commercial laser scanning microscope (LSM), even in the absence of the dedicated FCS module. We show how data can be acquired on a Leica SP8 confocal microscope and then exported and processed with a custom software in MATLAB. The software performs segmentation of the data to extract an average ACF and measure the diffusion coefficient in specific subcellular regions. First of all, we measure the diffusion of fluorophores of different size in solution, to show that good-quality ACFs can be obtained in a commercial LSM. Next, we validate the method by measuring the diffusion coefficient of GFP in the nucleus of HeLa cells, exploiting variations of the intensity to distinguish between nucleoplasm and nucleolus. As expected, the measured diffusion coefficient of GFP is slower in the nucleolus relative to nucleoplasm. Finally, we apply the method to HeLa cells expressing a PARP1 chromobody to measure the diffusion coefficient of PARP1 in different subcellular regions. We find that PARP1 diffusion is slower in the nucleolus compared to the nucleoplasm.

Nascent shifts in renal cellular metabolism, structure, and function due to chronic empagliflozin in prediabetic mice

Sodium-glucose cotransporter, type 2 inhibitors (SGLT2i) are emerging as the gold standard for treatment of type 2 diabetes (T2D) with renal protective benefits independent of glucose lowering. We took a high-level approach to evaluate the effects of the SGLT2i, empagliflozin (EMPA) on renal metabolism and function in a prediabetic model of metabolic syndrome. Male and female 12-wk-old TallyHo (TH) mice, and their closest genetic lean strain (Swiss-Webster, SW) were treated with a high-milk-fat diet (HMFD) plus/minus EMPA (@0.01%) for 12-wk. Kidney weights and glomerular filtration rate were slightly increased by EMPA in the TH mice. Glomerular feature analysis by unsupervised clustering revealed sexually dimorphic clustering, and one unique cluster relating to EMPA. Periodic acid Schiff (PAS) positive areas, reflecting basement membranes and mesangium were slightly reduced by EMPA. Phasor-fluorescent life-time imaging (FLIM) of free-to-protein bound NADH in cortex showed a marginally greater reliance on oxidative phosphorylation with EMPA. Overall, net urine sodium, glucose, and albumin were slightly increased by EMPA. In TH, EMPA reduced the sodium phosphate cotransporter, type 2 (NaPi-2), but increased sodium hydrogen exchanger, type 3 (NHE3). These changes were absent or blunted in SW. EMPA led to changes in urine exosomal microRNA profile including, in females, enhanced levels of miRs 27a-3p, 190a-5p, and 196b-5p. Network analysis revealed "cancer pathways" and "FOXO signaling" as the major regulated pathways. Overall, EMPA treatment to prediabetic mice with limited renal disease resulted in modifications in renal metabolism, structure, and transport, which may preclude and underlie protection against kidney disease with developing T2D.NEW & NOTEWORTHY Renal protection afforded by sodium glucose transporter, type 2 inhibitors (SGLT2i), e.g., empagliflozin (EMPA) involves complex intertwined mechanisms. Using a novel mouse model of obesity with insulin resistance, the TallyHo/Jng (TH) mouse on a high-milk-fat diet (HMFD), we found subtle changes in metabolism including altered regulation of sodium transporters that line the renal tubule. New potential epigenetic determinants of metabolic changes relating to FOXO and cancer signaling pathways were elucidated from an altered urine exosomal microRNA signature.

Learning Continuous 2D Diffusion Maps from Particle Trajectories without Data Binning

Diffusion coefficients often vary across regions, such as cellular membranes, and quantifying their variation can provide valuable insight into local membrane properties such as composition and stiffness. Toward quantifying diffusion coefficient spatial maps and uncertainties from particle tracks, we use a Bayesian method and place Gaussian Process (GP) Priors on the maps. For the sake of computational efficiency, we leverage inducing point methods on GPs arising from the mathematical structure of the data giving rise to non-conjugate likelihood-prior pairs. We analyze both synthetic data, where ground truth is known, as well as data drawn from live-cell single-molecule imaging of membrane proteins. The resulting tool provides an unsupervised method to rigorously map diffusion coefficients continuously across membranes without data binning.

Particle-based phasor-FLIM-FRET resolves protein-protein interactions inside single viral particles

Fluorescence lifetime imaging microscopy (FLIM) is a popular modality to create additional contrast in fluorescence images. By carefully analyzing pixel-based nanosecond lifetime patterns, FLIM allows studying complex molecular populations. At the single-molecule or single-particle level, however, image series often suffer from low signal intensities per pixel, rendering it difficult to quantitatively disentangle different lifetime species, such as during Förster resonance energy transfer (FRET) analysis in the presence of a significant donor-only fraction. In this article we investigate whether an object localization strategy and the phasor approach to FLIM have beneficial effects when carrying out FRET analyses of single particles. Using simulations, we first showed that an average of ∼300 photons, spread over the different pixels encompassing single fluorescing particles and without background, is enough to determine a correct phasor signature (SD < 5% for a 4-ns lifetime). For immobilized single- or double-labeled dsDNA molecules, we next validated that particle-based phasor-FLIM-FRET readily allows estimating fluorescence lifetimes and FRET from single molecules. Thirdly, we applied particle-based phasor-FLIM-FRET to investigate protein-protein interactions in subdiffraction HIV-1 viral particles. To do this, we first quantitatively compared the fluorescence brightness, lifetime, and photostability of different popular fluorescent protein-based FRET probes when genetically fused to the HIV-1 integrase enzyme in viral particles, and conclude that eGFP, mTurquoise2, and mScarlet perform best. Finally, for viral particles coexpressing FRET-donor/acceptor-labeled IN, we determined the absolute FRET efficiency of IN oligomers. Available in a convenient open-source graphical user interface, we believe that particle-based phasor-FLIM-FRET is a promising tool to provide detailed insights in samples suffering from low overall signal intensities.

Riluzole Suppresses Growth and Enhances Response to Endocrine Therapy in ER+ Breast Cancer

Background

Resistance to endocrine therapy in estrogen receptor-positive (ER+) breast cancer remains a significant clinical problem. Riluzole is FDA-approved for the treatment of amyotrophic lateral sclerosis. A benzothiazole-based glutamate release inhibitor with several context-dependent mechanism(s) of action, riluzole has shown antitumor activity in multiple malignancies, including melanoma, glioblastoma, and breast cancer. We previously reported that the acquisition of tamoxifen resistance in a cellular model of invasive lobular breast cancer is accompanied by the upregulation of GRM mRNA expression and growth inhibition by riluzole.

Methods

We tested the ability of riluzole to reduce cell growth, alone and in combination with endocrine therapy, in a diverse set of ER+ invasive ductal and lobular breast cancer-derived cell lines, primary breast tumor explant cultures, and the estrogen-independent, ESR1-mutated invasive lobular breast cancer patient-derived xenograft model HCI-013EI.

Results

Single-agent riluzole suppressed the growth of ER+ invasive ductal and lobular breast cancer cell lines in vitro, inducing a histologic subtype-associated cell cycle arrest (G0-G1 for ductal, G2-M for lobular). Riluzole induced apoptosis and ferroptosis and reduced phosphorylation of multiple prosurvival signaling molecules, including Akt/mTOR, CREB, and Fak/Src family kinases. Riluzole, in combination with either fulvestrant or 4-hydroxytamoxifen, additively suppressed ER+ breast cancer cell growth in vitro. Single-agent riluzole significantly inhibited HCI-013EI patient-derived xenograft growth in vivo, and the combination of riluzole plus fulvestrant significantly reduced proliferation in ex vivo primary breast tumor explant cultures.

Conclusion

Riluzole may offer therapeutic benefits in diverse ER+ breast cancers, including lobular breast cancer.

Current capabilities and future perspectives of FCS: super-resolution microscopy, machine learning, and in vivo applications

Fluorescence correlation spectroscopy (FCS) is a single molecule sensitive tool for the quantitative measurement of biomolecular dynamics and interactions. Improvements in biology, computation, and detection technology enable real-time FCS experiments with multiplexed detection even in vivo. These new imaging modalities of FCS generate data at the rate of hundreds of MB/s requiring efficient data processing tools to extract information. Here, we briefly review FCS's capabilities and limitations before discussing recent directions that address these limitations with a focus on imaging modalities of FCS, their combinations with super-resolution microscopy, new evaluation strategies, especially machine learning, and applications in vivo.

Autocorrelation function of finite-length data in fluorescence correlation spectroscopy

The experimental autocorrelation function of fluorescence correlation spectroscopy calculated from finite-length data is a biased estimator of the theoretical correlation function. This study presents a new theoretical framework that explicitly accounts for the data length to allow for unbiased analysis of experimental autocorrelation functions. To validate our theory, we applied it to experiments and simulations of diffusion and characterized the accuracy and precision of the resulting parameter estimates. Because measurements in living cells are often affected by instabilities of the fluorescence signal, autocorrelation functions are typically calculated on segmented data to improve their robustness. Our reformulated theory extends the range of usable segment times down to timescales approaching the diffusion time. This flexibility confers unique advantages for live-cell data that contain intensity variations and instabilities. We describe several applications of short segmentation to analyze data contaminated with unwanted fluctuations, drifts, or spikes in the intensity that are not suited for conventional fluorescence correlation analysis. These results demonstrate the potential of our theoretical framework to significantly expand the experimental systems accessible to fluorescence correlation spectroscopy.

Model-free phasor image analysis of quantitative myocardial T1 mapping

Model-free phasor image analysis, well established in fluorescence lifetime imaging and only recently applied to qMRI [Formula: see text] data processing, is here adapted and validated for myocardial qMRI [Formula: see text] mapping. Contrarily to routine mono-exponential fitting procedures, phasor enables mapping the lifetime information from all image voxels to a single plot, without resorting to any regression fitting analysis, and describing multi-exponential qMRI decays without biases due to violated modelling assumptions. In this feasibility study, we test the performance of our recently developed full-harmonics phasor method for unravelling partial-volume effects, motion or pathological tissue alteration, respectively on a numerically-simulated dataset, a healthy subject scan, and two pilot patient datasets. Our results show that phasor analysis can be used, as alternative method to fitting analysis or other model-free approaches, to identify motion artifacts or partial-volume effects at the myocardium-blood interface as characteristic deviations, or delineations of scar and remote myocardial tissue in patient data.

Type 1 Innate Lymphoid Cells Are Proinflammatory Effector Cells in Ischemia-Reperfusion Injury of Steatotic Livers

Innate lymphoid cells (ILCs), the most recently described family of lymphoid cells, play fundamental roles in tissue homeostasis through the production of key cytokine. Group 1 ILCs, comprised of conventional natural killer cells (cNKs) and type 1 ILCs (ILC1s), have been implicated in regulating immune-mediated inflammatory diseases. However, the role of ILC1s in nonalcoholic fatty liver disease (NAFLD) and ischemia-reperfusion injury (IRI) is unclear. Here, we investigated the role of ILC1 and cNK cells in a high-fat diet (HFD) murine model of partial warm IRI. We demonstrated that hepatic steatosis results in more severe IRI compared to non-steatotic livers. We further elicited that HFD-IRI mice show a significant increase in the ILC1 population, whereas the cNK population was unchanged. Since ILC1 and cNK are major sources of IFN-γ and TNF-α, we measured the level of ex vivo cytokine expression in normal diet (ND)-IRI and HFD-IRI conditions. We found that ILC1s in HFD-IRI mice produce significantly more IFN-γ and TNF-α when compared to ND-IRI. To further assess whether ILC1s are key proinflammatory effector cells in hepatic IRI of fatty livers, we studied both Rag1−/− mice, which possess cNK cells, and a substantial population of ILC1s versus the newly generated Rag1−/−Tbx21−/− double knockout (Rag1-Tbet DKO) mice, which lack type 1 ILCs, under HFD IRI conditions. Importantly, HFD Rag1-Tbet DKO mice showed significant protection from hepatic injury upon IRI when compared to Rag1−/− mice, suggesting that T-bet-expressing ILC1s play a role, at least in part, as proinflammatory effector cells in hepatic IRI under steatotic conditions.

Linear Combination Properties of the Phasor Space in Fluorescence Imaging

The phasor approach to fluorescence lifetime imaging, and more recently hyperspectral fluorescence imaging, has increased the use of these techniques, and improved the ease and intuitiveness of the data analysis. The fit-free nature of the phasor plots increases the speed of the analysis and reduces the dimensionality, optimization of data handling and storage. The reciprocity principle between the real and imaginary space-where the phasor and the pixel that the phasor originated from are linked and can be converted from one another-has helped the expansion of this method. The phasor coordinates calculated from a pixel, where multiple fluorescent species are present, depends on the phasor positions of those components. The relative positions are governed by the linear combination properties of the phasor space. According to this principle, the phasor position of a pixel with multiple components lies inside the polygon whose vertices are occupied by the phasor positions of these individual components and the distance between the image phasor to any of the vertices is inversely proportional to the fractional intensity contribution of that component to the total fluorescence from that image pixel. The higher the fractional intensity contribution of a vertex, the closer is the resultant phasor. The linear additivity in the phasor space can be exploited to obtain the fractional intensity contribution from multiple species and quantify their contribution. This review details the various mathematical models that can be used to obtain two/three/four components from phasor space with known phasor signatures and then how to obtain both the fractional intensities and phasor positions without any prior knowledge of either, assuming they are mono-exponential in nature. We note that other than for blind components, there are no restrictions on the type of the decay or their phasor positions for linear combinations to be valid-and they are applicable to complicated fluorescence lifetime decays from components with intensity decays described by multi-exponentials.

Phasor approach of Mueller matrix optical scanning microscopy for biological tissue imaging

Mueller matrix microscopy is an advanced imaging technique providing a full characterization of the optical polarization fingerprint of a sample. The Lu-Chipman (LC) decomposition, a method based on the modeling of elementary polarimetric arrangements and matrix inversions, is the gold standard to extract each polarimetric component separately. However, this models the optical system as a small number of discrete optical elements and requires a priori knowledge of the order in which these elements occur. In stratified media or when the ordering is not known, the interpretation of the LC decomposition becomes difficult. In this work, we propose a new, to our knowledge, representation dedicated to the study of biological tissues that combines Mueller matrix microscopy with a phasor approach. We demonstrate that this method provides an easier and direct interpretation of the retardance images in any birefringent material without the use of mathematical assumptions regarding the structure of the sample and yields comparable contrast to the LC decomposition. By validating this approach through numerical simulations, we demonstrate that it is able to give access to localized structural information, resulting in a simple determination of the birefringent parameters at the microscopic level. We apply our novel, to our knowledge, method to typical biological tissues that are of interest in the field of biomedical diagnosis.

The Phasor Plot: A Universal Circle to Advance Fluorescence Lifetime Analysis and Interpretation

The phasor approach to fluorescence lifetime imaging has become a common method to analyze complicated fluorescence signals from biological samples. The appeal of the phasor representation of complex fluorescence decays in biological systems is that a visual representation of the decay of entire cells or tissues can be used to easily interpret fundamental biological states related to metabolism and oxidative stress. Phenotyping based on autofluorescence provides new avenues for disease characterization and diagnostics. The phasor approach is a transformation of complex fluorescence decays that does not use fits to model decays and therefore has the same information content as the original data. The phasor plot is unique for a given system, is highly reproducible, and provides a robust method to evaluate the existence of molecular interactions such as Förster resonance energy transfer or the response of ion indicators. Recent advances permitquantification of multiple components from phasor plots in fluorescence lifetime imaging microscopy, which is not presently possible using data fitting methods, especially in biological systems.

Investigating Spatial Heterogeneity of Nanoparticles Movement in Live Cells with Pair-Correlation Microscopy and Phasor Analysis

How nanoparticles distribute in living cells and overcome cellular barriers are important criteria in the design of drug carriers. Pair-correlation microscopy is a correlation analysis of fluctuation in the fluorescence intensity obtained by a confocal line scan that can quantify the dynamic properties of nanoparticle diffusion including the number of mobile nanoparticles, diffusion coefficient, and transit time across a spatial distance. Due to the potential heterogeneities in nanoparticle properties and the complexity within the cellular environment, quantification of averaged auto- and pair-correlation profiles may obscure important insights into the ability of nanoparticles to deliver drugs. To overcome this issue, we used phasor analysis to develop a data standardizing method, which can segment the scanned line into several subregions according to diffusion and address the spatial heterogeneity of nanoparticles moving inside cells. The phasor analysis is a fit-free method that represents autocorrelation profiles for each pixel relative to free diffusion on the so-called phasor plots. Phasor plots can then be used to select subpopulations for which the auto- and pair-correlation analysis can be performed separately. We demonstrate the phasor analysis for pair-correlation microscopy for investigating 16 nm, Cy5-labeled silica nanoparticles diffusing across the plasma membrane and green fluorescent proteins (GFP) diffusing across nuclear envelope in MCF-7 cells.

Imaging FCS delineates subtle heterogeneity in plasma membranes of resting mast cells

A myriad of transient, nanoscopic lipid- and protein-based interactions confer a steady-state organization of the plasma membrane in resting cells that is poised to orchestrate assembly of key signaling components upon reception of an extracellular stimulus. Although difficult to observe directly in live cells, these subtle interactions can be discerned by their impact on the diffusion of membrane constituents. Here, we quantified the diffusion properties of a panel of structurally distinct lipid, lipid-anchored, and transmembrane (TM) probes in RBL mast cells by imaging fluorescence correlation spectroscopy (ImFCS). We developed a statistical analysis of data combined from many pixels over multiple cells to characterize differences in diffusion coefficients as small as 10%, which reflect differences in underlying interactions. We found that the distinctive diffusion properties of lipid probes can be explained by their dynamic partitioning into Lo-like proteolipid nanodomains, which encompass a major fraction of the membrane and whose physical properties are influenced by actin polymerization. Effects on diffusion of functional protein modules in both lipid-­anchored and TM probes reflect additional complexity in steady state membrane organization. The contrast we observe between different probes diffusing through the same membrane milieu represents the dynamic resting steady state, which serves as a baseline for monitoring plasma membrane remodeling that occurs upon stimulation.

Phasor-assisted nanoscopy reveals differences in the spatial organization of major nuclear lamina proteins

Phasor-assisted Metal Induced Energy Transfer-Fluorescence Lifetime Imaging Microscopy (MIET-FLIM) nanoscopy is introduced as a powerful tool for functional cell biology research. Thin metal substrates can be used to obtain axial super-resolution via nanoscale distance-dependent MIET from fluorescent dyes towards a nearby metal layer, thereby creating fluorescence lifetime contrast between dyes located at different nanoscale distance from the metal. Such data can be used to achieve axially super-resolved microscopy images, a process known as MIET-FLIM nanoscopy. Suitability of the phasor approach in MIET-FLIM nanoscopy is first demonstrated using nanopatterned substrates, and furthermore applied to characterize the distance distribution of the epithelial basal membrane of a biological cell from the gold substrate. The phasor plot of an entire cell can be used to characterize the full Förster resonance energy transfer (FRET) trajectory as a large distance heterogeneity within the sensing range of about 100 nm from the metal surface is present due to the extended shape of cell with curvatures. In contrast, the different proteins of nuclear lamina show strong confinement close to the nuclear envelope in nanoscale. We find the lamin B layer resides in average at shorter distances from the gold surface compared to the lamin A/C layer located in more extended ranges. This and the observed heterogeneity of the protein layer thicknesses suggests that A- and B-type lamins form distinct networks in the nuclear lamina. Our results provide detailed insights for the study of the different roles of lamin proteins in chromatin tethering and nuclear mechanics.

Paxillin S273 Phosphorylation Regulates Adhesion Dynamics and Cell Migration through a Common Protein Complex with PAK1 and βPIX

Cell migration is an important biological phenomenon involved in many homeostatic and aberrant physiological processes. Phosphorylation of the focal adhesion adaptor protein, paxillin, on serine 273 (S273) has been implicated as a key regulator of cell migration. Here, it is shown that phosphorylation on paxillin S273 leads to highly migratory cells with small dynamic adhesions. Adhesions at protrusive edges of the cell were more dynamic than adhesions at retracting edges. Temporal image correlation microscopy revealed that these dynamic adhesions undergo rapid binding of paxillin, PAK1 and βPIX. We identified membrane proximal adhesion subdomains in protrusive regions of the cell that show rapid protein binding that is dependent on paxillin S273 phosphorylation, PAK1 kinase activity and phosphatases. These dynamic adhesion subdomains corresponded to regions of the adhesion that also show co-binding of paxillin/PAK1 and paxillin/βPIX complexes. It is likely that parts of individual adhesions are more dynamic while others are less dynamic due to their association with the actin cytoskeleton. Variable adhesion and binding dynamics are regulated via differential paxillin S273 phosphorylation across the cell and within adhesions and are required for regulated cell migration. Dysregulation through phosphomutants, PAK1-KD or βPIX mutants resulted in large stable adhesions, long protein binding times and slow cell migration. Dysregulation through phosphomimics or PAK1-CA led to small dynamic adhesions and rapid cell migration reminiscent of highly migratory cancer cells. Thus, phosphorylation of paxillin S273 is a key regulator of cell migration through recruitment of βPIX and PAK1 to sites of adhesion.

Analysis of novel hyperosmotic shock response suggests 'beads in liquid' cytosol structure

Proteins can aggregate in response to stresses, including hyperosmotic shock. Formation and disassembly of aggregates is a relatively slow process. We describe a novel instant response of the cell to hyperosmosis, during which chaperones and other proteins form numerous foci with properties uncharacteristic of classical aggregates. These foci appeared/disappeared seconds after shock onset/removal, in close correlation with cell volume changes. Genome-wide and targeted testing revealed chaperones, metabolic enzymes, P-body components and amyloidogenic proteins in the foci. Most of these proteins can form large assemblies and for some, the assembled state was pre-requisite for participation in foci. A genome-wide screen failed to identify genes whose absence prevented foci participation by Hsp70. Shapes of and interconnections between foci, revealed by super-resolution microscopy, indicated that the foci were compressed between other entities. Based on our findings, we suggest a new model of cytosol architecture as a collection of numerous gel-like regions suspended in a liquid network. This network is reduced in volume in response to hyperosmosis and forms small pockets between the gel-like regions.

Fluorescence fluctuation spectroscopy: an invaluable microscopy tool for uncovering the biophysical rules for navigating the nuclear landscape

Nuclear architecture is fundamental to the manner by which molecules traverse the nucleus. The nucleoplasm is a crowded environment where dynamic rearrangements in local chromatin compaction locally redefine the space accessible toward nuclear protein diffusion. Here, we review a suite of methods based on fluorescence fluctuation spectroscopy (FFS) and how they have been employed to interrogate chromatin organization, as well as the impact this structural framework has on nuclear protein target search. From first focusing on a set of studies that apply FFS to an inert fluorescent tracer diffusing inside the nucleus of a living cell, we demonstrate the capacity of this technology to measure the accessibility of the nucleoplasm. Then with a baseline understanding of the exploration volume available to nuclear proteins during target search, we review direct applications of FFS to fluorescently labeled transcription factors (TFs). FFS can detect changes in TF mobility due to DNA binding, as well as the formation of TF complexes via changes in brightness due to oligomerization. Collectively, we find that FFS-based methods can uncover how nuclear proteins in general navigate the nuclear landscape.

Phasor histone FLIM-FRET microscopy quantifies spatiotemporal rearrangement of chromatin architecture during the DNA damage response

To investigate how chromatin architecture is spatiotemporally organized at a double-strand break (DSB) repair locus, we established a biophysical method to quantify chromatin compaction at the nucleosome level during the DNA damage response (DDR). The method is based on phasor image-correlation spectroscopy of histone fluorescence lifetime imaging microscopy (FLIM)-Förster resonance energy transfer (FRET) microscopy data acquired in live cells coexpressing H2B-eGFP and H2B-mCherry. This multiplexed approach generates spatiotemporal maps of nuclear-wide chromatin compaction that, when coupled with laser microirradiation-induced DSBs, quantify the size, stability, and spacing between compact chromatin foci throughout the DDR. Using this technology, we identify that ataxia-telangiectasia mutated (ATM) and RNF8 regulate rapid chromatin decompaction at DSBs and formation of compact chromatin foci surrounding the repair locus. This chromatin architecture serves to demarcate the repair locus from the surrounding nuclear environment and modulate 53BP1 mobility.

Visualizing the regulation of SLC34 proteins at the apical membrane

The cloning of the renal NaPi-2a (SLC34A1) and NaPi-2c (SLC34A3) phosphate transporters has made it possible to characterize the molecular and biophysical regulation of renal proximal tubular reabsorption of inorganic phosphate (Pi). Dietary factors, such as Pi and K, and several hormones and phosphatonins, including parathyroid hormone (PTH), fibroblast growth factor 23 (FGF23), and glucocorticoids, regulate the transporters through various transcriptional, translational, and post-translational mechanisms that involve acute trafficking via endocytosis or exocytosis, interactions with PDZ domain proteins, lipid microdomains, and diffusion and clustering in the apical brush border membrane. The visualization of these trafficking events by means of novel microscopy techniques that includes fluorescence lifetime imaging microscopy (FLIM), Förster resonance energy transfer (FRET), fluctuation correlation spectroscopy (FCS), and modulation tracking (MT), is the primary focus of this review.

Measuring Mobility in Chromatin by Intensity-Sorted FCS

The architectural organization of chromatin can play an important role in genome regulation by affecting the mobility of molecules within its surroundings via binding interactions and molecular crowding. The diffusion of molecules at specific locations in the nucleus can be studied by fluorescence correlation spectroscopy (FCS), a well-established technique based on the analysis of fluorescence intensity fluctuations detected in a confocal observation volume. However, detecting subtle variations of mobility between different chromatin regions remains challenging with currently available FCS methods. Here, we introduce a method that samples multiple positions by slowly scanning the FCS observation volume across the nucleus. Analyzing the data in short time segments, we preserve the high temporal resolution of single-point FCS while probing different nuclear regions in the same cell. Using the intensity level of the probe (or a DNA marker) as a reference, we efficiently sort the FCS segments into different populations and obtain average correlation functions that are associated to different chromatin regions. This sorting and averaging strategy renders the method statistically robust while preserving the observation of intranuclear variations of mobility. Using this approach, we quantified diffusion of monomeric GFP in high versus low chromatin density regions. We found that GFP mobility was reduced in heterochromatin, especially within perinucleolar heterochromatin. Moreover, we found that modulation of chromatin compaction by ATP depletion, or treatment with solutions of different osmolarity, differentially affected the ratio of diffusion in both regions. Then, we used the approach to probe the mobility of estrogen receptor-α in the vicinity of an integrated multicopy prolactin gene array. Finally, we discussed the coupling of this method with stimulated emission depletion FCS for performing FCS at subdiffraction spatial scales.

Label-free Multiscale Transport Imaging of the Living Cell

The living cell is characterized by a myriad of parallel intracellular transport processes. Simultaneously capturing their global features across multiple temporal and spatial scales is a nearly unsurmountable task. Here we present a method that enables the microscopic imaging of the entire spectrum of intracellular transport on a broad time scale without the need for prior labeling. We show that from the time-dependent fluctuation of pixel intensity, in either bright-field or phase-contrast microscopic images, a scaling factor can be derived that reflects the local Hurst coefficient (H), the value of which reveals the microscopic mechanisms of intracellular motion. The Hurst coefficient image of the interphase cell displays an unexpected, overwhelming superdiffusion (H > 0.5) in the cytoplasm and subdiffusion (H < 0.5) in the nucleus, and provides unprecedented sensitivity in detecting transport processes associated with the living state.

Local raster image correlation spectroscopy generates high-resolution intracellular diffusion maps

Raster image correlation spectroscopy (RICS) is a powerful method for measuring molecular diffusion in live cells directly from images acquired on a laser scanning microscope. However, RICS only provides single average diffusion coefficients from regions with a lateral size on the order of few micrometers, which means that its spatial resolution is mainly limited to the cellular level. Here we introduce the local RICS (L-RICS), an easy-to-use tool that generates high resolution maps of diffusion coefficients from images acquired on a laser scanning microscope. As an application we show diffusion maps of a green fluorescent protein (GFP) within the nucleus and within the nucleolus of live cells at an effective spatial resolution of 500 nm. We find not only that diffusion in the nucleolus is slowed down compared to diffusion in the nucleoplasm, but also that diffusion in the nucleolus is highly heterogeneous.

Lorenzo Scipioni et al. present Local Raster Image Correlation Spectroscopy (L-RICS), a method for generating sub-micrometer diffusion maps. They apply L-RICS to GFP in live cells and find that diffusion coefficients differ between the nucleus and nucleolus and are highly heterogeneous within compartments.

μMAPPS: a novel phasor approach to second harmonic analysis for in vitro-in vivo investigation of collagen microstructure

Second Harmonic Generation (SHG) is a label-free imaging method used to monitor collagen organization in tissues. Due to its sensitivity to the incident polarization, it provides microstructural information otherwise unreachable by other intensity based imaging methods. We develop and test a Microscopic Multiparametric Analysis by Phasor projection of Polarization-dependent SHG (μMAPPS) that maps the features of the collagen architecture in tissues at the micrometer scale. μMAPPS retrieves pixel-by-pixel the collagen fibrils anisotropy and orientation by operating directly on two coupled phasor spaces, avoiding direct fitting of the polarization dependent SHG signal. We apply μMAPPS to fixed tissue sections and to the study of the collagen microscopic organization in tumors ex-vivo and in-vivo. We develop a clustering algorithm to automatically group pixels with similar microstructural features. μMAPPS can perform fast analyses of tissues and opens to future applications for in-situ diagnosis of pathologies and diseases that could assist histo-pathological evaluation.

Measurement of nanoscale three-dimensional diffusion in the interior of living cells by STED-FCS

The observation of molecular diffusion at different spatial scales, and in particular below the optical diffraction limit (<200 nm), can reveal details of the subcellular topology and its functional organization. Stimulated-emission depletion microscopy (STED) has been previously combined with fluorescence correlation spectroscopy (FCS) to investigate nanoscale diffusion (STED-FCS). However, stimulated-emission depletion fluorescence correlation spectroscopy has only been used successfully to reveal functional organization in two-dimensional space, such as the plasma membrane, while, an efficient implementation for measurements in three-dimensional space, such as the cellular interior, is still lacking. Here we integrate the STED-FCS method with two analytical approaches, the recent separation of photons by lifetime tuning and the fluorescence lifetime correlation spectroscopy, to simultaneously probe diffusion in three dimensions at different sub-diffraction scales. We demonstrate that this method efficiently provides measurement of the diffusion of EGFP at spatial scales tunable from the diffraction size down to ∼80 nm in the cytoplasm of living cells.

The measurement of molecular diffusion at sub-diffraction scales has been achieved in 2D space using STED-FCS, but an implementation for 3D diffusion is lacking. Here the authors present an analytical approach to probe diffusion in 3D space using STED-FCS and measure the diffusion of EGFP at different spatial scales.

Phasor Analysis of Local ICS Detects Heterogeneity in Size and Number of Intracellular Vesicles

Organelles represent the scale of organization immediately below that of the cell itself, and their composition, size, and number are tailored to their function. Monitoring the size and number of organelles in live cells is relevant for many applications but can be challenging due to their highly heterogeneous properties. Image correlation spectroscopy is a well-established analysis method capable of extracting the average size and number of particles in images. However, when image correlation spectroscopy is applied to a highly heterogeneous system, it can fail to retrieve, from a single correlation function, the characteristic size and the relative amount associated to each subspecies. Here, we describe a fast, unbiased, and fit-free algorithm based on the phasor analysis of multiple local image correlation functions, capable of mapping the sizes of elements contained in a heterogeneous system. The method correctly provides the size and number of separate subspecies, which otherwise would be hidden in the average properties of a single correlation function. We apply the method to quantify the spatial and temporal heterogeneity in the size and number of intracellular vesicles formed after endocytosis in live cells.

Spatial dynamics of SIRT1 and the subnuclear distribution of NADH species

Sirtuin 1 (SIRT1) is an NAD⁺-dependent deacetylase that functions as metabolic sensor of cellular energy and modulates biochemical pathways in the adaptation to changes in the environment. SIRT1 substrates include histones and proteins related to enhancement of mitochondrial function as well as antioxidant protection. Fluctuations in intracellular NAD⁺ levels regulate SIRT1 activity, but how SIRT1 enzymatic activity impacts on NAD⁺ levels and its intracellular distribution remains unclear. Here, we show that SIRT1 determines the nuclear organization of protein-bound NADH. Using multiphoton microscopy in live cells, we show that free and bound NADH are compartmentalized inside of the nucleus, and its subnuclear distribution depends on SIRT1. Importantly, SIRT6, a chromatin-bound deacetylase of the same class, does not influence NADH nuclear localization. In addition, using fluorescence fluctuation spectroscopy in single living cells, we reveal that NAD⁺ metabolism in the nucleus is linked to subnuclear dynamics of active SIRT1. These results reveal a connection between NAD⁺ metabolism, NADH distribution, and SIRT1 activity in the nucleus of live cells and pave the way to decipher links between nuclear organization and metabolism.

ANALYSIS AND DESIGN OF JUMP COEFFICIENTS IN DISCRETE STOCHASTIC DIFFUSION MODELS

In computational systems biology, the mesoscopic model of reaction-diffusion kinetics is described by a continuous time, discrete space Markov process. To simulate diffusion stochastically, the jump coefficients are obtained by a discretization of the diffusion equation. Using unstructured meshes to represent complicated geometries may lead to negative coefficients when using piecewise linear finite elements. Several methods have been proposed to modify the coefficients to enforce the nonnegativity needed in the stochastic setting. In this paper, we present a method to quantify the error introduced by that change. We interpret the modified discretization matrix as the exact finite element discretization of a perturbed equation. The forward error, the error between the analytical solutions to the original and the perturbed equations, is bounded by the backward error, the error between the diffusion of the two equations. We present a backward analysis algorithm to compute the diffusion coefficient from a given discretization matrix. The analysis suggests a new way of deriving nonnegative jump coefficients that minimizes the backward error. The theory is tested in numerical experiments indicating that the new method is superior and also minimizes the forward error.