Single molecule tracking and analysis framework including theory-predicted parameter settings

Nanodomains and Their Temperature Dependence in a Phosphonium-Based Ionic Liquid: A Single-Molecule Tracking Study

Ionic liquids (ILs) exhibit a unique nanoscale structure (i.e., nanodomains) characterized by their organization into distinct domains. We present evidence of nanodomains in trihexyl(tetradecyl)phosphonium chloride, [P66614][Cl], using single-molecule tracking (SMT) and the maximum entropy method (MEM) to analyze single-molecule trajectories. The diffusion properties of ATTO 647N were assessed as the temperature of [P66614][Cl] increased from 20 °C (4020 cP), 35 °C (1239 cP), 45 °C (599 cP) to 50 °C (439 cP). The MEM analysis revealed a distinct two-population distribution of diffusion coefficients representing nanodomains in [P66614][Cl] at 20 °C (4020 cP). The slow population accounts for 16%, with a diffusion coefficient of 0.104 μm2/s, while the fast population constitutes 84% with a diffusion coefficient of 0.634 μm2/s. Two diffusing populations were also measured for the chemically different probes ATTO 647N, DiD, and Nile Blue chloride in [P66614][Cl] at 20 °C. In contrast, only a single fast population was measured in [P66614][Cl] at 50 °C. At a similar viscosity (640 cP) but a lower temperature of 20 °C, trihexyl(tetradecyl)phosphonium bis[(trifluoromethyl)-sulfonyl]imide, [P66614][NTf2], also showed only a single diffusing population. The elimination of the slow population and the presence of a single diffusing population in [P66614][Cl] as the temperature increases and the viscosity decreases is consistent with liquid-liquid phase separation (LLPS) as a mechanism of nanodomain formation. In addition, the measurement of two diffusing populations for three fluorophores with different chemical structures is also consistent with a physical mechanism, and not a chemical mechanism, for nanodomain formation.

Transcription dynamics and genome organization in the mammalian nucleus: Recent advances

Single-molecule tracking (SMT) has emerged as the dominant technology to investigate the dynamics of chromatin-transcription factor (TF) interactions. How long a TF needs to bind to a regulatory site to elicit a transcriptional response is a fundamentally important question. However, highly divergent estimates of TF binding have been presented in the literature, stemming from differences in photobleaching correction and data analysis. TF movement is often interpreted as specific or non-specific association with chromatin, yet the dynamic nature of the chromatin polymer is often overlooked. In this perspective, we highlight how recent SMT studies have reshaped our understanding of TF dynamics, chromatin mobility, and genome organization in the mammalian nucleus, focusing on the technical details and biological implications of these approaches. In a remarkable convergence of fixed and live-cell imaging, we show how super-resolution and SMT studies of chromatin have dovetailed to provide a convincing nanoscale view of genome organization.

Real-time imaging of axonal membrane protein life cycles

The construction of neuronal membranes is a dynamic process involving the biogenesis, vesicular packaging, transport, insertion and recycling of membrane proteins. Optical imaging is well suited for the study of protein spatial organization and transport. However, various shortcomings of existing imaging techniques have prevented the study of specific types of proteins and cellular processes. Here we describe strategies for protein tagging and labeling, cell culture and microscopy that enable the real-time imaging of axonal membrane protein trafficking and subcellular distribution as they progress through some stages of their life cycle. First, we describe a process for engineering membrane proteins with extracellular self-labeling tags (either HaloTag or SNAPTag), which can be labeled with fluorescent ligands of various colors and cell permeability, providing flexibility for investigating the trafficking and spatiotemporal regulation of multiple membrane proteins in neuronal compartments. Next, we detail the dissection, transfection and culture of dorsal root ganglion sensory neurons in microfluidic chambers, which physically compartmentalizes cell bodies and distal axons. Finally, we describe four labeling and imaging procedures that utilize these enzymatically tagged proteins, flexible fluorescent labels and compartmentalized neuronal cultures to study axonal membrane protein anterograde and retrograde transport, the cotransport of multiple proteins, protein subcellular localization, exocytosis and endocytosis. Additionally, we generated open-source software for analyzing the imaging data in a high throughput manner. The experimental and analysis workflows provide an approach for studying the dynamics of neuronal membrane protein homeostasis, addressing longstanding challenges in this area. The protocol requires 5-7 days and expertise in cell culture and microscopy.

AMPK regulates phagophore-to-autophagosome maturation

Autophagy is an important metabolic pathway that can non-selectively recycle cellular material or lead to targeted degradation of protein aggregates or damaged organelles. Autophagosome formation starts with autophagy factors accumulating on lipid vesicles containing ATG9. These phagophores attach to donor membranes, expand via ATG2-mediated lipid transfer, capture cargo, and mature into autophagosomes, ultimately fusing with lysosomes for their degradation. Autophagy can be activated by nutrient stress, for example, by a reduction in the cellular levels of amino acids. In contrast, how autophagy is regulated by low cellular ATP levels via the AMP-activated protein kinase (AMPK), an important therapeutic target, is less clear. Using live-cell imaging and an automated image analysis pipeline, we systematically dissect how nutrient starvation regulates autophagosome biogenesis. We demonstrate that glucose starvation downregulates autophagosome maturation by AMPK-mediated inhibition of phagophore tethering to donor membrane. Our results clarify AMPKs regulatory role in autophagy and highlight its potential as a therapeutic target to reduce autophagy.

Compartmentalized Cytoplasmic Flows Direct Protein Transport to the Cell's Leading Edge

Inside the cell, proteins essential for signaling, morphogenesis, and migration navigate complex pathways, typically via vesicular trafficking or microtubule-driven mechanisms 1-3 . However, the process by which soluble cytoskeletal monomers maneuver through the cytoplasm's ever-changing environment to reach their destinations without using these pathways remains unknown. 4-6 Here, we show that actin cytoskeletal treadmilling leads to the formation of a semi-permeable actin-myosin barrier, creating a specialized compartment separated from the rest of the cell body that directs proteins toward the cell edge by advection, diffusion facilitated by fluid flow. Contraction at this barrier generates a molecularly non-specific fluid flow that transports actin, actin-binding proteins, adhesion proteins, and even inert proteins forward. The local curvature of the barrier specifically targets these proteins toward protruding edges of the leading edge, sites of new filament growth, effectively coordinating protein distribution with cellular dynamics. Outside this compartment, diffusion remains the primary mode of protein transport, contrasting sharply with the directed advection within. This discovery reveals a novel protein transport mechanism that redefines the front of the cell as a pseudo-organelle, actively orchestrating protein mobilization for cellular front activities such as protrusion and adhesion. By elucidating a new model of protein dynamics at the cellular front, this work contributes a critical piece to the puzzle of how cells adapt their internal structures for targeted and rapid response to extracellular cues. The findings challenge the current understanding of intracellular transport, suggesting that cells possess highly specialized and previously unrecognized organizational strategies for managing protein distribution efficiently, providing a new framework for understanding the cellular architecture's role in rapid response and adaptation to environmental changes.

Dual DNA/RNA-binding factor regulates dynamics of hnRNP splicing condensates

Despite decades of research, mechanisms by which co-transcriptional alternative splicing events are targeted to the correct genomic locations to drive cell fate decisions remain unknown. By combining structural and molecular approaches, we define a new mechanism by which an essential transcription factor (TF) targets co-transcriptional splicing through physical and functional interaction with RNA and RNA binding proteins (RBPs). We show that an essential TF co-transcriptionally regulates sex-specific alternative splicing by directly interacting with a subset of target RNAs on chromatin and modulating the dynamics of hnRNPA2 homolog nuclear splicing condensates.

u-track3D: Measuring, navigating, and validating dense particle trajectories in three dimensions

We describe u-track3D, a software package that extends the versatile u-track framework established in 2D to address the specific challenges of 3D particle tracking. First, we present the performance of the new package in quantifying a variety of intracellular dynamics imaged by multiple 3D microcopy platforms and on the standard 3D test dataset of the particle tracking challenge. These analyses indicate that u-track3D presents a tracking solution that is competitive to both conventional and deep-learning-based approaches. We then present the concept of dynamic region of interest (dynROI), which allows an experimenter to interact with dynamic 3D processes in 2D views amenable to visual inspection. Third, we present an estimator of trackability that automatically defines a score for every trajectory, thereby overcoming the challenges of trajectory validation by visual inspection. With these combined strategies, u-track3D provides a complete framework for unbiased studies of molecular processes in complex volumetric sequences.

Transcriptional reprogramming by mutated IRF4 in lymphoma

Disease-causing mutations in genes encoding transcription factors (TFs) can affect TF interactions with their cognate DNA-binding motifs. Whether and how TF mutations impact upon the binding to TF composite elements (CE) and the interaction with other TFs is unclear. Here, we report a distinct mechanism of TF alteration in human lymphomas with perturbed B cell identity, in particular classic Hodgkin lymphoma. It is caused by a recurrent somatic missense mutation c.295 T > C (p.Cys99Arg; p.C99R) targeting the center of the DNA-binding domain of Interferon Regulatory Factor 4 (IRF4), a key TF in immune cells. IRF4-C99R fundamentally alters IRF4 DNA-binding, with loss-of-binding to canonical IRF motifs and neomorphic gain-of-binding to canonical and non-canonical IRF CEs. IRF4-C99R thoroughly modifies IRF4 function by blocking IRF4-dependent plasma cell induction, and up-regulates disease-specific genes in a non-canonical Activator Protein-1 (AP-1)-IRF-CE (AICE)-dependent manner. Our data explain how a single mutation causes a complex switch of TF specificity and gene regulation and open the perspective to specifically block the neomorphic DNA-binding activities of a mutant TF.

Transcription Factor Dynamics: One Molecule at a Time

Cells must tightly regulate their gene expression programs and yet rapidly respond to acute biochemical and biophysical cues within their environment. This information is transmitted to the nucleus through various signaling cascades, culminating in the activation or repression of target genes. Transcription factors (TFs) are key mediators of these signals, binding to specific regulatory elements within chromatin. While live-cell imaging has conclusively proven that TF-chromatin interactions are highly dynamic, how such transient interactions can have long-term impacts on developmental trajectories and disease progression is still largely unclear. In this review, we summarize our current understanding of the dynamic nature of TF functions, starting with a historical overview of early live-cell experiments. We highlight key factors that govern TF dynamics and how TF dynamics, in turn, affect downstream transcriptional bursting. Finally, we conclude with open challenges and emerging technologies that will further our understanding of transcriptional regulation.

Real-time imaging of drug-induced trapping of cellular topoisomerases and poly(ADP-ribose) polymerase 1 at the single-molecule level

Topoisomerases (TOP1, TOP2α, and β) are nuclear enzymes crucial for virtually all aspects of DNA metabolisms. They also are the targets of important anti-tumor chemotherapeutics that act by trapping the otherwise reversible topoisomerase-DNA covalent complex intermediates (TOPccs) that are formed during their catalytic reactions, resulting in long-lived topoisomerase DNA-protein crosslinks (TOP-DPCs) that interfere with DNA transactions. The Poly(ADP-ribose) polymerase (PARP) family protein PARP1 is activated by DNA damage to recruit DNA repair proteins, and PARP inhibitors are another class of commonly used chemotherapeutics, which bind and trap PARP molecules on DNA. To date, the trapping of TOPccs and PARP by their respective inhibitors can only be measured by immune-biochemical methods in cells. Here, we developed an imaging-based approach enabling real-time monitoring of drug-induced trapping of TOPccs and PARP1 in live cells at the single-molecule level. Capitalizing on this approach, we calculated the fraction of self-fluorescence tag-labeled topoisomerases and PARP single-molecules that are trapped by their respective inhibitors in real time. This novel technique should help elucidate the molecular processes that repair TOPcc and PARP trapping and facilitate the development of novel topoisomerase and PARP inhibitor-based therapies.

Sorzano CO. TrackAnalyzer: A Fiji/ImageJ toolbox for a holistic analysis of tracks

Current live-cell imaging techniques make possible the observation of live events and the acquisition of large datasets to characterize the different parameters of the visualized events. They provide new insights into the dynamics of biological processes with unprecedented spatial and temporal resolutions. Here we describe the implementation and application of a new tool called TrackAnalyzer, accessible from Fiji and ImageJ. Our tool allows running semi-automated single-particle tracking (SPT) and subsequent motion classification, as well as quantitative analysis of diffusion and intensity for selected tracks relying on the graphical user interface (GUI) for large sets of temporal images (X-Y-T or X-Y-C-T dimensions). TrackAnalyzer also allows 3D visualization of the results as overlays of either spots, cells or end-tracks over time, along with corresponding feature extraction and further classification according to user criteria. Our analysis workflow automates the following steps: (1) spot or cell detection and filtering, (2) construction of tracks, (3) track classification and analysis (diffusion and chemotaxis), and (4) detailed analysis and visualization of all the outputs along the pipeline. All these analyses are automated and can be run in batch mode for a set of similar acquisitions.

Using single molecule imaging to explore intracellular heterogeneity

Despite more than 100 years of study, it is unclear if the movement of proteins inside the cell is best described as a mosh pit or an exquisitely choreographed dance. Recent studies suggest the latter. Local interactions induce molecular condensates such as liquid-liquid phase separations (LLPSs) or non-liquid, functionally significant molecular aggregates, including synaptic densities, nucleoli, and Amyloid fibrils. Molecular condensates trigger intracellular signaling and drive processes ranging from gene expression to cell division. However, the descriptions of condensates tend to be qualitative and correlative. Here, we indicate how single-molecule imaging and analyses can be applied to quantify condensates. We discuss the pros and cons of different techniques for measuring differences between transient molecular behaviors inside and outside condensates. Finally, we offer suggestions for how imaging and analyses from different time and space regimes can be combined to identify molecular behaviors indicative of condensates within the dynamic high-density intracellular environment.

Unravelling the Mystery inside Cells by Using Single-Molecule Fluorescence Imaging

Live-cell imaging is a powerful technique to study the dynamics and mechanics of various biological molecules like proteins, organelles, DNA, and RNA. With the rapid evolution of optical microscopy, our understanding of how these molecules are implicated in the cells' most critical physiological roles deepens. In this review, we focus on how spatiotemporal nanoscale live-cell imaging at the single molecule level allows for profound contributions towards new discoveries in life science. This review will start by summarizing how single-molecule tracking has been used to analyze membrane dynamics, receptor-ligand interactions, protein-protein interactions, inner- and extra-cellular transport, gene expression/transcription, and whole organelle tracking. We then move on to how current authors are trying to improve single-molecule tracking and overcome current limitations by offering new ways of labeling proteins of interest, multi-channel/color detection, improvements in time-lapse imaging, and new methods and programs to analyze the colocalization and movement of targets. We later discuss how single-molecule tracking can be a beneficial tool used for medical diagnosis. Finally, we wrap up with the limitations and future perspectives of single-molecule tracking and total internal reflection microscopy.

Single-molecule tracking of Nanog and Oct4 in living mouse embryonic stem cells uncovers a feedback mechanism of pluripotency maintenance

Nanog and Oct4 are core transcription factors that form part of a gene regulatory network to regulate hundreds of target genes for pluripotency maintenance in mouse embryonic stem cells (ESCs). To understand their function in the pluripotency maintenance, we visualised and quantified the dynamics of single molecules of Nanog and Oct4 in a mouse ESCs during pluripotency loss. Interestingly, Nanog interacted longer with its target loci upon reduced expression or at the onset of differentiation, suggesting a feedback mechanism to maintain the pluripotent state. The expression level and interaction time of Nanog and Oct4 correlate with their fluctuation and interaction frequency, respectively, which in turn depend on the ESC differentiation status. The DNA viscoelasticity near the Oct4 target locus remained flexible during differentiation, supporting its role either in chromatin opening or a preferred binding to uncondensed chromatin regions. Based on these results, we propose a new negative feedback mechanism for pluripotency maintenance via the DNA condensation state-dependent interplay of Nanog and Oct4.

Using Single Molecule Imaging to Explore Intracellular Heterogeneity

Despite more than 100 years of study, it is unclear if the movement of proteins inside the cell is best described as a mosh pit or an exquisitely choreographed dance. Recent studies suggest the latter. Local interactions induce molecular condensates such as liquid-liquid phase separations (LLPSs) or non-liquid, functionally significant molecular aggregates, including synaptic densities, nucleoli, and Amyloid fibrils. Molecular condensates trigger intracellular signaling and drive processes ranging from gene expression to cell division. However, the descriptions of condensates tend to be qualitative and correlative. Here, we indicate how single-molecule imaging and analyses can be applied to quantify condensates. We discuss the pros and cons of different techniques for measuring differences between transient molecular behaviors inside and outside condensates. Finally, we offer suggestions for how imaging and analyses from different time and space regimes can be combined to identify molecular behaviors indicative of condensates within the dynamic high-density intracellular environment.

Quantitative analysis of autophagy reveals the role of ATG9 and ATG2 in autophagosome formation

Autophagy is a catabolic pathway required for the recycling of cytoplasmic materials. To define the mechanisms underlying autophagy it is critical to quantitatively characterize the dynamic behavior of autophagy factors in living cells. Using a panel of cell lines expressing HaloTagged autophagy factors from their endogenous loci, we analyzed the abundance, single-molecule dynamics, and autophagosome association kinetics of autophagy proteins involved in autophagosome biogenesis. We demonstrate that autophagosome formation is inefficient and ATG2-mediated tethering to donor membranes is a key commitment step in autophagosome formation. Furthermore, our observations support the model that phagophores are initiated by the accumulation of autophagy factors on mobile ATG9 vesicles, and that the ULK1 complex and PI3-kinase form a positive feedback loop required for autophagosome formation. Finally, we demonstrate that the duration of autophagosome biogenesis is ∼110 s. In total, our work provides quantitative insight into autophagosome biogenesis and establishes an experimental framework to analyze autophagy in human cells.

Single-molecule tracking (SMT): a window into live-cell transcription biochemistry

How molecules interact governs how they move. Single-molecule tracking (SMT) thus provides a unique window into the dynamic interactions of biomolecules within live cells. Using transcription regulation as a case study, we describe how SMT works, what it can tell us about molecular biology, and how it has changed our perspective on the inner workings of the nucleus. We also describe what SMT cannot yet tell us and how new technical advances seek to overcome its limitations. This ongoing progress will be imperative to address outstanding questions about how dynamic molecular machines function in live cells.

A multimorphic mutation in IRF4 causes human autosomal dominant combined immunodeficiency

Interferon regulatory factor 4 (IRF4) is a transcription factor (TF) and key regulator of immune cell development and function. We report a recurrent heterozygous mutation in IRF4, p.T95R, causing an autosomal dominant combined immunodeficiency (CID) in seven patients from six unrelated families. The patients exhibited profound susceptibility to opportunistic infections, notably Pneumocystis jirovecii, and presented with agammaglobulinemia. Patients' B cells showed impaired maturation, decreased immunoglobulin isotype switching, and defective plasma cell differentiation, whereas their T cells contained reduced TH17 and TFH populations and exhibited decreased cytokine production. A knock-in mouse model of heterozygous T95R showed a severe defect in antibody production both at the steady state and after immunization with different types of antigens, consistent with the CID observed in these patients. The IRF4T95R variant maps to the TF's DNA binding domain, alters its canonical DNA binding specificities, and results in a simultaneous multimorphic combination of loss, gain, and new functions for IRF4. IRF4T95R behaved as a gain-of-function hypermorph by binding to DNA with higher affinity than IRF4WT. Despite this increased affinity for DNA, the transcriptional activity on IRF4 canonical genes was reduced, showcasing a hypomorphic activity of IRF4T95R. Simultaneously, IRF4T95R functions as a neomorph by binding to noncanonical DNA sites to alter the gene expression profile, including the transcription of genes exclusively induced by IRF4T95R but not by IRF4WT. This previously undescribed multimorphic IRF4 pathophysiology disrupts normal lymphocyte biology, causing human disease.

Single molecule imaging simulations with advanced fluorophore photophysics

Advanced fluorescence imaging techniques such as single-molecule localization microscopy (SMLM) fundamentally rely on the photophysical behavior of the employed fluorophores. This behavior is generally complex and impacts data quality in a subtle manner. A simulation software named Single-Molecule Imaging Simulator (SMIS) is introduced that simulates a widefield microscope and incorporates fluorophores with their spectral and photophysical properties. With SMIS, data collection schemes combining 3D, multicolor, single-particle-tracking or quantitative SMLM can be implemented. The influence of advanced fluorophore characteristics, imaging conditions, and environmental parameters can be evaluated, facilitating the design of real experiments and their proper interpretation.

Single-molecule tracking for studying protein dynamics and target-search mechanism in live cells of S. cerevisiae

Single-molecule tracking (SMT) is a powerful approach to quantify the biophysical parameters of protein dynamics in live cells. Here, we describe a protocol for SMT in live cells of the budding yeast Saccharomyces cerevisiae. We detail how to genetically engineer yeast strains for SMT, how to set up image acquisition parameters, and how different software programs can be used to quantify a variety of biophysical parameters such as diffusion coefficient, residence time, bound fraction, jump angles, and target-search parameters. For complete details on the use and execution of this protocol, please refer to Mehta et al. ¹ and Ball et al..².

Single-molecule tracking of Nodal and Lefty in live zebrafish embryos supports hindered diffusion model

The hindered diffusion model postulates that the movement of a signaling molecule through an embryo is affected by tissue geometry and binding-mediated hindrance, but these effects have not been directly demonstrated in vivo. Here, we visualize extracellular movement and binding of individual molecules of the activator-inhibitor signaling pair Nodal and Lefty in live developing zebrafish embryos using reflected light-sheet microscopy. We observe that diffusion coefficients of molecules are high in extracellular cavities, whereas mobility is reduced and bound fractions are high within cell-cell interfaces. Counterintuitively, molecules nevertheless accumulate in cavities, which we attribute to the geometry of the extracellular space by agent-based simulations. We further find that Nodal has a larger bound fraction than Lefty and shows a binding time of tens of seconds. Together, our measurements and simulations provide direct support for the hindered diffusion model and yield insights into the nanometer-to-micrometer-scale mechanisms that lead to macroscopic signal dispersal.

A feed-forward pathway drives LRRK2 kinase membrane recruitment and activation

Activating mutations in the leucine-rich repeat kinase 2 (LRRK2) cause Parkinson's disease, and previously we showed that activated LRRK2 phosphorylates a subset of Rab GTPases (Steger et al., 2017). Moreover, Golgi-associated Rab29 can recruit LRRK2 to the surface of the Golgi and activate it there for both auto- and Rab substrate phosphorylation. Here, we define the precise Rab29 binding region of the LRRK2 Armadillo domain between residues 360-450 and show that this domain, termed 'site #1,' can also bind additional LRRK2 substrates, Rab8A and Rab10. Moreover, we identify a distinct, N-terminal, higher-affinity interaction interface between LRRK2 phosphorylated Rab8 and Rab10 termed 'site #2' that can retain LRRK2 on membranes in cells to catalyze multiple, subsequent phosphorylation events. Kinase inhibitor washout experiments demonstrate that rapid recovery of kinase activity in cells depends on the ability of LRRK2 to associate with phosphorylated Rab proteins, and phosphorylated Rab8A stimulates LRRK2 phosphorylation of Rab10 in vitro. Reconstitution of purified LRRK2 recruitment onto planar lipid bilayers decorated with Rab10 protein demonstrates cooperative association of only active LRRK2 with phospho-Rab10-containing membrane surfaces. These experiments reveal a feed-forward pathway that provides spatial control and membrane activation of LRRK2 kinase activity.

Stress induced TDP-43 mobility loss independent of stress granules

TAR DNA binding protein 43 (TDP-43) is closely related to the pathogenesis of amyotrophic lateral sclerosis (ALS) and translocates to stress granules (SGs). The role of SGs as aggregation-promoting “crucibles” for TDP-43, however, is still under debate. We analyzed TDP-43 mobility and localization under different stress and recovery conditions using live cell single-molecule tracking and super-resolution microscopy. Besides reduced mobility within SGs, a stress induced decrease of TDP-43 mobility in the cytoplasm and the nucleus was observed. Stress removal led to a recovery of TDP-43 mobility, which strongly depended on the stress duration. ‘Stimulated-emission depletion microscopy’ (STED) and ‘tracking and localization microscopy’ (TALM) revealed not only TDP-43 substructures within stress granules but also numerous patches of slow TDP-43 species throughout the cytoplasm. This work provides insights into the aggregation of TDP-43 in living cells and provide evidence suggesting that TDP-43 oligomerization and aggregation takes place in the cytoplasm separate from SGs.

Amyotrophic Lateral Sclerosis related TDP-43 protein translocates to stress granules with a concomitant reduction in mobility. Here, the authors use single molecule tracking and find a stress-induced reduction in TDP-43 mobility also in the cytoplasm potentially relevant for TDP-43 aggregation.

Classification-based motion analysis of single-molecule trajectories using DiffusionLab

Single-particle tracking is a powerful approach to study the motion of individual molecules and particles. It can uncover heterogeneities that are invisible to ensemble techniques, which places it uniquely among techniques to study mass transport. Analysis of the trajectories obtained with single-particle tracking in inorganic porous hosts is often challenging, because trajectories are short and/or motion is heterogeneous. We present the DiffusionLab software package for motion analysis of such challenging data sets. Trajectories are first classified into populations with similar characteristics to which the motion analysis is tailored in a second step. DiffusionLab provides tools to classify trajectories based on the motion type either with machine learning or manually. It also offers quantitative mean squared displacement analysis of the trajectories. The software can compute the diffusion constant for an individual trajectory if it is sufficiently long, or the average diffusion constant for multiple shorter trajectories. We demonstrate the DiffusionLab approach via the analysis of a simulated data set with motion types frequently observed in inorganic porous hosts, such as zeolites. The software package with graphical user interface and its documentation are freely available.

Single-molecule tracking (SMT) and localization of SRF and MRTF transcription factors during neuronal stimulation and differentiation

In cells, proteins encoded by the same gene do not all behave uniformly but engage in functional subpopulations induced by spatial or temporal segregation. While conventional microscopy has limitations in revealing such spatial and temporal diversity, single-molecule tracking (SMT) microscopy circumvented this problem and allows for high-resolution imaging and quantification of dynamic single-molecule properties. Particularly in the nucleus, SMT has identified specific DNA residence times of transcription factors (TFs), DNA-bound TF fractions and positions of transcriptional hot-spots upon cell stimulation. By contrast to cell stimulation, SMT has not been employed to follow dynamic TF changes along stages of cell differentiation. Herein, we analysed the serum response factor (SRF), a TF involved in the differentiation of many cell types to study nuclear single-molecule dynamics in neuronal differentiation. Our data in living mouse hippocampal neurons show dynamic changes in SRF DNA residence time and SRF DNA-bound fraction between the stages of adhesion, neurite growth and neurite differentiation in axon and dendrites. Using TALM (tracking and localization microscopy), we identified nuclear positions of SRF clusters and observed changes in their numbers and size during differentiation. Furthermore, we show that the SRF cofactor MRTF-A (myocardin-related TF or MKL1) responds to cell activation by enhancing the long-bound DNA fraction. Finally, a first SMT colocalization study of two proteins was performed in living cells showing enhanced SRF/MRTF-A colocalization upon stimulation. In summary, SMT revealed modulation of dynamic TF properties during cell stimulation and differentiation.

Following the tracks: how transcription factor binding dynamics control transcription

Transcription, the process of copying genetic information from DNA to messenger RNA, is regulated by sequence-specific DNA binding proteins known as transcription factors (TFs). Recent advances in single-molecule tracking (SMT) technologies have enabled visualization of individual TF molecules as they diffuse and interact with the DNA in the context of living cells. These SMT studies have uncovered multiple populations of DNA binding events characterized by their distinctive DNA residence times. In this perspective, we review recent insights into how these residence times relate to specific and non-specific DNA binding, as well as the contribution of TF domains on the DNA binding dynamics. We discuss different models that aim to link transient DNA binding by TFs to bursts of transcription and present an outlook for how future advances in microscopy development may broaden our understanding of the dynamics of the molecular steps that underlie transcription activation.

In-vivo Single-Molecule Imaging in Yeast: Applications and Challenges

Single-molecule imaging has gained momentum to quantify the dynamics of biomolecules in live cells, as it provides direct real-time measurements of various cellular activities under their physiological environment. Yeast, a simple and widely used eukaryote, serves as a good model system to quantify single-molecule dynamics of various cellular processes because of its low genomic and cellular complexities, as well as its facile ability to be genetically manipulated. In the past decade, significant developments have been made regarding the intracellular labeling of biomolecules (proteins, mRNA, fatty acids), the microscopy setups to visualize single-molecules and capture their fast dynamics, and the data analysis pipelines to interpret such dynamics. In this review, we summarize the current state of knowledge for the single-molecule imaging in live yeast cells to provide a ready reference for beginners. We provide a comprehensive table to demonstrate how various labs tailored the imaging regimes and data analysis pipelines to estimate various biophysical parameters for a variety of biological processes. Lastly, we present current challenges and future directions for developing better tools and resources for single-molecule imaging in live yeast cells.

Transcription Factor RBPJL Is Able to Repress Notch Target Gene Expression but Is Non-Responsive to Notch Activation

Simple Summary

The transcription factor RBPJ is an integral part of the Notch signaling cascade. RBPJ can function as a coactivator when Notch signaling is activated but acts as a repressor in the absence of a Notch stimulus. Here, we characterized the function of RBPJL, a pancreas-specific paralog of RBPJ. Upon depletion of RBPJ using CRISPR/Cas9, we observed specific upregulation of Notch target gene expression. Reconstitution with RBPJL can compensate for the lack of RBPJ function in the repression of Notch target genes but is not able to mediate the Notch-dependent activation of gene expression. On the molecular level, we identified a limited capacity of RBPJL to interact with activated Notch1–4.

Abstract

The Notch signaling pathway is an evolutionary conserved signal transduction cascade present in almost all tissues and is required for embryonic and postnatal development, as well as for stem cell maintenance, but it is also implicated in tumorigenesis including pancreatic cancer and leukemia. The transcription factor RBPJ forms a coactivator complex in the presence of a Notch signal, whereas it represses Notch target genes in the absence of a Notch stimulus. In the pancreas, a specific paralog of RBPJ, called RBPJL, is expressed and found as part of the heterotrimeric PTF1-complex. However, the function of RBPJL in Notch signaling remains elusive. Using molecular modeling, biochemical and functional assays, as well as single-molecule time-lapse imaging, we show that RBPJL and RBPJ, despite limited sequence homology, possess a high degree of structural similarity. RBPJL is specifically expressed in the exocrine pancreas, whereas it is mostly undetectable in pancreatic tumour cell lines. Importantly, RBPJL is not able to interact with Notch−1 to −4 and it does not support Notch-mediated transactivation. However, RBPJL can bind to canonical RBPJ DNA elements and shows migration dynamics comparable to that of RBPJ in the nuclei of living cells. Importantly, RBPJL is able to interact with SHARP/SPEN, the central corepressor of the Notch pathway. In line with this, RBPJL is able to fully reconstitute transcriptional repression at Notch target genes in cells lacking RBPJ. Together, RBPJL can act as an antagonist of RBPJ, which renders cells unresponsive to the activation of Notch.

Altering transcription factor binding reveals comprehensive transcriptional kinetics of a basic gene

Transcription is a vital process activated by transcription factor (TF) binding. The active gene releases a burst of transcripts before turning inactive again. While the basic course of transcription is well understood, it is unclear how binding of a TF affects the frequency, duration and size of a transcriptional burst. We systematically varied the residence time and concentration of a synthetic TF and characterized the transcription of a synthetic reporter gene by combining single molecule imaging, single molecule RNA-FISH, live transcript visualisation and analysis with a novel algorithm, Burst Inference from mRNA Distributions (BIRD). For this well-defined system, we found that TF binding solely affected burst frequency and variations in TF residence time had a stronger influence than variations in concentration. This enabled us to device a model of gene transcription, in which TF binding triggers multiple successive steps before the gene transits to the active state and actual mRNA synthesis is decoupled from TF presence. We quantified all transition times of the TF and the gene, including the TF search time and the delay between TF binding and the onset of transcription. Our quantitative measurements and analysis revealed detailed kinetic insight, which may serve as basis for a bottom-up understanding of gene regulation.