Probing cellular processes by long-term live imaging--historic problems and current solutions

Combined ion beam irradiation platform and 3D fluorescence microscope for cellular cancer research

To improve particle radiotherapy, we need a better understanding of the biology of radiation effects, particularly in heavy ion radiation therapy, where global responses are observed despite energy deposition in only a subset of cells. Here, we integrated a high-speed swept confocally-aligned planar excitation (SCAPE) microscope into a focused ion beam irradiation platform to allow real-time 3D structural and functional imaging of living biological samples during and after irradiation. We demonstrate dynamic imaging of the acute effects of irradiation on 3D cultures of U87 human glioblastoma cells, revealing characteristic changes in cellular movement and intracellular calcium signaling following ionizing irradiation.

Dynamics of astrocytes Ca2+ signaling: a low-cost fluorescence customized system for 2D cultures

In an effort to help reduce the costs of fluorescence microscopy and expand the use of this valuable technique, we developed a low-cost platform capable of visualising and analysing the spatio-temporal dynamics of intracellular Ca2+ signalling in astrocytes. The created platform, consisting of a specially adapted fluorescence microscope and a data analysis procedure performed with Imagej Fiji software and custom scripts, allowed us to detect relative changes of intracellular Ca2+ ions in astrocytes. To demonstrate the usefulness of the workflow, we applied the methodology to several in vitro astrocyte preparations, specifically immortalised human astrocyte cells and wild-type mouse cells. To demonstrate the reliability of the procedure, analyses were conducted by stimulating astrocyte activity with the agonist dihydroxyphenylglycine (DHPG), alone or in the presence of the antagonist 2-methyl-6-phenylethyl-pyridine (MPEP).

ALFI: Cell cycle phenotype annotations of label-free time-lapse imaging data from cultured human cells

Detecting and tracking multiple moving objects in a video is a challenging task. For living cells, the task becomes even more arduous as cells change their morphology over time, can partially overlap, and mitosis leads to new cells. Differently from fluorescence microscopy, label-free techniques can be easily applied to almost all cell lines, reducing sample preparation complexity and phototoxicity. In this study, we present ALFI, a dataset of images and annotations for label-free microscopy, made publicly available to the scientific community, that notably extends the current panorama of expertly labeled data for detection and tracking of cultured living nontransformed and cancer human cells. It consists of 29 time-lapse image sequences from HeLa, U2OS, and hTERT RPE-1 cells under different experimental conditions, acquired by differential interference contrast microscopy, for a total of 237.9 hours. It contains various annotations (pixel-wise segmentation masks, object-wise bounding boxes, tracking information). The dataset is useful for testing and comparing methods for identifying interphase and mitotic events and reconstructing their lineage, and for discriminating different cellular phenotypes.

Uncovering diffusive states of the yeast membrane protein, Pma1, and how labeling method can change diffusive behavior

We present and analyze video-microscopy-based single-particle-tracking measurements of the budding yeast (Saccharomyces cerevisiae) membrane protein, Pma1, fluorescently labeled either by direct fusion to the switchable fluorescent protein, mEos3.2, or by a novel, light-touch, labeling scheme, in which a 5 amino acid tag is directly fused to the C-terminus of Pma1, which then binds mEos3.2. The track diffusivity distributions of these two populations of single-particle tracks differ significantly, demonstrating that labeling method can be an important determinant of diffusive behavior. We also applied perturbation expectation maximization (pEMv2) (Koo and Mochrie in Phys Rev E 94(5):052412, 2016), which sorts trajectories into the statistically optimum number of diffusive states. For both TRAP-labeled Pma1 and Pma1-mEos3.2, pEMv2 sorts the tracks into two diffusive states: an essentially immobile state and a more mobile state. However, the mobile fraction of Pma1-mEos3.2 tracks is much smaller ([Formula: see text]) than the mobile fraction of TRAP-labeled Pma1 tracks ([Formula: see text]). In addition, the diffusivity of Pma1-mEos3.2's mobile state is several times smaller than the diffusivity of TRAP-labeled Pma1's mobile state. Thus, the two different labeling methods give rise to very different overall diffusive behaviors. To critically assess pEMv2's performance, we compare the diffusivity and covariance distributions of the experimental pEMv2-sorted populations to corresponding theoretical distributions, assuming that Pma1 displacements realize a Gaussian random process. The experiment-theory comparisons for both the TRAP-labeled Pma1 and Pma1-mEos3.2 reveal good agreement, bolstering the pEMv2 approach.

Live Cell Imaging of Dynamic Processes in Adult Zebrafish Retinal Cross-Section Cultures

Following retinal injury, zebrafish possess the remarkable capacity to endogenously regenerate lost retinal neurons from Müller glia-derived neuronal progenitor cells. Additionally, neuronal cell types that are undamaged and persist in the injured retina are also produced. Thus, the zebrafish retina is an excellent system to study the integration of all neuronal cell types into an existing neuronal circuit. The few studies that examined axonal/dendritic outgrowth and the establishment of synaptic contacts by regenerated neurons predominantly utilized fixed tissue samples. We recently established a flatmount culture model to monitor Müller glia nuclear migration in real time by two-photon microscopy. However, in retinal flatmounts, z-stacks of the entire retinal z-dimension have to be acquired to image cells that extend through parts or the entirety of the neural retina, such as bipolar cells and Müller glia, respectively. Cellular processes with fast kinetics might thus be missed. Therefore, we generated a retinal cross-section culture from light-damaged zebrafish to image the entire Müller glia in one z-plane. Isolated dorsal retinal hemispheres were cut into two dorsal quarters and mounted with the cross-section view facing the coverslips of culture dishes, which allowed monitoring Müller glia nuclear migration using confocal microscopy. Confocal imaging of cross-section cultures is ultimately also applicable to live cell imaging of axon/dendrite formation of regenerated bipolar cells, while the flatmount culture model will be more suitable to monitor axon outgrowth of ganglion cells.

Monitoring Virus-Induced Stress Granule Dynamics Using Long-Term Live-Cell Imaging

The integrated stress response is a highly regulated signaling cascade that allows cells to react to a variety of external and internal stimuli. Activation of different stress-responsive kinases leads to the phosphorylation of their common downstream target, the eukaryotic translation initiation factor 2 alpha (eIF2α), which is a critical component of functional translation preinitiation complexes. As a consequence, stalled ribonucleoprotein complexes accumulate in the cytoplasm and condense into microscopically visible cytoplasmic stress granules (SGs). Over the past years, numerous microscopy approaches have been developed to study the spatiotemporal control of SG formation in response to a variety of stressors. Here, we apply long-term live-cell microscopy to monitor the dynamic cellular stress response triggered by infection with chronic hepatitis C virus (HCV) at single-cell level and study the behavior of infected cells that repeatedly switch between a stressed and unstressed state. We describe in detail the engineering of fluorescent SG-reporter cells expressing enhanced yellow fluorescent protein (YFP)-tagged T cell internal antigen 1 (TIA-1) using lentiviral delivery, as well as the production of mCherry-tagged HCV trans-complemented particles, which allow live tracking of SG assembly and disassembly, SG number and size in single infected cells over time.

Quantitative analysis of neuronal mitochondrial movement reveals patterns resulting from neurotoxicity of rotenone and 6-hydroxydopamine

Alterations in mitochondrial dynamics, including their intracellular trafficking, are common early manifestations of neuronal degeneration. However, current methodologies used to study mitochondrial trafficking events rely on parameters that are primarily altered in later stages of neurodegeneration. Our objective was to establish a reliable applied statistical analysis to detect early alterations in neuronal mitochondrial trafficking. We propose a novel quantitative analysis of mitochondria trajectories based on innovative movement descriptors, including straightness, efficiency, anisotropy, and kurtosis. We evaluated time- and dose-dependent alterations in trajectory descriptors using biological data from differentiated SH-SY5Y cells treated with the mitochondrial toxicants 6-hydroxydopamine and rotenone. MitoTracker Red CMXRos-labelled mitochondria movement was analyzed by total internal reflection fluorescence microscopy followed by computational modelling to describe the process. Based on the aforementioned trajectory descriptors, this innovative analysis of mitochondria trajectories provides insights into mitochondrial movement characteristics and can be a consistent and sensitive method to detect alterations in mitochondrial trafficking occurring in the earliest time points of neurodegeneration.

Multicolor 3D Confocal Imaging of Thick Tissue Sections

In multicellular organisms, most physiological and pathological processes involve an interplay between various cells and molecules that act both locally and systemically. To understand how these complex and dynamic processes occur in time and space, imaging techniques are key. Advances in tissue processing techniques and microscopy now allow us to probe these processes at a large scale and at the same time at a level of detail previously unachievable. Indeed, it is now possible to reliably quantify multiple protein expression levels at single-cell resolution in whole organs using three-dimensional fluorescence imaging techniques. Here we describe a method to prepare adult mouse bone tissue for multiplexed confocal imaging of thick tissue sections. Up to eight different fluorophores can be multiplexed using this technique and spectrally resolved using standard confocal microscopy. The optical clearing method described allows detection of these fluorophores up to a depth of >700 μm in the far-red. Although the method was initially developed for bone tissue imaging, we have successfully applied it to several other tissue types.

Long-Term Mg2+ Imaging in Live Cells with a Targetable Fluorescent Probe

Living cells dynamically change their morphology and function according to the cell cycle. Long-term observations of living cells are privileged when we spy the unique, cell cycle-driven molecular events, which cannot be obtained from short-term ones. Mg²⁺, a metal ion abundant in cells, has been shown to be involved in a variety of physiological phenomena by noninvasive cellular observation using fluorescence microscopy. However, long-term observation of Mg²⁺ in cells has been a great challenge. Herein, we present a protocol for the long-term microscopic imaging of intracellular Mg²⁺ levels using a small molecule-protein hybrid fluorescent probe we developed.

Advances in visualizing transcription factor - DNA interactions

At the heart of the transcription process is the specific interaction between transcription factors (TFs) and their target DNA sequences. Decades of molecular biology research have led to unprecedented insights into how TFs access the genome to regulate transcription. In the last 20 years, advances in microscopy have enabled scientists to add imaging as a powerful tool in probing two specific aspects of TF-DNA interactions: structure and dynamics. In this review, we examine how applications of diverse imaging technologies can provide structural and dynamic information that complements insights gained from molecular biology assays. As a case study, we discuss how applications of advanced imaging techniques have reshaped our understanding of TF behavior across the cell cycle, leading to a rethinking in the field of mitotic bookmarking.

Time-Gated FRET Nanoprobes for Autofluorescence-Free Long-Term In Vivo Imaging of Developing Zebrafish

The zebrafish is an important vertebrate model for disease, drug discovery, toxicity, embryogenesis, and neuroscience. In vivo fluorescence microscopy can reveal cellular and subcellular details down to the molecular level with fluorescent proteins (FPs) currently the main tool for zebrafish imaging. However, long maturation times, low brightness, photobleaching, broad emission spectra, and sample autofluorescence are disadvantages that cannot be easily overcome by FPs. Here, a bright and photostable terbium-to-quantum dot (QD) Förster resonance energy transfer (FRET) nanoprobe with narrow and tunable emission bands for intracellular in vivo imaging is presented. The long photoluminescence (PL) lifetime enables time-gated (TG) detection without autofluorescence background. Intracellular four-color multiplexing with a single excitation wavelength and in situ assembly and FRET to mCherry demonstrate the versatility of the TG-FRET nanoprobes and the possibility of in vivo bioconjugation to FPs and combined nanoprobe-FP FRET sensing. Upon injection at the one-cell stage, FRET nanoprobes can be imaged in developing zebrafish embryos over seven days with toxicity similar to injected RNA and strongly improved signal-to-background ratios compared to non-TG imaging. This work provides a strategy for advancing in vivo fluorescence imaging applications beyond the capabilities of FPs.

Towards smart biomanufacturing: a perspective on recent developments in industrial measurement and monitoring technologies for bio-based production processes

The biomanufacturing industry has now the opportunity to upgrade its production processes to be in harmony with the latest industrial revolution. Technology creates capabilities that enable smart manufacturing while still complying with unfolding regulations. However, many biomanufacturing companies, especially in the biopharma sector, still have a long way to go to fully benefit from smart manufacturing as they first need to transition their current operations to an information-driven future. One of the most significant obstacles towards the implementation of smart biomanufacturing is the collection of large sets of relevant data. Therefore, in this work, we both summarize the advances that have been made to date with regards to the monitoring and control of bioprocesses, and highlight some of the key technologies that have the potential to contribute to gathering big data. Empowering the current biomanufacturing industry to transition to Industry 4.0 operations allows for improved productivity through information-driven automation, not only by developing infrastructure, but also by introducing more advanced monitoring and control strategies.

Using confocal imaging approaches to understand the structure and function of osteocytes and the lacunocanalicular network

Although overlooked in the past, osteocytes have come to the forefront of skeletal biology and are now recognized as a key cell type that integrates hormonal, mechanical and other signals to control bone mass through regulation of both osteoblast and osteoclast activity. With the surge of recent interest in osteocytes as bone regulatory cells and the discovery that they also function as endocrine regulators of phosphate homeostasis, there has been renewed interest in understanding the structure and function of these unique and relatively inaccessible cells. Osteocytes are embedded within the mineralized bone matrix and are housed within a complex lacunocanalicular system which connects them with the circulation and with other organ systems. This has presented unique challenges for imaging these cells. This review summarizes recent advances in confocal imaging approaches for visualizing osteocytes and their lacunocanalicular networks in both living and fixed bone specimens and discusses how computational approaches can be combined with live and fixed cell imaging techniques to generate quantitative outputs and predictive models. The integration of advanced imaging with computational approaches promises to lead to a more in depth understanding of the structure and function of osteocyte networks and the lacunocanalicular system in the healthy and aging state as well as in pathological conditions in bone.

Microfluidic Immunoassays for Time-Resolved Measurement of Protein Secretion from Single Cells

Measurement of humoral factors secreted from cells has served as an indispensable method to monitor the states of a cell ensemble because humoral factors play crucial roles in cell-cell interaction and aptly reflect the states of individual cells. Although a cell ensemble consisting of a large number of cells has conventionally been the object of such measurements, recent advances in microfluidic technology together with highly sensitive immunoassays have enabled us to quantify secreted humoral factors even from individual cells in either a population or a temporal context. Many groups have reported various miniaturized platforms for immunoassays of proteins secreted from single cells. This review focuses on the current status of time-resolved assay platforms for protein secretion with single-cell resolution. We also discuss future perspectives of time-resolved immunoassays from the viewpoint of systems biology.

Resolving Single-Nanoconstruct Dynamics during Targeting and Nontargeting Live-Cell Membrane Interactions

This paper describes how differences in the dynamics of targeting and nontargeting constructs can provide information on nanoparticle (NP)-cell interactions. We probed translational and rotational dynamics of functionalized Au nanostar (AuNS) nanoconstructs interacting with cells in serum-containing medium. We found that AuNS with targeting ligands had a larger dynamical footprint and faster rotational speed on cell membranes expressing human epidermal growth factor receptor 2 (HER-2) receptors compared to that of AuNS with nontargeting ligands. Targeting and nontargeting nanoconstructs displayed distinct membrane dynamics despite their similar protein adsorption profiles, which suggests that targeted interactions are preserved even in the presence of a protein corona. The high sensitivity of single-NP dynamics can be used to compare different nanoconstruct properties (such as NP size, shape, and surface chemistry) to improve their design as delivery vehicles.

Correlation of Capacitance and Microscopy Measurements Using Image Processing for a Lab-on-CMOS Microsystem

We present a capacitance sensor chip developed in a 0.35-μm complementary metal-oxide-semiconductor process for monitoring biological cell viability and proliferation. The chip measures the cell-to-substrate binding through capacitance-to-frequency conversion with a sensitivity of 590 kHz/fF. In vitro experiments with two human ovarian cancer cell lines (CP70 and A2780) were performed and showed the ability to track cell viability in realtime over three days. An imaging platform was developed to provide time-lapse images of the sensor surface, which allowed for concurrent visual and capacitance observation of the cells. The results showed the ability to detect single-cell binding events and changes in cell morphology. Image processing was performed to estimate the cell coverage of sensor electrodes, showing good linear correlation and providing a sensor gain of 1.28 ± 0.29 aF/μm², which agrees with values reported in the literature. The device is designed for unsupervised operation with minimal packaging requirements. Only a microcontroller is required for readout, making it suitable for applications outside the traditional laboratory setting.

CytoPacq: a web-interface for simulating multi-dimensional cell imaging

MOTIVATION

Objective assessment of bioimage analysis methods is an essential step towards understanding their robustness and parameter sensitivity, calling for the availability of heterogeneous bioimage datasets accompanied by their reference annotations. Because manual annotations are known to be arduous, highly subjective and barely reproducible, numerous simulators have emerged over past decades, generating synthetic bioimage datasets complemented with inherent reference annotations. However, the installation and configuration of these tools generally constitutes a barrier to their widespread use.

RESULTS

We present a modern, modular web-interface, CytoPacq, to facilitate the generation of synthetic benchmark datasets relevant for multi-dimensional cell imaging. CytoPacq poses a user-friendly graphical interface with contextual tooltips and currently allows a comfortable access to various cell simulation systems of fluorescence microscopy, which have already been recognized and used by the scientific community, in a straightforward and self-contained form.

AVAILABILITY AND IMPLEMENTATION

CytoPacq is a publicly available online service running at https://cbia.fi.muni.cz/simulator. More information about it as well as examples of generated bioimage datasets are available directly through the web-interface.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Ptychographic imaging of NaD1 induced yeast cell death

Characterising and understanding the mechanisms involved in cell death are especially important to combating threats to human health, particularly for the study of antimicrobial peptides and their effectiveness against pathogenic fungi. However, imaging these processes often relies on the use of synthetic molecules which bind to specific cellular targets to produce contrast. Here we study yeast cell death, induced by the anti-fungal peptide, NaD1. By treating yeast as a model organism we aim to understand anti-fungal cell death processes without relying on sample modification. Using a quantitative phase imaging technique, ptychography, we were able to produce label free images of yeast cells during death and use them to investigate the mode of action of NaD1. Using this technique we were able to identify a significant phase shift which provided a clear signature of yeast cell death. Additionally, ptychography identifies cell death much earlier than a comparative fluorescence study, providing new insights into the cellular changes that occur during cell death. The results indicate ptychography has great potential as a means of providing additional information about cellular processes which otherwise may be masked by indirect labelling approaches.

Cytoplasmic Protein Imaging with Mid-Infrared Photothermal Microscopy: Cellular Dynamics of Live Neurons and Oligodendrocytes

Mid-infrared photothermal microscopy has been suggested as an alternative to conventional infrared microscopy because in addition to the inherent chemical contrast available upon vibrational excitation, it can feasibly achieve spatial resolution at the submicrometer level. Furthermore, it has substantial potential for real-time bioimaging for the observation of cellular dynamics without photodamage or photobleaching of fluorescent labels. We performed real-time imaging of oligodendrocytes to investigate cellular dynamics throughout the life cycle of a cell, revealing details of cell division and apoptosis, as well as cellular migration. In the case of live neurons, we observed a photothermal contrast associated with traveling protein complexes on an axon, which correspond to the transport of vesicles from the cell body to the dendritic branches of the neuron through the cytoskeleton. We anticipate that mid-infrared photothermal imaging will be of great use for gaining insights into the field of biophysical science, especially with regard to cellular dynamics and functions.

A fully-automated, robust, and versatile algorithm for long-term budding yeast segmentation and tracking

Live cell time-lapse microscopy, a widely-used technique to study gene expression and protein dynamics in single cells, relies on segmentation and tracking of individual cells for data generation. The potential of the data that can be extracted from this technique is limited by the inability to accurately segment a large number of cells from such microscopy images and track them over long periods of time. Existing segmentation and tracking algorithms either require additional dyes or markers specific to segmentation or they are highly specific to one imaging condition and cell morphology and/or necessitate manual correction. Here we introduce a fully automated, fast and robust segmentation and tracking algorithm for budding yeast that overcomes these limitations. Full automatization is achieved through a novel automated seeding method, which first generates coarse seeds, then automatically fine-tunes cell boundaries using these seeds and automatically corrects segmentation mistakes. Our algorithm can accurately segment and track individual yeast cells without any specific dye or biomarker. Moreover, we show how existing channels devoted to a biological process of interest can be used to improve the segmentation. The algorithm is versatile in that it accurately segments not only cycling cells with smooth elliptical shapes, but also cells with arbitrary morphologies (e.g. sporulating and pheromone treated cells). In addition, the algorithm is independent of the specific imaging method (bright-field/phase) and objective used (40X/63X/100X). We validate our algorithm's performance on 9 cases each entailing a different imaging condition, objective magnification and/or cell morphology. Taken together, our algorithm presents a powerful segmentation and tracking tool that can be adapted to numerous budding yeast single-cell studies.

3-D Quantification of Filopodia in Motile Cancer Cells

We present a 3D bioimage analysis workflow to quantitatively analyze single, actin-stained cells with filopodial protrusions of diverse structural and temporal attributes, such as number, length, thickness, level of branching, and lifetime, in time-lapse confocal microscopy image data. Our workflow makes use of convolutional neural networks trained using real as well as synthetic image data, to segment the cell volumes with highly heterogeneous fluorescence intensity levels and to detect individual filopodial protrusions, followed by a constrained nearest-neighbor tracking algorithm to obtain valuable information about the spatio-temporal evolution of individual filopodia. We validated the workflow using real and synthetic 3-D time-lapse sequences of lung adenocarcinoma cells of three morphologically distinct filopodial phenotypes and show that it achieves reliable segmentation and tracking performance, providing a robust, reproducible and less time-consuming alternative to manual analysis of the 3D+t image data.

Analysis of Cell Lineage Trees by Exact Bayesian Inference Identifies Negative Autoregulation of Nanog in Mouse Embryonic Stem Cells

Many cellular effectors of pluripotency are dynamically regulated. In principle, regulatory mechanisms can be inferred from single-cell observations of effector activity across time. However, rigorous inference techniques suitable for noisy, incomplete, and heterogeneous data are lacking. Here, we introduce stochastic inference on lineage trees (STILT), an algorithm capable of identifying stochastic models that accurately describe the quantitative behavior of cell fate markers observed using time-lapse microscopy data collected from proliferating cell populations. STILT performs exact Bayesian parameter inference and stochastic model selection using a particle-filter-based algorithm. We use STILT to investigate the autoregulation of Nanog, a heterogeneously expressed core pluripotency factor, in mouse embryonic stem cells. STILT rejects the possibility of positive Nanog autoregulation with high confidence; instead, model predictions indicate weak negative feedback. We use STILT for rational experimental design and validate model predictions using novel experimental data. STILT is available for download as an open source framework from http://www.imsb.ethz.ch/research/claassen/Software/stilt---stochastic-inference-on-lineage-trees.html.

FiloGen: A Model-Based Generator of Synthetic 3-D Time-Lapse Sequences of Single Motile Cells With Growing and Branching Filopodia

The existence of diverse image datasets accompanied by reference annotations is a crucial prerequisite for an objective benchmarking of bioimage analysis methods. Nevertheless, such a prerequisite is hard to satisfy for time lapse, multidimensional fluorescence microscopy image data, manual annotations of which are laborious and often impracticable. In this paper, we present a simulation system capable of generating 3-D time-lapse sequences of single motile cells with filopodial protrusions of user-controlled structural and temporal attributes, such as the number, thickness, length, level of branching, and lifetime of filopodia, accompanied by inherently generated reference annotations. The proposed simulation system involves three globally synchronized modules, each being responsible for a separate task: the evolution of filopodia on a molecular level, linear elastic deformation of the entire cell with filopodia, and the synthesis of realistic, time-coherent cell texture. Its flexibility is demonstrated by generating multiple synthetic 3-D time-lapse sequences of single lung cancer cells of two different phenotypes, qualitatively and quantitatively resembling their real counterparts acquired using a confocal fluorescence microscope.

Automated Microfluidic System for Dynamic Stimulation and Tracking of Single Cells

Dynamic environments determine cell fate decisions and function. Understanding the relationship between extrinsic signals on cellular responses and cell fate requires the ability to dynamically change environmental inputs in vitro, while continuously observing individual cells over extended periods of time. This is challenging for nonadherent cells, such as hematopoietic stem and progenitor cells, because media flow displaces and disturbs such cells, preventing culture and tracking of single cells. Here, we present a programmable microfluidic system designed for the long-term culture and time-lapse imaging of nonadherent cells in dynamically changing cell culture conditions without losing track of individual cells. The dynamic, valve-controlled design permits targeted seeding of cells in up to 48 independently controlled culture chambers, each providing sufficient space for long-term cell colony expansion. Diffusion-based media exchange occurs rapidly and minimizes displacement of cells and eliminates shear stress. The chip was successfully tested with long-term culture and tracking of primary hematopoietic stem and progenitor cells, and murine embryonic stem cells. This system will have important applications to analyze dynamic signaling inputs controlling fate choices.

Lineage marker synchrony in hematopoietic genealogies refutes the PU.1/GATA1 toggle switch paradigm

Molecular regulation of cell fate decisions underlies health and disease. To identify molecules that are active or regulated during a decision, and not before or after, the decision time point is crucial. However, cell fate markers are usually delayed and the time of decision therefore unknown. Fortunately, dividing cells induce temporal correlations in their progeny, which allow for retrospective inference of the decision time point. We present a computational method to infer decision time points from correlated marker signals in genealogies and apply it to differentiating hematopoietic stem cells. We find that myeloid lineage decisions happen generations before lineage marker onsets. Inferred decision time points are in agreement with data from colony assay experiments. The levels of the myeloid transcription factor PU.1 do not change during, but long after the predicted lineage decision event, indicating  that the PU.1/GATA1 toggle switch paradigm cannot explain the initiation of early myeloid lineage choice.

Stem/Stromal Cells for Treatment of Kidney Injuries With Focus on Preclinical Models

Within the last years, the use of stem cells (embryonic, induced pluripotent stem cells, or hematopoietic stem cells), Progenitor cells (e.g., endothelial progenitor cells), and most intensely mesenchymal stromal cells (MSC) has emerged as a promising cell-based therapy for several diseases including nephropathy. For patients with end-stage renal disease (ESRD), dialysis or finally organ transplantation are the only therapeutic modalities available. Since ESRD is associated with a high healthcare expenditure, MSC therapy represents an innovative approach. In a variety of preclinical and clinical studies, MSC have shown to exert renoprotective properties, mediated mainly by paracrine effects, immunomodulation, regulation of inflammation, secretion of several trophic factors, and possibly differentiation to renal precursors. However, studies are highly diverse; thus, knowledge is still limited regarding the exact mode of action, source of MSC in comparison to other stem cell types, administration route and dose, tracking of cells and documentation of therapeutic efficacy by new imaging techniques and tissue visualization. The aim of this review is to provide a summary of published studies of stem cell therapy in acute and chronic kidney injury, diabetic nephropathy, polycystic kidney disease, and kidney transplantation. Preclinical studies with allogeneic or xenogeneic cell therapy were first addressed, followed by a summary of clinical trials carried out with autologous or allogeneic hMSC. Studies were analyzed with respect to source of cell type, mechanism of action etc.

Analysis of cardiac stem cell self-renewal dynamics in serum-free medium by single cell lineage tracking

Cardiac colony forming unit-fibroblasts (cCFU-F) are a population of stromal cells residing within the SCA1⁺/PDGFRα⁺/CD31^- fraction of adult mouse hearts, and which have functional characteristics akin to bone marrow mesenchymal stem cells. We hypothesise that they participate in cardiac homeostasis and repair through their actions as lineage progenitors and paracrine signaling hubs. However, cCFU-F are rare and there are no specific markers for these cells, making them challenging to study. cCFU can self-renew in vitro, although the common use of serum has made it difficult to identify cytokines that maintain lineage identity and self-renewal ability. Cell heterogeneity is an additional confounder as cCFU-F cultures are metastable. Here, we address these limitations by identifying serum-free medium (SFM) for growth, and by using cCFU-F isolated from Pdgfra^GFP/+ mice to record fate outcomes, morphology and PDGFRα expression for hundreds of single cells over time. We show that SFM supplemented with basic fibroblast growth factor, transforming growth factor-β and platelet-derived growth factor, enhanced cCFU-F colony formation and long-term self-renewal, while maintaining cCFU-F potency. cCFU-F cultured in SFM maintained a higher proportion of PDGFRα⁺ cells, a marker of self-renewing cCFU-F, by increasing Pdgfra-GFP⁺ divisions and reducing the probability of spontaneous myofibroblast differentiation.

A Biologist-Friendly Method to Analyze Cross-Correlation Between Protrusion Dynamics and Membrane Recruitment of Actin Regulators

During mesenchymal cell motility, various actin regulators are recruited to the leading edge with exquisite precision in time and space to generate protrusion and retraction cycles. We present here an automated method, named CorRecD (from Correlation Recruitment Dynamics), which quantifies cell edge dynamics, protein recruitment and analyze their cross-correlation. The Wave Regulatory Complex (WRC), a master driver of protrusions, is used as a case-of-study. This biologist-friendly method relies on free software tools and can be applied to any fluorescently tagged protein of interest.

Time-dependent propagators for stochastic models of gene expression: an analytical method

The inherent stochasticity of gene expression in the context of regulatory networks profoundly influences the dynamics of the involved species. Mathematically speaking, the propagators which describe the evolution of such networks in time are typically defined as solutions of the corresponding chemical master equation (CME). However, it is not possible in general to obtain exact solutions to the CME in closed form, which is due largely to its high dimensionality. In the present article, we propose an analytical method for the efficient approximation of these propagators. We illustrate our method on the basis of two categories of stochastic models for gene expression that have been discussed in the literature. The requisite procedure consists of three steps: a probability-generating function is introduced which transforms the CME into (a system of) partial differential equations (PDEs); application of the method of characteristics then yields (a system of) ordinary differential equations (ODEs) which can be solved using dynamical systems techniques, giving closed-form expressions for the generating function; finally, propagator probabilities can be reconstructed numerically from these expressions via the Cauchy integral formula. The resulting ‘library’ of propagators lends itself naturally to implementation in a Bayesian parameter inference scheme, and can be generalised systematically to related categories of stochastic models beyond the ones considered here.

On the statistical analysis of single cell lineage trees

Stem cells play a central role in the regeneration and repair of multicellular organisms. However, it remains far from trivial to reliably identify them. Despite decades of work, current techniques to isolate hematopoietic stem cells (HSCs) based on cell-surface markers only result in 50% purity, i.e. half of the sorted cells are not stem cells when functionally tested. Modern microscopy techniques allow us to follow single cells and their progeny for up to weeks in vitro, while recording the cell fates and lifetime of each individual cell. This cell tracking generates so-called lineage trees. Here, we propose statistical techniques to determine if the initial cell in a lineage tree was a HSC. We apply these techniques to murine hematopoietic lineage trees, revealing that 18% of the trees in our HSC dataset display a unique signature, and this signature is compatible with these trees having started from a true stem cell. Assuming 50% purity of HSC empirical datasets, this corresponds to a 0.35 power of the test, and the type-1-error is estimated to be 0.047. In summary, this study shows that statistical analysis of lineage trees could improve the classification of cells, which is currently done based on bio-markers only. Our statistical techniques are not limited to mammalian stem cell biology. Any type of single cell lineage trees, be it from bacteria, single cell eukaryotes, or single cells in a multicellular organism can be investigated. We expect this to contribute to a better understanding of the molecules influencing cellular dynamics at the single cell level.

Multicolor quantitative confocal imaging cytometry

Multicolor 3D quantitative imaging of large tissue volumes is necessary to understand tissue development and organization as well as interactions between distinct cell types in situ. However, tissue imaging remains technically challenging, particularly imaging of bone and marrow. Here, we describe a pipeline to reproducibly generate high-dimensional quantitative data from bone and bone marrow that may be extended to any tissue. We generate thick bone sections from adult mouse femurs with preserved tissue microarchitecture and demonstrate eight-color imaging using confocal microscopy without linear unmixing. We introduce XiT, an open-access software for fast and easy data curation, exploration and quantification of large imaging data sets with single-cell resolution. We describe how XiT can be used to correct for potential artifacts in quantitative 3D imaging, and we use the pipeline to measure the spatial relationship between hematopoietic cells, bone matrix and marrow Schwann cells.

Quantitative label-free single cell tracking in 3D biomimetic matrices

Live cell imaging enables an observation of cell behavior over a period of time and is a growing field in modern cell biology. Quantitative analysis of the spatio-temporal dynamics of heterogeneous cell populations in three-dimensional (3D) microenvironments contributes a better understanding of cell-cell and cell-matrix interactions for many biomedical questions of physiological and pathological processes. However, current live cell imaging and analysis techniques are frequently limited by non-physiological 2D settings. Furthermore, they often rely on cell labelling by fluorescent dyes or expression of fluorescent proteins to enhance contrast of cells, which frequently affects cell viability and behavior of cells. In this work, we present a quantitative, label-free 3D single cell tracking technique using standard bright-field microscopy and affordable computational resources for data analysis. We demonstrate the efficacy of the automated method by studying migratory behavior of a large number of primary human macrophages over long time periods of several days in a biomimetic 3D microenvironment. The new technology provides a highly affordable platform for long-term studies of single cell behavior in 3D settings with minimal cell manipulation and can be implemented for various studies regarding cell-matrix interactions, cell-cell interactions as well as drug screening platform for primary and heterogeneous cell populations.

Acquisition of cell migration defines NK cell differentiation from hematopoietic stem cell precursors

Human natural killer (NK) cell precursors undergoing in vitro differentiation from hematopoietic stem cell precursors are tracked by long-term live-cell imaging. As differentiation progresses, NK cells acquire increasingly motile and complex modes of migration.

Human natural killer (NK) cells are generated from CD34⁺ precursors and can be differentiated in vitro by coculture with developmentally supportive stromal cells. We have previously described the acquisition of cell migration as a feature of NK cell terminal maturation in this system. Here we perform continuous long-term imaging and tracking of NK cell progenitors undergoing in vitro differentiation. We demonstrate that NK cell precursors can be tracked over long time periods on the order of weeks by utilizing phase-contrast microscopy and show that these cells acquire increasing motility as they mature. Additionally, we observe that NK cells display a more heterogeneous range of migratory behaviors at later stages of development, with the acquisition of complex modes of migration that are associated with terminal maturation. Together these data demonstrate previously unknown migratory behaviors of innate lymphocytes undergoing lineage differentiation revealed by long-term imaging and analysis workflows.

A BaSiC tool for background and shading correction of optical microscopy images

Quantitative analysis of bioimaging data is often skewed by both shading in space and background variation in time. We introduce BaSiC, an image correction method based on low-rank and sparse decomposition which solves both issues. In comparison to existing shading correction tools, BaSiC achieves high-accuracy with significantly fewer input images, works for diverse imaging conditions and is robust against artefacts. Moreover, it can correct temporal drift in time-lapse microscopy data and thus improve continuous single-cell quantification. BaSiC requires no manual parameter setting and is available as a Fiji/ImageJ plugin.

Accelerating Live Single-Cell Signalling Studies

The dynamics of signalling networks that couple environmental conditions with cellular behaviour can now be characterised in exquisite detail using live single-cell imaging experiments. Recent improvements in our abilities to introduce fluorescent sensors into cells, coupled with advances in pipelines for quantifying and extracting single-cell data, mean that high-throughput systematic analyses of signalling dynamics are becoming possible. In this review, we consider current technologies that are driving progress in the scale and range of such studies. Moreover, we discuss novel approaches that are allowing us to explore how pathways respond to changes in inputs and even predict the fate of a cell based upon its signalling history and state.

Culture of Adult Transgenic Zebrafish Retinal Explants for Live-cell Imaging by Multiphoton Microscopy

An endogenous regeneration program is initiated by Müller glia in the adult zebrafish (Danio rerio) retina following neuronal damage and death. The Müller glia re-enter the cell cycle and produce neuronal progenitor cells that undergo subsequent rounds of cell divisions and differentiate into the lost neuronal cell types. Both Müller glia and neuronal progenitor cell nuclei replicate their DNA and undergo mitosis in distinct locations of the retina, i.e. they migrate between the basal Inner Nuclear Layer (INL) and the Outer Nuclear Layer (ONL), respectively, in a process described as Interkinetic Nuclear Migration (INM). INM has predominantly been studied in the developing retina. To examine the dynamics of INM in the adult regenerating zebrafish retina in detail, live-cell imaging of fluorescently-labeled Müller glia/neuronal progenitor cells is required. Here, we provide the conditions to isolate and culture dorsal retinas from Tg[gfap:nGFP]^mi2004 zebrafish that were exposed to constant intense light for 35 h. We also show that these retinal cultures are viable to perform live-cell imaging experiments, continuously acquiring z-stack images throughout the thickness of the retinal explant for up to 8 h using multiphoton microscopy to monitor the migratory behavior of gfap:nGFP-positive cells. In addition, we describe the details to perform post-imaging analysis to determine the velocity of apical and basal INM. To summarize, we established conditions to study the dynamics of INM in an adult model of neuronal regeneration. This will advance our understanding of this crucial cellular process and allow us to determine the mechanisms that control INM.

Automated microbeam observation environment for biological analysis-Custom portable environmental control applied to a vertical microbeam system

Vertical Microbeams (VMB) are used to irradiate individual cells with low MeV energy ions. The irradiation of cells using VMBs requires cells to be removed from an incubator; this can cause physiological changes to cells because of the lower CO2 concentration, temperature and relative humidity outside of the incubator. Consequently, for experiments where cells require irradiation and observation for extended time periods, it is important to provide a controlled environment. The highly customised nature of the microscopes used on VMB systems means that there are no commercially available environmentally controlled microscope systems for VMB systems. The Automated Microbeam Observation Environment for Biological Analysis (AMOEBA) is a highly flexible modular environmental control system used to create incubator conditions on the end of a VMB. The AMOEBA takes advantage of the recent "maker" movement to create an open source control system that can be easily configured by the user to fit their control needs even beyond VMB applications. When applied to the task of controlling cell medium temperature, CO2 concentration and relative humidity on VMBs it creates a stable environment that allows cells to multiply on the end of a VMB over a period of 36 h, providing a low-cost (costing less than $2700 to build), customisable alternative to commercial time-lapse microscopy systems. AMOEBA adds the potential of VMBs to explore the long-term effects of radiation on single cells opening up new research areas for VMBs.

Relocation sensors to quantify signaling dynamics in live single cells

All cells are different. Even isogenic cells can possess diverse shapes, reside in different cell-cycle stages or express various sets of proteins. These variations can modulate the cell response to environmental stimuli and thereby provide key insights into the regulation of signal transduction cascades. Fluorescence microscopy allows to visualize these differences and monitor in real-time the responses of live single cells. In order to observe key cellular events, fluorescent biosensors have been developed. Among many assays, relocation reporters play an important role since they enable the quantification of the signal transduction dynamics. Fluorescently tagged endogenous proteins, as well as synthetic constructs, have allowed the measurement of kinase activity, transcription factor activation, transcription and protein expression in live single cells.

Characterising live cell behaviour: Traditional label-free and quantitative phase imaging approaches

Label-free imaging uses inherent contrast mechanisms within cells to create image contrast without introducing dyes/labels, which may confound results. Quantitative phase imaging is label-free and offers higher content and contrast compared to traditional techniques. High-contrast images facilitate generation of individual cell metrics via more robust segmentation and tracking, enabling formation of a label-free dynamic phenotype describing cell-to-cell heterogeneity and temporal changes. Compared to population-level averages, individual cell-level dynamic phenotypes have greater power to differentiate between cellular responses to treatments, which has clinical relevance e.g. in the treatment of cancer. Furthermore, as the data is obtained label-free, the same cells can be used for further assays or expansion, of potential benefit for the fields of regenerative and personalised medicine.

iCellFusion

Temporal, multimodal microscopy imaging of live cells is becoming widely used in studies of cellular processes. In general, temporal sequences of images with functional and morphological data from live cells are acquired using multiple image sensors. The images from the different sources usually differ in resolution and have non-coincident fields of view, making the merging process complex. We present a new tool – iCellFusion – that performs data fusion of images from Phase-Contrast Microscopy and Fluorescence Microscopy in order to correlate the information on cell morphology, lineage and functionality. Prior to image fusion, iCellFusion performs automatic or computer-aided cell segmentation and establishes cell lineages. We exemplify its usage on time-lapse, multimodal microscopy images of bacteria producing fluorescent spots. We expect iCellFusion to assist research in Cell and Molecular Biology and the healthcare sector, where live-cell imaging is an increasingly important technique to detect and study diseases at the cellular level.

Live-cell imaging: new avenues to investigate retinal regeneration

Sensing and responding to our environment requires functional neurons that act in concert. Neuronal cell loss resulting from degenerative diseases cannot be replaced in humans, causing a functional impairment to integrate and/or respond to sensory cues. In contrast, zebrafish (Danio rerio) possess an endogenous capacity to regenerate lost neurons. Here, we will focus on the processes that lead to neuronal regeneration in the zebrafish retina. Dying retinal neurons release a damage signal, tumor necrosis factor α, which induces the resident radial glia, the Müller glia, to reprogram and re-enter the cell cycle. The Müller glia divide asymmetrically to produce a Müller glia that exits the cell cycle and a neuronal progenitor cell. The arising neuronal progenitor cells undergo several rounds of cell divisions before they migrate to the site of damage to differentiate into the neuronal cell types that were lost. Molecular and immunohistochemical studies have predominantly provided insight into the mechanisms that regulate retinal regeneration. However, many processes during retinal regeneration are dynamic and require live-cell imaging to fully discern the underlying mechanisms. Recently, a multiphoton imaging approach of adult zebrafish retinal cultures was developed. We will discuss the use of live-cell imaging, the currently available tools and those that need to be developed to advance our knowledge on major open questions in the field of retinal regeneration.

Identification of factors promoting ex vivo maintenance of mouse hematopoietic stem cells by long-term single-cell quantification

AFT024-induced HSC maintenance correlates with early survival/proliferation whereas early death is a major reason for HSC loss in culture. Dermatopontin is required for ex vivo HSC maintenance, and also improves HSC clonogenicity in stroma-based and stroma-free cultures.

Quantitative dynamics of VE-cadherin at endothelial cell junctions at a glance: basic requirements and current concepts

Intercellular junctions of the vascular endothelium are dynamic structures that display a high degree of plasticity, which is required to contribute to their regulation of many physiological and pathological processes including monolayer integrity, barrier function, wound healing and angiogenesis. Vascular endothelial cadherin (VE-cadherin) is connected via catenins to the actin cytoskeleton, both of which are key structures in endothelial junction regulation, and thus are the focus of much investigation. Fluorescence-based live cell imaging is the method of choice to study dynamic remodeling in living cells. Although these methods have been successfully applied to many cell types, investigations of endothelial junction dynamics were for a long time limited as they are largely resistant to transfection using many classical protocols. Application of virus-based gene transduction techniques, together with advanced microscopy, now allows both sufficient expression of fluorescence tagged junction-localized proteins in the endothelium and time-lapse recording over long periods. Using highly spatiotemporally resolved fluorescence microscopy it turned out that endothelial junctions display extensive junction heterogeneity at the subcellular level; a fact that largely limits automated quantification by available software. Recent work describes open software tools to quantitatively analyze large amounts of fluorescence-based image data in either single or confluent epithelial and endothelial cells. Based on quantitative VE-cadherin and actin dynamics novel key players, mechanisms and concepts have been suggested that control endothelial junction dynamics. Here we aim to summarize the recent developments in the field.

Targeted systemic mesenchymal stem cell delivery using hyaluronate - wheat germ agglutinin conjugate

A variety of receptors for hyaluronate (HA), a natural linear polysaccharide, were found in the body, which have been exploited as target sites for HA-based drug delivery systems. In this work, mesenchymal stem cells (MSCs) were surface-modified with HA - wheat germ agglutinin (WGA) conjugate for targeted systemic delivery of MSCs to the liver. WGA was conjugated to HA by coupling reaction between aldehyde-modified HA and amine group of WGA. The conjugation of WGA to HA was corroborated by gel permeation chromatography (GPC) and the successful surface modification of MSCs with HA-WGA conjugate was confirmed by confocal microscopy. The synthesized HA-WGA conjugate could be incorporated onto the cellular membrane by agglutinating the cell-associated carbohydrates. Fluorescent imaging for in vivo biodistribution visualized the targeted delivery of the HA-WGA/MSC complex to the liver after intravenous injection. This new strategy for targeted delivery of MSCs using HA-WGA conjugate might be successfully exploited for various regenerative medicines including cell therapy.