Extracting fluorescent reporter time courses of cell lineages from high-throughput microscopy at low temporal resolution

Optical microscopic imaging, manipulation, and analysis methods for morphogenesis research

Morphogenesis is a developmental process of organisms being shaped through complex and cooperative cellular movements. To understand the interplay between genetic programs and the resulting multicellular morphogenesis, it is essential to characterize the morphologies and dynamics at the single-cell level and to understand how physical forces serve as both signaling components and driving forces of tissue deformations. In recent years, advances in microscopy techniques have led to improvements in imaging speed, resolution and depth. Concurrently, the development of various software packages has supported large-scale, analyses of challenging images at the single-cell resolution. While these tools have enhanced our ability to examine dynamics of cells and mechanical processes during morphogenesis, their effective integration requires specialized expertise. With this background, this review provides a practical overview of those techniques. First, we introduce microscopic techniques for multicellular imaging and image analysis software tools with a focus on cell segmentation and tracking. Second, we provide an overview of cutting-edge techniques for mechanical manipulation of cells and tissues. Finally, we introduce recent findings on morphogenetic mechanisms and mechanosensations that have been achieved by effectively combining microscopy, image analysis tools and mechanical manipulation techniques.

Methods and computational tools to study eukaryotic cell migration in vitro

Cellular movement is essential for many vital biological functions where it plays a pivotal role both at the single cell level, such as during division or differentiation, and at the macroscopic level within tissues, where coordinated migration is crucial for proper morphogenesis. It also has an impact on various pathological processes, one for all, cancer spreading. Cell migration is a complex phenomenon and diverse experimental methods have been developed aimed at dissecting and analysing its distinct facets independently. In parallel, corresponding analytical procedures and tools have been devised to gain deep insight and interpret experimental results. Here we review established experimental techniques designed to investigate specific aspects of cell migration and present a broad collection of historical as well as cutting-edge computational tools used in quantitative analysis of cell motion.

TreeJ: an ImageJ plugin for interactive cell lineage reconstruction from static images

BACKGROUND

With the emergence of deep-learning methods, tools are needed to capture and standardize image annotations made by experimentalists. In developmental biology, cell lineages are generally reconstructed from time-lapse data. However, some tissues need to be fixed to be accessible or to improve the staining. In this case, classical software do not offer the possibility of generating any lineage. Because of their rigid cell walls, plants present the advantage of keeping traces of the cell division history over successive generations in the cell patterns. To record this information despite having only a static image, dedicated tools are required.

RESULTS

We developed an interface to assist users in the building and editing of a lineage tree from a 3D labeled image. Each cell within the tree can be tagged. From the created tree, cells of a sub-tree or cells sharing the same tag can be extracted. The tree can be exported in a format compatible with dedicated software for advanced graph visualization and manipulation.

CONCLUSIONS

The TreeJ plugin for ImageJ/Fiji allows the user to generate and manipulate a lineage tree structure. The tree is compatible with other software to analyze the tree organization at the graphical level and at the cell pattern level. The code source is available at https://github.com/L-EL/TreeJ .

Effect of SPARC Suppression in Mice, Perfused Human Anterior Segments, and Trabecular Meshwork Cells

Purpose

Secreted protein, acidic and rich in cysteine (SPARC) elevates intraocular pressure (IOP), increases certain structural extracellular matrix (ECM) proteins in the juxtacanalicular trabecular meshwork (JCT), and decreases matrix metalloproteinase (MMP) protein levels in trabecular meshwork (TM) endothelial cells. We investigated SPARC as a potential target for lowering IOP. We hypothesized that suppressing SPARC will decrease IOP, decrease structural JCT ECM proteins, and alter the levels of MMPs and/or their inhibitors.

Methods

A lentivirus containing short hairpin RNA of human SPARC suppressed SPARC in mouse eyes and perfused cadaveric human anterior segments with subsequent IOP measurements. Immunohistochemistry determined structural correlates. Human TM cell cultures were treated with SPARC suppressing lentivirus. Quantitative reverse transcriptase polymerase chain reaction (PCR), immunoblotting, and zymography determined total RNA, relative protein levels, and MMP enzymatic activity, respectively.

Results

Suppressing SPARC decreased IOP in mouse eyes and perfused human anterior segments by approximately 20%. Histologically, this correlated to a decrease in collagen I, IV, and VI in both the mouse TM and human JCT regions; in the mouse, fibronectin was also decreased but not in the human. In TM cells, collagen I and IV, fibronectin, MMP-2, and tissue inhibitor of MMP-1 were decreased. Messenger RNA of the aforementioned genes was not changed. Plasminogen activator inhibitor 1 (PAI-1) was upregulated in vitro by quantitative PCR and immunoblotting. MMP-1 activity was reduced in vitro by zymography.

Conclusions

Suppressing SPARC decreased IOP in mice and perfused cadaveric human anterior segments corresponding to qualitative structural changes in the JCT ECM, which do not appear to be the result of transcription regulation.

Cyton2: A Model of Immune Cell Population Dynamics That Includes Familial Instructional Inheritance

Lymphocytes are the central actors in adaptive immune responses. When challenged with antigen, a small number of B and T cells have a cognate receptor capable of recognising and responding to the insult. These cells proliferate, building an exponentially growing, differentiating clone army to fight off the threat, before ceasing to divide and dying over a period of weeks, leaving in their wake memory cells that are primed to rapidly respond to any repeated infection. Due to the non-linearity of lymphocyte population dynamics, mathematical models are needed to interrogate data from experimental studies. Due to lack of evidence to the contrary and appealing to arguments based on Occam's Razor, in these models newly born progeny are typically assumed to behave independently of their predecessors. Recent experimental studies, however, challenge that assumption, making clear that there is substantial inheritance of timed fate changes from each cell by its offspring, calling for a revision to the existing mathematical modelling paradigms used for information extraction. By assessing long-term live-cell imaging of stimulated murine B and T cells in vitro, we distilled the key phenomena of these within-family inheritances and used them to develop a new mathematical model, Cyton2, that encapsulates them. We establish the model's consistency with these newly observed fine-grained features. Two natural concerns for any model that includes familial correlations would be that it is overparameterised or computationally inefficient in data fitting, but neither is the case for Cyton2. We demonstrate Cyton2's utility by challenging it with high-throughput flow cytometry data, which confirms the robustness of its parameter estimation as well as its ability to extract biological meaning from complex mixed stimulation experiments. Cyton2, therefore, offers an alternate mathematical model, one that is, more aligned to experimental observation, for drawing inferences on lymphocyte population dynamics.

Automated Deep Lineage Tree Analysis Using a Bayesian Single Cell Tracking Approach

Single-cell methods are beginning to reveal the intrinsic heterogeneity in cell populations, arising from the interplay of deterministic and stochastic processes. However, it remains challenging to quantify single-cell behaviour from time-lapse microscopy data, owing to the difficulty of extracting reliable cell trajectories and lineage information over long time-scales and across several generations. Therefore, we developed a hybrid deep learning and Bayesian cell tracking approach to reconstruct lineage trees from live-cell microscopy data. We implemented a residual U-Net model coupled with a classification CNN to allow accurate instance segmentation of the cell nuclei. To track the cells over time and through cell divisions, we developed a Bayesian cell tracking methodology that uses input features from the images to enable the retrieval of multi-generational lineage information from a corpus of thousands of hours of live-cell imaging data. Using our approach, we extracted 20,000 + fully annotated single-cell trajectories from over 3,500 h of video footage, organised into multi-generational lineage trees spanning up to eight generations and fourth cousin distances. Benchmarking tests, including lineage tree reconstruction assessments, demonstrate that our approach yields high-fidelity results with our data, with minimal requirement for manual curation. To demonstrate the robustness of our minimally supervised cell tracking methodology, we retrieve cell cycle durations and their extended inter- and intra-generational family relationships in 5,000 + fully annotated cell lineages. We observe vanishing cycle duration correlations across ancestral relatives, yet reveal correlated cyclings between cells sharing the same generation in extended lineages. These findings expand the depth and breadth of investigated cell lineage relationships in approximately two orders of magnitude more data than in previous studies of cell cycle heritability, which were reliant on semi-manual lineage data analysis.

Automated tracking of S. pombe spindle elongation dynamics

The mitotic spindle is a microtubule-based machine that pulls the two identical sets of chromosomes to opposite ends of the cell during cell division. The fission yeast Schizosaccharomyces pombe is an important model organism for studying mitosis due to its simple, stereotyped spindle structure and well-established genetic toolset. S. pombe spindle length is a useful metric for mitotic progression, but manually tracking spindle ends in each frame to measure spindle length over time is laborious and can limit experimental throughput. We have developed an ImageJ plugin that can automatically track S. pombe spindle length over time and replace manual or semi-automated tracking of spindle elongation dynamics. Using an algorithm that detects the principal axis of the spindle and then finds its ends, we reliably track the length of the spindle as the cell divides. The plugin integrates with existing ImageJ features, exports its data for further analysis outside of ImageJ and does not require any programming by the user. Thus, the plugin provides an accessible tool for quantification of S. pombe spindle length that will allow automatic analysis of large microscopy data sets and facilitate screening for effects of cell biological perturbations on mitotic progression.

Current approaches to fate mapping and lineage tracing using image data

Visualizing, tracking and reconstructing cell lineages in developing embryos has been an ongoing effort for well over a century. Recent advances in light microscopy, labelling strategies and computational methods to analyse complex image datasets have enabled detailed investigations into the fates of cells. Combined with powerful new advances in genomics and single-cell transcriptomics, the field of developmental biology is able to describe the formation of the embryo like never before. In this Review, we discuss some of the different strategies and applications to lineage tracing in live-imaging data and outline software methodologies that can be applied to various cell-tracking challenges.

Fully unsupervised symmetry-based mitosis detection in time-lapse cell microscopy

MOTIVATION

Cell microscopy datasets have great diversity due to variability in cell types, imaging techniques and protocols. Existing methods are either tailored to specific datasets or are based on supervised learning, which requires comprehensive manual annotations. Using the latter approach, however, poses a significant difficulty due to the imbalance between the number of mitotic cells with respect to the entire cell population in a time-lapse microscopy sequence.

RESULTS

We present a fully unsupervised framework for both mitosis detection and mother-daughters association in fluorescence microscopy data. The proposed method accommodates the difficulty of the different cell appearances and dynamics. Addressing symmetric cell divisions, a key concept is utilizing daughters' similarity. Association is accomplished by defining cell neighborhood via a stochastic version of the Delaunay triangulation and optimization by dynamic programing. Our framework presents promising detection results for a variety of fluorescence microscopy datasets of different sources, including 2D and 3D sequences from the Cell Tracking Challenge.

AVAILABILITY AND IMPLEMENTATION

Code is available in github (github.com/topazgl/mitodix).

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Cell cycle dynamics of mouse embryonic stem cells in the ground state and during transition to formative pluripotency

Mouse embryonic stem cells (mESCs) can be maintained as homogeneous populations in the ground state of pluripotency. Release from this state in minimal conditions allows to obtain cells that resemble those of the early post-implantation epiblast, providing an important developmental model to study cell identity transitions. However, the cell cycle dynamics of mESCs in the ground state and during its dissolution have not been extensively studied. By performing live imaging experiments of mESCs bearing cell cycle reporters, we show here that cells in the pluripotent ground state display a cell cycle structure comparable to the reported for mESCs in serum-based media. Upon release from self-renewal, the cell cycle is rapidly accelerated by a reduction in the length of the G1 phase and of the S/G2/M phases, causing an increased proliferation rate. Analysis of cell lineages indicates that cell cycle variables of sister cells are highly correlated, suggesting the existence of inherited cell cycle regulators from the parental cell. Together with a major morphological reconfiguration upon differentiation, our findings support a correlation between this in vitro model and early embryonic events.

Circadian Clock Synchronization of the Cell Cycle in Zebrafish Occurs through a Gating Mechanism Rather Than a Period-phase Locking Process

Studies from a number of model systems have shown that the circadian clock controls expression of key cell cycle checkpoints, thus providing permissive or inhibitory windows in which specific cell cycle events can occur. However, a major question remains: Is the clock actually regulating the cell cycle through such a gating mechanism or, alternatively, is there a coupling process that controls the speed of cell cycle progression? Using our light-responsive zebrafish cell lines, we address this issue directly by synchronizing the cell cycle in culture simply by changing the entraining light-dark (LD) cycle in the incubator without the need for pharmacological intervention. Our results show that the cell cycle rapidly reentrains to a shifted LD cycle within 36 h, with changes in p21 expression and subsequent S phase timing occurring within the first few hours of resetting. Reentrainment of mitosis appears to lag S phase resetting by 1 circadian cycle. The range of entrainment of the zebrafish clock to differing LD cycles is large, from 16 to 32 hour periods. We exploited this feature to explore cell cycle entrainment at both the population and single cell levels. At the population level, cell cycle length is shortened or lengthened under corresponding T-cycles, suggesting that a 1:1 coupling mechanism is capable of either speeding up or slowing down the cell cycle. However, analysis at the single cell level reveals that this, in fact, is not true and that a gating mechanism is the fundamental method of timed cell cycle regulation in zebrafish. Cell cycle length at the single cell level is virtually unaltered with varying T-cycles.

Single-cell variability in multicellular organisms

Noisy gene expression is of fundamental importance to single cells, and is therefore widely studied in single-celled organisms. Extending these studies to multicellular organisms is challenging since their cells are generally not isolated, but individuals in a tissue. Cell–cell coupling via signalling, active transport or pure diffusion, ensures that tissue-bound cells are neither fully independent of each other, nor an entirely homogeneous population. In this article, we show that increasing the strength of coupling between cells can either increase or decrease the single-cell variability (and, therefore, the heterogeneity of the tissue), depending on the statistical properties of the underlying genetic network. We confirm these predictions using spatial stochastic simulations of simple genetic networks, and experimental data from animal and plant tissues. The results suggest that cell–cell coupling may be one of several noise-control strategies employed by multicellular organisms, and highlight the need for a deeper understanding of multicellular behaviour.

While gene expression noise in single-celled organisms is well understood, it is less so in the context of tissues. Here the authors show that coupling between cells in tissues can increase or decrease cell-to-cell variability depending on the level of noise intrinsic to the regulatory networks.

Sensing relative signal in the Tgf-β/Smad pathway

How signaling pathways function reliably despite cellular variation remains a question in many systems. In the transforming growth factor-β (Tgf-β) pathway, exposure to ligand stimulates nuclear localization of Smad proteins, which then regulate target gene expression. Examining Smad3 dynamics in live reporter cells, we found evidence for fold-change detection. Although the level of nuclear Smad3 varied across cells, the fold change in the level of nuclear Smad3 was a more precise outcome of ligand stimulation. The precision of the fold-change response was observed throughout the signaling duration and across Tgf-β doses, and significantly increased the information transduction capacity of the pathway. Using single-molecule FISH, we further observed that expression of Smad3 target genes (ctgf, snai1, and wnt9a) correlated more strongly with the fold change, rather than the level, of nuclear Smad3. These findings suggest that some target genes sense Smad3 level relative to background, as a strategy for coping with cellular noise.

High-Throughput Single-Cell Kinetics of Virus Infections in the Presence of Defective Interfering Particles

Defective interfering particles (DIPs) are virus mutants that lack essential genes for growth. In coinfections with helper virus, the diversion of viral proteins to the replication and packaging of DIP genomes can interfere with virus production. Mounting cases of DIPs and DIP-like genomes in clinical and natural isolates, as well as growing interest in DIP-based therapies, underscore a need to better elucidate how DIPs work. DIP activity is primarily measured by its inhibition of virus infection yield, an endpoint that masks the dynamic and potentially diverse individual cell behaviors. Using vesicular stomatitis virus (VSV) as a model, we coinfected BHK cells with VSV DIPs and recombinant helper virus carrying a gene encoding a red fluorescent protein (RFP) whose expression correlates with the timing and level of virus release. For single cells within a monolayer, 10 DIPs per cell suppressed the reporter expression in only 1.2% of the cells. In most cells, it slowed and reduced viral gene expression, manifested as a shift in mean latent time from 4 to 6 h and reduced virus yields by 10-fold. For single cells isolated in microwells, DIP effects were more pronounced, reducing virus yields by 100-fold and extending latent times to 12 h, including individual instances above 20 h. Together, these results suggest that direct or indirect cell-cell interactions prevent most coinfected cells from being completely suppressed by DIPs. Finally, a gamma distribution model captures well how the infection kinetics quantitatively depends on the DIP dose. Such models will be useful for advancing a predictive biology of DIP-associated virus growth and infection spread.

IMPORTANCE

During the last century, basic studies in virology have focused on developing a molecular mechanistic understanding of how infectious viruses reproduce in their living host cells. However, over the last 10 years, the advent of deep sequencing and other powerful technologies has revealed in natural and patient infections that viruses do not act alone. Instead, viruses are often accompanied by defective virus-like particles that carry large deletions in their genomes and fail to replicate on their own. Coinfections of viable and defective viruses behave in unpredictable ways, but they often interfere with normal virus growth, potentially enabling infections to evade host immune surveillance. In the current study, controlled levels of defective viruses are coinfected with viable viruses that have been engineered to express a fluorescent reporter protein during infection. Unique profiles of reporter expression acquired from thousands of coinfected cells reveal how interference acts at multiple stages of infection.

Strontium folate loaded biohybrid scaffolds seeded with dental pulp stem cells induce in vivo bone regeneration in critical sized defects

Strontium folate loaded biohybrid scaffolds enhance dental pulp stem cells replication and differentiation, promoting complete regeneration of critical bone defects.

Conserved Cis-Regulatory Modules Control Robustness in Msx1 Expression at Single-Cell Resolution

The process of transcription is highly stochastic leading to cell-to-cell variations and noise in gene expression levels. However, key essential genes have to be precisely expressed at the correct amount and time to ensure proper cellular development and function. Studies in yeast and bacterial systems have shown that gene expression noise decreases as mean expression levels increase, a relationship that is controlled by promoter DNA sequence. However, the function of distal cis-regulatory modules (CRMs), an evolutionary novelty of metazoans, in controlling transcriptional robustness and variability is poorly understood. In this study, we used live cell imaging of transfected reporters combined with a mathematical modelling and statistical inference scheme to quantify the function of conserved Msx1 CRMs and promoters in modulating single-cell real-time transcription rates in C2C12 mouse myoblasts. The results show that the mean expression–noise relationship is solely promoter controlled for this key pluripotency regulator. In addition, we demonstrate that CRMs modulate single-cell basal promoter rate distributions in a graded manner across a population of cells. This extends the rheostatic model of CRM action to provide a more detailed understanding of CRM function at single-cell resolution. We also identify a novel CRM transcriptional filter function that acts to reduce intracellular variability in transcription rates and show that this can be phylogenetically separable from rate modulating CRM activities. These results are important for understanding how the expression of key vertebrate developmental transcription factors is precisely controlled both within and between individual cells.

TGF-β2-mediated ocular hypertension is attenuated in SPARC-null mice

PURPOSE

Transforming growth factor-β2 (TGF-β2) has been implicated in the pathogenesis of primary open-angle glaucoma through extracellular matrix (ECM) alteration among various mechanisms. Secreted protein acidic and rich in cysteine (SPARC) is a matricellular protein that regulates ECM within the trabecular meshwork (TM), and is highly upregulated by TGF-β2. We hypothesized that, in vivo, SPARC is a critical regulatory node in TGF-β2-mediated ocular hypertension.

METHODS

Empty (Ad.empty) or TGF-β2-containing adenovirus (Ad.TGF-β2) was injected intravitreally into C57BL6-SV129 WT and SPARC-null mice. An initial study was performed to identify a stable period for IOP measurement under isoflurane. The IOP was measured before injection and every other day for two weeks using rebound tonometry. Additional mice were euthanized at peak IOP for immunohistochemistry.

RESULTS

The IOP was stable under isoflurane during minutes 5 to 8. The IOP was significantly elevated in Ad.TGF-β2-injected (n = 8) versus Ad.empty-injected WT (n = 8) mice and contralateral uninjected eyes during days 4 to 11 (P < 0.03). The IOPs were not significantly elevated in Ad.TGF-β2-injected versus Ad.empty-injected SPARC-null mice. However, on day 8, the IOP of Ad.TGF-β2-injected SPARC-null eyes was elevated compared to that of contralateral uninjected eyes (P = 0.0385). Immunohistochemistry demonstrated that TGF-β2 stimulated increases in collagen IV, fibronectin, plasminogen activator inhibitor-1 (PAI-1), connective tissue growth factor (CTGF), and SPARC in WT mice, but only PAI-1 and CTGF in SPARC-null mice (P < 0.05).

CONCLUSIONS

SPARC is essential to the regulation of TGF-β2-mediated ocular hypertension. Deletion of SPARC significantly attenuates the effects of TGF-β2 by restricting collagen IV and fibronectin expression. These data provide further evidence that SPARC may have an important role in IOP regulation and possibly glaucoma pathogenesis.

A hierarchical model of transcriptional dynamics allows robust estimation of transcription rates in populations of single cells with variable gene copy number

Motivation:cis-regulatory DNA sequence elements, such as enhancers and silencers, function to control the spatial and temporal expression of their target genes. Although the overall levels of gene expression in large cell populations seem to be precisely controlled, transcription of individual genes in single cells is extremely variable in real time. It is, therefore, important to understand how these cis-regulatory elements function to dynamically control transcription at single-cell resolution. Recently, statistical methods have been proposed to back calculate the rates involved in mRNA transcription using parameter estimation of a mathematical model of transcription and translation. However, a major complication in these approaches is that some of the parameters, particularly those corresponding to the gene copy number and transcription rate, cannot be distinguished; therefore, these methods cannot be used when the copy number is unknown.

Results: Here, we develop a hierarchical Bayesian model to estimate biokinetic parameters from live cell enhancer–promoter reporter measurements performed on a population of single cells. This allows us to investigate transcriptional dynamics when the copy number is variable across the population. We validate our method using synthetic data and then apply it to quantify the function of two known developmental enhancers in real time and in single cells.

Availability: Supporting information is submitted with the article.

Contact:d.j.woodcock@warwick.ac.uk

Supplementary information:Supplementary data are available at Bioinformatics online.

Beyond annexin V: fluorescence response of cellular membranes to apoptosis

Dramatic changes in the structure of cell membranes on apoptosis allow easy, sensitive and non-destructive analysis of this process with the application of fluorescence methods. The strong plasma membrane asymmetry is present in living cells, and its loss on apoptosis is commonly detected with the probes interacting strongly and specifically with phosphatidylserine (PS). This phospholipid becomes exposed to the cell surface, and the application of annexin V labeled with fluorescent dye is presently the most popular tool for its detection. Several methods have been suggested recently that offer important advantages over annexin V assay with the ability to study apoptosis by spectroscopy of cell suspensions, flow cytometry and confocal or two-photon microscopy. The PS exposure marks the integrated changes in the outer leaflet of cell membrane that involve electrostatic potential and hydration, and the attempts are being made to provide direct probing of these changes. This review describes the basic mechanisms underlying the loss of membrane asymmetry during apoptosis and discusses, in comparison with the annexin V-binding assay, the novel fluorescence techniques of detecting apoptosis on cellular membrane level. In more detail we describe the detection method based on smart fluorescent dye F2N12S incorporated into outer leaflet of cell membrane and reporting on apoptotic cell transformation by easily detectable change of the spectral distribution of fluorescent emission. It can be adapted to any assay format.