EllipTrack: A Global-Local Cell-Tracking Pipeline for 2D Fluorescence Time-Lapse Microscopy

CDK2 activity crosstalk on the ERK kinase translocation reporter can be resolved computationally

The mitogen-activated protein kinase (MAPK) pathway integrates growth factor signaling through extracellular signal-regulated kinase (ERK) to control cell proliferation. To study ERK dynamics, many researchers use an ERK activity kinase translocation reporter (KTR). Our study reveals that this ERK KTR also partially senses cyclin-dependent kinase 2 (CDK2) activity, making it appear as if ERK activity rises as cells progress through the cell cycle. Through single-cell time-lapse imaging, we identified a residual ERK KTR signal that was eliminated by selective CDK2 inhibitors, indicating crosstalk from CDK2 onto the ERK KTR. By contrast, EKAREN5, a FRET-based ERK sensor, showed no CDK2 crosstalk. A related p38 KTR is also partly affected by CDK2 activity. To address this, we developed linear and non-linear computational correction methods that subtract CDK2 signal from the ERK and p38 KTRs. These findings will allow for more accurate quantification of MAPK activities, especially for studies of actively cycling cells.

BRAFV600 and ErbB inhibitors directly activate GCN2 in an off-target manner to limit cancer cell proliferation

Targeted kinase inhibitors are well known for their promiscuity and off-target effects. Herein, we define an off-target effect in which several clinical BRAFV600 inhibitors, including the widely used dabrafenib and encorafenib, interact directly with GCN2 to activate the Integrated Stress Response and ATF4. Blocking this off-target effect by co-drugging with a GCN2 inhibitor in A375 melanoma cells causes enhancement rather than suppression of cancer cell outgrowth, suggesting that the off-target activation of GCN2 is detrimental to these cells. This result is mirrored in PC9 lung cancer cells treated with erlotinib, an EGFR inhibitor, that shares the same off-target activation of GCN2. Using an in silico kinase inhibitor screen, we identified dozens of FDA-approved drugs that appear to share this off-target activation of GCN2 and ATF4. Thus, GCN2 activation may modulate the therapeutic efficacy of some kinase inhibitors, depending on the cancer context.

Protocol for measuring cell cycle Zn2+ dynamics using a FRET-based biosensor

The exchangeable Zn2+ pool in cells is not static but responds to perturbations as well as fluctuates naturally through the cell cycle. Here, we present a protocol to carry out long-term live-cell imaging of cells expressing a cytosolic Zn2+ sensor. We then describe how to track cells using the published pipeline EllipTrack and how to analyze the single-cell traces to determine changes in labile Zn2+ in response to perturbation. For complete details on the use and execution of this protocol, please refer to Rakshit and Holtzen et al.1.

Transient Zn2+ deficiency induces replication stress and compromises daughter cell proliferation

Cells must replicate their genome quickly and accurately, and they require metabolites and cofactors to do so. Ionic zinc (Zn2+) is an essential micronutrient that is required for hundreds of cellular processes, including DNA synthesis and adequate proliferation. Deficiency in this micronutrient impairs DNA synthesis and inhibits proliferation, but the mechanism is unknown. Using fluorescent reporters to track single cells via long-term live-cell imaging, we find that Zn2+ is required at the G1/S transition and during S phase for timely completion of S phase. A short pulse of Zn2+ deficiency impairs DNA synthesis and increases markers of replication stress. These markers of replication stress are reversed upon resupply of Zn2+. Finally, we find that if Zn2+ is chelated during the mother cell's S phase, daughter cells enter a transient quiescent state, maintained by sustained expression of p21, which disappears upon reentry into the cell cycle. In summary, short pulses of mild Zn2+ deficiency in S phase specifically induce replication stress, which causes downstream proliferation impairments in daughter cells.

Investigating Heterogeneous Cell-Cycle Progression Using Single-Cell Imaging Approaches

Investigating cell-cycle progression has been challenging due to the complex interconnectivity of regulatory processes and inherent cell-to-cell heterogeneity, which often require synchronization procedures. However, recent advancements in cell-cycle sensors and single-cell imaging techniques have turned this heterogeneity into an advantage for investigating the molecular mechanisms underlying diverse responses. This has led to significant progress in our understanding of cell-cycle regulation. In this paper, we present a comprehensive live single-cell imaging workflow that leverages cutting-edge live-cell sensors. These advanced single-cell imaging procedures provide promising opportunities for elucidating the molecular mechanisms underpinnings of heterogeneous responses in cell-cycle progression.

Cells use multiple mechanisms for cell-cycle arrest upon withdrawal of individual amino acids

Amino acids are required for cell growth and proliferation, but it remains unclear when and how amino acid availability impinges on the proliferation-quiescence decision. Here, we used time-lapse microscopy and single-cell tracking of cyclin-dependent kinase 2 (CDK2) activity to assess the response of individual cells to withdrawal of single amino acids and found strikingly different cell-cycle effects depending on the amino acid. For example, upon leucine withdrawal, MCF10A cells complete two cell cycles and then enter a CDK2-low quiescence, whereas lysine withdrawal causes immediate cell-cycle stalling. Methionine withdrawal triggers a restriction point phenotype similar to serum starvation or Mek inhibition: upon methionine withdrawal, cells complete their current cell cycle and enter a CDK2-low quiescence after mitosis. Modulation of restriction point regulators p21/p27 or cyclin D1 enables short-term rescue of proliferation under methionine and leucine withdrawal, and to a lesser extent lysine withdrawal, revealing a checkpoint connecting nutrient signaling to cell-cycle entry.

A guide to ERK dynamics, part 1: mechanisms and models

Extracellular signal-regulated kinase (ERK) has long been studied as a key driver of both essential cellular processes and disease. A persistent question has been how this single pathway is able to direct multiple cell behaviors, including growth, proliferation, and death. Modern biosensor studies have revealed that the temporal pattern of ERK activity is highly variable and heterogeneous, and critically, that these dynamic differences modulate cell fate. This two-part review discusses the current understanding of dynamic activity in the ERK pathway, how it regulates cellular decisions, and how these cell fates lead to tissue regulation and pathology. In part 1, we cover the optogenetic and live-cell imaging technologies that first revealed the dynamic nature of ERK, as well as current challenges in biosensor data analysis. We also discuss advances in mathematical models for the mechanisms of ERK dynamics, including receptor-level regulation, negative feedback, cooperativity, and paracrine signaling. While hurdles still remain, it is clear that higher temporal and spatial resolution provide mechanistic insights into pathway circuitry. Exciting new algorithms and advanced computational tools enable quantitative measurements of single-cell ERK activation, which in turn inform better models of pathway behavior. However, the fact that current models still cannot fully recapitulate the diversity of ERK responses calls for a deeper understanding of network structure and signal transduction in general.

Transient Zn2+ deficiency induces replication stress and compromises daughter cell proliferation

Cells must replicate their genome quickly and accurately, and they require metabolites and cofactors to do so. Ionic zinc (Zn2+) is an essential micronutrient that is required for hundreds of cellular processes, including DNA synthesis and adequate proliferation. Deficiency in this micronutrient impairs DNA synthesis and inhibits proliferation, but the mechanism is unknown. Using fluorescent reporters to track single cells via long-term live-cell imaging, we find that Zn2+ is required at the G1/S transition and during S-phase for timely completion of S-phase. A short pulse of Zn2+ deficiency impairs DNA synthesis and increases markers of replication stress. These markers of replication stress are reversed upon resupply of Zn2+. Finally, we find that if Zn2+ is removed during the mother cell's S-phase, daughter cells enter a transient quiescent state, maintained by sustained expression of p21, which disappears upon reentry into the cell cycle. In summary, short pulses of mild Zn2+ deficiency in S-phase specifically induce replication stress, which causes downstream proliferation impairments in daughter cells.

Instant processing of large-scale image data with FACT, a real-time cell segmentation and tracking algorithm

Quantifying cellular characteristics from a large heterogeneous population is essential to identify rare, disease-driving cells. A recent development in the combination of high-throughput screening microscopy with single-cell profiling provides an unprecedented opportunity to decipher disease-driving phenotypes. Accurately and instantly processing large amounts of image data, however, remains a technical challenge when an analysis output is required minutes after data acquisition. Here, we present fast and accurate real-time cell tracking (FACT). FACT can segment ∼20,000 cells in an average of 2.5 s (1.9-93.5 times faster than the state of the art). It can export quantifiable features minutes after data acquisition (independent of the number of acquired image frames) with an average of 90%-96% precision. We apply FACT to identify directionally migrating glioblastoma cells with 96% precision and irregular cell lineages from a 24 h movie with an average F1 score of 0.91.

Multiple cancers escape from multiple MAPK pathway inhibitors and use DNA replication stress signaling to tolerate aberrant cell cycles

Many cancers harbor pro-proliferative mutations of the mitogen-activated protein kinase (MAPK) pathway. In BRAF-driven melanoma cells treated with BRAF inhibitors, subpopulations of cells escape drug-induced quiescence through a nongenetic manner of adaptation and resume slow proliferation. Here, we found that this phenomenon is common to many cancer types driven by EGFR, KRAS, or BRAF mutations in response to multiple, clinically approved MAPK pathway inhibitors. In 2D cultures and 3D spheroid models of various cancer cell lines, a subset of cells escaped drug-induced quiescence within 4 days to resume proliferation. These "escapee" cells exhibited DNA replication deficits, accumulated DNA lesions, and mounted a stress response that depended on the ataxia telangiectasia and RAD3-related (ATR) kinase. We further identified that components of the Fanconi anemia (FA) DNA repair pathway are recruited to sites of mitotic DNA synthesis (MiDAS) in escapee cells, enabling successful completion of cell division. Analysis of patient tumor samples and clinical data correlated disease progression with an increase in DNA replication stress response factors. Our findings suggest that many MAPK pathway-mutant cancers rapidly escape drug action and that suppressing early stress tolerance pathways may achieve more durable clinical responses to MAPK pathway inhibitors.

Human cells experience a Zn2+ pulse in early G1

Zinc is an essential micronutrient required for all domains of life. Cells maintain zinc homeostasis using a network of transporters, buffers, and transcription factors. Zinc is required for mammalian cell proliferation, and zinc homeostasis is remodeled during the cell cycle, but whether labile zinc changes in naturally cycling cells has not been established. We use genetically encoded fluorescent reporters, long-term time-lapse imaging, and computational tools to track labile zinc over the cell cycle in response to changes in growth media zinc and knockdown of the zinc-regulatory transcription factor MTF-1. Cells experience a pulse of labile zinc in early G1, whose magnitude varies with zinc in growth media. Knockdown of MTF-1 increases labile zinc and the zinc pulse. Our results suggest that cells need a minimum zinc pulse to proliferate and that if labile zinc levels are too high, cells pause proliferation until labile cellular zinc is lowered.

Toward a systems-level probing of tumor clonality

Cancer has been described as a genetic disease that clonally evolves in the face of selective pressures imposed by cell-intrinsic and extrinsic factors. Although classical models based on genetic data predominantly propose Darwinian mechanisms of cancer evolution, recent single-cell profiling of cancers has described unprecedented heterogeneity in tumors providing support for alternative models of branched and neutral evolution through both genetic and non-genetic mechanisms. Emerging evidence points to a complex interplay between genetic, non-genetic, and extrinsic environmental factors in shaping the evolution of tumors. In this perspective, we briefly discuss the role of cell-intrinsic and extrinsic factors that shape clonal behaviors during tumor progression, metastasis, and drug resistance. Taking examples of pre-malignant states associated with hematological malignancies and esophageal cancer, we discuss recent paradigms of tumor evolution and prospective approaches to further enhance our understanding of this spatiotemporally regulated process.

Unraveling non-genetic heterogeneity in cancer with dynamical models and computational tools

Individual cells within an otherwise genetically homogenous population constantly undergo fluctuations in their molecular state, giving rise to non-genetic heterogeneity. Such diversity is being increasingly implicated in cancer therapy resistance and metastasis. Identifying the origins of non-genetic heterogeneity is therefore crucial for making clinical breakthroughs. We discuss with examples how dynamical models and computational tools have provided critical multiscale insights into the nature and consequences of non-genetic heterogeneity in cancer. We demonstrate how mechanistic modeling has been pivotal in establishing key concepts underlying non-genetic diversity at various biological scales, from population dynamics to gene regulatory networks. We discuss advances in single-cell longitudinal profiling techniques to reveal patterns of non-genetic heterogeneity, highlighting the ongoing efforts and challenges in statistical frameworks to robustly interpret such multimodal datasets. Moving forward, we stress the need for data-driven statistical and mechanistically motivated dynamical frameworks to come together to develop predictive cancer models and inform therapeutic strategies.

Multiple cancer types rapidly escape from multiple MAPK inhibitors to generate mutagenesis-prone subpopulations

Many cancers harbor pro-proliferative mutations of the mitogen-activated protein kinase (MAPK) pathway and many targeted inhibitors now exist for clinical use, but drug resistance remains a major issue. We recently showed that BRAF-driven melanoma cells treated with BRAF inhibitors can non-genetically adapt to drug within 3-4 days to escape quiescence and resume slow proliferation. Here we show that this phenomenon is not unique to melanomas treated with BRAF inhibitors but rather is widespread across many clinical MAPK inhibitors and cancer types driven by EGFR, KRAS, and BRAF mutations. In all treatment contexts examined, a subset of cells can escape drug-induced quiescence within four days to resume proliferation. These escapee cells broadly experience aberrant DNA replication, accumulate DNA lesions, spend longer in G2-M cell cycle phases, and mount an ATR-dependent stress response. We further identify the Fanconi anemia (FA) DNA repair pathway as critical for successful mitotic completion in escapees. Long-term cultures, patient samples, and clinical data demonstrate a broad dependency on ATR- and FA-mediated stress tolerance. Together, these results highlight the pervasiveness with which MAPK-mutant cancers are able to rapidly escape drug and the importance of suppressing early stress tolerance pathways to potentially achieve more durable clinical responses to targeted MAPK pathway inhibitors.

Multi-range ERK responses shape the proliferative trajectory of single cells following oncogene induction

Oncogene-induced senescence is a phenomenon in which aberrant oncogene expression causes non-transformed cells to enter a non-proliferative state. Cells undergoing oncogenic induction display phenotypic heterogeneity, with some cells senescing and others remaining proliferative. The causes of heterogeneity remain unclear. We studied the sources of heterogeneity in the responses of human epithelial cells to oncogenic BRAF^V600E expression. We found that a narrow expression range of BRAF^V600E generated a wide range of activities of its downstream effector ERK. In population-level and single-cell assays, ERK activity displayed a non-monotonic relationship to proliferation, with intermediate ERK activities leading to maximal proliferation. We profiled gene expression across a range of ERK activities over time and characterized four distinct ERK response classes, which we propose act in concert to generate the ERK-proliferation response. Altogether, our studies map the input-output relationships between ERK activity and proliferation, elucidating how heterogeneity can be generated during oncogene induction.

Multiplexed and reproducible high content screening of live and fixed cells using Dye Drop

High-throughput measurement of cells perturbed using libraries of small molecules, gene knockouts, or different microenvironmental factors is a key step in functional genomics and pre-clinical drug discovery. However, it remains difficult to perform accurate single-cell assays in 384-well plates, limiting many studies to well-average measurements (e.g., CellTiter-Glo®). Here we describe a public domain Dye Drop method that uses sequential density displacement and microscopy to perform multi-step assays on living cells. We use Dye Drop cell viability and DNA replication assays followed by immunofluorescence imaging to collect single-cell dose-response data for 67 investigational and clinical-grade small molecules in 58 breast cancer cell lines. By separating the cytostatic and cytotoxic effects of drugs computationally, we uncover unexpected relationships between the two. Dye Drop is rapid, reproducible, customizable, and compatible with manual or automated laboratory equipment. Dye Drop improves the tradeoff between data content and cost, enabling the collection of information-rich perturbagen-response datasets.

19F MRI-fluorescence imaging dual-modal cell tracking with partially fluorinated nanoemulsions

As a noninvasive “hot-spot” imaging technology, fluorine-19 magnetic resonance imaging (19F MRI) has been extensively used in cell tracking. However, the peculiar physicochemical properties of perfluorocarbons (PFCs), the most commonly used 19F MRI agents, sometimes cause low sensitivity, poor cell uptake, and misleading results. In this study, a partially fluorinated agent, perfluoro-tert-butyl benzyl ether, was used to formulate a 19F MRI-fluorescence imaging (FLI) dual-modal nanoemulsion for cell tracking. Compared with PFCs, the partially fluorinated agent showed considerably improved physicochemical properties, such as lower density, shorter longitudinal relaxation times, and higher solubility to fluorophores, while maintaining high 19F MRI sensitivity. After being formulated into stable, monodisperse, and paramagnetic Fe3+-promoted nanoemulsions, the partially fluorinated agent was used in 19F MRI-FLI dual imaging tracking of lung cancer A549 cells and macrophages in an inflammation mouse model.

Adaptive tracking algorithm for trajectory analysis of cells and layer-by-layer assessment of motility dynamics

Tracking biological objects such as cells or subcellular components imaged with time-lapse microscopy enables us to understand the molecular principles about the dynamics of cell behaviors. However, automatic object detection, segmentation and extracting trajectories remain as a rate-limiting step due to intrinsic challenges of video processing. This paper presents an adaptive tracking algorithm (Adtari) that automatically finds the optimum search radius and cell linkages to determine trajectories in consecutive frames. A critical assumption in most tracking studies is that displacement remains unchanged throughout the movie and cells in a few frames are usually analyzed to determine its magnitude. Tracking errors and inaccurate association of cells may occur if the user does not correctly evaluate the value or prior knowledge is not present on cell movement. The key novelty of our method is that minimum intercellular distance and maximum displacement of cells between frames are dynamically computed and used to determine the threshold distance. Since the space between cells is highly variable in a given frame, our software recursively alters the magnitude to determine all plausible matches in the trajectory analysis. Our method therefore eliminates a major preprocessing step where a constant distance was used to determine the neighbor cells in tracking methods. Cells having multiple overlaps and splitting events were further evaluated by using the shape attributes including perimeter, area, ellipticity and distance. The features were applied to determine the closest matches by minimizing the difference in their magnitudes. Finally, reporting section of our software were used to generate instant maps by overlaying cell features and trajectories. Adtari was validated by using videos with variable signal-to-noise, contrast ratio and cell density. We compared the adaptive tracking with constant distance and other methods to evaluate performance and its efficiency. Our algorithm yields reduced mismatch ratio, increased ratio of whole cell track, higher frame tracking efficiency and allows layer-by-layer assessment of motility to characterize single-cells. Adaptive tracking provides a reliable, accurate, time efficient and user-friendly open source software that is well suited for analysis of 2D fluorescence microscopy video datasets.

Imaging developmental cell cycles

The last decade has seen a major expansion in development of live biosensors, the tools needed to genetically encode them into model organisms, and the microscopic techniques used to visualize them. When combined, these offer us powerful tools with which to make fundamental discoveries about complex biological processes. In this review, we summarize the availability of biosensors to visualize an essential cellular process, the cell cycle, and the techniques for single-cell tracking and quantification of these reporters. We also highlight studies investigating the connection of cellular behavior to the cell cycle, particularly through live imaging, and anticipate exciting discoveries with the combination of these technologies in developmental contexts.

Single cell biology-a Keystone Symposia report

Single cell biology has the potential to elucidate many critical biological processes and diseases, from development and regeneration to cancer. Single cell analyses are uncovering the molecular diversity of cells, revealing a clearer picture of the variation among and between different cell types. New techniques are beginning to unravel how differences in cell state-transcriptional, epigenetic, and other characteristics-can lead to different cell fates among genetically identical cells, which underlies complex processes such as embryonic development, drug resistance, response to injury, and cellular reprogramming. Single cell technologies also pose significant challenges relating to processing and analyzing vast amounts of data collected. To realize the potential of single cell technologies, new computational approaches are needed. On March 17-19, 2021, experts in single cell biology met virtually for the Keystone eSymposium "Single Cell Biology" to discuss advances both in single cell applications and technologies.

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.

Computational methods for characterizing and learning from heterogeneous cell signaling data

Heterogeneity in cell signaling pathways is increasingly appreciated as a fundamental feature of cell biology and a driver of clinically relevant disease phenotypes. Understanding the causes of heterogeneity, the cellular mechanisms used to control heterogeneity, and the downstream effects of heterogeneity in single cells are all key obstacles for manipulating cellular populations and treating disease. Recent advances in genetic engineering, including multiplexed fluorescent reporters, have provided unprecedented measurements of signaling heterogeneity, but these vast data sets are often difficult to interpret, necessitating the use of computational techniques to extract meaning from the data. Here, we review recent advances in computational methods for extracting meaning from these novel data streams. In particular, we evaluate how machine learning methods related to dimensionality reduction and classification can identify structure in complex, dynamic datasets, simplifying interpretation. We also discuss how mechanistic models can be merged with heterogeneous data to understand the underlying differences between cells in a population. These methods are still being developed, but the work reviewed here offers useful applications of specific analysis techniques that could enable the translation of single-cell signaling data to actionable biological understanding.

Melanoma subpopulations that rapidly escape MAPK pathway inhibition incur DNA damage and rely on stress signalling

Despite the increasing number of effective anti-cancer therapies, successful treatment is limited by the development of drug resistance. While the contribution of genetic factors to drug resistance is undeniable, little is known about how drug-sensitive cells first evade drug action to proliferate in drug. Here we track the responses of thousands of single melanoma cells to BRAF inhibitors and show that a subset of cells escapes drug via non-genetic mechanisms within the first three days of treatment. Cells that escape drug rely on ATF4 stress signalling to cycle periodically in drug, experience DNA replication defects leading to DNA damage, and yet out-proliferate other cells over extended treatment. Together, our work reveals just how rapidly melanoma cells can adapt to drug treatment, generating a mutagenesis-prone subpopulation that expands over time.