Optogenetic manipulation identifies the roles of ERK and AKT dynamics in controlling mouse embryonic stem cell exit from pluripotency

Molecular basis of cell fate plasticity - insights from the privileged cells

In the post-Yamanaka era, the rolling balls on Waddington's hilly landscape not only roll downward, but also go upward or sideways. This new-found mobility implies that the tantalizing somatic cell plasticity fueling regeneration, once only known to planarians and newts, might be sparking in the cells of mice and humans, if only we knew how to fully unlock it. The hope for ultimate regeneration was made even more tangible by the observations that partial reprogramming by the Yamanaka factors reverses many hallmarks of aging [76], even though the underlying mechanism remains unclear. We intend to revisit the milestones in the evolving understanding of cell fate plasticity and glean molecular insights from an unusual somatic cell state, the privileged cell state that reprograms in a manner defying the stochastic model. We synthesize our view of the molecular underpinning of cell fate plasticity, from which we speculate how to harness it for regeneration and rejuvenation. We propose that senescence, aging and malignancy represent distinct cell states with definable biochemical and biophysical parameters.

Gossiping about death: Apoptosis-induced ERK waves as coordinators of multicellular fate decisions

Apoptosis is now recognized as a highly dynamic process that involves the release of a large set of signaling molecules that convey information to cells neighboring an apoptotic site. Recent studies in epithelial systems have discovered that apoptotic cells trigger waves of pulses of mitogen-activated protein kinase (MAPK) / extracellular signal-regulated kinase (ERK) pathway activity in their neighbors. At the single-cell level, the ERK pulses emerge from the MAPK pathway's excitable network properties, such as ultrasensitivity and adaptation. At the cell population level, apoptosis-induced ERK waves (AiEWs) emerge from propagation of ERK pulses across cells via a mechanism that involves mechanical inputs and paracrine signaling. AiEWs enable cell populations to dynamically coordinate fate decision signaling during tissue homeostasis and development. This spatio-temporal signaling mechanism can be hijacked by cancer cells to induce drug-tolerant persister states when apoptosis is triggered by cytotoxic or targeted therapies, undermining treatment efficacy. In this review, we summarize our current understanding of AiEWs, including their initiation, propagation, and coordination of fate decision signaling within a population. We discuss how the relatively simple properties of single cells, and their interactions within a collective coordinate these dynamic signaling patterns. We highlight their implication in resistance to cancer therapy and explore potential strategies to target these waves to re-sensitize cancer cells. Finally, we discuss emerging technologies and future directions to expand the study of this biological phenomenon.

A Frequency Domain Analysis of the Growth Factor-Driven Extra-Cellular-Regulated Kinase (ERK) Pathway

The ERK pathway is an important biochemical cascade and acts as a master regulator of myriad cell processes including cell proliferation, differentiation, and survival. Early biochemical work established that the timing of ERK phosphorylation was an important determinant of PC12 cell fate, with extended phosphorylation (with nerve growth factor treatment) linked to differentiation but rapid on-off ERK phosphorylation kinetics (with epidermal growth factor treatment) linked to cell proliferation. Recent work from several laboratories has revealed that periodic forcing the phosphorylation of ERK with growth factors, light (optogenetics) or electronically can switch cell fate from proliferative to differentiated depending on type of stimulus (amplitude and frequency). Here, we take an ERK model and analyze it from the frequency domain perspective. The key is the transfer function, which provides a compact description of input (growth factor)-output (ERK activation) behavior over a range of input frequencies, allowing an understanding of system dynamics in terms of amplitude modulations, phase shifts, and signaling bandwidths. Our analysis of transfer functions indicates that, at normal receptor levels, the ERK pathway acts as a negative feedback amplifier to growth factor fluctuations, amplifying them at low receptor occupancy but suppressing them at high receptor occupancy. The frequency dependence is best described as a resonant low pass filter, which selectively filters out high frequency input oscillations. We use the transfer function to predict how different growth factor input dynamics shape ERK activation.

Optogenetic control of cAMP oscillations reveals frequency-selective transcription factor dynamics in Dictyostelium

Oscillatory dynamics and their modulation are crucial for cellular decision-making; however, analysing these dynamics remains challenging. Here, we present a tool that combines the light-activated adenylate cyclase mPAC with the cAMP biosensor Pink Flamindo, enabling precise manipulation and real-time monitoring of cAMP oscillation frequencies in Dictyostelium. High-frequency modulation of cAMP oscillations induced cell aggregation and multicellular formation, even at low cell densities, such as a few dozen cells. At the population level, chemotactic aggregation is driven by modulated frequency signals. Additionally, modulation of cAMP frequency significantly reduced the amplitude of the shuttling behaviour of the transcription factor GtaC, demonstrating low-pass filter characteristics capable of converting subtle oscillation changes, such as from 6 min to 4 min, into gene expression. These findings enhance our understanding of frequency-selective cellular decoding and its role in cellular signalling and development.

Common modes of ERK induction resolve into context-specific signalling via emergent networks and cell-type-specific transcriptional repression

Fibroblast Growth Factor signalling via ERK exerts diverse roles in development and disease. In mammalian preimplantation embryos and naïve pluripotent stem cells ERK promotes differentiation, whereas in primed pluripotent states closer to somatic differentiation ERK sustains self-renewal. How can the same pathway produce different outcomes in two related cell types? To explore context-dependent ERK signalling we generated cell and mouse lines that allow for tissue- and time-specific ERK activation. Using these tools, we find that specificity in ERK response is mostly mediated by repression of transcriptional targets that occur in tandem with reductions in chromatin accessibility at regulatory regions. Furthermore, immediate early ERK responses are largely shared by different cell types but produce cell-specific programmes as these responses interface with emergent networks in the responding cells. Induction in naïve pluripotency is accompanied by chromatin changes, whereas in later stages it is not, suggesting that chromatin context does not shape signalling response. Altogether, our data suggest that cell-type-specific responses to ERK signalling exploit the same immediate early response, but then sculpt it to specific lineages via repression of distinct cellular programmes.

aiSEGcell: User-friendly deep learning-based segmentation of nuclei in transmitted light images

Segmentation is required to quantify cellular structures in microscopic images. This typically requires their fluorescent labeling. Convolutional neural networks (CNNs) can detect these structures also in only transmitted light images. This eliminates the need for transgenic or dye fluorescent labeling, frees up imaging channels, reduces phototoxicity and speeds up imaging. However, this approach currently requires optimized experimental conditions and computational specialists. Here, we introduce "aiSEGcell" a user-friendly CNN-based software to segment nuclei and cells in bright field images. We extensively evaluated it for nucleus segmentation in different primary cell types in 2D cultures from different imaging modalities in hand-curated published and novel imaging data sets. We provide this curated ground-truth data with 1.1 million nuclei in 20,000 images. aiSEGcell accurately segments nuclei from even challenging bright field images, very similar to manual segmentation. It retains biologically relevant information, e.g. for demanding quantification of noisy biosensors reporting signaling pathway activity dynamics. aiSEGcell is readily adaptable to new use cases with only 32 images required for retraining. aiSEGcell is accessible through both a command line, and a napari graphical user interface. It is agnostic to computational environments and does not require user expert coding experience.

ERK signalling eliminates Nanog and maintains Oct4 to drive the formative pluripotency transition

Naïve epiblast cells in the embryo and pluripotent stem cells in vitro undergo developmental progression to a formative state competent for lineage specification. During this transition, transcription factors and chromatin are rewired to encode new functional features. Here, we examine the role of mitogen-activated protein kinase (ERK1/2) signalling in pluripotent state transition. We show that a primary consequence of ERK activation in mouse embryonic stem cells is elimination of Nanog, which precipitates breakdown of the naïve state gene regulatory network. Variability in pERK dynamics results in heterogeneous loss of Nanog and metachronous state transition. Knockdown of Nanog allows exit without ERK activation. However, transition to formative pluripotency does not proceed and cells collapse to an indeterminate identity. This outcome is due to failure to maintain expression of the central pluripotency factor Oct4. Thus, during formative transition ERK signalling both dismantles the naïve state and preserves pluripotency. These results illustrate how a single signalling pathway can both initiate and secure transition between cell states.

Low-frequency ERK and Akt activity dynamics are predictive of stochastic cell division events

Understanding the dynamics of intracellular signaling pathways, such as ERK1/2 (ERK) and Akt1/2 (Akt), in the context of cell fate decisions is important for advancing our knowledge of cellular processes and diseases, particularly cancer. While previous studies have established associations between ERK and Akt activities and proliferative cell fate, the heterogeneity of single-cell responses adds complexity to this understanding. This study employed a data-driven approach to address this challenge, developing machine learning models trained on a dataset of growth factor-induced ERK and Akt activity time courses in single cells, to predict cell division events. The most predictive models were developed by applying discrete wavelet transforms (DWTs) to extract low-frequency features from the time courses, followed by using Ensemble Integration, a data integration and predictive modeling framework. The results demonstrated that these models effectively predicted cell division events in MCF10A cells (F-measure=0.524, AUC=0.726). ERK dynamics were found to be more predictive than Akt, but the combination of both measurements further enhanced predictive performance. The ERK model`s performance also generalized to predicting division events in RPE cells, indicating the potential applicability of these models and our data-driven methodology for predicting cell division across different biological contexts. Interpretation of these models suggested that ERK dynamics throughout the cell cycle, rather than immediately after growth factor stimulation, were associated with the likelihood of cell division. Overall, this work contributes insights into the predictive power of intra-cellular signaling dynamics for cell fate decisions, and highlights the potential of machine learning approaches in unraveling complex cellular behaviors.

Lighting the way: recent developments and applications in molecular optogenetics

Molecular optogenetics utilizes genetically encoded, light-responsive protein switches to control the function of molecular processes. Over the last two years, there have been notable advances in the development of novel optogenetic switches, their utilization in elucidating intricate signaling pathways, and their progress toward practical applications in biotechnological processes, material sciences, and therapeutic applications. In this review, we discuss these areas, offer insights into recent developments, and contemplate future directions.

Conditional fluorescent mouse translocation reporters for ERK1/2 and AKT signaling

Understanding how cells activate intracellular signaling pathways in response to external signals, such as growth factors, is a longstanding goal of cell and developmental biology. Recently, live-cell signaling reporters have greatly expanded our understanding of signaling dynamics in response to wide-ranging stimuli and chemical or genetic perturbation, both ex vivo (cell lines) and in vivo (whole embryos or animals). Among the many varieties of reporter systems, translocation reporters that change sub-cellular localization in response to pathway activation have received considerable attention for their ease of use compared to FRET systems and favorable response times compared to transcriptional reporters. We reasoned that mouse reporter lines expressed in a conditional fashion would be a useful addition to the arsenal of mouse genetic tools, as such lines remain undeveloped despite widespread use of these sensors. We therefore created and validated two novel mouse reporter lines at the ROSA26 locus. One expresses an ERK1/2 pathway reporter and a nuclear marker from a single transcript, while the second additionally expresses an AKT reporter in order to simultaneously interrogate both pathways.

Quantitative insights in tissue growth and morphogenesis with optogenetics

Cells communicate with each other to jointly regulate cellular processes during cellular differentiation and tissue morphogenesis. This multiscale coordination arises through the spatiotemporal activity of morphogens to pattern cell signaling and transcriptional factor activity. This coded information controls cell mechanics, proliferation, and differentiation to shape the growth and morphogenesis of organs. While many of the molecular components and physical interactions have been identified in key model developmental systems, there are still many unresolved questions related to the dynamics involved due to challenges in precisely perturbing and quantitatively measuring signaling dynamics. Recently, a broad range of synthetic optogenetic tools have been developed and employed to quantitatively define relationships between signal transduction and downstream cellular responses. These optogenetic tools can control intracellular activities at the single cell or whole tissue scale to direct subsequent biological processes. In this brief review, we highlight a selected set of studies that develop and implement optogenetic tools to unravel quantitative biophysical mechanisms for tissue growth and morphogenesis across a broad range of biological systems through the manipulation of morphogens, signal transduction cascades, and cell mechanics. More generally, we discuss how optogenetic tools have emerged as a powerful platform for probing and controlling multicellular development.

Shedding light on stem cells: Optogenetics uncover the role of ERK dynamics in pluripotency

In this issue of Developmental Cell, Arekatla et al. use optogenetic technologies to dissect the roles of ERK and AKT dynamics in pluripotency. They show how mouse embryonic stem cells can retain memory of signaling events controlling their fate.