Patient iPSC-derived neural progenitor cells display aberrant cell cycle control, p53, and DNA damage response protein expression in schizophrenia.

BACKGROUND: Schizophrenia (SCZ) is a severe psychiatric disorder associated with alterations in early brain development. Details of underlying pathomechanisms remain unclear, despite genome and transcriptome studies providing evidence for aberrant cellular phenotypes and pathway deregulation in developing neuronal cells. However, mechanistic insight at the protein level is limited. METHODS: Here, we investigate SCZ-specific protein expression signatures of neuronal progenitor cells (NPC) derived from patient iPSC in comparison to healthy controls using high-throughput Western Blotting (DigiWest) in a targeted proteomics approach. RESULTS: SCZ neural progenitors displayed altered expression and phosphorylation patterns related to Wnt and MAPK signaling, protein synthesis, cell cycle regulation and DNA damage response. Consistent with impaired cell cycle control, SCZ NPCs also showed accumulation in the G2/M cell phase and reduced differentiation capacity. Furthermore, we correlated these findings with elevated p53 expression and phosphorylation levels in SCZ patient-derived cells, indicating a potential implication of p53 in hampering cell cycle progression and efficient neurodevelopment in SCZ. CONCLUSIONS: Through targeted proteomics we demonstrate that SCZ NPC display coherent mechanistic alterations in regulation of DNA damage response, cell cycle control and p53 expression. These findings highlight the suitability of iPSC-based approaches for modeling psychiatric disorders and contribute to a better understanding of the disease mechanisms underlying SCZ, particularly during early development.

Inertial effect of cell state velocity on the quiescence-proliferation fate decision.

Energy landscapes can provide intuitive depictions of population heterogeneity and dynamics. However, it is unclear whether individual cell behavior, hypothesized to be determined by initial position and noise, is faithfully recapitulated. Using the p21-/Cdk2-dependent quiescence-proliferation decision in breast cancer dormancy as a testbed, we examined single-cell dynamics on the landscape when perturbed by hypoxia, a dormancy-inducing stress. Combining trajectory-based energy landscape generation with single-cell time-lapse microscopy, we found that a combination of initial position and velocity on a p21/Cdk2 landscape, but not position alone, was required to explain the observed cell fate heterogeneity under hypoxia. This is likely due to additional cell state information such as epigenetic features and/or other species encoded in velocity but missing in instantaneous position determined by p21 and Cdk2 levels alone. Here, velocity dependence manifested as inertia: cells with higher cell cycle velocities prior to hypoxia continued progressing along the cell cycle under hypoxia, resisting the change in landscape towards cell cycle exit. Such inertial effects may markedly influence cell fate trajectories in tumors and other dynamically changing microenvironments where cell state transitions are governed by coordination across several biochemical species.

Macrophage Cell Cycle.

Macrophages are dynamic and plastic immune cells essential for tissue homeostasis and pathogen defense. Their cell cycle regulation is highly influenced by intrinsic and extrinsic signals facilitating rapid responses to infections and tissue damage. Dysregulation of their cell cycle leads to diseases like cancer and HIV. This chapter highlights aspects of the macrophage cell cycle crucial for the development of targeted therapies.

Stochastic Boolean model of normal and aberrant cell cycles in budding yeast.

The cell cycle of budding yeast is governed by an intricate protein regulatory network whose dysregulation can lead to lethal mistakes or aberrant cell division cycles. In this work, we model this network in a Boolean framework for stochastic simulations. Our model is sufficiently detailed to account for the phenotypes of 40 mutant yeast strains (83% of the experimentally characterized strains that we simulated) and also to simulate an endoreplicating strain (multiple rounds of DNA synthesis without mitosis) and a strain that exhibits 'Cdc14 endocycles' (periodic transitions between metaphase and anaphase). Because our model successfully replicates the observed properties of both wild-type yeast cells and many mutant strains, it provides a reasonable, validated starting point for more comprehensive stochastic-Boolean models of cell cycle controls. Such models may provide a better understanding of cell cycle anomalies in budding yeast and ultimately in mammalian cells.

Capturing the mechanosensitivity of cell proliferation in models of epithelium.

Despite the primary role of cell proliferation in tissue development and homeostatic maintenance, the interplay between cell density, cell mechanoresponse, and cell growth and division is not yet understood. In this article, we address this issue by reporting on an experimental investigation of cell proliferation on all time- and length-scales of the development of a model tissue, grown on collagen-coated glass or deformable substrates. Through extensive data analysis, we demonstrate the relation between mechanoresponse and probability for cell division, as a function of the local cell density. Motivated by these results, we construct a minimal model of cell division in tissue environment that can recover the data. By parameterizing the growth and the dividing phases of the cell cycle, and introducing such a proliferation model in dissipative particle dynamics simulations, we recover the mechanoresponsive, time-dependent density profiles in 2D tissues growing to macroscopic scales. The importance of separating the cell population into growing and dividing cells, each characterized by a particular time scale, is further emphasized by calculations of density profiles based on adapted Fisher-Kolmogorov equations. Together, these results show that the mechanoresponse on the level of a constitutive cell and its proliferation results in a matrix-sensitive active pressure. The latter evokes massive cooperative displacement of cells in the invading tissue and is a key factor for developing large-scale structures in the steady state.

Coupling of cell growth modulation to asymmetric division and cell cycle regulation in Caulobacter crescentus.

In proliferating bacteria, growth rate is often assumed to be similar between daughter cells. However, most of our knowledge of cell growth derives from studies on symmetrically dividing bacteria. In many α-proteobacteria, asymmetric division is a normal part of the life cycle, with each division producing daughter cells with different sizes and fates. Here, we demonstrate that the functionally distinct swarmer and stalked daughter cells produced by the model α-proteobacterium Caulobacter crescentus can have different average growth rates under nutrient-replete conditions despite sharing an identical genome and environment. The discrepancy in growth rate is due to a growth slowdown associated with the cell cycle stage preceding DNA replication (the G1 phase), which initiates in the late predivisional mother cell before daughter cell separation. Both progenies experience a G1-associated growth slowdown, but the effect is more severe in swarmer cells because they have a longer G1 phase. Activity of SpoT, which produces the (p)ppGpp alarmone and extends the G1 phase, accentuates the cell cycle-dependent growth slowdown. Collectively, our data identify a coupling between cell growth, the G1 phase, and asymmetric division that C. crescentus may exploit for environmental adaptation through SpoT activity. This coupling differentially modulates the growth rate of functionally distinct daughter cells, thereby altering the relative abundance of ecologically important G1-specific traits within the population.

Newton's cradle: Cell cycle regulation by two mutually inhibitory oscillators.

The cell division cycle is a fundamental physiological process displaying a great degree of plasticity during the course of multicellular development. This plasticity is evident in the transition from rapid and stringently-timed divisions of the early embryo to subsequent size-controlled mitotic cycles. Later in development, cells may pause and restart proliferation in response to myriads of internal or external signals, or permanently exit the cell cycle following terminal differentiation or senescence. Beyond this, cells can undergo modified cell division variants, such as endoreplication, which increases their ploidy, or meiosis, which reduces their ploidy. This wealth of behaviours has led to numerous conceptual analogies intended as frameworks for understanding the proliferative program. Here, we aim to unify these mechanisms under one dynamical paradigm. To this end, we take a control theoretical approach to frame the cell cycle as a pair of arrestable and mutually-inhibiting, doubly amplified, negative feedback oscillators controlling chromosome replication and segregation events, respectively. Under appropriate conditions, this framework can reproduce fixed-period oscillations, checkpoint arrests of variable duration, and endocycles. Subsequently, we use phase plane and bifurcation analysis to explain the dynamical basis of these properties. Then, using a physiologically realistic, biochemical model, we show that the very same regulatory structure underpins the diverse functions of the cell cycle control network. We conclude that Newton's cradle may be a suitable mechanical analogy of how the cell cycle is regulated.

Cellular Energy Cycle Mediates an Advection-Like Forward Cell Flow to Support Collective Invasion.

Collective cell migration is a model for nonequilibrium biological dynamics, which is important for morphogenesis, pattern formation, and cancer metastasis. The current understanding of cellular collective dynamics is based primarily on cells moving within a 2D epithelial monolayer. However, solid tumors often invade surrounding tissues in the form of a stream-like 3D structure, and how biophysical cues are integrated at the cellular level to give rise to this collective streaming remains unclear. Here, it is shown that cell cycle-mediated bioenergetics drive a forward advective flow of cells and energy to the front to support 3D collective invasion. The cell division cycle mediates a corresponding energy cycle such that cellular adenosine triphosphate (ATP) energy peaks just before division. A reaction-advection-diffusion (RAD) type model coupled with experimental measurements further indicates that most cells enter an active division cycle at rear positions during 3D streaming. Once the cells progress to a later stage toward division, the high intracellular energy allows them to preferentially stream toward the tip and become leader cells. This energy-driven cellular flow may be a fundamental characteristic of 3D collective dynamics based on thermodynamic principles important for not only cancer invasion but also tissue morphogenesis.

Behavioral dynamics of medicinal signaling cells from porcine bone marrow in long-term culture.

Medicinal signaling cells (MSC) hold promise for regenerative medicine due to their ability to repair damaged tissues. However, their effectiveness can be affected by how long they are cultured in the lab. This study investigated how passage number influences key properties for regenerative medicine of pig bone marrow MSC. The medicinal signiling cells derived from pig bone marrow (BM-MSC) were cultured in D-MEM High Glucose supplemented with 15% foetal bovine serum until the 25th passage and assessed their growth, viability, ability to differentiate into different cell types (plasticity), and cell cycle activity. Our findings showed that while the cells remained viable until the 25th passage, their ability to grow and differentiate declined after the 5th passage. Additionally, cells in later passages spent more time in a resting phase, suggesting reduced activity. In conclusion, the number of passages is a critical factor for maintaining ideal MSC characteristics. From the 9th passage BM-MSC exhibit decline in proliferation, differentiation potential, and cell cycle activity. Given this, it is possible to suggest that the use of 5th passage cells is the most suitable for therapeutic applications.

PRMT1 mediates the proliferation of Y79 retinoblastoma cells by regulating the p53/p21/CDC2/cyclin B pathway.

Retinoblastoma (RB) is the most common intraocular malignancy among children and presents a certain mortality risk, especially in low- and middle-income countries. Clarifying the molecular mechanisms underlying the onset and progression of retinoblastoma is vital for devising effective cancer treatment approaches. PRMT1, a major type I PRMT, plays significant roles in cancer development. However, its expression and role in retinoblastoma are still unclear. Our research revealed a marked increase in PRMT1 levels in both retinoblastoma tissues and Y79 cells. The overexpression of PRMT1 in Y79 cells promoted their growth and cell cycle progression. Conversely, the suppression of PRMT1 hindered the growth of Y79 cells and impeded cell cycle progression. Mechanistically, PRMT1 mediated the growth of Y79 retinoblastoma cells by targeting the p53/p21/CDC2/Cyclin B pathway. Additionally, the ability of PRMT1 knockdown to suppress cell proliferation was also observed in vivo. Overall, PRMT1 could function as a potential target for therapeutic treatment in individuals with retinoblastoma.

Modeling the START transition in the budding yeast cell cycle.

Budding yeast, Saccharomyces cerevisiae, is widely used as a model organism to study the genetics underlying eukaryotic cellular processes and growth critical to cancer development, such as cell division and cell cycle progression. The budding yeast cell cycle is also one of the best-studied dynamical systems owing to its thoroughly resolved genetics. However, the dynamics underlying the crucial cell cycle decision point called the START transition, at which the cell commits to a new round of DNA replication and cell division, are under-studied. The START machinery involves a central cyclin-dependent kinase; cyclins responsible for starting the transition, bud formation, and initiating DNA synthesis; and their transcriptional regulators. However, evidence has shown that the mechanism is more complicated than a simple irreversible transition switch. Activating a key transcription regulator SBF requires the phosphorylation of its inhibitor, Whi5, or an SBF/MBF monomeric component, Swi6, but not necessarily both. Also, the timing and mechanism of the inhibitor Whi5's nuclear export, while important, are not critical for the timing and execution of START. Therefore, there is a need for a consolidated model for the budding yeast START transition, reconciling regulatory and spatial dynamics. We built a detailed mathematical model (START-BYCC) for the START transition in the budding yeast cell cycle based on established molecular interactions and experimental phenotypes. START-BYCC recapitulates the underlying dynamics and correctly emulates key phenotypic traits of ~150 known START mutants, including regulation of size control, localization of inhibitor/transcription factor complexes, and the nutritional effects on size control. Such a detailed mechanistic understanding of the underlying dynamics gets us closer towards deconvoluting the aberrant cellular development in cancer.

Multiciliogenesis: Tricking the cell-cycle machinery to build hundreds of cilia.

Multiciliated cells produce over a hundred motile cilia anchored to the membrane by modified centrioles. Recent work has characterized an alternative cell cycle used by this post-mitotic cell type to generate additional centrioles without undergoing cell division.

The cellular basis of feeding-dependent body size plasticity in sea anemones.

Many animals share a lifelong capacity to adapt their growth rates and body sizes to changing environmental food supplies. However, the cellular and molecular basis underlying this plasticity remains only poorly understood. We therefore studied how the sea anemones Nematostella vectensis and Aiptasia (Exaiptasia pallida) respond to feeding and starvation. Combining quantifications of body size and cell numbers with mathematical modelling, we observed that growth and shrinkage rates in Nematostella are exponential, stereotypic and accompanied by dramatic changes in cell numbers. Notably, shrinkage rates, but not growth rates, are independent of body size. In the facultatively symbiotic Aiptasia, we show that growth and cell proliferation rates are dependent on the symbiotic state. On a cellular level, we found that >7% of all cells in Nematostella juveniles reversibly shift between S/G2/M and G1/G0 cell cycle phases when fed or starved, respectively. Furthermore, we demonstrate that polyp growth and cell proliferation are dependent on TOR signalling during feeding. Altogether, we provide a benchmark and resource for further investigating the nutritional regulation of body plasticity on multiple scales using the genetic toolkit available for Nematostella.

A comprehensive review of computational cell cycle models in guiding cancer treatment strategies.

This article reviews the current knowledge and recent advancements in computational modeling of the cell cycle. It offers a comparative analysis of various modeling paradigms, highlighting their unique strengths, limitations, and applications. Specifically, the article compares deterministic and stochastic models, single-cell versus population models, and mechanistic versus abstract models. This detailed analysis helps determine the most suitable modeling framework for various research needs. Additionally, the discussion extends to the utilization of these computational models to illuminate cell cycle dynamics, with a particular focus on cell cycle viability, crosstalk with signaling pathways, tumor microenvironment, DNA replication, and repair mechanisms, underscoring their critical roles in tumor progression and the optimization of cancer therapies. By applying these models to crucial aspects of cancer therapy planning for better outcomes, including drug efficacy quantification, drug discovery, drug resistance analysis, and dose optimization, the review highlights the significant potential of computational insights in enhancing the precision and effectiveness of cancer treatments. This emphasis on the intricate relationship between computational modeling and therapeutic strategy development underscores the pivotal role of advanced modeling techniques in navigating the complexities of cell cycle dynamics and their implications for cancer therapy.

Protocol for in vitro co-culture, proliferation, and cell cycle analyses of patient-derived leukemia cells.

Leukemia niche impacts quiescence; however, culturing patient-derived samples ex vivo is technically challenging. Here, we present a protocol for in vitro co-culture of patient-derived xenograft acute lymphoblastic leukemia (PDX-ALL) cells with human mesenchymal stem cells (MSCs). We describe steps for labeling PDX-ALL cells with CellTrace Violet dye to demonstrate MSC-primed PDX-ALL cycling. We then detail procedures to identify MSC-primed G0/quiescent PDX-ALL cells via Hoechst-33342/Pyronin Y live cell cycle analysis. For complete details on the use and execution of this protocol, please refer to Pal et al.1,2.

Activation of the Neuronal Cell Cycle in Brains in Amnestic Mild Cognitive Impairment: Early Involvement in the Progression of Alzheimer's Disease.

Activation of cell-cycle machinery in Alzheimer's disease (AD) brain was reported by Mark Smith and colleagues and by other researchers. Among other biochemical processes underlying this activation, the notion that AD brain, under the onslaught of oxidative and nitrosative damage leading to neuronal loss, neurons would attempt to replenish their numbers by entering the cell cycle. However, being post-mitotic, neurons entering the cell cycle would become trapped therein, ultimately leading to death of these neurons. Yang and co-workers and the Butterfield laboratory first reported that similar activation of the cell cycle was present in the brains of individuals with amnestic mild cognitive impairment (MCI), arguably the earliest clinical stage of AD, but who demonstrate normal activities of daily living and no dementia. Activation of the cell cycle in MCI brain is consonant with the concept that this process is an early aspect in the progression of AD. This brief review article discusses these findings and recognizes the contribution of Dr. Mark Smith to the investigation of cell-cycle activation in AD brain and other aspects of AD neuropathology.

Eukaryotic cell size regulation and its implications for cellular function and dysfunction.

Depending on cell type, environmental inputs, and disease, the cells in the human body can have widely different sizes. In recent years, it has become clear that cell size is a major regulator of cell function. However, we are only beginning to understand how the optimization of cell function determines a given cell's optimal size. Here, we review currently known size control strategies of eukaryotic cells and the intricate link of cell size to intracellular biomolecular scaling, organelle homeostasis, and cell cycle progression. We detail the cell size-dependent regulation of early development and the impact of cell size on cell differentiation. Given the importance of cell size for normal cellular physiology, cell size control must account for changing environmental conditions. We describe how cells sense environmental stimuli, such as nutrient availability, and accordingly adapt their size by regulating cell growth and cell cycle progression. Moreover, we discuss the correlation of pathological states with misregulation of cell size and how for a long time this was considered a downstream consequence of cellular dysfunction. We review newer studies that reveal a reversed causality, with misregulated cell size leading to pathophysiological phenotypes such as senescence and aging. In summary, we highlight the important roles of cell size in cellular function and dysfunction, which could have major implications for both diagnostics and treatment in the clinic.

A Reversible Neural Stem Cell Quiescence and Activation Culture System for Metabolic Study.

Stem cells in vivo can transit between quiescence and activation, two metabolically distinct states. It is increasingly appreciated that cell metabolism assumes profound roles in stem cell maintenance and tissue homeostasis. However, the lack of suitable models greatly hinders our understanding of the metabolic control of stem cell quiescence and activation. In the present study, we have utilized classical signaling pathways and developed a cell culture system to model reversible NSC quiescence and activation. Unlike activated ones, quiescent NSCs manifested distinct morphology characteristics, cell proliferation, and cell cycle properties but retained the same cell proliferation and differentiation potentials once reactivated. Further transcriptomic analysis revealed that extensive metabolic differences existed between quiescent and activated NSCs. Subsequent experimentations confirmed that NSC quiescence and activation transition was accompanied by a dramatic yet coordinated and dynamic shift in RNA metabolism, protein synthesis, and mitochondrial and autophagy activity. The present work not only showcases the broad utilities of this powerful in vitro NSC quiescence and activation culture system but also provides timely insights for the field and warrants further investigations.

ConfluentFUCCI for fully-automated analysis of cell-cycle progression in a highly dense collective of migrating cells.

Understanding mechanisms underlying various physiological and pathological processes often requires accurate and fully automated analysis of dense cell populations that collectively migrate. In such multicellular systems, there is a rising interest in the relations between biophysical and cell cycle progression aspects. A seminal tool that led to a leap in real-time study of cell cycle is the fluorescent ubiquitination-based cell cycle indicator (FUCCI). Here, we introduce ConfluentFUCCI, an open-source graphical user interface-based framework that is designed, unlike previous tools, for fully automated analysis of cell cycle progression, cellular dynamics, and cellular morphology, in highly dense migrating cell collectives. We integrated into ConfluentFUCCI's pipeline state-of-the-art tools such as Cellpose, TrackMate, and Napari, some of which incorporate deep learning, and we wrap the entire tool into an isolated computational environment termed container. This provides an easy installation and workflow that is independent of any specific operation system. ConfluentFUCCI offers accurate nuclear segmentation and tracking using FUCCI tags, enabling comprehensive investigation of cell cycle progression at both the tissue and single-cell levels. We compare ConfluentFUCCI to the most recent relevant tool, showcasing its accuracy and efficiency in handling large datasets. Furthermore, we demonstrate the ability of ConfluentFUCCI to monitor cell cycle transitions, dynamics, and morphology within densely packed epithelial cell populations, enabling insights into mechanotransductive regulation of cell cycle progression. The presented tool provides a robust approach for investigating cell cycle-related phenomena in complex biological systems, offering potential applications in cancer research and other fields.

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.