Cell State Transitions Research Articles

Cellular Automata Modeling as a Tool in Corrosion Management.

Cellular automata models have emerged as a valuable tool in corrosion management. This manuscript provides an overview of the application of cellular automata models in corrosion research, highlighting their benefits and contributions to understanding the complex nature of corrosion processes. Cellular automata models offer a computational approach to simulating corrosion behavior at the microscale, capturing the intricate interactions between electrochemical reactions, material properties, and environmental factors and generating a new vision of predictive maintenance. It reviews the key features of cellular automata, such as the grid-based representation of the material surface, the definition of state variables, and the rules governing cell-state transitions. The ability to model local interactions and emergent global behavior makes cellular automata particularly suitable for simulating corrosion processes. Finally, cellular automata models offer a powerful and versatile approach to studying corrosion processes, expanding models that can continue to enhance our understanding of corrosion and contribute to the development of effective corrosion prevention and control strategies.

Featured immune characteristics of COVID-19 and systemic lupus erythematosus revealed by multidimensional integrated analyses.

Coronavirus disease 2019 (COVID-19) shares similar immune characteristics with autoimmune diseases like systemic lupus erythematosus (SLE). However, such associations have not yet been investigated at the single-cell level. We integrated and analyzed RNA sequencing results from different patients and normal controls from the GEO database and identified subsets of immune cells that might involve in the pathogenesis of SLE and COVID- 19. We also disentangled the characteristic alterations in cell and molecular subset proportions as well as gene expression patterns in SLE patients compared with COVID-19 patients. Key immune characteristic genes (such as CXCL10 and RACK1) and multiple immune-related pathways (such as the coronavirus disease-COVID-19, T-cell receptor signaling, and MIF-related signaling pathways) were identified. We also highlighted the differences in peripheral blood mononuclear cells (PBMCs) between SLE and COVID-19 patients. Moreover, we provided an opportunity to comprehensively probe underlying B-cell‒cell communication with multiple ligand-receptor pairs (MIF-CD74+CXCR4, MIF-CD74+CD44) and the differentiation trajectory of B-cell clusters that is deemed to promote cell state transitions in COVID-19 and SLE. Our results demonstrate the immune response differences and immune characteristic similarities, such as the cytokine storm, between COVID-19 and SLE, which might pivotally function in the pathogenesis of the two diseases and provide potential intervention targets for both diseases.

Dynamical modeling of proliferative-invasive plasticity and IFNγ signaling in melanoma reveals mechanisms of PD-L1 expression heterogeneity

BackgroundPhenotypic heterogeneity of melanoma cells contributes to drug tolerance, increased metastasis, and immune evasion in patients with progressive disease. Diverse mechanisms have been individually reported to shape extensive intra-tumor and...

Substrate-specific binding of 8-oxoguanine DNA glycosylase 1 (OGG1) reprograms mucosal adaptations to chronic airway injury.

Recent advances have uncovered the non-random distribution of 7, 8-dihydro-8-oxoguanine (8-oxoGua) induced by reactive oxygen species, which is believed to have epigenetic effects. Its cognate repair protein, 8-oxoguanine DNA glycosylase 1 (OGG1), reads oxidative substrates and participates in transcriptional initiation. When redox signaling is activated in small airway epithelial cells, the DNA repair function of OGG1 is repurposed to transmit acute inflammatory signals accompanied by cell state transitions and modification of the extracellular matrix. Epithelial-mesenchymal and epithelial-immune interactions act cooperatively to establish a local niche that instructs the mucosal immune landscape. If the transitional cell state governed by OGG1 remains responsive to inflammatory mediators instead of differentiation, the collateral damage provides positive feedback to inflammation, ascribing inflammatory remodeling to one of the drivers in chronic pathologies. In this review, we discuss the substrate-specific read through OGG1 has evolved in regulating the innate immune response, controlling adaptations of the airway to environmental and inflammatory injury, with a focus on the reader function of OGG1 in initiation and progression of epithelial to mesenchymal transitions in chronic pulmonary disease.

Tissue factor is a critical regulator of radiation therapy-induced glioblastoma remodeling.

Radiation therapy (RT) provides therapeutic benefits for patients with glioblastoma (GBM), but inevitably induces poorly understood global changes in GBM and its microenvironment (TME) that promote radio-resistance and recurrence. Through a cell surface marker screen, we identified that CD142 (tissue factor or F3) is robustly induced in the senescence-associated β-galactosidase (SA-βGal)-positive GBM cells after irradiation. F3 promotes clonal expansion of irradiated SA-βGal+ GBM cells and orchestrates oncogenic TME remodeling by activating both tumor-autonomous signaling and extrinsic coagulation pathways. Intratumoral F3 signaling induces a mesenchymal-like cell state transition and elevated chemokine secretion. Simultaneously, F3-mediated focal hypercoagulation states lead to activation of tumor-associated macrophages (TAMs) and extracellular matrix (ECM) remodeling. A newly developed F3-targeting agent potently inhibits the aforementioned oncogenic events and impedes tumor relapse invivo. These findings support F3 as a critical regulator for therapeutic resistance and oncogenic senescence in GBM, opening potential therapeutic avenues.

Dynamic network-guided CRISPRi screen identifies CTCF-loop-constrained nonlinear enhancer gene regulatory activity during cell state transitions.

Comprehensive enhancer discovery is challenging because most enhancers, especially those contributing to complex diseases, have weak effects on gene expression. Our gene regulatory network modeling identified that nonlinear enhancer gene regulation during cell state transitions can be leveraged to improve the sensitivity of enhancer discovery. Using human embryonic stem cell definitive endoderm differentiation as a dynamic transition system, we conducted a mid-transition CRISPRi-based enhancer screen. We discovered a comprehensive set of enhancers for each of the core endoderm-specifying transcription factors. Many enhancers had strong effects mid-transition but weak effects post-transition, consistent with the nonlinear temporal responses to enhancer perturbation predicted by the modeling. Integrating three-dimensional genomic information, we were able to develop a CTCF-loop-constrained Interaction Activity model that can better predict functional enhancers compared to models that rely on Hi-C-based enhancer-promoter contact frequency. Our study provides generalizable strategies for sensitive and systematic enhancer discovery in both normal and pathological cell state transitions.

An organoid-based CRISPR-Cas9 screen for regulators of intestinal epithelial maturation and cell fate

Generation of functionally mature organs requires exquisite control of transcriptional programs governing cell state transitions during development. Despite advances in understanding the behavior of adult intestinal stem cells and their progeny, the transcriptional regulators that control the emergence of the mature intestinal phenotype remain largely unknown. Using mouse fetal and adult small intestinal organoids, we uncover transcriptional differences between the fetal and adult state and identify rare adult-like cells present in fetal organoids. This suggests that fetal organoids have an inherent potential to mature, which is locked by a regulatory program. By implementing a CRISPR-Cas9 screen targeting transcriptional regulators expressed in fetal organoids, we establishSmarca4andSmarcc1as important factors safeguarding the immature progenitor state. Our approach demonstrates the utility of organoid models in the identification of factors regulating cell fate and state transitions during tissue maturation and reveals that SMARCA4 and SMARCC1 prevent precocious differentiation during intestinal development.

β-catenin/CBP activation of mTORC1 signaling promotes partial epithelial-mesenchymal states in head and neck cancer

Head and neck cancers, which include oral squamous cell carcinoma (OSCC) as a major subsite, exhibit cellular plasticity that includes features of an epithelial-mesenchymal transition (EMT), referred to as partial-EMT (p-EMT). To identify molecular mechanisms contributing to OSCC plasticity, we performed a multiphase analysis of single cell RNA sequencing (scRNAseq) data from human OSCC. This included a multiresolution characterization of cancer cell subgroups to identify pathways and cell states that are heterogeneously represented, followed by casual inference analysis to elucidate activating and inhibitory relationships between these pathways and cell states. This approach revealed signaling networks associated with hierarchical cell state transitions, which notably included an association between β-catenin-driven CREB-binding protein (CBP) activity and mTORC1 signaling. This network was associated with subpopulations of cancer cells that were enriched for markers of the p-EMT state and poor patient survival. Functional analyses revealed that β-catenin/CBP induced mTORC1 activity in part through the transcriptional regulation of a raptor-interacting protein, chaperonin containing TCP1 subunit 5 (CCT5). Inhibition of β-catenin-CBP activity through the use of the orally active small molecule, E7386, reduced the expression of CCT5 and mTORC1 activity in vitro, and inhibited p-EMT-associated markers and tumor development in a murine model of OSCC. Our study highlights the use of multiresolution network analyses of scRNAseq data to identify targetable signals for therapeutic benefit, thus defining an underappreciated association between β-catenin/CBP and mTORC1 signaling in head and neck cancer plasticity.

Discovering cellular programs of intrinsic and extrinsic drivers of metabolic traits using LipocyteProfiler

A primary obstacle in translating genetic associations with disease into therapeutic strategies is elucidating the cellular programs affected by genetic risk variants and effector genes. Here, we introduce LipocyteProfiler, a cardiometabolic-disease-oriented high-content image-based profiling tool that enables evaluation of thousands of morphological and cellular profiles that can be systematically linked to genes and genetic variants relevant to cardiometabolic disease. We show that LipocyteProfiler allows surveillance of diverse cellular programs by generating rich context- and process-specific cellular profiles across hepatocyte and adipocyte cell-state transitions. We use LipocyteProfiler to identify known and novel cellular mechanisms altered by polygenic risk of metabolic disease, including insulin resistance, fat distribution, and the polygenic contribution to lipodystrophy. LipocyteProfiler paves the way for large-scale forward and reverse deep phenotypic profiling in lipocytes and provides a framework for the unbiased identification of causal relationships between genetic variants and cellular programs relevant to human disease.

Low-level repressive histone marks fine-tune gene transcription in neural stem cells.

Coordinated regulation of gene activity by transcriptional and translational mechanisms poise stem cells for a timely cell-state transition during differentiation. Although important for all stemness-to-differentiation transitions, mechanistic understanding of the fine-tuning of gene transcription is lacking due to the compensatory effect of translational control. We used intermediate neural progenitor (INP) identity commitment to define the mechanisms that fine-tune stemness gene transcription in fly neural stem cells (neuroblasts). We demonstrate that the transcription factor FruitlessC (FruC) binds cis-regulatory elements of most genes uniquely transcribed in neuroblasts. Loss of fruC function alone has no effect on INP commitment but drives INP dedifferentiation when translational control is reduced. FruC negatively regulates gene expression by promoting low-level enrichment of the repressive histone mark H3K27me3 in gene cis-regulatory regions. Identical to fruC loss-of-function, reducing Polycomb Repressive Complex 2 activity increases stemness gene activity. We propose low-level H3K27me3 enrichment fine-tunes gene transcription in stem cells, a mechanism likely conserved from flies to humans.

A RhoA-mediated biomechanical response in Schwann cells modulates peripheral nerve myelination

Myelin improves axonal conduction velocity and is essential for nerve development and regeneration. In peripheral nerves, Schwann cells depend on bidirectional mechanical and biochemical signaling to form the myelin sheath but the mechanism underlying this process is not understood. Rho GTPases are integrators of “outside-in” signaling that link cytoskeletal dynamics with cellular architecture to regulate morphology and adhesion. Using Schwann cell-specific gene inactivation in the mouse, we discovered that RhoA promotes the initiation of myelination, and is required to both drive and terminate myelin growth at different stages of peripheral myelination, suggesting developmentally-specific modes of action. In Schwann cells, RhoA targets actin filament turnover, via Cofilin 1, actomyosin contractility and cortical actin-membrane attachments. This mechanism couples actin cortex mechanics with the molecular organization of the cell boundary to target specific signaling networks that regulate axon-Schwann cell interaction/adhesion and myelin growth. This work shows that RhoA is a key component of a biomechanical response required to control Schwann cell state transitions for proper myelination of peripheral nerves.

DIPG-19. BAF COMPLEX PERTURBATION AS A NOVEL THERAPEUTIC OPPORTUNITY IN H3K27M PEDIATRIC GLIOMA

Abstract Epigenetic dysregulation resulting in stalled development plays a crucial role in pediatric cancer tumorigenesis. Diffuse midline gliomas (DMG) are universally fatal pediatric brain cancers refractory to standard of care treatment modalities. These malignancies are driven by heterozygous mutations in genes encoding histone 3 (H3K27M) which create an aberrant epigenetic landscape that keeps glioma cells in an undifferentiated stem-like state. Consequently, targeting epigenetic regulators to restore the epigenome and force glioma cells to exit this stem-like cell state represents a promising new therapeutic strategy for H3K27M-DMG. To interrogate for epigenetic dependencies, we performed a CRISPR/Cas9 inactivation screen in patient-derived H3K27M-DMG neurospheres using an epigenetically focused sgRNA library and identified several core components of the mammalian BAF (SWI/SNF) chromatin remodeling complex as genetic vulnerabilities. Validation assays revealed that knockout of the BAF catalytic subunit BRG1 results in decreased glioma cell proliferation and tumor growth in orthotopic mouse models. Mechanistically, genome wide localization and DNA accessibility studies combined with regulatory network analysis demonstrated that BRG1 controls the transcription factor and enhancer landscapes that maintain H3K27M-DMG cells in a cycling, oligodendrocyte precursor cell-like state. Single cell transcriptome analysis in vitro and immunofluorescence studies in vivo confirmed that genetic perturbation of this chromatin remodeler promotes progression of differentiation along the astrocytic lineage. Similarly, pharmacological suppression of BRG1 activity, using both catalytic inhibitors as well as recently developed degraders, opposes tumor cell proliferation, stimulates cell state transition, and improves overall survival of patient-derived xenograft models. Interestingly, these effects seem to be restricted to H3K27M mutant glioma, as H3 wildtype glioma cells were less sensitive to BRG1 inhibition both in vitro and in vivo. In summary, we demonstrate that the BAF complex contributes to the maintenance of glioma cells in a proliferative stem-like state and that its therapeutic inhibition has translational potential for children bearing H3K27M-DMG.

Automated time-lapse data segmentation reveals in vivo cell state dynamics.

Embryonic development proceeds as a series of orderly cell state transitions built upon noisy molecular processes. We defined gene expression and cell motion states using single-cell RNA sequencing data and in vivo time-lapse cell tracking data of the zebrafish tailbud. We performed a parallel identification of these states using dimensional reduction methods and a change point detection algorithm. Both types of cell states were quantitatively mapped onto embryos, and we used the cell motion states to study the dynamics of biological state transitions over time. The time average pattern of cell motion states is reproducible among embryos. However, individual embryos exhibit transient deviations from the time average forming left-right asymmetries in collective cell motion. Thus, the reproducible pattern of cell states and bilateral symmetry arise from temporal averaging. In addition, collective cell behavior can be a source of asymmetry rather than a buffer against noisy individual cell behavior.

Morphodynamical cell state description via live-cell imaging trajectory embedding

Time-lapse imaging is a powerful approach to gain insight into the dynamic responses of cells, but the quantitative analysis of morphological changes over time remains challenging. Here, we exploit the concept of “trajectory embedding” to analyze cellular behavior using morphological feature trajectory histories—that is, multiple time points simultaneously, rather than the more common practice of examining morphological feature time courses in single timepoint (snapshot) morphological features. We apply this approach to analyze live-cell images of MCF10A mammary epithelial cells after treatment with a panel of microenvironmental perturbagens that strongly modulate cell motility, morphology, and cell cycle behavior. Our morphodynamical trajectory embedding analysis constructs a shared cell state landscape revealing ligand-specific regulation of cell state transitions and enables quantitative and descriptive models of single-cell trajectories. Additionally, we show that incorporation of trajectories into single-cell morphological analysis enables (i) systematic characterization of cell state trajectories, (ii) better separation of phenotypes, and (iii) more descriptive models of ligand-induced differences as compared to snapshot-based analysis. This morphodynamical trajectory embedding is broadly applicable to the quantitative analysis of cell responses via live-cell imaging across many biological and biomedical applications.

Predicting anti-cancer drug combination responses with a temporal cell state network model.

Cancer chemotherapy combines multiple drugs, but predicting the effects of drug combinations on cancer cell proliferation remains challenging, even for simple in vitro systems. We hypothesized that by combining knowledge of single drug dose responses and cell state transition network dynamics, we could predict how a population of cancer cells will respond to drug combinations. We tested this hypothesis here using three targeted inhibitors of different cell cycle states in two different cell lines in vitro. We formulated a Markov model to capture temporal cell state transitions between different cell cycle phases, with single drug data constraining how drug doses affect transition rates. This model was able to predict the landscape of all three different pairwise drug combinations across all dose ranges for both cell lines with no additional data. While further application to different cell lines, more drugs, additional cell state networks, and more complex co-culture or in vivo systems remain, this work demonstrates how currently available or attainable information could be sufficient for prediction of drug combination response for single cell lines in vitro.

Glial progenitor heterogeneity and key regulators revealed by single-cell RNA sequencing provide insight to regeneration in spinal cord injury

Recent studies have revealed the heterogeneous nature of astrocytes; however, how diverse constituents of astrocyte-lineage cells are regulated in adult spinal cord after injury and contribute to regeneration remains elusive. We perform single-cell RNA sequencing of GFAP-expressing cells from sub-chronic spinal cord injury models and identify and compare with the subpopulations in acute-stage data. We find subpopulations with distinct functional enrichment and their identities defined by subpopulation-specific transcription factors and regulons. Immunohistochemistry, RNAscope experiments, and quantification by stereology verify the molecular signature, location, and morphology of potential resident neural progenitors or neural stem cells in the adult spinal cord before and after injury and uncover the populations of the intermediate cells enriched in neuronal genes that could potentially transition into other subpopulations. This study has expanded the knowledge of the heterogeneity and cell state transition of glial progenitors in adult spinal cord before and after injury.

A lymph node slice culture model to characterize T cell activation dynamics and anti-viral responses in human tissue

Abstract T cell activation in the lymph node (LN) is critical to initiating adaptive immune responses to vaccination, tumors, and infection. We previously demonstrated that T cells from human tissue sites (blood, LNs, bone marrow, lung) undergo conserved cell state transitions during activation. However, these studies were performed in suspension culture from dissociated tissue, depleting the spatial and signaling contributions of the tissue microenvironment. To address this, we developed techniques for culture and single-cell analysis of human LN slices, which preserve tissue architecture, local signaling, and physiological cell frequencies. Single-cell RNA-seq (scRNA-seq) of matched LN suspension and slice cultures stimulated with anti-CD3/28 antibody tetramers revealed distinct activation patterns. While anti-CD3/28 stimulation is commonly used to study T cell activation, this reagent circumvents antigen presentation and may not fully recapitulate antigen-mediated signaling. Conversely, antigen-dependent stimulation with superantigen mimics require MHCII/TCR binding and may benefit from the intact microenvironment in slice culture. We discovered a distinct metabolic intermediate through scRNA-seq analysis of superantigen-stimulated LN suspension and slice cultures that is not observed with anti-CD3/28 stimulation. Overall, these studies demonstrate the utility of analyzing T cell responses in intact tissue and comparative analysis of distinct mechanisms of activation. 1T32GM145440-01 (MSTP Training Grant) U19AI128949 (NIAID)

Abstract 284: Pro-Inflammatory Adventitial Fibroblast Contribute To Aortic Aneurysms In Loeys Dietz Syndrome

Introduction: Vascular smooth muscle cell (SMC) phenotype modulation is implicated in thoracic aneurysm formation, however, the role of adventitial fibroblasts (AdvFib) in aneurysm formation remains poorly characterized. Loeys-Dietz Syndrome (LDS), caused by a spectrum of mutations in the TGF-β signaling cascade, leads to aggressive thoracic aneurysms. Given the ubiquitous nature of TGF-β signaling machinery, the exact cell type(s) responsible for initiation of LDS pathogenesis is poorly understood. Methods: We performed single cell transcriptomic characterization of aortic root and ascending aortic samples from LDS patients ((n=6 LDS (harboring TGFB2 , TGFBR1 , TGFBR2 , or SMAD3 mutation); n=2 Donor control)) as well as root/ascending aorta from a murine model of LDS ( Tgfbr2 G357W/+ ) to understand cell-state transitions and transcriptomic alterations in LDS. Results: Single cell RNA sequencing (scRNAseq) of human and mice LDS samples (in total >40,000 cells) revealed a secondary pattern of cellular activation in LDS as compared to Marfan Syndrome. Instead of SMC phenotypic modulation as seen in MFS, LDS appears to preferentially modulate adventitial fibroblasts (AdvFib) phenotype in the Tgfbr2 G357W/+ mouse model. Human LDS patient’s AdvFib turn on high levels of macrophage-recruiting pro-inflammatory cytokines CCL2 and HLA-B, with a corresponding 1.8-fold increase in LDS aortic wall macrophages compared to Donor. A more extreme pattern was observed in the Tgfbr2 G357W/+ LDS mouse model. While Tgfbr2 G357W/+ SMC are transcriptomically similar to wild type counterparts, AdvFib were activated into a pro-inflammatory state associated with increased aortic macrophage recruitment ( Ccl2 , Il6 , Vcam1, and Cxcl2 ) and fibrotic response ( Col1a1 , Col1a2 , Col3a1, and Fn1 ). A 6-fold increase in the number of aortic wall macrophages was identified in Tgfbr2 G357W/+ compared to WT. Conclusions: LDS mouse and human AdvFib undergo phenotypic alterations into a pro-inflammatory state evidenced by increased expression of numerous cytokines, macrophage recruitment, and ECM deposition. AdvFib, in addition to SMCs, are potentially another important pathological cell population in LDS aneurysm formation.

Leveraging developmental landscapes for model selection in Boolean gene regulatory networks.

Boolean models are a well-established framework to model developmental gene regulatory networks (DGRNs) for acquisition of cellular identities. During the reconstruction of Boolean DGRNs, even if the network structure is given, there is generally a large number of combinations of Boolean functions that will reproduce the different cell fates (biological attractors). Here we leverage the developmental landscape to enable model selection on such ensembles using the relative stability of the attractors. First we show that previously proposed measures of relative stability are strongly correlated and we stress the usefulness of the one that captures best the cell state transitions via the mean first passage time (MFPT) as it also allows the construction of a cellular lineage tree. A property of great computational importance is the insensitivity of the different stability measures to changes in noise intensities. That allows us to use stochastic approaches to estimate the MFPT and thereby scale up the computations to large networks. Given this methodology, we revisit different Boolean models of Arabidopsis thaliana root development, showing that a most recent one does not respect the biologically expected hierarchy of cell states based on relative stabilities. We therefore developed an iterative greedy algorithm that searches for models which satisfy the expected hierarchy of cell states and found that its application to the root development model yields many models that meet this expectation. Our methodology thus provides new tools that can enable reconstruction of more realistic and accurate Boolean models of DGRNs.

Ratiometric sensing of Pnt and Yan transcription factor levels confers ultrasensitivity to photoreceptor fate transitions in Drosophila.

Cell state transitions are often triggered by large changes in the concentrations of transcription factors and therefore large differences in their stoichiometric ratios. Whether cells can elicit transitions using modest changes in the ratios of co-expressed factors is unclear. Here, we investigate how cells in the Drosophila eye resolve state transitions by quantifying the expression dynamics of the ETS transcription factors Pnt and Yan. Eye progenitor cells maintain a relatively constant ratio of Pnt/Yan protein, despite expressing both proteins with pulsatile dynamics. A rapid and sustained twofold increase in the Pnt/Yan ratio accompanies transitions to photoreceptor fates. Genetic perturbations that modestly disrupt the Pnt/Yan ratio produce fate transition defects consistent with the hypothesis that transitions are normally driven by a twofold shift in the ratio. A biophysical model based on cooperative Yan-DNA binding coupled with non-cooperative Pnt-DNA binding illustrates how twofold ratio changes could generate ultrasensitive changes in target gene transcription to drive fate transitions. Thus, coupling cell state transitions to the Pnt/Yan ratio sensitizes the system to modest fold-changes, conferring robustness and ultrasensitivity to the developmental program.