Journal articles: 'Cell state transition'

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Schramm, Vern L. "Enzymatic Transition State Theory and Transition State Analogue Design." Journal of Biological Chemistry 282, no. 39 (August 9, 2007): 28297–300. http://dx.doi.org/10.1074/jbc.r700018200.

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Gravenmier, Curtis, Ling Zhang, Lynn Moscinski, and Jeffrey West. "Abstract PR008: Cell state transitions drive the evolution of disease progression in B-cell acute lymphoblastic leukemia." Cancer Research 84, no. 3_Supplement_2 (February 1, 2024): PR008. http://dx.doi.org/10.1158/1538-7445.canevol23-pr008.

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Abstract A mathematical framework is constructed to predict the risk of B-lymphoblastic leukemia (B-ALL) relapse post-induction chemotherapy. The framework is a Markov chain model that quantifies spontaneous cell state transitions between distinct immunophenotypic subpopulations defined by CD34 and CD38 expression relative to neutrophils. Cell states are analyzed via flow cytometry pre- and post-treatment, providing insight into the evolution of cell state transition rates during disease progression. Cancer stem cells (CSCs) are hypothesized to promote tumor progression through innate chemoresistance and self-renewal. Ostensible CSCs were first identified in acute myeloid leukemia and were found to have a CD34+/CD38- immunophenotype similar to hematopoietic stem cells. However, the isolation of CSCs from B-ALL has proved more difficult. B-ALL cells with stem cell-like properties have been reported with variable immunophenotype, perhaps due to temporal variation of CD34 and CD38 expression in this setting. We hypothesized that transitions between stem cell-like, hematogone-like, and naive B-cell-like leukemia subpopulations play a significant role in B-ALL disease progression. To test this hypothesis, we trained a Markov chain mathematical model using flow cytometry characterization of four B-ALL cell states with their normal counterpart appearing in parentheses: CD34+/CD38- (hematopoietic stem cells), CD34+/CD38+ (stage 1 hematogones), CD34-/CD38+ (stage 2 and 3 hematogones), and CD34-/CD38- (naïve B-cells). An iterative numerical search procedure was used to derive patient-specific Markov matrices, describing the stochastic cell state transitions. This flow cytometry evaluation was performed on a cohort of patient samples of peripheral blood (N=46) and bone marrow (N=63) with matched clinical features such as BCR::ABL1 status, comprehensive genomic profiling, minimal residual disease (MRD) post-induction chemotherapy, and 3-year relapse. Critical to our goal of quantifying the evolution of state transition rates, we also obtained bone marrow measurements for a cohort of normal/healthy individuals. Patients were divided into post-induction flow MRD positive (N=16), MRD negative (N=30), healthy (N=6) cohorts, as well as relapsed and non-relapsed cohorts to compare features of the transition matrices. Importantly, pre-treatment flow cytometry derived cell state distribution alone is not predictive of relapse or MRD. In contrast, pre-treatment Markov chain transition parameters are found to be clinically predictive of relapse and MRD. MRD correlates to high reciprocity (the product of incoming and outgoing transitions) of the stem cell state. This approach provides supporting evidence that cell state transitions drive B-ALL disease progression. There is an additional strong correlation between Markov transition parameters and both BCR::ABL1 and BCR::ABL1-like B-ALL classification. Finally, comparison of Markov parameters pre- and post-treatment quantifies the evolutionary selection pressures acting on transition rates induced by chemotherapy treatment. Citation Format: Curtis Gravenmier, Ling Zhang, Lynn Moscinski, Jeffrey West. Cell state transitions drive the evolution of disease progression in B-cell acute lymphoblastic leukemia [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Cancer Evolution and Data Science: The Next Frontier; 2023 Dec 3-6; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_2):Abstract nr PR008.

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Brackston, Rowan D., Eszter Lakatos, and Michael P. H. Stumpf. "Transition state characteristics during cell differentiation." PLOS Computational Biology 14, no. 9 (September 20, 2018): e1006405. http://dx.doi.org/10.1371/journal.pcbi.1006405.

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Wang, Ping, Chaoming Song, Hang Zhang, Zhanghan Wu, Xiao-Jun Tian, and Jianhua Xing. "Epigenetic state network approach for describing cell phenotypic transitions." Interface Focus 4, no. 3 (June 6, 2014): 20130068. http://dx.doi.org/10.1098/rsfs.2013.0068.

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Recent breakthroughs of cell phenotype reprogramming impose theoretical challenges on unravelling the complexity of large circuits maintaining cell phenotypes coupled at many different epigenetic and gene regulation levels, and quantitatively describing the phenotypic transition dynamics. A popular picture proposed by Waddington views cell differentiation as a ball sliding down a landscape with valleys corresponding to different cell types separated by ridges. Based on theories of dynamical systems, we establish a novel ‘epigenetic state network’ framework that captures the global architecture of cell phenotypes, which allows us to translate the metaphorical low-dimensional Waddington epigenetic landscape concept into a simple-yet-predictive rigorous mathematical framework of cell phenotypic transitions. Specifically, we simplify a high-dimensional epigenetic landscape into a collection of discrete states corresponding to stable cell phenotypes connected by optimal transition pathways among them. We then apply the approach to the phenotypic transition processes among fibroblasts (FBs), pluripotent stem cells (PSCs) and cardiomyocytes (CMs). The epigenetic state network for this case predicts three major transition pathways connecting FBs and CMs. One goes by way of PSCs. The other two pathways involve transdifferentiation either indirectly through cardiac progenitor cells or directly from FB to CM. The predicted pathways and multiple intermediate states are supported by existing microarray data and other experiments. Our approach provides a theoretical framework for studying cell phenotypic transitions. Future studies at single-cell levels can directly test the model predictions.

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Buder, Thomas, Andreas Deutsch, Michael Seifert, and Anja Voss-Böhme. "CellTrans: An R Package to Quantify Stochastic Cell State Transitions." Bioinformatics and Biology Insights 11 (January 1, 2017): 117793221771224. http://dx.doi.org/10.1177/1177932217712241.

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Many normal and cancerous cell lines exhibit a stable composition of cells in distinct states which can, e.g., be defined on the basis of cell surface markers. There is evidence that such an equilibrium is associated with stochastic transitions between distinct states. Quantifying these transitions has the potential to better understand cell lineage compositions. We introduce CellTrans, an R package to quantify stochastic cell state transitions from cell state proportion data from fluorescence-activated cell sorting and flow cytometry experiments. The R package is based on a mathematical model in which cell state alterations occur due to stochastic transitions between distinct cell states whose rates only depend on the current state of a cell. CellTrans is an automated tool for estimating the underlying transition probabilities from appropriately prepared data. We point out potential analytical challenges in the quantification of these cell transitions and explain how CellTrans handles them. The applicability of CellTrans is demonstrated on publicly available data on the evolution of cell state compositions in cancer cell lines. We show that CellTrans can be used to (1) infer the transition probabilities between different cell states, (2) predict cell line compositions at a certain time, (3) predict equilibrium cell state compositions, and (4) estimate the time needed to reach this equilibrium. We provide an implementation of CellTrans in R, freely available via GitHub ( https://github.com/tbuder/CellTrans ).

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Chu, Xiakun, and Jin Wang. "Insights into the cell fate decision-making processes from chromosome structural reorganizations." Biophysics Reviews 3, no. 4 (December 2022): 041402. http://dx.doi.org/10.1063/5.0107663.

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The cell fate decision-making process, which provides the capability of a cell transition to a new cell type, involves the reorganizations of 3D genome structures. Currently, the high temporal resolution picture of how the chromosome structural rearrangements occur and further influence the gene activities during the cell-state transition is still challenging to acquire. Here, we study the chromosome structural reorganizations during the cell-state transitions among the pluripotent embryonic stem cell, the terminally differentiated normal cell, and the cancer cell using a nonequilibrium landscape-switching model implemented in the molecular dynamics simulation. We quantify the chromosome (de)compaction pathways during the cell-state transitions and find that the two pathways having the same destinations can merge prior to reaching the final states. The chromosomes at the merging states have similar structural geometries but can differ in long-range compartment segregation and spatial distribution of the chromosomal loci and genes, leading to cell-type-specific transition mechanisms. We identify the irreversible pathways of chromosome structural rearrangements during the forward and reverse transitions connecting the same pair of cell states, underscoring the critical roles of nonequilibrium dynamics in the cell-state transitions. Our results contribute to the understanding of the cell fate decision-making processes from the chromosome structural perspective.

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Ichimura, Taro, Liang-da Chiu, Katsumasa Fujita, Satoshi Kawata, Tomonobu M. Watanabe, Toshio Yanagida, and Hideaki Fujita. "Visualizing Cell State Transition Using Raman Spectroscopy." PLoS ONE 9, no. 1 (January 7, 2014): e84478. http://dx.doi.org/10.1371/journal.pone.0084478.

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Huang, Rongsheng, and Jinzhi Lei. "Dynamics of gene expression with positive feedback to histone modifications at bivalent domains." International Journal of Modern Physics B 32, no. 07 (March 5, 2018): 1850075. http://dx.doi.org/10.1142/s0217979218500753.

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Experiments have shown that in embryonic stem cells, the promoters of many lineage-control genes contain “bivalent domains”, within which the nucleosomes possess both active (H3K4me3) and repressive (H3K27me3) marks. Such bivalent modifications play important roles in maintaining pluripotency in embryonic stem cells. Here, to investigate gene expression dynamics when there are regulations in bivalent histone modifications and random partition in cell divisions, we study how positive feedback to histone methylation/demethylation controls the transition dynamics of the histone modification patterns along with cell cycles. We constructed a computational model that includes dynamics of histone marks, three-stage chromatin state transitions, transcription and translation, feedbacks from protein product to enzymes to regulate the addition and removal of histone marks, and the inheritance of nucleosome state between cell cycles. The model reveals how dynamics of both nucleosome state transition and gene expression are dependent on the enzyme activities and feedback regulations. Results show that the combination of stochastic histone modification at each cell division and the deterministic feedback regulation work together to adjust the dynamics of chromatin state transition in stem cell regenerations.

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Gopal, Priyanka, Aaron Petty, Kevin Rogacki, Titas Bera, Rohan Bareja, Craig Peacock, and Mohamed Abazeed. "Abstract 2229: Cell state transitions shape the intratumoral composition of small cell lung carcinoma." Cancer Research 83, no. 7_Supplement (April 4, 2023): 2229. http://dx.doi.org/10.1158/1538-7445.am2023-2229.

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Abstract Introduction: Small cell lung carcinoma (SCLC) is characterized by rapid growth, early metastases, and initial response followed by almost invariable resistance to therapy. Studies to date have not determined the extent that diverse transcriptional programs drive SCLC and contribute to its lethality. We sought to characterize the intra-tumoral transcriptional heterogeneity of SCLC. We identify multivalent, distinct, and commutable transcriptional states that confer discrete functions in individual SCLC tumors. Methods: We developed a biorepository of patient-derived xenografts (PDX) (n = 64) and matched PDX-derived ex vivo lines. We used multi-omic profiling (RNAseq, scRNAseq, and ATAC seq), single-cell fluorescence tracking of fate-defining transcription factor (TF)-driven states, and mathematical and statistical models (Markov chain) to study the topology of the SCLC transcriptional landscape and its plasticity. Human tumor material and associated clinical data were obtained after informed written consent on an IRB-approved prospective registry. Results: We show that individual SCLC tumors are more heterogenous than previously appreciated, displaying distinctive equilibria in the proportion of cells within well-delimited cellular states (ASCL1, NEUROD1 and YAP1). We also show that transcriptional states undergo transitions, which we identified as a mechanism for maintaining cell state diversity. We measured the kinetics of state transitions using single-cell fluorescence tracking of ex vivo cultures and found that these measure were associated significantly with transition estimates using stochastic transition theory (i.e. Markov chains). ATAC-seq profiling indicated a role for the epigenome in the state diversity of SCLC. Namely, there was preferential promoter accessibility to Ascl1, NeuroD1, and Yap1 in a manner consistent with gene and protein expression in the respective subpopulations. Our results indicate that the transition rates between cell types in individual tumors were largely governed by tendencies to reach an equilibrium state that are critical for configuring intratumoral cell state proportions. Conclusion: In conclusion, we demonstrate that TF driven cell states can transition to maintain an equilibrium in cell state proportions. Our work advances a model of cellular states and program diversity in SCLC and nominates new therapeutic strategies designed to limit the plasticity of this lethal cancer. Citation Format: Priyanka Gopal, Aaron Petty, Kevin Rogacki, Titas Bera, Rohan Bareja, Craig Peacock, Mohamed Abazeed. Cell state transitions shape the intratumoral composition of small cell lung carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2229.

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Jagannathan, N. Suhas, Mario O. Ihsan, Xiao Xuan Kin, Roy E. Welsch, Marie-Véronique Clément, and Lisa Tucker-Kellogg. "Transcompp: understanding phenotypic plasticity by estimating Markov transition rates for cell state transitions." Bioinformatics 36, no. 9 (January 23, 2020): 2813–20. http://dx.doi.org/10.1093/bioinformatics/btaa021.

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Abstract Motivation Gradual population-level changes in tissues can be driven by stochastic plasticity, meaning rare stochastic transitions of single-cell phenotype. Quantifying the rates of these stochastic transitions requires time-intensive experiments, and analysis is generally confounded by simultaneous bidirectional transitions and asymmetric proliferation kinetics. To quantify cellular plasticity, we developed Transcompp (Transition Rate ANalysis of Single Cells to Observe and Measure Phenotypic Plasticity), a Markov modeling algorithm that uses optimization and resampling to compute best-fit rates and statistical intervals for stochastic cell-state transitions. Results We applied Transcompp to time-series datasets in which purified subpopulations of stem-like or non-stem cancer cells were exposed to various cell culture environments, and allowed to re-equilibrate spontaneously over time. Results revealed that commonly used cell culture reagents hydrocortisone and cholera toxin shifted the cell population equilibrium toward stem-like or non-stem states, respectively, in the basal-like breast cancer cell line MCF10CA1a. In addition, applying Transcompp to patient-derived cells showed that transition rates computed from short-term experiments could predict long-term trajectories and equilibrium convergence of the cultured cell population. Availability and implementation Freely available for download at http://github.com/nsuhasj/Transcompp. Supplementary information Supplementary data are available at Bioinformatics online.

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Bhargava, Pushpa M., and Sushil A. Chandani. "Regulation of cell division and malignant transformation." Bioscience Reports 8, no. 6 (December 1, 1988): 519–29. http://dx.doi.org/10.1007/bf01117330.

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The problem of regulation of cell division is essentially a problem of understanding regulation of transition from the resting state of a cell to the dividing state and vice versa. In malignancy the ability to revert back to a normal resting state is impaired. A model is presented which attempts to explain the control of the above transitions through control of uptake of essential nutrients by a transport-inhibitory protein. Experimental evidence in favour of the model is given.

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D’Aniello, Cristina, Federica Cermola, Eduardo J. Patriarca, and Gabriella Minchiotti. "Metabolic–Epigenetic Axis in Pluripotent State Transitions." Epigenomes 3, no. 3 (July 31, 2019): 13. http://dx.doi.org/10.3390/epigenomes3030013.

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Cell state transition (CST) occurs during embryo development and in adult life in response to different stimuli and is associated with extensive epigenetic remodeling. Beyond growth factors and signaling pathways, increasing evidence point to a crucial role of metabolic signals in this process. Indeed, since several epigenetic enzymes are sensitive to availability of specific metabolites, fluctuations in their levels may induce the epigenetic changes associated with CST. Here we analyze how fluctuations in metabolites availability influence DNA/chromatin modifications associated with pluripotent stem cell (PSC) transitions. We discuss current studies and focus on the effects of metabolites in the context of naïve to primed transition, PSC differentiation and reprogramming of somatic cells to induced pluripotent stem cells (iPSCs), analyzing their mechanism of action and the causal correlation between metabolites availability and epigenetic alteration.

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Fu, Xudong, Mohamed Nadhir Djekidel, and Yi Zhang. "A transcriptional roadmap for 2C-like–to–pluripotent state transition." Science Advances 6, no. 22 (May 2020): eaay5181. http://dx.doi.org/10.1126/sciadv.aay5181.

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In mouse embryonic stem cell (ESC), a small cell population displays totipotent features by expressing a set of genes that are transiently active in 2-cell–stage embryos. These 2-cell–like (2C-like) cells spontaneously transit back into the pluripotent state. We previously dissected the transcriptional dynamics of the transition from pluripotency to the totipotent 2C-like state and identified factors that modulate the process. However, how 2C-like cells transit back into the pluripotent state remains largely unknown. In this study, we analyzed the transcriptional dynamics from the 2C-like state to pluripotent ESCs and identified an intermediate state. The intermediate state characterized by two-wave step up-regulation of pluripotent genes is different from the one observed during the 2C-like entry transition. Nonsense-mediated Dux mRNA decay plays an important role in the 2C-like state exit. Thus, our study not only provides a transcriptional roadmap for 2C-like–to–pluripotent state transition but also reveals a key molecular event driving the transition.

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Blackstone, Neil W. "Evolution and cell physiology. 2. The evolution of cell signaling: from mitochondria to Metazoa." American Journal of Physiology-Cell Physiology 305, no. 9 (November 1, 2013): C909—C915. http://dx.doi.org/10.1152/ajpcell.00216.2013.

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The history of life is a history of levels-of-selection transitions. Each transition requires mechanisms that mediate conflict among the lower-level units. In the origins of multicellular eukaryotes, cell signaling is one such mechanism. The roots of cell signaling, however, may extend to the previous major transition, the origin of eukaryotes. Energy-converting protomitochondria within a larger cell allowed eukaryotes to transcend the surface-to-volume constraints inherent in the design of prokaryotes. At the same time, however, protomitochondria can selfishly allocate energy to their own replication. Metabolic signaling may have mediated this principal conflict in several ways. Variation of the protomitochondria was constrained by stoichiometry and strong metabolic demand (state 3) exerted by the protoeukaryote. Variation among protoeukaryotes was increased by the sexual stage of the life cycle, triggered by weak metabolic demand (state 4), resulting in stochastic allocation of protomitochondria to daughter cells. Coupled with selection, many selfish protomitochondria could thus be removed from the population. Hence, regulation of states 3 and 4, as, for instance, provided by the CO2/soluble adenylyl cyclase/cAMP pathway in mitochondria, was critical for conflict mediation. Subsequently, as multicellular eukaryotes evolved, metabolic signaling pathways employed by eukaryotes to mediate conflict within cells could now be co-opted into conflict mediation between cells. For example, in some fungi, the CO2/soluble adenylyl cyclase/cAMP pathway regulates the transition from yeast to forms with hyphae. In animals, this pathway regulates the maturation of sperm. While the particular features (sperm and hyphae) are distinct, both may involve between-cell conflicts that required mediation.

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Bargaje, Rhishikesh, Kalliopi Trachana, Martin N. Shelton, Christopher S. McGinnis, Joseph X. Zhou, Cora Chadick, Savannah Cook, Christopher Cavanaugh, Sui Huang, and Leroy Hood. "Cell population structure prior to bifurcation predicts efficiency of directed differentiation in human induced pluripotent cells." Proceedings of the National Academy of Sciences 114, no. 9 (February 6, 2017): 2271–76. http://dx.doi.org/10.1073/pnas.1621412114.

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Steering the differentiation of induced pluripotent stem cells (iPSCs) toward specific cell types is crucial for patient-specific disease modeling and drug testing. This effort requires the capacity to predict and control when and how multipotent progenitor cells commit to the desired cell fate. Cell fate commitment represents a critical state transition or “tipping point” at which complex systems undergo a sudden qualitative shift. To characterize such transitions during iPSC to cardiomyocyte differentiation, we analyzed the gene expression patterns of 96 developmental genes at single-cell resolution. We identified a bifurcation event early in the trajectory when a primitive streak-like cell population segregated into the mesodermal and endodermal lineages. Before this branching point, we could detect the signature of an imminent critical transition: increase in cell heterogeneity and coordination of gene expression. Correlation analysis of gene expression profiles at the tipping point indicates transcription factors that drive the state transition toward each alternative cell fate and their relationships with specific phenotypic readouts. The latter helps us to facilitate small molecule screening for differentiation efficiency. To this end, we set up an analysis of cell population structure at the tipping point after systematic variation of the protocol to bias the differentiation toward mesodermal or endodermal cell lineage. We were able to predict the proportion of cardiomyocytes many days before cells manifest the differentiated phenotype. The analysis of cell populations undergoing a critical state transition thus affords a tool to forecast cell fate outcomes and can be used to optimize differentiation protocols to obtain desired cell populations.

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Su, Yapeng, Wei Wei, Lidia Robert, Min Xue, Jennifer Tsoi, Angel Garcia-Diaz, Blanca Homet Moreno, et al. "Single-cell analysis resolves the cell state transition and signaling dynamics associated with melanoma drug-induced resistance." Proceedings of the National Academy of Sciences 114, no. 52 (December 11, 2017): 13679–84. http://dx.doi.org/10.1073/pnas.1712064115.

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Continuous BRAF inhibition of BRAF mutant melanomas triggers a series of cell state changes that lead to therapy resistance and escape from immune control before establishing acquired resistance genetically. We used genome-wide transcriptomics and single-cell phenotyping to explore the response kinetics to BRAF inhibition for a panel of patient-derived BRAFV600-mutant melanoma cell lines. A subset of plastic cell lines, which followed a trajectory covering multiple known cell state transitions, provided models for more detailed biophysical investigations. Markov modeling revealed that the cell state transitions were reversible and mediated by both Lamarckian induction and nongenetic Darwinian selection of drug-tolerant states. Single-cell functional proteomics revealed activation of certain signaling networks shortly after BRAF inhibition, and before the appearance of drug-resistant phenotypes. Drug targeting those networks, in combination with BRAF inhibition, halted the adaptive transition and led to prolonged growth inhibition in multiple patient-derived cell lines.

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Jin, Suoqin, Adam L. MacLean, Tao Peng, and Qing Nie. "scEpath: energy landscape-based inference of transition probabilities and cellular trajectories from single-cell transcriptomic data." Bioinformatics 34, no. 12 (February 5, 2018): 2077–86. http://dx.doi.org/10.1093/bioinformatics/bty058.

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Abstract Motivation Single-cell RNA-sequencing (scRNA-seq) offers unprecedented resolution for studying cellular decision-making processes. Robust inference of cell state transition paths and probabilities is an important yet challenging step in the analysis of these data. Results Here we present scEpath, an algorithm that calculates energy landscapes and probabilistic directed graphs in order to reconstruct developmental trajectories. We quantify the energy landscape using ‘single-cell energy’ and distance-based measures, and find that the combination of these enables robust inference of the transition probabilities and lineage relationships between cell states. We also identify marker genes and gene expression patterns associated with cell state transitions. Our approach produces pseudotemporal orderings that are—in combination—more robust and accurate than current methods, and offers higher resolution dynamics of the cell state transitions, leading to new insight into key transition events during differentiation and development. Moreover, scEpath is robust to variation in the size of the input gene set, and is broadly unsupervised, requiring few parameters to be set by the user. Applications of scEpath led to the identification of a cell-cell communication network implicated in early human embryo development, and novel transcription factors important for myoblast differentiation. scEpath allows us to identify common and specific temporal dynamics and transcriptional factor programs along branched lineages, as well as the transition probabilities that control cell fates. Availability and implementation A MATLAB package of scEpath is available at https://github.com/sqjin/scEpath. Supplementary information Supplementary data are available at Bioinformatics online.

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Sarmah, Deepraj, Wesley O. Meredith, Ian K. Weber, Madison R. Price, and Marc R. Birtwistle. "Predicting anti-cancer drug combination responses with a temporal cell state network model." PLOS Computational Biology 19, no. 5 (May 1, 2023): e1011082. http://dx.doi.org/10.1371/journal.pcbi.1011082.

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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.

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Kim, Peter S., and Peter P. Lee. "T cell state transition produces an emergent change detector." Journal of Theoretical Biology 275, no. 1 (April 2011): 59–69. http://dx.doi.org/10.1016/j.jtbi.2011.01.031.

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Mojtahedi, Mitra, Alexander Skupin, Joseph Zhou, Ivan G. Castaño, Rebecca Y. Y. Leong-Quong, Hannah Chang, Kalliopi Trachana, Alessandro Giuliani, and Sui Huang. "Cell Fate Decision as High-Dimensional Critical State Transition." PLOS Biology 14, no. 12 (December 27, 2016): e2000640. http://dx.doi.org/10.1371/journal.pbio.2000640.

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Biggins, John, and Doug Bruce. "Mechanism of the light state transition in photosynthesis. III. Kinetics of the state transition in Porphyridium cruentum." Biochimica et Biophysica Acta (BBA) - Bioenergetics 806, no. 2 (February 1985): 230–36. http://dx.doi.org/10.1016/0005-2728(85)90100-8.

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Du, Quan, Zhen Wang, and Vern L. Schramm. "Human DNMT1 transition state structure." Proceedings of the National Academy of Sciences 113, no. 11 (February 29, 2016): 2916–21. http://dx.doi.org/10.1073/pnas.1522491113.

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Human DNA methyltransferase 1 (DNMT1) maintains the epigenetic state of DNA by replicating CpG methylation signatures from parent to daughter strands, producing heritable methylation patterns through cell divisions. The proposed catalytic mechanism of DNMT1 involves nucleophilic attack of Cys1226 to cytosine (Cyt) C6, methyl transfer from S-adenosyl-l-methionine (SAM) to Cyt C5, and proton abstraction from C5 to form methylated CpG in DNA. Here, we report the subangstrom geometric and electrostatic structure of the major transition state (TS) of the reaction catalyzed by human DNMT1. Experimental kinetic isotope effects were used to guide quantum mechanical calculations to solve the TS structure. Methyl transfer occurs after Cys1226 attack to Cyt C6, and the methyl transfer step is chemically rate-limiting for DNMT1. Electrostatic potential maps were compared for the TS and ground states, providing the electronic basis for interactions between the protein and reactants at the TS. Understanding the TS of DNMT1 demonstrates the possibility of using similar analysis to gain subangstrom geometric insight into the complex reactions of epigenetic modifications.

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Bennett, Ashley Lauren, and Rory Henderson. "HIV-1 Envelope Conformation, Allostery, and Dynamics." Viruses 13, no. 5 (May 7, 2021): 852. http://dx.doi.org/10.3390/v13050852.

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The HIV-1 envelope glycoprotein (Env) mediates host cell fusion and is the primary target for HIV-1 vaccine design. The Env undergoes a series of functionally important conformational rearrangements upon engagement of its host cell receptor, CD4. As the sole target for broadly neutralizing antibodies, our understanding of these transitions plays a critical role in vaccine immunogen design. Here, we review available experimental data interrogating the HIV-1 Env conformation and detail computational efforts aimed at delineating the series of conformational changes connecting these rearrangements. These studies have provided a structural mapping of prefusion closed, open, and transition intermediate structures, the allosteric elements controlling rearrangements, and state-to-state transition dynamics. The combination of these investigations and innovations in molecular modeling set the stage for advanced studies examining rearrangements at greater spatial and temporal resolution.

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Yu, Hongyao, Jiajia Wang, Brad Lackford, Brian Bennett, Jian-liang Li, and Guang Hu. "INO80 promotes H2A.Z occupancy to regulate cell fate transition in pluripotent stem cells." Nucleic Acids Research 49, no. 12 (June 17, 2021): 6739–55. http://dx.doi.org/10.1093/nar/gkab476.

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Abstract The INO80 chromatin remodeler is involved in many chromatin-dependent cellular functions. However, its role in pluripotency and cell fate transition is not fully defined. We examined the impact of Ino80 deletion in the naïve and primed pluripotent stem cells. We found that Ino80 deletion had minimal effect on self-renewal and gene expression in the naïve state, but led to cellular differentiation and de-repression of developmental genes in the transition toward and maintenance of the primed state. In the naïve state, INO80 pre-marked gene promoters that would adopt bivalent histone modifications by H3K4me3 and H3K27me3 upon transition into the primed state. In the primed state, in contrast to its known role in H2A.Z exchange, INO80 promoted H2A.Z occupancy at these bivalent promoters and facilitated H3K27me3 installation and maintenance as well as downstream gene repression. Together, our results identified an unexpected function of INO80 in H2A.Z deposition and gene regulation. We showed that INO80-dependent H2A.Z occupancy is a critical licensing step for the bivalent domains, and thereby uncovered an epigenetic mechanism by which chromatin remodeling, histone variant deposition and histone modification coordinately control cell fate.

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Pan, Huize, Chenyi Xue, Benjamin J. Auerbach, Jiaxin Fan, Alexander C. Bashore, Jian Cui, Dina Y. Yang, et al. "Single-Cell Genomics Reveals a Novel Cell State During Smooth Muscle Cell Phenotypic Switching and Potential Therapeutic Targets for Atherosclerosis in Mouse and Human." Circulation 142, no. 21 (November 24, 2020): 2060–75. http://dx.doi.org/10.1161/circulationaha.120.048378.

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Background: Smooth muscle cells (SMCs) play significant roles in atherosclerosis via phenotypic switching, a pathological process in which SMC dedifferentiation, migration, and transdifferentiation into other cell types. Yet how SMCs contribute to the pathophysiology of atherosclerosis remains elusive. Methods: To reveal the trajectories of SMC transdifferentiation during atherosclerosis and to identify molecular targets for disease therapy, we combined SMC fate mapping and single-cell RNA sequencing of both mouse and human atherosclerotic plaques. We also performed cell biology experiments on isolated SMC-derived cells, conducted integrative human genomics, and used pharmacological studies targeting SMC-derived cells both in vivo and in vitro. Results: We found that SMCs transitioned to an intermediate cell state during atherosclerosis, which was also found in human atherosclerotic plaques of carotid and coronary arteries. SMC-derived intermediate cells, termed “SEM” cells (stem cell, endothelial cell, monocyte), were multipotent and could differentiate into macrophage-like and fibrochondrocyte-like cells, as well as return toward the SMC phenotype. Retinoic acid (RA) signaling was identified as a regulator of SMC to SEM cell transition, and RA signaling was dysregulated in symptomatic human atherosclerosis. Human genomics revealed enrichment of genome-wide association study signals for coronary artery disease in RA signaling target gene loci and correlation between coronary artery disease risk alleles and repressed expression of these genes. Activation of RA signaling by all-trans RA, an anticancer drug for acute promyelocytic leukemia, blocked SMC transition to SEM cells, reduced atherosclerotic burden, and promoted fibrous cap stability. Conclusions: Integration of cell-specific fate mapping, single-cell genomics, and human genetics adds novel insights into the complexity of SMC biology and reveals regulatory pathways for therapeutic targeting of SMC transitions in atherosclerotic cardiovascular disease.

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Taylor, Craig R., Wim van Ieperen, and Jeremy Harbinson. "Demonstration of a relationship between state transitions and photosynthetic efficiency in a higher plant." Biochemical Journal 476, no. 21 (November 11, 2019): 3295–312. http://dx.doi.org/10.1042/bcj20190576.

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A consequence of the series configuration of PSI and PSII is that imbalanced excitation of the photosystems leads to a reduction in linear electron transport and a drop in photosynthetic efficiency. Achieving balanced excitation is complicated by the distinct nature of the photosystems, which differ in composition, absorption spectra, and intrinsic efficiency, and by a spectrally variable natural environment. The existence of long- and short-term mechanisms that tune the photosynthetic apparatus and redistribute excitation energy between the photosystems highlights the importance of maintaining balanced excitation. In the short term, state transitions help restore balance through adjustments which, though not fully characterised, are observable using fluorescence techniques. Upon initiation of a state transition in algae and cyanobacteria, increases in photosynthetic efficiency are observable. However, while higher plants show fluorescence signatures associated with state transitions, no correlation between a state transition and photosynthetic efficiency has been demonstrated. In the present study, state 1 and state 2 were alternately induced in tomato leaves by illuminating leaves produced under artificial sun and shade spectra with a sequence of irradiances extreme in terms of PSI or PSII overexcitation. Light-use efficiency increased in both leaf types during transition from one state to the other with remarkably similar kinetics to that of F′m/Fm, F′o/Fo, and, during the PSII-overexciting irradiance, ΦPSII and qP. We have provided compelling evidence for the first time of a correlation between photosynthetic efficiency and state transitions in a higher plant. The importance of this relationship in natural ecophysiological contexts remains to be elucidated.

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Wang, Shao-Hua, Chao Zhang, and Yangming Wang. "microRNA regulation of pluripotent state transition." Essays in Biochemistry 64, no. 6 (December 2020): 947–54. http://dx.doi.org/10.1042/ebc20200028.

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Abstract microRNAs (miRNAs) play essential roles in mouse embryonic stem cells (ESCs) and early embryo development. The exact mechanism by which miRNAs regulate cell fate transition during embryo development is still not clear. Recent studies have identified and captured various pluripotent stem cells (PSCs) that share similar characteristics with cells from different stages of pre- and post-implantation embryos. These PSCs provide valuable models to understand miRNA functions in early mammalian development. In this short review, we will summarize recent work towards understanding the function and mechanism of miRNAs in regulating the transition or conversion between different pluripotent states. In addition, we will highlight unresolved questions and key future directions related to miRNAs in pluripotent state transition. Studies in these areas will further our understanding of miRNA functions in early embryo development, and may lead to practical means to control human PSCs for clinical applications in regenerative medicine.

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Kline, P. C., and V. L. Schramm. "Electrostatic potential surfaces of the transition state for AMP deaminase and for (R)-coformycin, a transition state inhibitor." Journal of Biological Chemistry 269, no. 35 (September 1994): 22385–90. http://dx.doi.org/10.1016/s0021-9258(17)31801-x.

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Hormoz, Sahand, Zakary S. Singer, James M. Linton, Yaron E. Antebi, Boris I. Shraiman, and Michael B. Elowitz. "Inferring Cell-State Transition Dynamics from Lineage Trees and Endpoint Single-Cell Measurements." Cell Systems 3, no. 5 (November 2016): 419–33. http://dx.doi.org/10.1016/j.cels.2016.10.015.

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Zhao, Zibo, Aileen P. Szczepanski, Natsumi Tsuboyama, Hiam Abdala-Valencia, Young Ah Goo, Benjamin D. Singer, Elizabeth T. Bartom, Feng Yue, and Lu Wang. "PAX9 Determines Epigenetic State Transition and Cell Fate in Cancer." Cancer Research 81, no. 18 (August 2, 2021): 4696–708. http://dx.doi.org/10.1158/0008-5472.can-21-1114.

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Zhu, Guanghui, Hui Yang, Xiao Chen, Jun Wu, Yong Zhang, and Xing-Ming Zhao. "CSTEA: a webserver for the Cell State Transition Expression Atlas." Nucleic Acids Research 45, W1 (May 9, 2017): W103—W108. http://dx.doi.org/10.1093/nar/gkx402.

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Kalkan, Tüzer, Nelly Olova, Mila Roode, Carla Mulas, Heather J. Lee, Isabelle Nett, Hendrik Marks, et al. "Tracking the embryonic stem cell transition from ground state pluripotency." Development 144, no. 7 (February 7, 2017): 1221–34. http://dx.doi.org/10.1242/dev.142711.

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Groves, Sarah M., Nicholas Panchy, Darren R. Tyson, Leonard A. Harris, Vito Quaranta, and Tian Hong. "Involvement of Epithelial–Mesenchymal Transition Genes in Small Cell Lung Cancer Phenotypic Plasticity." Cancers 15, no. 5 (February 25, 2023): 1477. http://dx.doi.org/10.3390/cancers15051477.

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Small cell lung cancer (SCLC) is an aggressive cancer recalcitrant to treatment, arising predominantly from epithelial pulmonary neuroendocrine (NE) cells. Intratumor heterogeneity plays critical roles in SCLC disease progression, metastasis, and treatment resistance. At least five transcriptional SCLC NE and non-NE cell subtypes were recently defined by gene expression signatures. Transition from NE to non-NE cell states and cooperation between subtypes within a tumor likely contribute to SCLC progression by mechanisms of adaptation to perturbations. Therefore, gene regulatory programs distinguishing SCLC subtypes or promoting transitions are of great interest. Here, we systematically analyze the relationship between SCLC NE/non-NE transition and epithelial to mesenchymal transition (EMT)—a well-studied cellular process contributing to cancer invasiveness and resistance—using multiple transcriptome datasets from SCLC mouse tumor models, human cancer cell lines, and tumor samples. The NE SCLC-A2 subtype maps to the epithelial state. In contrast, SCLC-A and SCLC-N (NE) map to a partial mesenchymal state (M1) that is distinct from the non-NE, partial mesenchymal state (M2). The correspondence between SCLC subtypes and the EMT program paves the way for further work to understand gene regulatory mechanisms of SCLC tumor plasticity with applicability to other cancer types.

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Bruce, Doug, and John Biggins. "Mechanism of the light-state transition in photosynthesis." Biochimica et Biophysica Acta (BBA) - Bioenergetics 810, no. 3 (December 1985): 295–301. http://dx.doi.org/10.1016/0005-2728(85)90213-0.

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Wang, Huan, Yan-Guo Zhang, Jing Ma, Jun-Chang Li, Jian Zhang, and Yao-Qing Yu. "Invasiveness-triggered state transition in malignant melanoma cells." Journal of Cellular Physiology 234, no. 5 (November 27, 2018): 5354–61. http://dx.doi.org/10.1002/jcp.27405.

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Shi, Jianrun, Leiyang Cui, Bo Gu, Bin Lyu, and Shimin Gong. "State Transition Graph-Based Spatial–Temporal Attention Network for Cell-Level Mobile Traffic Prediction." Sensors 23, no. 23 (November 21, 2023): 9308. http://dx.doi.org/10.3390/s23239308.

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Mobile traffic prediction enables the efficient utilization of network resources and enhances user experience. In this paper, we propose a state transition graph-based spatial–temporal attention network (STG-STAN) for cell-level mobile traffic prediction, which is designed to exploit the underlying spatial–temporal dynamic information hidden in the historical mobile traffic data. Specifically, we first identify the semantic context information over different segments of the historical data by constructing the state transition graphs, which may reveal different patterns of random fluctuation. Then, based on the state transition graphs, a spatial attention extraction module using graph convolutional networks (GCNs) is designed to aggregate the spatial information of different nodes in the state transition graph. Moreover, a temporal extraction module is employed to capture the dynamic evolution and temporal correlation of the state transition graphs over time. Such a spatial–temporal attention network can be further integrated with a parallel long short-term memory (LSTM) module to improve the accuracy of mobile traffic prediction. Extensive experiments demonstrate that the STG-STAN can better exploit the spatial–temporal information hidden in the state transition graphs, achieving superior performance compared with several baselines.

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Eich, Christina, Jochen Arlt, Chris S. Vink, Parham Solaimani Kartalaei, Polynikis Kaimakis, Samanta A. Mariani, Reinier van der Linden, Wiggert A. van Cappellen, and Elaine Dzierzak. "In vivo single cell analysis reveals Gata2 dynamics in cells transitioning to hematopoietic fate." Journal of Experimental Medicine 215, no. 1 (December 7, 2017): 233–48. http://dx.doi.org/10.1084/jem.20170807.

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Cell fate is established through coordinated gene expression programs in individual cells. Regulatory networks that include the Gata2 transcription factor play central roles in hematopoietic fate establishment. Although Gata2 is essential to the embryonic development and function of hematopoietic stem cells that form the adult hierarchy, little is known about the in vivo expression dynamics of Gata2 in single cells. Here, we examine Gata2 expression in single aortic cells as they establish hematopoietic fate in Gata2Venus mouse embryos. Time-lapse imaging reveals rapid pulsatile level changes in Gata2 reporter expression in cells undergoing endothelial-to-hematopoietic transition. Moreover, Gata2 reporter pulsatile expression is dramatically altered in Gata2+/− aortic cells, which undergo fewer transitions and are reduced in hematopoietic potential. Our novel finding of dynamic pulsatile expression of Gata2 suggests a highly unstable genetic state in single cells concomitant with their transition to hematopoietic fate. This reinforces the notion that threshold levels of Gata2 influence fate establishment and has implications for transcription factor–related hematologic dysfunctions.

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Porciatti, Vittorio, and Tsung-Han Chou. "Modeling Retinal Ganglion Cell Dysfunction in Optic Neuropathies." Cells 10, no. 6 (June 5, 2021): 1398. http://dx.doi.org/10.3390/cells10061398.

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As in glaucoma and other optic neuropathies cellular dysfunction often precedes cell death, the assessment of retinal ganglion cell (RGC) function represents a key outcome measure for neuroprotective strategies aimed at targeting distressed but still viable cells. RGC dysfunction can be assessed with the pattern electroretinogram (PERG), a sensitive measure of electrical activity of RGCs that is recorded non-invasively in human subjects and mouse models. Here, we offer a conceptual framework based on an intuitive state-transition model used for disease management in patients to identify progressive, potentially reversible stages of RGC dysfunction leading to cell death in mouse models of glaucoma and other optic neuropathies. We provide mathematical equations to describe state-transitions with a set of modifiable parameters that alter the time course and severity of state-transitions, which can be used for hypothesis testing and fitting experimental PERG data. PERG dynamics as a function of physiological stimuli are also used to differentiate phenotypic and altered RGC response dynamics, to assess susceptibility to stressors and to assess reversible dysfunction upon pharmacological treatment.

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Devaraj, Vimalathithan, and Biplab Bose. "Morphological State Transition Dynamics in EGF-Induced Epithelial to Mesenchymal Transition." Journal of Clinical Medicine 8, no. 7 (June 26, 2019): 911. http://dx.doi.org/10.3390/jcm8070911.

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Epithelial to Mesenchymal Transition (EMT) is a multi-state process. Here, we investigated phenotypic state transition dynamics of Epidermal Growth Factor (EGF)-induced EMT in a breast cancer cell line MDA-MB-468. We have defined phenotypic states of these cells in terms of their morphologies and have shown that these cells have three distinct morphological states—cobble, spindle, and circular. The spindle and circular states are the migratory phenotypes. Using quantitative image analysis and mathematical modeling, we have deciphered state transition trajectories in different experimental conditions. This analysis shows that the phenotypic state transition during EGF-induced EMT in these cells is reversible, and depends upon the dose of EGF and level of phosphorylation of the EGF receptor (EGFR). The dominant reversible state transition trajectory in this system was cobble to circular to spindle to cobble. We have observed that there exists an ultrasensitive on/off switch involving phospho-EGFR that decides the transition of cells in and out of the circular state. In general, our observations can be explained by the conventional quasi-potential landscape model for phenotypic state transition. As an alternative to this model, we have proposed a simpler discretized energy-level model to explain the observed state transition dynamics.

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Phillips, M. A., R. Fletterick, and W. J. Rutter. "Arginine 127 stabilizes the transition state in carboxypeptidase." Journal of Biological Chemistry 265, no. 33 (November 1990): 20692–98. http://dx.doi.org/10.1016/s0021-9258(17)30559-8.

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Zhang, Yong, Gary B. Evans, Keith Clinch, Douglas R. Crump, Lawrence D. Harris, Richard F. G. Fröhlich, Peter C. Tyler, Keith Z. Hazleton, María B. Cassera, and Vern L. Schramm. "Transition State Analogues ofPlasmodium falciparumand Human Orotate Phosphoribosyltransferases." Journal of Biological Chemistry 288, no. 48 (October 24, 2013): 34746–54. http://dx.doi.org/10.1074/jbc.m113.521955.

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Wang, Yuliang, Abdiasis M. Hussein, Logeshwaran Somasundaram, Rithika Sankar, Damien Detraux, Julie Mathieu, and Hannele Ruohola-Baker. "microRNAs Regulating Human and Mouse Naïve Pluripotency." International Journal of Molecular Sciences 20, no. 23 (November 22, 2019): 5864. http://dx.doi.org/10.3390/ijms20235864.

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microRNAs are ~22bp nucleotide non-coding RNAs that play important roles in the post-transcriptional regulation of gene expression. Many studies have established that microRNAs are important for cell fate choices, including the naïve to primed pluripotency state transitions, and their intermediate state, the developmentally suspended diapause state in early development. However, the full extent of microRNAs associated with these stage transitions in human and mouse remain under-explored. By meta-analysis of microRNA-seq, RNA-seq, and metabolomics datasets from human and mouse, we found a set of microRNAs, and importantly, their experimentally validated target genes that show consistent changes in naïve to primed transitions (microRNA up, target genes down, or vice versa). The targets of these microRNAs regulate developmental pathways (e.g., the Hedgehog-pathway), primary cilium, and remodeling of metabolic processes (oxidative phosphorylation, fatty acid metabolism, and amino acid transport) during the transition. Importantly, we identified 115 microRNAs that significantly change in the same direction in naïve to primed transitions in both human and mouse, many of which are novel candidate regulators of pluripotency. Furthermore, we identified 38 microRNAs and 274 target genes that may be involved in diapause, where embryonic development is temporarily suspended prior to implantation to uterus. The upregulated target genes suggest that microRNAs activate stress response in the diapause stage. In conclusion, we provide a comprehensive resource of microRNAs and their target genes involved in naïve to primed transition and in the paused intermediate, the embryonic diapause stage.

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Sun, Yubao, Li Jiang, Zaidong Li, Hongmei Ma, and Zhidong Zhang. "Transition voltage of asymmetric H state to bend in pi cell." Applied Physics Letters 91, no. 1 (July 2, 2007): 011103. http://dx.doi.org/10.1063/1.2753492.

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Rosenberg, Laura H., Anne-Laure Cattin, Xavier Fontana, Elizabeth Harford-Wright, Jemima J. Burden, Ian J. White, Jacob G. Smith, et al. "HDAC3 Regulates the Transition to the Homeostatic Myelinating Schwann Cell State." Cell Reports 25, no. 10 (December 2018): 2755–65. http://dx.doi.org/10.1016/j.celrep.2018.11.045.

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Zhang, Xiao-Jie, and Zhi-Pan Liu. "Variable-Cell Double-Ended Surface Walking Method for Fast Transition State Location of Solid Phase Transitions." Journal of Chemical Theory and Computation 11, no. 10 (October 5, 2015): 4885–94. http://dx.doi.org/10.1021/acs.jctc.5b00641.

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Yuan, Meichen, Weirong Hong, and Pu Li. "Identification of optimal strategies for state transition of complex biological networks." Biochemical Society Transactions 45, no. 4 (July 21, 2017): 1015–24. http://dx.doi.org/10.1042/bst20160419.

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Complex biological networks typically contain numerous parameters, and determining feasible strategies for state transition by parameter perturbation is not a trivial task. In the present study, based on dynamical and structural analyses of the biological network, we optimized strategies for controlling variables in a two-node gene regulatory network and a T-cell large granular lymphocyte signaling network associated with blood cancer by using an efficient dynamic optimization method. Optimization revealed the critical value for each decision variable to steer the system from an undesired state into a desired attractor. In addition, the minimum time for the state transition was determined by defining and solving a time-optimal control problem. Moreover, time-dependent variable profiles for state transitions were achieved rather than constant values commonly adopted in previous studies. Furthermore, the optimization method allows multiple controls to be simultaneously adjusted to drive the system out of an undesired attractor. Optimization improved the results of the parameter perturbation method, thus providing a valuable guidance for experimental design.

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Sohl, Julie, Larry D. Sutton, Donald J. Burton, and Daniel M. Quinn. "Haloketone transition state analog inhibitors of cholesterol esterase." Biochemical and Biophysical Research Communications 151, no. 1 (February 1988): 554–60. http://dx.doi.org/10.1016/0006-291x(88)90630-4.

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Cheng, Zhangliang, Kohei Kume, and Markus Müschen. "MYC to BCL6 State-Transitions Determine Cell Size and Metabolic Fluctuations and Define a Novel Biorhythm in B-Cell Malignancies." Blood 142, Supplement 1 (November 28, 2023): 2769. http://dx.doi.org/10.1182/blood-2023-190972.

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Background: Cell size fluctuations are well-documented during critical transitions during normal B-cell development. For instance, during early stages of development, “large cycling pre-B cells” (also classified as Fraction C') eventually exit cell cycle and shrink to become “small resting pre-B cells” (Fraction D) to enable immunoglobulin light chain gene recombination. We and others had shown that this transition is marked by loss of Myc expression and gain of Bcl6. Later in development, germinal center B-cells cycle between large MYC+ “centroblast” and smaller BCL6+ “centrocyte” states between dark and light zones, respectively. MYC is involved in biomass accumulation and provides fuel for cell division, while BCL6 confers a quiescent phenotype to cells and protects B cells from DNA damage-induced apoptosis. BCL6 can suppress MYC transcription, indicating MYC and BCL6 is mutually exclusive, and their expression dictates distinct cellular states. Significance: In B-cell malignancies, transitions between mutually exclusive MYC+ and BCL6+ states seem to be important as well: B-ALL cells that are driven by oncogenic tyrosine kinases (e.g. BCR-ABL1) express predominantly MYC but can be forced into a BCL6+ state upon tyrosine kinase inhibition (e.g. imatinib). In germinal center-derived B-cell lymphoma, both MYC and BCL6 are frequently targeted by chromosomal translocation, suggesting that disruption of physiological state transitions may be part of the malignant transformation program. Results: To elucidate regulation of MYC-BCL6 state transitions and their importance in progression and development of drug resistance in B-ALL and germinal center-derived B-cell lymphoma, we developed a MYC-eGFP and BCL6-mCherry dual-reporter mouse model. In addition, we engineered human B-ALL PDX cells with MYC-mNeonGreen and BCL6mScarlet knockin fusion genes by CRISPR/Cas9-mediated HDRT. As expected, MYC+ and BCL6+ states were largely mutually exclusive during early stages of B-cell development, as well as in BCR-ABL1- and NRAS G12D-driven B-ALL. Interestingly, a large fraction of B-ALL cells expressed neither MYC nor BCL6, as validated by cell sorting and Western blot. Based on single-cell sorting and subsequent time-lapse monitoring over 12 hours, we found MYC+ cells transitioning through a double-negative state to become BCL6+ and then revert again to a MYC+ state ( Figure A), suggesting dynamic transitions between MYC and BCL6 cycles. We characterized these populations by analyzing cell size, cell proliferation, cell cycle, clone formation, and gene expression profiles. The results indicated that MYC+ cells exhibited larger cell size, active proliferation, and increased glycolytic activity. Conversely, BCL6+ cells displayed smaller cell size, activation of autophagy with suppression of glycolysis, and cell cycle arrest in the G0 phase of the cell cycle. Conclusions and future directions: Given the dynamic inter-transition between MYC and BCL6 states, and the significant roles of both MYC and BCL6 in B-ALL and germinal center-derived B-cell lymphomas, we propose MYC- and BCL6-dependent fluctuations of cellular activity (wake) and quiescence (sleep; Figure B). Thereby, MYC and BCL6 are expressed in an oscillatory manner. During the MYC state, cells exhibit high glycolysis activity, actively accumulate biomass, and undergo proliferation, representing the wake phase. In contrast, during the BCL6 state, cells suppress glycolysis metabolism, pause the cell cycle, and display a quiescent phenotype, representing the sleep phase. Based on this discovery, we will examine the ‘B-cell exhaustion’ paradigm that Bcl6 and Myc mark iterative cycles of quiescence and activation. In analogy to sleep-wake phases, we hypothesize that the Bcl6-autophagy phase is essential for recovery and regeneration. We will investigate how B-cells transition from one phase to the next and consequences of elongation of one phase at the expense of the other. Malignant B-cells may be particularly sensitive to shortening of quiescence periods (“sleep deprivation”). These and other observations will lead to new conceptual frameworks for the understanding of how MYC-BCL6 state transitions, cell-size fluctuations and the length of recovery-periods regulate energy-supply and survival of B-cell malignancies and create opportunities for therapeutic intervention.

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Ishihara, Hiroshi, and Michael J. Welsh. "Block by MOPS reveals a conformation change in the CFTR pore produced by ATP hydrolysis." American Journal of Physiology-Cell Physiology 273, no. 4 (October 1, 1997): C1278—C1289. http://dx.doi.org/10.1152/ajpcell.1997.273.4.c1278.

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ATP hydrolysis by the cystic fibrosis transmembrane conductance regulator (CFTR) Cl− channel predicts that energy from hydrolysis might cause asymmetric transitions in the gating cycle. We found that 3-( N-morpholino)propanesulfonic acid (MOPS) blocked the open channel by binding to a site 50% of the way through the electrical field. Block by MOPS revealed two distinct states, O1 and O2, which showed a strong asymmetry during bursts of activity; the first opening in a burst was in the O1 state and the last was in the O2 state. Addition of a nonhydrolyzable nucleoside triphosphate prevented the transition to the O2 state and prolonged the O1 state. These data indicate that ATP hydrolysis by the nucleotide-binding domains drives a series of asymmetric transitions in the gating cycle. They also indicate that ATP hydrolysis changes the conformation of the pore, thereby altering MOPS binding.

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Singh, Indrajeet, Abhishek Gandhi, Manoranjan Biswal, Smita Mohanty, and S. K. Nayak. "Multi-Stage Recycling Induced Morphological Transformations in Solid-State Microcellular Foaming of Polystyrene." Cellular Polymers 37, no. 3 (May 2018): 121–49. http://dx.doi.org/10.1177/026248931803700302.

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In this article, the general-purpose polystyrene was reprocessed four times. The effect of repeated reprocessing of polystyrene on its polymeric properties and on its microcellular, foaming behaviour were investigated. It was observed that reprocessing leads to break of long polymeric chains into short chains, which resulted increment in PDI and MFI. Molecular weight and Glass transition temperature were found to decrease with increasing recycling stages. Reprocessing resulted abruptly decrement in viscosity of neat polystyrene. Effect of reprocessing on foaming behaviour was analysed properly in this report and it was found that reprocessing resulted in improvement in cell sizes and their distribution. A positive effect on expansion ratio was also observed during foaming of reprocessed specimens. Cell density was found to decrease with increasing recycling stages. The effect of saturation pressure and foaming temperature on microcellular foam morphology along with recycling were investigated. Effect of foaming time on cell size, cell size distribution, cell density, expansion ratio and cell wall thickness was investigated.

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Journal articles on the topic 'Cell state transition'

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