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Solra M, Kapila R, Das S, Bhatt P, Rana S. Transient Metallo-Lipidoid Assemblies Amplify Covalent Catalysis of Aqueous and Non-Aqueous Reactions. Angew Chem Int Ed Engl 2024; 63:e202400348. [PMID: 38315883 DOI: 10.1002/anie.202400348] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2024] [Revised: 02/02/2024] [Accepted: 02/05/2024] [Indexed: 02/07/2024]
Abstract
Dissipative supramolecular assemblies are hallmarks of living systems, contributing to their complex, dynamic structures and emerging functions. Living cells can spatiotemporally control diverse biochemical reactions in membrane compartments and condensates, regulating metabolite levels, signal transduction or remodeling of the cytoskeleton. Herein, we constructed membranous compartments using self-assembly of lipid-like amphiphiles (lipidoid) in aqueous medium. The new double-tailed lipidoid features Cu(II) coordinated with a tetravalent chelator that dictates the binding of two amphiphilic ligands in cis-orientation. Hydrophobic interactions between the lipidoids coupled with intermolecular hydrogen bonding led to a well-defined bilayer vesicle structure. Oil-soluble SNAr reaction is efficiently upregulated in the hydrophobic cavity, acting as a catalytic crucible. The modular system allows easy incorporation of exposed primary amine groups, which augments the catalysis of retro aldol and C-N bond formation reactions. Moreover, a higher-affinity chelator enables consumption of the Cu(II) template leveraging the differential thermodynamic stability, which allows a controllable lifetime of the vesicular assemblies. Concomitant temporal upregulation of the catalytic reactions could be tuned by the metal ion concentration. This work offers new possibilities for metal ion-mediated dynamic supramolecular systems, opening up a massive repertoire of functionally active dynamic "life-like" materials.
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Affiliation(s)
- Manju Solra
- Materials Research Centre, Division of Chemical Sciences, Indian Institute of Science, C. V. Raman Road, Bangalore, 560012, India
| | - Rohit Kapila
- Materials Research Centre, Division of Chemical Sciences, Indian Institute of Science, C. V. Raman Road, Bangalore, 560012, India
| | - Sourav Das
- Materials Research Centre, Division of Chemical Sciences, Indian Institute of Science, C. V. Raman Road, Bangalore, 560012, India
| | - Preeti Bhatt
- Materials Research Centre, Division of Chemical Sciences, Indian Institute of Science, C. V. Raman Road, Bangalore, 560012, India
| | - Subinoy Rana
- Materials Research Centre, Division of Chemical Sciences, Indian Institute of Science, C. V. Raman Road, Bangalore, 560012, India
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2
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Jashnsaz H, Neuert G. Phenotypic consequences of logarithmic signaling in MAPK stress response. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.05.570188. [PMID: 38106069 PMCID: PMC10723343 DOI: 10.1101/2023.12.05.570188] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
How cells respond to dynamic environmental changes is crucial for understanding fundamental biological processes and cell physiology. In this study, we developed an experimental and quantitative analytical framework to explore how dynamic stress gradients that change over time regulate cellular volume, signaling activation, and growth phenotypes. Our findings reveal that gradual stress conditions substantially enhance cell growth compared to conventional acute stress. This growth advantage correlates with a minimal reduction in cell volume dependent on the dynamic of stress. We explain the growth phenotype with our finding of a logarithmic signal transduction mechanism in the yeast Mitogen-Activated Protein Kinase (MAPK) osmotic stress response pathway. These insights into the interplay between gradual environments, cell volume change, dynamic cell signaling, and growth, advance our understanding of fundamental cellular processes in gradual stress environments.
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Affiliation(s)
- Hossein Jashnsaz
- Department of Molecular Physiology and Biophysics, School of Medicine, Vanderbilt University, Nashville, TN 37232 USA
| | - Gregor Neuert
- Department of Molecular Physiology and Biophysics, School of Medicine, Vanderbilt University, Nashville, TN 37232 USA
- Lead Contact
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3
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Peng L, Tan J, Xiong W, Zhang L, Wang Z, Yuan R, Li Z, Chen X. Deciphering ligand-receptor-mediated intercellular communication based on ensemble deep learning and the joint scoring strategy from single-cell transcriptomic data. Comput Biol Med 2023; 163:107137. [PMID: 37364528 DOI: 10.1016/j.compbiomed.2023.107137] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2023] [Revised: 05/18/2023] [Accepted: 06/04/2023] [Indexed: 06/28/2023]
Abstract
BACKGROUND Cell-cell communication in a tumor microenvironment is vital to tumorigenesis, tumor progression and therapy. Intercellular communication inference helps understand molecular mechanisms of tumor growth, progression and metastasis. METHODS Focusing on ligand-receptor co-expressions, in this study, we developed an ensemble deep learning framework, CellComNet, to decipher ligand-receptor-mediated cell-cell communication from single-cell transcriptomic data. First, credible LRIs are captured by integrating data arrangement, feature extraction, dimension reduction, and LRI classification based on an ensemble of heterogeneous Newton boosting machine and deep neural network. Next, known and identified LRIs are screened based on single-cell RNA sequencing (scRNA-seq) data in certain tissues. Finally, cell-cell communication is inferred by incorporating scRNA-seq data, the screened LRIs, a joint scoring strategy that combines expression thresholding and expression product of ligands and receptors. RESULTS The proposed CellComNet framework was compared with four competing protein-protein interaction prediction models (PIPR, XGBoost, DNNXGB, and OR-RCNN) and obtained the best AUCs and AUPRs on four LRI datasets, elucidating the optimal LRI classification ability. CellComNet was further applied to analyze intercellular communication in human melanoma and head and neck squamous cell carcinoma (HNSCC) tissues. The results demonstrate that cancer-associated fibroblasts highly communicate with melanoma cells and endothelial cells strong communicate with HNSCC cells. CONCLUSIONS The proposed CellComNet framework efficiently identified credible LRIs and significantly improved cell-cell communication inference performance. We anticipate that CellComNet can contribute to anticancer drug design and tumor-targeted therapy.
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Affiliation(s)
- Lihong Peng
- School of Computer Science, Hunan University of Technology, Zhuzhou, 412007, Hunan, China; College of Life Sciences and Chemistry, Hunan University of Technology, Zhuzhou, 412007, Hunan, China
| | - Jingwei Tan
- School of Computer Science, Hunan University of Technology, Zhuzhou, 412007, Hunan, China
| | - Wei Xiong
- School of Computer Science, Hunan University of Technology, Zhuzhou, 412007, Hunan, China
| | - Li Zhang
- School of Information and Control Engineering, China University of Mining and Technology, Xuzhou, 221116, Jiangsu, China
| | - Zhao Wang
- School of Computer Science, Hunan University of Technology, Zhuzhou, 412007, Hunan, China
| | - Ruya Yuan
- School of Computer Science, Hunan University of Technology, Zhuzhou, 412007, Hunan, China
| | - Zejun Li
- School of Computer Science, Hunan Institute of Technology, Hengyang, 421002, Hunan, China.
| | - Xing Chen
- School of Science, Jiangnan University, Wuxi, 214122, Jiangsu, China.
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4
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Manzer ZA, Selivanovitch E, Ostwalt AR, Daniel S. Membrane protein synthesis: no cells required. Trends Biochem Sci 2023; 48:642-654. [PMID: 37087310 DOI: 10.1016/j.tibs.2023.03.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Revised: 02/20/2023] [Accepted: 03/22/2023] [Indexed: 04/24/2023]
Abstract
Despite advances in membrane protein (MP) structural biology and a growing interest in their applications, these proteins remain challenging to study. Progress has been hindered by the complex nature of MPs and innovative methods will be required to circumvent technical hurdles. Cell-free protein synthesis (CFPS) is a burgeoning technique for synthesizing MPs directly into a membrane environment using reconstituted components of the cellular transcription and translation machinery in vitro. We provide an overview of CFPS and how this technique can be applied to the synthesis and study of MPs. We highlight numerous strategies including synthesis methods and folding environments, each with advantages and limitations, to provide a survey of how CFPS techniques can advance the study of MPs.
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Affiliation(s)
- Zachary A Manzer
- R.F. School of Chemical and Biomolecular Engineering, Cornell University, Ithaca, NY 14853, USA
| | - Ekaterina Selivanovitch
- R.F. School of Chemical and Biomolecular Engineering, Cornell University, Ithaca, NY 14853, USA
| | - Alexis R Ostwalt
- R.F. School of Chemical and Biomolecular Engineering, Cornell University, Ithaca, NY 14853, USA
| | - Susan Daniel
- R.F. School of Chemical and Biomolecular Engineering, Cornell University, Ithaca, NY 14853, USA.
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5
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Pandey AK, Loscalzo J. Network medicine: an approach to complex kidney disease phenotypes. Nat Rev Nephrol 2023:10.1038/s41581-023-00705-0. [PMID: 37041415 DOI: 10.1038/s41581-023-00705-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/13/2023] [Indexed: 04/13/2023]
Abstract
Scientific reductionism has been the basis of disease classification and understanding for more than a century. However, the reductionist approach of characterizing diseases from a limited set of clinical observations and laboratory evaluations has proven insufficient in the face of an exponential growth in data generated from transcriptomics, proteomics, metabolomics and deep phenotyping. A new systematic method is necessary to organize these datasets and build new definitions of what constitutes a disease that incorporates both biological and environmental factors to more precisely describe the ever-growing complexity of phenotypes and their underlying molecular determinants. Network medicine provides such a conceptual framework to bridge these vast quantities of data while providing an individualized understanding of disease. The modern application of network medicine principles is yielding new insights into the pathobiology of chronic kidney diseases and renovascular disorders by expanding the understanding of pathogenic mediators, novel biomarkers and new options for renal therapeutics. These efforts affirm network medicine as a robust paradigm for elucidating new advances in the diagnosis and treatment of kidney disorders.
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Affiliation(s)
- Arvind K Pandey
- Division of Cardiovascular Medicine, Department of Medicine, Brigham and Women's Hospital, and Harvard Medical School, Boston, MA, USA
| | - Joseph Loscalzo
- Division of Cardiovascular Medicine, Department of Medicine, Brigham and Women's Hospital, and Harvard Medical School, Boston, MA, USA.
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6
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Barua A, Hatzikirou H. Cell Decision Making through the Lens of Bayesian Learning. ENTROPY (BASEL, SWITZERLAND) 2023; 25:e25040609. [PMID: 37190396 PMCID: PMC10137733 DOI: 10.3390/e25040609] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/06/2023] [Revised: 03/20/2023] [Accepted: 03/29/2023] [Indexed: 05/17/2023]
Abstract
Cell decision making refers to the process by which cells gather information from their local microenvironment and regulate their internal states to create appropriate responses. Microenvironmental cell sensing plays a key role in this process. Our hypothesis is that cell decision-making regulation is dictated by Bayesian learning. In this article, we explore the implications of this hypothesis for internal state temporal evolution. By using a timescale separation between internal and external variables on the mesoscopic scale, we derive a hierarchical Fokker-Planck equation for cell-microenvironment dynamics. By combining this with the Bayesian learning hypothesis, we find that changes in microenvironmental entropy dominate the cell state probability distribution. Finally, we use these ideas to understand how cell sensing impacts cell decision making. Notably, our formalism allows us to understand cell state dynamics even without exact biochemical information about cell sensing processes by considering a few key parameters.
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Affiliation(s)
- Arnab Barua
- Departement de Biochimie, Université de Montréal, Montréal, QC H3T 1C5, Canada
- Centre Robert-Cedergren en Bio-Informatique et Génomique, Université de Montréal, Montréal, QC H3C 3J7, Canada
| | - Haralampos Hatzikirou
- Center for Information Services and High Performance Computing, Technische Univesität Dresden, 01062 Dresden, Germany
- Mathematics Department, Khalifa University, Abu Dhabi P.O. Box 127788, United Arab Emirates
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7
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Kardynska M, Kogut D, Pacholczyk M, Smieja J. Mathematical modeling of regulatory networks of intracellular processes - Aims and selected methods. Comput Struct Biotechnol J 2023; 21:1523-1532. [PMID: 36851915 PMCID: PMC9958294 DOI: 10.1016/j.csbj.2023.02.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Revised: 02/03/2023] [Accepted: 02/03/2023] [Indexed: 02/11/2023] Open
Abstract
Regulatory networks structure and signaling pathways dynamics are uncovered in time- and resource consuming experimental work. However, it is increasingly supported by modeling, analytical and computational techniques as well as discrete mathematics and artificial intelligence applied to to extract knowledge from existing databases. This review is focused on mathematical modeling used to analyze dynamics and robustness of these networks. This paper presents a review of selected modeling methods that facilitate advances in molecular biology.
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Affiliation(s)
- Malgorzata Kardynska
- Dept. of Biosensors and Processing of Biomedical Signals, Silesian University of Technology, Gliwice, Poland
| | - Daria Kogut
- Dept. of Biosensors and Processing of Biomedical Signals, Silesian University of Technology, Gliwice, Poland.,Dept. of Systems Biology and Engineering, Silesian University of Technology, Gliwice, Poland
| | - Marcin Pacholczyk
- Dept. of Biosensors and Processing of Biomedical Signals, Silesian University of Technology, Gliwice, Poland.,Dept. of Systems Biology and Engineering, Silesian University of Technology, Gliwice, Poland
| | - Jaroslaw Smieja
- Dept. of Biosensors and Processing of Biomedical Signals, Silesian University of Technology, Gliwice, Poland.,Dept. of Systems Biology and Engineering, Silesian University of Technology, Gliwice, Poland
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8
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Kuznetsov IA, Berlew EE, Glantz ST, Hannanta-Anan P, Chow BY. Computational framework for single-cell spatiotemporal dynamics of optogenetic membrane recruitment. CELL REPORTS METHODS 2022; 2:100245. [PMID: 35880018 PMCID: PMC9308134 DOI: 10.1016/j.crmeth.2022.100245] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Revised: 05/18/2022] [Accepted: 06/09/2022] [Indexed: 10/27/2022]
Abstract
We describe a modular computational framework for analyzing cell-wide spatiotemporal signaling dynamics in single-cell microscopy experiments that accounts for the experiment-specific geometric and diffractive complexities that arise from heterogeneous cell morphologies and optical instrumentation. Inputs are unique cell geometries and protein concentrations derived from confocal stacks and spatiotemporally varying environmental stimuli. After simulating the system with a model of choice, the output is convolved with the microscope point-spread function for direct comparison with the observable image. We experimentally validate this approach in single cells with BcLOV4, an optogenetic membrane recruitment system for versatile control over cell signaling, using a three-dimensional non-linear finite element model with all parameters experimentally derived. The simulations recapitulate observed subcellular and cell-to-cell variability in BcLOV4 signaling, allowing for inter-experimental differences of cellular and instrumentation origins to be elucidated and resolved for improved interpretive robustness. This single-cell approach will enhance optogenetics and spatiotemporally resolved signaling studies.
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Affiliation(s)
- Ivan A. Kuznetsov
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Erin E. Berlew
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Spencer T. Glantz
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Pimkhuan Hannanta-Anan
- Department of Biomedical Engineering, School of Engineering, King Mongkut's Institute of Technology Ladkrabang, Bangkok 10520, Thailand
| | - Brian Y. Chow
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA 19104, USA
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9
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Kardynska M, Smieja J, Paszek P, Puszynski K. Application of Sensitivity Analysis to Discover Potential Molecular Drug Targets. Int J Mol Sci 2022; 23:ijms23126604. [PMID: 35743048 PMCID: PMC9223434 DOI: 10.3390/ijms23126604] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Revised: 06/07/2022] [Accepted: 06/10/2022] [Indexed: 11/24/2022] Open
Abstract
Mathematical modeling of signaling pathways and regulatory networks has been supporting experimental research for some time now. Sensitivity analysis, aimed at finding model parameters whose changes yield significantly altered cellular responses, is an important part of modeling work. However, sensitivity methods are often directly transplanted from analysis of technical systems, and thus, they may not serve the purposes of analysis of biological systems. This paper presents a novel sensitivity analysis method that is particularly suited to the task of searching for potential molecular drug targets in signaling pathways. Using two sample models of pathways, p53/Mdm2 regulatory module and IFN-β-induced JAK/STAT signaling pathway, we show that the method leads to biologically relevant conclusions, identifying processes suitable for targeted pharmacological inhibition, represented by the reduction of kinetic parameter values. That, in turn, facilitates subsequent search for active drug components.
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Affiliation(s)
- Malgorzata Kardynska
- Department of Biosensors and Processing of Biomedical Signals, Silesian University of Technology, 41-800 Zabrze, Poland;
- Department of Systems Biology and Engineering, Silesian University of Technology, 44-100 Gliwice, Poland;
| | - Jaroslaw Smieja
- Department of Systems Biology and Engineering, Silesian University of Technology, 44-100 Gliwice, Poland;
- Correspondence:
| | - Pawel Paszek
- School of Biology, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester M13 9PT, UK;
| | - Krzysztof Puszynski
- Department of Systems Biology and Engineering, Silesian University of Technology, 44-100 Gliwice, Poland;
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10
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The Hedgehog Signaling Pathway in Idiopathic Pulmonary Fibrosis: Resurrection Time. Int J Mol Sci 2021; 23:ijms23010171. [PMID: 35008597 PMCID: PMC8745434 DOI: 10.3390/ijms23010171] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Revised: 12/20/2021] [Accepted: 12/22/2021] [Indexed: 02/07/2023] Open
Abstract
The hedgehog (Hh) pathway is a sophisticated conserved cell signaling pathway that plays an essential role in controlling cell specification and proliferation, survival factors, and tissue patterning formation during embryonic development. Hh signal activity does not entirely disappear after development and may be reactivated in adulthood within tissue-injury-associated diseases, including idiopathic pulmonary fibrosis (IPF). The dysregulation of Hh-associated activating transcription factors, genomic abnormalities, and microenvironments is a co-factor that induces the initiation and progression of IPF.
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11
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Jones-Tabah J, Martin RD, Tanny JC, Clarke PBS, Hébert TE. High-Content Single-Cell Förster Resonance Energy Transfer Imaging of Cultured Striatal Neurons Reveals Novel Cross-Talk in the Regulation of Nuclear Signaling by Protein Kinase A and Extracellular Signal-Regulated Kinase 1/2. Mol Pharmacol 2021; 100:526-539. [PMID: 34503973 DOI: 10.1124/molpharm.121.000290] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2021] [Accepted: 09/07/2021] [Indexed: 11/22/2022] Open
Abstract
Genetically encoded biosensors can be used to track signaling events in living cells by measuring changes in fluorescence emitted by one or more fluorescent proteins. Here, we describe the use of genetically encoded biosensors based on Förster resonance energy transfer (FRET), combined with high-content microscopy, to image dynamic signaling events simultaneously in thousands of neurons in response to drug treatments. We first applied this approach to examine intercellular variation in signaling responses among cultured striatal neurons stimulated with multiple drugs. Using high-content FRET imaging and immunofluorescence, we identified neuronal subpopulations with unique responses to pharmacological manipulation and used nuclear morphology to identify medium spiny neurons within these heterogeneous striatal cultures. Focusing on protein kinase A (PKA) and extracellular signal-regulated kinase 1/2 (ERK1/2) signaling in the cytoplasm and nucleus, we noted pronounced intercellular differences among putative medium spiny neurons, in both the magnitude and kinetics of signaling responses to drug application. Importantly, a conventional "bulk" analysis that pooled all cells in culture yielded a different rank order of drug potency than that revealed by single-cell analysis. Using a single-cell analytical approach, we dissected the relative contributions of PKA and ERK1/2 signaling in striatal neurons and unexpectedly identified a novel role for ERK1/2 in promoting nuclear activation of PKA in striatal neurons. This finding adds a new dimension of signaling crosstalk between PKA and ERK1/2 with relevance to dopamine D1 receptor signaling in striatal neurons. In conclusion, high-content single-cell imaging can complement and extend traditional population-level analyses and provides a novel vantage point from which to study cellular signaling. SIGNIFICANCE STATEMENT: High-content imaging revealed substantial intercellular variation in the magnitude and pattern of intracellular signaling events driven by receptor stimulation. Since individual neurons within the same population can respond differently to a given agonist, interpreting measures of intracellular signaling derived from the averaged response of entire neuronal populations may not always reflect what happened at the single-cell level. This study uses this approach to identify a new form of cross-talk between PKA and ERK1/2 signaling in the nucleus of striatal neurons.
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Affiliation(s)
- Jace Jones-Tabah
- Department of Pharmacology and Therapeutics, McGill University, Montréal, Québec, Canada
| | - Ryan D Martin
- Department of Pharmacology and Therapeutics, McGill University, Montréal, Québec, Canada
| | - Jason C Tanny
- Department of Pharmacology and Therapeutics, McGill University, Montréal, Québec, Canada
| | - Paul B S Clarke
- Department of Pharmacology and Therapeutics, McGill University, Montréal, Québec, Canada
| | - Terence E Hébert
- Department of Pharmacology and Therapeutics, McGill University, Montréal, Québec, Canada
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12
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Zhang Y, Liu T, Hu X, Wang M, Wang J, Zou B, Tan P, Cui T, Dou Y, Ning L, huang Y, Rao S, Wang D, Zhao X. CellCall: integrating paired ligand-receptor and transcription factor activities for cell-cell communication. Nucleic Acids Res 2021; 49:8520-8534. [PMID: 34331449 PMCID: PMC8421219 DOI: 10.1093/nar/gkab638] [Citation(s) in RCA: 92] [Impact Index Per Article: 30.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2021] [Revised: 06/24/2021] [Accepted: 07/16/2021] [Indexed: 12/14/2022] Open
Abstract
With the dramatic development of single-cell RNA sequencing (scRNA-seq) technologies, the systematic decoding of cell-cell communication has received great research interest. To date, several in-silico methods have been developed, but most of them lack the ability to predict the communication pathways connecting the insides and outsides of cells. Here, we developed CellCall, a toolkit to infer inter- and intracellular communication pathways by integrating paired ligand-receptor and transcription factor (TF) activity. Moreover, CellCall uses an embedded pathway activity analysis method to identify the significantly activated pathways involved in intercellular crosstalk between certain cell types. Additionally, CellCall offers a rich suite of visualization options (Circos plot, Sankey plot, bubble plot, ridge plot, etc.) to present the analysis results. Case studies on scRNA-seq datasets of human testicular cells and the tumor immune microenvironment demonstrated the reliable and unique functionality of CellCall in intercellular communication analysis and internal TF activity exploration, which were further validated experimentally. Comparative analysis of CellCall and other tools indicated that CellCall was more accurate and offered more functions. In summary, CellCall provides a sophisticated and practical tool allowing researchers to decipher intercellular communication and related internal regulatory signals based on scRNA-seq data. CellCall is freely available at https://github.com/ShellyCoder/cellcall.
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Affiliation(s)
- Yang Zhang
- Department of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China
| | - Tianyuan Liu
- Department of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China
| | - Xuesong Hu
- State Key Laboratory of Organ Failure Research, Department of Developmental Biology, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China
| | - Mei Wang
- State Key Laboratory of Organ Failure Research, Department of Developmental Biology, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China
| | - Jing Wang
- Department of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China
| | - Bohao Zou
- Department of Statistics, University of California Davis, Davis, CA, USA
| | - Puwen Tan
- Department of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China
| | - Tianyu Cui
- Department of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China
| | - Yiying Dou
- Department of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China
| | - Lin Ning
- Department of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China
| | - Yan huang
- Department of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China
| | - Shuan Rao
- Department of Thoracic Surgery, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China
| | - Dong Wang
- Department of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China
| | - Xiaoyang Zhao
- State Key Laboratory of Organ Failure Research, Department of Developmental Biology, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China
- Guangdong Key Laboratory of Construction and Detection in Tissue Engineering, Southern Medical University, Guangzhou 510515, China
- Department of Gynecology, Zhujiang Hospital, Southern Medical University, Guangzhou 510280, China
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13
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Study of Signal Transduction Pathways by Phospho-Protein Evaluation. Methods Mol Biol 2021. [PMID: 33928554 DOI: 10.1007/978-1-0716-1311-5_16] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register]
Abstract
Flow cytometric evaluation of phosphorylation status of signal transduction molecules is a useful method to study T-cell signaling pathways. As mutations occurring in TCR complex molecules, common gamma chain family's cytokines, their receptors or molecules involved in these pathways can lead to severe immune system defects, the study of T-cell signal transduction can be applied to both basic and clinical/translational research areas. In the present chapter, we show two different protocols for the study of T- cell response to an antigen-like stimulus and to IL-2.
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14
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Haggerty RA, Purvis JE. Inferring the structures of signaling motifs from paired dynamic traces of single cells. PLoS Comput Biol 2021; 17:e1008657. [PMID: 33539338 PMCID: PMC7889133 DOI: 10.1371/journal.pcbi.1008657] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2019] [Revised: 02/17/2021] [Accepted: 12/26/2020] [Indexed: 11/18/2022] Open
Abstract
Individual cells show variability in their signaling dynamics that often correlates with phenotypic responses, indicating that cell-to-cell variability is not merely noise but can have functional consequences. Based on this observation, we reasoned that cell-to-cell variability under the same treatment condition could be explained in part by a single signaling motif that maps different upstream signals into a corresponding set of downstream responses. If this assumption holds, then repeated measurements of upstream and downstream signaling dynamics in a population of cells could provide information about the underlying signaling motif for a given pathway, even when no prior knowledge of that motif exists. To test these two hypotheses, we developed a computer algorithm called MISC (Motif Inference from Single Cells) that infers the underlying signaling motif from paired time-series measurements from individual cells. When applied to measurements of transcription factor and reporter gene expression in the yeast stress response, MISC predicted signaling motifs that were consistent with previous mechanistic models of transcription. The ability to detect the underlying mechanism became less certain when a cell's upstream signal was randomly paired with another cell's downstream response, demonstrating how averaging time-series measurements across a population obscures information about the underlying signaling mechanism. In some cases, motif predictions improved as more cells were added to the analysis. These results provide evidence that mechanistic information about cellular signaling networks can be systematically extracted from the dynamical patterns of single cells.
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Affiliation(s)
- Raymond A. Haggerty
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina, United States of America
- Computational Medicine Program, University of North Carolina, Chapel Hill, North Carolina, United States of America
- Curriculum for Bioinformatics and Computational Biology, University of North Carolina, Chapel Hill, North Carolina, United States of America
| | - Jeremy E. Purvis
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina, United States of America
- Computational Medicine Program, University of North Carolina, Chapel Hill, North Carolina, United States of America
- Curriculum for Bioinformatics and Computational Biology, University of North Carolina, Chapel Hill, North Carolina, United States of America
- Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, North Carolina, United States of America
- * E-mail:
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15
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Patino CA, Mukherjee P, Lemaitre V, Pathak N, Espinosa HD. Deep Learning and Computer Vision Strategies for Automated Gene Editing with a Single-Cell Electroporation Platform. SLAS Technol 2021; 26:26-36. [PMID: 33449846 DOI: 10.1177/2472630320982320] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
Single-cell delivery platforms like microinjection and nanoprobe electroporation enable unparalleled control over cell manipulation tasks but are generally limited in throughput. Here, we present an automated single-cell electroporation system capable of automatically detecting cells with artificial intelligence (AI) software and delivering exogenous cargoes of different sizes with uniform dosage. We implemented a fully convolutional network (FCN) architecture to precisely locate the nuclei and cytosol of six cell types with various shapes and sizes, using phase contrast microscopy. Nuclear staining or reporter fluorescence was used along with phase contrast images of cells within the same field of view to facilitate the manual annotation process. Furthermore, we leveraged the near-human inference capabilities of the FCN network in detecting stained nuclei to automatically generate ground-truth labels of thousands of cells within seconds, and observed no statistically significant difference in performance compared to training with manual annotations. The average detection sensitivity and precision of the FCN network were 95±1.7% and 90±1.8%, respectively, outperforming a traditional image-processing algorithm (72±7.2% and 72±5.5%) used for comparison. To test the platform, we delivered fluorescent-labeled proteins into adhered cells and measured a delivery efficiency of 90%. As a demonstration, we used the automated single-cell electroporation platform to deliver Cas9-guide RNA (gRNA) complexes into an induced pluripotent stem cell (iPSC) line to knock out a green fluorescent protein-encoding gene in a population of ~200 cells. The results demonstrate that automated single-cell delivery is a useful cell manipulation tool for applications that demand throughput, control, and precision.
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Affiliation(s)
- Cesar A Patino
- Department of Mechanical Engineering, Northwestern University, Evanston, IL, USA.,iNfinitesimal LLC, Skokie, IL, USA
| | - Prithvijit Mukherjee
- Department of Mechanical Engineering, Northwestern University, Evanston, IL, USA.,Theoretical and Applied Mechanics Program, Northwestern University, Evanston, IL, USA.,iNfinitesimal LLC, Skokie, IL, USA
| | | | - Nibir Pathak
- Department of Mechanical Engineering, Northwestern University, Evanston, IL, USA.,Theoretical and Applied Mechanics Program, Northwestern University, Evanston, IL, USA
| | - Horacio D Espinosa
- Department of Mechanical Engineering, Northwestern University, Evanston, IL, USA.,Theoretical and Applied Mechanics Program, Northwestern University, Evanston, IL, USA.,iNfinitesimal LLC, Skokie, IL, USA
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16
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Manninen T, Saudargiene A, Linne ML. Astrocyte-mediated spike-timing-dependent long-term depression modulates synaptic properties in the developing cortex. PLoS Comput Biol 2020; 16:e1008360. [PMID: 33170856 PMCID: PMC7654831 DOI: 10.1371/journal.pcbi.1008360] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2020] [Accepted: 09/22/2020] [Indexed: 12/26/2022] Open
Abstract
Astrocytes have been shown to modulate synaptic transmission and plasticity in specific cortical synapses, but our understanding of the underlying molecular and cellular mechanisms remains limited. Here we present a new biophysicochemical model of a somatosensory cortical layer 4 to layer 2/3 synapse to study the role of astrocytes in spike-timing-dependent long-term depression (t-LTD) in vivo. By applying the synapse model and electrophysiological data recorded from rodent somatosensory cortex, we show that a signal from a postsynaptic neuron, orchestrated by endocannabinoids, astrocytic calcium signaling, and presynaptic N-methyl-D-aspartate receptors coupled with calcineurin signaling, induces t-LTD which is sensitive to the temporal difference between post- and presynaptic firing. We predict for the first time the dynamics of astrocyte-mediated molecular mechanisms underlying t-LTD and link complex biochemical networks at presynaptic, postsynaptic, and astrocytic sites to the time window of t-LTD induction. During t-LTD a single astrocyte acts as a delay factor for fast neuronal activity and integrates fast neuronal sensory processing with slow non-neuronal processing to modulate synaptic properties in the brain. Our results suggest that astrocytes play a critical role in synaptic computation during postnatal development and are of paramount importance in guiding the development of brain circuit functions, learning and memory.
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Affiliation(s)
- Tiina Manninen
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Department of Neurobiology, Stanford University, Stanford, CA, USA
| | - Ausra Saudargiene
- Neuroscience Institute, Lithuanian University of Health Sciences, Kaunas, Lithuania
- Department of Informatics, Vytautas Magnus University, Kaunas, Lithuania
| | - Marja-Leena Linne
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
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17
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Jashnsaz H, Fox ZR, Hughes JJ, Li G, Munsky B, Neuert G. Diverse Cell Stimulation Kinetics Identify Predictive Signal Transduction Models. iScience 2020; 23:101565. [PMID: 33083733 PMCID: PMC7549069 DOI: 10.1016/j.isci.2020.101565] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2019] [Revised: 08/18/2020] [Accepted: 09/11/2020] [Indexed: 11/28/2022] Open
Abstract
Computationally understanding the molecular mechanisms that give rise to cell signaling responses upon different environmental, chemical, and genetic perturbations is a long-standing challenge that requires models that fit and predict quantitative responses for new biological conditions. Overcoming this challenge depends not only on good models and detailed experimental data but also on the rigorous integration of both. We propose a quantitative framework to perturb and model generic signaling networks using multiple and diverse changing environments (hereafter "kinetic stimulations") resulting in distinct pathway activation dynamics. We demonstrate that utilizing multiple diverse kinetic stimulations better constrains model parameters and enables predictions of signaling dynamics that would be impossible using traditional dose-response or individual kinetic stimulations. To demonstrate our approach, we use experimentally identified models to predict signaling dynamics in normal, mutated, and drug-treated conditions upon multitudes of kinetic stimulations and quantify which proteins and reaction rates are most sensitive to which extracellular stimulations.
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Affiliation(s)
- Hossein Jashnsaz
- Department of Molecular Physiology and Biophysics, School of Medicine, Vanderbilt University, Nashville, TN 37232, USA
| | - Zachary R Fox
- Inria Saclay Ile-de-France, Palaiseau 91120, France.,Institut Pasteur, USR 3756 IP CNRS, Paris 75015, France.,Keck Scholars, School of Biomedical Engineering, Colorado State University, Fort Collins, CO 80523, USA
| | - Jason J Hughes
- Department of Molecular Physiology and Biophysics, School of Medicine, Vanderbilt University, Nashville, TN 37232, USA
| | - Guoliang Li
- Department of Molecular Physiology and Biophysics, School of Medicine, Vanderbilt University, Nashville, TN 37232, USA
| | - Brian Munsky
- Keck Scholars, School of Biomedical Engineering, Colorado State University, Fort Collins, CO 80523, USA.,Department of Chemical and Biological Engineering, Colorado State University, Fort Collins, CO 80523, USA
| | - Gregor Neuert
- Department of Molecular Physiology and Biophysics, School of Medicine, Vanderbilt University, Nashville, TN 37232, USA.,Department of Biomedical Engineering, School of Engineering, Vanderbilt University, Nashville, TN 37232, USA.,Department of Pharmacology, School of Medicine, Vanderbilt University, Nashville, TN 37232, USA
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18
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Poberezhnyi V, Marchuk O, Katilov O, Shvydiuk O, Lohvinov O. Basic concepts and physical-chemical phenomena, that have conceptual meaning for the formation of systemic clinical thinking and formalization of the knowledge of systemic structural-functional organization of the human’s organism. PAIN MEDICINE 2020. [DOI: 10.31636/pmjua.v5i2.2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
From the point of view of perception and generalization processes there are complex, logic and conceptual forms of thinking. Its conceptual form is the highest result of interaction between thinking and speech. While realizing it, human uses the concept, which are logically formed thoughts, that are the meaning of representation in thinking of unity of meaningful features, relations of subjects or phenomena of objective reality. Special concepts, that are used in the science and technique are called terms. They perform a function of corresponding, special, precise marking of subjects and phenomena, their features and interactions. Scientific knowledge are in that way an objective representation of material duality in our consciousness. Certain complex of terms forms a terminological system, that lies in the basis of corresponding sphere of scientific knowledge and conditions a corresponding form and way of thinking. Clinical thinking is a conceptual form, that manifests and represents by the specialized internal speech with gnostic motivation lying in its basis. Its structural elements are corresponding definitions, terms and concepts. Cardinal features of clinical systems are consistency, criticality, justification and substantiation. Principles of perception and main concepts are represented in the article along with short descriptions of physical and chemical phenomena, that have conceptual meaning for the formation of systematic clinical thinking and formalization of systemic structural-functional organization of the human’s organism
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19
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Salazar-Cavazos E, Nitta CF, Mitra ED, Wilson BS, Lidke KA, Hlavacek WS, Lidke DS. Multisite EGFR phosphorylation is regulated by adaptor protein abundances and dimer lifetimes. Mol Biol Cell 2020; 31:695-708. [PMID: 31913761 PMCID: PMC7202077 DOI: 10.1091/mbc.e19-09-0548] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022] Open
Abstract
Differential epidermal growth factor receptor (EGFR) phosphorylation is thought to couple receptor activation to distinct signaling pathways. However, the molecular mechanisms responsible for biased signaling are unresolved due to a lack of insight into the phosphorylation patterns of full-length EGFR. We extended a single-molecule pull-down technique previously used to study protein-protein interactions to allow for robust measurement of receptor phosphorylation. We found that EGFR is predominantly phosphorylated at multiple sites, yet phosphorylation at specific tyrosines is variable and only a subset of receptors share phosphorylation at the same site, even with saturating ligand concentrations. We found distinct populations of receptors as soon as 1 min after ligand stimulation, indicating early diversification of function. To understand this heterogeneity, we developed a mathematical model. The model predicted that variations in phosphorylation are dependent on the abundances of signaling partners, while phosphorylation levels are dependent on dimer lifetimes. The predictions were confirmed in studies of cell lines with different expression levels of signaling partners, and in experiments comparing low- and high-affinity ligands and oncogenic EGFR mutants. These results reveal how ligand-regulated receptor dimerization dynamics and adaptor protein concentrations play critical roles in EGFR signaling.
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Affiliation(s)
| | | | - Eshan D Mitra
- Theoretical Biology and Biophysics Group, Theoretical Division, Los Alamos National Laboratory, Los Alamos, NM 87545
| | | | - Keith A Lidke
- Comprehensive Cancer Center, and.,Department of Physics and Astronomy, University of New Mexico, Albuquerque, NM 87131
| | - William S Hlavacek
- Comprehensive Cancer Center, and.,Theoretical Biology and Biophysics Group, Theoretical Division, Los Alamos National Laboratory, Los Alamos, NM 87545
| | - Diane S Lidke
- Department of Pathology.,Comprehensive Cancer Center, and
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20
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Del Sol A, Okawa S, Ravichandran S. Computational Strategies for Niche-Dependent Cell Conversion to Assist Stem Cell Therapy. Trends Biotechnol 2019; 37:687-696. [PMID: 30782480 DOI: 10.1016/j.tibtech.2019.01.005] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2018] [Revised: 01/14/2019] [Accepted: 01/15/2019] [Indexed: 12/28/2022]
Abstract
The field of regenerative medicine has blossomed in recent decades. However, the ultimate goal of tissue regeneration - replacing damaged or aged cells with healthy functioning cells - still faces a number of challenges. In particular, better understanding of the role of the cellular niche in shaping stem cell phenotype and conversion would aid in improving current protocols for stem cell therapies. In this regard, the implementation of novel computational approaches that consider the niche effect on stem cells would be valuable. Here we discuss current problems in stem cell transplantation and rejuvenation, and we propose computational strategies to control niche-dependent cell conversion to overcome them.
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Affiliation(s)
- Antonio Del Sol
- Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg,7 Avenue des Hauts-Fourneaux, Esch-sur-Alzette, L-4362 Luxembourg City, Luxembourg; CIC bioGUNE,Bizkaia Technology Park, 801 Building, 48160 Derio, Spain; IKERBASQUE, Basque Foundation for Science, Bilbao 48013, Spain; Moscow Institute of Physics and Technology, 141700 Dolgoprudny, Russia.
| | - Satoshi Okawa
- Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg,7 Avenue des Hauts-Fourneaux, Esch-sur-Alzette, L-4362 Luxembourg City, Luxembourg
| | - Srikanth Ravichandran
- Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg,7 Avenue des Hauts-Fourneaux, Esch-sur-Alzette, L-4362 Luxembourg City, Luxembourg
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21
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Mathematical Modeling and Parameter Estimation of Intracellular Signaling Pathway: Application to LPS-induced NFκB Activation and TNFα Production in Macrophages. Processes (Basel) 2018. [DOI: 10.3390/pr6030021] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022] Open
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22
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The emergence of dynamic phenotyping. Cell Biol Toxicol 2017; 33:507-509. [DOI: 10.1007/s10565-017-9413-x] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2017] [Accepted: 09/18/2017] [Indexed: 02/07/2023]
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23
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Pu J, Dewey JA, Hadji A, LaBelle JL, Dickinson BC. RNA Polymerase Tags To Monitor Multidimensional Protein-Protein Interactions Reveal Pharmacological Engagement of Bcl-2 Proteins. J Am Chem Soc 2017; 139:11964-11972. [PMID: 28767232 PMCID: PMC5828006 DOI: 10.1021/jacs.7b06152] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
We report the development of a new technology for monitoring multidimensional protein-protein interactions (PPIs) inside live mammalian cells using split RNA polymerase (RNAP) tags. In this new system, a protein-of-interest is tagged with an N-terminal split RNAP (RNAPN), and multiple potential binding partners are each fused to orthogonal C-terminal RNAPs (RNAPC). Assembly of RNAPN with each RNAPC is highly dependent on interactions between the tagged proteins. Each PPI-mediated RNAPN-RNAPC assembly transcribes from a separate promoter on a supplied DNA substrate, thereby generating a unique RNA output signal for each PPI. We develop and validate this new approach in the context of the Bcl-2 family of proteins. These key regulators of apoptosis are important cancer mediators, but are challenging to therapeutically target due to imperfect selectivity that leads to either off-target toxicity or tumor resistance. We demonstrate binary (1 × 1) and ternary (1 × 2) Bcl-2 PPI analyses by imaging fluorescent protein translation from mRNA outputs. Next, we perform a 1 × 4 PPI network analysis by direct measurement of four unique RNA signals via RT-qPCR. Finally, we use these new tools to monitor pharmacological engagement of Bcl-2 protein inhibitors, and uncover inhibitor-dependent competitive PPIs. The split RNAP tags improve upon other protein fragment complementation (PFC) approaches by offering both multidimensionality and sensitive detection using nucleic acid amplification and analysis techniques. Furthermore, this technology opens new opportunities for synthetic biology applications due to the versatility of RNA outputs for cellular engineering applications.
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Affiliation(s)
- Jinyue Pu
- Department of Chemistry, The University of Chicago, Chicago, IL 60637
| | - Jeffrey A. Dewey
- Department of Chemistry, The University of Chicago, Chicago, IL 60637
| | - Abbas Hadji
- Section of Hematology, Oncology, Stem Cell Transplantation, Department of Pediatrics, The University of Chicago, Comer Children’s Hospital, Chicago, IL, 60637
| | - James L. LaBelle
- Section of Hematology, Oncology, Stem Cell Transplantation, Department of Pediatrics, The University of Chicago, Comer Children’s Hospital, Chicago, IL, 60637
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24
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