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Dhillon N, Kamakaka RT. Transcriptional silencing in Saccharomyces cerevisiae: known unknowns. Epigenetics Chromatin 2024; 17:28. [PMID: 39272151 PMCID: PMC11401328 DOI: 10.1186/s13072-024-00553-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2024] [Accepted: 09/02/2024] [Indexed: 09/15/2024] Open
Abstract
Transcriptional silencing in Saccharomyces cerevisiae is a persistent and highly stable form of gene repression. It involves DNA silencers and repressor proteins that bind nucleosomes. The silenced state is influenced by numerous factors including the concentration of repressors, nature of activators, architecture of regulatory elements, modifying enzymes and the dynamics of chromatin.Silencers function to increase the residence time of repressor Sir proteins at silenced domains while clustering of silenced domains enables increased concentrations of repressors and helps facilitate long-range interactions. The presence of an accessible NDR at the regulatory regions of silenced genes, the cycling of chromatin configurations at regulatory sites, the mobility of Sir proteins, and the non-uniform distribution of the Sir proteins across the silenced domain, all result in silenced chromatin that only stably silences weak promoters and enhancers via changes in transcription burst duration and frequency.These data collectively suggest that silencing is probabilistic and the robustness of silencing is achieved through sub-optimization of many different nodes of action such that a stable expression state is generated and maintained even though individual constituents are in constant flux.
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Affiliation(s)
- Namrita Dhillon
- Department of Biomolecular Engineering, University of California, 1156 High Street, Santa Cruz, CA, 95064, USA
| | - Rohinton T Kamakaka
- Department of MCD Biology, University of California, 1156 High Street, Santa Cruz, CA, 95064, USA.
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2
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Volteras D, Shahrezaei V, Thomas P. Global transcription regulation revealed from dynamical correlations in time-resolved single-cell RNA sequencing. Cell Syst 2024; 15:694-708.e12. [PMID: 39121860 DOI: 10.1016/j.cels.2024.07.002] [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: 10/24/2023] [Revised: 02/29/2024] [Accepted: 07/11/2024] [Indexed: 08/12/2024]
Abstract
Single-cell transcriptomics reveals significant variations in transcriptional activity across cells. Yet, it remains challenging to identify mechanisms of transcription dynamics from static snapshots. It is thus still unknown what drives global transcription dynamics in single cells. We present a stochastic model of gene expression with cell size- and cell cycle-dependent rates in growing and dividing cells that harnesses temporal dimensions of single-cell RNA sequencing through metabolic labeling protocols and cel lcycle reporters. We develop a parallel and highly scalable approximate Bayesian computation method that corrects for technical variation and accurately quantifies absolute burst frequency, burst size, and degradation rate along the cell cycle at a transcriptome-wide scale. Using Bayesian model selection, we reveal scaling between transcription rates and cell size and unveil waves of gene regulation across the cell cycle-dependent transcriptome. Our study shows that stochastic modeling of dynamical correlations identifies global mechanisms of transcription regulation. A record of this paper's transparent peer review process is included in the supplemental information.
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Affiliation(s)
- Dimitris Volteras
- Department of Mathematics, Faculty of Natural Sciences, Imperial College London, London, SW7 2AZ, UK
| | - Vahid Shahrezaei
- Department of Mathematics, Faculty of Natural Sciences, Imperial College London, London, SW7 2AZ, UK.
| | - Philipp Thomas
- Department of Mathematics, Faculty of Natural Sciences, Imperial College London, London, SW7 2AZ, UK.
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3
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Hasterok S, Jankovskaja S, Miletic Dahlström R, Prgomet Z, Ohlsson L, Björklund S, Gustafsson A. Exploring the Surface: Sampling of Potential Skin Cancer Biomarkers Kynurenine and Tryptophan, Studied on 3D Melanocyte and Melanoma Models. Biomolecules 2024; 14:815. [PMID: 39062529 PMCID: PMC11274760 DOI: 10.3390/biom14070815] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2024] [Revised: 07/01/2024] [Accepted: 07/05/2024] [Indexed: 07/28/2024] Open
Abstract
Early detection of cancer via biomarkers is vital for improving patient survival rates. In the case of skin cancers, low-molecular-weight biomarkers can penetrate the skin barrier, enabling non-invasive sampling at an early stage. This study focuses on detecting tryptophan (Trp) and kynurenine (Kyn) on the surface of reconstructed 3D melanoma and melanocyte models. This is examined in connection with IDO-1 and IL-6 expression in response to IFN-γ or UVB stimulation, both crucial factors of the melanoma tumor microenvironment (TME). Using a polystyrene scaffold, full-thickness human skin equivalents containing fibroblasts, keratinocytes, and melanocytes or melanoma cells were developed. The samples were stimulated with IFN-γ or UVB, and Trp and Kyn secretion was measured using HPLC-PDA and HPLC-MS. The expression of IDO-1 and IL-6 was measured using RT-qPCR. Increased Trp catabolism to Kyn was observed in IFN-γ-stimulated melanoma and melanocyte models, along with higher IDO-1 expression. UVB exposure led to significant changes in Kyn levels but only in the melanoma model. This study demonstrates the potential of skin surface Trp and Kyn monitoring to capture TME metabolic changes. It also lays the groundwork for future in vivo studies, aiding in understanding and monitoring skin cancer progression.
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Affiliation(s)
- Sylwia Hasterok
- Department of Biomedical Science, Faculty of Health and Society, Malmö University, 205 06 Malmo, Sweden; (S.J.); (R.M.D.); (Z.P.); (L.O.); (S.B.)
- Biofilms Research Center for Biointerfaces, Malmö University, 205 06 Malmo, Sweden
| | - Skaidre Jankovskaja
- Department of Biomedical Science, Faculty of Health and Society, Malmö University, 205 06 Malmo, Sweden; (S.J.); (R.M.D.); (Z.P.); (L.O.); (S.B.)
- Biofilms Research Center for Biointerfaces, Malmö University, 205 06 Malmo, Sweden
| | - Ruzica Miletic Dahlström
- Department of Biomedical Science, Faculty of Health and Society, Malmö University, 205 06 Malmo, Sweden; (S.J.); (R.M.D.); (Z.P.); (L.O.); (S.B.)
- Biofilms Research Center for Biointerfaces, Malmö University, 205 06 Malmo, Sweden
| | - Zdenka Prgomet
- Department of Biomedical Science, Faculty of Health and Society, Malmö University, 205 06 Malmo, Sweden; (S.J.); (R.M.D.); (Z.P.); (L.O.); (S.B.)
- Biofilms Research Center for Biointerfaces, Malmö University, 205 06 Malmo, Sweden
- Section for Oral Biology and Pathology, Faculty of Odontology, Malmö University, 214 21 Malmo, Sweden
| | - Lars Ohlsson
- Department of Biomedical Science, Faculty of Health and Society, Malmö University, 205 06 Malmo, Sweden; (S.J.); (R.M.D.); (Z.P.); (L.O.); (S.B.)
- Biofilms Research Center for Biointerfaces, Malmö University, 205 06 Malmo, Sweden
| | - Sebastian Björklund
- Department of Biomedical Science, Faculty of Health and Society, Malmö University, 205 06 Malmo, Sweden; (S.J.); (R.M.D.); (Z.P.); (L.O.); (S.B.)
- Biofilms Research Center for Biointerfaces, Malmö University, 205 06 Malmo, Sweden
| | - Anna Gustafsson
- Department of Biomedical Science, Faculty of Health and Society, Malmö University, 205 06 Malmo, Sweden; (S.J.); (R.M.D.); (Z.P.); (L.O.); (S.B.)
- Biofilms Research Center for Biointerfaces, Malmö University, 205 06 Malmo, Sweden
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4
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Derks J, Jonson T, Leduc A, Khan S, Khoury L, Rafiee MR, Slavov N. Single-nucleus proteomics identifies regulators of protein transport. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.17.599449. [PMID: 38948785 PMCID: PMC11212961 DOI: 10.1101/2024.06.17.599449] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/02/2024]
Abstract
The physiological response of a cell to stimulation depends on its proteome configuration. Therefore, the abundance variation of regulatory proteins across unstimulated single cells can be associatively linked with their response to stimulation. Here we developed an approach that leverages this association across individual cells and nuclei to systematically identify potential regulators of biological processes, followed by targeted validation. Specifically, we applied this approach to identify regulators of nucleocytoplasmic protein transport in macrophages stimulated with lipopolysaccharide (LPS). To this end, we quantified the proteomes of 3,412 individual nuclei, sampling the dynamic response to LPS treatment, and linking functional variability to proteomic variability. Minutes after the stimulation, the protein transport in individual nuclei correlated strongly with the abundance of known protein transport regulators, thus revealing the impact of natural protein variability on functional cellular response. We found that simple biophysical constraints, such as the quantity of nuclear pores, partially explain the variability in LPS-induced nucleocytoplasmic transport. Among the many proteins newly identified to be associated with the response, we selected 16 for targeted validation by knockdown. The knockdown phenotypes confirmed the inferences derived from natural protein and functional variation of single nuclei, thus demonstrating the potential of (sub-)single-cell proteomics to infer functional regulation. We expect this approach to generalize to broad applications and enhance the functional interpretability of single-cell omics data.
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Affiliation(s)
- Jason Derks
- Departments of Bioengineering, Biology, Chemistry and Chemical Biology, Single Cell Center, Northeastern University, Boston, MA 02115, USA
- Parallel Squared Technology Institute, Watertown, MA 02472, USA
| | - Tobias Jonson
- Departments of Bioengineering, Biology, Chemistry and Chemical Biology, Single Cell Center, Northeastern University, Boston, MA 02115, USA
| | - Andrew Leduc
- Departments of Bioengineering, Biology, Chemistry and Chemical Biology, Single Cell Center, Northeastern University, Boston, MA 02115, USA
| | - Saad Khan
- Departments of Bioengineering, Biology, Chemistry and Chemical Biology, Single Cell Center, Northeastern University, Boston, MA 02115, USA
| | - Luke Khoury
- Departments of Bioengineering, Biology, Chemistry and Chemical Biology, Single Cell Center, Northeastern University, Boston, MA 02115, USA
| | - Mahmoud-Reza Rafiee
- Departments of Bioengineering, Biology, Chemistry and Chemical Biology, Single Cell Center, Northeastern University, Boston, MA 02115, USA
| | - Nikolai Slavov
- Departments of Bioengineering, Biology, Chemistry and Chemical Biology, Single Cell Center, Northeastern University, Boston, MA 02115, USA
- Parallel Squared Technology Institute, Watertown, MA 02472, USA
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Guha M, Singh A, Butzin NC. Gram-positive bacteria are primed for surviving lethal doses of antibiotics and chemical stress. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.28.596288. [PMID: 38895422 PMCID: PMC11185512 DOI: 10.1101/2024.05.28.596288] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/21/2024]
Abstract
Antibiotic resistance kills millions worldwide yearly. However, a major contributor to recurrent infections lies in a small fraction of bacterial cells, known as persisters. These cells are not inherently antibiotic-resistant, yet they lead to increased antibiotic usage, raising the risk of developing resistant progenies. In a bacterial population, individual cells exhibit considerable fluctuations in their gene expression levels despite being cultivated under identical, stable conditions. This variability in cell-to-cell characteristics (phenotypic diversity) within an isogenic population enables persister cells to withstand antibiotic exposure by entering a non-dividing state. We recently showed the existence of "primed cells" in E. coli. Primed cells are dividing cells prepared for antibiotic stress before encountering it and are more prone to form persisters. They also pass their "prepared state" down for several generations through epigenetic memory. Here, we show that primed cells are common among distant bacterial lineages, allowing for survival against antibiotics and other chemical stress, and form in different growth phases. They are also responsible for increased persister levels in transition and stationary phases compared to the log phase. We tested and showed that the Gram-positive bacterium Bacillus megaterium, evolutionarily very distant from E. coli, forms primed cells and has a transient epigenetic memory that is maintained for 7 generations or more. We showed this using ciprofloxacin and the non-antibiotic chemical stress fluoride. It is well established that persister levels are higher in the stationary phase than in the log phase, and B. megaterium persisters levels are nearly identical from the early to late-log phase but are ~2-fold and ~4-fold higher in the transition and stationary phase, respectively. It was previously proposed that there are two distinct types of persisters: Type II forms in the log phase, while Type I forms in the stationary phase. However, we show that primed cells lead to increased persisters in the transition and stationary phase and found no evidence of Type I or II persisters with distant phenotypes. Overall, we have provided substantial evidence of the importance of primed cells and their transitory epigenetic memories to surviving stress.
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Affiliation(s)
- Manisha Guha
- Department of Biology and Microbiology; South Dakota State University; Brookings, SD, 57006; USA
| | - Abhyudai Singh
- Electrical & Computer Engineering; University of Delaware; Newark, DE 19716; USA
| | - Nicholas C. Butzin
- Department of Biology and Microbiology; South Dakota State University; Brookings, SD, 57006; USA
- Department of Chemistry and Biochemistry; South Dakota State University; Brookings, SD, 57006; USA
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Ramirez Flores RO, Schäfer PSL, Küchenhoff L, Saez-Rodriguez J. Complementing Cell Taxonomies with a Multicellular Analysis of Tissues. Physiology (Bethesda) 2024; 39:0. [PMID: 38319138 DOI: 10.1152/physiol.00001.2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2024] [Accepted: 01/31/2024] [Indexed: 02/07/2024] Open
Abstract
The application of single-cell molecular profiling coupled with spatial technologies has enabled charting of cellular heterogeneity in reference tissues and in disease. This new wave of molecular data has highlighted the expected diversity of single-cell dynamics upon shared external queues and spatial organizations. However, little is known about the relationship between single-cell heterogeneity and the emergence and maintenance of robust multicellular processes in developed tissues and its role in (patho)physiology. Here, we present emerging computational modeling strategies that use increasingly available large-scale cross-condition single-cell and spatial datasets to study multicellular organization in tissues and complement cell taxonomies. This perspective should enable us to better understand how cells within tissues collectively process information and adapt synchronized responses in disease contexts and to bridge the gap between structural changes and functions in tissues.
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Affiliation(s)
- Ricardo Omar Ramirez Flores
- Faculty of Medicine, Heidelberg University and Institute for Computational Biomedicine, Heidelberg University Hospital, Heidelberg, Germany
| | - Philipp Sven Lars Schäfer
- Faculty of Medicine, Heidelberg University and Institute for Computational Biomedicine, Heidelberg University Hospital, Heidelberg, Germany
| | - Leonie Küchenhoff
- Faculty of Medicine, Heidelberg University and Institute for Computational Biomedicine, Heidelberg University Hospital, Heidelberg, Germany
| | - Julio Saez-Rodriguez
- Faculty of Medicine, Heidelberg University and Institute for Computational Biomedicine, Heidelberg University Hospital, Heidelberg, Germany
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Van Eyndhoven LC, Chouri E, Matos CI, Pandit A, Radstake TRDJ, Broen JCA, Singh A, Tel J. Unraveling IFN-I response dynamics and TNF crosstalk in the pathophysiology of systemic lupus erythematosus. Front Immunol 2024; 15:1322814. [PMID: 38596672 PMCID: PMC11002168 DOI: 10.3389/fimmu.2024.1322814] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Accepted: 03/08/2024] [Indexed: 04/11/2024] Open
Abstract
Introduction The innate immune system serves the crucial first line of defense against a wide variety of potential threats, during which the production of pro-inflammatory cytokines IFN-I and TNFα are key. This astonishing power to fight invaders, however, comes at the cost of risking IFN-I-related pathologies, such as observed during autoimmune diseases, during which IFN-I and TNFα response dynamics are dysregulated. Therefore, these response dynamics must be tightly regulated, and precisely matched with the potential threat. This regulation is currently far from understood. Methods Using droplet-based microfluidics and ODE modeling, we studied the fundamentals of single-cell decision-making upon TLR signaling in human primary immune cells (n = 23). Next, using biologicals used for treating autoimmune diseases [i.e., anti-TNFα, and JAK inhibitors], we unraveled the crosstalk between IFN-I and TNFα signaling dynamics. Finally, we studied primary immune cells isolated from SLE patients (n = 8) to provide insights into SLE pathophysiology. Results single-cell IFN-I and TNFα response dynamics display remarkable differences, yet both being highly heterogeneous. Blocking TNFα signaling increases the percentage of IFN-I-producing cells, while blocking IFN-I signaling decreases the percentage of TNFα-producing cells. Single-cell decision-making in SLE patients is dysregulated, pointing towards a dysregulated crosstalk between IFN-I and TNFα response dynamics. Discussion We provide a solid droplet-based microfluidic platform to study inherent immune secretory behaviors, substantiated by ODE modeling, which can challenge the conceptualization within and between different immune signaling systems. These insights will build towards an improved fundamental understanding on single-cell decision-making in health and disease.
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Affiliation(s)
- Laura C. Van Eyndhoven
- Laboratory of Immunoengineering, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands
- Institute for Complex Molecular Systems (ICMS), Eindhoven University of Technology, Eindhoven, Netherlands
| | - Eleni Chouri
- Laboratory of Immunoengineering, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands
- Institute for Complex Molecular Systems (ICMS), Eindhoven University of Technology, Eindhoven, Netherlands
| | - Catarina I. Matos
- Laboratory of Immunoengineering, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands
- Institute for Complex Molecular Systems (ICMS), Eindhoven University of Technology, Eindhoven, Netherlands
| | - Aridaman Pandit
- Center for Translational Immunology, Department of Immunology, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
- Department of Rheumatology and Clinical Immunology, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
| | - Timothy R. D. J. Radstake
- Center for Translational Immunology, Department of Immunology, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
- Department of Rheumatology and Clinical Immunology, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
| | - Jasper C. A. Broen
- Regional Rheumatology Center, Máxima Medical Center, Eindhoven and Veldhoven, Eindhoven, Netherlands
| | - Abhyudai Singh
- Department of Electrical and Computer Engineering, University of Delaware, Newark, DE, United States
| | - Jurjen Tel
- Laboratory of Immunoengineering, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands
- Institute for Complex Molecular Systems (ICMS), Eindhoven University of Technology, Eindhoven, Netherlands
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8
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Shlyakhtina Y, Bloechl B, Moran KL, Portal MM. Protocol to study the inheritance and propagation of non-genetically encoded states using barcode decay lineage tracing. STAR Protoc 2024; 5:102809. [PMID: 38180835 PMCID: PMC10801334 DOI: 10.1016/j.xpro.2023.102809] [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: 10/08/2023] [Revised: 11/21/2023] [Accepted: 12/15/2023] [Indexed: 01/07/2024] Open
Abstract
Here, we present a protocol to perform barcode decay lineage tracing followed by single-cell transcriptome analysis (BdLT-Seq). We describe steps for BdLT-Seq experimental design, building barcoded episome reporters, performing episome transfection, and barcode retrieval. We then describe procedures for sequencing library construction while providing options for sample multiplexing and data analysis. This BdLT-Seq technique enables the assessment of clonal evolution in a directional manner while preserving isogeneity, thus allowing the comparison of non-genetic molecular features between isogenic cell lineages. For complete details on the use and execution of this protocol, please refer to Shlyakhtina et al. (2023).1.
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Affiliation(s)
- Yelyzaveta Shlyakhtina
- Cell Plasticity & Epigenetics Lab, Cancer Research UK Manchester Institute, The University of Manchester, Manchester M20 4BX, UK; Cell Plasticity & Epigenetics Lab, Cancer Research UK - Cancer Research UK Scotland Institute, The University of Glasgow, Glasgow G61 1BD, UK
| | - Bianca Bloechl
- Cell Plasticity & Epigenetics Lab, Cancer Research UK Manchester Institute, The University of Manchester, Manchester M20 4BX, UK; Cell Plasticity & Epigenetics Lab, Cancer Research UK - Cancer Research UK Scotland Institute, The University of Glasgow, Glasgow G61 1BD, UK
| | - Katherine L Moran
- Cell Plasticity & Epigenetics Lab, Cancer Research UK Manchester Institute, The University of Manchester, Manchester M20 4BX, UK
| | - Maximiliano M Portal
- Cell Plasticity & Epigenetics Lab, Cancer Research UK Manchester Institute, The University of Manchester, Manchester M20 4BX, UK; Cell Plasticity & Epigenetics Lab, Cancer Research UK - Cancer Research UK Scotland Institute, The University of Glasgow, Glasgow G61 1BD, UK.
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9
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Mitchell KJ. Variability in Neural Circuit Formation. Cold Spring Harb Perspect Biol 2024; 16:a041504. [PMID: 38253418 PMCID: PMC10910361 DOI: 10.1101/cshperspect.a041504] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
The study of neural development is usually concerned with the question of how nervous systems get put together. Variation in these processes is usually of interest as a means of revealing these normative mechanisms. However, variation itself can be an object of study and is of interest from multiple angles. First, the nature of variation in both the processes and the outcomes of neural development is relevant to our understanding of how these processes and outcomes are encoded in the genome. Second, variation in the wiring of the brain in humans may underlie variation in all kinds of psychological and behavioral traits, as well as neurodevelopmental disorders. And third, genetic variation that affects circuit development provides the raw material for evolutionary change. Here, I examine these different aspects of variation in circuit development and consider what they may tell us about these larger questions.
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Affiliation(s)
- Kevin J Mitchell
- Smurfit Institute of Genetics and Institute of Neuroscience, Trinity College Dublin, Dublin D02 PN40, Ireland
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10
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Jain N, Goyal Y, Dunagin MC, Cote CJ, Mellis IA, Emert B, Jiang CL, Dardani IP, Reffsin S, Arnett M, Yang W, Raj A. Retrospective identification of cell-intrinsic factors that mark pluripotency potential in rare somatic cells. Cell Syst 2024; 15:109-133.e10. [PMID: 38335955 PMCID: PMC10940218 DOI: 10.1016/j.cels.2024.01.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Revised: 05/31/2023] [Accepted: 01/12/2024] [Indexed: 02/12/2024]
Abstract
Pluripotency can be induced in somatic cells by the expression of OCT4, KLF4, SOX2, and MYC. Usually only a rare subset of cells reprogram, and the molecular characteristics of this subset remain unknown. We apply retrospective clone tracing to identify and characterize the rare human fibroblasts primed for reprogramming. These fibroblasts showed markers of increased cell cycle speed and decreased fibroblast activation. Knockdown of a fibroblast activation factor identified by our analysis increased the reprogramming efficiency. We provide evidence for a unified model in which cells can move into and out of the primed state over time, explaining how reprogramming appears deterministic at short timescales and stochastic at long timescales. Furthermore, inhibiting the activity of LSD1 enlarged the pool of cells that were primed for reprogramming. Thus, even homogeneous cell populations can exhibit heritable molecular variability that can dictate whether individual rare cells will reprogram or not.
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Affiliation(s)
- Naveen Jain
- Genetics and Epigenetics Program, Cell and Molecular Biology Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Yogesh Goyal
- Department of Cell and Developmental Biology, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA; Center for Synthetic Biology, Northwestern University, Chicago, IL 60611, USA; Robert H. Lurie Comprehensive Cancer Center, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA; Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Margaret C Dunagin
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Christopher J Cote
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Ian A Mellis
- Genomics and Computational Biology Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Benjamin Emert
- Genomics and Computational Biology Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Connie L Jiang
- Genetics and Epigenetics Program, Cell and Molecular Biology Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Ian P Dardani
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Sam Reffsin
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Miles Arnett
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Wenli Yang
- Department of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Institute for Regenerative Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Penn Cardiovascular Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Arjun Raj
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
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11
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Alibekova Long M, Benman WKJ, Petrikas N, Bugaj LJ, Hughes AJ. Enhancing Single-Cell Western Blotting Sensitivity Using Diffusive Analyte Blotting and Antibody Conjugate Amplification. Anal Chem 2023; 95:17894-17902. [PMID: 37974303 DOI: 10.1021/acs.analchem.3c04130] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2023]
Abstract
While there are many techniques to achieve highly sensitive, multiplex detection of RNA and DNA from single cells, detecting protein content often suffers from low limits of detection and throughput. Miniaturized, high-sensitivity Western blots on single cells (scWesterns) are attractive because they do not require advanced instrumentation. By physically separating analytes, scWesterns also uniquely mitigate limitations to target protein multiplexing posed by the affinity reagent performance. However, a fundamental limitation of scWesterns is their limited sensitivity for detecting low-abundance proteins, which arises from transport barriers posed by the separation gel against detection species. Here we address the sensitivity by decoupling the electrophoretic separation medium from the detection medium. We transfer scWestern separations to a nitrocellulose blotting medium with distinct mass transfer advantages over traditional in-gel probing, yielding a 5.9-fold improvement in the limit of detection. We next amplify probing of blotted proteins with enzyme-antibody conjugates, which are incompatible with traditional in-gel probing to achieve further improvement in the limit of detection to 1000 molecules, a 120-fold improvement. This enables us to detect 100% of cells in an EGFP-expressing population using fluorescently tagged and enzyme-conjugated antibodies compared to 84.5% of cells using in-gel detection. These results suggest the compatibility of nitrocellulose-immobilized scWesterns with a variety of affinity reagents─not previously accessible for in-gel use─for further signal amplification and detection of low-abundance targets.
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Affiliation(s)
- Mariia Alibekova Long
- Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
- Bioengineering Graduate Group, University of Pennsylvania, Philadelphia, Pennsylvania, 19104, United States
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
| | - William K J Benman
- Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
- Bioengineering Graduate Group, University of Pennsylvania, Philadelphia, Pennsylvania, 19104, United States
| | - Nathan Petrikas
- Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
| | - Lukasz J Bugaj
- Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
- Bioengineering Graduate Group, University of Pennsylvania, Philadelphia, Pennsylvania, 19104, United States
- Institute for Regenerative Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
- Abramson Cancer Center, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
| | - Alex J Hughes
- Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
- Bioengineering Graduate Group, University of Pennsylvania, Philadelphia, Pennsylvania, 19104, United States
- Institute for Regenerative Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
- Department of Cell and Developmental Biology, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
- Center for Soft and Living Matter, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
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12
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Rey T, Tábara LC, Prudent J, Minczuk M. mtFociCounter for automated single-cell mitochondrial nucleoid quantification and reproducible foci analysis. Nucleic Acids Res 2023; 51:e107. [PMID: 37850644 PMCID: PMC10681798 DOI: 10.1093/nar/gkad864] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Revised: 09/13/2023] [Accepted: 10/01/2023] [Indexed: 10/19/2023] Open
Abstract
Mitochondrial DNA (mtDNA) encodes the core subunits for OXPHOS, essential in near-all eukaryotes. Packed into distinct foci (nucleoids) inside mitochondria, the number of mtDNA copies differs between cell-types and is affected in several human diseases. Currently, common protocols estimate per-cell mtDNA-molecule numbers by sequencing or qPCR from bulk samples. However, this does not allow insight into cell-to-cell heterogeneity and can mask phenotypical sub-populations. Here, we present mtFociCounter, a single-cell image analysis tool for reproducible quantification of nucleoids and other foci. mtFociCounter is a light-weight, open-source freeware and overcomes current limitations to reproducible single-cell analysis of mitochondrial foci. We demonstrate its use by analysing 2165 single fibroblasts, and observe a large cell-to-cell heterogeneity in nucleoid numbers. In addition, mtFociCounter quantifies mitochondrial content and our results show good correlation (R = 0.90) between nucleoid number and mitochondrial area, and we find nucleoid density is less variable than nucleoid numbers in wild-type cells. Finally, we demonstrate mtFociCounter readily detects differences in foci-numbers upon sample treatment, and applies to Mitochondrial RNA Granules and superresolution microscopy. mtFociCounter provides a versatile solution to reproducibly quantify cellular foci in single cells and our results highlight the importance of accounting for cell-to-cell variance and mitochondrial context in mitochondrial foci analysis.
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Affiliation(s)
- Timo Rey
- Medical Research Council Mitochondrial Biology Unit, University of Cambridge, Cambridge CB2 0XY, UK
| | - Luis Carlos Tábara
- Medical Research Council Mitochondrial Biology Unit, University of Cambridge, Cambridge CB2 0XY, UK
| | - Julien Prudent
- Medical Research Council Mitochondrial Biology Unit, University of Cambridge, Cambridge CB2 0XY, UK
| | - Michal Minczuk
- Medical Research Council Mitochondrial Biology Unit, University of Cambridge, Cambridge CB2 0XY, UK
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13
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Wu K, Dhillon N, Bajor A, Abrahamson S, Kamakaka RT. Yeast Heterochromatin Only Stably Silences Weak Regulatory Elements by Altering Burst Duration. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.05.561072. [PMID: 37873261 PMCID: PMC10592971 DOI: 10.1101/2023.10.05.561072] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
The interplay between nucleosomes and transcription factors leads to programs of gene expression. Transcriptional silencing involves the generation of a chromatin state that represses transcription and is faithfully propagated through DNA replication and cell division. Using multiple reporter assays, including directly visualizing transcription in single cells, we investigated a diverse set of UAS enhancers and core promoters for their susceptibility to heterochromatic gene silencing. These results show that heterochromatin only stably silences weak and stress induced regulatory elements but is unable to stably repress housekeeping gene regulatory elements and the partial repression did not result in bistable expression states. Permutation analysis of different UAS enhancers and core promoters indicate that both elements function together to determine the susceptibility of regulatory sequences to repression. Specific histone modifiers and chromatin remodellers function in an enhancer specific manner to aid these elements to resist repression suggesting that Sir proteins likely function in part by reducing nucleosome mobility. We also show that the strong housekeeping regulatory elements can be repressed if silencer bound Sir1 is increased, suggesting that Sir1 is a limiting component in silencing. Together, our data suggest that the heterochromatic locus has been optimized to stably silence the weak mating type gene regulatory elements but not strong housekeeping gene regulatory sequences which could help explain why these genes are often found at the boundaries of silenced domains.
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Affiliation(s)
- Kenneth Wu
- Department of MCD Biology, 1156 High Street, University of California, Santa Cruz, CA 95064 USA
| | - Namrita Dhillon
- Department of MCD Biology, 1156 High Street, University of California, Santa Cruz, CA 95064 USA
| | - Antone Bajor
- Electrical Engineering Department, Baskin School of Engineering, 1156 High Street, University of California, Santa Cruz, CA 95064 USA
| | - Sara Abrahamson
- Electrical Engineering Department, Baskin School of Engineering, 1156 High Street, University of California, Santa Cruz, CA 95064 USA
| | - Rohinton T. Kamakaka
- Department of MCD Biology, 1156 High Street, University of California, Santa Cruz, CA 95064 USA
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14
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Hossain T, Singh A, Butzin NC. Escherichia coli cells are primed for survival before lethal antibiotic stress. Microbiol Spectr 2023; 11:e0121923. [PMID: 37698413 PMCID: PMC10581089 DOI: 10.1128/spectrum.01219-23] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Accepted: 07/16/2023] [Indexed: 09/13/2023] Open
Abstract
Non-genetic factors can cause significant fluctuations in gene expression levels. Regardless of growing in a stable environment, this fluctuation leads to cell-to-cell variability in an isogenic population. This phenotypic heterogeneity allows a tiny subset of bacterial cells in a population called persister cells to tolerate long-term lethal antibiotic effects by entering into a non-dividing, metabolically repressed state. We occasionally noticed a high variation in persister levels, and to explore this, we tested clonal populations starting from a single cell using a modified Luria-Delbrück fluctuation test. Although we kept the conditions same, the diversity in persistence level among clones was relatively consistent: varying from ~60- to 100- and ~40- to 70-fold for ampicillin and apramycin, respectively. Then, we divided and diluted each clone to observe whether the same clone had comparable persister levels for more than one generation. Replicates had similar persister levels even when clones were divided, diluted by 1:20, and allowed to grow for approximately five generations. This result explicitly shows a cellular memory passed on for generations and eventually lost when cells are diluted to 1:100 and regrown (>seven generations). Our result demonstrates (1) the existence of a small population prepared for stress ("primed cells") resulting in higher persister numbers; (2) the primed memory state is reproducible and transient, passed down for generations but eventually lost; and (3) a heterogeneous persister population is a result of a transiently primed reversible cell state and not due to a pre-existing genetic mutation. IMPORTANCE Antibiotics have been highly effective in treating lethal infectious diseases for almost a century. However, the increasing threat of antibiotic resistance is again causing these diseases to become life-threatening. The longer a bacteria can survive antibiotics, the more likely it is to develop resistance. Complicating matters is that non-genetic factors can allow bacterial cells with identical DNA to gain transient resistance (also known as persistence). Here, we show that a small fraction of the bacterial population called primed cells can pass down non-genetic information ("memory") to their offspring, enabling them to survive lethal antibiotics for a long time. However, this memory is eventually lost. These results demonstrate how bacteria can leverage differences among genetically identical cells formed through non-genetic factors to form primed cells with a selective advantage to survive antibiotics.
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Affiliation(s)
- Tahmina Hossain
- Department of Biology and Microbiology, South Dakota State University, Brookings, South Dakota, USA
| | - Abhyudai Singh
- Electrical & Computer Engineering, University of Delaware, Newark, Delaware, USA
| | - Nicholas C. Butzin
- Department of Biology and Microbiology, South Dakota State University, Brookings, South Dakota, USA
- Department of Chemistry and Biochemistry, South Dakota State University, Brookings, South Dakota, USA
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15
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Aslan Kamil M, Fourneaux C, Yilmaz A, Stavros S, Parmentier R, Paldi A, Gonin-Giraud S, deMello AJ, Gandrillon O. An image-guided microfluidic system for single-cell lineage tracking. PLoS One 2023; 18:e0288655. [PMID: 37527253 PMCID: PMC10393162 DOI: 10.1371/journal.pone.0288655] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Accepted: 06/30/2023] [Indexed: 08/03/2023] Open
Abstract
Cell lineage tracking is a long-standing and unresolved problem in biology. Microfluidic technologies have the potential to address this problem, by virtue of their ability to manipulate and process single-cells in a rapid, controllable and efficient manner. Indeed, when coupled with traditional imaging approaches, microfluidic systems allow the experimentalist to follow single-cell divisions over time. Herein, we present a valve-based microfluidic system able to probe the decision-making processes of single-cells, by tracking their lineage over multiple generations. The system operates by trapping single-cells within growth chambers, allowing the trapped cells to grow and divide, isolating sister cells after a user-defined number of divisions and finally extracting them for downstream transcriptome analysis. The platform incorporates multiple cell manipulation operations, image processing-based automation for cell loading and growth monitoring, reagent addition and device washing. To demonstrate the efficacy of the microfluidic workflow, 6C2 (chicken erythroleukemia) and T2EC (primary chicken erythrocytic progenitors) cells are tracked inside the microfluidic device over two generations, with a cell viability rate in excess of 90%. Sister cells are successfully isolated after division and extracted within a 500 nL volume, which was demonstrated to be compatible with downstream single-cell RNA sequencing analysis.
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Affiliation(s)
- Mahmut Aslan Kamil
- Institute for Chemical and Bioengineering, Department of Chemistry and Applied Biosciences, ETH Zürich, Zürich, Switzerland
| | - Camille Fourneaux
- Laboratory of Biology and Modelling of the Cell, Université de Lyon, Ecole Normale Supérieure de Lyon, CNRS, UMR5239, Université Claude Bernard, Lyon, France
| | | | - Stavrakis Stavros
- Institute for Chemical and Bioengineering, Department of Chemistry and Applied Biosciences, ETH Zürich, Zürich, Switzerland
| | - Romuald Parmentier
- Ecole Pratique des Hautes Etudes, St-Antoine Research Center, Inserm U938, PSL Research University, Paris, France
| | - Andras Paldi
- Ecole Pratique des Hautes Etudes, St-Antoine Research Center, Inserm U938, PSL Research University, Paris, France
| | - Sandrine Gonin-Giraud
- Laboratory of Biology and Modelling of the Cell, Université de Lyon, Ecole Normale Supérieure de Lyon, CNRS, UMR5239, Université Claude Bernard, Lyon, France
| | - Andrew J deMello
- Institute for Chemical and Bioengineering, Department of Chemistry and Applied Biosciences, ETH Zürich, Zürich, Switzerland
| | - Olivier Gandrillon
- Laboratory of Biology and Modelling of the Cell, Université de Lyon, Ecole Normale Supérieure de Lyon, CNRS, UMR5239, Université Claude Bernard, Lyon, France
- Inria, France
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16
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Goyal Y, Busch GT, Pillai M, Li J, Boe RH, Grody EI, Chelvanambi M, Dardani IP, Emert B, Bodkin N, Braun J, Fingerman D, Kaur A, Jain N, Ravindran PT, Mellis IA, Kiani K, Alicea GM, Fane ME, Ahmed SS, Li H, Chen Y, Chai C, Kaster J, Witt RG, Lazcano R, Ingram DR, Johnson SB, Wani K, Dunagin MC, Lazar AJ, Weeraratna AT, Wargo JA, Herlyn M, Raj A. Diverse clonal fates emerge upon drug treatment of homogeneous cancer cells. Nature 2023; 620:651-659. [PMID: 37468627 PMCID: PMC10628994 DOI: 10.1038/s41586-023-06342-8] [Citation(s) in RCA: 61] [Impact Index Per Article: 61.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2021] [Accepted: 06/19/2023] [Indexed: 07/21/2023]
Abstract
Even among genetically identical cancer cells, resistance to therapy frequently emerges from a small subset of those cells1-7. Molecular differences in rare individual cells in the initial population enable certain cells to become resistant to therapy7-9; however, comparatively little is known about the variability in the resistance outcomes. Here we develop and apply FateMap, a framework that combines DNA barcoding with single-cell RNA sequencing, to reveal the fates of hundreds of thousands of clones exposed to anti-cancer therapies. We show that resistant clones emerging from single-cell-derived cancer cells adopt molecularly, morphologically and functionally distinct resistant types. These resistant types are largely predetermined by molecular differences between cells before drug addition and not by extrinsic factors. Changes in the dose and type of drug can switch the resistant type of an initial cell, resulting in the generation and elimination of certain resistant types. Samples from patients show evidence for the existence of these resistant types in a clinical context. We observed diversity in resistant types across several single-cell-derived cancer cell lines and cell types treated with a variety of drugs. The diversity of resistant types as a result of the variability in intrinsic cell states may be a generic feature of responses to external cues.
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Affiliation(s)
- Yogesh Goyal
- Department of Cell and Developmental Biology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
- Center for Synthetic Biology, Northwestern University, Chicago, IL, USA.
- Robert H. Lurie Comprehensive Cancer Center, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA, USA.
| | - Gianna T Busch
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA, USA
| | - Maalavika Pillai
- Department of Cell and Developmental Biology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
- Center for Synthetic Biology, Northwestern University, Chicago, IL, USA
- Robert H. Lurie Comprehensive Cancer Center, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Jingxin Li
- Genetics and Epigenetics, Cell and Molecular Biology Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Ryan H Boe
- Genetics and Epigenetics, Cell and Molecular Biology Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Emanuelle I Grody
- Department of Cell and Developmental Biology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
- Center for Synthetic Biology, Northwestern University, Chicago, IL, USA
- Robert H. Lurie Comprehensive Cancer Center, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Manoj Chelvanambi
- Department of Genomic Medicine, Division of Cancer Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Ian P Dardani
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA, USA
| | - Benjamin Emert
- Genomics and Computational Biology Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Nicholas Bodkin
- Department of Cell and Developmental Biology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
- Center for Synthetic Biology, Northwestern University, Chicago, IL, USA
- Robert H. Lurie Comprehensive Cancer Center, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Jonas Braun
- Department of Cell and Developmental Biology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
- Center for Synthetic Biology, Northwestern University, Chicago, IL, USA
- Robert H. Lurie Comprehensive Cancer Center, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | | | - Amanpreet Kaur
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA, USA
| | - Naveen Jain
- Genetics and Epigenetics, Cell and Molecular Biology Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Pavithran T Ravindran
- Genetics and Epigenetics, Cell and Molecular Biology Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Ian A Mellis
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA, USA
- Genomics and Computational Biology Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Karun Kiani
- Genetics and Epigenetics, Cell and Molecular Biology Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Gretchen M Alicea
- Department of Biochemistry and Molecular Biology, Johns Hopkins School of Public Health, Baltimore, MD, USA
- Department of Oncology, Sidney Kimmel Cancer Center, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Mitchell E Fane
- Department of Biochemistry and Molecular Biology, Johns Hopkins School of Public Health, Baltimore, MD, USA
- Department of Oncology, Sidney Kimmel Cancer Center, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Syeda Subia Ahmed
- Department of Cell and Developmental Biology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
- Center for Synthetic Biology, Northwestern University, Chicago, IL, USA
- Robert H. Lurie Comprehensive Cancer Center, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Haiyin Li
- The Wistar Institute, Philadelphia, PA, USA
| | | | - Cedric Chai
- Department of Cell and Developmental Biology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
- Center for Synthetic Biology, Northwestern University, Chicago, IL, USA
- Robert H. Lurie Comprehensive Cancer Center, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
- Center for Reproductive Science, Northwestern University, Chicago, IL, USA
| | | | - Russell G Witt
- Department of Genomic Medicine, Division of Cancer Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Rossana Lazcano
- Department of Genomic Medicine, Division of Cancer Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
- Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Davis R Ingram
- Department of Genomic Medicine, Division of Cancer Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
- Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Sarah B Johnson
- Department of Genomic Medicine, Division of Cancer Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Khalida Wani
- Department of Genomic Medicine, Division of Cancer Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Margaret C Dunagin
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Alexander J Lazar
- Department of Genomic Medicine, Division of Cancer Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
- Department of Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Ashani T Weeraratna
- Department of Biochemistry and Molecular Biology, Johns Hopkins School of Public Health, Baltimore, MD, USA
- Department of Oncology, Sidney Kimmel Cancer Center, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Jennifer A Wargo
- Department of Genomic Medicine, Division of Cancer Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | | | - Arjun Raj
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
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17
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Long MA, Benman W, Petrikas N, Bugaj LJ, Hughes AJ. Enhancing single-cell western blotting sensitivity using diffusive analyte blotting and antibody conjugate amplification. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.06.13.544857. [PMID: 37398364 PMCID: PMC10312704 DOI: 10.1101/2023.06.13.544857] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/04/2023]
Abstract
While there are many techniques to achieve highly sensitive, multiplex detection of RNA and DNA from single cells, detecting protein contents often suffers from low limits of detection and throughput. Miniaturized, high-sensitivity western blots on single cells (scWesterns) are attractive since they do not require advanced instrumentation. By physically separating analytes, scWesterns also uniquely mitigate limitations to target protein multiplexing posed by affinity reagent performance. However, a fundamental limitation of scWesterns is their limited sensitivity for detecting low-abundance proteins, which arises from transport barriers posed by the separation gel against detection species. Here we address sensitivity by decoupling the electrophoretic separation medium from the detection medium. We transfer scWestern separations to a nitrocellulose blotting medium with distinct mass transfer advantages over traditional in-gel probing, yielding a 5.9-fold improvement in limit of detection. We next amplify probing of blotted proteins with enzyme-antibody conjugates which are incompatible with traditional in-gel probing to achieve further improvement in the limit of detection to 103 molecules, a 520-fold improvement. This enables us to detect 85% and 100% of cells in an EGFP-expressing population using fluorescently tagged and enzyme-conjugated antibodies respectively, compared to 47% of cells using in-gel detection. These results suggest compatibility of nitrocellulose-immobilized scWesterns with a variety of affinity reagents - not previously accessible for in-gel use - for further signal amplification and detection of low abundance targets.
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Affiliation(s)
- Mariia Alibekova Long
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, 19104, PA, USA
- Bioengineering Graduate Group, University of Pennsylvania, Philadelphia, PA, 19104, PA, USA
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, PA, USA
| | - William Benman
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, 19104, PA, USA
- Bioengineering Graduate Group, University of Pennsylvania, Philadelphia, PA, 19104, PA, USA
| | - Nathan Petrikas
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, 19104, PA, USA
- Currently at Tempus Labs Inc., Chicago, IL, USA
| | - Lukasz J. Bugaj
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, 19104, PA, USA
- Bioengineering Graduate Group, University of Pennsylvania, Philadelphia, PA, 19104, PA, USA
- Institute for Regenerative Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Alex J. Hughes
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, 19104, PA, USA
- Bioengineering Graduate Group, University of Pennsylvania, Philadelphia, PA, 19104, PA, USA
- Institute for Regenerative Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Cell and Developmental Biology, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Center for Soft and Living Matter, University of Pennsylvania, Philadelphia, PA, 19104, USA
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18
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Quantifying how promoter-associated nucleosomes regulate transcriptional bursting. Nat Struct Mol Biol 2023; 30:577-578. [PMID: 37130986 DOI: 10.1038/s41594-023-00982-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
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19
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Itani A, Shida Y, Ogasawara W. A microfluidic device for simultaneous detection of enzyme secretion and elongation of a single hypha. Front Microbiol 2023; 14:1125760. [PMID: 36937311 PMCID: PMC10020217 DOI: 10.3389/fmicb.2023.1125760] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Accepted: 02/16/2023] [Indexed: 03/06/2023] Open
Abstract
Filamentous fungi grow through elongation of their apical region by exocytosis and secrete enzymes that can be of commercial or industrial importance. Their hyphae exhibit extensive branching, making it difficult to control hyphal growth for observation and analysis. Therefore, although hyphal morphology and productivity are closely related, the relationship between the two has not yet been clarified. Conventional morphology and productivity studies have only compared the results of macro imaging of fungal pellets cultured in bulk with the averaged products in the culture medium. Filamentous fungi are multicellular and their expression differs between different hyphae. To truly understand the relationship between morphology and productivity, it is necessary to compare the morphology and productivity of individual hyphae. To achieve this, we developed a microfluidic system that confines hyphae to individual channels for observation and investigated the relationship between their growth, morphology, and enzyme productivity. Furthermore, using Trichoderma reesei, a potent cellulase-producing fungus, as a model, we developed a cellulase detection assay with 4-MUC substrate to detect hyphal growth and enzyme secretion in a microfluidic device in real time. Using a strain that expresses cellobiohydrolase I (CBH I) fused with AcGFP1, we compared fluorescence from the detection assay with GFP fluorescence intensity, which showed a strong correlation between the two. These results indicate that extracellular enzymes can be easily detected in the microfluidic device in real time because the production of cellulase is synchronized in T. reesei. This microfluidic system enables real-time visualization of the dynamics of hypha and enzymes during carbon source exchange and the quantitative dynamics of gene expression. This technology can be applied to many biosystems from bioenergy production to human health.
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Affiliation(s)
- Ayaka Itani
- Department of Bioengineering, Nagaoka University of Technology, Nagaoka, Japan
| | - Yosuke Shida
- Department of Bioengineering, Nagaoka University of Technology, Nagaoka, Japan
| | - Wataru Ogasawara
- Department of Bioengineering, Nagaoka University of Technology, Nagaoka, Japan
- Department of Science of Technology Innovation, Nagaoka University of Technology, Nagaoka, Japan
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20
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Shlyakhtina Y, Bloechl B, Portal MM. BdLT-Seq as a barcode decay-based method to unravel lineage-linked transcriptome plasticity. Nat Commun 2023; 14:1085. [PMID: 36841849 PMCID: PMC9968323 DOI: 10.1038/s41467-023-36744-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2022] [Accepted: 02/14/2023] [Indexed: 02/26/2023] Open
Abstract
Cell plasticity is a core biological process underlying a myriad of molecular and cellular events taking place throughout organismal development and evolution. It has been postulated that cellular systems thrive to balance the organization of meta-stable states underlying this phenomenon, thereby maintaining a degree of populational homeostasis compatible with an ever-changing environment and, thus, life. Notably, albeit circumstantial evidence has been gathered in favour of the latter conceptual framework, a direct observation of meta-state dynamics and the biological consequences of such a process in generating non-genetic clonal diversity and divergent phenotypic output remains largely unexplored. To fill this void, here we develop a lineage-tracing technology termed Barcode decay Lineage Tracing-Seq. BdLT-Seq is based on episome-encoded molecular identifiers that, supported by the dynamic decay of the tracing information upon cell division, ascribe directionality to a cell lineage tree whilst directly coupling non-genetic molecular features to phenotypes in comparable genomic landscapes. We show that cell transcriptome states are both inherited, and dynamically reshaped following constrained rules encoded within the cell lineage in basal growth conditions, upon oncogene activation and throughout the process of reversible resistance to therapeutic cues thus adjusting phenotypic output leading to intra-clonal non-genetic diversity.
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Affiliation(s)
- Yelyzaveta Shlyakhtina
- Cell Plasticity & Epigenetics Lab, Cancer Research UK - Manchester Institute, The University of Manchester, SK10 4TG, Manchester, UK
| | - Bianca Bloechl
- Cell Plasticity & Epigenetics Lab, Cancer Research UK - Manchester Institute, The University of Manchester, SK10 4TG, Manchester, UK
| | - Maximiliano M Portal
- Cell Plasticity & Epigenetics Lab, Cancer Research UK - Manchester Institute, The University of Manchester, SK10 4TG, Manchester, UK.
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21
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Jain N, Goyal Y, Dunagin MC, Cote CJ, Mellis IA, Emert B, Jiang CL, Dardani IP, Reffsin S, Raj A. Retrospective identification of intrinsic factors that mark pluripotency potential in rare somatic cells. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.10.527870. [PMID: 36798299 PMCID: PMC9934612 DOI: 10.1101/2023.02.10.527870] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/13/2023]
Abstract
Pluripotency can be induced in somatic cells by the expression of the four "Yamanaka" factors OCT4, KLF4, SOX2, and MYC. However, even in homogeneous conditions, usually only a rare subset of cells admit reprogramming, and the molecular characteristics of this subset remain unknown. Here, we apply retrospective clone tracing to identify and characterize the individual human fibroblast cells that are primed for reprogramming. These fibroblasts showed markers of increased cell cycle speed and decreased fibroblast activation. Knockdown of a fibroblast activation factor identified by our analysis led to increased reprogramming efficiency, identifying it as a barrier to reprogramming. Changing the frequency of reprogramming by inhibiting the activity of LSD1 led to an enlarging of the pool of cells that were primed for reprogramming. Our results show that even homogeneous cell populations can exhibit heritable molecular variability that can dictate whether individual rare cells will reprogram or not.
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Affiliation(s)
- Naveen Jain
- Genetics and Epigenetics Program, Cell and Molecular Biology Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Yogesh Goyal
- Department of Cell and Developmental Biology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
- Center for Synthetic Biology, Northwestern University, Chicago, IL, USA
- Robert H. Lurie Comprehensive Cancer Center, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA, USA
| | - Margaret C Dunagin
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA, USA
| | - Christopher J Cote
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA, USA
| | - Ian A Mellis
- Genomics and Computational Biology Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Benjamin Emert
- Genomics and Computational Biology Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Connie L Jiang
- Genetics and Epigenetics Program, Cell and Molecular Biology Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Ian P Dardani
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA, USA
| | - Sam Reffsin
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA, USA
| | - Arjun Raj
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
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22
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Kilic Z, Schweiger M, Moyer C, Shepherd D, Pressé S. Gene expression model inference from snapshot RNA data using Bayesian non-parametrics. NATURE COMPUTATIONAL SCIENCE 2023; 3:174-183. [PMID: 38125199 PMCID: PMC10732567 DOI: 10.1038/s43588-022-00392-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Accepted: 12/15/2022] [Indexed: 12/23/2023]
Abstract
Gene expression models, which are key towards understanding cellular regulatory response, underlie observations of single-cell transcriptional dynamics. Although RNA expression data encode information on gene expression models, existing computational frameworks do not perform simultaneous Bayesian inference of gene expression models and parameters from such data. Rather, gene expression models-composed of gene states, their connectivities and associated parameters-are currently deduced by pre-specifying gene state numbers and connectivity before learning associated rate parameters. Here we propose a method to learn full distributions over gene states, state connectivities and associated rate parameters, simultaneously and self-consistently from single-molecule RNA counts. We propagate noise from fluctuating RNA counts over models by treating models themselves as random variables. We achieve this within a Bayesian non-parametric paradigm. We demonstrate our method on the Escherichia coli lacZ pathway and the Saccharomyces cerevisiae STL1 pathway, and verify its robustness on synthetic data.
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Affiliation(s)
- Zeliha Kilic
- Department of Structural Biology, St. Jude Children’s Research Hospital, Memphis, TN, USA
- These authors contributed equally: Zeliha Kilic, Max Schweiger
| | - Max Schweiger
- Center for Biological Physics, ASU, Tempe, AZ, USA
- Department of Physics, ASU, Tempe, AZ, USA
- These authors contributed equally: Zeliha Kilic, Max Schweiger
| | - Camille Moyer
- Center for Biological Physics, ASU, Tempe, AZ, USA
- School of Mathematics and Statistical Sciences, ASU, Tempe, AZ, USA
| | - Douglas Shepherd
- Center for Biological Physics, ASU, Tempe, AZ, USA
- Department of Physics, ASU, Tempe, AZ, USA
| | - Steve Pressé
- Center for Biological Physics, ASU, Tempe, AZ, USA
- Department of Physics, ASU, Tempe, AZ, USA
- School of Molecular Sciences, ASU, Tempe, AZ, USA
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23
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Van Eyndhoven LC, Verberne VPG, Bouten CVC, Singh A, Tel J. Transiently heritable fates and quorum sensing drive early IFN-I response dynamics. eLife 2023; 12:83055. [PMID: 36629318 PMCID: PMC9910831 DOI: 10.7554/elife.83055] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Accepted: 01/10/2023] [Indexed: 01/12/2023] Open
Abstract
Type I interferon (IFN-I)-mediated antiviral responses are central to host defense against viral infections. Crucial is the tight and well-orchestrated control of cellular decision-making leading to the production of IFN-Is. Innovative single-cell approaches revealed that the initiation of IFN-I production is limited to only fractions of 1-3% of the total population, both found in vitro, in vivo, and across cell types, which were thought to be stochastically regulated. To challenge this dogma, we addressed the influence of various stochastic and deterministic host-intrinsic factors on dictating early IFN-I responses, using a murine fibroblast reporter model. Epigenetic drugs influenced the percentage of responding cells. Next, with the classical Luria-Delbrück fluctuation test, we provided evidence for transient heritability driving responder fates, which was verified with mathematical modeling. Finally, while studying varying cell densities, we substantiated an important role for cell density in dictating responsiveness, similar to the phenomenon of quorum sensing. Together, this systems immunology approach opens up new avenues to progress the fundamental understanding on cellular decision-making during early IFN-I responses, which can be translated to other (immune) signaling systems.
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Affiliation(s)
- Laura C Van Eyndhoven
- Laboratory of Immunoengineering, Department of Biomedical Engineering, Eindhoven University of TechnologyEindhovenNetherlands
- Institute for Complex Molecular Systems (ICMS), Eindhoven University of TechnologyEindhovenNetherlands
| | - Vincent PG Verberne
- Laboratory of Immunoengineering, Department of Biomedical Engineering, Eindhoven University of TechnologyEindhovenNetherlands
- Institute for Complex Molecular Systems (ICMS), Eindhoven University of TechnologyEindhovenNetherlands
| | - Carlijn VC Bouten
- Institute for Complex Molecular Systems (ICMS), Eindhoven University of TechnologyEindhovenNetherlands
- Department of Biomedical Engineering, Eindhoven University of TechnologyEindhovenNetherlands
| | - Abhyudai Singh
- Department of Electrical and Computer Engineering, University of DelawareNewarkUnited States
| | - Jurjen Tel
- Laboratory of Immunoengineering, Department of Biomedical Engineering, Eindhoven University of TechnologyEindhovenNetherlands
- Institute for Complex Molecular Systems (ICMS), Eindhoven University of TechnologyEindhovenNetherlands
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24
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Boe RH, Ayyappan V, Schuh L, Raj A. Allelic correlation is a marker of trade-offs between barriers to transmission of expression variability and signal responsiveness in genetic networks. Cell Syst 2022; 13:1016-1032.e6. [PMID: 36450286 PMCID: PMC9811561 DOI: 10.1016/j.cels.2022.10.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2021] [Revised: 06/28/2022] [Accepted: 10/28/2022] [Indexed: 12/03/2022]
Abstract
Genetic networks should respond to signals but prevent the transmission of spontaneous fluctuations. Limited data from mammalian cells suggest that noise transmission is uncommon, but systematic claims about noise transmission have been limited by the inability to directly measure it. Here, we build a mathematical framework modeling allelic correlation and noise transmission, showing that allelic correlation and noise transmission correspond across model parameters and network architectures. Limiting noise transmission comes with the trade-off of being unresponsive to signals, and within responsive regimes, there is a further trade-off between response time and basal noise transmission. Analysis of allele-specific single-cell RNA-sequencing data revealed that genes encoding upstream factors in signaling pathways and cell-type-specific factors have higher allelic correlation than downstream factors, suggesting they are more subject to regulation. Overall, our findings suggest that some noise transmission must result from signal responsiveness, but it can be minimized by trading off for a slower response. A record of this paper's transparent peer review process is included in the supplemental information.
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Affiliation(s)
- Ryan H Boe
- Genetics and Epigenetics, Cell and Molecular Biology Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Vinay Ayyappan
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA, USA
| | - Lea Schuh
- Institute of AI for Health, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764 Neuherberg, Germany; Department of Mathematics, Technical University of Munich, Garching 85748, Germany
| | - Arjun Raj
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA, USA; Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
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25
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Ding T, Zhang H. Novel biological insights revealed from the investigation of multiscale genome architecture. Comput Struct Biotechnol J 2022; 21:312-325. [PMID: 36582436 PMCID: PMC9791078 DOI: 10.1016/j.csbj.2022.12.009] [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: 08/12/2022] [Revised: 12/06/2022] [Accepted: 12/06/2022] [Indexed: 12/13/2022] Open
Abstract
Gene expression and cell fate determination require precise and coordinated epigenetic regulation. The complex three-dimensional (3D) genome organization plays a critical role in transcription in myriad biological processes. A wide range of architectural features of the 3D genome, including chromatin loops, topologically associated domains (TADs), chromatin compartments, and phase separation, together regulate the chromatin state and transcriptional activity at multiple levels. With the help of 3D genome informatics, recent biochemistry and imaging approaches based on different strategies have revealed functional interactions among biomacromolecules, even at the single-cell level. Here, we review the occurrence, mechanistic basis, and functional implications of dynamic genome organization, and outline recent experimental and computational approaches for profiling multiscale genome architecture to provide robust tools for studying the 3D genome.
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Affiliation(s)
- Tianyi Ding
- Institute for Regenerative Medicine of Shanghai East Hospital, Frontier Science Research Center for Stem Cells, School of Life Science and Technology, Tongji University, Shanghai, PR China
| | - He Zhang
- Institute for Regenerative Medicine of Shanghai East Hospital, Frontier Science Research Center for Stem Cells, School of Life Science and Technology, Tongji University, Shanghai, PR China
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26
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Petelski AA, Slavov N, Specht H. Single-Cell Proteomics Preparation for Mass Spectrometry Analysis Using Freeze-Heat Lysis and an Isobaric Carrier. J Vis Exp 2022:10.3791/63802. [PMID: 36571403 PMCID: PMC10027359 DOI: 10.3791/63802] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
Single-cell proteomics analysis requires sensitive, quantitatively accurate, widely accessible, and robust methods. To meet these requirements, the Single-Cell ProtEomics (SCoPE2) protocol was developed as a second-generation method for quantifying hundreds to thousands of proteins from limited samples, down to the level of a single cell. Experiments using this method have achieved quantifying over 3,000 proteins across 1,500 single mammalian cells (500-1,000 proteins per cell) in 10 days of mass spectrometer instrument time. SCoPE2 leverages a freeze-heat cycle for cell lysis, obviating the need for clean-up of single cells and consequently reducing sample losses, while expediting sample preparation and simplifying its automation. Additionally, the method uses an isobaric carrier, which aids protein identification and reduces sample losses. This video protocol provides detailed guidance to enable the adoption of automated single-cell protein analysis using only equipment and reagents that are widely accessible. We demonstrate critical steps in the procedure of preparing single cells for proteomic analysis, from harvesting up to injection to liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis. Additionally, viewers are guided through the principles of experimental design with the isobaric carrier, quality control for both isobaric carrier and single-cell preparations, and representative results with a discussion of limitations of the approach.
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Affiliation(s)
| | - Nikolai Slavov
- Department of Bioengineering, Northeastern University; Barnett Institute, Northeastern University; Department of Biology, Northeastern University
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27
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Van Eyndhoven LC, Tel J. Revising immune cell coordination: Origins and importance of single-cell variation. Eur J Immunol 2022; 52:1889-1897. [PMID: 36250412 PMCID: PMC10092580 DOI: 10.1002/eji.202250073] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Revised: 08/15/2022] [Accepted: 10/11/2022] [Indexed: 12/13/2022]
Abstract
Moving from the optimalization of single-cell technologies to the interpretation of the multi-complex single-cell data, the field of immunoengineering is granted with numerous important insights into the coordination of immune cell activation and how to modulate it for therapeutic purposes. However, insights come with additional follow-up questions that challenge our perception on how immune responses are generated and fine-tuned to fight a wide array of pathogens in ever-changing and often unpredictable microenvironments. Are immune responses really either being tightly regulated by molecular determinants, or highly flexible attributed to stochasticity? What exactly makes up the basic rules by which single cells cooperate to establish tissue-level immunity? Taking the type I IFN system and its newest insights as a main example throughout this review, we revise the basic concepts of (single) immune cell coordination, redefine the concepts of noise, stochasticity and determinism, and highlight the importance of single-cell variation in immunology and beyond.
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Affiliation(s)
- Laura C Van Eyndhoven
- Laboratory of Immunoengineering, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.,Institute for Complex Molecular Systems (ICMS), Eindhoven University of Technology, Eindhoven, The Netherlands
| | - Jurjen Tel
- Laboratory of Immunoengineering, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.,Institute for Complex Molecular Systems (ICMS), Eindhoven University of Technology, Eindhoven, The Netherlands
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28
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Multiple parameters shape the 3D chromatin structure of single nuclei at the doc locus in Drosophila. Nat Commun 2022; 13:5375. [PMID: 36104317 PMCID: PMC9474875 DOI: 10.1038/s41467-022-32973-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2022] [Accepted: 08/25/2022] [Indexed: 11/08/2022] Open
Abstract
AbstractThe spatial organization of chromatin at the scale of topologically associating domains (TADs) and below displays large cell-to-cell variations. Up until now, how this heterogeneity in chromatin conformation is shaped by chromatin condensation, TAD insulation, and transcription has remained mostly elusive. Here, we used Hi-M, a multiplexed DNA-FISH imaging technique providing developmental timing and transcriptional status, to show that the emergence of TADs at the ensemble level partially segregates the conformational space explored by single nuclei during the early development of Drosophila embryos. Surprisingly, a substantial fraction of nuclei display strong insulation even before TADs emerge. Moreover, active transcription within a TAD leads to minor changes to the local inter- and intra-TAD chromatin conformation in single nuclei and only weakly affects insulation to the neighboring TAD. Overall, our results indicate that multiple parameters contribute to shaping the chromatin architecture of single nuclei at the TAD scale.
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29
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Comandante-Lou N, Baumann DG, Fallahi-Sichani M. AP-1 transcription factor network explains diverse patterns of cellular plasticity in melanoma cells. Cell Rep 2022; 40:111147. [PMID: 35926467 DOI: 10.1016/j.celrep.2022.111147] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Revised: 06/04/2022] [Accepted: 07/07/2022] [Indexed: 12/28/2022] Open
Abstract
Cellular plasticity associated with fluctuations in transcriptional programs allows individual cells in a tumor to adopt heterogeneous differentiation states and switch phenotype during their adaptive responses to therapies. Despite increasing knowledge of such transcriptional programs, the molecular basis of cellular plasticity remains poorly understood. Here, we combine multiplexed transcriptional and protein measurements at population and single-cell levels with multivariate statistical modeling to show that the state of AP-1 transcription factor network plays a unifying role in explaining diverse patterns of plasticity in melanoma. We find that a regulated balance among AP-1 factors cJUN, JUND, FRA2, FRA1, and cFOS determines the intrinsic diversity of differentiation states and adaptive responses to MAPK inhibitors in melanoma cells. Perturbing this balance through genetic depletion of specific AP-1 proteins, or by MAPK inhibitors, shifts cellular heterogeneity in a predictable fashion. Thus, AP-1 may serve as a critical node for manipulating cellular plasticity with potential therapeutic implications.
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Affiliation(s)
- Natacha Comandante-Lou
- Department of Biomedical Engineering, University of Virginia, Charlottesville, VA 22908, USA; Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI 48109, USA
| | - Douglas G Baumann
- Department of Biomedical Engineering, University of Virginia, Charlottesville, VA 22908, USA
| | - Mohammad Fallahi-Sichani
- Department of Biomedical Engineering, University of Virginia, Charlottesville, VA 22908, USA; UVA Cancer Center, University of Virginia, Charlottesville, VA 22908, USA.
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30
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Loell K, Wu Y, Staller MV, Cohen B. Activation domains can decouple the mean and noise of gene expression. Cell Rep 2022; 40:111118. [PMID: 35858548 PMCID: PMC9912357 DOI: 10.1016/j.celrep.2022.111118] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2021] [Revised: 01/18/2022] [Accepted: 06/28/2022] [Indexed: 11/03/2022] Open
Abstract
Regulatory mechanisms set a gene's average level of expression, but a gene's expression constantly fluctuates around that average. These stochastic fluctuations, or expression noise, play a role in cell-fate transitions, bet hedging in microbes, and the development of chemotherapeutic resistance in cancer. An outstanding question is what regulatory mechanisms contribute to noise. Here, we demonstrate that, for a fixed mean level of expression, strong activation domains (ADs) at low abundance produce high expression noise, while weak ADs at high abundance generate lower expression noise. We conclude that differences in noise can be explained by the interplay between a TF's nuclear concentration and the strength of its AD's effect on mean expression, without invoking differences between classes of ADs. These results raise the possibility of engineering gene expression noise independently of mean levels in synthetic biology contexts and provide a potential mechanism for natural selection to tune the noisiness of gene expression.
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Affiliation(s)
- Kaiser Loell
- Department of Genetics, Washington University School of Medicine in St. Louis, St. Louis, MO 63108, USA,The Edison Family Center for Genome Sciences & Systems Biology, Washington University School of Medicine in St. Louis, St. Louis, MO 63108, USA
| | - Yawei Wu
- Department of Genetics, Washington University School of Medicine in St. Louis, St. Louis, MO 63108, USA,The Edison Family Center for Genome Sciences & Systems Biology, Washington University School of Medicine in St. Louis, St. Louis, MO 63108, USA
| | - Max V. Staller
- Center for Computational Biology, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Barak Cohen
- Department of Genetics, Washington University School of Medicine in St. Louis, St. Louis, MO 63108, USA; The Edison Family Center for Genome Sciences & Systems Biology, Washington University School of Medicine in St. Louis, St. Louis, MO 63108, USA.
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31
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Zreika S, Fourneaux C, Vallin E, Modolo L, Seraphin R, Moussy A, Ventre E, Bouvier M, Ozier-Lafontaine A, Bonnaffoux A, Picard F, Gandrillon O, Gonin-Giraud S. Evidence for close molecular proximity between reverting and undifferentiated cells. BMC Biol 2022; 20:155. [PMID: 35794592 PMCID: PMC9258043 DOI: 10.1186/s12915-022-01363-7] [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] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2022] [Accepted: 06/27/2022] [Indexed: 11/28/2022] Open
Abstract
BACKGROUND According to Waddington's epigenetic landscape concept, the differentiation process can be illustrated by a cell akin to a ball rolling down from the top of a hill (proliferation state) and crossing furrows before stopping in basins or "attractor states" to reach its stable differentiated state. However, it is now clear that some committed cells can retain a certain degree of plasticity and reacquire phenotypical characteristics of a more pluripotent cell state. In line with this dynamic model, we have previously shown that differentiating cells (chicken erythrocytic progenitors (T2EC)) retain for 24 h the ability to self-renew when transferred back in self-renewal conditions. Despite those intriguing and promising results, the underlying molecular state of those "reverting" cells remains unexplored. The aim of the present study was therefore to molecularly characterize the T2EC reversion process by combining advanced statistical tools to make the most of single-cell transcriptomic data. For this purpose, T2EC, initially maintained in a self-renewal medium (0H), were induced to differentiate for 24H (24H differentiating cells); then, a part of these cells was transferred back to the self-renewal medium (48H reverting cells) and the other part was maintained in the differentiation medium for another 24H (48H differentiating cells). For each time point, cell transcriptomes were generated using scRT-qPCR and scRNAseq. RESULTS Our results showed a strong overlap between 0H and 48H reverting cells when applying dimensional reduction. Moreover, the statistical comparison of cell distributions and differential expression analysis indicated no significant differences between these two cell groups. Interestingly, gene pattern distributions highlighted that, while 48H reverting cells have gene expression pattern more similar to 0H cells, they are not completely identical, which suggest that for some genes a longer delay may be required for the cells to fully recover. Finally, sparse PLS (sparse partial least square) analysis showed that only the expression of 3 genes discriminates 48H reverting and 0H cells. CONCLUSIONS Altogether, we show that reverting cells return to an earlier molecular state almost identical to undifferentiated cells and demonstrate a previously undocumented physiological and molecular plasticity during the differentiation process, which most likely results from the dynamic behavior of the underlying molecular network.
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Affiliation(s)
- Souad Zreika
- Laboratory of Biology and Modelling of the Cell, Université de Lyon, Ecole Normale Supérieure de Lyon, CNRS, UMR5239, Université Claude Bernard Lyon 1, Lyon, France
- Azm Center for Research in Biotechnology and its Applications, LBA3B, EDST, Lebanese University, Tripoli, 1300, Lebanon
| | - Camille Fourneaux
- Laboratory of Biology and Modelling of the Cell, Université de Lyon, Ecole Normale Supérieure de Lyon, CNRS, UMR5239, Université Claude Bernard Lyon 1, Lyon, France
| | - Elodie Vallin
- Laboratory of Biology and Modelling of the Cell, Université de Lyon, Ecole Normale Supérieure de Lyon, CNRS, UMR5239, Université Claude Bernard Lyon 1, Lyon, France
| | - Laurent Modolo
- Laboratory of Biology and Modelling of the Cell, Université de Lyon, Ecole Normale Supérieure de Lyon, CNRS, UMR5239, Université Claude Bernard Lyon 1, Lyon, France
| | - Rémi Seraphin
- Laboratory of Biology and Modelling of the Cell, Université de Lyon, Ecole Normale Supérieure de Lyon, CNRS, UMR5239, Université Claude Bernard Lyon 1, Lyon, France
| | - Alice Moussy
- Ecole Pratique des Hautes Etudes, PSL Research University, UMRS951, INSERM, Univ-Evry, Paris, France
| | - Elias Ventre
- Laboratory of Biology and Modelling of the Cell, Université de Lyon, Ecole Normale Supérieure de Lyon, CNRS, UMR5239, Université Claude Bernard Lyon 1, Lyon, France
- Inria Team Dracula, Inria Center Grenoble Rhone-Alpes, Grenoble, France
- Institut Camille Jordan, CNRS UMR 5208, Université Claude Bernard Lyon 1, Villeurbanne, France
| | - Matteo Bouvier
- Laboratory of Biology and Modelling of the Cell, Université de Lyon, Ecole Normale Supérieure de Lyon, CNRS, UMR5239, Université Claude Bernard Lyon 1, Lyon, France
- Vidium solutions, Lyon, France
| | - Anthony Ozier-Lafontaine
- Nantes Université, Centrale Nantes, Laboratoire de mathématiques Jean Leray, LMJL, F-44000, Nantes, France
| | - Arnaud Bonnaffoux
- Laboratory of Biology and Modelling of the Cell, Université de Lyon, Ecole Normale Supérieure de Lyon, CNRS, UMR5239, Université Claude Bernard Lyon 1, Lyon, France
- Vidium solutions, Lyon, France
| | - Franck Picard
- Laboratory of Biology and Modelling of the Cell, Université de Lyon, Ecole Normale Supérieure de Lyon, CNRS, UMR5239, Université Claude Bernard Lyon 1, Lyon, France
| | - Olivier Gandrillon
- Laboratory of Biology and Modelling of the Cell, Université de Lyon, Ecole Normale Supérieure de Lyon, CNRS, UMR5239, Université Claude Bernard Lyon 1, Lyon, France
- Inria Team Dracula, Inria Center Grenoble Rhone-Alpes, Grenoble, France
| | - Sandrine Gonin-Giraud
- Laboratory of Biology and Modelling of the Cell, Université de Lyon, Ecole Normale Supérieure de Lyon, CNRS, UMR5239, Université Claude Bernard Lyon 1, Lyon, France.
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32
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Capolupo L, Khven I, Lederer AR, Mazzeo L, Glousker G, Ho S, Russo F, Montoya JP, Bhandari DR, Bowman AP, Ellis SR, Guiet R, Burri O, Detzner J, Muthing J, Homicsko K, Kuonen F, Gilliet M, Spengler B, Heeren RMA, Dotto GP, La Manno G, D'Angelo G. Sphingolipids control dermal fibroblast heterogeneity. Science 2022; 376:eabh1623. [PMID: 35420948 DOI: 10.1126/science.abh1623] [Citation(s) in RCA: 64] [Impact Index Per Article: 32.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
Human cells produce thousands of lipids that change during cell differentiation and can vary across individual cells of the same type. However, we are only starting to characterize the function of these cell-to-cell differences in lipid composition. Here, we measured the lipidomes and transcriptomes of individual human dermal fibroblasts by coupling high-resolution mass spectrometry imaging with single-cell transcriptomics. We found that the cell-to-cell variations of specific lipid metabolic pathways contribute to the establishment of cell states involved in the organization of skin architecture. Sphingolipid composition is shown to define fibroblast subpopulations, with sphingolipid metabolic rewiring driving cell-state transitions. Therefore, cell-to-cell lipid heterogeneity affects the determination of cell states, adding a new regulatory component to the self-organization of multicellular systems.
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Affiliation(s)
- Laura Capolupo
- Interfaculty Institute of Bioengineering and Global Health Institute, École Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland
| | - Irina Khven
- Brain Mind Institute, Faculty of Life Sciences, École Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland
| | - Alex R Lederer
- Brain Mind Institute, Faculty of Life Sciences, École Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland
| | - Luigi Mazzeo
- Department of Biochemistry, University of Lausanne, CH-1066 Epalinges, Switzerland
| | - Galina Glousker
- School of Life Sciences, Swiss Institute for Experimental Cancer Research, École Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland
| | - Sylvia Ho
- Interfaculty Institute of Bioengineering and Global Health Institute, École Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland
| | - Francesco Russo
- Institute of Biochemistry and Cellular Biology, National Research Council of Italy, 80131 Napoli, Italy
| | - Jonathan Paz Montoya
- Interfaculty Institute of Bioengineering and Global Health Institute, École Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland
| | - Dhaka R Bhandari
- Institute for Inorganic and Analytical Chemistry, Justus Liebig University Giessen, 35392 Giessen, Germany
| | - Andrew P Bowman
- Maastricht MultiModal Molecular Imaging Institute, Division of Imaging Mass Spectrometry, Maastricht University, 6629 ER Maastricht, Netherlands
| | - Shane R Ellis
- Maastricht MultiModal Molecular Imaging Institute, Division of Imaging Mass Spectrometry, Maastricht University, 6629 ER Maastricht, Netherlands.,Molecular Horizons and School of Chemistry and Molecular Bioscience, University of Wollongong, Wollongong, New South Wales 2522, Australia.,Illawarra Health and Medical Research Institute, Wollongong, New South Wales 2522, Australia
| | - Romain Guiet
- Faculté des Sciences de la Vie, Bioimaging and Optics Platform, École Polytechnique Fédérale de Lausanne, Lausanne, CH-1015 Vaud, Switzerland
| | - Olivier Burri
- Faculté des Sciences de la Vie, Bioimaging and Optics Platform, École Polytechnique Fédérale de Lausanne, Lausanne, CH-1015 Vaud, Switzerland
| | - Johanna Detzner
- Institute of Hygiene, University of Münster, D-48149 Münster, Germany
| | - Johannes Muthing
- Institute of Hygiene, University of Münster, D-48149 Münster, Germany
| | - Krisztian Homicsko
- Department of Oncology, Centre Hospitalier Universitaire Vaudois, CH-1011 Lausanne, Switzerland.,Swiss Cancer Center Leman, CH-1015 Lausanne, Switzerland.,The Ludwig Institute for Cancer Research, Lausanne Branch, CH-1066 Epalinges, Switzerland
| | - François Kuonen
- Département de Dermatologie et Vénéréologie, Centre Hospitalier Universitaire Vaudois, CH-1011 Lausanne, Switzerland
| | - Michel Gilliet
- Département de Dermatologie et Vénéréologie, Centre Hospitalier Universitaire Vaudois, CH-1011 Lausanne, Switzerland
| | - Bernhard Spengler
- Institute for Inorganic and Analytical Chemistry, Justus Liebig University Giessen, 35392 Giessen, Germany
| | - Ron M A Heeren
- Maastricht MultiModal Molecular Imaging Institute, Division of Imaging Mass Spectrometry, Maastricht University, 6629 ER Maastricht, Netherlands
| | - G Paolo Dotto
- Personalized Cancer Prevention Research Unit, Head and Neck Surgery Division, Centre Hospitalier Universitaire Vaudois, CH-1011 Lausanne, Switzerland.,Department of Biochemistry, University of Lausanne, CH-1066 Epalinges, Switzerland.,Cutaneous Biology Research Center, Massachusetts General Hospital, Charlestown, MA 02129, USA
| | - Gioele La Manno
- Brain Mind Institute, Faculty of Life Sciences, École Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland
| | - Giovanni D'Angelo
- Interfaculty Institute of Bioengineering and Global Health Institute, École Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland.,Institute of Biochemistry and Cellular Biology, National Research Council of Italy, 80131 Napoli, Italy
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Hematopoietic differentiation is characterized by a transient peak of entropy at a single-cell level. BMC Biol 2022; 20:60. [PMID: 35260165 PMCID: PMC8905725 DOI: 10.1186/s12915-022-01264-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2021] [Accepted: 02/22/2022] [Indexed: 12/11/2022] Open
Abstract
Background Mature blood cells arise from hematopoietic stem cells in the bone marrow by a process of differentiation along one of several different lineage trajectories. This is often represented as a series of discrete steps of increasing progenitor cell commitment to a given lineage, but as for differentiation in general, whether the process is instructive or stochastic remains controversial. Here, we examine this question by analyzing single-cell transcriptomic data from human bone marrow cells, assessing cell-to-cell variability along the trajectories of hematopoietic differentiation into four different types of mature blood cells. The instructive model predicts that cells will be following the same sequence of instructions and that there will be minimal variability of gene expression between them throughout the process, while the stochastic model predicts a role for cell-to-cell variability when lineage commitments are being made. Results Applying Shannon entropy to measure cell-to-cell variability among human hematopoietic bone marrow cells at the same stage of differentiation, we observed a transient peak of gene expression variability occurring at characteristic points in all hematopoietic differentiation pathways. Strikingly, the genes whose cell-to-cell variation of expression fluctuated the most over the course of a given differentiation trajectory are pathway-specific genes, whereas genes which showed the greatest variation of mean expression are common to all pathways. Finally, we showed that the level of cell-to-cell variation is increased in the most immature compartment of hematopoiesis in myelodysplastic syndromes. Conclusions These data suggest that human hematopoietic differentiation could be better conceptualized as a dynamical stochastic process with a transient stage of cellular indetermination, and strongly support the stochastic view of differentiation. They also highlight the need to consider the role of stochastic gene expression in complex physiological processes and pathologies such as cancers, paving the way for possible noise-based therapies through epigenetic regulation. Supplementary Information The online version contains supplementary material available at 10.1186/s12915-022-01264-9.
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Topolewski P, Zakrzewska KE, Walczak J, Nienałtowski K, Müller-Newen G, Singh A, Komorowski M. Phenotypic variability, not noise, accounts for most of the cell-to-cell heterogeneity in IFN-γ and oncostatin M signaling responses. Sci Signal 2022; 15:eabd9303. [PMID: 35167339 DOI: 10.1126/scisignal.abd9303] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
Cellular signaling responses show substantial cell-to-cell heterogeneity, which is often ascribed to the inherent randomness of biochemical reactions, termed molecular noise, wherein high noise implies low signaling fidelity. Alternatively, heterogeneity could arise from differences in molecular content between cells, termed molecular phenotypic variability, which does not necessarily imply imprecise signaling. The contribution of these two processes to signaling heterogeneity is unclear. Here, we fused fibroblasts to produce binuclear syncytia to distinguish noise from phenotypic variability in the analysis of cytokine signaling. We reasoned that the responses of the two nuclei within one syncytium could approximate the signaling outcomes of two cells with the same molecular content, thereby disclosing noise contribution, whereas comparison of different syncytia should reveal contribution of phenotypic variability. We found that ~90% of the variance in the primary response (which was the abundance of phosphorylated, nuclear STAT) to stimulation with the cytokines interferon-γ and oncostatin M resulted from differences in the molecular content of individual cells. Thus, our data reveal that cytokine signaling in the system used here operates in a reproducible, high-fidelity manner.
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Affiliation(s)
- Piotr Topolewski
- Institute of Fundamental Technological Research, Polish Academy of Sciences, 02-106 Warsaw, Poland
| | - Karolina E Zakrzewska
- Institute of Fundamental Technological Research, Polish Academy of Sciences, 02-106 Warsaw, Poland
| | - Jarosław Walczak
- Institute of Fundamental Technological Research, Polish Academy of Sciences, 02-106 Warsaw, Poland
| | - Karol Nienałtowski
- Institute of Fundamental Technological Research, Polish Academy of Sciences, 02-106 Warsaw, Poland
| | - Gerhard Müller-Newen
- Institute of Biochemistry and Molecular Biology, RWTH Aachen University, 52074 Aachen, Germany
| | - Abhyudai Singh
- Department of Electrical and Computer Engineering, University of Delaware, Newark, DE 19716, USA
| | - Michał Komorowski
- Institute of Fundamental Technological Research, Polish Academy of Sciences, 02-106 Warsaw, Poland
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35
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Olfactory receptor choice: a case study for gene regulation in a multi-enhancer system. Curr Opin Genet Dev 2021; 72:101-109. [PMID: 34896807 DOI: 10.1016/j.gde.2021.11.003] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2021] [Revised: 10/25/2021] [Accepted: 11/11/2021] [Indexed: 12/14/2022]
Abstract
The mammalian genome possesses >2000 olfactory receptor (OR) alleles regulated by 63 known OR-Enhancer elements, yet each olfactory sensory neuron (OSN) expresses only a single OR allele. Choreographed changes to OSN nuclear architecture are evidently necessary for OR expression. Additionally, the insulated organization of OR-enhancers around an OR allele is a hallmark of the chosen OR. However, the biology guiding OR choice itself is unclear. Innovations in single-cell and biophysics-based analysis of nuclear architecture are revising previous models of the nucleus to include its dynamic and probabilistic nature. In this review, we ground current knowledge of OR gene regulation in these emerging theories to speculate on mechanisms that may give rise to diverse and singular OR expression.
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36
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Petelski AA, Emmott E, Leduc A, Huffman RG, Specht H, Perlman DH, Slavov N. Multiplexed single-cell proteomics using SCoPE2. Nat Protoc 2021; 16:5398-5425. [PMID: 34716448 PMCID: PMC8643348 DOI: 10.1038/s41596-021-00616-z] [Citation(s) in RCA: 109] [Impact Index Per Article: 36.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2021] [Accepted: 08/12/2021] [Indexed: 11/09/2022]
Abstract
Many biological systems are composed of diverse single cells. This diversity necessitates functional and molecular single-cell analysis. Single-cell protein analysis has long relied on affinity reagents, but emerging mass-spectrometry methods (either label-free or multiplexed) have enabled quantifying >1,000 proteins per cell while simultaneously increasing the specificity of protein quantification. Here we describe the Single Cell ProtEomics (SCoPE2) protocol, which uses an isobaric carrier to enhance peptide sequence identification. Single cells are isolated by FACS or CellenONE into multiwell plates and lysed by Minimal ProteOmic sample Preparation (mPOP), and their peptides labeled by isobaric mass tags (TMT or TMTpro) for multiplexed analysis. SCoPE2 affords a cost-effective single-cell protein quantification that can be fully automated using widely available equipment and scaled to thousands of single cells. SCoPE2 uses inexpensive reagents and is applicable to any sample that can be processed to a single-cell suspension. The SCoPE2 workflow allows analyzing ~200 single cells per 24 h using only standard commercial equipment. We emphasize experimental steps and benchmarks required for achieving quantitative protein analysis.
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Affiliation(s)
- Aleksandra A Petelski
- Department of Bioengineering, Northeastern University, Boston, MA, USA
- Barnett Institute, Northeastern University, Boston, MA, USA
| | - Edward Emmott
- Department of Bioengineering, Northeastern University, Boston, MA, USA
- Barnett Institute, Northeastern University, Boston, MA, USA
- Centre for Proteome Research, Department of Biochemistry & Systems Biology, University of Liverpool, Liverpool, UK
| | - Andrew Leduc
- Department of Bioengineering, Northeastern University, Boston, MA, USA
- Barnett Institute, Northeastern University, Boston, MA, USA
| | - R Gray Huffman
- Department of Bioengineering, Northeastern University, Boston, MA, USA
- Barnett Institute, Northeastern University, Boston, MA, USA
| | - Harrison Specht
- Department of Bioengineering, Northeastern University, Boston, MA, USA
- Barnett Institute, Northeastern University, Boston, MA, USA
| | - David H Perlman
- Department of Bioengineering, Northeastern University, Boston, MA, USA
- Merck Exploratory Sciences Center, Merck Sharp & Dohme Corp., Cambridge, MA, USA
| | - Nikolai Slavov
- Department of Bioengineering, Northeastern University, Boston, MA, USA.
- Barnett Institute, Northeastern University, Boston, MA, USA.
- Department of Biology, Northeastern University, Boston, MA, USA.
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37
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Abstract
To predict transcription, one needs a mechanistic understanding of how the numerous required transcription factors (TFs) explore the nuclear space to find their target genes, assemble, cooperate, and compete with one another. Advances in fluorescence microscopy have made it possible to visualize real-time TF dynamics in living cells, leading to two intriguing observations: first, most TFs contact chromatin only transiently; and second, TFs can assemble into clusters through their intrinsically disordered regions. These findings suggest that highly dynamic events and spatially structured nuclear microenvironments might play key roles in transcription regulation that are not yet fully understood. The emerging model is that while some promoters directly convert TF-binding events into on/off cycles of transcription, many others apply complex regulatory layers that ultimately lead to diverse phenotypic outputs. Cracking this kinetic code is an ongoing and challenging task that is made possible by combining innovative imaging approaches with biophysical models.
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Affiliation(s)
- Feiyue Lu
- Institute for Systems Genetics and Cell Biology Department, NYU School of Medicine, New York, New York 10016, USA
| | - Timothée Lionnet
- Institute for Systems Genetics and Cell Biology Department, NYU School of Medicine, New York, New York 10016, USA
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38
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Abstract
Nuclei are central hubs for information processing in eukaryotic cells. The need to fit large genomes into small nuclei imposes severe restrictions on genome organization and the mechanisms that drive genome-wide regulatory processes. How a disordered polymer such as chromatin, which has vast heterogeneity in its DNA and histone modification profiles, folds into discernibly consistent patterns is a fundamental question in biology. Outstanding questions include how genomes are spatially and temporally organized to regulate cellular processes with high precision and whether genome organization is causally linked to transcription regulation. The advent of next-generation sequencing, super-resolution imaging, multiplexed fluorescent in situ hybridization, and single-molecule imaging in individual living cells has caused a resurgence in efforts to understand the spatiotemporal organization of the genome. In this review, we discuss structural and mechanistic properties of genome organization at different length scales and examine changes in higher-order chromatin organization during important developmental transitions.
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Affiliation(s)
- Rajarshi P Ghosh
- Department of Molecular and Cell Biology and Howard Hughes Medical Institute, University of California, Berkeley, California 94720, USA; ,
| | - Barbara J Meyer
- Department of Molecular and Cell Biology and Howard Hughes Medical Institute, University of California, Berkeley, California 94720, USA; ,
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39
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Cao Y, Tian R, Lv X, Li J, Liu L, Du G, Chen J, Liu Y. Inducible Population Quality Control of Engineered Bacillus subtilis for Improved N-Acetylneuraminic Acid Biosynthesis. ACS Synth Biol 2021; 10:2197-2209. [PMID: 34404207 DOI: 10.1021/acssynbio.1c00086] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
Biosynthesis by microorganisms using renewable feedstocks is an important approach for realizing sustainable chemical manufacturing. However, cell-to-cell variation in biosynthesis capability during fermentation restricts the robustness and efficiency of bioproduction, hampering the industrialization of biosynthesis. Herein, we developed an inducible population quality control system (iPopQC) for dynamically modulating the producing and nonproducing subpopulations of engineered Bacillus subtilis, which was constructed via inducible promoter- and metabolite-responsive biosensor-based genetic circuit for regulating essential genes. Moreover, iPopQC achieved a 1.97-fold increase in N-acetylneuraminic acid (NeuAc) titer by enriching producing cell subpopulation during cultivation, representing 52% higher than that of previous PopQC. Strains with double-output iPopQC cocoupling the expression of double essential genes with NeuAc production improved production robustness further, retaining NeuAc production throughout 96 h of fermentation, upon which the strains cocoupling one essential gene expression with NeuAc production abolished the production ability.
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Affiliation(s)
- Yanting Cao
- Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, Jiangnan University, Wuxi, 214122, China
- Science Center for Future Foods, Jiangnan University, Wuxi, 214122, China
| | - Rongzhen Tian
- Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, Jiangnan University, Wuxi, 214122, China
- Science Center for Future Foods, Jiangnan University, Wuxi, 214122, China
| | - Xueqin Lv
- Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, Jiangnan University, Wuxi, 214122, China
- Science Center for Future Foods, Jiangnan University, Wuxi, 214122, China
| | - Jianghua Li
- Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, Jiangnan University, Wuxi, 214122, China
- Science Center for Future Foods, Jiangnan University, Wuxi, 214122, China
| | - Long Liu
- Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, Jiangnan University, Wuxi, 214122, China
- Science Center for Future Foods, Jiangnan University, Wuxi, 214122, China
| | - Guocheng Du
- Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, Jiangnan University, Wuxi, 214122, China
- Science Center for Future Foods, Jiangnan University, Wuxi, 214122, China
| | - Jian Chen
- Science Center for Future Foods, Jiangnan University, Wuxi, 214122, China
- National Engineering Laboratory for Cereal Fermentation Technology, Jiangnan University, Wuxi, 214122, China
| | - Yanfeng Liu
- Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, Jiangnan University, Wuxi, 214122, China
- Science Center for Future Foods, Jiangnan University, Wuxi, 214122, China
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40
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Joober R, Karama S. Randomness and nondeterminism: from genes to free will with implications for psychiatry. J Psychiatry Neurosci 2021; 46:E500-E505. [PMID: 34415691 PMCID: PMC8410475 DOI: 10.1503/jpn.210141] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Affiliation(s)
- Ridha Joober
- From the Department of Psychiatry, McGill University, Montreal, Que., Canada (Joober, Karama); and the Douglas Hospital Research Centre, Montreal, Que., Canada (Joober, Karama)
| | - Sherif Karama
- From the Department of Psychiatry, McGill University, Montreal, Que., Canada (Joober, Karama); and the Douglas Hospital Research Centre, Montreal, Que., Canada (Joober, Karama)
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41
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The mechanics and dynamics of cancer cells sensing noisy 3D contact guidance. Proc Natl Acad Sci U S A 2021; 118:2024780118. [PMID: 33658384 DOI: 10.1073/pnas.2024780118] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Contact guidance is a major physical cue that modulates cancer cell morphology and motility, and is directly linked to the prognosis of cancer patients. Under physiological conditions, particularly in the three-dimensional (3D) extracellular matrix (ECM), the disordered assembly of fibers presents a complex directional bias to the cells. It is unclear how cancer cells respond to these noncoherent contact guidance cues. Here we combine quantitative experiments, theoretical analysis, and computational modeling to study the morphological and migrational responses of breast cancer cells to 3D collagen ECM with varying degrees of fiber alignment. We quantify the strength of contact guidance using directional coherence of ECM fibers, and find that stronger contact guidance causes cells to polarize more strongly along the principal direction of the fibers. Interestingly, sensitivity to contact guidance is positively correlated with cell aspect ratio, with elongated cells responding more strongly to ECM alignment than rounded cells. Both experiments and simulations show that cell-ECM adhesions and actomyosin contractility modulate cell responses to contact guidance by inducing a population shift between rounded and elongated cells. We also find that cells rapidly change their morphology when navigating the ECM, and that ECM fiber coherence modulates cell transition rates between different morphological phenotypes. Taken together, we find that subcellular processes that integrate conflicting mechanical cues determine cell morphology, which predicts the polarization and migration dynamics of cancer cells in 3D ECM.
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42
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Wadkin LE, Orozco-Fuentes S, Neganova I, Lako M, Parker NG, Shukurov A. A mathematical modelling framework for the regulation of intra-cellular OCT4 in human pluripotent stem cells. PLoS One 2021; 16:e0254991. [PMID: 34347824 PMCID: PMC8336844 DOI: 10.1371/journal.pone.0254991] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2021] [Accepted: 07/07/2021] [Indexed: 12/04/2022] Open
Abstract
Human pluripotent stem cells (hPSCs) have the potential to differentiate into all cell types, a property known as pluripotency. A deeper understanding of how pluripotency is regulated is required to assist in controlling pluripotency and differentiation trajectories experimentally. Mathematical modelling provides a non-invasive tool through which to explore, characterise and replicate the regulation of pluripotency and the consequences on cell fate. Here we use experimental data of the expression of the pluripotency transcription factor OCT4 in a growing hPSC colony to develop and evaluate mathematical models for temporal pluripotency regulation. We consider fractional Brownian motion and the stochastic logistic equation and explore the effects of both additive and multiplicative noise. We illustrate the use of time-dependent carrying capacities and the introduction of Allee effects to the stochastic logistic equation to describe cell differentiation. We conclude both methods adequately capture the decline in OCT4 upon differentiation, but the Allee effect model has the advantage of allowing differentiation to occur stochastically in a sub-set of cells. This mathematical framework for describing intra-cellular OCT4 regulation can be extended to other transcription factors and developed into predictive models.
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Affiliation(s)
- L E Wadkin
- School of Mathematics, Statistics and Physics, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - S Orozco-Fuentes
- Department of Mathematics, Physics and Electrical Engineering, Northumbria University, Newcastle upon Tyne, United Kingdom
| | - I Neganova
- Institute of Cytology, RAS St Petersburg, Novosibirsk, Russia
| | - M Lako
- Bioscience Institute, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - N G Parker
- School of Mathematics, Statistics and Physics, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - A Shukurov
- School of Mathematics, Statistics and Physics, Newcastle University, Newcastle upon Tyne, United Kingdom
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43
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Nienałtowski K, Rigby RE, Walczak J, Zakrzewska KE, Głów E, Rehwinkel J, Komorowski M. Fractional response analysis reveals logarithmic cytokine responses in cellular populations. Nat Commun 2021; 12:4175. [PMID: 34234126 PMCID: PMC8263596 DOI: 10.1038/s41467-021-24449-2] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2020] [Accepted: 06/17/2021] [Indexed: 01/10/2023] Open
Abstract
Although we can now measure single-cell signaling responses with multivariate, high-throughput techniques our ability to interpret such measurements is still limited. Even interpretation of dose–response based on single-cell data is not straightforward: signaling responses can differ significantly between cells, encompass multiple signaling effectors, and have dynamic character. Here, we use probabilistic modeling and information-theory to introduce fractional response analysis (FRA), which quantifies changes in fractions of cells with given response levels. FRA can be universally performed for heterogeneous, multivariate, and dynamic measurements and, as we demonstrate, quantifies otherwise hidden patterns in single-cell data. In particular, we show that fractional responses to type I interferon in human peripheral blood mononuclear cells are very similar across different cell types, despite significant differences in mean or median responses and degrees of cell-to-cell heterogeneity. Further, we demonstrate that fractional responses to cytokines scale linearly with the log of the cytokine dose, which uncovers that heterogeneous cellular populations are sensitive to fold-changes in the dose, as opposed to additive changes. Our ability to interpret single-cell multivariate signaling responses is still limited. Here the authors introduce fractional response analysis (FRA), involving fractional cell counting, capable of deconvoluting heterogeneous multivariate responses of cellular populations.
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Affiliation(s)
- Karol Nienałtowski
- Institute of Fundamental Technological Research, Polish Academy of Sciences, Warsaw, Poland
| | - Rachel E Rigby
- Medical Research Council Human Immunology Unit, Medical Research Council Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Jarosław Walczak
- Institute of Fundamental Technological Research, Polish Academy of Sciences, Warsaw, Poland
| | - Karolina E Zakrzewska
- Institute of Fundamental Technological Research, Polish Academy of Sciences, Warsaw, Poland
| | - Edyta Głów
- Institute of Fundamental Technological Research, Polish Academy of Sciences, Warsaw, Poland
| | - Jan Rehwinkel
- Medical Research Council Human Immunology Unit, Medical Research Council Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Michał Komorowski
- Institute of Fundamental Technological Research, Polish Academy of Sciences, Warsaw, Poland.
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44
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Luzak V, López-Escobar L, Siegel TN, Figueiredo LM. Cell-to-Cell Heterogeneity in Trypanosomes. Annu Rev Microbiol 2021; 75:107-128. [PMID: 34228491 DOI: 10.1146/annurev-micro-040821-012953] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Recent developments in single-cell and single-molecule techniques have revealed surprising levels of heterogeneity among isogenic cells. These advances have transformed the study of cell-to-cell heterogeneity into a major area of biomedical research, revealing that it can confer essential advantages, such as priming populations of unicellular organisms for future environmental stresses. Protozoan parasites, such as trypanosomes, face multiple and often hostile environments, and to survive, they undergo multiple changes, including changes in morphology, gene expression, and metabolism. But why does only a subset of proliferative cells differentiate to the next life cycle stage? Why do only some bloodstream parasites undergo antigenic switching while others stably express one variant surface glycoprotein? And why do some parasites invade an organ while others remain in the bloodstream? Building on extensive research performed in bacteria, here we suggest that biological noise can contribute to the fitness of eukaryotic pathogens and discuss the importance of cell-to-cell heterogeneity in trypanosome infections. Expected final online publication date for the Annual Review of Microbiology, Volume 75 is October 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
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Affiliation(s)
- Vanessa Luzak
- Division of Experimental Parasitology, Faculty of Veterinary Medicine, Ludwig-Maximilians-Universität München, Munich 82152, Germany.,Biomedical Center, Division of Physiological Chemistry, Faculty of Medicine, Ludwig-Maximilians-Universität München, Munich 82152, Germany
| | - Lara López-Escobar
- Instituto de Medicina Molecular João Lobo Antunes, Faculdade de Medicina, Universidade de Lisboa, 1649-028 Lisboa, Portugal;
| | - T Nicolai Siegel
- Division of Experimental Parasitology, Faculty of Veterinary Medicine, Ludwig-Maximilians-Universität München, Munich 82152, Germany.,Biomedical Center, Division of Physiological Chemistry, Faculty of Medicine, Ludwig-Maximilians-Universität München, Munich 82152, Germany
| | - Luisa M Figueiredo
- Instituto de Medicina Molecular João Lobo Antunes, Faculdade de Medicina, Universidade de Lisboa, 1649-028 Lisboa, Portugal;
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45
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Emert BL, Cote CJ, Torre EA, Dardani IP, Jiang CL, Jain N, Shaffer SM, Raj A. Variability within rare cell states enables multiple paths toward drug resistance. Nat Biotechnol 2021; 39:865-876. [PMID: 33619394 PMCID: PMC8277666 DOI: 10.1038/s41587-021-00837-3] [Citation(s) in RCA: 75] [Impact Index Per Article: 25.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2020] [Accepted: 01/18/2021] [Indexed: 01/07/2023]
Abstract
Molecular differences between individual cells can lead to dramatic differences in cell fate, such as death versus survival of cancer cells upon drug treatment. These originating differences remain largely hidden due to difficulties in determining precisely what variable molecular features lead to which cellular fates. Thus, we developed Rewind, a methodology that combines genetic barcoding with RNA fluorescence in situ hybridization to directly capture rare cells that give rise to cellular behaviors of interest. Applying Rewind to BRAFV600E melanoma, we trace drug-resistant cell fates back to single-cell gene expression differences in their drug-naive precursors (initial frequency of ~1:1,000-1:10,000 cells) and relative persistence of MAP kinase signaling soon after drug treatment. Within this rare subpopulation, we uncover a rich substructure in which molecular differences among several distinct subpopulations predict future differences in phenotypic behavior, such as proliferative capacity of distinct resistant clones after drug treatment. Our results reveal hidden, rare-cell variability that underlies a range of latent phenotypic outcomes upon drug exposure.
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Affiliation(s)
- Benjamin L Emert
- Genomics and Computational Biology Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Christopher J Cote
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA, USA
| | - Eduardo A Torre
- Biochemistry and Molecular Biophysics Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Ian P Dardani
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA, USA
| | - Connie L Jiang
- Genetics and Epigenetics, Cell and Molecular Biology Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Naveen Jain
- Genetics and Epigenetics, Cell and Molecular Biology Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Sydney M Shaffer
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA, USA
- Department of Pathology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Cancer Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Arjun Raj
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA, USA.
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46
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Jouffrey V, Leonard AS, Ahnert SE. Gene duplication and subsequent diversification strongly affect phenotypic evolvability and robustness. ROYAL SOCIETY OPEN SCIENCE 2021; 8:201636. [PMID: 34168886 PMCID: PMC8220273 DOI: 10.1098/rsos.201636] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/12/2020] [Accepted: 03/17/2021] [Indexed: 06/13/2023]
Abstract
We study the effects of non-determinism and gene duplication on the structure of genotype-phenotype (GP) maps by introducing a non-deterministic version of the Polyomino self-assembly model. This model has previously been used in a variety of contexts to model the assembly and evolution of protein quaternary structure. Firstly, we show the limit of the current deterministic paradigm which leads to built-in anti-correlation between evolvability and robustness at the genotypic level. We develop a set of metrics to measure structural properties of GP maps in a non-deterministic setting and use them to evaluate the effects of gene duplication and subsequent diversification. Our generalized versions of evolvability and robustness exhibit positive correlation for a subset of genotypes. This positive correlation is only possible because non-deterministic phenotypes can contribute to both robustness and evolvability. Secondly, we show that duplication increases robustness and reduces evolvability initially, but that the subsequent diversification that duplication enables has a stronger, inverse effect, greatly increasing evolvability and reducing robustness relative to their original values.
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Affiliation(s)
- V. Jouffrey
- Cavendish Laboratory, University of Cambridge, JJ Thomson Avenue, Cambridge CB3 0HE, UK
- Sainsbury Laboratory, University of Cambridge, Bateman Street, Cambridge CB2 1LR, UK
| | - A. S. Leonard
- Cavendish Laboratory, University of Cambridge, JJ Thomson Avenue, Cambridge CB3 0HE, UK
- Sainsbury Laboratory, University of Cambridge, Bateman Street, Cambridge CB2 1LR, UK
| | - S. E. Ahnert
- Cavendish Laboratory, University of Cambridge, JJ Thomson Avenue, Cambridge CB3 0HE, UK
- Sainsbury Laboratory, University of Cambridge, Bateman Street, Cambridge CB2 1LR, UK
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Stein-O'Brien GL, Ainsile MC, Fertig EJ. Forecasting cellular states: from descriptive to predictive biology via single-cell multiomics. CURRENT OPINION IN SYSTEMS BIOLOGY 2021; 26:24-32. [PMID: 34660940 PMCID: PMC8516130 DOI: 10.1016/j.coisb.2021.03.008] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
As the single cell field races to characterize each cell type, state, and behavior, the complexity of the computational analysis approaches the complexity of the biological systems. Single cell and imaging technologies now enable unprecedented measurements of state transitions in biological systems, providing high-throughput data that capture tens-of-thousands of measurements on hundreds-of-thousands of samples. Thus, the definition of cell type and state is evolving to encompass the broad range of biological questions now attainable. To answer these questions requires the development of computational tools for integrated multi-omics analysis. Merged with mathematical models, these algorithms will be able to forecast future states of biological systems, going from statistical inferences of phenotypes to time course predictions of the biological systems with dynamic maps analogous to weather systems. Thus, systems biology for forecasting biological system dynamics from multi-omic data represents the future of cell biology empowering a new generation of technology-driven predictive medicine.
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Affiliation(s)
- Genevieve L Stein-O'Brien
- Department of Oncology, Division of Biostatistics and Bioinformatics, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins School of Medicine, Baltimore, MD
- Department of Neuroscience, Johns Hopkins School of Medicine, Baltimore, MD
- McKusick-Nathans Department of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore, MD
- Kavli Neuroscience Discovery Institute, Johns Hopkins University, Baltimore, MD
- Convergence Institute, Johns Hopkins University, Baltimore, MD
| | - Michaela C Ainsile
- Department of Oncology, Division of Biostatistics and Bioinformatics, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins School of Medicine, Baltimore, MD
| | - Elana J Fertig
- Department of Oncology, Division of Biostatistics and Bioinformatics, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins School of Medicine, Baltimore, MD
- Convergence Institute, Johns Hopkins University, Baltimore, MD
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD
- Department of Applied Mathematics & Statistics, Whiting School of Engineering, Johns Hopkins University, Baltimore, MD
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Cortes MG, Lin Y, Zeng L, Balázsi G. From Bench to Keyboard and Back Again: A Brief History of Lambda Phage Modeling. Annu Rev Biophys 2021; 50:117-134. [PMID: 33957052 DOI: 10.1146/annurev-biophys-082020-063558] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Cellular decision making is the process whereby cells choose one developmental pathway from multiple possible ones, either spontaneously or due to environmental stimuli. Examples in various cell types suggest an almost inexhaustible plethora of underlying molecular mechanisms. In general, cellular decisions rely on the gene regulatory network, which integrates external signals to drive cell fate choice. The search for general principles of such a process benefits from appropriate biological model systems that reveal how and why certain gene regulatory mechanisms drive specific cellular decisions according to ecological context and evolutionary outcomes. In this article, we review the historical and ongoing development of the phage lambda lysis-lysogeny decision as a model system to investigate all aspects of cellular decision making. The unique generality, simplicity, and richness of phage lambda decision making render it a constant source ofmathematical modeling-aided inspiration across all of biology. We discuss the origins and progress of quantitative phage lambda modeling from the 1950s until today, as well as its possible future directions. We provide examples of how modeling enabled methods and theory development, leading to new biological insights by revealing gaps in the theory and pinpointing areas requiring further experimental investigation. Overall, we highlight the utility of theoretical approaches both as predictive tools, to forecast the outcome of novel experiments, and as explanatory tools, to elucidate the natural processes underlying experimental data.
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Affiliation(s)
- Michael G Cortes
- The Louis and Beatrice Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, New York 11794, USA; .,Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, New York 11794, USA
| | - Yiruo Lin
- Department of Computer Science and Engineering, Texas A&M University, College Station, Texas 77843, USA
| | - Lanying Zeng
- Department of Biochemistry and Biophysics, Texas A&M University, College Station, Texas 77843, USA; .,Center for Phage Technology, Texas A&M University, College Station, Texas 77843, USA
| | - Gábor Balázsi
- The Louis and Beatrice Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, New York 11794, USA; .,Department of Biomedical Engineering, Stony Brook University, Stony Brook, New York 11794, USA
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Koneru SL, Quah FX, Ghose R, Hintze M, Gritti N, van Zon JS, Barkoulas M. A role for the fusogen eff-1 in epidermal stem cell number robustness in Caenorhabditis elegans. Sci Rep 2021; 11:9787. [PMID: 33963222 PMCID: PMC8105389 DOI: 10.1038/s41598-021-88500-4] [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] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2020] [Accepted: 04/13/2021] [Indexed: 02/03/2023] Open
Abstract
Developmental patterning in Caenorhabditis elegans is known to proceed in a highly stereotypical manner, which raises the question of how developmental robustness is achieved despite the inevitable stochastic noise. We focus here on a population of epidermal cells, the seam cells, which show stem cell-like behaviour and divide symmetrically and asymmetrically over post-embryonic development to generate epidermal and neuronal tissues. We have conducted a mutagenesis screen to identify mutants that introduce phenotypic variability in the normally invariant seam cell population. We report here that a null mutation in the fusogen eff-1 increases seam cell number variability. Using time-lapse microscopy and single molecule fluorescence hybridisation, we find that seam cell division and differentiation patterns are mostly unperturbed in eff-1 mutants, indicating that cell fusion is uncoupled from the cell differentiation programme. Nevertheless, seam cell losses due to the inappropriate differentiation of both daughter cells following division, as well as seam cell gains through symmetric divisions towards the seam cell fate were observed at low frequency. We show that these stochastic errors likely arise through accumulation of defects interrupting the continuity of the seam and changing seam cell shape, highlighting the role of tissue homeostasis in suppressing phenotypic variability during development.
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Affiliation(s)
- Sneha L Koneru
- Department of Life Sciences, Imperial College, London, SW7 2AZ, UK
| | - Fu Xiang Quah
- Department of Life Sciences, Imperial College, London, SW7 2AZ, UK
| | - Ritobrata Ghose
- Department of Life Sciences, Imperial College, London, SW7 2AZ, UK
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Dr. Aiguader 88, 08003, Barcelona, Spain
| | - Mark Hintze
- Department of Life Sciences, Imperial College, London, SW7 2AZ, UK
| | - Nicola Gritti
- AMOLF, Science Park 104, 1098 XG, Amsterdam, the Netherlands
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Seddon AR, Liau Y, Pace PE, Miller AL, Das AB, Kennedy MA, Hampton MB, Stevens AJ. Genome-wide impact of hydrogen peroxide on maintenance DNA methylation in replicating cells. Epigenetics Chromatin 2021; 14:17. [PMID: 33761969 PMCID: PMC7992848 DOI: 10.1186/s13072-021-00388-6] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2020] [Accepted: 03/01/2021] [Indexed: 12/22/2022] Open
Abstract
Background Environmental factors, such as oxidative stress, have the potential to modify the epigenetic landscape of cells. We have previously shown that DNA methyltransferase (DNMT) activity can be inhibited by sublethal doses of hydrogen peroxide (H2O2). However, site-specific changes in DNA methylation and the reversibility of any changes have not been explored. Using bead chip array technology, differential methylation was assessed in Jurkat T-lymphoma cells following exposure to H2O2. Results Sublethal H2O2 exposure was associated with an initial genome-wide decrease in DNA methylation in replicating cells, which was largely corrected 72 h later. However, some alterations were conserved through subsequent cycles of cell division. Significant changes to the variability of DNA methylation were also observed both globally and at the site-specific level. Conclusions This research indicates that increased exposure to H2O2 can result in long-term alterations to DNA methylation patterns, providing a mechanism for environmental factors to have prolonged impact on gene expression. Supplementary Information The online version contains supplementary material available at 10.1186/s13072-021-00388-6.
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Affiliation(s)
- Annika R Seddon
- Department of Pathology and Biomedical Science, University of Otago, PO Box 4345, Christchurch, 8140, New Zealand.
| | - Yusmiati Liau
- Department of Pathology and Biomedical Science, University of Otago, PO Box 4345, Christchurch, 8140, New Zealand
| | - Paul E Pace
- Department of Pathology and Biomedical Science, University of Otago, PO Box 4345, Christchurch, 8140, New Zealand
| | - Allison L Miller
- Department of Pathology and Biomedical Science, University of Otago, PO Box 4345, Christchurch, 8140, New Zealand
| | - Andrew B Das
- Department of Pathology and Biomedical Science, University of Otago, PO Box 4345, Christchurch, 8140, New Zealand
| | - Martin A Kennedy
- Department of Pathology and Biomedical Science, University of Otago, PO Box 4345, Christchurch, 8140, New Zealand
| | - Mark B Hampton
- Department of Pathology and Biomedical Science, University of Otago, PO Box 4345, Christchurch, 8140, New Zealand
| | - Aaron J Stevens
- Department of Pathology and Biomedical Science, University of Otago, PO Box 4345, Christchurch, 8140, New Zealand.
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