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Petkidis A, Suomalainen M, Andriasyan V, Singh A, Greber UF. Preexisting cell state rather than stochastic noise confers high or low infection susceptibility of human lung epithelial cells to adenovirus. mSphere 2024:e0045424. [PMID: 39315811 DOI: 10.1128/msphere.00454-24] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2024] [Accepted: 08/20/2024] [Indexed: 09/25/2024] Open
Abstract
Viruses display large variability across all stages of their life cycle, including entry, gene expression, replication, assembly, and egress. We previously reported that the immediate early adenovirus (AdV) E1A transcripts accumulate in human lung epithelial A549 cancer cells with high variability, mostly independent of the number of incoming viral genomes, but somewhat correlated to the cell cycle state at the time of inoculation. Here, we leveraged the classical Luria-Delbrück fluctuation analysis to address whether infection variability primarily arises from the cell state or stochastic noise. The E1A expression was measured by the expression of green fluorescent protein (GFP) from the endogenous E1A promoter in AdV-C5_E1A-FS2A-GFP and found to be highly correlated with the viral plaque formation, indicating reliability of the reporter virus. As an ensemble, randomly picked clonal A549 cell isolates displayed significantly higher coefficients of variation in the E1A expression than technical noise, indicating a phenotypic variability larger than noise. The underlying cell state determining infection variability was maintained for at least 9 weeks of cell cultivation. Our results indicate that preexisting cell states tune adenovirus infection in favor of the cell or the virus. These findings have implications for antiviral strategies and gene therapy applications.IMPORTANCEViral infections are known for their variability. Underlying mechanisms are still incompletely understood but have been associated with particular cell states, for example, the eukaryotic cell division cycle in DNA virus infections. A cell state is the collective of biochemical, morphological, and contextual features owing to particular conditions or at random. It affects how intrinsic or extrinsic cues trigger a response, such as cell division or anti-viral state. Here, we provide evidence that cell states with a built-in memory confer high or low susceptibility of clonal human epithelial cells to adenovirus infection. Results are reminiscent of the Luria-Delbrück fluctuation test with bacteriophage infections back in 1943, which demonstrated that mutations, in the absence of selective pressure prior to infection, cause infection resistance rather than being a consequence of infection. Our findings of dynamic cell states conferring adenovirus infection susceptibility uncover new challenges for the prediction and treatment of viral infections.
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Affiliation(s)
- Anthony Petkidis
- Department of Molecular Life Sciences, Universitat Zurich, Zurich, Switzerland
| | - Maarit Suomalainen
- Department of Molecular Life Sciences, Universitat Zurich, Zurich, Switzerland
| | - Vardan Andriasyan
- Department of Molecular Life Sciences, Universitat Zurich, Zurich, Switzerland
| | - Abhyudai Singh
- Department of Electrical and Computer Engineering, University of Delaware, Newark, Delaware, USA
| | - Urs F Greber
- Department of Molecular Life Sciences, Universitat Zurich, Zurich, Switzerland
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2
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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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3
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Hong CKY, Ramu A, Zhao S, Cohen BA. Effect of genomic and cellular environments on gene expression noise. Genome Biol 2024; 25:137. [PMID: 38790076 PMCID: PMC11127367 DOI: 10.1186/s13059-024-03277-9] [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: 12/07/2022] [Accepted: 05/13/2024] [Indexed: 05/26/2024] Open
Abstract
BACKGROUND Individual cells from isogenic populations often display large cell-to-cell differences in gene expression. This "noise" in expression derives from several sources, including the genomic and cellular environment in which a gene resides. Large-scale maps of genomic environments have revealed the effects of epigenetic modifications and transcription factor occupancy on mean expression levels, but leveraging such maps to explain expression noise will require new methods to assay how expression noise changes at locations across the genome. RESULTS To address this gap, we present Single-cell Analysis of Reporter Gene Expression Noise and Transcriptome (SARGENT), a method that simultaneously measures the noisiness of reporter genes integrated throughout the genome and the global mRNA profiles of individual reporter-gene-containing cells. Using SARGENT, we perform the first comprehensive genome-wide survey of how genomic locations impact gene expression noise. We find that the mean and noise of expression correlate with different histone modifications. We quantify the intrinsic and extrinsic components of reporter gene noise and, using the associated mRNA profiles, assign the extrinsic component to differences between the CD24+ "stem-like" substate and the more "differentiated" substate. SARGENT also reveals the effects of transgene integrations on endogenous gene expression, which will help guide the search for "safe-harbor" loci. CONCLUSIONS Taken together, we show that SARGENT is a powerful tool to measure both the mean and noise of gene expression at locations across the genome and that the data generatd by SARGENT reveals important insights into the regulation of gene expression noise genome-wide.
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Affiliation(s)
- Clarice K Y Hong
- The Edison Family Center for Genome Sciences and Systems Biology, School of Medicine, Washington University in St. Louis, Saint Louis, MO, 63110, USA
- Department of Genetics, School of Medicine, Washington University in St. Louis, Saint Louis, MO, 63110, USA
| | - Avinash Ramu
- The Edison Family Center for Genome Sciences and Systems Biology, School of Medicine, Washington University in St. Louis, Saint Louis, MO, 63110, USA
- Department of Genetics, School of Medicine, Washington University in St. Louis, Saint Louis, MO, 63110, USA
| | - Siqi Zhao
- The Edison Family Center for Genome Sciences and Systems Biology, School of Medicine, Washington University in St. Louis, Saint Louis, MO, 63110, USA
- Department of Genetics, School of Medicine, Washington University in St. Louis, Saint Louis, MO, 63110, USA
| | - Barak A Cohen
- The Edison Family Center for Genome Sciences and Systems Biology, School of Medicine, Washington University in St. Louis, Saint Louis, MO, 63110, USA.
- Department of Genetics, School of Medicine, Washington University in St. Louis, Saint Louis, MO, 63110, USA.
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4
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Witmond M, Keizer E, Kiffen B, Huck WTS, van Buggenum JAGL. Dynamic hydrogen peroxide levels reveal a rate-dependent sensitivity in B-cell lymphoma signaling. Sci Rep 2024; 14:4265. [PMID: 38383739 PMCID: PMC10882005 DOI: 10.1038/s41598-024-54871-7] [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: 09/19/2023] [Accepted: 02/17/2024] [Indexed: 02/23/2024] Open
Abstract
Although in vivo extracellular microenvironments are dynamic, most in vitro studies are conducted under static conditions. Here, we exposed diffuse large B-cell lymphoma (DLBCL) cells to gradient increases in the concentration of hydrogen peroxide (H2O2), thereby capturing some of the dynamics of the tumour microenvironment. Subsequently, we measured the phosphorylation response of B-cell receptor (BCR) signalling proteins CD79a, SYK and PLCγ2 at a high temporal resolution via single-cell phospho-specific flow cytometry. We demonstrated that the cells respond bimodally to static extracellular H2O2, where the percentage of cells that respond is mainly determined by the concentration. Computational analysis revealed that the bimodality results from a combination of a steep dose-response relationship and cell-to-cell variability in the response threshold. Dynamic gradient inputs of varying durations indicated that the H2O2 concentration is not the only determinant of the signalling response, as cells exposed to more shallow gradients respond at lower H2O2 levels. A minimal model of the proximal BCR network qualitatively reproduced the experimental findings and uncovered a rate-dependent sensitivity to H2O2, where a lower rate of increase correlates to a higher sensitivity. These findings will bring us closer to understanding how cells process information from their complex and dynamic in vivo environments.
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Affiliation(s)
- Melde Witmond
- Institute for Molecules and Materials (IMM), Radboud University Nijmegen, Nijmegen, The Netherlands
| | - Emma Keizer
- Institute for Molecules and Materials (IMM), Radboud University Nijmegen, Nijmegen, The Netherlands
| | - Bas Kiffen
- Institute for Molecules and Materials (IMM), Radboud University Nijmegen, Nijmegen, The Netherlands
| | - Wilhelm T S Huck
- Institute for Molecules and Materials (IMM), Radboud University Nijmegen, Nijmegen, The Netherlands.
| | - Jessie A G L van Buggenum
- Institute for Molecules and Materials (IMM), Radboud University Nijmegen, Nijmegen, The Netherlands.
- Single Cell Discoveries (SCD), Utrecht, The Netherlands.
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Jo H, Hong H, Hwang HJ, Chang W, Kim JK. Density physics-informed neural networks reveal sources of cell heterogeneity in signal transduction. PATTERNS (NEW YORK, N.Y.) 2024; 5:100899. [PMID: 38370126 PMCID: PMC10873160 DOI: 10.1016/j.patter.2023.100899] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Revised: 11/05/2023] [Accepted: 11/24/2023] [Indexed: 02/20/2024]
Abstract
The transduction time between signal initiation and final response provides valuable information on the underlying signaling pathway, including its speed and precision. Furthermore, multi-modality in a transduction-time distribution indicates that the response is regulated by multiple pathways with different transduction speeds. Here, we developed a method called density physics-informed neural networks (Density-PINNs) to infer the transduction-time distribution from measurable final stress response time traces. We applied Density-PINNs to single-cell gene expression data from sixteen promoters regulated by unknown pathways in response to antibiotic stresses. We found that promoters with slower signaling initiation and transduction exhibit larger cell-to-cell heterogeneity in response intensity. However, this heterogeneity was greatly reduced when the response was regulated by slow and fast pathways together. This suggests a strategy for identifying effective signaling pathways for consistent cellular responses to disease treatments. Density-PINNs can also be applied to understand other time delay systems, including infectious diseases.
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Affiliation(s)
- Hyeontae Jo
- Biomedical Mathematics Group, Pioneer Research Center for Mathematical and Computational Sciences, Institute for Basic Science, Daejeon 34126, Republic of Korea
| | - Hyukpyo Hong
- Biomedical Mathematics Group, Pioneer Research Center for Mathematical and Computational Sciences, Institute for Basic Science, Daejeon 34126, Republic of Korea
- Department of Mathematical Sciences, KAIST, Daejeon 34141, Republic of Korea
| | - Hyung Ju Hwang
- Department of Mathematics, Pohang University of Science and Technology, Pohang 37673, Republic of Korea
| | - Won Chang
- Division of Statistics and Data Science, University of Cincinnati, Cincinnati, OH 45221, USA
| | - Jae Kyoung Kim
- Biomedical Mathematics Group, Pioneer Research Center for Mathematical and Computational Sciences, Institute for Basic Science, Daejeon 34126, Republic of Korea
- Department of Mathematical Sciences, KAIST, Daejeon 34141, Republic of Korea
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6
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Naigles B, Narla AV, Soroczynski J, Tsimring LS, Hao N. Quantifying dynamic pro-inflammatory gene expression and heterogeneity in single macrophage cells. J Biol Chem 2023; 299:105230. [PMID: 37689116 PMCID: PMC10579967 DOI: 10.1016/j.jbc.2023.105230] [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: 05/12/2023] [Revised: 09/02/2023] [Accepted: 09/03/2023] [Indexed: 09/11/2023] Open
Abstract
Macrophages must respond appropriately to pathogens and other pro-inflammatory stimuli in order to perform their roles in fighting infection. One way in which inflammatory stimuli can vary is in their dynamics-that is, the amplitude and duration of stimulus experienced by the cell. In this study, we performed long-term live cell imaging in a microfluidic device to investigate how the pro-inflammatory genes IRF1, CXCL10, and CXCL9 respond to dynamic interferon-gamma (IFNγ) stimulation. We found that IRF1 responds to low concentration or short duration IFNγ stimulation, whereas CXCL10 and CXCL9 require longer or higherconcentration stimulation to be expressed. We also investigated the heterogeneity in the expression of each gene and found that CXCL10 and CXCL9 have substantial cell-to-cell variability. In particular, the expression of CXCL10 appears to be largely stochastic with a subpopulation of nonresponding cells across all the stimulation conditions tested. We developed both deterministic and stochastic models for the expression of each gene. Our modeling analysis revealed that the heterogeneity in CXCL10 can be attributed to a slow chromatin-opening step that is on a similar timescale to that of adaptation of the upstream signal. In this way, CXCL10 expression in individual cells can remain stochastic in response to each pulse of repeated stimulation, which we also validated by experiments. Together, we conclude that pro-inflammatory genes in the same signaling pathway can respond to dynamic IFNγ stimulus with very different response features and that upstream signal adaptation can contribute to shaping heterogeneous gene expression.
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Affiliation(s)
- Beverly Naigles
- Department of Molecular Biology, University of California San Diego, La Jolla, California, USA
| | - Avaneesh V Narla
- Department of Physics, University of California San Diego, La Jolla, California, USA
| | - Jan Soroczynski
- Laboratory of Genome Architecture and Dynamics, The Rockefeller University, New York, New York, USA
| | - Lev S Tsimring
- Synthetic Biology Institute, University of California San Diego, La Jolla, California, USA
| | - Nan Hao
- Department of Molecular Biology, University of California San Diego, La Jolla, California, USA; Synthetic Biology Institute, University of California San Diego, La Jolla, California, USA; Department of Bioengineering, University of California San Diego, La Jolla, California, USA.
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7
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Koval A, Zhang X, Katanaev VL. Improved approaches to channel capacity estimation discover compromised GPCR signaling in diverse cancer cells. iScience 2023; 26:107270. [PMID: 37502258 PMCID: PMC10368911 DOI: 10.1016/j.isci.2023.107270] [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: 12/21/2022] [Revised: 04/20/2023] [Accepted: 06/28/2023] [Indexed: 07/29/2023] Open
Abstract
Intracellular signaling orchestrates an organism's development and functioning and underlies various pathologies, such as cancer, when aberrant. A universal cell signaling characteristic is channel capacity - the measure of how much information a given transmitting system can reliably transduce. Here, we describe improved approaches to quantify GPCR signaling channel capacity in single cells, averaged across cell population. We assess the channel capacity based on distribution of residuals by the cellular response amplitude. We further develop means to handle irregularly responding cancer cells using the integral values of their response to different agonist concentrations. These approaches enabled us to analyze, for the first time, channel capacity in single cancer cells. A universal feature emerging for different cancer cell types is a decreased channel capacity of their GPCR signaling. These findings provide experimental validation to the hypothesis that cancer is an information disease, bearing importance for basic cancer biology and anticancer drug discovery.
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Affiliation(s)
- Alexey Koval
- Department of Cell Physiology and Metabolism, Translational Research Center in Oncohaematology, Faculty of Medicine, University of Geneva, 1206 Geneva, Switzerland
| | - Xin Zhang
- Department of Cell Physiology and Metabolism, Translational Research Center in Oncohaematology, Faculty of Medicine, University of Geneva, 1206 Geneva, Switzerland
| | - Vladimir L. Katanaev
- Department of Cell Physiology and Metabolism, Translational Research Center in Oncohaematology, Faculty of Medicine, University of Geneva, 1206 Geneva, Switzerland
- Institute of Life Sciences and Biomedicine, Far Eastern Federal University, 690922 Vladivostok, Russia
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8
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Ramu A, Cohen BA. Transcription factor fluctuations underlie cell-to-cell variability in a signaling pathway response. Genetics 2023; 224:iyad094. [PMID: 37226217 PMCID: PMC10691749 DOI: 10.1093/genetics/iyad094] [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: 03/08/2023] [Revised: 04/25/2023] [Accepted: 05/05/2023] [Indexed: 05/26/2023] Open
Abstract
Stochastic differences among clonal cells can initiate cell fate decisions in development or cause cell-to-cell differences in the responses to drugs or extracellular ligands. One hypothesis is that some of this phenotypic variability is caused by stochastic fluctuations in the activities of transcription factors (TFs). We tested this hypothesis in NIH3T3-CG cells using the response to Hedgehog signaling as a model cellular response. Here, we present evidence for the existence of distinct fast- and slow-responding substates in NIH3T3-CG cells. These two substates have distinct expression profiles, and fluctuations in the Prrx1 TF underlie some of the differences in expression and responsiveness between fast and slow cells. Our results show that fluctuations in TFs can contribute to cell-to-cell differences in Hedgehog signaling.
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Affiliation(s)
- Avinash Ramu
- The Edison Family Center for Genome Sciences and Systems Biology, School of Medicine, Washington University in St. Louis, Saint Louis, MO 63110, USA
- Department of Genetics, School of Medicine, Washington University in St. Louis, Saint Louis, MO 63110, USA
| | - Barak A Cohen
- The Edison Family Center for Genome Sciences and Systems Biology, School of Medicine, Washington University in St. Louis, Saint Louis, MO 63110, USA
- Department of Genetics, School of Medicine, Washington University in St. Louis, Saint Louis, MO 63110, USA
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9
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Jeknić S, Kudo T, Song JJ, Covert MW. An optimized reporter of the transcription factor hypoxia-inducible factor 1α reveals complex HIF-1α activation dynamics in single cells. J Biol Chem 2023; 299:104599. [PMID: 36907438 PMCID: PMC10124923 DOI: 10.1016/j.jbc.2023.104599] [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: 10/18/2022] [Revised: 02/08/2023] [Accepted: 02/20/2023] [Indexed: 03/13/2023] Open
Abstract
Immune cells adopt a variety of metabolic states to support their many biological functions, which include fighting pathogens, removing tissue debris, and tissue remodeling. One of the key mediators of these metabolic changes is the transcription factor hypoxia-inducible factor 1α (HIF-1α). Single-cell dynamics have been shown to be an important determinant of cell behavior; however, despite the importance of HIF-1α, little is known about its single-cell dynamics or their effect on metabolism. To address this knowledge gap, here we optimized a HIF-1α fluorescent reporter and applied it to study single-cell dynamics. First, we showed that single cells are likely able to differentiate multiple levels of prolyl hydroxylase inhibition, a marker of metabolic change, via HIF-1α activity. We then applied a physiological stimulus known to trigger metabolic change, interferon-γ, and observed heterogeneous, oscillatory HIF-1α responses in single cells. Finally, we input these dynamics into a mathematical model of HIF-1α-regulated metabolism and discovered a profound difference between cells exhibiting high versus low HIF-1α activation. Specifically, we found cells with high HIF-1α activation are able to meaningfully reduce flux through the tricarboxylic acid cycle and show a notable increase in the NAD+/NADH ratio compared with cells displaying low HIF-1α activation. Altogether, this work demonstrates an optimized reporter for studying HIF-1α in single cells and reveals previously unknown principles of HIF-1α activation.
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Affiliation(s)
- Stevan Jeknić
- Department of Bioengineering, Stanford University, Stanford, California, USA
| | - Takamasa Kudo
- Department of Chemical and Systems Biology, Stanford University, Stanford, California, USA
| | - Joanna J Song
- Department of Bioengineering, Stanford University, Stanford, California, USA
| | - Markus W Covert
- Department of Bioengineering, Stanford University, Stanford, California, USA.
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10
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Sheu KM, Guru AA, Hoffmann A. Quantifying stimulus-response specificity to probe the functional state of macrophages. Cell Syst 2023; 14:180-195.e5. [PMID: 36657439 PMCID: PMC10023480 DOI: 10.1016/j.cels.2022.12.012] [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: 06/01/2022] [Revised: 10/05/2022] [Accepted: 12/22/2022] [Indexed: 01/19/2023]
Abstract
Immune sentinel macrophages initiate responses to pathogens via hundreds of immune response genes. Each immune threat demands a tailored response, suggesting that the capacity for stimulus-specific gene expression is a key functional hallmark of healthy macrophages. To quantify this property, termed "stimulus-response specificity" (SRS), we developed a single-cell experimental workflow and analytical approaches based on information theory and machine learning. We found that the response specificity of macrophages is driven by combinations of specific immune genes that show low cell-to-cell heterogeneity and are targets of separate signaling pathways. The "response specificity profile," a systematic comparison of multiple stimulus-response distributions, was distinctly altered by polarizing cytokines, and it enabled an assessment of the functional state of macrophages. Indeed, the response specificity profile of peritoneal macrophages from old and obese mice showed characteristic differences, suggesting that SRS may be a basis for measuring the functional state of innate immune cells. A record of this paper's transparent peer review process is included in the supplemental information.
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Affiliation(s)
- Katherine M Sheu
- Department of Microbiology, Immunology, and Molecular Genetics, and Institute for Quantitative and Computational Biosciences, University of California, Los Angeles, 611 Charles E. Young Dr S, Los Angeles, CA 90093, USA
| | - Aditya A Guru
- Department of Microbiology, Immunology, and Molecular Genetics, and Institute for Quantitative and Computational Biosciences, University of California, Los Angeles, 611 Charles E. Young Dr S, Los Angeles, CA 90093, USA
| | - Alexander Hoffmann
- Department of Microbiology, Immunology, and Molecular Genetics, and Institute for Quantitative and Computational Biosciences, University of California, Los Angeles, 611 Charles E. Young Dr S, Los Angeles, CA 90093, USA.
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11
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Singh A, Saint-Antoine M. Probing transient memory of cellular states using single-cell lineages. Front Microbiol 2023; 13:1050516. [PMID: 36824587 PMCID: PMC9942930 DOI: 10.3389/fmicb.2022.1050516] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Accepted: 12/22/2022] [Indexed: 02/10/2023] Open
Abstract
The inherent stochasticity in the gene product levels can drive single cells within an isoclonal population to different phenotypic states. The dynamic nature of this intercellular variation, where individual cells can transition between different states over time, makes it a particularly hard phenomenon to characterize. We reviewed recent progress in leveraging the classical Luria-Delbrück experiment to infer the transient heritability of the cellular states. Similar to the original experiment, individual cells were first grown into cell colonies, and then, the fraction of cells residing in different states was assayed for each colony. We discuss modeling approaches for capturing dynamic state transitions in a growing cell population and highlight formulas that identify the kinetics of state switching from the extent of colony-to-colony fluctuations. The utility of this method in identifying multi-generational memory of the both expression and phenotypic states is illustrated across diverse biological systems from cancer drug resistance, reactivation of human viruses, and cellular immune responses. In summary, this fluctuation-based methodology provides a powerful approach for elucidating cell-state transitions from a single time point measurement, which is particularly relevant in situations where measurements lead to cell death (as in single-cell RNA-seq or drug treatment) or cause an irreversible change in cell physiology.
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Affiliation(s)
- Abhyudai Singh
- Departments of Electrical and Computer Engineering, Biomedical Engineering, Mathematical Sciences University of Delaware, Newark, DE, United States
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12
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Kalliara E, Kardynska M, Bagnall J, Spiller DG, Müller W, Ruckerl D, Śmieja J, Biswas SK, Paszek P. Post-transcriptional regulatory feedback encodes JAK-STAT signal memory of interferon stimulation. Front Immunol 2022; 13:947213. [PMID: 36238296 PMCID: PMC9552616 DOI: 10.3389/fimmu.2022.947213] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Accepted: 09/08/2022] [Indexed: 11/13/2022] Open
Abstract
Immune cells fine tune their responses to infection and inflammatory cues. Here, using live-cell confocal microscopy and mathematical modelling, we investigate interferon-induced JAK-STAT signalling in innate immune macrophages. We demonstrate that transient exposure to IFN-γ stimulation induces a long-term desensitisation of STAT1 signalling and gene expression responses, revealing a dose- and time-dependent regulatory feedback that controls JAK-STAT responses upon re-exposure to stimulus. We show that IFN-α/β1 elicit different level of desensitisation from IFN-γ, where cells refractory to IFN-α/β1 are sensitive to IFN-γ, but not vice versa. We experimentally demonstrate that the underlying feedback mechanism involves regulation of STAT1 phosphorylation but is independent of new mRNA synthesis and cognate receptor expression. A new feedback model of the protein tyrosine phosphatase activity recapitulates experimental data and demonstrates JAK-STAT network’s ability to decode relative changes of dose, timing, and type of temporal interferon stimulation. These findings reveal that STAT desensitisation renders cells with signalling memory of type I and II interferon stimulation, which in the future may improve administration of interferon therapy.
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Affiliation(s)
- Eirini Kalliara
- School of Biology, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, United Kingdom
- Singapore Immunology Network, Agency for Science, Technology and Research (A*STAR), Singapore, Singapore
| | - Malgorzata Kardynska
- Department of Biosensors and Processing of Biomedical Signals, Silesian University of Technology, Zabrze, Poland
- Department of Systems Biology and Engineering, Silesian University of Technology, Gliwice, Poland
| | - James Bagnall
- School of Biology, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, United Kingdom
| | - David G. Spiller
- School of Biology, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, United Kingdom
| | - Werner Müller
- School of Biology, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, United Kingdom
| | - Dominik Ruckerl
- School of Biology, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, United Kingdom
| | - Jarosław Śmieja
- Department of Systems Biology and Engineering, Silesian University of Technology, Gliwice, Poland
| | - Subhra K. Biswas
- Singapore Immunology Network, Agency for Science, Technology and Research (A*STAR), Singapore, Singapore
| | - Pawel Paszek
- School of Biology, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, United Kingdom
- *Correspondence: Pawel Paszek,
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13
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Salivary gland carcinomas and molecular chaos: Additional perspectives. Oral Oncol 2022; 127:105802. [DOI: 10.1016/j.oraloncology.2022.105802] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Accepted: 02/27/2022] [Indexed: 11/19/2022]
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Jain P, Bhatia S, Thompson EW, Jolly MK. Population Dynamics of Epithelial-Mesenchymal Heterogeneity in Cancer Cells. Biomolecules 2022; 12:biom12030348. [PMID: 35327538 PMCID: PMC8945776 DOI: 10.3390/biom12030348] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Revised: 02/17/2022] [Accepted: 02/18/2022] [Indexed: 11/16/2022] Open
Abstract
Phenotypic heterogeneity is a hallmark of aggressive cancer behaviour and a clinical challenge. Despite much characterisation of this heterogeneity at a multi-omics level in many cancers, we have a limited understanding of how this heterogeneity emerges spontaneously in an isogenic cell population. Some longitudinal observations of dynamics in epithelial-mesenchymal heterogeneity, a canonical example of phenotypic heterogeneity, have offered us opportunities to quantify the rates of phenotypic switching that may drive such heterogeneity. Here, we offer a mathematical modeling framework that explains the salient features of population dynamics noted in PMC42-LA cells: (a) predominance of EpCAMhigh subpopulation, (b) re-establishment of parental distributions from the EpCAMhigh and EpCAMlow subpopulations, and (c) enhanced heterogeneity in clonal populations established from individual cells. Our framework proposes that fluctuations or noise in content duplication and partitioning of SNAIL—an EMT-inducing transcription factor—during cell division can explain spontaneous phenotypic switching and consequent dynamic heterogeneity in PMC42-LA cells observed experimentally at both single-cell and bulk level analysis. Together, we propose that asymmetric cell division can be a potential mechanism for phenotypic heterogeneity.
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Affiliation(s)
- Paras Jain
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India;
| | - Sugandha Bhatia
- School of Biomedical Sciences, Faculty of Health, Queensland University of Technology, Brisbane 4000, Australia;
- The University of Queensland Diamantina Institute, Faculty of Medicine, The University of Queensland, Woolloongabba 4102, Australia
- Translational Research Institute, Woolloongabba 4102, Australia
| | - Erik W. Thompson
- School of Biomedical Sciences, Faculty of Health, Queensland University of Technology, Brisbane 4000, Australia;
- Translational Research Institute, Woolloongabba 4102, Australia
- Correspondence: (E.W.T.); (M.K.J.)
| | - Mohit Kumar Jolly
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India;
- Correspondence: (E.W.T.); (M.K.J.)
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