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Sechkar K, Steel H, Perrino G, Stan GB. A coarse-grained bacterial cell model for resource-aware analysis and design of synthetic gene circuits. Nat Commun 2024; 15:1981. [PMID: 38438391 PMCID: PMC10912777 DOI: 10.1038/s41467-024-46410-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Accepted: 02/27/2024] [Indexed: 03/06/2024] Open
Abstract
Within a cell, synthetic and native genes compete for expression machinery, influencing cellular process dynamics through resource couplings. Models that simplify competitive resource binding kinetics can guide the design of strategies for countering these couplings. However, in bacteria resource availability and cell growth rate are interlinked, which complicates resource-aware biocircuit design. Capturing this interdependence requires coarse-grained bacterial cell models that balance accurate representation of metabolic regulation against simplicity and interpretability. We propose a coarse-grained E. coli cell model that combines the ease of simplified resource coupling analysis with appreciation of bacterial growth regulation mechanisms and the processes relevant for biocircuit design. Reliably capturing known growth phenomena, it provides a unifying explanation to disparate empirical relations between growth and synthetic gene expression. Considering a biomolecular controller that makes cell-wide ribosome availability robust to perturbations, we showcase our model's usefulness in numerically prototyping biocircuits and deriving analytical relations for design guidance.
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Affiliation(s)
- Kirill Sechkar
- Department of Engineering Science, University of Oxford, Parks Road, Oxford, OX1 3PJ, UK
| | - Harrison Steel
- Department of Engineering Science, University of Oxford, Parks Road, Oxford, OX1 3PJ, UK
| | - Giansimone Perrino
- Department of Bioengineering, Imperial College London, South Kensington Campus, London, SW7 2AZ, UK.
- Imperial College Centre of Excellence in Synthetic Biology, Imperial College London, South Kensington Campus, London, SW7 2AZ, UK.
| | - Guy-Bart Stan
- Department of Bioengineering, Imperial College London, South Kensington Campus, London, SW7 2AZ, UK.
- Imperial College Centre of Excellence in Synthetic Biology, Imperial College London, South Kensington Campus, London, SW7 2AZ, UK.
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2
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Pérez-Ortín JE, García-Marcelo MJ, Delgado-Román I, Muñoz-Centeno MC, Chávez S. Influence of cell volume on the gene transcription rate. Biochim Biophys Acta Gene Regul Mech 2024; 1867:195008. [PMID: 38246270 DOI: 10.1016/j.bbagrm.2024.195008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/06/2023] [Revised: 01/14/2024] [Accepted: 01/15/2024] [Indexed: 01/23/2024]
Abstract
Cells vary in volume throughout their life cycle and in many other circumstances, while their genome remains identical. Hence, the RNA production factory must adapt to changing needs, while maintaining the same production lines. This paradox is resolved by different mechanisms in distinct cells and circumstances. RNA polymerases have evolved to cope with the particular circumstances of each case and the different characteristics of the several RNA molecule types, especially their stabilities. Here we review current knowledge on these issues. We focus on the yeast Saccharomyces cerevisiae, where many of the studies have been performed, although we compare and discuss the results obtained in other eukaryotes and propose several ideas and questions to be tested and solved in the future. TAKE AWAY.
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Affiliation(s)
- José E Pérez-Ortín
- Instituto de Biotecnología y Biomedicina (BIOTECMED), Facultad de Biológicas, Universitat de València, C/ Dr. Moliner 50, E46100 Burjassot, Spain.
| | - María J García-Marcelo
- Instituto de Biotecnología y Biomedicina (BIOTECMED), Facultad de Biológicas, Universitat de València, C/ Dr. Moliner 50, E46100 Burjassot, Spain; Instituto de Biomedicina de Sevilla, Universidad de Sevilla-CSIC-Hospital Universitario V. del Rocío, Seville 41012, Spain; Departamento de Genética, Facultad de Biología, Universidad de Sevilla, Seville, Spain
| | - Irene Delgado-Román
- Instituto de Biomedicina de Sevilla, Universidad de Sevilla-CSIC-Hospital Universitario V. del Rocío, Seville 41012, Spain; Departamento de Genética, Facultad de Biología, Universidad de Sevilla, Seville, Spain
| | - María C Muñoz-Centeno
- Instituto de Biomedicina de Sevilla, Universidad de Sevilla-CSIC-Hospital Universitario V. del Rocío, Seville 41012, Spain; Departamento de Genética, Facultad de Biología, Universidad de Sevilla, Seville, Spain
| | - Sebastián Chávez
- Instituto de Biomedicina de Sevilla, Universidad de Sevilla-CSIC-Hospital Universitario V. del Rocío, Seville 41012, Spain; Departamento de Genética, Facultad de Biología, Universidad de Sevilla, Seville, Spain
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3
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Baghdassarian HM, Lewis NE. Resource allocation in mammalian systems. Biotechnol Adv 2024; 71:108305. [PMID: 38215956 DOI: 10.1016/j.biotechadv.2023.108305] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Revised: 12/17/2023] [Accepted: 12/18/2023] [Indexed: 01/14/2024]
Abstract
Cells execute biological functions to support phenotypes such as growth, migration, and secretion. Complementarily, each function of a cell has resource costs that constrain phenotype. Resource allocation by a cell allows it to manage these costs and optimize their phenotypes. In fact, the management of resource constraints (e.g., nutrient availability, bioenergetic capacity, and macromolecular machinery production) shape activity and ultimately impact phenotype. In mammalian systems, quantification of resource allocation provides important insights into higher-order multicellular functions; it shapes intercellular interactions and relays environmental cues for tissues to coordinate individual cells to overcome resource constraints and achieve population-level behavior. Furthermore, these constraints, objectives, and phenotypes are context-dependent, with cells adapting their behavior according to their microenvironment, resulting in distinct steady-states. This review will highlight the biological insights gained from probing resource allocation in mammalian cells and tissues.
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Affiliation(s)
- Hratch M Baghdassarian
- Bioinformatics and Systems Biology Graduate Program, University of California, San Diego, La Jolla, CA 92093, USA; Department of Pediatrics, University of California, San Diego, La Jolla, CA 92093, USA
| | - Nathan E Lewis
- Department of Pediatrics, University of California, San Diego, La Jolla, CA 92093, USA; Department of Bioengineering, University of California, San Diego, La Jolla, CA 92093, USA.
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4
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Fromm B, Sorger T. Rapid adaptation of cellular metabolic rate to the MicroRNA complements of mammals and its relevance to the evolution of endothermy. iScience 2024; 27:108740. [PMID: 38327773 PMCID: PMC10847693 DOI: 10.1016/j.isci.2023.108740] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Revised: 09/13/2023] [Accepted: 12/12/2023] [Indexed: 02/09/2024] Open
Abstract
The metabolic efficiency of mammalian cells depends on the attenuation of intrinsic translation noise by microRNAs. We devised a metric of cellular metabolic rate (cMR), rMR/Mexp optimally fit to the number of microRNA families (mirFam), that is robust to variation in mass and sensitive to body temperature (Tb), consistent with the heat dissipation limit theory of Speakman and Król (2010). Using mirFam as predictor, an Ornstein-Uhlenbeck process of stabilizing selection, with an adaptive shift at the divergence of Boreoeutheria, accounted for 95% of the variation in cMR across mammals. Branchwise rates of evolution of cMR, mirFam and Tb concurrently increased 6- to 7-fold at the divergence of Boreoeutheria, independent of mass. Cellular MR variation across placental mammals was also predicted by the sum of model conserved microRNA-target interactions, revealing an unexpected degree of integration of the microRNA-target apparatus into the energy economy of the mammalian cell.
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Affiliation(s)
- Bastian Fromm
- The Arctic University Museum of Norway, UiT- The Arctic University of Norway, Tromsø, Norway
| | - Thomas Sorger
- Department of Biology, Roger Williams University, Bristol, RI 02809, USA
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5
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Pountain AW, Jiang P, Yao T, Homaee E, Guan Y, McDonald KJC, Podkowik M, Shopsin B, Torres VJ, Golding I, Yanai I. Transcription-replication interactions reveal bacterial genome regulation. Nature 2024; 626:661-669. [PMID: 38267581 PMCID: PMC10923101 DOI: 10.1038/s41586-023-06974-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Accepted: 12/14/2023] [Indexed: 01/26/2024]
Abstract
Organisms determine the transcription rates of thousands of genes through a few modes of regulation that recur across the genome1. In bacteria, the relationship between the regulatory architecture of a gene and its expression is well understood for individual model gene circuits2,3. However, a broader perspective of these dynamics at the genome scale is lacking, in part because bacterial transcriptomics has hitherto captured only a static snapshot of expression averaged across millions of cells4. As a result, the full diversity of gene expression dynamics and their relation to regulatory architecture remains unknown. Here we present a novel genome-wide classification of regulatory modes based on the transcriptional response of each gene to its own replication, which we term the transcription-replication interaction profile (TRIP). Analysing single-bacterium RNA-sequencing data, we found that the response to the universal perturbation of chromosomal replication integrates biological regulatory factors with biophysical molecular events on the chromosome to reveal the local regulatory context of a gene. Whereas the TRIPs of many genes conform to a gene dosage-dependent pattern, others diverge in distinct ways, and this is shaped by factors such as intra-operon position and repression state. By revealing the underlying mechanistic drivers of gene expression heterogeneity, this work provides a quantitative, biophysical framework for modelling replication-dependent expression dynamics.
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Affiliation(s)
- Andrew W Pountain
- Institute for Systems Genetics, NYU Grossman School of Medicine, New York, NY, USA
| | - Peien Jiang
- Institute for Systems Genetics, NYU Grossman School of Medicine, New York, NY, USA
- Department of Biology, New York University, New York, NY, USA
| | - Tianyou Yao
- Department of Physics, University of Illinois at Urbana Champaign, Urbana, IL, USA
| | - Ehsan Homaee
- Department of Physics, University of Illinois at Urbana Champaign, Urbana, IL, USA
- Center for Biophysics and Computational Biology, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Yichao Guan
- Department of Physics, University of Illinois at Urbana Champaign, Urbana, IL, USA
| | - Kevin J C McDonald
- Department of Physics, University of Illinois at Urbana Champaign, Urbana, IL, USA
| | - Magdalena Podkowik
- Department of Medicine, Division of Infectious Diseases, NYU Grossman School of Medicine, New York, NY, USA
| | - Bo Shopsin
- Department of Medicine, Division of Infectious Diseases, NYU Grossman School of Medicine, New York, NY, USA
- Department of Microbiology, NYU Grossman School of Medicine, New York, NY, USA
| | - Victor J Torres
- Department of Microbiology, NYU Grossman School of Medicine, New York, NY, USA
- Department of Host-Microbe Interactions, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Ido Golding
- Department of Physics, University of Illinois at Urbana Champaign, Urbana, IL, USA
- Department of Microbiology, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Itai Yanai
- Institute for Systems Genetics, NYU Grossman School of Medicine, New York, NY, USA.
- Department of Biochemistry and Molecular Pharmacology, NYU Grossman School of Medicine, New York, NY, USA.
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Liu X, Yan J, Kirschner MW. Cell size homeostasis is tightly controlled throughout the cell cycle. PLoS Biol 2024; 22:e3002453. [PMID: 38180950 PMCID: PMC10769027 DOI: 10.1371/journal.pbio.3002453] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Accepted: 11/28/2023] [Indexed: 01/07/2024] Open
Abstract
To achieve a stable size distribution over multiple generations, proliferating cells require a means of counteracting stochastic noise in the rate of growth, the time spent in various phases of the cell cycle, and the imprecision in the placement of the plane of cell division. In the most widely accepted model, cell size is thought to be regulated at the G1/S transition, such that cells smaller than a critical size pause at the end of G1 phase until they have accumulated mass to a predetermined size threshold, at which point the cells proceed through the rest of the cell cycle. However, a model, based solely on a specific size checkpoint at G1/S, cannot readily explain why cells with deficient G1/S control mechanisms are still able to maintain a very stable cell size distribution. Furthermore, such a model would not easily account for stochastic variation in cell size during the subsequent phases of the cell cycle, which cannot be anticipated at G1/S. To address such questions, we applied computationally enhanced quantitative phase microscopy (ceQPM) to populations of cultured human cell lines, which enables highly accurate measurement of cell dry mass of individual cells throughout the cell cycle. From these measurements, we have evaluated the factors that contribute to maintaining cell mass homeostasis at any point in the cell cycle. Our findings reveal that cell mass homeostasis is accurately maintained, despite disruptions to the normal G1/S machinery or perturbations in the rate of cell growth. Control of cell mass is generally not confined to regulation of the G1 length. Instead mass homeostasis is imposed throughout the cell cycle. In the cell lines examined, we find that the coefficient of variation (CV) in dry mass of cells in the population begins to decline well before the G1/S transition and continues to decline throughout S and G2 phases. Among the different cell types tested, the detailed response of cell growth rate to cell mass differs. However, in general, when it falls below that for exponential growth, the natural increase in the CV of cell mass is effectively constrained. We find that both mass-dependent cell cycle regulation and mass-dependent growth rate modulation contribute to reducing cell mass variation within the population. Through the interplay and coordination of these 2 processes, accurate cell mass homeostasis emerges. Such findings reveal previously unappreciated and very general principles of cell size control in proliferating cells. These same regulatory processes might also be operative in terminally differentiated cells. Further quantitative dynamical studies should lead to a better understanding of the underlying molecular mechanisms of cell size control.
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Affiliation(s)
- Xili Liu
- Department of Systems Biology, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Jiawei Yan
- Department of Chemistry, Stanford University, Stanford, California, United States of America
| | - Marc W. Kirschner
- Department of Systems Biology, Harvard Medical School, Boston, Massachusetts, United States of America
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7
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Maiti S, Bhattacharya K, Wider D, Hany D, Panasenko O, Bernasconi L, Hulo N, Picard D. Hsf1 and the molecular chaperone Hsp90 support a 'rewiring stress response' leading to an adaptive cell size increase in chronic stress. eLife 2023; 12:RP88658. [PMID: 38059913 DOI: 10.7554/elife.88658] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/08/2023] Open
Abstract
Cells are exposed to a wide variety of internal and external stresses. Although many studies have focused on cellular responses to acute and severe stresses, little is known about how cellular systems adapt to sublethal chronic stresses. Using mammalian cells in culture, we discovered that they adapt to chronic mild stresses of up to two weeks, notably proteotoxic stresses such as heat, by increasing their size and translation, thereby scaling the amount of total protein. These adaptations render them more resilient to persistent and subsequent stresses. We demonstrate that Hsf1, well known for its role in acute stress responses, is required for the cell size increase, and that the molecular chaperone Hsp90 is essential for coupling the cell size increase to augmented translation. We term this translational reprogramming the 'rewiring stress response', and propose that this protective process of chronic stress adaptation contributes to the increase in size as cells get older, and that its failure promotes aging.
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Affiliation(s)
- Samarpan Maiti
- Département de Biologie Moléculaire et Cellulaire, Université de Genève, Genève, Switzerland
| | - Kaushik Bhattacharya
- Département de Biologie Moléculaire et Cellulaire, Université de Genève, Genève, Switzerland
| | - Diana Wider
- Département de Biologie Moléculaire et Cellulaire, Université de Genève, Genève, Switzerland
| | - Dina Hany
- Département de Biologie Moléculaire et Cellulaire, Université de Genève, Genève, Switzerland
- On leave from: Department of Pharmacology and Therapeutics, Faculty of Pharmacy, Pharos University in Alexandria, Alexandria, Egypt
| | - Olesya Panasenko
- BioCode: RNA to Proteins Core Facility, Département de Microbiologie et Médecine Moléculaire, Faculté de Médecine, Université de Genève, Genève, Switzerland
| | - Lilia Bernasconi
- Département de Biologie Moléculaire et Cellulaire, Université de Genève, Genève, Switzerland
| | - Nicolas Hulo
- Institute of Genetics and Genomics of Geneva, Université de Genève, Genève, Switzerland
| | - Didier Picard
- Département de Biologie Moléculaire et Cellulaire, Université de Genève, Genève, Switzerland
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8
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Gonzalez Rodriguez S, Wirshing AC, Goodman AL, Goode BL. Cytosolic concentrations of actin binding proteins and the implications for in vivo F-actin turnover. J Cell Biol 2023; 222:e202306036. [PMID: 37801069 PMCID: PMC10558290 DOI: 10.1083/jcb.202306036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2023] [Revised: 08/31/2023] [Accepted: 09/21/2023] [Indexed: 10/07/2023] Open
Abstract
Understanding how numerous actin-binding proteins (ABPs) work in concert to control the assembly, organization, and turnover of the actin cytoskeleton requires quantitative information about the levels of each component. Here, we measured the cellular concentrations of actin and the majority of the conserved ABPs in Saccharomyces cerevisiae, as well as the free (cytosolic) fractions of each ABP. The cellular concentration of actin is estimated to be 13.2 µM, with approximately two-thirds in the F-actin form and one-third in the G-actin form. Cellular concentrations of ABPs range from 12.4 to 0.85 µM (Tpm1> Pfy1> Cof1> Abp1> Srv2> Abp140> Tpm2> Aip1> Cap1/2> Crn1> Sac6> Twf1> Arp2/3> Scp1). The cytosolic fractions of all ABPs are unexpectedly high (0.6-0.9) and remain so throughout the cell cycle. Based on these numbers, we speculate that F-actin binding sites are limited in vivo, which leads to high cytosolic levels of ABPs, and in turn helps drive the rapid assembly and turnover of cellular F-actin structures.
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Affiliation(s)
- Sofia Gonzalez Rodriguez
- Department of Biology, Rosenstiel Basic Medical Science Research Center, Brandeis University, Waltham, MA, USA
| | - Alison C.E. Wirshing
- Department of Biology, Rosenstiel Basic Medical Science Research Center, Brandeis University, Waltham, MA, USA
| | - Anya L. Goodman
- Department of Biology, Rosenstiel Basic Medical Science Research Center, Brandeis University, Waltham, MA, USA
- Department of Chemistry and Biochemistry, California Polytechnic State University SLO, San Luis Obispo, CA, USA
| | - Bruce L. Goode
- Department of Biology, Rosenstiel Basic Medical Science Research Center, Brandeis University, Waltham, MA, USA
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9
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Swaffer MP, Marinov GK, Zheng H, Fuentes Valenzuela L, Tsui CY, Jones AW, Greenwood J, Kundaje A, Greenleaf WJ, Reyes-Lamothe R, Skotheim JM. RNA polymerase II dynamics and mRNA stability feedback scale mRNA amounts with cell size. Cell 2023; 186:5254-5268.e26. [PMID: 37944513 DOI: 10.1016/j.cell.2023.10.012] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Revised: 07/16/2023] [Accepted: 10/10/2023] [Indexed: 11/12/2023]
Abstract
A fundamental feature of cellular growth is that total protein and RNA amounts increase with cell size to keep concentrations approximately constant. A key component of this is that global transcription rates increase in larger cells. Here, we identify RNA polymerase II (RNAPII) as the limiting factor scaling mRNA transcription with cell size in budding yeast, as transcription is highly sensitive to the dosage of RNAPII but not to other components of the transcriptional machinery. Our experiments support a dynamic equilibrium model where global RNAPII transcription at a given size is set by the mass action recruitment kinetics of unengaged nucleoplasmic RNAPII to the genome. However, this only drives a sub-linear increase in transcription with size, which is then partially compensated for by a decrease in mRNA decay rates as cells enlarge. Thus, limiting RNAPII and feedback on mRNA stability work in concert to scale mRNA amounts with cell size.
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Affiliation(s)
| | - Georgi K Marinov
- Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Huan Zheng
- Department of Biology, McGill University, Montreal, QC H3G 0B1, Canada
| | | | - Crystal Yee Tsui
- Department of Biology, Stanford University, Stanford, CA 94305, USA
| | | | | | - Anshul Kundaje
- Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | | | | | - Jan M Skotheim
- Department of Biology, Stanford University, Stanford, CA 94305, USA; Chan Zuckerberg Biohub, San Francisco, CA 94158, USA.
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10
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Ciolli Mattioli C, Eisner K, Rosenbaum A, Wang M, Rivalta A, Amir A, Golding I, Avraham R. Physiological stress drives the emergence of a Salmonella subpopulation through ribosomal RNA regulation. Curr Biol 2023; 33:4880-4892.e14. [PMID: 37879333 PMCID: PMC10843543 DOI: 10.1016/j.cub.2023.09.064] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Revised: 08/24/2023] [Accepted: 09/26/2023] [Indexed: 10/27/2023]
Abstract
Bacteria undergo cycles of growth and starvation to which they must adapt swiftly. One important strategy for adjusting growth rates relies on ribosomal levels. Although high ribosomal levels are required for fast growth, their dynamics during starvation remain unclear. Here, we analyzed ribosomal RNA (rRNA) content of individual Salmonella cells by using fluorescence in situ hybridization (rRNA-FISH) and measured a dramatic decrease in rRNA numbers only in a subpopulation during nutrient limitation, resulting in a bimodal distribution of cells with high and low rRNA content. During nutritional upshifts, the two subpopulations were associated with distinct phenotypes. Using a transposon screen coupled with rRNA-FISH, we identified two mutants, DksA and RNase I, acting on rRNA transcription shutdown and degradation, which abolished the formation of the subpopulation with low rRNA content. Our work identifies a bacterial mechanism for regulation of ribosomal bimodality that may be beneficial for population survival during starvation.
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Affiliation(s)
- Camilla Ciolli Mattioli
- Department of Immunology and Regenerative Biology, Weizmann Institute of Science, Rehovot 7610001, Israel
| | - Kfir Eisner
- Department of Physics of Complex Systems, Weizmann Institute of Science, Rehovot 7610001, Israel
| | - Aviel Rosenbaum
- Department of Immunology and Regenerative Biology, Weizmann Institute of Science, Rehovot 7610001, Israel
| | - Mengyu Wang
- Department of Physics, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Andre' Rivalta
- Department of Chemical and Structural Biology, Weizmann Institute of Science, Rehovot 7610001, Israel
| | - Ariel Amir
- Department of Physics of Complex Systems, Weizmann Institute of Science, Rehovot 7610001, Israel
| | - Ido Golding
- Department of Physics, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Roi Avraham
- Department of Immunology and Regenerative Biology, Weizmann Institute of Science, Rehovot 7610001, Israel.
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11
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Aboragah AA, Sherlock DN, Wichasit N, Mauck J, Loor JJ. Intermediate metabolites and molecular correlates of one‑carbon and nutrient metabolism differ in tissues from Holstein fetuses. Res Vet Sci 2023; 164:104988. [PMID: 37678126 DOI: 10.1016/j.rvsc.2023.104988] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Revised: 08/11/2023] [Accepted: 08/21/2023] [Indexed: 09/09/2023]
Abstract
Methionine and folate cycles along with transsulfuration comprise the one‑carbon metabolism (OCM) pathway. Amino acids and other nutrients feed into OCM, which is central to cellular function. mRNA abundance, proteins (Western blotting), and metabolites (GC-MC) associated with OCM were used to characterize these mechanisms in fetal tissues. Liver, whole intestine, and semitendinosus muscle were harvested from fetuses in 6 multiparous Holstein cows (37 kg milk/d, 100 d gestation). Data were analyzed using PROC MIXED (SAS 9.4). Protein abundance of BHMT was greatest (P < 0.01) in liver suggesting active remethylation of homocysteine to methionine. This idea was supported by the greater (P < 0.05) mRNA of CBS, BHMT, MTR, SHMT1, and MAT1A (encoding OCM enzymes) in liver. The antioxidant protein GPX3 had greatest (P < 0.05) abundance in liver, whereas the glutathione-transferase GSTM1 was 5-fold greater (P < 0.05) in intestine than liver and muscle. Greatest concentrations of glycine, serine, and taurine along with lower cysteine underscored the relevance of OCM in fetal liver. Phosphoethanolamine concentration was greatest (4-fold, P < 0.05) in intestine and along with the greatest (P < 0.05) mRNA of SLC44A1 (choline transporter), CHKA, and CEPT1 underscored the importance of the CDP-choline pathway. Greatest (P < 0.05) mRNA of PPARA, CPT1A, and HMGCS2 along with lower PCK1 in liver highlighted a potential reliance on fatty acid oxidation. In contrast, greater (P < 0.05) concentration of myo-inositol in muscle and intestine suggested both tissues rely on glucose as main source of energy. Future research should address how environmental inputs such as maternal nutrition alter these pathways in fetal tissues and their phenotypic outcomes.
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Affiliation(s)
- Ahmad A Aboragah
- Department of Animal Sciences, University of Illinois, Urbana 61801, USA; Department of Animal Production, College of Food and Agriculture Sciences, King Saud University, Riyadh 11451, Saudi Arabia
| | | | - Nithat Wichasit
- Department of Animal Sciences, University of Illinois, Urbana 61801, USA; Department of Agricultural Science, Naresuan University, Phitsanulok 65000, Thailand
| | - John Mauck
- Department of Animal Sciences, University of Illinois, Urbana 61801, USA
| | - Juan J Loor
- Department of Animal Sciences, University of Illinois, Urbana 61801, USA; Division of Nutritional Sciences, University of Illinois, Urbana 61801, USA.
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12
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Lanz MC, Zhang S, Swaffer MP, Hernández Götz L, McCarty F, Ziv I, Jarosz DF, Elias JE, Skotheim JM. Genome dilution by cell growth drives starvation-like proteome remodeling in mammalian and yeast cells. bioRxiv 2023:2023.10.16.562558. [PMID: 37905015 PMCID: PMC10614910 DOI: 10.1101/2023.10.16.562558] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/02/2023]
Abstract
Cell size is tightly controlled in healthy tissues and single-celled organisms, but it remains unclear how size influences cell physiology. Increasing cell size was recently shown to remodel the proteomes of cultured human cells, demonstrating that large and small cells of the same type can be biochemically different. Here, we corroborate these results in mouse hepatocytes and extend our analysis using yeast. We find that size-dependent proteome changes are highly conserved and mostly independent of metabolic state. As eukaryotic cells grow larger, the dilution of the genome elicits a starvation-like proteome phenotype, suggesting that growth in large cells is limited by the genome in a manner analogous to a limiting nutrient. We also demonstrate that the proteomes of replicatively-aged yeast are primarily determined by their large size. Overall, our data suggest that genome concentration is a universal determinant of proteome content in growing cells.
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13
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Jager K, Orozco-Hidalgo MT, Springstein BL, Joly-Smith E, Papazotos F, McDonough E, Fleming E, McCallum G, Yuan AH, Hilfinger A, Hochschild A, Potvin-Trottier L. Measuring prion propagation in single bacteria elucidates a mechanism of loss. Proc Natl Acad Sci U S A 2023; 120:e2221539120. [PMID: 37738299 PMCID: PMC10523482 DOI: 10.1073/pnas.2221539120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Accepted: 07/26/2023] [Indexed: 09/24/2023] Open
Abstract
Prions are self-propagating protein aggregates formed by specific proteins that can adopt alternative folds. Prions were discovered as the cause of the fatal transmissible spongiform encephalopathies in mammals, but prions can also constitute nontoxic protein-based elements of inheritance in fungi and other species. Prion propagation has recently been shown to occur in bacteria for more than a hundred cell divisions, yet a fraction of cells in these lineages lost the prion through an unknown mechanism. Here, we investigate prion propagation in single bacterial cells as they divide using microfluidics and fluorescence microscopy. We show that the propagation occurs in two distinct modes. In a fraction of the population, cells had multiple small visible aggregates and lost the prion through random partitioning of aggregates to one of the two daughter cells at division. In the other subpopulation, cells had a stable large aggregate localized to the pole; upon division the mother cell retained this polar aggregate and a daughter cell was generated that contained small aggregates. Extending our findings to prion domains from two orthologous proteins, we observe similar propagation and loss properties. Our findings also provide support for the suggestion that bacterial prions can form more than one self-propagating state. We implement a stochastic version of the molecular model of prion propagation from yeast and mammals that recapitulates all the observed single-cell properties. This model highlights challenges for prion propagation that are unique to prokaryotes and illustrates the conservation of fundamental characteristics of prion propagation.
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Affiliation(s)
- Krista Jager
- Department of Biology, Concordia University, Montréal, QCH4B 1R6, Canada
| | | | | | - Euan Joly-Smith
- Department of Physics, University of Toronto, Toronto, ONM5S 1A7, Canada
| | - Fotini Papazotos
- Department of Biology, Concordia University, Montréal, QCH4B 1R6, Canada
| | | | - Eleanor Fleming
- Department of Microbiology, Harvard Medical School, Boston, MA02115
| | - Giselle McCallum
- Department of Biology, Concordia University, Montréal, QCH4B 1R6, Canada
| | - Andy H. Yuan
- Department of Cell Biology, Harvard Medical School, Boston, MA02115
| | - Andreas Hilfinger
- Department of Physics, University of Toronto, Toronto, ONM5S 1A7, Canada
- Department of Mathematics, University of Toronto, Toronto, ONM5S 2E4, Canada
- Department of Cell and Systems Biology, University of Toronto, Toronto, ONM5S 3G5, Canada
| | - Ann Hochschild
- Department of Microbiology, Harvard Medical School, Boston, MA02115
| | - Laurent Potvin-Trottier
- Department of Biology, Concordia University, Montréal, QCH4B 1R6, Canada
- Department of Physics, Concordia University, Montréal, QCH4B 1R6, Canada
- Center for Applied Synthetic Biology, Concordia University, Montréal, QCH4B 1R6, Canada
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14
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Vashistha H, Jammal-Touma J, Singh K, Rabin Y, Salman H. Bacterial cell-size changes resulting from altering the relative expression of Min proteins. Nat Commun 2023; 14:5710. [PMID: 37714867 PMCID: PMC10504268 DOI: 10.1038/s41467-023-41487-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Accepted: 09/06/2023] [Indexed: 09/17/2023] Open
Abstract
The timing of cell division, and thus cell size in bacteria, is determined in part by the accumulation dynamics of the protein FtsZ, which forms the septal ring. FtsZ localization depends on membrane-associated Min proteins, which inhibit FtsZ binding to the cell pole membrane. Changes in the relative concentrations of Min proteins can disrupt FtsZ binding to the membrane, which in turn can delay cell division until a certain cell size is reached, in which the dynamics of Min proteins frees the cell membrane long enough to allow FtsZ ring formation. Here, we study the effect of Min proteins relative expression on the dynamics of FtsZ ring formation and cell size in individual Escherichia coli bacteria. Upon inducing overexpression of minE, cell size increases gradually to a new steady-state value. Concurrently, the time required to initiate FtsZ ring formation grows as the size approaches the new steady-state, at which point the ring formation initiates as early as before induction. These results highlight the contribution of Min proteins to cell size control, which may be partially responsible for the size fluctuations observed in bacterial populations, and may clarify how the size difference acquired during asymmetric cell division is offset.
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Affiliation(s)
- Harsh Vashistha
- Department of Physics and Astronomy, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, CT, USA
| | - Joanna Jammal-Touma
- Department of Physics and Astronomy, University of Pittsburgh, Pittsburgh, PA, USA
| | - Kulveer Singh
- Department of Physics and Institute for Nanotechnology and Advanced Materials, Bar-Ilan University, Ramat-Gan, Israel
| | - Yitzhak Rabin
- Department of Physics and Institute for Nanotechnology and Advanced Materials, Bar-Ilan University, Ramat-Gan, Israel
| | - Hanna Salman
- Department of Physics and Astronomy, University of Pittsburgh, Pittsburgh, PA, USA.
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15
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Carrall JA, Lie W, Lambert JM, Harris HH, Lai B, Dillon CT. Optimizing Arsenic Therapy by Selectively Targeting Leukemia Cells. J Med Chem 2023; 66:12101-12114. [PMID: 37594965 DOI: 10.1021/acs.jmedchem.3c00676] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/20/2023]
Abstract
Arsenic, in the simple form of arsenic trioxide, is currently marketed for the treatment of acute promyelocytic leukemia. Due to the multifaceted mechanisms of action of arsenic, it has also shown promise in other types of leukemias but is hindered by its toxic effects toward normal cells. This research has aimed to determine whether tumor-homing peptide complexes of arsenic can be designed and developed to strategically target specific cancers. The end goal is to achieve dose reduction and decreased side effects of the resultant arsenic therapeutic agent. In this article, we present the synthesis, characterization, and stability studies of a new class of As-peptide complexes designed to target leukemia. In vitro biological studies of the most stable complex show 1000 times greater toxicity toward leukemia cells over human blood cells, indicating potential for progression to in vivo studies.
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Affiliation(s)
- Judith A Carrall
- School of Chemistry and Molecular Bioscience, University of Wollongong, Wollongong 2522, New South Wales, Australia
| | - Wilford Lie
- School of Chemistry and Molecular Bioscience, University of Wollongong, Wollongong 2522, New South Wales, Australia
| | - Jacob M Lambert
- School of Chemistry and Molecular Bioscience, University of Wollongong, Wollongong 2522, New South Wales, Australia
- Molecular Horizons, University of Wollongong, Wollongong 2522, New South Wales, Australia
| | - Hugh H Harris
- School of Physical Sciences, The University of Adelaide, Adelaide 5005, South Australia, Australia
| | - Barry Lai
- X-ray Science Division, Advanced Photon Source, Argonne National Laboratory, Lemont 60439, Illinois, United States
| | - Carolyn T Dillon
- School of Chemistry and Molecular Bioscience, University of Wollongong, Wollongong 2522, New South Wales, Australia
- Molecular Horizons, University of Wollongong, Wollongong 2522, New South Wales, Australia
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16
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Biondo M, Singh A, Caselle M, Osella M. Out-of-equilibrium gene expression fluctuations in the presence of extrinsic noise. Phys Biol 2023; 20:10.1088/1478-3975/acea4e. [PMID: 37489881 PMCID: PMC10680095 DOI: 10.1088/1478-3975/acea4e] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Accepted: 07/25/2023] [Indexed: 07/26/2023]
Abstract
Cell-to-cell variability in protein concentrations is strongly affected by extrinsic noise, especially for highly expressed genes. Extrinsic noise can be due to fluctuations of several possible cellular factors connected to cell physiology and to the level of key enzymes in the expression process. However, how to identify the predominant sources of extrinsic noise in a biological system is still an open question. This work considers a general stochastic model of gene expression with extrinsic noise represented as fluctuations of the different model rates, and focuses on the out-of-equilibrium expression dynamics. Combining analytical calculations with stochastic simulations, we characterize how extrinsic noise shapes the protein variability during gene activation or inactivation, depending on the prevailing source of extrinsic variability, on its intensity and timescale. In particular, we show that qualitatively different noise profiles can be identified depending on which are the fluctuating parameters. This indicates an experimentally accessible way to pinpoint the dominant sources of extrinsic noise using time-coarse experiments.
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Affiliation(s)
- Marta Biondo
- Department of Physics, University of Turin and INFN, via P. Giuria 1, I-10125 Turin, Italy
| | - Abhyudai Singh
- Department of Electrical and Computer Engineering, Department of Biomedical Engineering, Department of Mathematical Sciences, Center for Bioinformatics and Computational Biology, University of Delaware, Newark, DE 19716, United States of America
| | - Michele Caselle
- Department of Physics, University of Turin and INFN, via P. Giuria 1, I-10125 Turin, Italy
| | - Matteo Osella
- Department of Physics, University of Turin and INFN, via P. Giuria 1, I-10125 Turin, Italy
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17
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Ji X, Lin J. Implications of differential size-scaling of cell-cycle regulators on cell size homeostasis. PLoS Comput Biol 2023; 19:e1011336. [PMID: 37506170 PMCID: PMC10411824 DOI: 10.1371/journal.pcbi.1011336] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2022] [Revised: 08/09/2023] [Accepted: 07/07/2023] [Indexed: 07/30/2023] Open
Abstract
Accurate timing of division and size homeostasis is crucial for cells. A potential mechanism for cells to decide the timing of division is the differential scaling of regulatory protein copy numbers with cell size. However, it remains unclear whether such a mechanism can lead to robust growth and division, and how the scaling behaviors of regulatory proteins influence the cell size distribution. Here we study a mathematical model combining gene expression and cell growth, in which the cell-cycle activators scale superlinearly with cell size while the inhibitors scale sublinearly. The cell divides once the ratio of their concentrations reaches a threshold value. We find that the cell can robustly grow and divide within a finite range of the threshold value with the cell size proportional to the ploidy. In a stochastic version of the model, the cell size at division is uncorrelated with that at birth. Also, the more differential the cell-size scaling of the cell-cycle regulators is, the narrower the cell-size distribution is. Intriguingly, our model with multiple regulators rationalizes the observation that after the deletion of a single regulator, the coefficient of variation of cell size remains roughly the same though the average cell size changes significantly. Our work reveals that the differential scaling of cell-cycle regulators provides a robust mechanism of cell size control.
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Affiliation(s)
- Xiangrui Ji
- Yuanpei College, Peking University, Beijing, China
| | - Jie Lin
- Center for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
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18
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Hansson KA, Eftestøl E. Scaling of nuclear numbers and their spatial arrangement in skeletal muscle cell size regulation. Mol Biol Cell 2023; 34:pe3. [PMID: 37339435 PMCID: PMC10398882 DOI: 10.1091/mbc.e22-09-0424] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Revised: 03/29/2023] [Accepted: 04/28/2023] [Indexed: 06/22/2023] Open
Abstract
Many cells display considerable functional plasticity and depend on the regulation of numerous organelles and macromolecules for their maintenance. In large cells, organelles also need to be carefully distributed to supply the cell with essential resources and regulate intracellular activities. Having multiple copies of the largest eukaryotic organelle, the nucleus, epitomizes the importance of scaling gene products to large cytoplasmic volumes in skeletal muscle fibers. Scaling of intracellular constituents within mammalian muscle fibers is, however, poorly understood, but according to the myonuclear domain hypothesis, a single nucleus supports a finite amount of cytoplasm and is thus postulated to act autonomously, causing the nuclear number to be commensurate with fiber volume. In addition, the orderly peripheral distribution of myonuclei is a hallmark of normal cell physiology, as nuclear mispositioning is associated with impaired muscle function. Because underlying structures of complex cell behaviors are commonly formalized by scaling laws and thus emphasize emerging principles of size regulation, the work presented herein offers more of a unified conceptual platform based on principles from physics, chemistry, geometry, and biology to explore cell size-dependent correlations of the largest mammalian cell by means of scaling.
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Affiliation(s)
- Kenth-Arne Hansson
- Section for Health and Exercise Physiology, Inland Norway University of Applied Sciences, 2624 Lillehammer, Norway
| | - Einar Eftestøl
- Department of Biosciences, University of Oslo, 0371 Oslo, Norway
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19
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Nieto C, Blanco SC, Vargas-García C, Singh A, Manuel PJ. PyEcoLib: a python library for simulating stochastic cell size dynamics. Phys Biol 2023; 20:10.1088/1478-3975/acd897. [PMID: 37224818 PMCID: PMC10665115 DOI: 10.1088/1478-3975/acd897] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Accepted: 05/24/2023] [Indexed: 05/26/2023]
Abstract
Recently, there has been an increasing need for tools to simulate cell size regulation due to important applications in cell proliferation and gene expression. However, implementing the simulation usually presents some difficulties, as the division has a cycle-dependent occurrence rate. In this article, we gather a recent theoretical framework inPyEcoLib, a python-based library to simulate the stochastic dynamics of the size of bacterial cells. This library can simulate cell size trajectories with an arbitrarily small sampling period. In addition, this simulator can include stochastic variables, such as the cell size at the beginning of the experiment, the cycle duration timing, the growth rate, and the splitting position. Furthermore, from a population perspective, the user can choose between tracking a single lineage or all cells in a colony. They can also simulate the most common division strategies (adder, timer, and sizer) using the division rate formalism and numerical methods. As an example of PyecoLib applications, we explain how to couple size dynamics with gene expression predicting, from simulations, how the noise in protein levels increases by increasing the noise in division timing, the noise in growth rate and the noise in cell splitting position. The simplicity of this library and its transparency about the underlying theoretical framework yield the inclusion of cell size stochasticity in complex models of gene expression.
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Affiliation(s)
- César Nieto
- Department of Electrical and Computer Engineering, University of Delaware, Newark, DE 19716, United States of America
- Department of Physics. Universidad de los Andes, Bogotá, Colombia
| | - Sergio Camilo Blanco
- Department of Mathematics and Engineering. Fundacion Universitaria Konrad Lorenz, Bogota, Colombia
| | | | - Abhyudai Singh
- Department of Electrical and Computer Engineering, Department of Biomedical Engineering and Department of Mathematical Sciences, University of Delaware, Newark, DE 19716, United States of America
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20
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Chung ES, Kar P, Kamkaew M, Amir A, Aldridge BB. Mycobacterium tuberculosis grows linearly at the single-cell level with larger variability than model organisms. bioRxiv 2023:2023.05.17.541183. [PMID: 37292927 PMCID: PMC10245742 DOI: 10.1101/2023.05.17.541183] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
The ability of bacterial pathogens to regulate growth is crucial to control homeostasis, virulence, and drug response. Yet, we do not understand the growth and cell cycle behaviors of Mycobacterium tuberculosis (Mtb), a slow-growing pathogen, at the single-cell level. Here, we use time-lapse imaging and mathematical modeling to characterize these fundamental properties of Mtb. Whereas most organisms grow exponentially at the single-cell level, we find that Mtb exhibits a unique linear growth mode. Mtb growth characteristics are highly variable from cell-to-cell, notably in their growth speeds, cell cycle timing, and cell sizes. Together, our study demonstrates that growth behavior of Mtb diverges from what we have learned from model bacteria. Instead, Mtb generates a heterogeneous population while growing slowly and linearly. Our study provides a new level of detail into how Mtb grows and creates heterogeneity, and motivates more studies of growth behaviors in bacterial pathogens.
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Abstract
The concept of phase-separation-mediated formation of biomolecular condensates provides a new framework to understand cellular organization and cooperativity-dependent cellular functions. With growing understanding of how biological systems drive phase separation and how cellular functions are encoded by biomolecular condensates, opportunities have emerged for cellular control through engineering of synthetic biomolecular condensates. In this Review, we discuss how to construct synthetic biomolecular condensates and how they can regulate cellular functions. We first describe the fundamental principles by which biomolecular components can drive phase separation. Next, we discuss the relationship between the properties of condensates and their cellular functions, which informs the design of components to create programmable synthetic condensates. Finally, we describe recent applications of synthetic biomolecular condensates for cellular control and discuss some of the design considerations and prospective applications.
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Affiliation(s)
- Yifan Dai
- Department of Biomedical Engineering, Duke University, Durham, NC USA
| | - Lingchong You
- Department of Biomedical Engineering, Duke University, Durham, NC USA
| | - Ashutosh Chilkoti
- Department of Biomedical Engineering, Duke University, Durham, NC USA
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22
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Plouviez M, Abyadeh M, Hasan M, Mirzaei M, Paulo J, Guieysse B. The proteome of Chlamydomonas reinhardtii during phosphorus depletion and repletion. ALGAL RES 2023. [DOI: 10.1016/j.algal.2023.103037] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/06/2023]
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23
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Akcan TS, Vilov S, Heinig M. Predictive model of transcriptional elongation control identifies trans regulatory factors from chromatin signatures. Nucleic Acids Res 2023; 51:1608-1624. [PMID: 36727445 PMCID: PMC9976927 DOI: 10.1093/nar/gkac1272] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Revised: 12/09/2022] [Accepted: 01/12/2023] [Indexed: 02/03/2023] Open
Abstract
Promoter-proximal Polymerase II (Pol II) pausing is a key rate-limiting step for gene expression. DNA and RNA-binding trans-acting factors regulating the extent of pausing have been identified. However, we lack a quantitative model of how interactions of these factors determine pausing, therefore the relative importance of implicated factors is unknown. Moreover, previously unknown regulators might exist. Here we address this gap with a machine learning model that accurately predicts the extent of promoter-proximal Pol II pausing from large-scale genome and transcriptome binding maps and gene annotation and sequence composition features. We demonstrate high accuracy and generalizability of the model by validation on an independent cell line which reveals the model's cell line agnostic character. Model interpretation in light of prior knowledge about molecular functions of regulatory factors confirms the interconnection of pausing with other RNA processing steps. Harnessing underlying feature contributions, we assess the relative importance of each factor, quantify their predictive effects and systematically identify previously unknown regulators of pausing. We additionally identify 16 previously unknown 7SK ncRNA interacting RNA-binding proteins predictive of pausing. Our work provides a framework to further our understanding of the regulation of the critical early steps in transcriptional elongation.
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Affiliation(s)
- Toray S Akcan
- Institute of Computational Biology, Helmholtz Zentrum München Deutsches Forschungszentrum für Gesundheit und Umwelt (GmbH), Ingolstädter Landstraße 1, 85764 Neuherberg, Germany.,Department of Computer Science, TUM School of Computation, Information and Technology, Technical University Munich, Munich, Germany
| | - Sergey Vilov
- Institute of Computational Biology, Helmholtz Zentrum München Deutsches Forschungszentrum für Gesundheit und Umwelt (GmbH), Ingolstädter Landstraße 1, 85764 Neuherberg, Germany
| | - Matthias Heinig
- Institute of Computational Biology, Helmholtz Zentrum München Deutsches Forschungszentrum für Gesundheit und Umwelt (GmbH), Ingolstädter Landstraße 1, 85764 Neuherberg, Germany.,Department of Computer Science, TUM School of Computation, Information and Technology, Technical University Munich, Munich, Germany.,DZHK (German Centre for Cardiovascular Research), Munich Heart Association, Partner Site Munich, 10785 Berlin, Germany
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24
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Bagley JR, Denes LT, McCarthy JJ, Wang ET, Murach KA. The myonuclear domain in adult skeletal muscle fibres: past, present and future. J Physiol 2023; 601:723-741. [PMID: 36629254 PMCID: PMC9931674 DOI: 10.1113/jp283658] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Accepted: 01/06/2023] [Indexed: 01/12/2023] Open
Abstract
Most cells in the body are mononuclear whereas skeletal muscle fibres are uniquely multinuclear. The nuclei of muscle fibres (myonuclei) are usually situated peripherally which complicates the equitable distribution of gene products. Myonuclear abundance can also change under conditions such as hypertrophy and atrophy. Specialised zones in muscle fibres have different functions and thus distinct synthetic demands from myonuclei. The complex structure and regulatory requirements of multinuclear muscle cells understandably led to the hypothesis that myonuclei govern defined 'domains' to maintain homeostasis and facilitate adaptation. The purpose of this review is to provide historical context for the myonuclear domain and evaluate its veracity with respect to mRNA and protein distribution resulting from myonuclear transcription. We synthesise insights from past and current in vitro and in vivo genetically modified models for studying the myonuclear domain under dynamic conditions. We also cover the most contemporary knowledge on mRNA and protein transport in muscle cells. Insights from emerging technologies such as single myonuclear RNA-sequencing further inform our discussion of the myonuclear domain. We broadly conclude: (1) the myonuclear domain can be flexible during muscle fibre growth and atrophy, (2) the mechanisms and role of myonuclear loss and motility deserve further consideration, (3) mRNA in muscle is actively transported via microtubules and locally restricted, but proteins may travel far from a myonucleus of origin and (4) myonuclear transcriptional specialisation extends beyond the classic neuromuscular and myotendinous populations. A deeper understanding of the myonuclear domain in muscle may promote effective therapies for ageing and disease.
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Affiliation(s)
- James R. Bagley
- Muscle Physiology Laboratory, Department of Kinesiology, San Francisco State University, San Francisco, California
| | | | - John J. McCarthy
- The Center for Muscle Biology, University of Kentucky, Lexington, Kentucky
- Department of Physiology, College of Medicine, University of Kentucky
| | - Eric T. Wang
- Department of Molecular Genetics and Microbiology, Center for NeuroGenetics, University of Florida, Gainesville, Florida
- Myology Institute, University of Florida
- Genetics Institute, University of Florida
| | - Kevin A. Murach
- Exercise Science Research Center, Department of Health, Human Performance, and Recreation, University of Arkansas, Fayetteville, Arkansas
- Cell and Molecular Biology Graduate Program, University of Arkansas
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25
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Subramanian A, Alperovich M, Yang Y, Li B. Biology-inspired data-driven quality control for scientific discovery in single-cell transcriptomics. Genome Biol 2022; 23:267. [PMID: 36575523 PMCID: PMC9793662 DOI: 10.1186/s13059-022-02820-w] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2021] [Accepted: 11/23/2022] [Indexed: 12/28/2022] Open
Abstract
BACKGROUND Quality control (QC) of cells, a critical first step in single-cell RNA sequencing data analysis, has largely relied on arbitrarily fixed data-agnostic thresholds applied to QC metrics such as gene complexity and fraction of reads mapping to mitochondrial genes. The few existing data-driven approaches perform QC at the level of samples or studies without accounting for biological variation. RESULTS We first demonstrate that QC metrics vary with both tissue and cell types across technologies, study conditions, and species. We then propose data-driven QC (ddqc), an unsupervised adaptive QC framework to perform flexible and data-driven QC at the level of cell types while retaining critical biological insights and improved power for downstream analysis. ddqc applies an adaptive threshold based on the median absolute deviation on four QC metrics (gene and UMI complexity, fraction of reads mapping to mitochondrial and ribosomal genes). ddqc retains over a third more cells when compared to conventional data-agnostic QC filters. Finally, we show that ddqc recovers biologically meaningful trends in gradation of gene complexity among cell types that can help answer questions of biological interest such as which cell types express the least and most number of transcripts overall, and ribosomal transcripts specifically. CONCLUSIONS ddqc retains cell types such as metabolically active parenchymal cells and specialized cells such as neutrophils which are often lost by conventional QC. Taken together, our work proposes a revised paradigm to quality filtering best practices-iterative QC, providing a data-driven QC framework compatible with observed biological diversity.
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Affiliation(s)
- Ayshwarya Subramanian
- grid.66859.340000 0004 0546 1623Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA USA ,grid.38142.3c000000041936754XBrigham and Womens’s Hospital, Harvard Medical School, Boston, USA
| | - Mikhail Alperovich
- grid.66859.340000 0004 0546 1623Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA USA ,grid.116068.80000 0001 2341 2786MIT PRIMES, Massachusetts Institute of Technology, Cambridge, MA USA ,Lexington High School, Lexington, MA USA ,grid.422478.f0000 0000 9142 997XPresent Address: Wake Technical Community College, Raleigh, USA
| | - Yiming Yang
- grid.66859.340000 0004 0546 1623Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA USA ,grid.32224.350000 0004 0386 9924Center for Immunology and Inflammatory Diseases, Department of Medicine, Massachusetts General Hospital, Boston, MA 02114 USA ,grid.418158.10000 0004 0534 4718Present Address: Department of Cellular and Tissue Genomics, Genentech Inc., South San Francisco, CA USA
| | - Bo Li
- grid.66859.340000 0004 0546 1623Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA USA ,grid.32224.350000 0004 0386 9924Center for Immunology and Inflammatory Diseases, Department of Medicine, Massachusetts General Hospital, Boston, MA 02114 USA ,grid.418158.10000 0004 0534 4718Present Address: Department of Cellular and Tissue Genomics, Genentech Inc., South San Francisco, CA USA ,grid.38142.3c000000041936754XDepartment of Medicine, Harvard Medical School, Boston, MA 02115 USA
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26
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Balakrishnan R, Mori M, Segota I, Zhang Z, Aebersold R, Ludwig C, Hwa T. Principles of gene regulation quantitatively connect DNA to RNA and proteins in bacteria. Science 2022; 378:eabk2066. [PMID: 36480614 PMCID: PMC9804519 DOI: 10.1126/science.abk2066] [Citation(s) in RCA: 34] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Protein concentrations are set by a complex interplay between gene-specific regulatory processes and systemic factors, including cell volume and shared gene expression machineries. Elucidating this interplay is crucial for discerning and designing gene regulatory systems. We quantitatively characterized gene-specific and systemic factors that affect transcription and translation genome-wide for Escherichia coli across many conditions. The results revealed two design principles that make regulation of gene expression insulated from concentrations of shared machineries: RNA polymerase activity is fine-tuned to match translational output, and translational characteristics are similar across most messenger RNAs (mRNAs). Consequently, in bacteria, protein concentration is set primarily at the promoter level. A simple mathematical formula relates promoter activities and protein concentrations across growth conditions, enabling quantitative inference of gene regulation from omics data.
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Affiliation(s)
- Rohan Balakrishnan
- Department of Physics, University of California at San Diego, La Jolla, California 92093-0374
| | - Matteo Mori
- Department of Physics, University of California at San Diego, La Jolla, California 92093-0374
| | - Igor Segota
- Departments of Medicine and Pharmacology, University of California at San Diego, La Jolla, California 92093
| | - Zhongge Zhang
- Section of Molecular Biology, Division of Biological Sciences, University of California at San Diego, La Jolla, California 92093
| | - Ruedi Aebersold
- Faculty of Science, University of Zurich, Zurich, Switzerland.,Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Switzerland
| | - Christina Ludwig
- Bavarian Center for Biomolecular Mass Spectrometry (BayBioMS), Technical University of Munich (TUM), Freising, Germany
| | - Terence Hwa
- Department of Physics, University of California at San Diego, La Jolla, California 92093-0374.,Section of Molecular Biology, Division of Biological Sciences, University of California at San Diego, La Jolla, California 92093.,CORRESPONDING AUTHOR: Terence Hwa ()
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27
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Abstract
The bacterium Escherichia coli initiates replication once per cell cycle at a precise volume per origin and adds an on average constant volume between successive initiation events, independent of the initiation size. Yet, a molecular model that can explain these observations has been lacking. Experiments indicate that E. coli controls replication initiation via titration and activation of the initiator protein DnaA. Here, we study by mathematical modelling how these two mechanisms interact to generate robust replication-initiation cycles. We first show that a mechanism solely based on titration generates stable replication cycles at low growth rates, but inevitably causes premature reinitiation events at higher growth rates. In this regime, the DnaA activation switch becomes essential for stable replication initiation. Conversely, while the activation switch alone yields robust rhythms at high growth rates, titration can strongly enhance the stability of the switch at low growth rates. Our analysis thus predicts that both mechanisms together drive robust replication cycles at all growth rates. In addition, it reveals how an origin-density sensor yields adder correlations.
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Affiliation(s)
- Mareike Berger
- grid.417889.b0000 0004 0646 2441Biochemical Networks Group, Department of Information in Matter, AMOLF, 1098 XG Amsterdam, The Netherlands
| | - Pieter Rein ten Wolde
- grid.417889.b0000 0004 0646 2441Biochemical Networks Group, Department of Information in Matter, AMOLF, 1098 XG Amsterdam, The Netherlands
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28
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Abstract
The most fundamental feature of cellular form is size, which sets the scale of all cell biological processes. Growth, form, and function are all necessarily linked in cell biology, but we often do not understand the underlying molecular mechanisms nor their specific functions. Here, we review progress toward determining the molecular mechanisms that regulate cell size in yeast, animals, and plants, as well as progress toward understanding the function of cell size regulation. It has become increasingly clear that the mechanism of cell size regulation is deeply intertwined with basic mechanisms of biosynthesis, and how biosynthesis can be scaled (or not) in proportion to cell size. Finally, we highlight recent findings causally linking aberrant cell size regulation to cellular senescence and their implications for cancer therapies.
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Affiliation(s)
- Shicong Xie
- Department of Biology, Stanford University, Stanford, California, USA;
| | - Matthew Swaffer
- Department of Biology, Stanford University, Stanford, California, USA;
| | - Jan M Skotheim
- Department of Biology, Stanford University, Stanford, California, USA;
- Chan Zuckerberg Biohub, San Francisco, California, USA
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29
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Jia C, Singh A, Grima R. Concentration fluctuations in growing and dividing cells: Insights into the emergence of concentration homeostasis. PLoS Comput Biol 2022; 18:e1010574. [PMID: 36194626 DOI: 10.1371/journal.pcbi.1010574] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Revised: 10/14/2022] [Accepted: 09/14/2022] [Indexed: 11/19/2022] Open
Abstract
Intracellular reaction rates depend on concentrations and hence their levels are often regulated. However classical models of stochastic gene expression lack a cell size description and cannot be used to predict noise in concentrations. Here, we construct a model of gene product dynamics that includes a description of cell growth, cell division, size-dependent gene expression, gene dosage compensation, and size control mechanisms that can vary with the cell cycle phase. We obtain expressions for the approximate distributions and power spectra of concentration fluctuations which lead to insight into the emergence of concentration homeostasis. We find that (i) the conditions necessary to suppress cell division-induced concentration oscillations are difficult to achieve; (ii) mRNA concentration and number distributions can have different number of modes; (iii) two-layer size control strategies such as sizer-timer or adder-timer are ideal because they maintain constant mean concentrations whilst minimising concentration noise; (iv) accurate concentration homeostasis requires a fine tuning of dosage compensation, replication timing, and size-dependent gene expression; (v) deviations from perfect concentration homeostasis show up as deviations of the concentration distribution from a gamma distribution. Some of these predictions are confirmed using data for E. coli, fission yeast, and budding yeast.
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30
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Lanz MC, Zatulovskiy E, Swaffer MP, Zhang L, Ilerten I, Zhang S, You DS, Marinov G, McAlpine P, Elias JE, Skotheim JM. Increasing cell size remodels the proteome and promotes senescence. Mol Cell 2022; 82:3255-3269.e8. [PMID: 35987199 PMCID: PMC9444988 DOI: 10.1016/j.molcel.2022.07.017] [Citation(s) in RCA: 42] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Revised: 06/06/2022] [Accepted: 07/25/2022] [Indexed: 01/10/2023]
Abstract
Cell size is tightly controlled in healthy tissues, but it is unclear how deviations in cell size affect cell physiology. To address this, we measured how the cell's proteome changes with increasing cell size. Size-dependent protein concentration changes are widespread and predicted by subcellular localization, size-dependent mRNA concentrations, and protein turnover. As proliferating cells grow larger, concentration changes typically associated with cellular senescence are increasingly pronounced, suggesting that large size may be a cause rather than just a consequence of cell senescence. Consistent with this hypothesis, larger cells are prone to replicative, DNA-damage-induced, and CDK4/6i-induced senescence. Size-dependent changes to the proteome, including those associated with senescence, are not observed when an increase in cell size is accompanied by an increase in ploidy. Together, our findings show how cell size could impact many aspects of cell physiology by remodeling the proteome and provide a rationale for cell size control and polyploidization.
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Affiliation(s)
- Michael C Lanz
- Department of Biology, Stanford University, Stanford, CA 94305, USA; Chan Zuckerberg Biohub, Stanford, CA 94305, USA
| | | | | | | | - Ilayda Ilerten
- Department of Biology, Stanford University, Stanford, CA 94305, USA
| | - Shuyuan Zhang
- Department of Biology, Stanford University, Stanford, CA 94305, USA
| | - Dong Shin You
- Department of Biology, Stanford University, Stanford, CA 94305, USA
| | - Georgi Marinov
- Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | | | | | - Jan M Skotheim
- Department of Biology, Stanford University, Stanford, CA 94305, USA.
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31
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Abstract
Cells adopt a size that is optimal for their function, and pushing them beyond this limit can cause cell aging and death by senescence or reduce proliferative potential. However, by increasing their genome copy number (ploidy), cells can increase their size dramatically and homeostatically maintain physiological properties such as biosynthesis rate. Recent studies investigating the relationship between cell size and rates of biosynthesis and metabolism under normal, polyploid, and pathological conditions are revealing new insights into how cells attain the best function or fitness for their size by tuning processes including transcription, translation, and mitochondrial respiration. A new frontier is to connect single-cell scaling relationships with tissue and whole-organism physiology, which promises to reveal molecular and evolutionary principles underlying the astonishing diversity of size observed across the tree of life.
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Affiliation(s)
- Clotilde Cadart
- Molecular and Cell Biology Department, University of California, Berkeley, Berkeley, CA 94720-3200
| | - Rebecca Heald
- Molecular and Cell Biology Department, University of California, Berkeley, Berkeley, CA 94720-3200
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32
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Pérez-Ortín JE, Chávez S. Nucleo-cytoplasmic shuttling of RNA-binding factors: mRNA buffering and beyond. Biochim Biophys Acta Gene Regul Mech 2022; 1865:194849. [PMID: 35907432 DOI: 10.1016/j.bbagrm.2022.194849] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/13/2022] [Revised: 07/18/2022] [Accepted: 07/23/2022] [Indexed: 06/15/2023]
Abstract
Gene expression is a highly regulated process that adapts RNAs and proteins content to the cellular context. Under steady-state conditions, mRNA homeostasis is robustly maintained by tight controls that act on both nuclear transcription and cytoplasmic mRNA stability. In recent years, it has been revealed that several RNA-binding proteins (RBPs) that perform functions in mRNA decay can move to the nucleus and regulate transcription. The RBPs involved in transcription can also travel to the cytoplasm and regulate mRNA degradation and/or translation. The multifaceted functions of these shuttling nucleo-cytoplasm RBPs have raised the possibility that they can act as mRNA metabolism coordinators. In addition, this indicates the existence of crosstalk mechanisms between the enzymatic machineries that drive the different mRNA life-cycle phases. The buffering of the mRNA concentration is the best known consequence of a transcription-degradation crosstalk counteraction, but alternative ways of RBP action can also imply enhanced gene regulation.
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Affiliation(s)
- José E Pérez-Ortín
- Instituto de Biotecnología y Biomedicina (Biotecmed), Facultad de Biológicas, Universitat de València. C/Dr. Moliner 50, E46100 Burjassot, Spain.
| | - Sebastián Chávez
- Departamento de Genética, Universidad de Sevilla and Instituto de Biomedicina de Sevilla (IBiS), Hospital Virgen del Rocío-CSIC-Universidad de Sevilla, 41013 Seville, Spain; Dirección de Evaluación y Acreditación, Agencia Andaluza del Conocimiento, Doña Berenguela s/n, planta 3ª C.P., 14006 Córdoba, Spain
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33
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Berry S, Pelkmans L. Mechanisms of cellular mRNA transcript homeostasis. Trends Cell Biol 2022:S0962-8924(22)00120-9. [PMID: 35660047 DOI: 10.1016/j.tcb.2022.05.003] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Revised: 05/08/2022] [Accepted: 05/09/2022] [Indexed: 11/20/2022]
Abstract
For most genes, mRNA transcript abundance scales with cell size to ensure a constant concentration. Scaling of mRNA synthesis rates with cell size plays an important role, with regulation of the activity and abundance of RNA polymerase II (Pol II) now emerging as a key point of control. However, there is also considerable evidence for feedback mechanisms that kinetically couple the rates of mRNA synthesis, nuclear export, and degradation to allow cells to compensate for changes in one by adjusting the others. Researchers are beginning to integrate results from these different fields to reveal the mechanisms underlying transcript homeostasis. This will be crucial for moving beyond our current understanding of relative gene expression towards an appreciation of how absolute transcript levels are linked to other aspects of the cellular phenotype.
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34
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Berry S, Müller M, Rai A, Pelkmans L. Feedback from nuclear RNA on transcription promotes robust RNA concentration homeostasis in human cells. Cell Syst 2022; 13:454-470.e15. [PMID: 35613616 DOI: 10.1016/j.cels.2022.04.005] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2021] [Revised: 12/13/2021] [Accepted: 04/21/2022] [Indexed: 12/18/2022]
Abstract
RNA concentration homeostasis involves coordinating RNA abundance and synthesis rates with cell size. Here, we study this in human cells by combining genome-wide perturbations with quantitative single-cell measurements. Despite relative ease in perturbing RNA synthesis, we find that RNA concentrations generally remain highly constant. Perturbations that would be expected to increase nuclear mRNA levels, including those targeting nuclear mRNA degradation or export, result in downregulation of RNA synthesis. This is associated with reduced abundance of transcription-associated proteins and protein states that are normally coordinated with RNA production in single cells, including RNA polymerase II (RNA Pol II) itself. Acute perturbations, elevation of nuclear mRNA levels, and mathematical modeling indicate that mammalian cells achieve robust mRNA concentration homeostasis by the mRNA-based negative feedback on transcriptional activity in the nucleus. This ultimately acts to coordinate RNA Pol II abundance with nuclear mRNA degradation and export rates and may underpin the scaling of mRNA abundance with cell size.
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Affiliation(s)
- Scott Berry
- Department of Molecular Life Sciences, University of Zurich, Zurich, Switzerland; EMBL Australia Node in Single Molecule Science, School of Medical Sciences, University of New South Wales, Sydney, NSW, Australia.
| | - Micha Müller
- Department of Molecular Life Sciences, University of Zurich, Zurich, Switzerland
| | - Arpan Rai
- Department of Molecular Life Sciences, University of Zurich, Zurich, Switzerland
| | - Lucas Pelkmans
- Department of Molecular Life Sciences, University of Zurich, Zurich, Switzerland.
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35
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Messerschmidt VL, Chintapula U, Bonetesta F, Laboy-Segarra S, Naderi A, Nguyen KT, Cao H, Mager E, Lee J. In vivo Evaluation of Non-viral NICD Plasmid-Loaded PLGA Nanoparticles in Developing Zebrafish to Improve Cardiac Functions. Front Physiol 2022; 13:819767. [PMID: 35283767 PMCID: PMC8906778 DOI: 10.3389/fphys.2022.819767] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Accepted: 01/07/2022] [Indexed: 12/12/2022] Open
Abstract
In the era of the advanced nanomaterials, use of nanoparticles has been highlighted in biomedical research. However, the demonstration of DNA plasmid delivery with nanoparticles for in vivo gene delivery experiments must be carefully tested due to many possible issues, including toxicity. The purpose of the current study was to deliver a Notch Intracellular Domain (NICD)-encoded plasmid via poly(lactic-co-glycolic acid) (PLGA) nanoparticles and to investigate the toxic environmental side effects for an in vivo experiment. In addition, we demonstrated the target delivery to the endothelium, including the endocardial layer, which is challenging to manipulate gene expression for cardiac functions due to the beating heart and rapid blood pumping. For this study, we used a zebrafish animal model and exposed it to nanoparticles at varying concentrations to observe for specific malformations over time for toxic effects of PLGA nanoparticles as a delivery vehicle. Our nanoparticles caused significantly less malformations than the positive control, ZnO nanoparticles. Additionally, the NICD plasmid was successfully delivered by PLGA nanoparticles and significantly increased Notch signaling related genes. Furthermore, our image based deep-learning analysis approach evaluated that the antibody conjugated nanoparticles were successfully bound to the endocardium to overexpress Notch related genes and improve cardiac function such as ejection fraction, fractional shortening, and cardiac output. This research demonstrates that PLGA nanoparticle-mediated target delivery to upregulate Notch related genes which can be a potential therapeutic approach with minimum toxic effects.
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Affiliation(s)
- Victoria L Messerschmidt
- Department of Bioengineering, University of Texas at Arlington, Arlington, TX, United States.,University of Texas Southwestern Medical Center, Dallas, TX, United States
| | - Uday Chintapula
- Department of Bioengineering, University of Texas at Arlington, Arlington, TX, United States.,University of Texas Southwestern Medical Center, Dallas, TX, United States
| | - Fabrizio Bonetesta
- Department of Biological Sciences, University of North Texas, Denton, TX, United States
| | - Samantha Laboy-Segarra
- Department of Bioengineering, University of Texas at Arlington, Arlington, TX, United States.,University of Texas Southwestern Medical Center, Dallas, TX, United States
| | - Amir Naderi
- Department of Electrical Engineering and Computer Science, University of California, Irvine, Irvine, CA, United States
| | - Kytai T Nguyen
- Department of Bioengineering, University of Texas at Arlington, Arlington, TX, United States.,University of Texas Southwestern Medical Center, Dallas, TX, United States
| | - Hung Cao
- Department of Electrical Engineering and Computer Science, University of California, Irvine, Irvine, CA, United States
| | - Edward Mager
- Department of Biological Sciences, University of North Texas, Denton, TX, United States
| | - Juhyun Lee
- Department of Bioengineering, University of Texas at Arlington, Arlington, TX, United States.,University of Texas Southwestern Medical Center, Dallas, TX, United States
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36
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Abstract
Despite extensive investigation demonstrating that resource competition can significantly alter the deterministic behaviors of synthetic gene circuits, it remains unclear how resource competition contributes to the gene expression noise and how this noise can be controlled. Utilizing a two-gene circuit as a prototypical system, we uncover a surprising double-edged role of resource competition in gene expression noise: competition decreases noise through introducing a resource constraint but generates its own type of noise which we name as "resource competitive noise." Utilization of orthogonal resources enables retainment of the noise reduction conferred by resource constraint while removing the added resource competitive noise. The noise reduction effects are studied using three negative feedback types: negatively competitive regulation (NCR), local, and global controllers, each having four placement architectures in the protein biosynthesis pathway (mRNA or protein inhibition on transcription or translation). Our results show that both local and NCR controllers with mRNA-mediated inhibition are efficacious at reducing noise, with NCR controllers demonstrating a superior noise-reduction capability. We also find that combining feedback controllers with orthogonal resources can improve the local controllers. This work provides deep insights into the origin of stochasticity in gene circuits with resource competition and guidance for developing effective noise control strategies.
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Affiliation(s)
- Hanah Goetz
- School for Engineering of Matter, Transport and EnergyArizona State UniversityTempeAZ85287USA
| | - Austin Stone
- School of Biological and Health Systems EngineeringArizona State UniversityTempeAZ85287USA
| | - Rong Zhang
- School of Biological and Health Systems EngineeringArizona State UniversityTempeAZ85287USA
| | - Ying‐Cheng Lai
- School of Electrical, Computer and Energy EngineeringArizona State UniversityTempeAZ85287USA
- Department of PhysicsArizona State UniversityTempeAZ85287USA
| | - Xiao‐Jun Tian
- School of Biological and Health Systems EngineeringArizona State UniversityTempeAZ85287USA
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37
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Sassi AS, Garcia-Alcala M, Aldana M, Tu Y. Protein concentration fluctuations in the high expression regime: Taylor's law and its mechanistic origin. Phys Rev X 2022; 12:011051. [PMID: 35756903 PMCID: PMC9233241 DOI: 10.1103/physrevx.12.011051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Protein concentration in a living cell fluctuates over time due to noise in growth and division processes. In the high expression regime, variance of the protein concentration in a cell was found to scale with the square of the mean, which belongs to a general phenomenon called Taylor's law (TL). To understand the origin for these fluctuations, we measured protein concentration dynamics in single E. coli cells from a set of strains with a variable expression of fluorescent proteins. The protein expression is controlled by a set of constitutive promoters with different strength, which allows to change the expression level over 2 orders of magnitude without introducing noise from fluctuations in transcription regulators. Our data confirms the square TL, but the prefactor A has a cell-to-cell variation independent of the promoter strength. Distributions of the normalized protein concentration for different promoters are found to collapse onto the same curve. To explain these observations, we used a minimal mechanistic model to describe the stochastic growth and division processes in a single cell with a feedback mechanism for regulating cell division. In the high expression regime where extrinsic noise dominates, the model reproduces our experimental results quantitatively. By using a mean-field approximation in the minimal model, we showed that the stochastic dynamics of protein concentration is described by a Langevin equation with multiplicative noise. The Langevin equation has a scale invariance which is responsible for the square TL. By solving the Langevin equation, we obtained an analytical solution for the protein concentration distribution function that agrees with experiments. The solution shows explicitly how the prefactor A depends on strength of different noise sources, which explains its cell-to-cell variability. By using this approach to analyze our single-cell data, we found that the noise in production rate dominates the noise from cell division. The deviation from the square TL in the low expression regime can also be captured in our model by including intrinsic noise in the production rate.
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Affiliation(s)
| | - Mayra Garcia-Alcala
- Department of Molecular and Cellular Biology, John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA
- Instituto de Ciencias Físicas, Universidad Nacional Autónoma de México, Cuernavaca, Morelos 62210, México
| | - Maximino Aldana
- Instituto de Ciencias Físicas, Universidad Nacional Autónoma de México, Cuernavaca, Morelos 62210, México
- Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, Ciudad de México 04510, México
| | - Yuhai Tu
- IBM T.J. Watson Research Center, Yorktown Heights, NY 10598, U.S.A
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38
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Zhu J, Wolf ID, Dulberger CL, Won HI, Kester JC, Judd JA, Wirth SE, Clark RR, Li Y, Luo Y, Gray TA, Wade JT, Derbyshire KM, Fortune SM, Rubin EJ. Spatiotemporal localization of proteins in mycobacteria. Cell Rep 2021; 37:110154. [PMID: 34965429 DOI: 10.1016/j.celrep.2021.110154] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2021] [Revised: 08/16/2021] [Accepted: 12/01/2021] [Indexed: 01/10/2023] Open
Abstract
Although prokaryotic organisms lack traditional organelles, they must still organize cellular structures in space and time, challenges that different species solve differently. To systematically define the subcellular architecture of mycobacteria, we perform high-throughput imaging of a library of fluorescently tagged proteins expressed in Mycobacterium smegmatis and develop a customized computational pipeline, MOMIA and GEMATRIA, to analyze these data. Our results establish a spatial organization network of over 700 conserved mycobacterial proteins and reveal a coherent localization pattern for many proteins of known function, including those in translation, energy metabolism, cell growth and division, as well as proteins of unknown function. Furthermore, our pipeline exploits morphologic proxies to enable a pseudo-temporal approximation of protein localization and identifies previously uncharacterized cell-cycle-dependent dynamics of essential mycobacterial proteins. Collectively, these data provide a systems perspective on the subcellular organization of mycobacteria and provide tools for the analysis of bacteria with non-standard growth characteristics. Zhu et al. develop a two-stage image analysis pipeline, MOMIA and GEMATRIA, that efficiently models the spatial and temporal dynamics of over 700 conserved proteins in M. smegmatis. Through the analysis they report spatial constraints of mycobacterial ribosomes and membrane complexes and reconstruct temporal dynamics from still image data.
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39
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Pollak N, Lindner A, Imig D, Kuritz K, Fritze JS, Decker L, Heinrich I, Stadager J, Eisler S, Stöhr D, Allgöwer F, Scheurich P, Rehm M. Cell cycle progression and transmitotic apoptosis resistance promote escape from extrinsic apoptosis. J Cell Sci 2021; 134:273757. [PMID: 34806752 DOI: 10.1242/jcs.258966] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2021] [Accepted: 11/02/2021] [Indexed: 11/20/2022] Open
Abstract
Extrinsic apoptosis relies on TNF-family receptor activation by immune cells or receptor-activating drugs. Here, we monitored cell cycle progression at a resolution of minutes to relate apoptosis kinetics and cell-to-cell heterogeneities in death decisions to cell cycle phases. Interestingly, we found that cells in S phase delay TRAIL receptor-induced death in favour of mitosis, thereby passing on an apoptosis-primed state to their offspring. This translates into two distinct fates, apoptosis execution post mitosis or cell survival from inefficient apoptosis. Transmitotic resistance is linked to Mcl-1 upregulation and its increased accumulation at mitochondria from mid-S phase onwards, which allows cells to pass through mitosis with activated caspase-8, and with cells escaping apoptosis after mitosis sustaining sublethal DNA damage. Antagonizing Mcl-1 suppresses cell cycle-dependent delays in apoptosis, prevents apoptosis-resistant progression through mitosis and averts unwanted survival after apoptosis induction. Cell cycle progression therefore modulates signal transduction during extrinsic apoptosis, with Mcl-1 governing decision making between death, proliferation and survival. Cell cycle progression thus is a crucial process from which cell-to-cell heterogeneities in fates and treatment outcomes emerge in isogenic cell populations during extrinsic apoptosis. This article has an associated First Person interview with the first author of the paper.
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Affiliation(s)
- Nadine Pollak
- Institute of Cell Biology and Immunology, University of Stuttgart, Allmandring 31, 70569 Stuttgart, Germany.,Stuttgart Research Center Systems Biology, University of Stuttgart, Nobelstrasse 15, 70569 Stuttgart, Germany
| | - Aline Lindner
- Institute of Cell Biology and Immunology, University of Stuttgart, Allmandring 31, 70569 Stuttgart, Germany
| | - Dirke Imig
- Institute for Systems Theory and Automatic Control, University of Stuttgart, Pfaffenwaldring 9, 70569 Stuttgart, Germany
| | - Karsten Kuritz
- Institute for Systems Theory and Automatic Control, University of Stuttgart, Pfaffenwaldring 9, 70569 Stuttgart, Germany
| | - Jacques S Fritze
- Institute of Cell Biology and Immunology, University of Stuttgart, Allmandring 31, 70569 Stuttgart, Germany
| | - Lorena Decker
- Institute of Cell Biology and Immunology, University of Stuttgart, Allmandring 31, 70569 Stuttgart, Germany
| | - Isabel Heinrich
- Institute of Cell Biology and Immunology, University of Stuttgart, Allmandring 31, 70569 Stuttgart, Germany
| | - Jannis Stadager
- Institute of Cell Biology and Immunology, University of Stuttgart, Allmandring 31, 70569 Stuttgart, Germany
| | - Stephan Eisler
- Stuttgart Research Center Systems Biology, University of Stuttgart, Nobelstrasse 15, 70569 Stuttgart, Germany
| | - Daniela Stöhr
- Institute of Cell Biology and Immunology, University of Stuttgart, Allmandring 31, 70569 Stuttgart, Germany
| | - Frank Allgöwer
- Stuttgart Research Center Systems Biology, University of Stuttgart, Nobelstrasse 15, 70569 Stuttgart, Germany.,Institute for Systems Theory and Automatic Control, University of Stuttgart, Pfaffenwaldring 9, 70569 Stuttgart, Germany
| | - Peter Scheurich
- Institute of Cell Biology and Immunology, University of Stuttgart, Allmandring 31, 70569 Stuttgart, Germany
| | - Markus Rehm
- Institute of Cell Biology and Immunology, University of Stuttgart, Allmandring 31, 70569 Stuttgart, Germany.,Stuttgart Research Center Systems Biology, University of Stuttgart, Nobelstrasse 15, 70569 Stuttgart, Germany
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40
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Kar P, Tiruvadi-Krishnan S, Männik J, Männik J, Amir A. Distinguishing different modes of growth using single-cell data. eLife 2021; 10:72565. [PMID: 34854811 PMCID: PMC8727026 DOI: 10.7554/elife.72565] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2021] [Accepted: 11/21/2021] [Indexed: 12/21/2022] Open
Abstract
Collection of high-throughput data has become prevalent in biology. Large datasets allow the use of statistical constructs such as binning and linear regression to quantify relationships between variables and hypothesize underlying biological mechanisms based on it. We discuss several such examples in relation to single-cell data and cellular growth. In particular, we show instances where what appears to be ordinary use of these statistical methods leads to incorrect conclusions such as growth being non-exponential as opposed to exponential and vice versa. We propose that the data analysis and its interpretation should be done in the context of a generative model, if possible. In this way, the statistical methods can be validated either analytically or against synthetic data generated via the use of the model, leading to a consistent method for inferring biological mechanisms from data. On applying the validated methods of data analysis to infer cellular growth on our experimental data, we find the growth of length in E. coli to be non-exponential. Our analysis shows that in the later stages of the cell cycle the growth rate is faster than exponential.
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Affiliation(s)
- Prathitha Kar
- Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, United States.,Department of Chemistry and Chemical Biology, Harvard University, Cambridge, United States
| | | | - Jaana Männik
- Department of Physics and Astronomy, University of Tennessee, Knoxville, United States
| | - Jaan Männik
- Department of Physics and Astronomy, University of Tennessee, Knoxville, United States
| | - Ariel Amir
- Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, United States
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41
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Wang Q, Lin J. Heterogeneous recruitment abilities to RNA polymerases generate nonlinear scaling of gene expression with cell volume. Nat Commun 2021; 12:6852. [PMID: 34824198 PMCID: PMC8617254 DOI: 10.1038/s41467-021-26952-y] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2021] [Accepted: 10/27/2021] [Indexed: 11/09/2022] Open
Abstract
While most genes' expression levels are proportional to cell volumes, some genes exhibit nonlinear scaling between their expression levels and cell volume. Therefore, their mRNA and protein concentrations change as the cell volume increases, which often have crucial biological functions such as cell-cycle regulation. However, the biophysical mechanism underlying the nonlinear scaling between gene expression and cell volume is still unclear. In this work, we show that the nonlinear scaling is a direct consequence of the heterogeneous recruitment abilities of promoters to RNA polymerases based on a gene expression model at the whole-cell level. Those genes with weaker (stronger) recruitment abilities than the average ability spontaneously exhibit superlinear (sublinear) scaling with cell volume. Analysis of the promoter sequences and the nonlinear scaling of Saccharomyces cerevisiae's mRNA levels shows that motifs associated with transcription regulation are indeed enriched in genes exhibiting nonlinear scaling, in concert with our model.
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Affiliation(s)
- Qirun Wang
- Center for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, 100871, China
| | - Jie Lin
- Center for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, 100871, China.
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, 100871, China.
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Mittli D, Tukacs V, Micsonai A, Ravasz L, Kardos J, Juhász G, Kékesi KA. The Single-Cell Transcriptomic Analysis of Prefrontal Pyramidal Cells and Interneurons Reveals the Neuronal Expression of Genes Encoding Antimicrobial Peptides and Immune Proteins. Front Immunol 2021; 12:749433. [PMID: 34759929 PMCID: PMC8574171 DOI: 10.3389/fimmu.2021.749433] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Accepted: 10/06/2021] [Indexed: 12/30/2022] Open
Abstract
The investigation of the molecular background of direct communication of neurons and immune cells in the brain is an important issue for understanding physiological and pathological processes in the nervous system. Direct contacts between brain-infiltrating immune cells and neurons, and the neuromodulatory effect of immune cell-derived regulatory peptides are well established. Several aspects of the role of immune and glial cells in the direct neuro-immune communication are also well known; however, there remain many questions regarding the molecular details of signaling from neurons to immune cells. Thus, we report here on the neuronal expression of genes encoding antimicrobial and immunomodulatory peptides, as well as proteins of immune cell-specific activation and communication mechanisms. In the present study, we analyzed the single-cell sequencing data of our previous transcriptomic work, obtained from electrophysiologically identified pyramidal cells and interneurons of the murine prefrontal cortex. We filtered out the genes that may be associated with the direct communication between immune cells and neurons and examined their expression pattern in the neuronal transcriptome. The expression of some of these genes by cortical neurons has not yet been reported. The vast majority of antimicrobial (~53%) and immune cell protein (~94%) transcripts was identified in the transcriptome of the 84 cells, owing to the high sensitivity of ultra-deep sequencing. Several of the antimicrobial and immune process-related protein transcripts showed cell type-specific or enriched expression. Individual neurons transcribed only a fraction of the investigated genes with low copy numbers probably due to the bursting kinetics of gene expression; however, the comparison of our data with available transcriptomic datasets from immune cells and neurons suggests the functional relevance of the reported findings. Accordingly, we propose further experimental and in silico studies on the neuronal expression of immune system-related genes and the potential role of the encoded proteins in neuroimmunological processes.
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Affiliation(s)
- Dániel Mittli
- ELTE NAP Neuroimmunology Research Group, Department of Biochemistry, Institute of Biology, ELTE Eötvös Loránd University, Budapest, Hungary
- Laboratory of Proteomics, Institute of Biology, ELTE Eötvös Loránd University, Budapest, Hungary
| | - Vanda Tukacs
- ELTE NAP Neuroimmunology Research Group, Department of Biochemistry, Institute of Biology, ELTE Eötvös Loránd University, Budapest, Hungary
- Laboratory of Proteomics, Institute of Biology, ELTE Eötvös Loránd University, Budapest, Hungary
| | - András Micsonai
- ELTE NAP Neuroimmunology Research Group, Department of Biochemistry, Institute of Biology, ELTE Eötvös Loránd University, Budapest, Hungary
| | - Lilla Ravasz
- ELTE NAP Neuroimmunology Research Group, Department of Biochemistry, Institute of Biology, ELTE Eötvös Loránd University, Budapest, Hungary
- Clinical Research Units (CRU) Hungary Ltd., Göd, Hungary
| | - József Kardos
- ELTE NAP Neuroimmunology Research Group, Department of Biochemistry, Institute of Biology, ELTE Eötvös Loránd University, Budapest, Hungary
| | - Gábor Juhász
- ELTE NAP Neuroimmunology Research Group, Department of Biochemistry, Institute of Biology, ELTE Eötvös Loránd University, Budapest, Hungary
- Laboratory of Proteomics, Institute of Biology, ELTE Eötvös Loránd University, Budapest, Hungary
- Clinical Research Units (CRU) Hungary Ltd., Göd, Hungary
- InnoScience Ltd., Mátranovák, Hungary
| | - Katalin Adrienna Kékesi
- ELTE NAP Neuroimmunology Research Group, Department of Biochemistry, Institute of Biology, ELTE Eötvös Loránd University, Budapest, Hungary
- Laboratory of Proteomics, Institute of Biology, ELTE Eötvös Loránd University, Budapest, Hungary
- InnoScience Ltd., Mátranovák, Hungary
- Department of Physiology and Neurobiology, Institute of Biology, ELTE Eötvös Loránd University, Budapest, Hungary
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García-Martínez J, Medina DA, Bellvís P, Sun M, Cramer P, Chávez S, Pérez-Ortín JE. The total mRNA concentration buffering system in yeast is global rather than gene-specific. RNA 2021; 27:1281-1290. [PMID: 34272303 PMCID: PMC8456998 DOI: 10.1261/rna.078774.121] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Accepted: 07/14/2021] [Indexed: 06/13/2023]
Abstract
Gene expression in eukaryotes does not follow a linear process from transcription to translation and mRNA degradation. Instead it follows a circular process in which cytoplasmic mRNA decay crosstalks with nuclear transcription. In many instances, this crosstalk contributes to buffer mRNA at a roughly constant concentration. Whether the mRNA buffering concept operates on the total mRNA concentration or at the gene-specific level, and if the mechanism to do so is a global or a specific one, remain unknown. Here we assessed changes in mRNA concentrations and their synthesis rates along the transcriptome of aneuploid strains of the yeast Saccharomyces cerevisiae We also assessed mRNA concentrations and their synthesis rates in nonsense-mediated decay (NMD) targets in euploid strains. We found that the altered synthesis rates in the genes from the aneuploid chromosome and the changes in their mRNA stabilities were not counterbalanced. In addition, the stability of NMD targets was not specifically compensated by the changes in synthesis rate. We conclude that there is no genetic compensation of NMD mRNA targets in yeast, and total mRNA buffering uses mostly a global system rather than a gene-specific one.
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Affiliation(s)
- José García-Martínez
- Instituto de Biotecnología y Biomedicina (BIOTECMED), Facultad de Biológicas, Universitat de València, E46100 Burjassot, Spain
| | - Daniel A Medina
- Instituto de Biotecnología y Biomedicina (BIOTECMED), Facultad de Biológicas, Universitat de València, E46100 Burjassot, Spain
| | - Pablo Bellvís
- Instituto de Biomedicina de Sevilla, Universidad de Sevilla-CSIC-Hospital Universitario V. del Rocío, Seville 41012, Spain
| | - Mai Sun
- Max Planck Institute for Biophysical Chemistry, Department of Molecular Biology, 37077 Göttingen, Germany
| | - Patrick Cramer
- Max Planck Institute for Biophysical Chemistry, Department of Molecular Biology, 37077 Göttingen, Germany
| | - Sebastián Chávez
- Instituto de Biomedicina de Sevilla, Universidad de Sevilla-CSIC-Hospital Universitario V. del Rocío, Seville 41012, Spain
- Dirección de Evaluación y Acreditación, Agencia Andaluza del Conocimiento, planta 3ª C.P. 14006 Córdoba, Spain
| | - José E Pérez-Ortín
- Instituto de Biotecnología y Biomedicina (BIOTECMED), Facultad de Biológicas, Universitat de València, E46100 Burjassot, Spain
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Belliveau NM, Chure G, Hueschen CL, Garcia HG, Kondev J, Fisher DS, Theriot JA, Phillips R. Fundamental limits on the rate of bacterial growth and their influence on proteomic composition. Cell Syst 2021; 12:924-944.e2. [PMID: 34214468 PMCID: PMC8460600 DOI: 10.1016/j.cels.2021.06.002] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2020] [Revised: 04/12/2021] [Accepted: 06/04/2021] [Indexed: 12/11/2022]
Abstract
Despite abundant measurements of bacterial growth rate, cell size, and protein content, we lack a rigorous understanding of what sets the scale of these quantities and when protein abundances should (or should not) depend on growth rate. Here, we estimate the basic requirements and physical constraints on steady-state growth by considering key processes in cellular physiology across a collection of Escherichia coli proteomic data covering ≈4,000 proteins and 36 growth rates. Our analysis suggests that cells are predominantly tuned for the task of cell doubling across a continuum of growth rates; specific processes do not limit growth rate or dictate cell size. We present a model of proteomic regulation as a function of nutrient supply that reconciles observed interdependences between protein synthesis, cell size, and growth rate and propose that a theoretical inability to parallelize ribosomal synthesis places a firm limit on the achievable growth rate. A record of this paper's transparent peer review process is included in the supplemental information.
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Affiliation(s)
- Nathan M Belliveau
- Department of Biology, Howard Hughes Medical Institute, University of Washington, Seattle, WA 98105, USA
| | - Griffin Chure
- Department of Applied Physics, California Institute of Technology, Pasadena, CA 91125, USA
| | - Christina L Hueschen
- Department of Chemical Engineering, Stanford University, Stanford, CA 94305, USA
| | - Hernan G Garcia
- Department of Molecular Cell Biology and Department of Physics, University of California Berkeley, Berkeley, CA 94720, USA
| | - Jane Kondev
- Department of Physics, Brandeis University, Waltham, MA 02453, USA
| | - Daniel S Fisher
- Department of Applied Physics, Stanford University, Stanford, CA 94305, USA
| | - Julie A Theriot
- Department of Biology, Howard Hughes Medical Institute, University of Washington, Seattle, WA 98105, USA.
| | - Rob Phillips
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125, USA; Department of Physics, California Institute of Technology, Pasadena, CA 91125, USA.
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45
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Kim MJ, Kim H, Gao X, Ryu JH, Yang Y, Kwon IC, Roberts TM, Kim SH. Multi-targeting siRNA nanoparticles for simultaneous inhibition of PI3K and Rac1 in PTEN-deficient prostate cancer. J IND ENG CHEM 2021. [DOI: 10.1016/j.jiec.2021.04.024] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
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46
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Killinger M, Veselá B, Procházková M, Matalová E, Klepárník K. A single-cell analytical approach to quantify activated caspase-3/7 during osteoblast proliferation, differentiation, and apoptosis. Anal Bioanal Chem 2021. [PMID: 34169347 DOI: 10.1007/s00216-021-03471-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Revised: 05/27/2021] [Accepted: 06/09/2021] [Indexed: 10/21/2022]
Abstract
The protein heterogeneity at the single-cell level has been recognized to be vital for an understanding of various life processes during animal development. In addition, the knowledge of accurate quantity of relevant proteins at cellular level is essential for appropriate interpretation of diagnostic and therapeutic results. Some low-copy-number proteins are known to play a crucial role during cell proliferation, differentiation, and also in apoptosis. The fate decision is often based on the concentration of these proteins in the individual cells. This is likely to apply also for caspases, cysteine proteases traditionally associated with cell death via apoptosis but recently being discovered also as important factors in cell proliferation and differentiation. The hypothesis was tested in bone-related cells, where modulation of fate from apoptosis to proliferation/differentiation and vice versa is particularly challenging, e.g., towards anti-osteoporotic treatments and anti-cancer strategies. An ultrasensitive and highly selective method based on bioluminescence photon counting was used to quantify activated caspase-3/7 in order to demonstrate protein-level heterogeneity in individual cells within one population and to associate quantitative measurements with different cell fates (proliferation, differentiation, apoptosis). The results indicate a gradual increase of caspase-3/7 activation from the proliferative status to differentiation (more than three times) and towards apoptosis (more than six times). The findings clearly support one of the putative key mechanisms of non-apoptotic functions of pro-apoptotic caspases based on fine-tuning of their activation levels.
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47
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Barber F, Min J, Murray AW, Amir A. Modeling the impact of single-cell stochasticity and size control on the population growth rate in asymmetrically dividing cells. PLoS Comput Biol 2021; 17:e1009080. [PMID: 34153030 PMCID: PMC8248971 DOI: 10.1371/journal.pcbi.1009080] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2020] [Revised: 07/01/2021] [Accepted: 05/14/2021] [Indexed: 11/18/2022] Open
Abstract
Microbial populations show striking diversity in cell growth morphology and lifecycle; however, our understanding of how these factors influence the growth rate of cell populations remains limited. We use theory and simulations to predict the impact of asymmetric cell division, cell size regulation and single-cell stochasticity on the population growth rate. Our model predicts that coarse-grained noise in the single-cell growth rate λ decreases the population growth rate, as previously seen for symmetrically dividing cells. However, for a given noise in λ we find that dividing asymmetrically can enhance the population growth rate for cells with strong size control (between a “sizer” and an “adder”). To reconcile this finding with the abundance of symmetrically dividing organisms in nature, we propose that additional constraints on cell growth and division must be present which are not included in our model, and we explore the effects of selected extensions thereof. Further, we find that within our model, epigenetically inherited generation times may arise due to size control in asymmetrically dividing cells, providing a possible explanation for recent experimental observations in budding yeast. Taken together, our findings provide insight into the complex effects generated by non-canonical growth morphologies. How rapidly a population of single-celled organisms can grow will strongly impact their long-term success. Prior work has shown that many factors impact this population growth rate, including the rate at which single cells grow, random variability between cells, and whether cells regulate their own size. Here we show that cell division asymmetry can also have a strong impact on the population growth rate. We use theory and computer simulations to study the growth rate of cells that divide asymmetrically, producing one smaller cell and one larger cell with each cell division event. We show that variability in how fast single cells grow will still decrease the population growth rate, when asymmetry is moderate or size control is weak, but that cells with strong size control can diminish this decrease by dividing more asymmetrically. We also demonstrate that cell cycle lengths can be positively correlated for closely related cells when they both divide asymmetrically and regulate their size. This counter-intuitive result contrasts with previous findings based on cell size regulation in symmetrically dividing cells that if cells grow for “too long” in one cell cycle, this will be corrected for by reduced growth during a shorter, subsequent cell cycle.
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Affiliation(s)
- Felix Barber
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, Massachusetts, United States of America
- Center for Genomics and Systems Biology, Department of Biology, New York University, New York, New York, United States of America
| | - Jiseon Min
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, Massachusetts, United States of America
| | - Andrew W. Murray
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, Massachusetts, United States of America
- FAS Center for Systems Biology, Harvard University, Cambridge, Massachusetts, United States of America
| | - Ariel Amir
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, United States of America
- * E-mail:
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48
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Willis L, Jönsson H, Huang KC. Limits and Constraints on Mechanisms of Cell-Cycle Regulation Imposed by Cell Size-Homeostasis Measurements. Cell Rep 2020; 32:107992. [PMID: 32783950 DOI: 10.1016/j.celrep.2020.107992] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2019] [Revised: 04/09/2020] [Accepted: 07/13/2020] [Indexed: 01/27/2023] Open
Abstract
High-throughput imaging has led to an explosion of observations about cell-size homeostasis across the kingdoms of life. Among bacteria, "adder" behavior-in which a constant size increment appears to be added during each cell cycle-is ubiquitous, while various eukaryotes show other size-homeostasis behaviors. Since interactions between cell-cycle progression and growth ultimately determine such behaviors, we developed a general model of cell-cycle regulation. Our analyses reveal a range of scenarios that are plausible but fail to regulate cell size, indicating that mechanisms of cell-cycle regulation are stringently limited by size-control requirements, and possibly why certain cell-cycle features are strongly conserved. Cell-cycle features can play unintuitive roles in altering size-homeostasis behaviors: noisy regulator production can enhance adder behavior, while Whi5-like inhibitor dilutors respond sensitively to perturbations to G2/M control and noisy G1/S checkpoints. Our model thus provides holistic insights into the mechanistic implications of size-homeostasis experimental measurements.
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49
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Thomas P, Shahrezaei V. Coordination of gene expression noise with cell size: analytical results for agent-based models of growing cell populations. J R Soc Interface 2021; 18:20210274. [PMID: 34034535 DOI: 10.1098/rsif.2021.0274] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
Abstract
The chemical master equation and the Gillespie algorithm are widely used to model the reaction kinetics inside living cells. It is thereby assumed that cell growth and division can be modelled through effective dilution reactions and extrinsic noise sources. We here re-examine these paradigms through developing an analytical agent-based framework of growing and dividing cells accompanied by an exact simulation algorithm, which allows us to quantify the dynamics of virtually any intracellular reaction network affected by stochastic cell size control and division noise. We find that the solution of the chemical master equation-including static extrinsic noise-exactly agrees with the agent-based formulation when the network under study exhibits stochastic concentration homeostasis, a novel condition that generalizes concentration homeostasis in deterministic systems to higher order moments and distributions. We illustrate stochastic concentration homeostasis for a range of common gene expression networks. When this condition is not met, we demonstrate by extending the linear noise approximation to agent-based models that the dependence of gene expression noise on cell size can qualitatively deviate from the chemical master equation. Surprisingly, the total noise of the agent-based approach can still be well approximated by extrinsic noise models.
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Affiliation(s)
- Philipp Thomas
- Department of Mathematics, Imperial College London, London, UK
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50
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Pandey PP, Singh H, Jain S. Exponential trajectories, cell size fluctuations, and the adder property in bacteria follow from simple chemical dynamics and division control. Phys Rev E 2021; 101:062406. [PMID: 32688579 DOI: 10.1103/physreve.101.062406] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2019] [Accepted: 04/03/2020] [Indexed: 02/03/2023]
Abstract
Experiments on steady-state bacterial cultures have uncovered several quantitative regularities at the system level. These include, first, the exponential growth of cell size with time and the balanced growth of intracellular chemicals between cell birth and division, which are puzzling given the nonlinear and decentralized chemical dynamics in the cell. We model a cell as a set of chemical populations undergoing nonlinear mass action kinetics in a container whose volume is a linear function of the chemical populations. This turns out to be a special class of dynamical systems that generically has attractors in which all populations grow exponentially with time at the same rate. This explains exponential balanced growth of bacterial cells without invoking any regulatory mechanisms and suggests that this could be a robust property of protocells as well. Second, we consider the hypothesis that cells commit themselves to division when a certain internal chemical population reaches a threshold of N molecules. We show that this hypothesis leads to a simple explanation of some of the variability observed across cells in a bacterial culture. In particular, it reproduces the adder property of cell size fluctuations observed recently in E. coli; the observed correlations among interdivision time, birth volume, and added volume in a generation; and the observed scale of the fluctuations (CV ≈ 10-30%) when N is between 10 and 100. Third, upon including a suitable regulatory mechanism that optimizes the growth rate of the cell, the model reproduces the observed bacterial growth laws including the dependence of the growth rate and ribosomal protein fraction on the medium. Thus, the models provide a framework for unifying diverse aspects of bacterial growth physiology under one roof. They also suggest new questions for experimental and theoretical enquiry.
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Affiliation(s)
- Parth Pratim Pandey
- Department of Physics and Astrophysics, University of Delhi, Delhi 110007, India
| | - Harshant Singh
- Department of Physics and Astrophysics, University of Delhi, Delhi 110007, India
| | - Sanjay Jain
- Department of Physics and Astrophysics, University of Delhi, Delhi 110007, India.,Santa Fe Institute, 1399 Hyde Park Road, Santa Fe, New Mexico 87501, USA
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