1
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Greiss F, Lardon N, Schütz L, Barak Y, Daube SS, Weinhold E, Noireaux V, Bar-Ziv R. A genetic circuit on a single DNA molecule as an autonomous dissipative nanodevice. Nat Commun 2024; 15:883. [PMID: 38287055 PMCID: PMC10825189 DOI: 10.1038/s41467-024-45186-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2023] [Accepted: 01/16/2024] [Indexed: 01/31/2024] Open
Abstract
Realizing genetic circuits on single DNA molecules as self-encoded dissipative nanodevices is a major step toward miniaturization of autonomous biological systems. A circuit operating on a single DNA implies that genetically encoded proteins localize during coupled transcription-translation to DNA, but a single-molecule measurement demonstrating this has remained a challenge. Here, we use a genetically encoded fluorescent reporter system with improved temporal resolution and observe the synthesis of individual proteins tethered to a DNA molecule by transient complexes of RNA polymerase, messenger RNA, and ribosome. Against expectations in dilute cell-free conditions where equilibrium considerations favor dispersion, these nascent proteins linger long enough to regulate cascaded reactions on the same DNA. We rationally design a pulsatile genetic circuit by encoding an activator and repressor in feedback on the same DNA molecule. Driven by the local synthesis of only several proteins per hour and gene, the circuit dynamics exhibit enhanced variability between individual DNA molecules, and fluctuations with a broad power spectrum. Our results demonstrate that co-expressional localization, as a nonequilibrium process, facilitates single-DNA genetic circuits as dissipative nanodevices, with implications for nanobiotechnology applications and artificial cell design.
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Affiliation(s)
- Ferdinand Greiss
- Department of Chemical and Biological Physics, Weizmann Institute of Science, Rehovot, 7610001, Israel.
| | - Nicolas Lardon
- Department of Chemical Biology, Max Planck Institute for Medical Research, 69120, Heidelberg, Germany
| | - Leonie Schütz
- Institute of Organic Chemistry, RWTH Aachen University, 52056, Aachen, Germany
| | - Yoav Barak
- Department of Chemical Research Support, Weizmann Institute of Science, Rehovot, 7610001, Israel
| | - Shirley S Daube
- Department of Chemical and Biological Physics, Weizmann Institute of Science, Rehovot, 7610001, Israel
| | - Elmar Weinhold
- Institute of Organic Chemistry, RWTH Aachen University, 52056, Aachen, Germany
| | - Vincent Noireaux
- School of Physics and Astronomy, University of Minnesota, Minneapolis, MN, 55455, USA
| | - Roy Bar-Ziv
- Department of Chemical and Biological Physics, Weizmann Institute of Science, Rehovot, 7610001, Israel.
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2
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Landman J, Verduyn Lunel SM, Kegel WK. Transcription factor competition facilitates self-sustained oscillations in single gene genetic circuits. PLoS Comput Biol 2023; 19:e1011525. [PMID: 37773967 PMCID: PMC10566692 DOI: 10.1371/journal.pcbi.1011525] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Revised: 10/11/2023] [Accepted: 09/18/2023] [Indexed: 10/01/2023] Open
Abstract
Genetic feedback loops can be used by cells to regulate internal processes or to keep track of time. It is often thought that, for a genetic circuit to display self-sustained oscillations, a degree of cooperativity is needed in the binding and unbinding of actor species. This cooperativity is usually modeled using a Hill function, regardless of the actual promoter architecture. Furthermore, genetic circuits do not operate in isolation and often transcription factors are shared between different promoters. In this work we show how mathematical modelling of genetic feedback loops can be facilitated with a mechanistic fold-change function that takes into account the titration effect caused by competing binding sites for transcription factors. The model shows how the titration effect facilitates self-sustained oscillations in a minimal genetic feedback loop: a gene that produces its own repressor directly without cooperative transcription factor binding. The use of delay-differential equations leads to a stability contour that predicts whether a genetic feedback loop will show self-sustained oscillations, even when taking the bursty nature of transcription into account.
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Affiliation(s)
- Jasper Landman
- Physics & Physical Chemistry of Foods, Wageningen University & Research, Wageningen, the Netherlands
| | | | - Willem K. Kegel
- Van ‘t Hoff Laboratory for Physical & Colloid Chemistry, Utrecht University, Utrecht, the Netherlands
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3
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Martin CS, Jubelin G, Darsonval M, Leroy S, Leneveu-Jenvrin C, Hmidene G, Omhover L, Stahl V, Guillier L, Briandet R, Desvaux M, Dubois-Brissonnet F. Genetic, physiological, and cellular heterogeneities of bacterial pathogens in food matrices: Consequences for food safety. Compr Rev Food Sci Food Saf 2022; 21:4294-4326. [PMID: 36018457 DOI: 10.1111/1541-4337.13020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2022] [Revised: 07/12/2022] [Accepted: 07/14/2022] [Indexed: 01/28/2023]
Abstract
In complex food systems, bacteria live in heterogeneous microstructures, and the population displays phenotypic heterogeneities at the single-cell level. This review provides an overview of spatiotemporal drivers of phenotypic heterogeneity of bacterial pathogens in food matrices at three levels. The first level is the genotypic heterogeneity due to the possibility for various strains of a given species to contaminate food, each of them having specific genetic features. Then, physiological heterogeneities are induced within the same strain, due to specific microenvironments and heterogeneous adaptative responses to the food microstructure. The third level of phenotypic heterogeneity is related to cellular heterogeneity of the same strain in a specific microenvironment. Finally, we consider how these phenotypic heterogeneities at the single-cell level could be implemented in mathematical models to predict bacterial behavior and help ensure microbiological food safety.
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Affiliation(s)
- Cédric Saint Martin
- MICALIS Institute, Université Paris-Saclay, INRAE, AgroParisTech, Jouy-en-Josas, France.,Université Clermont Auvergne, INRAE, UMR454 MEDIS, Clermont-Ferrand, France
| | - Grégory Jubelin
- Université Clermont Auvergne, INRAE, UMR454 MEDIS, Clermont-Ferrand, France
| | - Maud Darsonval
- MICALIS Institute, Université Paris-Saclay, INRAE, AgroParisTech, Jouy-en-Josas, France
| | - Sabine Leroy
- Université Clermont Auvergne, INRAE, UMR454 MEDIS, Clermont-Ferrand, France
| | - Charlène Leneveu-Jenvrin
- MICALIS Institute, Université Paris-Saclay, INRAE, AgroParisTech, Jouy-en-Josas, France.,Association pour le Développement de l'Industrie de la Viande (ADIV), Clermont-Ferrand, France
| | - Ghaya Hmidene
- Risk Assessment Department, ANSES, Maisons-Alfort, France
| | - Lysiane Omhover
- Aerial, Technical Institute of Agro-Industry, Illkirch, France
| | - Valérie Stahl
- Aerial, Technical Institute of Agro-Industry, Illkirch, France
| | | | - Romain Briandet
- MICALIS Institute, Université Paris-Saclay, INRAE, AgroParisTech, Jouy-en-Josas, France
| | - Mickaël Desvaux
- Université Clermont Auvergne, INRAE, UMR454 MEDIS, Clermont-Ferrand, France
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4
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Mines RC, Lipniacki T, Shen X. Slow nucleosome dynamics set the transcriptional speed limit and induce RNA polymerase II traffic jams and bursts. PLoS Comput Biol 2022; 18:e1009811. [PMID: 35143483 PMCID: PMC8865691 DOI: 10.1371/journal.pcbi.1009811] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Revised: 02/23/2022] [Accepted: 01/06/2022] [Indexed: 11/19/2022] Open
Abstract
Nucleosomes are recognized as key regulators of transcription. However, the relationship between slow nucleosome unwrapping dynamics and bulk transcriptional properties has not been thoroughly explored. Here, an agent-based model that we call the dynamic defect Totally Asymmetric Simple Exclusion Process (ddTASEP) was constructed to investigate the effects of nucleosome-induced pausing on transcriptional dynamics. Pausing due to slow nucleosome dynamics induced RNAPII convoy formation, which would cooperatively prevent nucleosome rebinding leading to bursts of transcription. The mean first passage time (MFPT) and the variance of first passage time (VFPT) were analytically expressed in terms of the nucleosome rate constants, allowing for the direct quantification of the effects of nucleosome-induced pausing on pioneering polymerase dynamics. The mean first passage elongation rate γ(hc, ho) is inversely proportional to the MFPT and can be considered to be a new axis of the ddTASEP phase diagram, orthogonal to the classical αβ-plane (where α and β are the initiation and termination rates). Subsequently, we showed that, for β = 1, there is a novel jamming transition in the αγ-plane that separates the ddTASEP dynamics into initiation-limited and nucleosome pausing-limited regions. We propose analytical estimates for the RNAPII density ρ, average elongation rate v, and transcription flux J and verified them numerically. We demonstrate that the intra-burst RNAPII waiting times tin follow the time-headway distribution of a max flux TASEP and that the average inter-burst interval tIBI¯ correlates with the index of dispersion De. In the limit γ→0, the average burst size reaches a maximum set by the closing rate hc. When α≪1, the burst sizes are geometrically distributed, allowing large bursts even while the average burst size NB¯ is small. Last, preliminary results on the relative effects of static and dynamic defects are presented to show that dynamic defects can induce equal or greater pausing than static bottle necks. To perform specific functions, cells must express specific genes by copying the information in DNA into RNA via transcription. Structural proteins called nucleosomes are spaced every 200 base pairs along the length of a strand of DNA and play a crucial function in the regulation of gene activity by tightly binding DNA strands and condensing them into heterochromatin, preventing transcription by RNA polymerase II (RNAPII). Even on active genes where nucleosomes are loosely attached to DNA strands, the wrapping and unwrapping of nucleosomes pause transcription as RNAPII passes by. Previous mathematical models of transcription have compared this biological process to traffic on a one lane highway without obstructions. In contrast, our proposed model simulates transcription like traffic in a grid system where nucleosomes can be thought of as pedestrians or other vehicles crossing the road at regularly spaced intersections. Just as side street traffic and pedestrian crossings can cause cars to form convoys and cause jams limiting the max speed in an area, nucleosomes can cause RNAPII to form convoys that lead to bursts of mRNA production and limit the average polymerase flux through the gene.
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Affiliation(s)
- Robert C. Mines
- Department of Biomedical Engineering, Duke University, Durham, North Carolina, United States of America
| | - Tomasz Lipniacki
- Department of Biosystems and Soft Matter, Institute of Fundamental Technological Research, Polish Academy of Sciences, Warsaw, Poland
- * E-mail: (TL); (XS)
| | - Xiling Shen
- Department of Biomedical Engineering, Duke University, Durham, North Carolina, United States of America
- Center for Genomic and Computational Biology, Duke University, Durham, North Carolina, United States of America
- Woo Center for Big Data and Precision Health, Duke University, Durham, North Carolina, United States of America
- * E-mail: (TL); (XS)
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5
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Klindziuk A, Kolomeisky AB. Understanding the molecular mechanisms of transcriptional bursting. Phys Chem Chem Phys 2021; 23:21399-21406. [PMID: 34550142 DOI: 10.1039/d1cp03665c] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
In recent years, it has been experimentally established that transcription, a fundamental biological process that involves the synthesis of messenger RNA molecules from DNA templates, does not proceed continuously as was expected. Rather, it exhibits a distinct dynamic behavior of alternating between productive phases when RNA molecules are actively synthesized and inactive phases when there is no RNA production at all. The bimodal transcriptional dynamics is now confirmed to be present in most living systems. This phenomenon is known as transcriptional bursting and it attracts significant amounts of attention from researchers in different fields. However, despite multiple experimental and theoretical investigations, the microscopic origin and biological functions of the transcriptional bursting remain unclear. Here we discuss the recent developments in uncovering the underlying molecular mechanisms of transcriptional bursting and our current understanding of them. Our analysis presents a physicochemical view of the processes that govern transcriptional bursting in living cells.
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Affiliation(s)
- Alena Klindziuk
- Department of Chemistry, Center for Theoretical Biological Physics and Applied Physics Graduate Program, Rice University, Houston, TX 77005-1892, USA.
| | - Anatoly B Kolomeisky
- Department of Chemistry, Department of Physics and Astronomy, Department of Chemical and Biomolecular Engineering and Center for Theoretical Biological Physics, Rice University, Houston, TX 77005-1892, USA.
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6
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Ali MZ, Choubey S, Das D, Brewster RC. Probing Mechanisms of Transcription Elongation Through Cell-to-Cell Variability of RNA Polymerase. Biophys J 2020; 118:1769-1781. [PMID: 32101716 PMCID: PMC7136280 DOI: 10.1016/j.bpj.2020.02.002] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2019] [Revised: 01/31/2020] [Accepted: 02/03/2020] [Indexed: 11/17/2022] Open
Abstract
The process of transcription initiation and elongation are primary points of control in the regulation of gene expression. Although biochemical studies have uncovered the mechanisms involved in controlling transcription at each step, how these mechanisms manifest in vivo at the level of individual genes is still unclear. Recent experimental advances have enabled single-cell measurements of RNA polymerase (RNAP) molecules engaged in the process of transcribing a gene of interest. In this article, we use Gillespie simulations to show that measurements of cell-to-cell variability of RNAP numbers and interpolymerase distances can reveal the prevailing mode of regulation of a given gene. Mechanisms of regulation at each step, from initiation to elongation dynamics, produce qualitatively distinct signatures, which can further be used to discern between them. Most intriguingly, depending on the initiation kinetics, stochastic elongation can either enhance or suppress cell-to-cell variability at the RNAP level. To demonstrate the value of this framework, we analyze RNAP number distribution data for ribosomal genes in Saccharomyces cerevisiae from three previously published studies and show that this approach provides crucial mechanistic insights into the transcriptional regulation of these genes.
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Affiliation(s)
- Md Zulfikar Ali
- Program in Systems Biology, University of Massachusetts Medical School, Worcester, Massachusetts; Department of Microbiology and Physiological Systems, University of Massachusetts Medical School, Worcester, Massachusetts
| | - Sandeep Choubey
- Max Planck institute for the Physics of Complex Systems, Dresden, Germany.
| | - Dipjyoti Das
- Department of Biological Sciences, Indian Institute of Science Education and Research Kolkata, Nadia, West Bengal, India
| | - Robert C Brewster
- Program in Systems Biology, University of Massachusetts Medical School, Worcester, Massachusetts; Department of Microbiology and Physiological Systems, University of Massachusetts Medical School, Worcester, Massachusetts.
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7
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Dissecting the in vivo dynamics of transcription locking due to positive supercoiling buildup. BIOCHIMICA ET BIOPHYSICA ACTA-GENE REGULATORY MECHANISMS 2020; 1863:194515. [PMID: 32113983 DOI: 10.1016/j.bbagrm.2020.194515] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/14/2019] [Revised: 02/07/2020] [Accepted: 02/20/2020] [Indexed: 01/04/2023]
Abstract
Positive supercoiling buildup (PSB) is a pervasive phenomenon in the transcriptional programs of Escherichia coli. After finding a range of Gyrase concentrations where the inverse of the transcription rate of a chromosome-integrated gene changes linearly with the inverse of Gyrase concentration, we apply a LineWeaver-Burk plot to dissect the expected in vivo transcription rate in absence of PSB. We validate the estimation by time-lapse microscopy of single-RNA production kinetics of the same gene when single-copy plasmid-borne, shown to be impervious to Gyrase inhibition. Next, we estimate the fraction of time in locked states and number of transcription events prior to locking, which we validate by measurements under Gyrase inhibition. Replacing the gene of interest by one with slower transcription rate decreases the fraction of time in locked states due to PSB. Finally, we combine data from both constructs to infer a range of possible transcription initiation locking kinetics in a chromosomal location, obtainable by tuning the transcription rate. We validate with measurements of transcription activity at different induction levels. This strategy for dissecting transcription initiation locking kinetics due to PSB can contribute to resolve the transcriptional programs of E. coli and in the engineering of synthetic genetic circuits.
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8
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Klindziuk A, Meadowcroft B, Kolomeisky AB. A Mechanochemical Model of Transcriptional Bursting. Biophys J 2020; 118:1213-1220. [PMID: 32049059 DOI: 10.1016/j.bpj.2020.01.017] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2019] [Revised: 12/20/2019] [Accepted: 01/09/2020] [Indexed: 12/29/2022] Open
Abstract
Populations of genetically identical cells generally show a large variability in cell phenotypes, which is typically associated with the stochastic nature of gene expression processes. It is widely believed that a significant source of such randomness is transcriptional bursting, which is when periods of active production of RNA molecules alternate with periods of RNA degradation. However, the molecular mechanisms of such strong fluctuations remain unclear. Recent studies suggest that DNA supercoiling, which happens during transcription, might be directly related to the bursting behavior. Stimulated by these observations, we developed a stochastic mechanochemical model of supercoiling-induced transcriptional bursting in which the RNA synthesis leads to the buildup of torsion in DNA. This slows down the RNA production until it is bound by the enzyme gyrase to DNA, which releases the stress and allows for the RNA synthesis to restart with the original rate. Using a thermodynamically consistent coupling between mechanical and chemical processes, the dynamic properties of transcription are explicitly evaluated. In addition, a first-passage method to evaluate the dynamics of transcription is developed. Theoretical analysis shows that transcriptional bursting is observed when both the supercoiling and the mechanical stress release due to gyrase are present in the system. It is also found that the overall RNA production rate is not constant and depends on the number of previously synthesized RNA molecules. A comparison with experimental data on bacteria allows us to evaluate the energetic cost of supercoiling during transcription. It is argued that the relatively weak mechanochemical coupling might allow transcription to be regulated most effectively.
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Affiliation(s)
- Alena Klindziuk
- Department of Chemistry, Rice University, Houston, Texas; Center for Theoretical Biological Physics, Rice University, Houston, Texas
| | - Billie Meadowcroft
- Department of Physics, University of Cambridge, Cambridge, United Kingdom
| | - Anatoly B Kolomeisky
- Department of Chemistry, Rice University, Houston, Texas; Department of Chemical and Biomolecular Engineering, Rice University, Houston, Texas; Department of Physics, Rice University, Houston, Texas; Center for Theoretical Biological Physics, Rice University, Houston, Texas.
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9
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Jensen D, Manzano AR, Rammohan J, Stallings CL, Galburt EA. CarD and RbpA modify the kinetics of initial transcription and slow promoter escape of the Mycobacterium tuberculosis RNA polymerase. Nucleic Acids Res 2020; 47:6685-6698. [PMID: 31127308 PMCID: PMC6648326 DOI: 10.1093/nar/gkz449] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2019] [Revised: 04/11/2019] [Accepted: 05/09/2019] [Indexed: 12/17/2022] Open
Abstract
The pathogen Mycobacterium tuberculosis (Mtb), the causative agent of tuberculosis, enacts unique transcriptional regulatory mechanisms when subjected to host-derived stresses. Initiation of transcription by the Mycobacterial RNA polymerase (RNAP) has previously been shown to exhibit different open complex kinetics and stabilities relative to Escherichia coli (Eco) RNAP. However, transcription initiation rates also depend on the kinetics following open complex formation such as initial nucleotide incorporation and subsequent promoter escape. Here, using a real-time fluorescence assay, we present the first in-depth kinetic analysis of initial transcription and promoter escape for the Mtb RNAP. We show that in relation to Eco RNAP, Mtb displays slower initial nucleotide incorporation but faster overall promoter escape kinetics on the Mtb rrnAP3 promoter. Furthermore, in the context of the essential transcription factors CarD and RbpA, Mtb promoter escape is slowed via differential effects on initially transcribing complexes. Finally, based on their ability to increase the rate of open complex formation and decrease the rate of promoter escape, we suggest that CarD and RbpA are capable of activation or repression depending on the rate-limiting step of a given promoter's basal initiation kinetics.
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Affiliation(s)
- Drake Jensen
- Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Ana Ruiz Manzano
- Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Jayan Rammohan
- Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Christina L Stallings
- Department of Molecular Microbiology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Eric A Galburt
- Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine, St. Louis, MO 63110, USA
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10
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Choubey S, Kondev J, Sanchez A. Distribution of Initiation Times Reveals Mechanisms of Transcriptional Regulation in Single Cells. Biophys J 2019; 114:2072-2082. [PMID: 29742401 DOI: 10.1016/j.bpj.2018.03.031] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2017] [Revised: 03/18/2018] [Accepted: 03/29/2018] [Indexed: 11/25/2022] Open
Abstract
Transcription is the dominant point of control of gene expression. Biochemical studies have revealed key molecular components of transcription and their interactions, but the dynamics of transcription initiation in cells is still poorly understood. This state of affairs is being remedied with experiments that observe transcriptional dynamics in single cells using fluorescent reporters. Quantitative information about transcription initiation dynamics can also be extracted from experiments that use electron micrographs of RNA polymerases caught in the act of transcribing a gene (Miller spreads). Inspired by these data, we analyze a general stochastic model of transcription initiation and elongation and compute the distribution of transcription initiation times. We show that different mechanisms of initiation leave distinct signatures in the distribution of initiation times that can be compared to experiments. We analyze published data from micrographs of RNA polymerases transcribing ribosomal RNA genes in Escherichia coli and compare the observed distributions of interpolymerase distances with the predictions from previously hypothesized mechanisms for the regulation of these genes. Our analysis demonstrates the potential of measuring the distribution of time intervals between initiation events as a probe for dissecting mechanisms of transcription initiation in live cells.
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Affiliation(s)
- Sandeep Choubey
- Department of Physics, Brandeis University, Waltham, Massachusetts
| | - Jane Kondev
- Department of Physics, Brandeis University, Waltham, Massachusetts
| | - Alvaro Sanchez
- Rowland Institute at Harvard, Harvard University, Cambridge, Massachusetts; Department of Ecology and Evolutionary Biology, Microbial Sciences Institute, Yale University, New Haven, Connecticut.
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11
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Ancona M, Bentivoglio A, Brackley CA, Gonnella G, Marenduzzo D. Transcriptional Bursts in a Nonequilibrium Model for Gene Regulation by Supercoiling. Biophys J 2019; 117:369-376. [PMID: 31103229 DOI: 10.1016/j.bpj.2019.04.023] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2019] [Accepted: 04/11/2019] [Indexed: 02/07/2023] Open
Abstract
We analyze transcriptional bursting within a stochastic nonequilibrium model, which accounts for the coupling between the dynamics of DNA supercoiling and gene transcription. We find a clear signature of bursty transcription when there is a separation between the timescales of transcription initiation and supercoiling dissipation (the latter may either be diffusive or mediated by topological enzymes, such as type I or type II topoisomerases). In multigenic DNA domains, we observe either bursty transcription or transcription waves; the type of behavior can be selected for by controlling gene activity and orientation. In the bursty phase, the statistics of supercoiling fluctuations at the promoter are markedly non-Gaussian.
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Affiliation(s)
- Marco Ancona
- SUPA, School of Physics and Astronomy, University of Edinburgh, Edinburgh, United Kingdom.
| | - Alessandro Bentivoglio
- SUPA, School of Physics and Astronomy, University of Edinburgh, Edinburgh, United Kingdom
| | - Chris A Brackley
- SUPA, School of Physics and Astronomy, University of Edinburgh, Edinburgh, United Kingdom
| | - Giuseppe Gonnella
- Dipartimento di Fisica, INFN, Università degli Studi di Bari Aldo Moro, Sezione di Bari, Bari, Italy
| | - Davide Marenduzzo
- SUPA, School of Physics and Astronomy, University of Edinburgh, Edinburgh, United Kingdom
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12
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Noise in bacterial gene expression. Biochem Soc Trans 2018; 47:209-217. [PMID: 30578346 DOI: 10.1042/bst20180500] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2018] [Revised: 11/22/2018] [Accepted: 11/26/2018] [Indexed: 12/25/2022]
Abstract
The expression level of a gene can fluctuate significantly between individuals within a population of genetically identical cells. The resultant phenotypic heterogeneity could be exploited by bacteria to adapt to changing environmental conditions. Noise is hence a genome-wide phenomenon that arises from the stochastic nature of the biochemical reactions that take place during gene expression and the relatively low abundance of the molecules involved. The production of mRNA and proteins therefore occurs in bursts, with alternating episodes of high and low activity during transcription and translation. Single-cell and single-molecule studies demonstrated that noise within gene expression is influenced by a combination of both intrinsic and extrinsic factors. However, our mechanistic understanding of this process at the molecular level is still rather limited. Further investigation is necessary that takes into account the detailed knowledge of gene regulation gained from biochemical studies.
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13
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Atitey K, Loskot P, Rees P. Elucidating effects of reaction rates on dynamics of the lac circuit in Escherichia coli. Biosystems 2018; 175:1-10. [PMID: 30447251 DOI: 10.1016/j.biosystems.2018.11.003] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2018] [Revised: 10/20/2018] [Accepted: 11/07/2018] [Indexed: 11/15/2022]
Abstract
Gene expression is regulated by a complex transcriptional network. It is of interest to quantify uncertainty of not knowing accurately reaction rates of underlying biochemical reactions, and to understand how they affect gene expression. Assuming a kinetic model of the lac circuit in Escherichia coli, regardless of how many reactions are involved in transcription regulation, transcription rate is shown to be the most important parameter affecting steady state production of mRNA and protein in the cell. In particular, doubling the transcription rate approximately doubles the number of mRNA synthesized at steady state for any rates of transcription inhibition and activation. On the other hand, increasing the rate of transcription inhibition by 10% reduces the average steady state count of mRNA by about 7%, whereas changes in the rate of transcription activation appear to have no such effect. Furthermore, for wide range of reaction rates in the kinetic model of the lac genetic switch considered, protein production was observed to always reach a maximum before the degradation reduces its count to zero, and this maximum was found to be always at least 27 protein molecules. Such value appears to be a fundamental structural property of genetic circuits making it very robust against changes in the internal and external conditions.
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Affiliation(s)
- Komlan Atitey
- College of Engineering, Swansea University, Swansea, United Kingdom
| | - Pavel Loskot
- College of Engineering, Swansea University, Swansea, United Kingdom.
| | - Paul Rees
- College of Engineering, Swansea University, Swansea, United Kingdom
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14
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Prajapat MK, Ribeiro AS. Added value of autoregulation and multi-step kinetics of transcription initiation. ROYAL SOCIETY OPEN SCIENCE 2018; 5:181170. [PMID: 30564410 PMCID: PMC6281912 DOI: 10.1098/rsos.181170] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/27/2018] [Accepted: 11/01/2018] [Indexed: 06/09/2023]
Abstract
Bacterial gene expression regulation occurs mostly during transcription, which has two main rate-limiting steps: the close complex formation, when the RNA polymerase binds to an active promoter, and the subsequent open complex formation, after which it follows elongation. Tuning these steps' kinetics by the action of e.g. transcription factors, allows for a wide diversity of dynamics. For example, adding autoregulation generates single-gene circuits able to perform more complex tasks. Using stochastic models of transcription kinetics with empirically validated parameter values, we investigate how autoregulation and the multi-step transcription initiation kinetics of single-gene autoregulated circuits can be combined to fine-tune steady state mean and cell-to-cell variability in protein expression levels, as well as response times. Next, we investigate how they can be jointly tuned to control complex behaviours, namely, time counting, switching dynamics and memory storage. Overall, our finding suggests that, in bacteria, jointly regulating a single-gene circuit's topology and the transcription initiation multi-step dynamics allows enhancing complex task performance.
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Affiliation(s)
- Mahendra Kumar Prajapat
- Laboratory of Biosystem Dynamics, Faculty of Biomedical Sciences and Engineering, BioMediTech Institute, Tampere University of Technology, 33101 Tampere, Finland
| | - Andre S. Ribeiro
- Laboratory of Biosystem Dynamics, Faculty of Biomedical Sciences and Engineering, BioMediTech Institute, Tampere University of Technology, 33101 Tampere, Finland
- Multi-scaled Biodata Analysis and Modelling Research Community, Tampere University of Technology, 33101 Tampere, Finland
- CA3 CTS/UNINOVA, Faculdade de Ciencias e Tecnologia, Universidade Nova de Lisboa, Quinta da Torre, 2829-516 Caparica, Portugal
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15
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Bursting onto the scene? Exploring stochastic mRNA production in bacteria. Curr Opin Microbiol 2018; 45:124-130. [PMID: 29705632 DOI: 10.1016/j.mib.2018.04.001] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2017] [Revised: 02/16/2018] [Accepted: 04/05/2018] [Indexed: 11/23/2022]
Abstract
Recent large-scale measurements of gene expression variability (or noise) in E. coli have led to the unexpected conclusion that the variability is in large part dictated by and increasing with the mean level of expression. Here we review the evidence for this apparent universal trend in variability, as well as for the related idea that transcription is fundamentally bursty. We examine recently proposed mechanisms for burstiness and universality and argue that they do not explain important features of observed data. Finally, we discuss potential limitations and pitfalls in the interpretation of experimental measurements of cell-to-cell variability.
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16
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Landman J, Brewster RC, Weinert FM, Phillips R, Kegel WK. Self-consistent theory of transcriptional control in complex regulatory architectures. PLoS One 2017; 12:e0179235. [PMID: 28686609 PMCID: PMC5501422 DOI: 10.1371/journal.pone.0179235] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2017] [Accepted: 05/25/2017] [Indexed: 11/24/2022] Open
Abstract
Individual regulatory proteins are typically charged with the simultaneous regulation of a battery of different genes. As a result, when one of these proteins is limiting, competitive effects have a significant impact on the transcriptional response of the regulated genes. Here we present a general framework for the analysis of any generic regulatory architecture that accounts for the competitive effects of the regulatory environment by isolating these effects into an effective concentration parameter. These predictions are formulated using the grand-canonical ensemble of statistical mechanics and the fold-change in gene expression is predicted as a function of the number of transcription factors, the strength of interactions between the transcription factors and their DNA binding sites, and the effective concentration of the transcription factor. The effective concentration is set by the transcription factor interactions with competing binding sites within the cell and is determined self-consistently. Using this approach, we analyze regulatory architectures in the grand-canonical ensemble ranging from simple repression and simple activation to scenarios that include repression mediated by DNA looping of distal regulatory sites. It is demonstrated that all the canonical expressions previously derived in the case of an isolated, non-competing gene, can be generalised by a simple substitution to their grand canonical counterpart, which allows for simple intuitive incorporation of the influence of multiple competing transcription factor binding sites. As an example of the strength of this approach, we build on these results to present an analytical description of transcriptional regulation of the lac operon.
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Affiliation(s)
- Jasper Landman
- Van ’t Hoff Laboratory for Physical & Colloid Chemistry, Utrecht University, Utrecht, the Netherlands
- European Synchrotron Radiation Facility, Grenoble, France
| | - Robert C. Brewster
- Program in Systems Biology, University of Massachusetts Medical School, Worcester, MA 01605, United States of America
| | - Franz M. Weinert
- Department of Applied Physics, California Institute of Technology, Pasadena, California, United States of America
| | - Rob Phillips
- Department of Applied Physics, California Institute of Technology, Pasadena, California, United States of America
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California, United States of America
| | - Willem K. Kegel
- Van ’t Hoff Laboratory for Physical & Colloid Chemistry, Utrecht University, Utrecht, the Netherlands
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17
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Sneppen K. Models of life: epigenetics, diversity and cycles. REPORTS ON PROGRESS IN PHYSICS. PHYSICAL SOCIETY (GREAT BRITAIN) 2017; 80:042601. [PMID: 28106010 DOI: 10.1088/1361-6633/aa5aeb] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
This review emphasizes aspects of biology that can be understood through repeated applications of simple causal rules. The selected topics include perspectives on gene regulation, phage lambda development, epigenetics, microbial ecology, as well as model approaches to diversity and to punctuated equilibrium in evolution. Two outstanding features are repeatedly described. One is the minimal number of rules to sustain specific states of complex systems for a long time. The other is the collapse of such states and the subsequent dynamical cycle of situations that restitute the system to a potentially new metastable state.
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Affiliation(s)
- Kim Sneppen
- Center for Models of Life, Niels Bohr Institute, Blegdamsvej 17, 2100 Copenhagen, Denmark
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18
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Lloyd-Price J, Startceva S, Kandavalli V, Chandraseelan JG, Goncalves N, Oliveira SMD, Häkkinen A, Ribeiro AS. Dissecting the stochastic transcription initiation process in live Escherichia coli. DNA Res 2016; 23:203-14. [PMID: 27026687 PMCID: PMC4909308 DOI: 10.1093/dnares/dsw009] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2015] [Accepted: 02/11/2016] [Indexed: 02/01/2023] Open
Abstract
We investigate the hypothesis that, in Escherichia coli, while the concentration of RNA polymerases differs in different growth conditions, the fraction of RNA polymerases free for transcription remains approximately constant within a certain range of these conditions. After establishing this, we apply a standard model-fitting procedure to fully characterize the in vivo kinetics of the rate-limiting steps in transcription initiation of the Plac/ara-1 promoter from distributions of intervals between transcription events in cells with different RNA polymerase concentrations. We find that, under full induction, the closed complex lasts ∼788 s while subsequent steps last ∼193 s, on average. We then establish that the closed complex formation usually occurs multiple times prior to each successful initiation event. Furthermore, the promoter intermittently switches to an inactive state that, on average, lasts ∼87 s. This is shown to arise from the intermittent repression of the promoter by LacI. The methods employed here should be of use to resolve the rate-limiting steps governing the in vivo dynamics of initiation of prokaryotic promoters, similar to established steady-state assays to resolve the in vitro dynamics.
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Affiliation(s)
- Jason Lloyd-Price
- Laboratory of Biosystem Dynamics, Department of Signal Processing, Tampere University of Technology, PO Box 553, Office TC336, 33101 Tampere, Finland
| | - Sofia Startceva
- Laboratory of Biosystem Dynamics, Department of Signal Processing, Tampere University of Technology, PO Box 553, Office TC336, 33101 Tampere, Finland
| | - Vinodh Kandavalli
- Laboratory of Biosystem Dynamics, Department of Signal Processing, Tampere University of Technology, PO Box 553, Office TC336, 33101 Tampere, Finland
| | - Jerome G Chandraseelan
- Laboratory of Biosystem Dynamics, Department of Signal Processing, Tampere University of Technology, PO Box 553, Office TC336, 33101 Tampere, Finland
| | - Nadia Goncalves
- Laboratory of Biosystem Dynamics, Department of Signal Processing, Tampere University of Technology, PO Box 553, Office TC336, 33101 Tampere, Finland
| | - Samuel M D Oliveira
- Laboratory of Biosystem Dynamics, Department of Signal Processing, Tampere University of Technology, PO Box 553, Office TC336, 33101 Tampere, Finland
| | - Antti Häkkinen
- Laboratory of Biosystem Dynamics, Department of Signal Processing, Tampere University of Technology, PO Box 553, Office TC336, 33101 Tampere, Finland
| | - Andre S Ribeiro
- Laboratory of Biosystem Dynamics, Department of Signal Processing, Tampere University of Technology, PO Box 553, Office TC336, 33101 Tampere, Finland
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19
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Choubey S, Kondev J, Sanchez A. Deciphering Transcriptional Dynamics In Vivo by Counting Nascent RNA Molecules. PLoS Comput Biol 2015; 11:e1004345. [PMID: 26544860 PMCID: PMC4636183 DOI: 10.1371/journal.pcbi.1004345] [Citation(s) in RCA: 45] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2014] [Accepted: 05/19/2015] [Indexed: 12/18/2022] Open
Abstract
Deciphering how the regulatory DNA sequence of a gene dictates its expression in response to intra and extracellular cues is one of the leading challenges in modern genomics. The development of novel single-cell sequencing and imaging techniques, as well as a better exploitation of currently available single-molecule imaging techniques, provides an avenue to interrogate the process of transcription and its dynamics in cells by quantifying the number of RNA polymerases engaged in the transcription of a gene (or equivalently the number of nascent RNAs) at a given moment in time. In this paper, we propose that measurements of the cell-to-cell variability in the number of nascent RNAs provide a mostly unexplored method for deciphering mechanisms of transcription initiation in cells. We propose a simple kinetic model of transcription initiation and elongation from which we calculate nascent RNA copy-number fluctuations. To demonstrate the usefulness of this approach, we test our theory against published nascent RNA data for twelve constitutively expressed yeast genes. Rather than transcription being initiated through a single rate limiting step, as it had been previously proposed, our single-cell analysis reveals the presence of at least two rate limiting steps. Surprisingly, half of the genes analyzed have nearly identical rates of transcription initiation, suggesting a common mechanism. Our analytical framework can be used to extract quantitative information about dynamics of transcription from single-cell sequencing data, as well as from single-molecule imaging and electron micrographs of fixed cells, and provides the mathematical means to exploit the quantitative power of these technologies.
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Affiliation(s)
- Sandeep Choubey
- Department of Physics, Brandeis University, Waltham, Massachusetts, United States of America
| | - Jane Kondev
- Department of Physics, Brandeis University, Waltham, Massachusetts, United States of America
| | - Alvaro Sanchez
- Rowland Institute at Harvard, Harvard University, Cambridge, Massachusetts, United States of America
- * E-mail:
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20
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Abstract
Transcription-coupled DNA supercoiling has been shown to be an important regulator of transcription that is broadly present in the cell. Here we review experimental work which shows that RNA polymerase is a powerful torsional motor that can alter DNA topology and structure, and DNA supercoiling in turn directly affects transcription elongation.
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Affiliation(s)
- Jie Ma
- a Department of Physics, Laboratory of Atomic and Solid State Physics; Cornell University; Ithaca, NY
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21
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Abstract
Protein noise measurements are increasingly used to elucidate biophysical parameters. Unfortunately noise analyses are often at odds with directly measured parameters. Here we show that these inconsistencies arise from two problematic analytical choices: (i) the assumption that protein translation rate is invariant for different proteins of different abundances, which has inadvertently led to (ii) the assumption that a large constitutive extrinsic noise sets the low noise limit in gene expression. While growing evidence suggests that transcriptional bursting may set the low noise limit, variability in translational bursting has been largely ignored. We show that genome-wide systematic variation in translational efficiency can–and in the case of E. coli does–control the low noise limit in gene expression. Therefore constitutive extrinsic noise is small and only plays a role in the absence of a systematic variation in translational efficiency. These results show the existence of two distinct expression noise patterns: (1) a global noise floor uniformly imposed on all genes by expression bursting; and (2) high noise distributed to only a select group of genes.
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22
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Mitarai N, Semsey S, Sneppen K. Dynamic competition between transcription initiation and repression: Role of nonequilibrium steps in cell-to-cell heterogeneity. PHYSICAL REVIEW. E, STATISTICAL, NONLINEAR, AND SOFT MATTER PHYSICS 2015; 92:022710. [PMID: 26382435 DOI: 10.1103/physreve.92.022710] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/07/2015] [Indexed: 06/05/2023]
Abstract
Transcriptional repression may cause transcriptional noise by a competition between repressor and RNA polymerase binding. Although promoter activity is often governed by a single limiting step, we argue here that the size of the noise strongly depends on whether this step is the initial equilibrium binding or one of the subsequent unidirectional steps. Overall, we show that nonequilibrium steps of transcription initiation systematically increase the cell-to-cell heterogeneity in bacterial populations. In particular, this allows also weak promoters to give substantial transcriptional noise.
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Affiliation(s)
- Namiko Mitarai
- Center for Models of Life, Niels Bohr Institute, University of Copenhagen, Blegdamsvej 17, 2100 Copenhagen, Denmark
| | - Szabolcs Semsey
- Center for Models of Life, Niels Bohr Institute, University of Copenhagen, Blegdamsvej 17, 2100 Copenhagen, Denmark
| | - Kim Sneppen
- Center for Models of Life, Niels Bohr Institute, University of Copenhagen, Blegdamsvej 17, 2100 Copenhagen, Denmark
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23
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Jones DL, Brewster RC, Phillips R. Promoter architecture dictates cell-to-cell variability in gene expression. Science 2014; 346:1533-6. [PMID: 25525251 DOI: 10.1126/science.1255301] [Citation(s) in RCA: 134] [Impact Index Per Article: 13.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
Variability in gene expression among genetically identical cells has emerged as a central preoccupation in the study of gene regulation; however, a divide exists between the predictions of molecular models of prokaryotic transcriptional regulation and genome-wide experimental studies suggesting that this variability is indifferent to the underlying regulatory architecture. We constructed a set of promoters in Escherichia coli in which promoter strength, transcription factor binding strength, and transcription factor copy numbers are systematically varied, and used messenger RNA (mRNA) fluorescence in situ hybridization to observe how these changes affected variability in gene expression. Our parameter-free models predicted the observed variability; hence, the molecular details of transcription dictate variability in mRNA expression, and transcriptional noise is specifically tunable and thus represents an evolutionarily accessible phenotypic parameter.
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Affiliation(s)
- Daniel L Jones
- Department of Applied Physics, California Institute of Technology, Pasadena, CA 91125, USA
| | - Robert C Brewster
- Department of Applied Physics, California Institute of Technology, Pasadena, CA 91125, USA. Division of Biology, California Institute of Technology, Pasadena, CA 91125, USA
| | - Rob Phillips
- Department of Applied Physics, California Institute of Technology, Pasadena, CA 91125, USA. Division of Biology, California Institute of Technology, Pasadena, CA 91125, USA.
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24
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Chong S, Chen C, Ge H, Xie XS. Mechanism of transcriptional bursting in bacteria. Cell 2014; 158:314-326. [PMID: 25036631 DOI: 10.1016/j.cell.2014.05.038] [Citation(s) in RCA: 255] [Impact Index Per Article: 25.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2013] [Revised: 03/17/2014] [Accepted: 05/08/2014] [Indexed: 11/18/2022]
Abstract
Transcription of highly expressed genes has been shown to occur in stochastic bursts. But the origin of such ubiquitous phenomenon has not been understood. Here, we present the mechanism in bacteria. We developed a high-throughput, in vitro, single-molecule assay to follow transcription on individual DNA templates in real time. We showed that positive supercoiling buildup on a DNA segment by transcription slows down transcription elongation and eventually stops transcription initiation. Transcription can be resumed upon gyrase binding to the DNA segment. Furthermore, using single-cell mRNA counting fluorescence in situ hybridization (FISH), we found that duty cycles of transcriptional bursting depend on the intracellular gyrase concentration. Together, these findings prove that transcriptional bursting of highly expressed genes in bacteria is primarily caused by reversible gyrase dissociation from and rebinding to a DNA segment, changing the supercoiling level of the segment.
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Affiliation(s)
- Shasha Chong
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA 02138, USA
| | - Chongyi Chen
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA 02138, USA; Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA 02138, USA
| | - Hao Ge
- Biodynamic Optical Imaging Center (BIOPIC), Peking University, Beijing 100871, China; Beijing International Center for Mathematical Research (BICMR), Peking University, Beijing 100871, China
| | - X Sunney Xie
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA 02138, USA; Biodynamic Optical Imaging Center (BIOPIC), Peking University, Beijing 100871, China.
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25
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SANCHEZ-OSORIO ISMAEL, RAMOS FERNANDO, MAYORGA PEDRO, DANTAN EDGAR. FOUNDATIONS FOR MODELING THE DYNAMICS OF GENE REGULATORY NETWORKS: A MULTILEVEL-PERSPECTIVE REVIEW. J Bioinform Comput Biol 2014; 12:1330003. [DOI: 10.1142/s0219720013300037] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
A promising alternative for unraveling the principles under which the dynamic interactions among genes lead to cellular phenotypes relies on mathematical and computational models at different levels of abstraction, from the molecular level of protein-DNA interactions to the system level of functional relationships among genes. This review article presents, under a bottom–up perspective, a hierarchy of approaches to modeling gene regulatory network dynamics, from microscopic descriptions at the single-molecule level in the spatial context of an individual cell to macroscopic models providing phenomenological descriptions at the population-average level. The reviewed modeling approaches include Molecular Dynamics, Particle-Based Brownian Dynamics, the Master Equation approach, Ordinary Differential Equations, and the Boolean logic abstraction. Each of these frameworks is motivated by a particular biological context and the nature of the insight being pursued. The setting of gene network dynamic models from such frameworks involves assumptions and mathematical artifacts often ignored by the non-specialist. This article aims at providing an entry point for biologists new to the field and computer scientists not acquainted with some recent biophysically-inspired models of gene regulation. The connections promoting intuition between different abstraction levels and the role that approximations play in the modeling process are highlighted throughout the paper.
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Affiliation(s)
- ISMAEL SANCHEZ-OSORIO
- Department of Computer Science, Monterrey Institute of Technology and Higher Education Campus Cuernavaca, Autopista del Sol km 104, Xochitepec, Morelos 62790, Mexico
| | - FERNANDO RAMOS
- Department of Computer Science, Monterrey Institute of Technology and Higher Education Campus Cuernavaca, Autopista del Sol km 104, Xochitepec, Morelos 62790, Mexico
| | - PEDRO MAYORGA
- Department of Computer Science, Monterrey Institute of Technology and Higher Education Campus Cuernavaca, Autopista del Sol km 104, Xochitepec, Morelos 62790, Mexico
| | - EDGAR DANTAN
- Centro de Investigación en Biotecnología, Universidad Autónoma del Estado de Morelos, Avenida Universidad 1001, Cuernavaca, Morelos 62209, Mexico
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26
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Arbel-Goren R, Tal A, Stavans J. Phenotypic noise: effects of post-transcriptional regulatory processes affecting mRNA. WILEY INTERDISCIPLINARY REVIEWS-RNA 2013; 5:197-207. [PMID: 24259395 DOI: 10.1002/wrna.1209] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/09/2013] [Revised: 10/28/2013] [Accepted: 10/29/2013] [Indexed: 11/10/2022]
Abstract
The inherently stochastic nature of biomolecular processes is one of the main sources giving rise to cell-to-cell variations in protein and mRNA abundance, termed noise. Noise in isogenic populations can enhance survival under adverse conditions and stress, and has therefore played a fundamental role in evolution. On the other hand, noise may have detrimental effects and therefore cells must also display robustness to fluctuations and possess mechanisms of control in order to function properly. Noise can be introduced at every step in the cascade of intermediate events resulting in the production of functional proteins. While initial studies of noise focused on stochasticity introduced at the transcriptional level, recent years have witnessed a gradual shift of emphasis into the effects that post-transcriptional processes have on phenotypic noise. Here, we survey the insights that have been gained on the effects of processes that modify RNA transcript populations on phenotypic noise, including regulation by noncoding RNAs in prokaryotes and eukaryotes, alternative splicing and transcriptional interference.
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Affiliation(s)
- Rinat Arbel-Goren
- Department of Physics of Complex Systems, Weizmann Institute of Science, Rehovot, Israel
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27
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Abstract
The biochemical processes leading to the synthesis of new proteins are random, as they typically involve a small number of diffusing molecules. They lead to fluctuations in the number of proteins in a single cell as a function of time and to cell-to-cell variability of protein abundances. These in turn can lead to phenotypic heterogeneity in a population of genetically identical cells. Phenotypic heterogeneity may have important consequences for the development of multicellular organisms and the fitness of bacterial colonies, raising the question of how it is regulated. Here we review the experimental evidence that transcriptional regulation affects noise in gene expression, and discuss how the noise strength is encoded in the architecture of the promoter region. We discuss how models based on specific molecular mechanisms of gene regulation can make experimentally testable predictions for how changes to the promoter architecture are reflected in gene expression noise.
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Affiliation(s)
- Alvaro Sanchez
- Department of Physics, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA.
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28
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Hensel Z, Xiao J. Single-molecule methods for studying gene regulation in vivo. Pflugers Arch 2013; 465:383-95. [PMID: 23430319 PMCID: PMC3595547 DOI: 10.1007/s00424-013-1243-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2013] [Revised: 01/30/2013] [Accepted: 01/31/2013] [Indexed: 01/25/2023]
Abstract
The recent emergence of new experimental tools employing sensitive fluorescence detection in vivo has made it possible to visualize various aspects of gene regulation at the single-molecule level in the native, intracellular context. In this review, we will first describe general considerations for in vivo, single-molecule fluorescence detection of DNA, mRNA, and protein molecules involved in gene regulation. We will then give an overview of the rapidly evolving suite of molecular tools available for observing gene regulation in vivo and discuss new insights they have brought into gene regulation.
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Affiliation(s)
- Zach Hensel
- Department of Biophysics and Biophysical Chemistry, Johns Hopkins University School of Medicine, Baltimore, MD 21211, USA
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29
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Ray JCJ, Igoshin OA. Interplay of gene expression noise and ultrasensitive dynamics affects bacterial operon organization. PLoS Comput Biol 2012; 8:e1002672. [PMID: 22956903 PMCID: PMC3431296 DOI: 10.1371/journal.pcbi.1002672] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2012] [Accepted: 07/16/2012] [Indexed: 11/30/2022] Open
Abstract
Bacterial chromosomes are organized into polycistronic cotranscribed operons, but the evolutionary pressures maintaining them are unclear. We hypothesized that operons alter gene expression noise characteristics, resulting in selection for or against maintaining operons depending on network architecture. Mathematical models for 6 functional classes of network modules showed that three classes exhibited decreased noise and 3 exhibited increased noise with same-operon cotranscription of interacting proteins. Noise reduction was often associated with a decreased chance of reaching an ultrasensitive threshold. Stochastic simulations of the lac operon demonstrated that the predicted effects of transcriptional coupling hold for a complex network module. We employed bioinformatic analysis to find overrepresentation of noise-minimizing operon organization compared with randomized controls. Among constitutively expressed physically interacting protein pairs, higher coupling frequencies appeared at lower expression levels, where noise effects are expected to be dominant. Our results thereby suggest an important role for gene expression noise, in many cases interacting with an ultrasensitive switch, in maintaining or selecting for operons in bacterial chromosomes. In some species, most notably bacteria, chromosomal genes are arranged into clusters called operons. In operons, the process of transcription is physically coupled: a single pass of the RNA polymerase enzyme reading that region of the chromosome simultaneously produces messenger RNA encoding multiple proteins. So far, we do not have a satisfying explanation for what evolutionary forces have maintained operons on bacterial chromosomes. We hypothesized that different types of interactions between operon-coded proteins affect how strongly operons are selected for between two genes. The proposed mechanism for this effect is that operons correlate gene expression noise, changing how it manifests in the post-translational network depending on the type of protein interaction. Mathematical models demonstrate that operons reduce noise for some types of interactions but not others. We found that operon-dependent noise reduction has an underlying dependence on surprisingly high sensitivity of the network to the ratio of proteins from each gene. Databases of genetic information show that E. coli has operons more frequently than random if operons reduce noise for the type of interaction various gene pairs have, but not otherwise. Our study thus provides an example of how the architecture of post-translational networks affects bacterial evolution.
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Affiliation(s)
- J. Christian J Ray
- Department of Bioengineering, Rice University, Houston, Texas, United States of America
- Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America
| | - Oleg A. Igoshin
- Department of Bioengineering, Rice University, Houston, Texas, United States of America
- Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America
- * E-mail:
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30
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Quantitative single-cell ion-channel gene expression profiling through an improved qRT-PCR technique combined with whole cell patch clamp. J Neurosci Methods 2012; 209:227-34. [PMID: 22728251 DOI: 10.1016/j.jneumeth.2012.06.008] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2012] [Revised: 05/17/2012] [Accepted: 06/09/2012] [Indexed: 12/19/2022]
Abstract
Cellular excitability originates from a concerted action of different ion channels. The genomic diversity of ion channels (over 100 different genes) underlies the functional diversity of neurons in the central nervous system (CNS) and even within a specific type of neurons large differences in channel expression have been observed. Patch-clamp is a powerful technique to study the electrophysiology of excitability at the single cell level, allowing exploration of cell-to-cell variability. Only a few attempts have been made to link electrophysiological profiling to mRNA transcript levels and most suffered from experimental noise precluding conclusive quantitative correlations. Here we describe a refinement to the technique that combines patch-clamp analysis with quantitative real-time (qRT) PCR at the single cell level. Hereto the expression of a housekeeping gene was used to normalize for cell-to-cell variability in mRNA isolation and the subsequent processing steps for performing qRT-PCR. However, the mRNA yield from a single cell was insufficient for performing a valid qRT-PCR assay; this was resolved by including a RNA amplification step. The technique was validated on a stable Ltk(-) cell line expressing the Kv2.1 channel and on embryonic dorsal root ganglion (DRG) cells probing for the expression of Kv2.1. Current density and transcript quantity displayed a clear correlation when the qRT-PCR assay was done in twofold and the data normalized to the transcript level of the housekeeping gene GAPD. Without this normalization no significant correlation was obtained. This improved technique should prove very valuable for studying the molecular background of diversity in cellular excitability.
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31
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So LH, Ghosh A, Zong C, Sepúlveda LA, Segev R, Golding I. General properties of transcriptional time series in Escherichia coli. Nat Genet 2011; 43:554-60. [PMID: 21532574 PMCID: PMC3102781 DOI: 10.1038/ng.821] [Citation(s) in RCA: 268] [Impact Index Per Article: 20.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2010] [Accepted: 04/05/2011] [Indexed: 11/09/2022]
Abstract
Gene activity is described by the time-series of discrete, stochastic mRNA production events. This transcriptional time-series exhibits intermittent, bursty behavior. One consequence of this temporal intricacy is that gene expression can be tuned by varying different features of the time-series. What schemes for varying the transcriptional time-series are observed in the cell? Are the observed properties of these time-series optimized for cellular function? To address these questions, we characterize mRNA copy-number statistics at single-molecule resolution from multiple Escherichia coli promoters. We find that the degree of burstiness depends only on the gene expression level, while being independent of the details of gene regulation. The observed behavior is explained by the underlying variation in the duration of bursting events. Using information theory, we find that the properties of the transcriptional time series allow the cell to efficiently map the extracellular concentration of inducer molecules to intracellular levels of mRNA and proteins.
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Affiliation(s)
- Lok-Hang So
- Verna and Marrs McLean Department of Biochemistry and Molecular Biology, Baylor College of Medicine, Houston, Texas, USA
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32
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Haldar S, Maharajan A, Chatterjee S, Hunter SA, Chowdhury N, Hinenoya A, Asakura M, Yamasaki S. Identification of Vibrio harveyi as a causative bacterium for a tail rot disease of sea bream Sparus aurata from research hatchery in Malta. Microbiol Res 2010; 165:639-48. [PMID: 20129765 DOI: 10.1016/j.micres.2009.12.001] [Citation(s) in RCA: 48] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2009] [Revised: 12/06/2009] [Accepted: 12/06/2009] [Indexed: 10/19/2022]
Abstract
A bacterial disease was reported from gilthead sea bream (Sparus aurata) within a hatchery environment in Malta. Symptoms included complete erosion of tail, infection in the eye, mucous secretion and frequent mortality. A total of 540 strains were initially isolated in marine agar from different infected body parts and culture water sources. Subsequently 100 isolates were randomly selected, identified biochemically and all were found to be Vibrio harveyi-related organisms; finally from 100 isolates a total of 13 numbers were randomly selected and accurately identified as V. harveyi by 16S rRNA gene sequencing and species-specific PCR. Ribotyping of these strains with HindIII revealed total of six clusters. In vivo challenge study with representative isolates from each cluster proved two clusters each were highly pathogenic, moderately pathogenic and non-pathogenic. All 13 isolates were positive for hemolysin gene, a potential virulence factor. Further analysis revealed probably a single copy of this gene was encoded in all isolates, although not in the same locus in the genome. Although V. harveyi was reported to be an important pathogen for many aquatic organisms, to our knowledge this might be the first report of disease caused by V. harveyi and their systematic study in the sea bream hatchery from Malta.
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Affiliation(s)
- S Haldar
- International Prevention of Epidemics, Graduate School of Life and Environmental Sciences, Osaka Prefecture University, 1-58, Rinkuourai-Kita, Izumisano, Osaka, Japan.
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Coulon A, Gandrillon O, Beslon G. On the spontaneous stochastic dynamics of a single gene: complexity of the molecular interplay at the promoter. BMC SYSTEMS BIOLOGY 2010; 4:2. [PMID: 20064204 PMCID: PMC2832887 DOI: 10.1186/1752-0509-4-2] [Citation(s) in RCA: 52] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/02/2009] [Accepted: 01/08/2010] [Indexed: 02/07/2023]
Abstract
BACKGROUND Gene promoters can be in various epigenetic states and undergo interactions with many molecules in a highly transient, probabilistic and combinatorial way, resulting in a complex global dynamics as observed experimentally. However, models of stochastic gene expression commonly consider promoter activity as a two-state on/off system. We consider here a model of single-gene stochastic expression that can represent arbitrary prokaryotic or eukaryotic promoters, based on the combinatorial interplay between molecules and epigenetic factors, including energy-dependent remodeling and enzymatic activities. RESULTS We show that, considering the mere molecular interplay at the promoter, a single-gene can demonstrate an elaborate spontaneous stochastic activity (eg. multi-periodic multi-relaxation dynamics), similar to what is known to occur at the gene-network level. Characterizing this generic model with indicators of dynamic and steady-state properties (including power spectra and distributions), we reveal the potential activity of any promoter and its influence on gene expression. In particular, we can reproduce, based on biologically relevant mechanisms, the strongly periodic patterns of promoter occupancy by transcription factors (TF) and chromatin remodeling as observed experimentally on eukaryotic promoters. Moreover, we link several of its characteristics to properties of the underlying biochemical system. The model can also be used to identify behaviors of interest (eg. stochasticity induced by high TF concentration) on minimal systems and to test their relevance in larger and more realistic systems. We finally show that TF concentrations can regulate many aspects of the stochastic activity with a considerable flexibility and complexity. CONCLUSIONS This tight promoter-mediated control of stochasticity may constitute a powerful asset for the cell. Remarkably, a strongly periodic activity that demonstrates a complex TF concentration-dependent control is obtained when molecular interactions have typical characteristics observed on eukaryotic promoters (high mobility, functional redundancy, many alternate states/pathways). We also show that this regime results in a direct and indirect energetic cost. Finally, this model can constitute a framework for unifying various experimental approaches. Collectively, our results show that a gene - the basic building block of complex regulatory networks - can itself demonstrate a significantly complex behavior.
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Affiliation(s)
- Antoine Coulon
- Université de Lyon, Université Lyon 1, Centre de Génétique Moléculaire et Cellulaire, CNRS UMR5534, F-69622 Lyon, France.
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Bruggeman FJ, Blüthgen N, Westerhoff HV. Noise management by molecular networks. PLoS Comput Biol 2009; 5:e1000506. [PMID: 19763166 PMCID: PMC2731877 DOI: 10.1371/journal.pcbi.1000506] [Citation(s) in RCA: 69] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2009] [Accepted: 08/13/2009] [Indexed: 11/18/2022] Open
Abstract
Fluctuations in the copy number of key regulatory macromolecules ("noise") may cause physiological heterogeneity in populations of (isogenic) cells. The kinetics of processes and their wiring in molecular networks can modulate this molecular noise. Here we present a theoretical framework to study the principles of noise management by the molecular networks in living cells. The theory makes use of the natural, hierarchical organization of those networks and makes their noise management more understandable in terms of network structure. Principles governing noise management by ultrasensitive systems, signaling cascades, gene networks and feedback circuitry are discovered using this approach. For a few frequently occurring network motifs we show how they manage noise. We derive simple and intuitive equations for noise in molecule copy numbers as a determinant of physiological heterogeneity. We show how noise levels and signal sensitivity can be set independently in molecular networks, but often changes in signal sensitivity affect noise propagation. Using theory and simulations, we show that negative feedback can both enhance and reduce noise. We identify a trade-off; noise reduction in one molecular intermediate by negative feedback is at the expense of increased noise in the levels of other molecules along the feedback loop. The reactants of the processes that are strongly (cooperatively) regulated, so as to allow for negative feedback with a high strength, will display enhanced noise.
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Affiliation(s)
- Frank J Bruggeman
- Regulatory Networks Group, Netherlands Institute for Systems Biology, Amsterdam, The Netherlands.
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Ou J, Furusawa C, Yomo T, Shimizu H. Analysis of stochasticity in promoter activation by using a dual-fluorescence reporter system. Biosystems 2009; 97:160-4. [PMID: 19555736 DOI: 10.1016/j.biosystems.2009.06.002] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2009] [Revised: 06/10/2009] [Accepted: 06/12/2009] [Indexed: 10/20/2022]
Abstract
Stochastic dynamics of promoter activity in bacterial cells were studied by using a dual-fluorescence reporter system of protein expression. The dual-fluorescence reporter system enabled us to calculate the amplitude of intrinsic noise generated during transcription and translation. By fitting the experimental data to a simple stochastic model of protein expression, we could estimate parameters representing the stochastic transition between the active and inactive states of a promoter. Using the system, we analyzed the stochastic dynamics of promoter activation of genes in the lysine biosynthesis pathway in Escherichia coli. We found that the promoter of lysA has a significantly slower transition rate between active and inactive states than other promoters in the lysine biosynthesis pathway. The infrequent switching between active and inactive states can be a dominant source of noise in lysA expression. Analysis using the dual-fluorescence reporter system provided a better understanding of stochastic dynamics in promoter activation.
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Affiliation(s)
- Jianhong Ou
- Department of Biotechnology, Graduate School of Engineering, Osaka University, Suita, Osaka, 565-0871, Japan
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Abstract
Cells in isogenic populations may differ substantially in their molecular make up because of the stochastic nature of molecular processes. Stochastic bursts in process activity have a great potential for generating molecular noise. They are characterized by (short) periods of high process activity followed by (long) periods of process silence causing different cells to experience activity periods varying in size, duration, and timing. We present an analytically solvable model of bursts in molecular networks, originally developed for the analysis of telecommunication networks. We define general measures for model-independent characterization of bursts (burst size, significance, and duration) from stochastic time series. Inspired by the discovery of bursts in mRNA and protein production by others, we use those indices to investigate the role of stochastic motion of motor proteins along biopolymer chains in determining burst properties. Collisions between neighboring motor proteins can attenuate bursts introduced at the initiation site on the chain. Pausing of motor proteins can give rise to bursts. We investigate how these effects are modulated by the length of the biopolymer chain and the kinetic properties of motion. We discuss the consequences of those results for transcription and translation.
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Dynamical analysis on gene activity in the presence of repressors and an interfering promoter. Biophys J 2008; 95:4228-40. [PMID: 18658208 DOI: 10.1529/biophysj.108.132894] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Transcription is regulated through interplay among transcription factors, an RNA polymerase (RNAP), and a promoter. Even for a simple repressive transcription factor that disturbs promoter activity at initial binding of RNAP, its repression level is not determined solely by the dissociation constant of transcription factor but is sensitive to timescales of processes in RNAP. We first analyze the promoter activity under strong repression by a slow binding repressor, in which case transcription events occur in bursts, followed by long quiescent periods while a repressor binds to the operator; the number of transcription events, bursting, and quiescent times are estimated by reaction rates. We then examine interference effect from an opposing promoter, using the correlation function of initiation events for a single promoter. The interference is shown to de-repress the promoter because RNAPs from the opposing promoter most likely encounter the repressor and remove it in case of strong repression. This de-repression mechanism should be especially prominent for the promoters that facilitate fast formation of open complex with the repressor whose binding rate is slower than approximately 1/s. Finally, we discuss possibility of this mechanism for high activity of promoter PR in the hyp-mutant of lambda-phage.
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