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Gorin G, Pachter L. New and notable: Revisiting the "two cultures" through extrinsic noise. Biophys J 2024; 123:1-3. [PMID: 38041403 PMCID: PMC10808022 DOI: 10.1016/j.bpj.2023.11.3400] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2023] [Revised: 11/27/2023] [Accepted: 11/28/2023] [Indexed: 12/03/2023] Open
Affiliation(s)
- Gennady Gorin
- Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, California
| | - Lior Pachter
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California; Department of Computing and Mathematical Sciences, California Institute of Technology, Pasadena, California.
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2
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Edwards DM, Davies P, Hebenstreit D. Synergising single-cell resolution and 4sU labelling boosts inference of transcriptional bursting. Genome Biol 2023; 24:138. [PMID: 37328900 PMCID: PMC10276402 DOI: 10.1186/s13059-023-02977-y] [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: 09/06/2022] [Accepted: 05/25/2023] [Indexed: 06/18/2023] Open
Abstract
Despite the recent rise of RNA-seq datasets combining single-cell (sc) resolution with 4-thiouridine (4sU) labelling, analytical methods exploiting their power to dissect transcriptional bursting are lacking. Here, we present a mathematical model and Bayesian inference implementation to facilitate genome-wide joint parameter estimation and confidence quantification (R package: burstMCMC). We demonstrate that, unlike conventional scRNA-seq, 4sU scRNA-seq resolves temporal parameters and furthermore boosts inference of dimensionless parameters via a synergy between single-cell resolution and 4sU labelling. We apply our method to published 4sU scRNA-seq data and linked with ChIP-seq data, we uncover previously obscured associations between different parameters and histone modifications.
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Affiliation(s)
| | - Philip Davies
- School of Life Sciences, University of Warwick, Coventry, UK
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Gautam P, Sinha SK. Theoretical investigation of functional responses of bio-molecular assembly networks. SOFT MATTER 2023; 19:3803-3817. [PMID: 37191191 DOI: 10.1039/d2sm01530g] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/17/2023]
Abstract
Cooperative protein-protein and protein-DNA interactions form programmable complex assemblies, often performing non-linear gene regulatory operations involved in signal transductions and cell fate determination. The apparent structure of those complex assemblies is very similar, but their functional response strongly depends on the topology of the protein-DNA interaction networks. Here, we demonstrate how the coordinated self-assembly creates gene regulatory network motifs that corroborate the existence of a precise functional response at the molecular level using thermodynamic and dynamic analyses. Our theoretical and Monte Carlo simulations show that a complex network of interactions can form a decision-making loop, such as feedback and feed-forward circuits, only by a few molecular mechanisms. We characterize each possible network of interactions by systematic variations of free energy parameters associated with the binding among biomolecules and DNA looping. We also find that the higher-order networks exhibit alternative steady states from the stochastic dynamics of each network. We capture this signature by calculating stochastic potentials and attributing their multi-stability features. We validate our findings against the Gal promoter system in yeast cells. Overall, we show that the network topology is vital in phenotype diversity in regulatory circuits.
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Affiliation(s)
- Pankaj Gautam
- Theoretical and Computational Biophysical Chemistry Group, Department of Chemistry, Indian Institute of Technology Ropar, Rupnagar, Punjab 140001, India.
| | - Sudipta Kumar Sinha
- Theoretical and Computational Biophysical Chemistry Group, Department of Chemistry, Indian Institute of Technology Ropar, Rupnagar, Punjab 140001, India.
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4
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Mahdavi S, Salmon GL, Daghlian P, Garcia HG, Phillips R. Flexibility and sensitivity in gene regulation out of equilibrium. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.04.11.536490. [PMID: 37090612 PMCID: PMC10120662 DOI: 10.1101/2023.04.11.536490] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/25/2023]
Abstract
Cells adapt to environments and tune gene expression by controlling the concentrations of proteins and their kinetics in regulatory networks. In both eukaryotes and prokaryotes, experiments and theory increasingly attest that these networks can and do consume bio-chemical energy. How does this dissipation enable cellular behaviors unobtainable in equilibrium? This open question demands quantitative models that transcend thermodynamic equilibrium. Here we study the control of a simple, ubiquitous gene regulatory motif to explore the consequences of departing equilibrium in kinetic cycles. Employing graph theory, we find that dissipation unlocks nonmonotonicity and enhanced sensitivity of gene expression with respect to a transcription factor's concentration. These features allow a single transcription factor to act as both a repressor and activator at different levels or achieve outputs with multiple concentration regions of locally-enhanced sensitivity. We systematically dissect how energetically-driving individual transitions within regulatory networks, or pairs of transitions, generates more adjustable and sensitive phenotypic responses. Our findings quantify necessary conditions and detectable consequences of energy expenditure. These richer mathematical behaviors-feasibly accessed using biological energy budgets and rates-may empower cells to accomplish sophisticated regulation with simpler architectures than those required at equilibrium. Significance Statement Growing theoretical and experimental evidence demonstrates that cells can (and do) spend biochemical energy while regulating their genes. Here we explore the impact of departing from equilibrium in simple regulatory cycles, and learn that beyond increasing sensitivity, dissipation can unlock more flexible input-output behaviors that are otherwise forbidden without spending energy. These more complex behaviors could enable cells to perform more sophisticated functions using simpler systems than those needed at equilibrium.
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5
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Sevier SA, Hormoz S. Collective polymerase dynamics emerge from DNA supercoiling during transcription. Biophys J 2022; 121:4153-4165. [PMID: 36171726 PMCID: PMC9675029 DOI: 10.1016/j.bpj.2022.09.026] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2022] [Revised: 07/19/2022] [Accepted: 09/22/2022] [Indexed: 11/29/2022] Open
Abstract
All biological processes ultimately come from physical interactions. The mechanical properties of DNA play a critical role in transcription. RNA polymerase can over or under twist DNA (referred to as DNA supercoiling) when it moves along a gene, resulting in mechanical stresses in DNA that impact its own motion and that of other polymerases. For example, when enough supercoiling accumulates, an isolated polymerase halts, and transcription stops. DNA supercoiling can also mediate nonlocal interactions between polymerases that shape gene expression fluctuations. Here, we construct a comprehensive model of transcription that captures how RNA polymerase motion changes the degree of DNA supercoiling, which in turn feeds back into the rate at which polymerases are recruited and move along the DNA. Surprisingly, our model predicts that a group of three or more polymerases move together at a constant velocity and sustain their motion (forming what we call a polymeton), whereas one or two polymerases would have halted. We further show that accounting for the impact of DNA supercoiling on both RNA polymerase recruitment and velocity recapitulates empirical observations of gene expression fluctuations. Finally, we propose a mechanical toggle switch whereby interactions between genes are mediated by DNA twisting as opposed to proteins. Understanding the mechanical regulation of gene expression provides new insights into how endogenous genes can interact and informs the design of new forms of engineered interactions.
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Affiliation(s)
- Stuart A Sevier
- Department of Systems Biology, Harvard Medical School, Boston, Massachusetts; Department of Data Sciences, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Sahand Hormoz
- Department of Systems Biology, Harvard Medical School, Boston, Massachusetts; Department of Data Sciences, Dana-Farber Cancer Institute, Boston, Massachusetts; Broad Institute of MIT and Harvard, Cambridge, Massachusetts.
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6
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Zoller B, Gregor T, Tkačik G. Eukaryotic gene regulation at equilibrium, or non? CURRENT OPINION IN SYSTEMS BIOLOGY 2022; 31:100435. [PMID: 36590072 PMCID: PMC9802646 DOI: 10.1016/j.coisb.2022.100435] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]
Abstract
Models of transcriptional regulation that assume equilibrium binding of transcription factors have been less successful at predicting gene expression from sequence in eukaryotes than in bacteria. This could be due to the non-equilibrium nature of eukaryotic regulation. Unfortunately, the space of possible non-equilibrium mechanisms is vast and predominantly uninteresting. The key question is therefore how this space can be navigated efficiently, to focus on mechanisms and models that are biologically relevant. In this review, we advocate for the normative role of theory-theory that prescribes rather than just describes-in providing such a focus. Theory should expand its remit beyond inferring mechanistic models from data, towards identifying non-equilibrium gene regulatory schemes that may have been evolutionarily selected, despite their energy consumption, because they are precise, reliable, fast, or otherwise outperform regulation at equilibrium. We illustrate our reasoning by toy examples for which we provide simulation code.
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Affiliation(s)
- Benjamin Zoller
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA
- Joseph Henry Laboratories of Physics, Princeton University, Princeton, NJ, USA
- Department of Developmental and Stem Cell Biology UMR3738, Institut Pasteur, Paris, France
| | - Thomas Gregor
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA
- Joseph Henry Laboratories of Physics, Princeton University, Princeton, NJ, USA
- Department of Developmental and Stem Cell Biology UMR3738, Institut Pasteur, Paris, France
| | - Gašper Tkačik
- Institute of Science and Technology Austria, Klosterneuburg, Austria
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Marklund E, Mao G, Yuan J, Zikrin S, Abdurakhmanov E, Deindl S, Elf J. Sequence specificity in DNA binding is mainly governed by association. Science 2022; 375:442-445. [PMID: 35084952 DOI: 10.1126/science.abg7427] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
Abstract
Sequence-specific binding of proteins to DNA is essential for accessing genetic information. We derive a model that predicts an anticorrelation between the macroscopic association and dissociation rates of DNA binding proteins. We tested the model for thousands of different lac operator sequences with a protein binding microarray and by observing kinetics for individual lac repressor molecules in single-molecule experiments. We found that sequence specificity is mainly governed by the efficiency with which the protein recognizes different targets. The variation in probability of recognizing different targets is at least 1.7 times as large as the variation in microscopic dissociation rates. Modulating the rate of binding instead of the rate of dissociation effectively reduces the risk of the protein being retained on nontarget sequences while searching.
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Affiliation(s)
- Emil Marklund
- Department of Cell and Molecular Biology, Science for Life Laboratory, Uppsala University, Box 596, 75124, Uppsala, Sweden
| | - Guanzhong Mao
- Department of Cell and Molecular Biology, Science for Life Laboratory, Uppsala University, Box 596, 75124, Uppsala, Sweden
| | - Jinwen Yuan
- Department of Cell and Molecular Biology, Science for Life Laboratory, Uppsala University, Box 596, 75124, Uppsala, Sweden
| | - Spartak Zikrin
- Department of Cell and Molecular Biology, Science for Life Laboratory, Uppsala University, Box 596, 75124, Uppsala, Sweden
| | - Eldar Abdurakhmanov
- Drug Discovery and Development Platform, Science for Life Laboratory, Department of Chemistry, BMC, Uppsala University, Box 576, 751 23 Uppsala, Sweden
| | - Sebastian Deindl
- Department of Cell and Molecular Biology, Science for Life Laboratory, Uppsala University, Box 596, 75124, Uppsala, Sweden
| | - Johan Elf
- Department of Cell and Molecular Biology, Science for Life Laboratory, Uppsala University, Box 596, 75124, Uppsala, Sweden
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Chowdhury D, Wang C, Lu A, Zhu H. Cis-Regulatory Logic Produces Gene-Expression Noise Describing Phenotypic Heterogeneity in Bacteria. Front Genet 2021; 12:698910. [PMID: 34650591 PMCID: PMC8506120 DOI: 10.3389/fgene.2021.698910] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2021] [Accepted: 08/31/2021] [Indexed: 12/04/2022] Open
Abstract
Gene transcriptional process is random. It occurs in bursts and follows single-molecular kinetics. Intermittent bursts are measured based on their frequency and size. They influence temporal fluctuations in the abundance of total mRNA and proteins by generating distinct transcriptional variations referred to as “noise”. Noisy expression induces uncertainty because the association between transcriptional variation and the extent of gene expression fluctuation is ambiguous. The promoter architecture and remote interference of different cis-regulatory elements are the crucial determinants of noise, which is reflected in phenotypic heterogeneity. An alternative perspective considers that cellular parameters dictating genome-wide transcriptional kinetics follow a universal pattern. Research on noise and systematic perturbations of promoter sequences reinforces that both gene-specific and genome-wide regulation occur across species ranging from bacteria and yeast to animal cells. Thus, deciphering gene-expression noise is essential across different genomics applications. Amidst the mounting conflict, it is imperative to reconsider the scope, progression, and rational construction of diversified viewpoints underlying the origin of the noise. Here, we have established an indication connecting noise, gene expression variations, and bacterial phenotypic variability. This review will enhance the understanding of gene-expression noise in various scientific contexts and applications.
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Affiliation(s)
- Debajyoti Chowdhury
- HKBU Institute for Research and Continuing Education, Shenzhen, China.,Computational Medicine Lab, Hong Kong Baptist University, Hong Kong, China.,Institute of Integrated Bioinformedicine and Translational Sciences, School of Chinese Medicine, Hong Kong Baptist University, Hong Kong, China
| | - Chao Wang
- HKBU Institute for Research and Continuing Education, Shenzhen, China.,Institute of Integrated Bioinformedicine and Translational Sciences, School of Chinese Medicine, Hong Kong Baptist University, Hong Kong, China
| | - Aiping Lu
- Computational Medicine Lab, Hong Kong Baptist University, Hong Kong, China.,Institute of Integrated Bioinformedicine and Translational Sciences, School of Chinese Medicine, Hong Kong Baptist University, Hong Kong, China
| | - Hailong Zhu
- HKBU Institute for Research and Continuing Education, Shenzhen, China.,Computational Medicine Lab, Hong Kong Baptist University, Hong Kong, China.,Institute of Integrated Bioinformedicine and Translational Sciences, School of Chinese Medicine, Hong Kong Baptist University, Hong Kong, China
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9
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Mazzocca M, Colombo E, Callegari A, Mazza D. Transcription factor binding kinetics and transcriptional bursting: What do we really know? Curr Opin Struct Biol 2021; 71:239-248. [PMID: 34481381 DOI: 10.1016/j.sbi.2021.08.002] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2021] [Revised: 08/02/2021] [Accepted: 08/06/2021] [Indexed: 11/18/2022]
Abstract
In eukaryotes, transcription is a discontinuous process with mRNA being generated in bursts, after the binding of transcription factors (TFs) to regulatory elements on the genome. Live-cell single-molecule microscopy has highlighted that transcriptional bursting can be controlled by tuning TF/DNA binding kinetics. Yet the timescales of these two processes seem disconnected with TF/DNA interactions typically lasting orders of magnitude shorter than transcriptional bursts. To test models that could reconcile these discrepancies, reliable measurements of TF binding kinetics are needed, also accounting for the current limitations in performing these single-molecule measurements at specific regulatory elements. Here, we review the recent studies linking TF binding kinetics to transcriptional bursting and outline some current and future challenges that need to be addressed to provide a microscopic description of transcriptional regulation kinetics.
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Affiliation(s)
- Matteo Mazzocca
- Experimental Imaging Center, IRCCS San Raffaele Scientific Institute, Milan 20132, Italy
| | - Emanuele Colombo
- Experimental Imaging Center, IRCCS San Raffaele Scientific Institute, Milan 20132, Italy
| | | | - Davide Mazza
- Experimental Imaging Center, IRCCS San Raffaele Scientific Institute, Milan 20132, Italy.
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