1
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Doughty BR, Hinks MM, Schaepe JM, Marinov GK, Thurm AR, Rios-Martinez C, Parks BE, Tan Y, Marklund E, Dubocanin D, Bintu L, Greenleaf WJ. Single-molecule chromatin configurations link transcription factor binding to expression in human cells. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.02.578660. [PMID: 38352517 PMCID: PMC10862896 DOI: 10.1101/2024.02.02.578660] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/23/2024]
Abstract
The binding of multiple transcription factors (TFs) to genomic enhancers activates gene expression in mammalian cells. However, the molecular details that link enhancer sequence to TF binding, promoter state, and gene expression levels remain opaque. We applied single-molecule footprinting (SMF) to measure the simultaneous occupancy of TFs, nucleosomes, and components of the transcription machinery on engineered enhancer/promoter constructs with variable numbers of TF binding sites for both a synthetic and an endogenous TF. We find that activation domains enhance a TF's capacity to compete with nucleosomes for binding to DNA in a BAF-dependent manner, TF binding on nucleosome-free DNA is consistent with independent binding between TFs, and average TF occupancy linearly contributes to promoter activation rates. We also decompose TF strength into separable binding and activation terms, which can be tuned and perturbed independently. Finally, we develop thermodynamic and kinetic models that quantitatively predict both the binding microstates observed at the enhancer and subsequent time-dependent gene expression. This work provides a template for quantitative dissection of distinct contributors to gene activation, including the activity of chromatin remodelers, TF activation domains, chromatin acetylation, TF concentration, TF binding affinity, and TF binding site configuration.
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Affiliation(s)
| | - Michaela M Hinks
- Bioengineering Department, Stanford University, Stanford, CA 94305, USA
| | - Julia M Schaepe
- Bioengineering Department, Stanford University, Stanford, CA 94305, USA
| | - Georgi K Marinov
- Genetics Department, Stanford University, Stanford, CA 94305, USA
| | - Abby R Thurm
- Biophysics Graduate Program, Stanford University, Stanford, CA 94305, USA
| | | | - Benjamin E Parks
- Computer Science Department, Stanford University, Stanford, CA 94305, USA
| | - Yingxuan Tan
- Computer Science Department, Stanford University, Stanford, CA 94305, USA
| | - Emil Marklund
- Science for Life Laboratory, Department of Biochemistry and Biophysics, Stockholm University, Stockholm, Sweden
| | - Danilo Dubocanin
- Genetics Department, Stanford University, Stanford, CA 94305, USA
| | - Lacramioara Bintu
- Bioengineering Department, Stanford University, Stanford, CA 94305, USA
| | - William J Greenleaf
- Genetics Department, Stanford University, Stanford, CA 94305, USA
- Department of Applied Physics, Stanford University, Stanford, CA 94205, USA
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2
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Sporrij A, Choudhuri A, Prasad M, Muhire B, Fast EM, Manning ME, Weiss JD, Koh M, Yang S, Kingston RE, Tolstorukov MY, Clevers H, Zon LI. PGE 2 alters chromatin through H2A.Z-variant enhancer nucleosome modification to promote hematopoietic stem cell fate. Proc Natl Acad Sci U S A 2023; 120:e2220613120. [PMID: 37126722 PMCID: PMC10175842 DOI: 10.1073/pnas.2220613120] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2022] [Accepted: 03/13/2023] [Indexed: 05/03/2023] Open
Abstract
Prostaglandin E2 (PGE2) and 16,16-dimethyl-PGE2 (dmPGE2) are important regulators of hematopoietic stem and progenitor cell (HSPC) fate and offer potential to enhance stem cell therapies [C. Cutler et al. Blood 122, 3074-3081(2013); W. Goessling et al. Cell Stem Cell 8, 445-458 (2011); W. Goessling et al. Cell 136, 1136-1147 (2009)]. Here, we report that PGE2-induced changes in chromatin at enhancer regions through histone-variant H2A.Z permit acute inflammatory gene induction to promote HSPC fate. We found that dmPGE2-inducible enhancers retain MNase-accessible, H2A.Z-variant nucleosomes permissive of CREB transcription factor (TF) binding. CREB binding to enhancer nucleosomes following dmPGE2 stimulation is concomitant with deposition of histone acetyltransferases p300 and Tip60 on chromatin. Subsequent H2A.Z acetylation improves chromatin accessibility at stimuli-responsive enhancers. Our findings support a model where histone-variant nucleosomes retained within inducible enhancers facilitate TF binding. Histone-variant acetylation by TF-associated nucleosome remodelers creates the accessible nucleosome landscape required for immediate enhancer activation and gene induction. Our work provides a mechanism through which inflammatory mediators, such as dmPGE2, lead to acute transcriptional changes and modify HSPC behavior to improve stem cell transplantation.
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Affiliation(s)
- Audrey Sporrij
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA02138
- Stem Cell Program and Division of Hematology/Oncology, Boston Children’s Hospital, Boston, MA02115
| | - Avik Choudhuri
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA02138
- Stem Cell Program and Division of Hematology/Oncology, Boston Children’s Hospital, Boston, MA02115
| | - Meera Prasad
- Stem Cell Program and Division of Hematology/Oncology, Boston Children’s Hospital, Boston, MA02115
| | - Brejnev Muhire
- Department of Molecular Biology, Massachusetts General Hospital and Harvard Medical School, Boston, MA02114
| | - Eva M. Fast
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA02138
- Stem Cell Program and Division of Hematology/Oncology, Boston Children’s Hospital, Boston, MA02115
| | - Margot E. Manning
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA02138
- Stem Cell Program and Division of Hematology/Oncology, Boston Children’s Hospital, Boston, MA02115
| | - Jodi D. Weiss
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA02138
- Stem Cell Program and Division of Hematology/Oncology, Boston Children’s Hospital, Boston, MA02115
| | - Michelle Koh
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA02138
- Stem Cell Program and Division of Hematology/Oncology, Boston Children’s Hospital, Boston, MA02115
| | - Song Yang
- Stem Cell Program and Division of Hematology/Oncology, Boston Children’s Hospital, Boston, MA02115
| | - Robert E. Kingston
- Department of Molecular Biology, Massachusetts General Hospital and Harvard Medical School, Boston, MA02114
| | | | - Hans Clevers
- Oncode Institute, Hubrecht Institute, Royal Netherlands Academy of Arts and Sciences and University Medical Center Utrecht, Utrecht3584 CT, The Netherlands
- Princess Máxima Center for Pediatric Oncology, Utrecht3584 CS, The Netherlands
| | - Leonard I. Zon
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA02138
- Stem Cell Program and Division of Hematology/Oncology, Boston Children’s Hospital, Boston, MA02115
- HHMI, Harvard Stem Cell Institute, Boston, MA02115
- Harvard Medical School, Harvard Stem Cell Institute, Boston, MA02115
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3
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Alamos S, Reimer A, Westrum C, Turner MA, Talledo P, Zhao J, Luu E, Garcia HG. Minimal synthetic enhancers reveal control of the probability of transcriptional engagement and its timing by a morphogen gradient. Cell Syst 2023; 14:220-236.e3. [PMID: 36696901 PMCID: PMC10125799 DOI: 10.1016/j.cels.2022.12.008] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2021] [Revised: 09/03/2022] [Accepted: 12/21/2022] [Indexed: 01/26/2023]
Abstract
How enhancers interpret morphogen gradients to generate gene expression patterns is a central question in developmental biology. Recent studies have proposed that enhancers can dictate whether, when, and at what rate promoters engage in transcription, but the complexity of endogenous enhancers calls for theoretical models with too many free parameters to quantitatively dissect these regulatory strategies. To overcome this limitation, we established a minimal promoter-proximal synthetic enhancer in embryos of Drosophila melanogaster. Here, a gradient of the Dorsal activator is read by a single Dorsal DNA binding site. Using live imaging to quantify transcriptional activity, we found that a single binding site can regulate whether promoters engage in transcription in a concentration-dependent manner. By modulating the binding-site affinity, we determined that a gene's decision to transcribe and its transcriptional onset time can be explained by a simple model where the promoter traverses multiple kinetic barriers before transcription can ensue.
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Affiliation(s)
- Simon Alamos
- Department of Plant and Microbial Biology, University of California at Berkeley, Berkeley, CA, USA
| | - Armando Reimer
- Biophysics Graduate Group, University of California at Berkeley, Berkeley, CA, USA
| | - Clay Westrum
- Department of Physics, University of California at Berkeley, Berkeley, CA, USA
| | - Meghan A Turner
- Department of Plant and Microbial Biology, University of California at Berkeley, Berkeley, CA, USA
| | - Paul Talledo
- Department of Molecular and Cell Biology, University of California at Berkeley, Berkeley, CA, USA
| | - Jiaxi Zhao
- Department of Physics, University of California at Berkeley, Berkeley, CA, USA
| | - Emma Luu
- Department of Physics, University of California at Berkeley, Berkeley, CA, USA
| | - Hernan G Garcia
- Biophysics Graduate Group, University of California at Berkeley, Berkeley, CA, USA; Department of Physics, University of California at Berkeley, Berkeley, CA, USA; Department of Molecular and Cell Biology, University of California at Berkeley, Berkeley, CA, USA; Institute for Quantitative Biosciences-QB3, University of California at Berkeley, Berkeley, CA, USA; Chan Zuckerberg Biohub, San Francisco, CA, USA.
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4
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Understanding the Genome-Wide Transcription Response To Various cAMP Levels in Bacteria Using Phenomenological Models. mSystems 2022; 7:e0090022. [PMID: 36409084 PMCID: PMC9765429 DOI: 10.1128/msystems.00900-22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
Attempts to understand gene regulation by global transcription factors have largely been limited to expression studies under binary conditions of presence and absence of the transcription factor. Studies addressing genome-wide transcriptional responses to changing transcription factor concentration at high resolution are lacking. Here, we create a data set containing the entire Escherichia coli transcriptome in Luria-Bertani (LB) broth as it responds to 10 different cAMP concentrations spanning the biological range. We use the Hill's model to accurately summarize individual gene responses into three intuitively understandable parameters, Emax, n, and k, reflecting the sensitivity, nonlinearity, and midpoint of the dynamic range. Our data show that most cAMP-regulated genes have an n of >2, with their k values centered around the wild-type concentration of cAMP. Additionally, cAMP receptor protein (CRP) affinity to a promoter is correlated with Emax but not k, hinting that a high-affinity CRP promoter need not ensure transcriptional activation at lower cAMP concentrations and instead affects the magnitude of the response. Finally, genes belonging to different functional classes are tuned to have different k, n, and Emax values. We demonstrate that phenomenological models are a better alternative for studying gene expression trends than classical clustering methods, with the phenomenological constants providing greater insights into how genes are tuned in a regulatory network. IMPORTANCE Different genes may follow different trends in response to various transcription factor concentrations. In this study, we ask two questions: (i) what are the trends that different genes follow in response to changing transcription factor concentrations and (ii) what methods can be used to extract information from the gene trends so obtained. We demonstrate a method to analyze transcription factor concentration-dependent genome-wide expression data using phenomenological models. Conventional clustering methods and principal-component analysis (PCA) can be used to summarize trends in data but have limited interpretability. The use of phenomenological models greatly enhances the interpretability and thus utility of conventional clustering. Transformation of dose-response data into phenomenological constants opens up avenues to ask and answer many different kinds of question. We show that the phenomenological constants obtained from the model fits can be used to generate insights about network topology and allows integration of other experimental data such as chromatin immunoprecipitation sequencing (ChIP-seq) to understand the system in greater detail.
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5
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Sanford A, Kiriakov S, Khalil AS. A Toolkit for Precise, Multigene Control in Saccharomyces cerevisiae. ACS Synth Biol 2022; 11:3912-3920. [PMID: 36367334 PMCID: PMC9764411 DOI: 10.1021/acssynbio.2c00423] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
Systems that allow researchers to precisely control the expression of genes are fundamental to biological research, biotechnology, and synthetic biology. However, few inducible gene expression systems exist that can enable simultaneous multigene control under common nutritionally favorable conditions in the important model organism and chassis Saccharomyces cerevisiae. Here we repurposed ligand binding domains from mammalian type I nuclear receptors to establish a family of up to five orthogonal synthetic gene expression systems in yeast. Our systems enable tight, independent, multigene control through addition of inert hormones and are capable of driving robust and rapid gene expression outputs, in some cases achieving up to 600-fold induction. As a proof of principle, we placed expression of four enzymes from the violacein biosynthetic pathway under independent expression control to selectively route pathway flux by addition of specific inducer combinations. Our results establish a modular, versatile, and potentially expandable toolkit for multidimensional control of gene expression in yeast that can be used to construct and control naturally occurring and synthetic gene networks.
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Affiliation(s)
- Adam Sanford
- Biological
Design Center, Boston University, Boston, Massachusetts 02215, United States,Department
of Biomedical Engineering, Boston University, Boston, Massachusetts 02215, United States
| | - Szilvia Kiriakov
- Biological
Design Center, Boston University, Boston, Massachusetts 02215, United States,Program
in Molecular Biology, Cell Biology, and Biochemistry, Boston University, Boston, Massachusetts 02215, United States
| | - Ahmad S. Khalil
- Biological
Design Center, Boston University, Boston, Massachusetts 02215, United States,Department
of Biomedical Engineering, Boston University, Boston, Massachusetts 02215, United States,Program
in Molecular Biology, Cell Biology, and Biochemistry, Boston University, Boston, Massachusetts 02215, United States,Wyss
Institute for Biologically Inspired Engineering, Harvard University, Boston, Massachusetts 02115, United States,
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6
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McCormack LS, Efremov AK, Yan J. Effects of size, cooperativity, and competitive binding on protein positioning on DNA. Biophys J 2021; 120:2040-2053. [PMID: 33771470 DOI: 10.1016/j.bpj.2021.03.016] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2020] [Revised: 02/26/2021] [Accepted: 03/18/2021] [Indexed: 11/24/2022] Open
Abstract
Accurate positioning of proteins on chromosomal DNA is crucial for its proper organization as well as gene transcription regulation. Recent experiments revealed existence of periodic patterns of nucleoprotein complexes on DNA, which frequently cannot be explained by sequence-dependent binding of proteins. Previous theoretical studies suggest that such patterns typically emerge as a result of the proteins' volume-exclusion effect. However, the role of other physical factors in patterns' formation, such as the length of DNA, its sequence heterogeneity, and protein binding cooperativity/binding competition to DNA, remains unclear. To address these less understood yet important aspects, we investigated potential effects of these factors on protein positioning on finite-size DNA by using transfer-matrix calculations. It has been found that upon binding to DNA, proteins form oscillatory patterns that span over the length of up to ∼10 times the size of the protein binding site, with the shape of the patterns being strongly dependent on the length of DNA and the proteins' binding cooperativity to DNA. Furthermore, calculations showed that small variations in the proteins' affinity to DNA due to its sequence heterogeneity do not much change the main geometric characteristics of the observed protein patterns. Finally, competition between two different types of proteins for binding to DNA has been found to lead to formation of highly diverse and complex alternating positioning of the two proteins. Altogether, these results provide new insights into the roles of physicochemical properties of proteins, the DNA length, and DNA-binding competition between proteins in formation of protein positioning patterns on DNA.
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Affiliation(s)
- Leo S McCormack
- Department of Physics, Imperial College London, London, United Kingdom; Mechanobiology InstituteNational University of Singapore, Singapore, Singapore
| | - Artem K Efremov
- Mechanobiology InstituteNational University of Singapore, Singapore, Singapore.
| | - Jie Yan
- Mechanobiology InstituteNational University of Singapore, Singapore, Singapore; Department of Physics, National University of Singapore, Singapore, Singapore.
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7
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Ramalingam V, Natarajan M, Johnston J, Zeitlinger J. TATA and paused promoters active in differentiated tissues have distinct expression characteristics. Mol Syst Biol 2021; 17:e9866. [PMID: 33543829 PMCID: PMC7863008 DOI: 10.15252/msb.20209866] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2020] [Revised: 12/22/2020] [Accepted: 01/07/2021] [Indexed: 12/18/2022] Open
Abstract
Core promoter types differ in the extent to which RNA polymerase II (Pol II) pauses after initiation, but how this affects their tissue-specific gene expression characteristics is not well understood. While promoters with Pol II pausing elements are active throughout development, TATA promoters are highly active in differentiated tissues. We therefore used a genomics approach on late-stage Drosophila embryos to analyze the properties of promoter types. Using tissue-specific Pol II ChIP-seq, we found that paused promoters have high levels of paused Pol II throughout the embryo, even in tissues where the gene is not expressed, while TATA promoters only show Pol II occupancy when the gene is active. The promoter types are associated with different chromatin accessibility in ATAC-seq data and have different expression characteristics in single-cell RNA-seq data. The two promoter types may therefore be optimized for different properties: paused promoters show more consistent expression when active, while TATA promoters have lower background expression when inactive. We propose that tissue-specific genes have evolved to use two different strategies for their differential expression across tissues.
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Affiliation(s)
- Vivekanandan Ramalingam
- Stowers Institute for Medical ResearchKansas CityMOUSA
- Department of Pathology and Laboratory MedicineUniversity of Kansas Medical CenterKansas CityKSUSA
- Present address:
Department of GeneticsStanford UniversityStanfordCAUSA
| | - Malini Natarajan
- Stowers Institute for Medical ResearchKansas CityMOUSA
- Present address:
Department of Molecular Biology, Cell Biology and BiochemistryBrown UniversityProvidenceRIUSA
| | - Jeff Johnston
- Stowers Institute for Medical ResearchKansas CityMOUSA
- Present address:
Center for Pediatric Genomic MedicineChildren's MercyKansas CityMOUSA
| | - Julia Zeitlinger
- Stowers Institute for Medical ResearchKansas CityMOUSA
- Department of Pathology and Laboratory MedicineUniversity of Kansas Medical CenterKansas CityKSUSA
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8
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Guo Y, Amir A. Exploring the effect of network topology, mRNA and protein dynamics on gene regulatory network stability. Nat Commun 2021; 12:130. [PMID: 33420076 PMCID: PMC7794440 DOI: 10.1038/s41467-020-20472-x] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2020] [Accepted: 12/03/2020] [Indexed: 12/13/2022] Open
Abstract
Homeostasis of protein concentrations in cells is crucial for their proper functioning, requiring steady-state concentrations to be stable to fluctuations. Since gene expression is regulated by proteins such as transcription factors (TFs), the full set of proteins within the cell constitutes a large system of interacting components, which can become unstable. We explore factors affecting stability by coupling the dynamics of mRNAs and proteins in a growing cell. We find that mRNA degradation rate does not affect stability, contrary to previous claims. However, global structural features of the network can dramatically enhance stability. Importantly, a network resembling a bipartite graph with a lower fraction of interactions that target TFs has a higher chance of being stable. Scrambling the E. coli transcription network, we find that the biological network is significantly more stable than its randomized counterpart, suggesting that stability constraints may have shaped network structure during the course of evolution.
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Affiliation(s)
- Yipei Guo
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA
- Program in Biophysics, Harvard University, Boston, MA, 02115, USA
| | - Ariel Amir
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA.
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9
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Aditham AK, Markin CJ, Mokhtari DA, DelRosso N, Fordyce PM. High-Throughput Affinity Measurements of Transcription Factor and DNA Mutations Reveal Affinity and Specificity Determinants. Cell Syst 2020; 12:112-127.e11. [PMID: 33340452 DOI: 10.1016/j.cels.2020.11.012] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2020] [Revised: 08/08/2020] [Accepted: 11/24/2020] [Indexed: 01/28/2023]
Abstract
Transcription factors (TFs) bind regulatory DNA to control gene expression, and mutations to either TFs or DNA can alter binding affinities to rewire regulatory networks and drive phenotypic variation. While studies have profiled energetic effects of DNA mutations extensively, we lack similar information for TF variants. Here, we present STAMMP (simultaneous transcription factor affinity measurements via microfluidic protein arrays), a high-throughput microfluidic platform enabling quantitative characterization of hundreds of TF variants simultaneously. Measured affinities for ∼210 mutants of a model yeast TF (Pho4) interacting with 9 oligonucleotides (>1,800 Kds) reveal that many combinations of mutations to poorly conserved TF residues and nucleotides flanking the core binding site alter but preserve physiological binding, providing a mechanism by which combinations of mutations in cis and trans could modulate TF binding to tune occupancies during evolution. Moreover, biochemical double-mutant cycles across the TF-DNA interface reveal molecular mechanisms driving recognition, linking sequence to function. A record of this paper's Transparent Peer Review process is included in the Supplemental Information.
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Affiliation(s)
- Arjun K Aditham
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA; Stanford ChEM-H, Stanford University, Stanford, CA 94305, USA
| | - Craig J Markin
- Department of Biochemistry, Stanford University, Stanford, CA 94305, USA
| | - Daniel A Mokhtari
- Department of Biochemistry, Stanford University, Stanford, CA 94305, USA
| | - Nicole DelRosso
- Graduate Program in Biophysics, Stanford University, Stanford, CA 94305, USA
| | - Polly M Fordyce
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA; Stanford ChEM-H, Stanford University, Stanford, CA 94305, USA; Department of Genetics, Stanford University, Stanford, CA 94305, USA; Chan Zuckerberg Biohub, San Francisco, CA 94110, USA.
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10
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Abstract
Determining whether and how a gene is transcribed are two of the central processes of life. The conceptual basis for understanding such gene regulation arose from pioneering biophysical studies in eubacteria. However, eukaryotic genomes exhibit vastly greater complexity, which raises questions not addressed by this bacterial paradigm. First, how is information integrated from many widely separated binding sites to determine how a gene is transcribed? Second, does the presence of multiple energy-expending mechanisms, which are absent from eubacterial genomes, indicate that eukaryotes are capable of improved forms of genetic information processing? An updated biophysical foundation is needed to answer such questions. We describe the linear framework, a graph-based approach to Markov processes, and show that it can accommodate many previous studies in the field. Under the assumption of thermodynamic equilibrium, we introduce a language of higher-order cooperativities and show how it can rigorously quantify gene regulatory properties suggested by experiment. We point out that fundamental limits to information processing arise at thermodynamic equilibrium and can only be bypassed through energy expenditure. Finally, we outline some of the mathematical challenges that must be overcome to construct an improved biophysical understanding of gene regulation.
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Affiliation(s)
- Felix Wong
- Institute for Medical Engineering & Science, Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA.,Infectious Disease and Microbiome Program, Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA
| | - Jeremy Gunawardena
- Department of Systems Biology, Harvard Medical School, Boston, Massachusetts 02115, USA;
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11
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Precise determination of input-output mapping for multimodal gene circuits using data from transient transfection. PLoS Comput Biol 2020; 16:e1008389. [PMID: 33253149 PMCID: PMC7728399 DOI: 10.1371/journal.pcbi.1008389] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2020] [Revised: 12/10/2020] [Accepted: 09/23/2020] [Indexed: 11/19/2022] Open
Abstract
The mapping of molecular inputs to their molecular outputs (input/output, I/O mapping) is an important characteristic of gene circuits, both natural and synthetic. Experimental determination of such mappings for synthetic circuits is best performed using stably integrated genetic constructs. In mammalian cells, stable integration of complex circuits is a time-consuming process that hampers rapid characterization of multiple circuit variants. On the other hand, transient transfection is quick. However, it is an extremely noisy process and it is unclear whether the obtained data have any relevance to the input/output mapping of a circuit obtained in the case of a stable integration. Here we describe a data processing workflow, Peakfinder algorithm for flow cytometry data (PFAFF), that allows extracting precise input/output mapping from single-cell protein expression data gathered by flow cytometry after a transient transfection. The workflow builds on the numerically-proven observation that the multivariate modes of input and output expression of multi-channel flow cytometry datasets, pre-binned by the expression level of an independent transfection reporter gene, harbor cells with circuit gene copy numbers distributions that depend deterministically on the properties of a bin. We validate our method by simulating flow cytometry data for seven multi-node circuit architectures, including a complex bi-modal circuit, under stable integration and transient transfection scenarios. The workflow applied to the simulated transient transfection data results in similar conclusions to those reached with simulated stable integration data. This indicates that the input/output mapping derived from transient transfection data using our method is an excellent approximation of the ground truth. Thus, the method allows to determine input/output mapping of complex gene network using noisy transient transfection data. One of the key features of a gene circuit is its input/output behavior. A few earlier publications attempted to develop methods to extract this behavior using transient transfection of circuit components in mammalian cells. However, the hitherto developed methods are only suitable for circuit with monomodal output distribution. Moreover, the relationship between the extracted I/O mapping and the "ground truth" that would have obtained with stably-integrated circuits, has not been addressed. Here we explore cell populations easily identifiable in flow cytometry data, namely, the peaks of fluorescent readout distribution in cells binned by the common expression value of the transfection reporter, or marker, gene. Using numerical simulations, we find that the distribution of circuit copy number in these cells deterministically depends on marker fluorescence in the noise-dependent manner. Moreover, we find that this is true also in the case of bi-modal output distribution. Using the peaks of input and output distributions, we are able to reconstruct the I/O mapping of the circuit and relate it to the I/O mapping of the stably-integrated circuit. The reconstruction is enabled by a new computational method we call PFAFF. The method is extensively validated with forward-simulated flow cytometry data from stable and transient transfections, with up to seven different circuits. The results show excellent correlation between the I/O behavior extracted by PFAFF from simulated transient transfection data, and the data simulated for stably integrated circuit.
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12
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Eck E, Liu J, Kazemzadeh-Atoufi M, Ghoreishi S, Blythe SA, Garcia HG. Quantitative dissection of transcription in development yields evidence for transcription-factor-driven chromatin accessibility. eLife 2020; 9:e56429. [PMID: 33074101 PMCID: PMC7738189 DOI: 10.7554/elife.56429] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2020] [Accepted: 10/16/2020] [Indexed: 12/28/2022] Open
Abstract
Thermodynamic models of gene regulation can predict transcriptional regulation in bacteria, but in eukaryotes, chromatin accessibility and energy expenditure may call for a different framework. Here, we systematically tested the predictive power of models of DNA accessibility based on the Monod-Wyman-Changeux (MWC) model of allostery, which posits that chromatin fluctuates between accessible and inaccessible states. We dissected the regulatory dynamics of hunchback by the activator Bicoid and the pioneer-like transcription factor Zelda in living Drosophila embryos and showed that no thermodynamic or non-equilibrium MWC model can recapitulate hunchback transcription. Therefore, we explored a model where DNA accessibility is not the result of thermal fluctuations but is catalyzed by Bicoid and Zelda, possibly through histone acetylation, and found that this model can predict hunchback dynamics. Thus, our theory-experiment dialogue uncovered potential molecular mechanisms of transcriptional regulatory dynamics, a key step toward reaching a predictive understanding of developmental decision-making.
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Affiliation(s)
- Elizabeth Eck
- Biophysics Graduate Group, University of California at BerkeleyBerkeleyUnited States
| | - Jonathan Liu
- Department of Physics, University of California at BerkeleyBerkeleyUnited States
| | | | - Sydney Ghoreishi
- Department of Molecular and Cell Biology, University of California at BerkeleyBerkeleyUnited States
| | - Shelby A Blythe
- Department of Molecular Biosciences, Northwestern UniversityEvanstonUnited States
| | - Hernan G Garcia
- Biophysics Graduate Group, University of California at BerkeleyBerkeleyUnited States
- Department of Physics, University of California at BerkeleyBerkeleyUnited States
- Department of Molecular and Cell Biology, University of California at BerkeleyBerkeleyUnited States
- Institute for Quantitative Biosciences-QB3, University of California at BerkeleyBerkeleyUnited States
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13
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Kinetic control of stationary flux ratios for a wide range of biochemical processes. Proc Natl Acad Sci U S A 2020; 117:8884-8889. [PMID: 32265281 DOI: 10.1073/pnas.1920873117] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
One of the most intriguing features of biological systems is their ability to regulate the steady-state fluxes of the underlying biochemical reactions; however, the regulatory mechanisms and their physicochemical properties are not fully understood. Fundamentally, flux regulation can be explained with a chemical kinetic formalism describing the transitions between discrete states, with the reaction rates defined by an underlying free energy landscape. Which features of the energy landscape affect the flux distribution? Here we prove that the ratios of the steady-state fluxes of quasi-first-order biochemical processes are invariant to energy perturbations of the discrete states and are only affected by the energy barriers. In other words, the nonequilibrium flux distribution is under kinetic and not thermodynamic control. We illustrate the generality of this result for three biological processes. For the network describing protein folding along competing pathways, the probabilities of proceeding via these pathways are shown to be invariant to the stability of the intermediates or to the presence of additional misfolded states. For the network describing protein synthesis, the error rate and the energy expenditure per peptide bond is proven to be independent of the stability of the intermediate states. For molecular motors such as myosin-V, the ratio of forward to backward steps and the number of adenosine 5'-triphosphate (ATP) molecules hydrolyzed per step is demonstrated to be invariant to energy perturbations of the intermediate states. These findings place important constraints on the ability of mutations and drug perturbations to affect the steady-state flux distribution for a wide class of biological processes.
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14
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Schikora-Tamarit MÀ, Lopez-Grado I Salinas G, Gonzalez-Navasa C, Calderón I, Marcos-Fa X, Sas M, Carey LB. Promoter Activity Buffering Reduces the Fitness Cost of Misregulation. Cell Rep 2019; 24:755-765. [PMID: 30021171 DOI: 10.1016/j.celrep.2018.06.059] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2017] [Revised: 05/04/2018] [Accepted: 06/14/2018] [Indexed: 01/21/2023] Open
Abstract
Organisms regulate gene expression through changes in the activity of transcription factors (TFs). In yeast, the response of genes to changes in TF activity is generally assumed to be encoded in the promoter. To directly test this assumption, we chose 42 genes and, for each, replaced the promoter with a synthetic inducible promoter and measured how protein expression changes as a function of TF activity. Most genes exhibited gene-specific TF dose-response curves not due to differences in mRNA stability, translation, or protein stability. Instead, most genes have an intrinsic ability to buffer the effects of promoter activity. This can be encoded in the open reading frame and the 3' end of genes and can be implemented by both autoregulatory feedback and by titration of limiting trans regulators. We show experimentally and computationally that, when misexpression of a gene is deleterious, this buffering insulates cells from fitness defects due to misregulation.
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Affiliation(s)
- Miquel Àngel Schikora-Tamarit
- Systems Bioengineering Program, Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Carrer Dr. Aiguader 88, 08003 Barcelona, Spain
| | - Guillem Lopez-Grado I Salinas
- Systems Bioengineering Program, Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Carrer Dr. Aiguader 88, 08003 Barcelona, Spain
| | - Carolina Gonzalez-Navasa
- Systems Bioengineering Program, Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Carrer Dr. Aiguader 88, 08003 Barcelona, Spain
| | - Irene Calderón
- Systems Bioengineering Program, Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Carrer Dr. Aiguader 88, 08003 Barcelona, Spain
| | - Xavi Marcos-Fa
- Systems Bioengineering Program, Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Carrer Dr. Aiguader 88, 08003 Barcelona, Spain
| | - Miquel Sas
- Systems Bioengineering Program, Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Carrer Dr. Aiguader 88, 08003 Barcelona, Spain
| | - Lucas B Carey
- Systems Bioengineering Program, Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Carrer Dr. Aiguader 88, 08003 Barcelona, Spain.
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15
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Friedrich D, Friedel L, Finzel A, Herrmann A, Preibisch S, Loewer A. Stochastic transcription in the p53-mediated response to DNA damage is modulated by burst frequency. Mol Syst Biol 2019; 15:e9068. [PMID: 31885199 PMCID: PMC6886302 DOI: 10.15252/msb.20199068] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2019] [Revised: 11/04/2019] [Accepted: 11/07/2019] [Indexed: 12/15/2022] Open
Abstract
Discontinuous transcription has been described for different mammalian cell lines and numerous promoters. However, our knowledge of how the activity of individual promoters is adjusted by dynamic signaling inputs from transcription factors is limited. To address this question, we characterized the activity of selected target genes that are regulated by pulsatile accumulation of the tumor suppressor p53 in response to ionizing radiation. We performed time-resolved measurements of gene expression at the single-cell level by smFISH and used the resulting data to inform a mathematical model of promoter activity. We found that p53 target promoters are regulated by frequency modulation of stochastic bursting and can be grouped along three archetypes of gene expression. The occurrence of these archetypes cannot solely be explained by nuclear p53 abundance or promoter binding of total p53. Instead, we provide evidence that the time-varying acetylation state of p53's C-terminal lysine residues is critical for gene-specific regulation of stochastic bursting.
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Affiliation(s)
- Dhana Friedrich
- Department for BiologyTechnische Universität DarmstadtDarmstadtGermany
- Berlin Institute for Medical Systems BiologyMax Delbrück Center in the Helmholtz AssociationBerlinGermany
- Department for BiologyHumboldt Universität zu BerlinBerlinGermany
| | - Laura Friedel
- Department for BiologyTechnische Universität DarmstadtDarmstadtGermany
| | - Ana Finzel
- Berlin Institute for Medical Systems BiologyMax Delbrück Center in the Helmholtz AssociationBerlinGermany
| | - Andreas Herrmann
- Department for BiologyHumboldt Universität zu BerlinBerlinGermany
| | - Stephan Preibisch
- Berlin Institute for Medical Systems BiologyMax Delbrück Center in the Helmholtz AssociationBerlinGermany
- Janelia Research CampusHoward Hughes Medical InstituteVAAshburnUSA
| | - Alexander Loewer
- Department for BiologyTechnische Universität DarmstadtDarmstadtGermany
- Berlin Institute for Medical Systems BiologyMax Delbrück Center in the Helmholtz AssociationBerlinGermany
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16
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Wong VC, Bass VL, Bullock ME, Chavali AK, Lee REC, Mothes W, Gaudet S, Miller-Jensen K. NF-κB-Chromatin Interactions Drive Diverse Phenotypes by Modulating Transcriptional Noise. Cell Rep 2019; 22:585-599. [PMID: 29346759 DOI: 10.1016/j.celrep.2017.12.080] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2017] [Revised: 11/27/2017] [Accepted: 12/21/2017] [Indexed: 10/18/2022] Open
Abstract
Noisy gene expression generates diverse phenotypes, but little is known about mechanisms that modulate noise. Combining experiments and modeling, we studied how tumor necrosis factor (TNF) initiates noisy expression of latent HIV via the transcription factor nuclear factor κB (NF-κB) and how the HIV genomic integration site modulates noise to generate divergent (low-versus-high) phenotypes of viral activation. We show that TNF-induced transcriptional noise varies more than mean transcript number and that amplification of this noise explains low-versus-high viral activation. For a given integration site, live-cell imaging shows that NF-κB activation correlates with viral activation, but across integration sites, NF-κB activation cannot account for differences in transcriptional noise and phenotypes. Instead, differences in transcriptional noise are associated with differences in chromatin state and RNA polymerase II regulation. We conclude that, whereas NF-κB regulates transcript abundance in each cell, the chromatin environment modulates noise in the population to support diverse HIV activation in response to TNF.
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Affiliation(s)
- Victor C Wong
- Department of Molecular, Cellular, and Developmental Biology, Yale University, New Haven, CT 06520, USA
| | - Victor L Bass
- Department of Molecular, Cellular, and Developmental Biology, Yale University, New Haven, CT 06520, USA
| | - M Elise Bullock
- Department of Biomedical Engineering, Yale University, New Haven, CT 06520, USA
| | - Arvind K Chavali
- Department of Biomedical Engineering, Yale University, New Haven, CT 06520, USA
| | - Robin E C Lee
- Department of Computational and Systems Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213, USA
| | - Walther Mothes
- Department of Microbial Pathogenesis, Yale School of Medicine, New Haven, CT 06536, USA
| | - Suzanne Gaudet
- Department of Cancer Biology and Center for Cancer Systems Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA.
| | - Kathryn Miller-Jensen
- Department of Molecular, Cellular, and Developmental Biology, Yale University, New Haven, CT 06520, USA; Department of Biomedical Engineering, Yale University, New Haven, CT 06520, USA.
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17
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Wong VC, Mathew S, Ramji R, Gaudet S, Miller-Jensen K. Fold-Change Detection of NF-κB at Target Genes with Different Transcript Outputs. Biophys J 2019; 116:709-724. [PMID: 30704857 PMCID: PMC6382958 DOI: 10.1016/j.bpj.2019.01.011] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2018] [Revised: 10/29/2018] [Accepted: 01/04/2019] [Indexed: 11/19/2022] Open
Abstract
The transcription factor nuclear factor (NF)-κB promotes inflammatory and stress-responsive gene transcription across a range of cell types in response to the cytokine tumor necrosis factor (TNF). Although NF-κB signaling exhibits significant variability across single cells, some target genes supporting high levels of TNF-inducible transcription exhibit fold-change detection of NF-κB, which may buffer against stochastic variation in signaling molecules. It is unknown whether fold-change detection is maintained at NF-κB target genes with low levels of TNF-inducible transcription, for which stochastic promoter events may be more pronounced. Here, we used a microfluidic cell-trapping device to measure how TNF-induced activation of NF-κB controls transcription in single Jurkat T cells at the promoters of integrated HIV and the endogenous cytokine gene IL6, which produce only a few transcripts per cell. We tracked TNF-stimulated NF-κB RelA nuclear translocation by live-cell imaging and then quantified transcript number by RNA FISH in the same cell. We found that TNF-induced transcript abundance at 2 h for low- and high-abundance target genes correlates with similar strength with the fold change in nuclear NF-κB. A computational model of TNF-NF-κB signaling, which implements fold-change detection from competition for binding to κB motifs, could reproduce fold-change detection across the experimentally measured range of transcript outputs. However, multiple model parameters affecting transcription had to be simultaneously varied across promoters to maintain fold-change detection while also matching other trends in the single-cell data for low-abundance transcripts. Our results suggest that cells use multiple biological mechanisms to tune transcriptional output while maintaining robustness of NF-κB fold-change detection.
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Affiliation(s)
- Victor C Wong
- Department of Molecular, Cellular, and Developmental Biology, Yale University, New Haven, Connecticut
| | - Shibin Mathew
- Department of Cancer Biology and Center for Cancer Systems Biology, Dana-Farber Cancer Institute, Boston, Massachusetts; Department of Genetics, Blavatnik Institute, Harvard Medical School, Boston, Massachusetts
| | - Ramesh Ramji
- Department of Biomedical Engineering, Yale University, New Haven, Connecticut
| | - Suzanne Gaudet
- Department of Cancer Biology and Center for Cancer Systems Biology, Dana-Farber Cancer Institute, Boston, Massachusetts; Department of Genetics, Blavatnik Institute, Harvard Medical School, Boston, Massachusetts.
| | - Kathryn Miller-Jensen
- Department of Molecular, Cellular, and Developmental Biology, Yale University, New Haven, Connecticut; Department of Biomedical Engineering, Yale University, New Haven, Connecticut.
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18
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Kabir MH, O'Connor MD. Stems cells, big data and compendium-based analyses for identifying cell types, signalling pathways and gene regulatory networks. Biophys Rev 2019; 11:41-50. [PMID: 30684132 DOI: 10.1007/s12551-018-0486-4] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2018] [Accepted: 11/15/2018] [Indexed: 01/31/2023] Open
Abstract
Identification of new drug and cell therapy targets for disease treatment will be facilitated by a detailed molecular understanding of normal and disease development. Human pluripotent stem cells can provide a large in vitro source of human cell types and, in a growing number of instances, also three-dimensional multicellular tissues called organoids. The application of stem cell technology to discovery and development of new therapies will be aided by detailed molecular characterisation of cell identity, cell signalling pathways and target gene networks. Big data or 'omics' techniques-particularly transcriptomics and proteomics-facilitate cell and tissue characterisation using thousands to tens-of-thousands of genes or proteins. These gene and protein profiles are analysed using existing and/or emergent bioinformatics methods, including a growing number of methods that compare sample profiles against compendia of reference samples. This review assesses how compendium-based analyses can aid the application of stem cell technology for new therapy development. This includes via robust definition of differentiated stem cell identity, as well as elucidation of complex signalling pathways and target gene networks involved in normal and diseased states.
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Affiliation(s)
- Md Humayun Kabir
- School of Medicine, Western Sydney University, Campbelltown, NSW, Australia.,Department of Computer Science and Engineering, University of Rajshahi, Rajshahi, Bangladesh
| | - Michael D O'Connor
- School of Medicine, Western Sydney University, Campbelltown, NSW, Australia. .,Medical Sciences Research Group, Western Sydney University, Campbelltown, NSW, Australia.
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19
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Zou F, Bai L. Using time-lapse fluorescence microscopy to study gene regulation. Methods 2018; 159-160:138-145. [PMID: 30599195 DOI: 10.1016/j.ymeth.2018.12.010] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2018] [Revised: 12/20/2018] [Accepted: 12/27/2018] [Indexed: 12/20/2022] Open
Abstract
Time-lapse fluorescence microscopy is a powerful tool to study gene regulation. By probing fluorescent signals in single cells over extended period of time, this method can be used to study the dynamics, noise, movement, memory, inheritance, and coordination, of gene expression during cell growth, development, and differentiation. In combination with a flow-cell device, it can also measure gene regulation by external stimuli. Due to the single cell nature and the spatial/temporal capacity, this method can often provide information that is hard to get using other methods. Here, we review the standard experimental procedures and new technical developments in this field.
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Affiliation(s)
- Fan Zou
- Department of Physics, The Pennsylvania State University, University Park, PA 16802, United States; Center for Eukaryotic Gene Regulation, The Pennsylvania State University, University Park, PA 16802, United States
| | - Lu Bai
- Department of Physics, The Pennsylvania State University, University Park, PA 16802, United States; Department of Biochemistry and Molecular Biology, The Pennsylvania State University, University Park, PA 16802, United States; Center for Eukaryotic Gene Regulation, The Pennsylvania State University, University Park, PA 16802, United States.
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20
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Ma X, Ezer D, Adryan B, Stevens TJ. Canonical and single-cell Hi-C reveal distinct chromatin interaction sub-networks of mammalian transcription factors. Genome Biol 2018; 19:174. [PMID: 30359306 PMCID: PMC6203279 DOI: 10.1186/s13059-018-1558-2] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2018] [Accepted: 10/04/2018] [Indexed: 12/20/2022] Open
Abstract
Background Transcription factor (TF) binding to regulatory DNA sites is a key determinant of cell identity within multi-cellular organisms and has been studied extensively in relation to site affinity and chromatin modifications. There has been a strong focus on the inference of TF-gene regulatory networks and TF-TF physical interaction networks. Here, we present a third type of TF network, the spatial network of co-localized TF binding sites within the three-dimensional genome. Results Using published canonical Hi-C data and single-cell genome structures, we assess the spatial proximity of a genome-wide array of potential TF-TF co-localizations in human and mouse cell lines. For individual TFs, the abundance of occupied binding sites shows a positive correspondence with their clustering in three dimensions, and this is especially apparent for weak TF binding sites and at enhancer regions. An analysis between different TF proteins identifies significantly proximal pairs, which are enriched in reported physical interactions. Furthermore, clustering of different TFs based on proximity enrichment identifies two partially segregated co-localization sub-networks, involving different TFs in different cell types. Using data from both human lymphoblastoid cells and mouse embryonic stem cells, we find that these sub-networks are enriched within, but not exclusive to, different chromosome sub-compartments that have been identified previously in Hi-C data. Conclusions This suggests that the association of TFs within spatial networks is closely coupled to gene regulatory networks. This applies to both differentiated and undifferentiated cells and is a potential causal link between lineage-specific TF binding and chromosome sub-compartment segregation. Electronic supplementary material The online version of this article (10.1186/s13059-018-1558-2) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Xiaoyan Ma
- Department of Genetics, University of Cambridge, Downing Street, Cambridge, CB2 3EH, UK
| | - Daphne Ezer
- The Alan Turing Institute for Data Science, British Library, 96 Euston Rd, Kings Cross, London, NW1 2DB, UK.,Department of Statistics, University of Warwick, Coventry, CV4 7AL, UK
| | - Boris Adryan
- Merck KGaA, Chief Digital Office, 64293, Darmstadt, Germany
| | - Tim J Stevens
- MRC Laboratory of Molecular Biology, Cambridge Biomedical Campus, Francis Crick Avenue, Cambridge, CB2 0QH, UK.
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21
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Comprehensive, high-resolution binding energy landscapes reveal context dependencies of transcription factor binding. Proc Natl Acad Sci U S A 2018; 115:E3702-E3711. [PMID: 29588420 PMCID: PMC5910820 DOI: 10.1073/pnas.1715888115] [Citation(s) in RCA: 51] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Transcription factors (TFs) are primary regulators of gene expression in cells, where they bind specific genomic target sites to control transcription. Quantitative measurements of TF-DNA binding energies can improve the accuracy of predictions of TF occupancy and downstream gene expression in vivo and shed light on how transcriptional networks are rewired throughout evolution. Here, we present a sequencing-based TF binding assay and analysis pipeline (BET-seq, for Binding Energy Topography by sequencing) capable of providing quantitative estimates of binding energies for more than one million DNA sequences in parallel at high energetic resolution. Using this platform, we measured the binding energies associated with all possible combinations of 10 nucleotides flanking the known consensus DNA target interacting with two model yeast TFs, Pho4 and Cbf1. A large fraction of these flanking mutations change overall binding energies by an amount equal to or greater than consensus site mutations, suggesting that current definitions of TF binding sites may be too restrictive. By systematically comparing estimates of binding energies output by deep neural networks (NNs) and biophysical models trained on these data, we establish that dinucleotide (DN) specificities are sufficient to explain essentially all variance in observed binding behavior, with Cbf1 binding exhibiting significantly more nonadditivity than Pho4. NN-derived binding energies agree with orthogonal biochemical measurements and reveal that dynamically occupied sites in vivo are both energetically and mutationally distant from the highest affinity sites.
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22
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Li C, Cesbron F, Oehler M, Brunner M, Höfer T. Frequency Modulation of Transcriptional Bursting Enables Sensitive and Rapid Gene Regulation. Cell Syst 2018; 6:409-423.e11. [PMID: 29454937 DOI: 10.1016/j.cels.2018.01.012] [Citation(s) in RCA: 32] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2017] [Revised: 11/16/2017] [Accepted: 01/11/2018] [Indexed: 01/17/2023]
Abstract
Gene regulation is a complex non-equilibrium process. Here, we show that quantitating the temporal regulation of key gene states (transcriptionally inactive, active, and refractory) provides a parsimonious framework for analyzing gene regulation. Our theory makes two non-intuitive predictions. First, for transcription factors (TFs) that regulate transcription burst frequency, as opposed to amplitude or duration, weak TF binding is sufficient to elicit strong transcriptional responses. Second, refractoriness of a gene after a transcription burst enables rapid responses to stimuli. We validate both predictions experimentally by exploiting the natural, optogenetic-like responsiveness of the Neurospora GATA-type TF White Collar Complex (WCC) to blue light. Further, we demonstrate that differential regulation of WCC target genes is caused by different gene activation rates, not different TF occupancy, and that these rates are tuned by both the core promoter and the distance between TF-binding site and core promoter. In total, our work demonstrates the relevance of a kinetic, non-equilibrium framework for understanding transcriptional regulation.
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Affiliation(s)
- Congxin Li
- Division of Theoretical Systems Biology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany; Bioquant Center, Heidelberg University, 69120 Heidelberg, Germany
| | - François Cesbron
- Biochemistry Center, Heidelberg University, 69120 Heidelberg, Germany
| | - Michael Oehler
- Biochemistry Center, Heidelberg University, 69120 Heidelberg, Germany
| | - Michael Brunner
- Biochemistry Center, Heidelberg University, 69120 Heidelberg, Germany.
| | - Thomas Höfer
- Division of Theoretical Systems Biology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany; Bioquant Center, Heidelberg University, 69120 Heidelberg, Germany.
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23
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Niina T, Brandani GB, Tan C, Takada S. Sequence-dependent nucleosome sliding in rotation-coupled and uncoupled modes revealed by molecular simulations. PLoS Comput Biol 2017; 13:e1005880. [PMID: 29194442 PMCID: PMC5728581 DOI: 10.1371/journal.pcbi.1005880] [Citation(s) in RCA: 43] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2017] [Revised: 12/13/2017] [Accepted: 11/11/2017] [Indexed: 12/12/2022] Open
Abstract
While nucleosome positioning on eukaryotic genome play important roles for genetic regulation, molecular mechanisms of nucleosome positioning and sliding along DNA are not well understood. Here we investigated thermally-activated spontaneous nucleosome sliding mechanisms developing and applying a coarse-grained molecular simulation method that incorporates both long-range electrostatic and short-range hydrogen-bond interactions between histone octamer and DNA. The simulations revealed two distinct sliding modes depending on the nucleosomal DNA sequence. A uniform DNA sequence showed frequent sliding with one base pair step in a rotation-coupled manner, akin to screw-like motions. On the contrary, a strong positioning sequence, the so-called 601 sequence, exhibits rare, abrupt transitions of five and ten base pair steps without rotation. Moreover, we evaluated the importance of hydrogen bond interactions on the sliding mode, finding that strong and weak bonds favor respectively the rotation-coupled and -uncoupled sliding movements.
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Affiliation(s)
- Toru Niina
- Department of Biophysics, Graduate School of Science, Kyoto University, Kyoto, Japan
| | - Giovanni B. Brandani
- Department of Biophysics, Graduate School of Science, Kyoto University, Kyoto, Japan
| | - Cheng Tan
- Department of Biophysics, Graduate School of Science, Kyoto University, Kyoto, Japan
| | - Shoji Takada
- Department of Biophysics, Graduate School of Science, Kyoto University, Kyoto, Japan
- * E-mail:
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24
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Wadsworth GM, Parikh RY, Choy JS, Kim HD. mRNA detection in budding yeast with single fluorophores. Nucleic Acids Res 2017; 45:e141. [PMID: 28666354 PMCID: PMC5587780 DOI: 10.1093/nar/gkx568] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2017] [Accepted: 06/21/2017] [Indexed: 12/29/2022] Open
Abstract
Quantitative measurement of mRNA levels in single cells is necessary to understand phenotypic variability within an otherwise isogenic population of cells. Single-molecule mRNA Fluorescence In Situ Hybridization (FISH) has been established as the standard method for this purpose, but current protocols require a long region of mRNA to be targeted by multiple DNA probes. Here, we introduce a new single-probe FISH protocol termed sFISH for budding yeast, Saccharomyces cerevisiae using a single DNA probe labeled with a single fluorophore. In sFISH, we markedly improved probe specificity and signal-to-background ratio by using methanol fixation and inclined laser illumination. We show that sFISH reports mRNA changes that correspond to protein levels and gene copy number. Using this new FISH protocol, we can detect >50% of the total target mRNA. We also demonstrate the versatility of sFISH using FRET detection and mRNA isoform profiling as examples. Our FISH protocol with single-fluorophore sensitivity significantly reduces cost and time compared to the conventional FISH protocols and opens up new opportunities to investigate small changes in RNA at the single cell level.
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Affiliation(s)
- Gable M Wadsworth
- School of Physics, Georgia Institute of Technology, 837 State Street, Atlanta, GA 30332-0430, USA
| | - Rasesh Y Parikh
- School of Physics, Georgia Institute of Technology, 837 State Street, Atlanta, GA 30332-0430, USA
| | - John S Choy
- Department of Biology, The Catholic University of America, 620 Michigan Avenue NE, Washington, DC 20064, USA
| | - Harold D Kim
- School of Physics, Georgia Institute of Technology, 837 State Street, Atlanta, GA 30332-0430, USA
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25
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Zhou X, Blocker AW, Airoldi EM, O'Shea EK. A computational approach to map nucleosome positions and alternative chromatin states with base pair resolution. eLife 2016; 5. [PMID: 27623011 PMCID: PMC5094857 DOI: 10.7554/elife.16970] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2016] [Accepted: 09/13/2016] [Indexed: 11/13/2022] Open
Abstract
Understanding chromatin function requires knowing the precise location of nucleosomes. MNase-seq methods have been widely applied to characterize nucleosome organization in vivo, but generally lack the accuracy to determine the precise nucleosome positions. Here we develop a computational approach leveraging digestion variability to determine nucleosome positions at a base-pair resolution from MNase-seq data. We generate a variability template as a simple error model for how MNase digestion affects the mapping of individual nucleosomes. Applied to both yeast and human cells, this analysis reveals that alternatively positioned nucleosomes are prevalent and create significant heterogeneity in a cell population. We show that the periodic occurrences of dinucleotide sequences relative to nucleosome dyads can be directly determined from genome-wide nucleosome positions from MNase-seq. Alternatively positioned nucleosomes near transcription start sites likely represent different states of promoter nucleosomes during transcription initiation. Our method can be applied to map nucleosome positions in diverse organisms at base-pair resolution.
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Affiliation(s)
- Xu Zhou
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, United States.,Faculty of Arts and Sciences Center for Systems Biology, Harvard University, Cambridge, USA.,Howard Hughes Medical Institute, Harvard University, Cambridge, United States
| | | | - Edoardo M Airoldi
- Department of Statistics, Harvard University, Cambridge, United States.,The Broad Institute of MIT and Harvard, Cambridge, United States
| | - Erin K O'Shea
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, United States.,Faculty of Arts and Sciences Center for Systems Biology, Harvard University, Cambridge, USA.,Howard Hughes Medical Institute, Harvard University, Cambridge, United States.,Department of Chemistry and Chemical Biology, Harvard University, Cambridge, United States
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26
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Angelici B, Mailand E, Haefliger B, Benenson Y. Synthetic Biology Platform for Sensing and Integrating Endogenous Transcriptional Inputs in Mammalian Cells. Cell Rep 2016; 16:2525-37. [PMID: 27545896 PMCID: PMC5009115 DOI: 10.1016/j.celrep.2016.07.061] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2016] [Revised: 06/19/2016] [Accepted: 07/22/2016] [Indexed: 11/02/2022] Open
Abstract
One of the goals of synthetic biology is to develop programmable artificial gene networks that can transduce multiple endogenous molecular cues to precisely control cell behavior. Realizing this vision requires interfacing natural molecular inputs with synthetic components that generate functional molecular outputs. Interfacing synthetic circuits with endogenous mammalian transcription factors has been particularly difficult. Here, we describe a systematic approach that enables integration and transduction of multiple mammalian transcription factor inputs by a synthetic network. The approach is facilitated by a proportional amplifier sensor based on synergistic positive autoregulation. The circuits efficiently transduce endogenous transcription factor levels into RNAi, transcriptional transactivation, and site-specific recombination. They also enable AND logic between pairs of arbitrary transcription factors. The results establish a framework for developing synthetic gene networks that interface with cellular processes through transcriptional regulators.
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Affiliation(s)
- Bartolomeo Angelici
- Department of Biosystems Science and Engineering, Swiss Federal Institute of Technology (ETH Zurich), Mattenstrasse 26, 4058 Basel, Switzerland
| | - Erik Mailand
- Department of Biosystems Science and Engineering, Swiss Federal Institute of Technology (ETH Zurich), Mattenstrasse 26, 4058 Basel, Switzerland
| | - Benjamin Haefliger
- Department of Biosystems Science and Engineering, Swiss Federal Institute of Technology (ETH Zurich), Mattenstrasse 26, 4058 Basel, Switzerland
| | - Yaakov Benenson
- Department of Biosystems Science and Engineering, Swiss Federal Institute of Technology (ETH Zurich), Mattenstrasse 26, 4058 Basel, Switzerland.
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27
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Gomes ALC, Wang HH. The Role of Genome Accessibility in Transcription Factor Binding in Bacteria. PLoS Comput Biol 2016; 12:e1004891. [PMID: 27104615 PMCID: PMC4841574 DOI: 10.1371/journal.pcbi.1004891] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2015] [Accepted: 03/31/2016] [Indexed: 02/01/2023] Open
Abstract
ChIP-seq enables genome-scale identification of regulatory regions that govern gene expression. However, the biological insights generated from ChIP-seq analysis have been limited to predictions of binding sites and cooperative interactions. Furthermore, ChIP-seq data often poorly correlate with in vitro measurements or predicted motifs, highlighting that binding affinity alone is insufficient to explain transcription factor (TF)-binding in vivo. One possibility is that binding sites are not equally accessible across the genome. A more comprehensive biophysical representation of TF-binding is required to improve our ability to understand, predict, and alter gene expression. Here, we show that genome accessibility is a key parameter that impacts TF-binding in bacteria. We developed a thermodynamic model that parameterizes ChIP-seq coverage in terms of genome accessibility and binding affinity. The role of genome accessibility is validated using a large-scale ChIP-seq dataset of the M. tuberculosis regulatory network. We find that accounting for genome accessibility led to a model that explains 63% of the ChIP-seq profile variance, while a model based in motif score alone explains only 35% of the variance. Moreover, our framework enables de novo ChIP-seq peak prediction and is useful for inferring TF-binding peaks in new experimental conditions by reducing the need for additional experiments. We observe that the genome is more accessible in intergenic regions, and that increased accessibility is positively correlated with gene expression and anti-correlated with distance to the origin of replication. Our biophysically motivated model provides a more comprehensive description of TF-binding in vivo from first principles towards a better representation of gene regulation in silico, with promising applications in systems biology.
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Affiliation(s)
- Antonio L. C. Gomes
- Department of Systems Biology, Columbia University, New York, New York, United States of America
| | - Harris H. Wang
- Department of Systems Biology, Columbia University, New York, New York, United States of America
- Department of Pathology and Cell Biology, Columbia University, New York, New York, United States of America
- * E-mail:
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28
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Siwo G, Rider A, Tan A, Pinapati R, Emrich S, Chawla N, Ferdig M. Prediction of fine-tuned promoter activity from DNA sequence. F1000Res 2016; 5:158. [PMID: 27347373 PMCID: PMC4916984 DOI: 10.12688/f1000research.7485.1] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 02/08/2016] [Indexed: 12/16/2022] Open
Abstract
The quantitative prediction of transcriptional activity of genes using promoter sequence is fundamental to the engineering of biological systems for industrial purposes and understanding the natural variation in gene expression. To catalyze the development of new algorithms for this purpose, the Dialogue on Reverse Engineering Assessment and Methods (DREAM) organized a community challenge seeking predictive models of promoter activity given normalized promoter activity data for 90 ribosomal protein promoters driving expression of a fluorescent reporter gene. By developing an unbiased modeling approach that performs an iterative search for predictive DNA sequence features using the frequencies of various k-mers, inferred DNA mechanical properties and spatial positions of promoter sequences, we achieved the best performer status in this challenge. The specific predictive features used in the model included the frequency of the nucleotide G, the length of polymeric tracts of T and TA, the frequencies of 6 distinct trinucleotides and 12 tetranucleotides, and the predicted protein deformability of the DNA sequence. Our method accurately predicted the activity of 20 natural variants of ribosomal protein promoters (Spearman correlation r = 0.73) as compared to 33 laboratory-mutated variants of the promoters (r = 0.57) in a test set that was hidden from participants. Notably, our model differed substantially from the rest in 2 main ways: i) it did not explicitly utilize transcription factor binding information implying that subtle DNA sequence features are highly associated with gene expression, and ii) it was entirely based on features extracted exclusively from the 100 bp region upstream from the translational start site demonstrating that this region encodes much of the overall promoter activity. The findings from this study have important implications for the engineering of predictable gene expression systems and the evolution of gene expression in naturally occurring biological systems.
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Affiliation(s)
- Geoffrey Siwo
- Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN, USA; Department of Biological Sciences, University of Notre Dame, Notre Dame, IN, USA; Interdisciplinary Center for Network Science and Applications (iCeNSA), University of Notre Dame, Notre Dame, IN, USA; IBM TJ Watson Research Center, NY, USA; IBM Research-Africa, Johannesberg, South Africa
| | - Andrew Rider
- Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN, USA; Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, USA; Interdisciplinary Center for Network Science and Applications (iCeNSA), University of Notre Dame, Notre Dame, IN, USA
| | - Asako Tan
- Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN, USA; Department of Biological Sciences, University of Notre Dame, Notre Dame, IN, USA; Epicentre, Madison, WI, USA
| | - Richard Pinapati
- Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN, USA; Department of Biological Sciences, University of Notre Dame, Notre Dame, IN, USA; Interdisciplinary Center for Network Science and Applications (iCeNSA), University of Notre Dame, Notre Dame, IN, USA
| | - Scott Emrich
- Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN, USA; Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, USA; Interdisciplinary Center for Network Science and Applications (iCeNSA), University of Notre Dame, Notre Dame, IN, USA
| | - Nitesh Chawla
- Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN, USA; Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, USA; Interdisciplinary Center for Network Science and Applications (iCeNSA), University of Notre Dame, Notre Dame, IN, USA
| | - Michael Ferdig
- Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN, USA; Department of Biological Sciences, University of Notre Dame, Notre Dame, IN, USA; Interdisciplinary Center for Network Science and Applications (iCeNSA), University of Notre Dame, Notre Dame, IN, USA
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29
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Kharerin H, Bhat PJ, Marko JF, Padinhateeri R. Role of transcription factor-mediated nucleosome disassembly in PHO5 gene expression. Sci Rep 2016; 6:20319. [PMID: 26843321 PMCID: PMC4740855 DOI: 10.1038/srep20319] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2015] [Accepted: 12/30/2015] [Indexed: 12/11/2022] Open
Abstract
Studying nucleosome dynamics in promoter regions is crucial for understanding gene regulation. Nucleosomes regulate gene expression by sterically occluding transcription factors (TFs) and other non–histone proteins accessing genomic DNA. How the binding competition between nucleosomes and TFs leads to transcriptionally compatible promoter states is an open question. Here, we present a computational study of the nucleosome dynamics and organization in the promoter region of PHO5 gene in Saccharomyces cerevisiae. Introducing a model for nucleosome kinetics that takes into account ATP-dependent remodeling activity, DNA sequence effects, and kinetics of TFs (Pho4p), we compute the probability of obtaining different “promoter states” having different nucleosome configurations. Comparing our results with experimental data, we argue that the presence of local remodeling activity (LRA) as opposed to basal remodeling activity (BRA) is crucial in determining transcriptionally active promoter states. By modulating the LRA and Pho4p binding rate, we obtain different mRNA distributions—Poisson, bimodal, and long-tail. Through this work we explain many features of the PHO5 promoter such as sequence-dependent TF accessibility and the role of correlated dynamics between nucleosomes and TFs in opening/coverage of the TATA box. We also obtain possible ranges for TF binding rates and the magnitude of LRA.
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Affiliation(s)
- Hungyo Kharerin
- Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Mumbai 400076, India
| | - Paike J Bhat
- Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Mumbai 400076, India
| | - John F Marko
- Department of Physics, Department of Molecular Biosciences, Northwestern University, Evanston, IL
| | - Ranjith Padinhateeri
- Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Mumbai 400076, India
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30
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Ravarani CNJ, Chalancon G, Breker M, de Groot NS, Babu MM. Affinity and competition for TBP are molecular determinants of gene expression noise. Nat Commun 2016; 7:10417. [PMID: 26832815 PMCID: PMC4740812 DOI: 10.1038/ncomms10417] [Citation(s) in RCA: 45] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2015] [Accepted: 12/09/2015] [Indexed: 12/14/2022] Open
Abstract
Cell-to-cell variation in gene expression levels (noise) generates phenotypic diversity and is an important phenomenon in evolution, development and disease. TATA-box binding protein (TBP) is an essential factor that is required at virtually every eukaryotic promoter to initiate transcription. While the presence of a TATA-box motif in the promoter has been strongly linked with noise, the molecular mechanism driving this relationship is less well understood. Through an integrated analysis of multiple large-scale data sets, computer simulation and experimental validation in yeast, we provide molecular insights into how noise arises as an emergent property of variable binding affinity of TBP for different promoter sequences, competition between interaction partners to bind the same surface on TBP (to either promote or disrupt transcription initiation) and variable residence times of TBP complexes at a promoter. These determinants may be fine-tuned under different conditions and during evolution to modulate eukaryotic gene expression noise.
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Affiliation(s)
- Charles N J Ravarani
- MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge CB2 0QH, UK
| | - Guilhem Chalancon
- MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge CB2 0QH, UK
| | - Michal Breker
- Department of Molecular Genetics, Weizmann Institute of Science, Rehovot 7610001, Israel
| | | | - M Madan Babu
- MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge CB2 0QH, UK
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31
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Glick Y, Orenstein Y, Chen D, Avrahami D, Zor T, Shamir R, Gerber D. Integrated microfluidic approach for quantitative high-throughput measurements of transcription factor binding affinities. Nucleic Acids Res 2015; 44:e51. [PMID: 26635393 PMCID: PMC4824076 DOI: 10.1093/nar/gkv1327] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2015] [Accepted: 11/14/2015] [Indexed: 01/16/2023] Open
Abstract
Protein binding to DNA is a fundamental process in gene regulation. Methodologies such as ChIP-Seq and mapping of DNase I hypersensitive sites provide global information on this regulation in vivo In vitro methodologies provide valuable complementary information on protein-DNA specificities. However, current methods still do not measure absolute binding affinities. There is a real need for large-scale quantitative protein-DNA affinity measurements. We developed QPID, a microfluidic application for measuring protein-DNA affinities. A single run is equivalent to 4096 gel-shift experiments. Using QPID, we characterized the different affinities of ATF1, c-Jun, c-Fos and AP-1 to the CRE consensus motif and CRE half-site in two different genomic sequences on a single device. We discovered that binding of ATF1, but not of AP-1, to the CRE half-site is highly affected by its genomic context. This effect was highly correlated with ATF1 ChIP-seq and PBM experiments. Next, we characterized the affinities of ATF1 and ATF3 to 128 genomic CRE and CRE half-site sequences. Our affinity measurements explained that in vivo binding differences between ATF1 and ATF3 to CRE and CRE half-sites are partially mediated by differences in the minor groove width. We believe that QPID would become a central tool for quantitative characterization of biophysical aspects affecting protein-DNA binding.
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Affiliation(s)
- Yair Glick
- Mina and Evrard Goodman life science faculty, Bar Ilan University, Ramat-Gan, 5290002, Israel
| | - Yaron Orenstein
- Blavatnik School of Computer Science, Tel-Aviv University, Tel-Aviv, 69978, Israel
| | - Dana Chen
- Mina and Evrard Goodman life science faculty, Bar Ilan University, Ramat-Gan, 5290002, Israel
| | - Dorit Avrahami
- Mina and Evrard Goodman life science faculty, Bar Ilan University, Ramat-Gan, 5290002, Israel
| | - Tsaffrir Zor
- Department of Biochemistry & Molecular Biology, Life Sciences Institute, Tel-Aviv University, Tel-Aviv, 69978, Israel
| | - Ron Shamir
- Blavatnik School of Computer Science, Tel-Aviv University, Tel-Aviv, 69978, Israel
| | - Doron Gerber
- Mina and Evrard Goodman life science faculty, Bar Ilan University, Ramat-Gan, 5290002, Israel
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32
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Goldschmidt Y, Yurkovsky E, Reif A, Rosner R, Akiva A, Nachman I. Control of relative timing and stoichiometry by a master regulator. PLoS One 2015; 10:e0127339. [PMID: 26000862 PMCID: PMC4441471 DOI: 10.1371/journal.pone.0127339] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2015] [Accepted: 04/14/2015] [Indexed: 02/03/2023] Open
Abstract
Developmental processes in cells require a series of complex steps. Often only a single master regulator activates genes in these different steps. This poses several challenges: some targets need to be ordered temporally, while co-functional targets may need to be synchronized in both time and expression level. Here we study in single cells the dynamic activation patterns of early meiosis genes in budding yeast, targets of the meiosis master regulator Ime1. We quantify the individual roles of the promoter and protein levels in expression pattern control, as well as the roles of individual promoter elements. We find a consistent expression pattern difference between a non-cofunctional pair of genes, and a highly synchronized activation of a co-functional pair. We show that dynamic control leading to these patterns is distributed between promoter, gene and external regions. Through specific reciprocal changes to the promoters of pairs of genes, we show that different genes can use different promoter elements to reach near identical activation patterns.
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Affiliation(s)
- Yifat Goldschmidt
- Department of Biochemistry and Molecular Biology, Tel Aviv University, Tel Aviv, Israel
| | - Evgeny Yurkovsky
- Department of Biochemistry and Molecular Biology, Tel Aviv University, Tel Aviv, Israel
| | - Amit Reif
- Department of Biochemistry and Molecular Biology, Tel Aviv University, Tel Aviv, Israel
| | - Roni Rosner
- Department of Biochemistry and Molecular Biology, Tel Aviv University, Tel Aviv, Israel
| | - Amit Akiva
- Department of Biochemistry and Molecular Biology, Tel Aviv University, Tel Aviv, Israel
| | - Iftach Nachman
- Department of Biochemistry and Molecular Biology, Tel Aviv University, Tel Aviv, Israel
- * E-mail:
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33
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Liu ZP. Reverse Engineering of Genome-wide Gene Regulatory Networks from Gene Expression Data. Curr Genomics 2015; 16:3-22. [PMID: 25937810 PMCID: PMC4412962 DOI: 10.2174/1389202915666141110210634] [Citation(s) in RCA: 54] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2014] [Revised: 09/05/2014] [Accepted: 09/05/2014] [Indexed: 12/17/2022] Open
Abstract
Transcriptional regulation plays vital roles in many fundamental biological processes. Reverse engineering of genome-wide regulatory networks from high-throughput transcriptomic data provides a promising way to characterize the global scenario of regulatory relationships between regulators and their targets. In this review, we summarize and categorize the main frameworks and methods currently available for inferring transcriptional regulatory networks from microarray gene expression profiling data. We overview each of strategies and introduce representative methods respectively. Their assumptions, advantages, shortcomings, and possible improvements and extensions are also clarified and commented.
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Affiliation(s)
- Zhi-Ping Liu
- Department of Biomedical Engineering, School of Control Science and Engineering, Shandong University, Jinan, Shandong 250061, China
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34
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Rybakova KN, Bruggeman FJ, Tomaszewska A, Moné MJ, Carlberg C, Westerhoff HV. Multiplex Eukaryotic Transcription (In)activation: Timing, Bursting and Cycling of a Ratchet Clock Mechanism. PLoS Comput Biol 2015; 11:e1004236. [PMID: 25909187 PMCID: PMC4409292 DOI: 10.1371/journal.pcbi.1004236] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2014] [Accepted: 03/11/2015] [Indexed: 12/12/2022] Open
Abstract
Activation of eukaryotic transcription is an intricate process that relies on a multitude of regulatory proteins forming complexes on chromatin. Chromatin modifications appear to play a guiding role in protein-complex assembly on chromatin. Together, these processes give rise to stochastic, often bursting, transcriptional activity. Here we present a model of eukaryotic transcription that aims to integrate those mechanisms. We use stochastic and ordinary-differential-equation modeling frameworks to examine various possible mechanisms of gene regulation by multiple transcription factors. We find that the assembly of large transcription factor complexes on chromatin via equilibrium-binding mechanisms is highly inefficient and insensitive to concentration changes of single regulatory proteins. An alternative model that lacks these limitations is a cyclic ratchet mechanism. In this mechanism, small protein complexes assemble sequentially on the promoter. Chromatin modifications mark the completion of a protein complex assembly, and sensitize the local chromatin for the assembly of the next protein complex. In this manner, a strict order of protein complex assemblies is attained. Even though the individual assembly steps are highly stochastic in duration, a sequence of them gives rise to a remarkable precision of the transcription cycle duration. This mechanism explains how transcription activation cycles, lasting for tens of minutes, derive from regulatory proteins residing on chromatin for only tens of seconds. Transcriptional bursts are an inherent feature of such transcription activation cycles. Bursting transcription can cause individual cells to remain in synchrony transiently, offering an explanation of transcriptional cycling as observed in cell populations, both on promoter chromatin status and mRNA levels.
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Affiliation(s)
- Katja N. Rybakova
- Molecular Cell Physiology, VU University Amsterdam, Amsterdam, The Netherlands
| | - Frank J. Bruggeman
- Systems Bioinformatics, VU University Amsterdam, Amsterdam, The Netherlands
| | - Aleksandra Tomaszewska
- School of Medicine, Institute of Biomedicine, University of Eastern Finland, Kuopio, Finland
| | - Martijn J. Moné
- Molecular Cell Physiology, VU University Amsterdam, Amsterdam, The Netherlands
| | - Carsten Carlberg
- School of Medicine, Institute of Biomedicine, University of Eastern Finland, Kuopio, Finland
| | - Hans V. Westerhoff
- Molecular Cell Physiology, VU University Amsterdam, Amsterdam, The Netherlands
- Manchester Centre for Integrative Systems Biology, University of Manchester, Manchester, United Kingdom
- Synthetic Systems Biology, Netherlands Institute for Systems Biology, University of Amsterdam, Amsterdam, The Netherlands
- * E-mail:
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35
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Ariño J, Aydar E, Drulhe S, Ganser D, Jorrín J, Kahm M, Krause F, Petrezsélyová S, Yenush L, Zimmermannová O, van Heusden GPH, Kschischo M, Ludwig J, Palmer C, Ramos J, Sychrová H. Systems biology of monovalent cation homeostasis in yeast: the translucent contribution. Adv Microb Physiol 2014; 64:1-63. [PMID: 24797924 DOI: 10.1016/b978-0-12-800143-1.00001-4] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
Maintenance of monovalent cation homeostasis (mainly K(+) and Na(+)) is vital for cell survival, and cation toxicity is at the basis of a myriad of relevant phenomena, such as salt stress in crops and diverse human diseases. Full understanding of the importance of monovalent cations in the biology of the cell can only be achieved from a systemic perspective. Translucent is a multinational project developed within the context of the SysMO (System Biology of Microorganisms) initiative and focussed in the study of cation homeostasis using the well-known yeast Saccharomyces cerevisiae as a model. The present review summarize how the combination of biochemical, genetic, genomic and computational approaches has boosted our knowledge in this field, providing the basis for a more comprehensive and coherent vision of the role of monovalent cations in the biology of the cell.
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Affiliation(s)
- Joaquín Ariño
- Institut de Biotecnologia i Biomedicina & Dept. Bioquímica i Biologia Molecular, Universitat Autònoma de Barcelona, Cerdanyola del Vallès, Barcelona, Spain.
| | - Ebru Aydar
- Faculty of Life Sciences and Computing, London Metropolitan University, London, United Kingdom
| | | | | | - Jesús Jorrín
- Department of Biochemistry and Molecular Biology, University of Córdoba, Córdoba, Spain
| | - Matthias Kahm
- RheinAhrCampus, University of Applied Sciences Koblenz, Remagen, Germany
| | | | - Silvia Petrezsélyová
- Institut de Biotecnologia i Biomedicina & Dept. Bioquímica i Biologia Molecular, Universitat Autònoma de Barcelona, Cerdanyola del Vallès, Barcelona, Spain
| | - Lynne Yenush
- Instituto de Biología Molecular y Celular de Plantas, Universidad Politécnica de Valencia-Consejo Superior de Investigaciones Científicas, Valencia, Spain
| | - Olga Zimmermannová
- Department of Membrane Transport, Institute of Physiology Academy of Sciences CR, Prague, Czech Republic
| | | | - Maik Kschischo
- RheinAhrCampus, University of Applied Sciences Koblenz, Remagen, Germany
| | | | - Chris Palmer
- Faculty of Life Sciences and Computing, London Metropolitan University, London, United Kingdom
| | - José Ramos
- Department of Microbiology, University of Córdoba, Córdoba, Spain
| | - Hana Sychrová
- Department of Membrane Transport, Institute of Physiology Academy of Sciences CR, Prague, Czech Republic
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36
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Ahsendorf T, Wong F, Eils R, Gunawardena J. A framework for modelling gene regulation which accommodates non-equilibrium mechanisms. BMC Biol 2014; 12:102. [PMID: 25475875 PMCID: PMC4288563 DOI: 10.1186/s12915-014-0102-4] [Citation(s) in RCA: 45] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2014] [Accepted: 11/21/2014] [Indexed: 12/22/2022] Open
Abstract
BACKGROUND Gene regulation has, for the most part, been quantitatively analysed by assuming that regulatory mechanisms operate at thermodynamic equilibrium. This formalism was originally developed to analyse the binding and unbinding of transcription factors from naked DNA in eubacteria. Although widely used, it has made it difficult to understand the role of energy-dissipating, epigenetic mechanisms, such as DNA methylation, nucleosome remodelling and post-translational modification of histones and co-regulators, which act together with transcription factors to regulate gene expression in eukaryotes. RESULTS Here, we introduce a graph-based framework that can accommodate non-equilibrium mechanisms. A gene-regulatory system is described as a graph, which specifies the DNA microstates (vertices), the transitions between microstates (edges) and the transition rates (edge labels). The graph yields a stochastic master equation for how microstate probabilities change over time. We show that this framework has broad scope by providing new insights into three very different ad hoc models, of steroid-hormone responsive genes, of inherently bounded chromatin domains and of the yeast PHO5 gene. We find, moreover, surprising complexity in the regulation of PHO5, which has not yet been experimentally explored, and we show that this complexity is an inherent feature of being away from equilibrium. At equilibrium, microstate probabilities do not depend on how a microstate is reached but, away from equilibrium, each path to a microstate can contribute to its steady-state probability. Systems that are far from equilibrium thereby become dependent on history and the resulting complexity is a fundamental challenge. To begin addressing this, we introduce a graph-based concept of independence, which can be applied to sub-systems that are far from equilibrium, and prove that history-dependent complexity can be circumvented when sub-systems operate independently. CONCLUSIONS As epigenomic data become increasingly available, we anticipate that gene function will come to be represented by graphs, as gene structure has been represented by sequences, and that the methods introduced here will provide a broader foundation for understanding how genes work.
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Affiliation(s)
- Tobias Ahsendorf
- DKFZ, Heidelberg, D-69120, Germany. .,Department of Systems Biology, Harvard Medical School, 200 Longwood Avenue, Boston, 02115, USA.
| | - Felix Wong
- Harvard College, Cambridge, 02138, USA. .,Department of Systems Biology, Harvard Medical School, 200 Longwood Avenue, Boston, 02115, USA.
| | - Roland Eils
- DKFZ, Heidelberg, D-69120, Germany. .,Institute of Pharmacy and Molecular Biotechnology (IPMB) and BioQuant, University of Heidelberg, Heidelberg, Germany.
| | - Jeremy Gunawardena
- Department of Systems Biology, Harvard Medical School, 200 Longwood Avenue, Boston, 02115, USA.
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37
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Junker JP, Peterson KA, Nishi Y, Mao J, McMahon AP, van Oudenaarden A. A predictive model of bifunctional transcription factor signaling during embryonic tissue patterning. Dev Cell 2014; 31:448-60. [PMID: 25458012 DOI: 10.1016/j.devcel.2014.10.017] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2014] [Revised: 09/05/2014] [Accepted: 10/24/2014] [Indexed: 11/26/2022]
Abstract
Hedgehog signaling controls pattern formation in many vertebrate tissues. The downstream effectors of the pathway are the bifunctional Gli transcription factors, which, depending on hedgehog concentration, act as either transcriptional activators or repressors. Quantitatively understanding the interplay between Gli activator and repressor forms for patterning complex tissues is an open challenge. Here, we describe a reductionist mathematical model for how Gli activators and repressors are integrated in space and time to regulate transcriptional outputs of hedgehog signaling, using the pathway readouts Gli1 and Ptch1 as a model system. Spatially resolved measurements of absolute transcript numbers for these genes allow us to infer spatiotemporal variations of Gli activator and repressor levels. We validate our model by successfully predicting expression changes of Gli1 and Ptch1 in mutants at different developmental stages and in different tissues. Our results provide a starting point for understanding gene regulation by bifunctional transcription factors during mammalian development.
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Affiliation(s)
- Jan Philipp Junker
- Departments of Physics and Biology, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Hubrecht Institute, KNAW, and University Medical Center Utrecht, 3584 CT Utrecht, the Netherlands
| | - Kevin A Peterson
- Department of Stem Cell Biology and Regenerative Medicine, Eli and Edythe Broad Center for Regenerative Medicine and Stem Cell Research, University of Southern California Keck School of Medicine, Los Angeles, CA 90089, USA
| | - Yuichi Nishi
- Department of Stem Cell Biology and Regenerative Medicine, Eli and Edythe Broad Center for Regenerative Medicine and Stem Cell Research, University of Southern California Keck School of Medicine, Los Angeles, CA 90089, USA
| | - Junhao Mao
- Department of Cancer Biology, University of Massachusetts Medical School, Worcester, MA 01605, USA
| | - Andrew P McMahon
- Department of Stem Cell Biology and Regenerative Medicine, Eli and Edythe Broad Center for Regenerative Medicine and Stem Cell Research, University of Southern California Keck School of Medicine, Los Angeles, CA 90089, USA
| | - Alexander van Oudenaarden
- Departments of Physics and Biology, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Hubrecht Institute, KNAW, and University Medical Center Utrecht, 3584 CT Utrecht, the Netherlands.
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38
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Anink-Groenen LCM, Maarleveld TR, Verschure PJ, Bruggeman FJ. Mechanistic stochastic model of histone modification pattern formation. Epigenetics Chromatin 2014; 7:30. [PMID: 25408711 PMCID: PMC4234852 DOI: 10.1186/1756-8935-7-30] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2014] [Accepted: 10/02/2014] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND The activity of a single gene is influenced by the composition of the chromatin in which it is embedded. Nucleosome turnover, conformational dynamics, and covalent histone modifications each induce changes in the structure of chromatin and its affinity for regulatory proteins. The dynamics of histone modifications and the persistence of modification patterns for long periods are still largely unknown. RESULTS In this study, we present a stochastic mathematical model that describes the molecular mechanisms of histone modification pattern formation along a single gene, with non-phenomenological, physical parameters. We find that diffusion and recruitment properties of histone modifying enzymes together with chromatin connectivity allow for a rich repertoire of stochastic histone modification dynamics and pattern formation. We demonstrate that histone modification patterns at a single gene can be established or removed within a few minutes through diffusion and weak recruitment mechanisms of histone modification spreading. Moreover, we show that strong synergism between diffusion and weak recruitment mechanisms leads to nearly irreversible transitions in histone modification patterns providing stable patterns. In the absence of chromatin connectivity spontaneous and dynamic histone modification boundaries can be formed that are highly unstable, and spontaneous fluctuations cause them to diffuse randomly. Chromatin connectivity destabilizes this synergistic system and introduces bistability, illustrating state switching between opposing modification states of the model gene. The observed bistable long-range and localized pattern formation are critical effectors of gene expression regulation. CONCLUSION This study illustrates how the cooperative interactions between regulatory proteins and the chromatin state generate complex stochastic dynamics of gene expression regulation.
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Affiliation(s)
- Lisette C M Anink-Groenen
- Swammerdam Institute for Life Science (SILS), University of Amsterdam, Science Park 904, P.O. Box 94215, 1098 GE Amsterdam, The Netherlands
| | - Timo R Maarleveld
- Systems Bioinformatics, Amsterdam Institute for Molecules Medicines and Systems, VU University Amsterdam, Amsterdam, The Netherlands ; Life Sciences, Centrum Wiskunde & Informatica, Amsterdam, The Netherlands ; BioSolar Cells, Wageningen, The Netherlands
| | - Pernette J Verschure
- Swammerdam Institute for Life Science (SILS), University of Amsterdam, Science Park 904, P.O. Box 94215, 1098 GE Amsterdam, The Netherlands
| | - Frank J Bruggeman
- Systems Bioinformatics, Amsterdam Institute for Molecules Medicines and Systems, VU University Amsterdam, Amsterdam, The Netherlands
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39
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Abstract
The histone-like nucleoid-structuring (H-NS) protein binds to horizontally acquired genes in the bacterium Salmonella enterica serovar Typhimurium, silencing their expression. We now report that overcoming the silencing effects of H-NS imposes a delay in the expression of genes activated by the transcriptional regulator PhoP. We determine that PhoP-activated genes ancestral to Salmonella are expressed before those acquired horizontally. This expression timing reflects the in vivo occupancy of the corresponding promoters by the PhoP protein. These results are surprising because some of these horizontally acquired genes reached higher mRNA levels than ancestral genes expressed earlier and were transcribed from promoters harboring PhoP-binding sites with higher in vitro affinity for the PhoP protein. Our findings challenge the often-made assumption that for genes coregulated by a given transcription factor, early genes are transcribed to higher mRNA levels than those transcribed at later times. Moreover, they provide a singular example of how gene ancestry can impact expression timing. We report that gene ancestry dictates the expression behavior of genes under the direct control of the Salmonella transcriptional regulator PhoP. That is, ancestral genes are transcribed before horizontally acquired genes. This reflects both the need to overcome silencing by the H-NS protein of the latter genes and the architecture of the corresponding promoters. Unexpectedly, transcription levels do not reflect transcription timing. Our results illustrate how a bacterium can exhibit an elaborate temporal expression behavior among genes coregulated by a transcription factor even though the products encoded by the target genes do not participate in a morphological or developmental pathway.
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40
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Korber P, Barbaric S. The yeast PHO5 promoter: from single locus to systems biology of a paradigm for gene regulation through chromatin. Nucleic Acids Res 2014; 42:10888-902. [PMID: 25190457 PMCID: PMC4176169 DOI: 10.1093/nar/gku784] [Citation(s) in RCA: 35] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023] Open
Abstract
Chromatin dynamics crucially contributes to gene regulation. Studies of the yeast PHO5 promoter were key to establish this nowadays accepted view and continuously provide mechanistic insight in chromatin remodeling and promoter regulation, both on single locus as well as on systems level. The PHO5 promoter is a context independent chromatin switch module where in the repressed state positioned nucleosomes occlude transcription factor sites such that nucleosome remodeling is a prerequisite for and not consequence of induced gene transcription. This massive chromatin transition from positioned nucleosomes to an extensive hypersensitive site, together with respective transitions at the co-regulated PHO8 and PHO84 promoters, became a prime model for dissecting how remodelers, histone modifiers and chaperones co-operate in nucleosome remodeling upon gene induction. This revealed a surprisingly complex cofactor network at the PHO5 promoter, including five remodeler ATPases (SWI/SNF, RSC, INO80, Isw1, Chd1), and demonstrated for the first time histone eviction in trans as remodeling mode in vivo. Recently, the PHO5 promoter and the whole PHO regulon were harnessed for quantitative analyses and computational modeling of remodeling, transcription factor binding and promoter input-output relations such that this rewarding single-locus model becomes a paradigm also for theoretical and systems approaches to gene regulatory networks.
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Affiliation(s)
- Philipp Korber
- Adolf-Butenandt-Institute, Molecular Biology, University of Munich, Munich 80336, Germany
| | - Slobodan Barbaric
- Faculty of Food Technology and Biotechnology, Laboratory of Biochemistry, University of Zagreb, Zagreb 10000, Croatia
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41
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Saccharomyces cerevisiae Sen1 as a model for the study of mutations in human Senataxin that elicit cerebellar ataxia. Genetics 2014; 198:577-90. [PMID: 25116135 DOI: 10.1534/genetics.114.167585] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023] Open
Abstract
The nuclear RNA and DNA helicase Sen1 is essential in the yeast Saccharomyces cerevisiae and is required for efficient termination of RNA polymerase II transcription of many short noncoding RNA genes. However, the mechanism of Sen1 function is not understood. We created a plasmid-based genetic system to study yeast Sen1 in vivo. Using this system, we show that (1) the minimal essential region of Sen1 corresponds to the helicase domain and one of two flanking nuclear localization sequences; (2) a previously isolated terminator readthrough mutation in the Sen1 helicase domain, E1597K, is rescued by a second mutation designed to restore a salt bridge within the first RecA domain; and (3) the human ortholog of yeast Sen1, Senataxin, cannot functionally replace Sen1 in yeast. Guided by sequence homology between the conserved helicase domains of Sen1 and Senataxin, we tested the effects of 13 missense mutations that cosegregate with the inherited disorder ataxia with oculomotor apraxia type 2 on Sen1 function. Ten of the disease mutations resulted in transcription readthrough of at least one of three Sen1-dependent termination elements tested. Our genetic system will facilitate the further investigation of structure-function relationships in yeast Sen1 and its orthologs.
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42
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Gomes ALC, Abeel T, Peterson M, Azizi E, Lyubetskaya A, Carvalho L, Galagan J. Decoding ChIP-seq with a double-binding signal refines binding peaks to single-nucleotides and predicts cooperative interaction. Genome Res 2014; 24:1686-97. [PMID: 25024162 PMCID: PMC4199365 DOI: 10.1101/gr.161711.113] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
The comprehension of protein and DNA binding in vivo is essential to understand gene regulation. Chromatin immunoprecipitation followed by sequencing (ChIP-seq) provides a global map of the regulatory binding network. Most ChIP-seq analysis tools focus on identifying binding regions from coverage enrichment. However, less work has been performed to infer the physical and regulatory details inside the enriched regions. This research extends a previous blind-deconvolution approach to develop a post-peak-calling algorithm that improves binding site resolution and predicts cooperative interactions. At the core of our new method is a physically motivated model that characterizes the binding signal as an extreme value distribution. This model suggests a mathematical framework to study physical properties of DNA shearing from the ChIP-seq coverage. The model explains the ChIP-seq coverage with two signals: The first considers DNA fragments with only a single binding event, whereas the second considers fragments with two binding events (a double-binding signal). The model incorporates motif discovery and is able to detect multiple sites in an enriched region with single-nucleotide resolution, high sensitivity, and high specificity. Our method improves peak caller sensitivity, from less than 45% up to 94%, at a false positive rate < 11% for a set of 47 experimentally validated prokaryotic sites. It also improves resolution of highly enriched regions of large-scale eukaryotic data sets. The double-binding signal provides a novel application in ChIP-seq analysis: the identification of cooperative interaction. Predictions of known cooperative binding sites show a 0.85 area under an ROC curve.
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Affiliation(s)
- Antonio L C Gomes
- Bioinformatics Program, Boston University, Boston, Massachusetts 02215, USA
| | - Thomas Abeel
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA; VIB Department of Plant Systems Biology, Ghent University, 9052 Ghent, Belgium
| | - Matthew Peterson
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts 02215, USA
| | - Elham Azizi
- Bioinformatics Program, Boston University, Boston, Massachusetts 02215, USA
| | - Anna Lyubetskaya
- Bioinformatics Program, Boston University, Boston, Massachusetts 02215, USA
| | - Luís Carvalho
- Bioinformatics Program, Boston University, Boston, Massachusetts 02215, USA; Department of Mathematics and Statistics, Boston University, Boston, Massachusetts 02215, USA
| | - James Galagan
- Bioinformatics Program, Boston University, Boston, Massachusetts 02215, USA; Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA; Department of Biomedical Engineering, Boston University, Boston, Massachusetts 02215, USA;
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43
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Single-cell nucleosome mapping reveals the molecular basis of gene expression heterogeneity. Proc Natl Acad Sci U S A 2014; 111:E2462-71. [PMID: 24889621 DOI: 10.1073/pnas.1400517111] [Citation(s) in RCA: 79] [Impact Index Per Article: 7.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Nucleosomes, the basic unit of chromatin, have a critical role in the control of gene expression. Nucleosome positions have generally been determined by examining bulk populations of cells and then correlated with overall gene expression. Here, we describe a technique to determine nucleosome positioning in single cells by virtue of the ability of the nucleosome to protect DNA from GpC methylation. In the acid phosphatase inducible PHO5 gene, we find that there is significant cell-to-cell variation in nucleosome positions and shifts in nucleosome positioning correlate with changes in gene expression. However, nucleosome positioning is not absolute, and even with major shifts in gene expression, some cells fail to change nucleosome configuration. Mutations of the PHO5 promoter that introduce a poly(dA:dT) tract-stimulated gene expression under nonpermissive conditions led to shifts of positioned nucleosomes similar to induction of PHO5. By contrast, mutations that altered AA/TT/AT periodicity reduced gene expression upon PHO5 induction and stabilized nucleosomes in most cells, suggesting that enhanced nucleosome affinity for DNA antagonizes chromatin remodelers. Finally, we determined nucleosome positioning in two regions described as "fuzzy" or nucleosome-free when examined in a bulk assay. These regions consisted of distinct nucleosomes with a larger footprint for potential location and an increase population of cells lacking a nucleosome altogether. These data indicate an underlying complexity of nucleosome positioning that may contribute to the flexibility and heterogeneity of gene expression.
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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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45
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Rydenfelt M, Cox RS, Garcia H, Phillips R. Statistical mechanical model of coupled transcription from multiple promoters due to transcription factor titration. PHYSICAL REVIEW. E, STATISTICAL, NONLINEAR, AND SOFT MATTER PHYSICS 2014; 89:012702. [PMID: 24580252 PMCID: PMC4043999 DOI: 10.1103/physreve.89.012702] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/15/2012] [Revised: 10/04/2013] [Indexed: 06/03/2023]
Abstract
Transcription factors (TFs) with regulatory action at multiple promoter targets is the rule rather than the exception, with examples ranging from the cAMP receptor protein (CRP) in E. coli that regulates hundreds of different genes simultaneously to situations involving multiple copies of the same gene, such as plasmids, retrotransposons, or highly replicated viral DNA. When the number of TFs heavily exceeds the number of binding sites, TF binding to each promoter can be regarded as independent. However, when the number of TF molecules is comparable to the number of binding sites, TF titration will result in correlation ("promoter entanglement") between transcription of different genes. We develop a statistical mechanical model which takes the TF titration effect into account and use it to predict both the level of gene expression for a general set of promoters and the resulting correlation in transcription rates of different genes. Our results show that the TF titration effect could be important for understanding gene expression in many regulatory settings.
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Affiliation(s)
- Mattias Rydenfelt
- Department of Physics, California Institute of Technology, Pasadena, California 91125, USA
| | - Robert Sidney Cox
- Technology Research Association of Highly Efficient Gene Design, Kobe University, Hyogo 657-8501, Japan
| | - Hernan Garcia
- Department of Physics, Princeton University, Princeton, New Jersey 08544, USA
| | - Rob Phillips
- Department of Applied Physics, California Institute of Technology, Pasadena, California 91125, USA and Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California 91125, USA
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46
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Gunawardena J. Time-scale separation--Michaelis and Menten's old idea, still bearing fruit. FEBS J 2014; 281:473-88. [PMID: 24103070 PMCID: PMC3991559 DOI: 10.1111/febs.12532] [Citation(s) in RCA: 61] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2013] [Revised: 08/30/2013] [Accepted: 09/09/2013] [Indexed: 11/30/2022]
Abstract
Michaelis and Menten introduced to biochemistry the idea of time-scale separation, in which part of a system is assumed to be operating sufficiently fast compared to the rest so that it may be taken to have reached a steady state. This allows, in principle, the fast components to be eliminated, resulting in a simplified description of the system's behaviour. Similar ideas have been widely used in different areas of biology, including enzyme kinetics, protein allostery, receptor pharmacology, gene regulation and post-translational modification. However, the methods used have been independent and ad hoc. In the present study, we review the use of time-scale separation as a means to simplify the description of molecular complexity and discuss recent work setting out a single framework that unifies these separate calculations. The framework offers new capabilities for mathematical analysis and helps to do justice to Michaelis and Menten's insights about individual enzymes in the context of multi-enzyme biological systems.
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Affiliation(s)
- Jeremy Gunawardena
- Department of Systems Biology, Harvard Medical School 200 Longwood Avenue, Boston, MA 02115, USA. ; Tel: (617) 432 4839; Fax: (617) 432 5012
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47
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Ye Z, Chen Z, Lan X, Hara S, Sunkel B, Huang THM, Elnitski L, Wang Q, Jin VX. Computational analysis reveals a correlation of exon-skipping events with splicing, transcription and epigenetic factors. Nucleic Acids Res 2013; 42:2856-69. [PMID: 24369421 PMCID: PMC3950716 DOI: 10.1093/nar/gkt1338] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Alternative splicing (AS), in higher eukaryotes, is one of the mechanisms of post-transcriptional regulation that generate multiple transcripts from the same gene. One particular mode of AS is the skipping event where an exon may be alternatively excluded or constitutively included in the resulting mature mRNA. Both transcript isoforms from this skipping event site, i.e. in which the exon is either included (inclusion isoform) or excluded (skipping isoform), are typically present in one cell, and maintain a subtle balance that is vital to cellular function and dynamics. However, how the prevailing conditions dictate which isoform is expressed and what biological factors might influence the regulation of this process remain areas requiring further exploration. In this study, we have developed a novel computational method, graph-based exon-skipping scanner (GESS), for de novo detection of skipping event sites from raw RNA-seq reads without prior knowledge of gene annotations, as well as for determining the dominant isoform generated from such sites. We have applied our method to publicly available RNA-seq data in GM12878 and K562 cells from the ENCODE consortium and experimentally validated several skipping site predictions by RT-PCR. Furthermore, we integrated other sequencing-based genomic data to investigate the impact of splicing activities, transcription factors (TFs) and epigenetic histone modifications on splicing outcomes. Our computational analysis found that splice sites within the skipping-isoform-dominated group (SIDG) tended to exhibit weaker MaxEntScan-calculated splice site strength around middle, 'skipping', exons compared to those in the inclusion-isoform-dominated group (IIDG). We further showed the positional preference pattern of splicing factors, characterized by enrichment in the intronic splice sites immediately bordering middle exons. Finally, our analysis suggested that different epigenetic factors may introduce a variable obstacle in the process of exon-intron boundary establishment leading to skipping events.
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Affiliation(s)
- Zhenqing Ye
- Departments of Molecular Medicine, University of Texas Health Science Center at San Antonio, San Antonio, TX 78229, Department of Molecular and Cellular Biochemistry and the Comprehensive Cancer Center, The Ohio State University, Columbus, OH 43210, USA, Department of Biomedical Informatics, The Ohio State University, Columbus, OH 43210, USA Genome Technology Branch, National Human Genome Research Institute, National Institutes of Health, Rockville, MD 20852, USA and Deparment of Epidemiology and Biostatistics, University of Texas Health Science Center at San Antonio, San Antonio, TX 78229, USA
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48
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Boedicker JQ, Garcia HG, Johnson S, Phillips R. DNA sequence-dependent mechanics and protein-assisted bending in repressor-mediated loop formation. Phys Biol 2013; 10:066005. [PMID: 24231252 DOI: 10.1088/1478-3975/10/6/066005] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
As the chief informational molecule of life, DNA is subject to extensive physical manipulations. The energy required to deform double-helical DNA depends on sequence, and this mechanical code of DNA influences gene regulation, such as through nucleosome positioning. Here we examine the sequence-dependent flexibility of DNA in bacterial transcription factor-mediated looping, a context for which the role of sequence remains poorly understood. Using a suite of synthetic constructs repressed by the Lac repressor and two well-known sequences that show large flexibility differences in vitro, we make precise statistical mechanical predictions as to how DNA sequence influences loop formation and test these predictions using in vivo transcription and in vitro single-molecule assays. Surprisingly, sequence-dependent flexibility does not affect in vivo gene regulation. By theoretically and experimentally quantifying the relative contributions of sequence and the DNA-bending protein HU to DNA mechanical properties, we reveal that bending by HU dominates DNA mechanics and masks intrinsic sequence-dependent flexibility. Such a quantitative understanding of how mechanical regulatory information is encoded in the genome will be a key step towards a predictive understanding of gene regulation at single-base pair resolution.
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Affiliation(s)
- James Q Boedicker
- Departments of Applied Physics and Biology, California Institute of Technology, 1200 California Boulevard, Pasadena, CA 91125, USA
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49
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Kulaeva OI, Malyuchenko NV, Nikitin DV, Demidenko AV, Chertkov OV, Efimova NS, Kirpichnikov MP, Studitsky VM. Molecular mechanisms of transcription through a nucleosome by RNA polymerase II. Mol Biol 2013. [DOI: 10.1134/s0026893313050099] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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50
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Abstract
In previous work, we have introduced a "linear framework" for time-scale separation in biochemical systems, which is based on a labelled, directed graph, G, and an associated linear differential equation, dx/dt = L(G) ∙ x, where L(G) is the Laplacian matrix of G. Biochemical nonlinearity is encoded in the graph labels. Many central results in molecular biology can be systematically derived within this framework, including those for enzyme kinetics, allosteric proteins, G-protein coupled receptors, ion channels, gene regulation at thermodynamic equilibrium, and protein post-translational modification. In the present paper, in response to new applications, which accommodate nonequilibrium mechanisms in eukaryotic gene regulation, we lay out the mathematical foundations of the framework. We show that, for any graph and any initial condition, the dynamics always reaches a steady state, which can be algorithmically calculated. If the graph is not strongly connected, which may occur in gene regulation, we show that the dynamics can exhibit flexible behavior that resembles multistability. We further reveal an unexpected equivalence between deterministic Laplacian dynamics and the master equations of continuous-time Markov processes, which allows rigorous treatment within the framework of stochastic, single-molecule mechanisms.
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