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Evolvability and hierarchy in rewired bacterial gene networks
Open accessAbstract
Sequencing DNA from several organisms has revealed that duplication and drift of existing genes have primarily moulded the contents of a given genome. Though the effect of knocking out or overexpressing a particular gene has been studied in many organisms, no study has systematically explored the effect of adding new links in a biological network. To explore network evolvability, we constructed 598 recombinations of promoters (including regulatory regions) with different transcription or sigma-factor genes in Escherichia coli, added over a wild-type genetic background. Here we show that approximately 95% of new networks are tolerated by the bacteria, that very few alter growth, and that expression level correlates with factor position in the wild-type network hierarchy. Most importantly, we find that certain networks consistently survive over the wild type under various selection pressures. Therefore new links in the network are rarely a barrier for evolution and can even confer a fitness advantage.
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“Microbial cells have an intrinsic capacity to balance self preservation (stress protection) and nutritional competence (SPANC).”
From Adaptive laboratory evolution—Principles and applications for biotechnology (2013) · cites this paper as [158]
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“This SPANC balance was intensively studied in E. coli and is governed by strict control of processes such as stress and stringent response [158,159].”
From Adaptive laboratory evolution—Principles and applications for biotechnology (2013) · cites this paper as [158]
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Cites
Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing
Benjamini, Y., & Hochberg, Y. (1995) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1995.tb02031.x · Cited by 109,482
Emergence of Scaling in Random Networks
Barabási, A.-L., & Albert, R. (1999) · Science · doi:10.1126/science.286.5439.509 · Cited by 36,135
A Simple Sequentially Rejective Multiple Test Procedure
(1979) · Scandinavian Journal of Statistics · doi:10.2307/4615733 · Cited by 21,526
Smyth, G. K. (2004) · Statistical Applications in Genetics and Molecular Biology · doi:10.2202/1544-6115.1027 · Cited by 11,829
The complete genome sequence of Escherichia coli K-12.
Blattner, F., Plunkett, G., Bloch, C., Perna, N., Burland, V., Riley, M., Collado-Vides, J., Glasner, J. D., Rode, C., Mayhew, G., et al. (1997) · Science · doi:10.1126/science.277.5331.1453 · Cited by 7,996
Error and attack tolerance of complex networks
Albert, R., Jeong, H., & Barabási, A.-L. (2000) · Nature · doi:10.1038/35019019 · Cited by 7,534
Error and attack tolerance of complex networksPreprint
Albert, R., Jeong, H., & Barabási, A.-Ĺ. (2000) · Cited by 6,554
The Evolutionary Fate and Consequences of Duplicate Genes
Lynch, M., & Conery, J. S. (2000) · Science · doi:10.1126/science.290.5494.1151 · Cited by 4,988
A synthetic oscillatory network of transcriptional regulators
Elowitz, M., & Leibler, S. (2000) · Nature · doi:10.1038/35002125 · Cited by 4,812
Construction of a genetic toggle switch in Escherichia coli
Gardner, T. S., Cantor, C. R., & Collins, J. J. (2000) · Nature · doi:10.1038/35002131 · Cited by 4,310
Flagged first, then by citations
Research works printed but not linked: 2
- Holm, S. A simple sequentially rejective multiple test procedure. Scand. J. Stat. 6, 65–70 (1979)
- Benjamini, Y. & Hochberg, Y. Controlling the false discovery rate: A practical and powerful approach to multiple testing. J. R. Stat. Soc. B 57, 289–300 (1995) · DOI · Paper page
Cited by
Sorted by citations
Items 101–200 of 306
Improved network performance via antagonism: From synthetic rescues to multi‐drug combinations
Motter, A. E. (2010) · BioEssays · doi:10.1002/bies.200900128 · Cited by 36
“(Fitness advantage may also be conferred by rewiring of the network circuitry at the signaling or regulatory level((22)), although”
BackgroundTwo transcription factors are necessary for iron homeostasis in a salt-dwelling archaeon
Schmid, A., Pan, M., Sharma, K., & Baliga, N. S. (2010) · Nucleic Acids Research · doi:10.1093/nar/gkq1211 · Cited by 37
Jimena: efficient computing and system state identification for genetic regulatory networks
Karl, S., & Dandekar, T. (2013) · BMC Bioinformatics · doi:10.1186/1471-2105-14-306 · Cited by 35
“coli [18] or the reported phenotypical robustness of C.”
BackgroundEmergence of cooperative bistability and robustness of gene regulatory networks
Nagata, S., & Kikuchi, M. (2020) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1007969 · Cited by 34
Meysman, P., Sánchez‐Rodríguez, A., Fu, Q., Marchal, K., & Engelen, K. (2013) · Molecular Biology and Evolution · doi:10.1093/molbev/mst029 · Cited by 36
Bhardwaj, N., Carson, M. B., Abyzov, A. S., Yan, K.-K., Lu, H. J., & Gerstein, M. (2010) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000755 · Cited by 34
“There has been progress towards finding and reconstructing aspects of the cellular program of combinatorial transcriptional control [19,20,21,22,23], their integration with diverse data [24,25] and their robustness to rewiring [26].”
BackgroundLevy, S. F., & Siegal, M. L. (2012) · Advances in experimental medicine and biology · doi:10.1007/978-1-4614-3567-9_20 · Cited by 35
Constraint and Contingency in Multifunctional Gene Regulatory Circuits
Payne, J. L., & Wagner, A. (2013) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1003071 · Cited by 33
“Further, circuits are highly robust to the experimental perturbation of their architecture, such as the rewiring of regulatory interactions [20].”
BackgroundHinman, V. F., Yankura, K. A., & McCauley, B. S. (2009) · Biochimica et Biophysica Acta (BBA) - Gene Regulatory Mechanisms · doi:10.1016/j.bbagrm.2009.01.004 · Cited by 32
Silva‐Rocha, R., & de Lorenzo, V. (2012) · Molecular BioSystems · doi:10.1039/c2mb25030f · Cited by 33
Robustness and innovation in synthetic genotype networks
Santos‐Moreno, J., Tasiudi, E., Kusumawardhani, H., Stelling, J., & Schaerli, Y. (2023) · Nature Communications · doi:10.1038/s41467-023-38033-3 · Cited by 33
Is central dogma a global property of cellular information flow?
Piras, V., Tomita, M., & Selvarajoo, K. (2012) · Frontiers in Physiology · doi:10.3389/fphys.2012.00439 · Cited by 35
“…that upon chemical perturbation, the initial response between mRNA and protein expressions deviates due to time-delay and different kinetic mechanisms between them, as well as secondary effects such as autocrine or paracrine signaling interference (Shvartsman et al., 2002; Isalan et al., 2008).”
BackgroundModel-based redesign of global transcription regulation
Carrera, J., Rodrigo, G., & Jaramillo, A. (2009) · Nucleic Acids Research · doi:10.1093/nar/gkp022 · Cited by 36
“In this direction, we have accounted for simple transcription rewirings (44) by obtaining the gene expressions using computational methods.”
BackgroundMethodInfluentialGenetically Encoded Sender–Receiver System in 3D Mammalian Cell Culture
Carvalho, A. F., Menéndez, D. B., Senthivel, V. R., Zimmermann, T., Diambra, L. A., & Isalan, M. (2013) · ACS Synthetic Biology · doi:10.1021/sb400053b · Cited by 29
Self-citationSynthetic Biology: A Bridge Between Functional and Evolutionary Biology
Morange, M. (2009) · Biological Theory · doi:10.1162/biot_a_00003 · Cited by 31
“Nevertheless, they can help to explore the robustness of biological systems as well as their evolvability ( Isalan et al. 2008 ).”
BackgroundSynthetic mammalian gene networks as a blueprint for the design of interactive biohybrid materials
Jakobus, K., Wend, S., & Weber, W. (2011) · Chemical Society Reviews · doi:10.1039/c1cs15176b · Cited by 30
Dynamics of Bacterial Gene Regulatory Networks
Shis, D. L., Bennett, M. R., & Igoshin, O. A. (2018) · Annual Review of Biophysics · doi:10.1146/annurev-biophys-070317-032947 · Cited by 30
Otoupal, P. B., Erickson, K. E., Bordoy, A. E., & Chatterjee, A. (2016) · ACS Synthetic Biology · doi:10.1021/acssynbio.6b00050 · Cited by 29
Evolutionary regain of lost gene circuit function
Gouda, M. K., Manhart, M., & Balázsi, G. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1912257116 · Cited by 31
“Besides experimental studies of natural gene network evolution under controlled conditions [5, 8, 17-21], synthetic gene circuits can serve as well-characterized models of natural stress-response modules in evolution experiments [9, 22, 23].”
BackgroundRobustness, Evolvability, and Accessibility in Linear Genetic Programming
Hu, T., Payne, J. L., Banzhaf, W., & Moore, J. H. (2011) · Lecture notes in computer science · doi:10.1007/978-3-642-20407-4_2 · Cited by 31
“Despite this apparent paradox, empirical analyses of several natural systems have revealed that robustness can actually facilitate evolvability [12,13,14].”
BackgroundA Postgenomic Perspective on Molecular Cytogenetics
Heng, H. H., Horne, S. D., Chaudhry, S. R., Regan, S. M., Liu, G., Abdallah, B. Y., & Ye, C. J. (2017) · Current Genomics · doi:10.2174/1389202918666170717145716 · Cited by 30
Robustness and Evolvability of the Human Signaling Network
Kim, J., Vandamme, D., Kim, J., Muñoz, A. G., Kölch, W., & Cho, K. (2014) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1003763 · Cited by 28
Escherichia coli transcriptional regulatory network
Martínez‐Antonio, A. (2014) · Figshare · doi:10.6084/m9.figshare.1282464 · Cited by 28
Structure, evolution and dynamics of transcriptional regulatory networks
Babu, M. M. (2010) · Biochemical Society Transactions · doi:10.1042/bst0381155 · Cited by 28
Adaptation by stochastic switching of a monostable genetic circuit in Escherichia coli
Tsuru, S., Yasuda, N., Murakami, Y., Ushioda, J., Kashiwagi, A., Suzuki, S., Mori, K., Ying, B., & Yomo, T. (2011) · Molecular Systems Biology · doi:10.1038/msb.2011.24 · Cited by 26
Lamrabet, O., PLUMBRIDGE, J. A., Martin, M., Lenski, R. E., Schneider, D., & Hindré, T. (2019) · Molecular Biology and Evolution · doi:10.1093/molbev/msz042 · Cited by 23
“Previous studies have shown that some bacterial regulatory networks are resilient to structural alterations (Isalan et al. 2008; Fitzgerald et al. 2015).”
BackgroundLocal genetic context shapes the function of a gene regulatory network
Staroń, A., Tomasek, K., Carter, C. C., Sonnleitner, E., Kavčič, B., Paixão, T., & Guet, C. C. (2021) · eLife · doi:10.7554/elife.65993 · Cited by 23
Making the right connections: biological networks in the light of evolution
Cg, K., & Pinney, J. W. (2009) · BioEssays · doi:10.1002/bies.200900043 · Cited by 27
“(41) This study shows the ability of transcriptional networks to tolerate substantial modification, but more importantly demonstrates an interaction (epistasis) between such introduced links and subsequent evolutionary changes: some added links seem consistently to enable more successful adaptation…”
BackgroundThe propagation of perturbations in rewired bacterial gene networks
Baumstark, R., Hänzelmann, S., Tsuru, S., Schaerli, Y., Francesconi, M., Mancuso, F. M., Castelo, R., & Isalan, M. (2015) · Nature Communications · doi:10.1038/ncomms10105 · Cited by 22
Self-citationProtein evolution in yeast transcription factor subnetworks
Wang, Y., Franzosa, E. A., Zhang, X.-S., & Xia, Y. (2010) · Nucleic Acids Research · doi:10.1093/nar/gkq353 · Cited by 23
Re-engineering cellular physiology by rewiring high-level global regulatory genes
Fitzgerald, S. F., Dillon, S. C., Chao, T., Wiencko, H. L., Hokamp, K., Cameron, A. D. S., & Dorman, C. J. (2015) · Scientific Reports · doi:10.1038/srep17653 · Cited by 23
Unraveling the Complex Interplay of Fis and IHF Through Synthetic Promoter Engineering
Monteiro, L. M. O., Sanches-Medeiros, A., Westmann, C. A., & Silva‐Rocha, R. (2020) · Frontiers in Bioengineering and Biotechnology · doi:10.3389/fbioe.2020.00510 · Cited by 23
Rewiring cell signalling through chimaeric regulatory protein engineering
Wang, B., Barahona, M., Buck, M., & Schumacher, J. (2013) · Biochemical Society Transactions · doi:10.1042/bst20130138 · Cited by 22
Multiple Genomic Changes Associated with Reorganization of Gene Regulation and Adaptation in Yeast
David, L., Ben-Harosh, Y., Stolovicki, E., Moore, L. S., Nguyen, M., Kuehn, R., Dean, J., Mancera, E., Steinmetz, L. M., & Braun, E. (2013) · Molecular Biology and Evolution · doi:10.1093/molbev/mst071 · Cited by 22
“However, compatible with the rich repertoire of adaptation solutions is the robust yet plastic nature of gene-regulation systems (Hartwell et al. 1999; Albert et al. 2000; Mayo et al. 2006; Isalan et al. 2008; Tuch, Galgoczy, et al. 2008), which can withstand elimination of elements and readily reorganize the remainin…”
BackgroundEvolution of a population of random Boolean networks
Mihaljev, T., & Drossel, B. (2009) · The European Physical Journal B · doi:10.1140/epjb/e2009-00032-8 · Cited by 22
Kosti, I., Predrag Radivojac, A., & Mandel‐Gutfreund, Y. (2012) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002603 · Cited by 22
Silva‐Rocha, R., & de Lorenzo, V. (2011) · Molecular BioSystems · doi:10.1039/c1mb05094j · Cited by 20
Robust network clocks: Design of genetic oscillators as a complex combinatorial optimization problem
Kobayashi, Y., Shibata, T., Kuramoto, Y., & Mikhailov, A. S. (2011) · Physical Review E · doi:10.1103/physreve.83.060901 · Cited by 21
Latent phenotypes pervade gene regulatory circuits
Payne, J. L., & Wagner, A. (2014) · BMC Systems Biology · doi:10.1186/1752-0509-8-64 · Cited by 23
“Such functions are embodied in a circuit’s spatiotemporal gene expression phenotype and can often be realized by a large number of different circuits [13,16].”
BackgroundAccelerated evolution of a minimal 63–amino acid dual transcription factor
Brödel, A. K., Rodrigues, R., Jaramillo, A., & Isalan, M. (2020) · Science Advances · doi:10.1126/sciadv.aba2728 · Cited by 21
Self-citationSudhakar, P., Reck, M., Wang, W., HeFeng, F. Q., Wagner‐Döbler, I., & Zeng, A. (2014) · BMC Genomics · doi:10.1186/1471-2164-15-362 · Cited by 20
Agnati, L. F., Guidolin, D., Leo, G., Guescini, M., Pizzi, M., Stocchi, V., Spano, P., Ghidoni, R., Ciruela, F., Genedani, S., et al. (2011) · Journal of Receptors and Signal Transduction · doi:10.3109/10799893.2011.599393 · Cited by 20
Functional models for large-scale gene regulation networks: realism and fiction
Lagomarsino, M. C., Bassetti, B., Castellani, G., & Remondini, D. (1900) · Molecular BioSystems · doi:10.1039/b816841p · Cited by 20
Taylor, T., Shepherd, M. J., Jackson, R. W., & Silby, M. W. (2022) · Current Opinion in Microbiology · doi:10.1016/j.mib.2022.02.002 · Cited by 19
Emergent Properties in Complex Synthetic Bacterial Promoters
Monteiro, L. M. O., Arruda, L., & Silva‐Rocha, R. (2017) · ACS Synthetic Biology · doi:10.1021/acssynbio.7b00344 · Cited by 19
Mechanisms of antibiotic action shape the fitness landscapes of resistance mutations
Hemez, C. F., Clarelli, F., Palmer, A. C., Bleis, C., Abel, S., Chindelevitch, L., Cohen, T., & Wiesch, P. A. Z. (2022) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2022.08.030 · Cited by 18
Towards the automated engineering of a synthetic genome
Carrera, J., Rodrigo, G., & Jaramillo, A. (2009) · Molecular BioSystems · doi:10.1039/b904400k · Cited by 18
Pujato, M. A., MacCarthy, T., Fiser, A., & Bergman, A. (2013) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002865 · Cited by 20
“An abundance of theoretical and experimental evidence has shown robustness operating at many levels ranging from microRNA precursors [2] to metabolic pathways [3] and gene regulatory networks [4].”
BackgroundMotif Participation by Genes in E. coli Transcriptional Networks
Mayo, M. L., Abdelzaher, A. F., Perkins, E. J., & Ghosh, P. (2012) · Frontiers in Physiology · doi:10.3389/fphys.2012.00357 · Cited by 18
“coli), in which 598 gene promoters were altered to “rewire” its genetic network, showed that most of these new connections are tolerated by the bacteria (Isalan et al., 2008).”
BackgroundTranscriptional Network Growing Models Using Motif-Based Preferential Attachment
Abdelzaher, A. F., Musawi, A. F. A., Ghosh, P., Mayo, M. L., & Perkins, E. J. (2015) · Frontiers in Bioengineering and Biotechnology · doi:10.3389/fbioe.2015.00157 · Cited by 17
“As aproofofprinciple,someexperimentaleffortshavealreadysuc-ceededinextensively“rewiring” E. coli ’s transcriptional regulatory network (Isalan et al., 2008).”
BackgroundEvolutionary Synthetic Biology
Peisajovich, S. G. (2012) · ACS Synthetic Biology · doi:10.1021/sb300012g · Cited by 16
Using Synthetic Biology to Understand the Evolution of Gene Expression
Bayer, T. S. (2010) · Current Biology · doi:10.1016/j.cub.2010.06.049 · Cited by 18
Systems Biology: Principles and Applications in Plant Research
Coruzzi, G. M., Burga, A. R., Katari, M. S., & Gutirrez, R. A. (2009) · Wiley-Blackwell eBooks · doi:10.1002/9781444312249.ch1 · Cited by 17
“Isalan et al. (2008) recently addressed this relationship in Escherichia coli.”
BackgroundInfluentialThe low cost of recombination in creating novel phenotypes
Wagner, A. (2011) · BioEssays · doi:10.1002/bies.201100027 · Cited by 19
Zou, Y. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq333 · Cited by 15
Pechenick, D. A., Payne, J. L., & Moore, J. H. (2011) · Journal of Theoretical Biology · doi:10.1016/j.jtbi.2011.11.029 · Cited by 16
A genome wide dosage suppressor network reveals genomic robustness
Patra, B. N., Kon, Y., Yadav, G., Sevold, A., Frumkin, J. P., Vallabhajosyula, R. R., Hintze, A., Østman, B., Schossau, J., Bhan, A., et al. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkw1148 · Cited by 17
Evolutionary Systems Biology: Historical and Philosophical Perspectives on an Emerging Synthesis
O’Malley, M. A. (2012) · Advances in experimental medicine and biology · doi:10.1007/978-1-4614-3567-9_1 · Cited by 17
A self‐propagating, barcoded transposon system for the dynamic rewiring of genomic networks
English, M. A., Alcantar, M. A., & Collins, J. J. (2023) · Molecular Systems Biology · doi:10.15252/msb.202211398 · Cited by 14
Han, Y., Li, W., Filko, A., Li, J., & Zhang, F. (2023) · Nature Communications · doi:10.1038/s41467-023-41572-4 · Cited by 15
“We found that more than 98% of TF-promoter pairs fell within the two-fold-change boundaries of the median activity, indicating robust promoter activities in most TFKD conditions 18,25 .”
Mutational Robustness of Gene Regulatory Networks
van Dijk, A. D. J., van Mourik, S., & van Ham, R. C. H. J. (2012) · PLoS ONE · doi:10.1371/journal.pone.0030591 · Cited by 16
“regulatory networks can be highly robust against network rewiring [25,26,27].”
The IHF regulon of exponentially growing Pseudomonas putida cells
Silva‐Rocha, R., Chavarría, M., Kleijn, R. J., Sauer, U., & de Lorenzo, V. (2012) · Environmental Microbiology · doi:10.1111/j.1462-2920.2012.02750.x · Cited by 15
Stochastic Switching Induced Adaptation in a Starved Escherichia coli Population
Shimizu, Y., Tsuru, S., Ito, Y., Ying, B., & Yomo, T. (2011) · PLoS ONE · doi:10.1371/journal.pone.0023953 · Cited by 15
Moser, J. W., Wilson, I. B. H., & Dragosits, M. (2017) · BMC Genomics · doi:10.1186/s12864-017-3952-7 · Cited by 13
Metacode: One code to rule them all
Paredes, O., Morales, J. A., Mendizabal-Ruiz, A. P., & Romo‐Vázquez, R. (2021) · Biosystems · doi:10.1016/j.biosystems.2021.104486 · Cited by 14
Computational design of genomic transcriptional networks with adaptation to varying environments
Carrera, J., Elena, S. F., & Jaramillo, A. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1200030109 · Cited by 14
“(3) added transcriptional fusions of promoters with different master transcriptional regulators and showed that Escherichia coli (E.”
BackgroundMethodInfluentialSellerio, A. L., Bassetti, B., Isambert, H., & Lagomarsino, M. C. (2008) · Molecular BioSystems · doi:10.1039/b815339f · Cited by 14
Systems science and the art of interdisciplinary integration
Green, S., & Andersen, H. M. (2019) · Systems Research and Behavioral Science · doi:10.1002/sres.2633 · Cited by 14
“For instance, the discovery of a set of simple and highly frequent regulatory “network motifs” (Alon, 2007) has been followed by scientific and philosophical debates on the potentials and shortcoming of simple abstract models in more complex biological contexts (Green, 2015a; Isalan et al., 2008).”
BackgroundGenetic networks for the functional study of genomes
Pisabarro, A. G., Pérez, G., Lavín, J. L., & Ramı́rez, L. (2008) · Briefings in Functional Genomics and Proteomics · doi:10.1093/bfgp/eln026 · Cited by 14
Genetic properties underlying transcriptional variability across different perturbations
Tsuru, S., & Furusawa, C. (2025) · Nature Communications · doi:10.1038/s41467-025-57642-8 · Cited by 13
“Inthe Rwr dataset, E. coli TOP10(K12)strains, which harbor synthetic shuf fl ed operons 44 (referred to as rewired strains), were cultured under identical environmental conditions.”
Global coordination in adaptation to gene rewiring
Murakami, Y., Matsumoto, Y., Tsuru, S., Ying, B., & Yomo, T. (2015) · Nucleic Acids Research · doi:10.1093/nar/gku1366 · Cited by 12
Kaneko, T., & Kikuchi, M. (2022) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1009796 · Cited by 13
Robustness in phenotypic plasticity and heterogeneity patterns enabled by EMT networks
Hebbar, A., Moger, A., Hari, K., & Jolly, M. K. (2022) · Biophysical Journal · doi:10.1016/j.bpj.2022.07.017 · Cited by 11
Estimation of Gene Regulatory Networks
McCall, M. N. (2013) · Postdoc Journal · doi:10.14304/surya.jpr.v1n1.7 · Cited by 13
“Examination of cellular networks has provided insights in evolution (Isalan et al., 2008), metabolism (Ideker et al., 2001), DNA damage response (Bandyopadhyay et al., 2010), and cancer metastasis (Chuang et al., 2007).”
BackgroundBennett, M. R., & Hasty, J. (2008) · Nature · doi:10.1038/452824a · Cited by 13
The Relevance of Irrelevance: Explanation in Systems Biology
Groß, F. (2015) · History, philosophy and theory of the life sciences · doi:10.1007/978-94-017-9822-8_8 · Cited by 12
Phenotypic Robustness and the Assortativity Signature of Human Transcription Factor Networks
Pechenick, D. A., Payne, J. L., & Moore, J. H. (2014) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1003780 · Cited by 11
“Experimental work has repeatedly demonstrated the robustness of TFNs to various forms of perturbation [28,29], including noisy gene expression [30], gene knockouts [31], and the rewiring of regulatory interactions [32].”
BackgroundElucidation of the Pathogenicity-Associated Regulatory Network in Xanthomonas oryzae pv. oryzae
Zheng, D., Wang, H. H., Zhong, H., Ke, W., Hu, H., Sun, M., & Ruan, L. (2021) · mSystems · doi:10.1128/msystems.00789-20 · Cited by 12
Material ecologies for synthetic biology: Biomineralization and the state space of design
Dade‐Robertson, M., Ramirez-Figueroa, C., & Zhang, M. (2014) · Computer-Aided Design · doi:10.1016/j.cad.2014.02.012 · Cited by 12
“Some suggest that complex biological networks cannot be reduced and partitioned into discrete parts [11] and this leads to informal and often hidden SB practices.”
BackgroundHigh-Throughput Identification ofCis-Regulatory Rewiring Events in Yeast
Sarda, S., & Hannenhalli, S. S. (2015) · Molecular Biology and Evolution · doi:10.1093/molbev/msv203 · Cited by 12
“Furthermore, such rewiring might even constitute changes essential for maintaining robustness in regulatory connections (Isalan et al. 2008).”
BackgroundDiao, C. (2019) · Remote Sensing of Environment · doi:10.1016/j.rse.2019.05.003 · Cited by 12
Phenotypic Signatures Arising from Unbalanced Bacterial Growth
Tan, C., Smith, R. P., Tsai, M.-C., Schwartz, R. S., & You, L. (2014) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1003751 · Cited by 12
“Each of these metrics describes a specific aspect of a growth curve and is commonly reported in microbiology experiments [5,32].”
BackgroundNetwork design meets in silico evolutionary biology
Rodrigo, G., Carrera, J., & Elena, S. F. (2010) · Biochimie · doi:10.1016/j.biochi.2010.04.003 · Cited by 12
Synthetic biology in the analysis and engineering of signaling processes
Kämpf, M. M., & Weber, W. (2009) · Integrative Biology · doi:10.1039/b913490e · Cited by 12
Pechenick, D. A., Moore, J. H., & Payne, J. L. (2013) · Journal of Theoretical Biology · doi:10.1016/j.jtbi.2013.03.019 · Cited by 11
Systematic and synthetic approaches to rewire regulatory networks
Park, J., & Wang, H. H. (2018) · Current Opinion in Systems Biology · doi:10.1016/j.coisb.2017.12.009 · Cited by 11
Evolution and the Stability of Functional Architectures
Wimsatt, W. C. (2013) · Synthese Library/Synthese library · doi:10.1007/978-94-007-5304-4_2 · Cited by 11
Design of robust flow processing networks with time-programmed responses
Kaluza, P., & Mikhailov, A. S. (2012) · The European Physical Journal B · doi:10.1140/epjb/e2012-20433-8 · Cited by 11
Antagonistic Coevolution Drives Whack-a-Mole Sensitivity in Gene Regulatory Networks
Shin, J., & MacCarthy, T. (2015) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1004432 · Cited by 11
“coli, for example, have been shown to be robust specifically to regulatory rewiring [7].”
BackgroundMAPK transgenic circuit to improve plant stress-tolerance?
Moustafa, K. (2014) · Plant Signaling & Behavior · doi:10.4161/15592316.2014.970101 · Cited by 11
“coli), the rewiring of promoters with different transcription or sigma factor genes in hundreds of combinations were tolerated by the bacteria genome with only slight effect on the growth.(22) In plant, Navqi et al (2009) have created multiplex transgenic maize expressing at least 5 genes involved in vitamin metabolic…”
BackgroundImproving plant stress tolerance: potential applications of engineered MAPK cascades
Moustafa, K. (2014) · Trends in biotechnology · doi:10.1016/j.tibtech.2014.06.005 · Cited by 11
Bacterial Cells Carrying Synthetic Dual‐Function Operon Survived Starvation
Matsumoto, Y., Ito, Y., Tsuru, S., Ying, B., & Yomo, T. (2011) · BioMed Research International · doi:10.1155/2011/489265 · Cited by 11
“…of Biomedicine and Biotechnology Volume 2011, Article ID 489265, 10 pages doi:10.1155/2011/489265 Research Article Bacterial Cells Carrying Synthetic Dual-Function Operon Survived Starvation Yuki Matsumoto,1 Yoichiro Ito,1 Saburo Tsuru,1 Bei-Wen Ying,1 and Tetsuya Yomo1, 2, 3 1 Department…”
BackgroundInfluentialRe-thinking our understanding of immunity: Robustness in the tissue reconstruction system
Truchetet, M., & Pradeu, T. (2018) · Seminars in Immunology · doi:10.1016/j.smim.2018.02.013 · Cited by 12
“For example, a plane is robust when it continues to fly despite severe turbulence (for example thanks to the flexibility of its wings), and a bacterial cell is robust to modifications in genetic regulation when it tolerates a high number of these modifications [10].”
BackgroundThe Evolution of Gene Regulatory Mechanisms in Bacteria
Dorman, C. J., Bhriain, N. N., & Dorman, M. J. (2018) · Grand challenges in biology and biotechnology · doi:10.1007/978-3-319-69078-0_6 · Cited by 11
Building Synthetic Systems to Learn Nature’s Design Principles
Davidson, E. A., Windram, O. P. F., & Bayer, T. S. (2012) · Advances in experimental medicine and biology · doi:10.1007/978-1-4614-3567-9_19 · Cited by 10
Engineering microbial phenotypes through rewiring of genetic networks
Windram, O. P. F., Rodrigues, R., Lee, S.-J., Haines, M., & Bayer, T. S. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkx197 · Cited by 9
A synthetic synthesis to explore animal evolution and development
Perkins, M. L., Gándara, L., & Crocker, J. (2022) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2020.0517 · Cited by 9
Shepherd, M. J., Reynolds, M., Pierce, A. P., Rice, A. M., & Taylor, T. (2023) · Microbiology · doi:10.1099/mic.0.001378 · Cited by 12
Shepherd, M. J., Pierce, A. P., & Taylor, T. (2023) · PLoS Biology · doi:10.1371/journal.pbio.3002348 · Cited by 8
Process-Driven Inference of Biological Network Structure: Feasibility, Minimality, and Multiplicity
Wang, G., Rong, Y., Chen, H., Pearson, C. A. B., Du, C., Simha, R., & Zeng, C. (2012) · PLoS ONE · doi:10.1371/journal.pone.0040330 · Cited by 8
“In other words, processes with high designability are more likely to occur (or be discovered by evolution) than low-designability ones [5,65].”
Background
Metadata
- Authors
- Isalan, M., Lemerle, C., Michalodimitrakis, K., Horn, C., Beltrao, P., Raineri, E., Garriga-Canut, M., & Serrano, L.
- Affiliations
- European Molecular Biology Laboratory (ES)
- European Molecular Biology Laboratory (DE)
- Centre for Genomic Regulation (ES)
- Corresponding author
- Isalan, Mark
- Venue
- Nature
- Published
- 2008-04
- Volume
- 452
- Issue
- 7189
- Pages
- 840-845
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC2666274
- OpenAlex
- W2159993062
- Cited by
- 307
- References
- 46
- Citations by year
- 2026: 2 · 2025: 2 · 2024: 9 · 2023: 8 · 2022: 11 · 2021: 7 · 2020: 8 · 2019: 12 · 2018: 13 · 2017: 9 · 2016: 13 · 2015: 19 · 2014: 18 · 2013: 29 · 2012: 27
- FWCI
- 16.30
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- Wellcome Trust (066543, WT066543)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Evolution and Genetic Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Bacterial Genetics and Biotechnology
- Keywords
- gene regulatory network rewiring, Escherichia coli, transcription factors, sigma factor, network hierarchy, synthetic gene networks, genome rearrangement, bacterial fitness
- MeSH terms
- Escherichia coli, Genes, Bacterial, Genetic Engineering, Promoter Regions, Genetic, Selection, Genetic, Serial Passage, Sigma Factor, Transcription Factors, Gene Expression Regulation, Bacterial, Open Reading Frames, Heat-Shock Response, Evolution, Molecular, Oligonucleotide Array Sequence Analysis, Escherichia coli Proteins, Gene Regulatory Networks
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