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Sil P, Subbaroyan A, Kulkarni S, Martin OC, Samal A. Biologically meaningful regulatory logic enhances the convergence rate in Boolean networks and bushiness of their state transition graph. Brief Bioinform 2024; 25:bbae150. [PMID: 38581421 PMCID: PMC10998641 DOI: 10.1093/bib/bbae150] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Revised: 02/14/2024] [Accepted: 03/19/2024] [Indexed: 04/08/2024] Open
Abstract
Boolean models of gene regulatory networks (GRNs) have gained widespread traction as they can easily recapitulate cellular phenotypes via their attractor states. Their overall dynamics are embodied in a state transition graph (STG). Indeed, two Boolean networks (BNs) with the same network structure and attractors can have drastically different STGs depending on the type of Boolean functions (BFs) employed. Our objective here is to systematically delineate the effects of different classes of BFs on the structural features of the STG of reconstructed Boolean GRNs while keeping network structure and biological attractors fixed, and explore the characteristics of BFs that drive those features. Using $10$ reconstructed Boolean GRNs, we generate ensembles that differ in BFs and compute from their STGs the dynamics' rate of contraction or 'bushiness' and rate of 'convergence', quantified with measures inspired from cellular automata (CA) that are based on the garden-of-Eden (GoE) states. We find that biologically meaningful BFs lead to higher STG 'bushiness' and 'convergence' than random ones. Obtaining such 'global' measures gets computationally expensive with larger network sizes, stressing the need for feasible proxies. So we adapt Wuensche's $Z$-parameter in CA to BFs in BNs and provide four natural variants, which, along with the average sensitivity of BFs computed at the network level, comprise our descriptors of local dynamics and we find some of them to be good proxies for bushiness. Finally, we provide an excellent proxy for the 'convergence' based on computing transient lengths originating at random states rather than GoE states.
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Affiliation(s)
- Priyotosh Sil
- The Institute of Mathematical Sciences (IMSc), Chennai, 600113, India
- Homi Bhabha National Institute (HBNI), Mumbai, 400094, India
| | - Ajay Subbaroyan
- The Institute of Mathematical Sciences (IMSc), Chennai, 600113, India
- Homi Bhabha National Institute (HBNI), Mumbai, 400094, India
| | - Saumitra Kulkarni
- The Institute of Mathematical Sciences (IMSc), Chennai, 600113, India
| | - Olivier C Martin
- Université Paris-Saclay, CNRS, INRAE, Univ Evry, Institute of Plant Sciences Paris-Saclay (IPS2), 91405, Orsay, France
- Université de Paris, CNRS, INRAE, Institute of Plant Sciences Paris-Saclay (IPS2), 91405, Orsay, France
| | - Areejit Samal
- The Institute of Mathematical Sciences (IMSc), Chennai, 600113, India
- Homi Bhabha National Institute (HBNI), Mumbai, 400094, India
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Mitra S, Sil P, Subbaroyan A, Martin OC, Samal A. Preponderance of generalized chain functions in reconstructed Boolean models of biological networks. Sci Rep 2024; 14:6734. [PMID: 38509145 PMCID: PMC10954731 DOI: 10.1038/s41598-024-57086-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2024] [Accepted: 03/14/2024] [Indexed: 03/22/2024] Open
Abstract
Boolean networks (BNs) have been extensively used to model gene regulatory networks (GRNs). The dynamics of BNs depend on the network architecture and regulatory logic rules (Boolean functions (BFs)) associated with nodes. Nested canalyzing functions (NCFs) have been shown to be enriched among the BFs in the large-scale studies of reconstructed Boolean models. The central question we address here is whether that enrichment is due to certain sub-types of NCFs. We build on one sub-type of NCFs, the chain functions (or chain-0 functions) proposed by Gat-Viks and Shamir. First, we propose two other sub-types of NCFs, namely, the class of chain-1 functions and generalized chain functions, the union of the chain-0 and chain-1 types. Next, we find that the fraction of NCFs that are chain-0 (also holds for chain-1) functions decreases exponentially with the number of inputs. We provide analytical treatment for this and other observations on BFs. Then, by analyzing three different datasets of reconstructed Boolean models we find that generalized chain functions are significantly enriched within the NCFs. Lastly we illustrate that upon imposing the constraints of generalized chain functions on three different GRNs we are able to obtain biologically viable Boolean models.
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Affiliation(s)
- Suchetana Mitra
- Indian Institute of Science Education and Research (IISER) Mohali, Manauli, Punjab, 140306, India
- The Institute of Mathematical Sciences (IMSc), Chennai, 600113, India
| | - Priyotosh Sil
- The Institute of Mathematical Sciences (IMSc), Chennai, 600113, India
- Homi Bhabha National Institute (HBNI), Mumbai, 400094, India
| | - Ajay Subbaroyan
- The Institute of Mathematical Sciences (IMSc), Chennai, 600113, India
- Homi Bhabha National Institute (HBNI), Mumbai, 400094, India
| | - Olivier C Martin
- Université Paris-Saclay, CNRS, INRAE, Univ Evry, Institute of Plant Sciences Paris-Saclay (IPS2), 91405, Orsay, France.
- Université Paris-Cité, CNRS, INRAE, Institute of Plant Sciences Paris-Saclay (IPS2), 91405, Orsay, France.
| | - Areejit Samal
- The Institute of Mathematical Sciences (IMSc), Chennai, 600113, India.
- Homi Bhabha National Institute (HBNI), Mumbai, 400094, India.
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Chen J, Yang Y, Li C, Chen Q, Liu S, Qin B. Genome-Wide Identification of MADS-Box Genes in Taraxacum kok-saghyz and Taraxacum mongolicum: Evolutionary Mechanisms, Conserved Functions and New Functions Related to Natural Rubber Yield Formation. Int J Mol Sci 2023; 24:10997. [PMID: 37446175 DOI: 10.3390/ijms241310997] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2023] [Revised: 06/27/2023] [Accepted: 06/29/2023] [Indexed: 07/15/2023] Open
Abstract
MADS-box transcription regulators play important roles in plant growth and development. However, very few MADS-box genes have been isolated in the genus Taraxacum, which consists of more than 3000 species. To explore their functions in the promising natural rubber (NR)-producing plant Taraxacum kok-saghyz (TKS), MADS-box genes were identified in the genome of TKS and the related species Taraxacum mongolicum (TM; non-NR-producing) via genome-wide screening. In total, 66 TkMADSs and 59 TmMADSs were identified in the TKS and TM genomes, respectively. From diploid TKS to triploid TM, the total number of MADS-box genes did not increase, but expansion occurred in specific subfamilies. Between the two genomes, a total of 11 duplications, which promoted the expansion of MADS-box genes, were identified in the two species. TkMADS and TmMADS were highly conserved, and showed good collinearity. Furthermore, most TkMADS genes exhibiting tissue-specific expression patterns, especially genes associated with the ABCDE model, were preferentially expressed in the flowers, suggesting their conserved and dominant functions in flower development in TKS. Moreover, by comparing the transcriptomes of different TKS lines, we identified 25 TkMADSs related to biomass formation and 4 TkMADSs related to NR content, which represented new targets for improving the NR yield of TKS.
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Affiliation(s)
- Jiaqi Chen
- Key Laboratory of Biology and Genetic Resources of Rubber Tree, Ministry of Agriculture and Rural Affairs, Rubber Research Institute, Chinese Academy of Tropical Agricultural Sciences, Haikou 571101, China
- Institute of Tropical Crops, Hainan University, Haikou 570228, China
| | - Yushuang Yang
- Key Laboratory of Biology and Genetic Resources of Rubber Tree, Ministry of Agriculture and Rural Affairs, Rubber Research Institute, Chinese Academy of Tropical Agricultural Sciences, Haikou 571101, China
| | - Chuang Li
- Key Laboratory of Biology and Genetic Resources of Rubber Tree, Ministry of Agriculture and Rural Affairs, Rubber Research Institute, Chinese Academy of Tropical Agricultural Sciences, Haikou 571101, China
- Institute of Tropical Crops, Hainan University, Haikou 570228, China
| | - Qiuhui Chen
- Key Laboratory of Biology and Genetic Resources of Rubber Tree, Ministry of Agriculture and Rural Affairs, Rubber Research Institute, Chinese Academy of Tropical Agricultural Sciences, Haikou 571101, China
| | - Shizhong Liu
- Key Laboratory of Biology and Genetic Resources of Rubber Tree, Ministry of Agriculture and Rural Affairs, Rubber Research Institute, Chinese Academy of Tropical Agricultural Sciences, Haikou 571101, China
| | - Bi Qin
- Key Laboratory of Biology and Genetic Resources of Rubber Tree, Ministry of Agriculture and Rural Affairs, Rubber Research Institute, Chinese Academy of Tropical Agricultural Sciences, Haikou 571101, China
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Argyris GA, Lluch Lafuente A, Tribastone M, Tschaikowski M, Vandin A. Reducing Boolean networks with backward equivalence. BMC Bioinformatics 2023; 24:212. [PMID: 37221494 DOI: 10.1186/s12859-023-05326-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Accepted: 05/05/2023] [Indexed: 05/25/2023] Open
Abstract
BACKGROUND Boolean Networks (BNs) are a popular dynamical model in biology where the state of each component is represented by a variable taking binary values that express, for instance, activation/deactivation or high/low concentrations. Unfortunately, these models suffer from the state space explosion, i.e., there are exponentially many states in the number of BN variables, which hampers their analysis. RESULTS We present Boolean Backward Equivalence (BBE), a novel reduction technique for BNs which collapses system variables that, if initialized with same value, maintain matching values in all states. A large-scale validation on 86 models from two online model repositories reveals that BBE is effective, since it is able to reduce more than 90% of the models. Furthermore, on such models we also show that BBE brings notable analysis speed-ups, both in terms of state space generation and steady-state analysis. In several cases, BBE allowed the analysis of models that were originally intractable due to the complexity. On two selected case studies, we show how one can tune the reduction power of BBE using model-specific information to preserve all dynamics of interest, and selectively exclude behavior that does not have biological relevance. CONCLUSIONS BBE complements existing reduction methods, preserving properties that other reduction methods fail to reproduce, and vice versa. BBE drops all and only the dynamics, including attractors, originating from states where BBE-equivalent variables have been initialized with different activation values The remaining part of the dynamics is preserved exactly, including the length of the preserved attractors, and their reachability from given initial conditions, without adding any spurious behaviours. Given that BBE is a model-to-model reduction technique, it can be combined with further reduction methods for BNs.
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Affiliation(s)
- Georgios A Argyris
- Department of Applied Mathematics and Computer Science, Technical University of Denmark, Lyngby, Denmark
| | - Alberto Lluch Lafuente
- Department of Applied Mathematics and Computer Science, Technical University of Denmark, Lyngby, Denmark
| | | | - Max Tschaikowski
- Department of Computer Science, University of Aalborg, Aalborg, Denmark
| | - Andrea Vandin
- Department of Applied Mathematics and Computer Science, Technical University of Denmark, Lyngby, Denmark.
- Department of Excellence EMbeDS and Institute of Economics, Sant'Anna School for Advanced Studies, Pisa, Italy.
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Subbaroyan A, Sil P, Martin OC, Samal A. Leveraging developmental landscapes for model selection in Boolean gene regulatory networks. Brief Bioinform 2023; 24:7145905. [PMID: 37114653 DOI: 10.1093/bib/bbad160] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2023] [Revised: 03/26/2023] [Accepted: 04/03/2023] [Indexed: 04/29/2023] Open
Abstract
Boolean models are a well-established framework to model developmental gene regulatory networks (DGRNs) for acquisition of cellular identities. During the reconstruction of Boolean DGRNs, even if the network structure is given, there is generally a large number of combinations of Boolean functions that will reproduce the different cell fates (biological attractors). Here we leverage the developmental landscape to enable model selection on such ensembles using the relative stability of the attractors. First we show that previously proposed measures of relative stability are strongly correlated and we stress the usefulness of the one that captures best the cell state transitions via the mean first passage time (MFPT) as it also allows the construction of a cellular lineage tree. A property of great computational importance is the insensitivity of the different stability measures to changes in noise intensities. That allows us to use stochastic approaches to estimate the MFPT and thereby scale up the computations to large networks. Given this methodology, we revisit different Boolean models of Arabidopsis thaliana root development, showing that a most recent one does not respect the biologically expected hierarchy of cell states based on relative stabilities. We therefore developed an iterative greedy algorithm that searches for models which satisfy the expected hierarchy of cell states and found that its application to the root development model yields many models that meet this expectation. Our methodology thus provides new tools that can enable reconstruction of more realistic and accurate Boolean models of DGRNs.
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Affiliation(s)
- Ajay Subbaroyan
- The Institute of Mathematical Sciences (IMSc), Chennai, 600113, India
- Homi Bhabha National Institute (HBNI), Mumbai, 400094, India
| | - Priyotosh Sil
- The Institute of Mathematical Sciences (IMSc), Chennai, 600113, India
- Homi Bhabha National Institute (HBNI), Mumbai, 400094, India
| | - Olivier C Martin
- Université Paris-Saclay, CNRS, INRAE, Univ Evry, Institute of Plant Sciences Paris-Saclay (IPS2), 91405, Orsay, France
- Université de Paris, CNRS, INRAE, Institute of Plant Sciences Paris-Saclay (IPS2), 91405, Orsay, France
| | - Areejit Samal
- The Institute of Mathematical Sciences (IMSc), Chennai, 600113, India
- Homi Bhabha National Institute (HBNI), Mumbai, 400094, India
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Müssel C, Ikonomi N, Werle SD, Weidner FM, Maucher M, Schwab JD, Kestler HA. CANTATA - prediction of missing links in Boolean networks using genetic programming. Bioinformatics 2022; 38:4893-4900. [PMID: 36094334 PMCID: PMC9620829 DOI: 10.1093/bioinformatics/btac623] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Revised: 08/25/2022] [Accepted: 09/09/2022] [Indexed: 11/27/2022] Open
Abstract
Motivation Biological processes are complex systems with distinct behaviour. Despite the growing amount of available data, knowledge is sparse and often insufficient to investigate the complex regulatory behaviour of these systems. Moreover, different cellular phenotypes are possible under varying conditions. Mathematical models attempt to unravel these mechanisms by investigating the dynamics of regulatory networks. Therefore, a major challenge is to combine regulations and phenotypical information as well as the underlying mechanisms. To predict regulatory links in these models, we established an approach called CANTATA to support the integration of information into regulatory networks and retrieve potential underlying regulations. This is achieved by optimizing both static and dynamic properties of these networks. Results Initial results show that the algorithm predicts missing interactions by recapitulating the known phenotypes while preserving the original topology and optimizing the robustness of the model. The resulting models allow for hypothesizing about the biological impact of certain regulatory dependencies. Availability and implementation Source code of the application, example files and results are available at https://github.com/sysbio-bioinf/Cantata. Supplementary information Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Christoph Müssel
- Institute of Medical Systems Biology, Ulm University, 89081 Ulm, Baden-Wuerttemberg, Germany
| | - Nensi Ikonomi
- Institute of Medical Systems Biology, Ulm University, 89081 Ulm, Baden-Wuerttemberg, Germany
| | - Silke D Werle
- Institute of Medical Systems Biology, Ulm University, 89081 Ulm, Baden-Wuerttemberg, Germany
| | - Felix M Weidner
- Institute of Medical Systems Biology, Ulm University, 89081 Ulm, Baden-Wuerttemberg, Germany
| | - Markus Maucher
- Institute of Medical Systems Biology, Ulm University, 89081 Ulm, Baden-Wuerttemberg, Germany
| | - Julian D Schwab
- Institute of Medical Systems Biology, Ulm University, 89081 Ulm, Baden-Wuerttemberg, Germany
| | - Hans A Kestler
- Institute of Medical Systems Biology, Ulm University, 89081 Ulm, Baden-Wuerttemberg, Germany
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7
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Hernández-Herrera P, Ugartechea-Chirino Y, Torres-Martínez HH, Arzola AV, Chairez-Veloz JE, García-Ponce B, Sánchez MDLP, Garay-Arroyo A, Álvarez-Buylla ER, Dubrovsky JG, Corkidi G. Live Plant Cell Tracking: Fiji plugin to analyze cell proliferation dynamics and understand morphogenesis. PLANT PHYSIOLOGY 2022; 188:846-860. [PMID: 34791452 PMCID: PMC8825436 DOI: 10.1093/plphys/kiab530] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/01/2021] [Accepted: 10/19/2021] [Indexed: 05/13/2023]
Abstract
Arabidopsis (Arabidopsis thaliana) primary and lateral roots (LRs) are well suited for 3D and 4D microscopy, and their development provides an ideal system for studying morphogenesis and cell proliferation dynamics. With fast-advancing microscopy techniques used for live-imaging, whole tissue data are increasingly available, yet present the great challenge of analyzing complex interactions within cell populations. We developed a plugin "Live Plant Cell Tracking" (LiPlaCeT) coupled to the publicly available ImageJ image analysis program and generated a pipeline that allows, with the aid of LiPlaCeT, 4D cell tracking and lineage analysis of populations of dividing and growing cells. The LiPlaCeT plugin contains ad hoc ergonomic curating tools, making it very simple to use for manual cell tracking, especially when the signal-to-noise ratio of images is low or variable in time or 3D space and when automated methods may fail. Performing time-lapse experiments and using cell-tracking data extracted with the assistance of LiPlaCeT, we accomplished deep analyses of cell proliferation and clonal relations in the whole developing LR primordia and constructed genealogical trees. We also used cell-tracking data for endodermis cells of the root apical meristem (RAM) and performed automated analyses of cell population dynamics using ParaView software (also publicly available). Using the RAM as an example, we also showed how LiPlaCeT can be used to generate information at the whole-tissue level regarding cell length, cell position, cell growth rate, cell displacement rate, and proliferation activity. The pipeline will be useful in live-imaging studies of roots and other plant organs to understand complex interactions within proliferating and growing cell populations. The plugin includes a step-by-step user manual and a dataset example that are available at https://www.ibt.unam.mx/documentos/diversos/LiPlaCeT.zip.
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Affiliation(s)
- Paul Hernández-Herrera
- Laboratorio de Imágenes y Visión por Computadora, Instituto de Biotecnología, Universidad Nacional Autónoma de México, Cd. de México, C.P. 04510, Mexico
| | - Yamel Ugartechea-Chirino
- Departamento de Ecología Funcional, Instituto de Ecología, Laboratorio de Genética Molecular, Epigenética, Desarrollo y Evolución de Plantas, Universidad Nacional Autónoma de México, Cd. de México, C.P. 04510, Mexico
| | - Héctor H Torres-Martínez
- Departamento de Biología Molecular de Plantas, Instituto de Biotecnología, Universidad Nacional Autónoma de México, Cd. de México, C.P. 04510, Mexico
| | - Alejandro V Arzola
- Instituto de Física, Universidad Nacional Autónoma de México, Cd. de México, C.P. 04510, Mexico
| | - José Eduardo Chairez-Veloz
- Departamento de Control Automático, Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional, Cd. de México, C.P. 07350, Mexico
| | - Berenice García-Ponce
- Departamento de Ecología Funcional, Instituto de Ecología, Laboratorio de Genética Molecular, Epigenética, Desarrollo y Evolución de Plantas, Universidad Nacional Autónoma de México, Cd. de México, C.P. 04510, Mexico
| | - María de la Paz Sánchez
- Departamento de Ecología Funcional, Instituto de Ecología, Laboratorio de Genética Molecular, Epigenética, Desarrollo y Evolución de Plantas, Universidad Nacional Autónoma de México, Cd. de México, C.P. 04510, Mexico
| | - Adriana Garay-Arroyo
- Departamento de Ecología Funcional, Instituto de Ecología, Laboratorio de Genética Molecular, Epigenética, Desarrollo y Evolución de Plantas, Universidad Nacional Autónoma de México, Cd. de México, C.P. 04510, Mexico
| | - Elena R Álvarez-Buylla
- Departamento de Ecología Funcional, Instituto de Ecología, Laboratorio de Genética Molecular, Epigenética, Desarrollo y Evolución de Plantas, Universidad Nacional Autónoma de México, Cd. de México, C.P. 04510, Mexico
- Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, Cd. de México, C.P. 04510, Mexico
| | - Joseph G Dubrovsky
- Departamento de Biología Molecular de Plantas, Instituto de Biotecnología, Universidad Nacional Autónoma de México, Cd. de México, C.P. 04510, Mexico
| | - Gabriel Corkidi
- Laboratorio de Imágenes y Visión por Computadora, Instituto de Biotecnología, Universidad Nacional Autónoma de México, Cd. de México, C.P. 04510, Mexico
- Author for communication:
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Dávila-Velderrain J, Caldú-Primo JL, Martínez-García JC, Álvarez-Buylla Roces ME. Gene Regulatory Network Dynamical Logical Models for Plant Development. Methods Mol Biol 2022; 2395:59-77. [PMID: 34822149 DOI: 10.1007/978-1-0716-1816-5_4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Mathematical and computational approaches that integrate and model the concerted action of multiple genetic and nongenetic components holding highly nonlinear interactions are fundamental for the study of developmental processes. Among these, gene regulatory network (GRN) dynamical models are very useful to understand how diverse types of regulatory constraints restrict the multigene expression patterns that characterize different cell fates. In this chapter we present a hands-on approach to model GRN dynamics, taking as a working example a well-curated and experimentally grounded GRN developmental module proposed by our group: the flower organ specification gene regulatory network (FOS-GRN). We demonstrate how to build and analyze a GRN model according to the following steps: (1) integration of molecular genetic data and formulation of logical rules specifying the dynamic behavior of each gene; (2) determination of steady states (attractors) corresponding to each cell type; (3) validation of the GRN model; and (4) extension of the deterministic model with the inclusion of stochasticity in order to model cell-state transitions dependent on noise due to fluctuations of the involved gen products. The methodologies explained here in detail can be applied to any other developmental module.
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Affiliation(s)
- José Dávila-Velderrain
- Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - José Luis Caldú-Primo
- Laboratorio de Genética Molecular, Epigenética, Desarrollo y Evolución de Plantas, Instituto de Ecología, Universidad Nacional Autónoma de México, Ciudad Universitaria, CDMX, Coyoacán, México
- Centro de Ciencias de la Complejidad (C3), Universidad Nacional Autónoma de México, Ciudad Universitaria, CDMX, México
| | | | - María Elena Álvarez-Buylla Roces
- Laboratorio de Genética Molecular, Epigenética, Desarrollo y Evolución de Plantas, Instituto de Ecología, Universidad Nacional Autónoma de México, Ciudad Universitaria, CDMX, Coyoacán, México.
- Centro de Ciencias de la Complejidad (C3), Universidad Nacional Autónoma de México, Ciudad Universitaria, CDMX, México.
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9
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Karanam A, Rappel WJ. Boolean modelling in plant biology. QUANTITATIVE PLANT BIOLOGY 2022; 3:e29. [PMID: 37077966 PMCID: PMC10095905 DOI: 10.1017/qpb.2022.26] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/17/2022] [Revised: 10/24/2022] [Accepted: 11/16/2022] [Indexed: 05/03/2023]
Abstract
Signalling and genetic networks underlie most biological processes and are often complex, containing many highly connected components. Modelling these networks can provide insight into mechanisms but is challenging given that rate parameters are often not well defined. Boolean modelling, in which components can only take on a binary value with connections encoded by logic equations, is able to circumvent some of these challenges, and has emerged as a viable tool to probe these complex networks. In this review, we will give an overview of Boolean modelling, with a specific emphasis on its use in plant biology. We review how Boolean modelling can be used to describe biological networks and then discuss examples of its applications in plant genetics and plant signalling.
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Affiliation(s)
- Aravind Karanam
- Department of Physics, University of California, San Diego, La Jolla, California92093, USA
| | - Wouter-Jan Rappel
- Department of Physics, University of California, San Diego, La Jolla, California92093, USA
- Author for correspondence: W.-J. Rappel, E-mail:
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10
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Dubrovsky JG, Ivanov VB. The quiescent centre of the root apical meristem: conceptual developments from Clowes to modern times. JOURNAL OF EXPERIMENTAL BOTANY 2021; 72:6687-6707. [PMID: 34161558 DOI: 10.1093/jxb/erab305] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/02/2021] [Accepted: 06/23/2021] [Indexed: 06/13/2023]
Abstract
In this review we discuss the concepts of the quiescent centre (QC) of the root apical meristem (RAM) and their change over time, from their formulation by F.A.L. Clowes to the present. This review is dedicated to the 100th anniversary of the birth of Clowes, and we present his short biography and a full bibliography of Clowes' work. Over time, the concept of the QC proved to be useful for the understanding of RAM organization and behaviour. We focus specifically on conceptual developments, from the organization of the QC to understanding its functions in RAM maintenance and activity, ranging from a model species, Arabidopsis thaliana, to crops. Concepts of initial cells, stem cells, and heterogeneity of the QC cells in the context of functional and structural stem cells are considered. We review the role of the QC in the context of cell flux in the RAM and the nature of quiescence of the QC cells. We discuss the origin of the QC and fluctuation of its size in ontogenesis and why the QC cells are more resistant to stress. Contemporary concepts of the organizer and stem cell niche are also considered. We also propose how the stem cell niche in the RAM can be defined in roots of a non-model species.
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Affiliation(s)
- Joseph G Dubrovsky
- Departamento de Biología Molecular de Plantas, Instituto de Biotecnología, Universidad Nacional Autónoma de México (UNAM), Cuernavaca, Mexico
| | - Victor B Ivanov
- Department of Root Physiology, Timiryazev Institute of Plant Physiology, Russian Academy of Sciences, Moscow, Russia
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11
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A system-level mechanistic explanation for asymmetric stem cell fates: Arabidopsis thaliana root niche as a study system. Sci Rep 2020; 10:3525. [PMID: 32103059 PMCID: PMC7044435 DOI: 10.1038/s41598-020-60251-8] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2019] [Accepted: 12/23/2019] [Indexed: 11/09/2022] Open
Abstract
Asymmetric divisions maintain long-term stem cell populations while producing new cells that proliferate and then differentiate. Recent reports in animal systems show that divisions of stem cells can be uncoupled from their progeny differentiation, and the outcome of a division could be influenced by microenvironmental signals. But the underlying system-level mechanisms, and whether this dynamics also occur in plant stem cell niches (SCN), remain elusive. This article presents a cell fate regulatory network model that contributes to understanding such mechanism and identify critical cues for cell fate transitions in the root SCN. Novel computational and experimental results show that the transcriptional regulator SHR is critical for the most frequent asymmetric division previously described for quiescent centre stem cells. A multi-scale model of the root tip that simulated each cell's intracellular regulatory network, and the dynamics of SHR intercellular transport as a cell-cell coupling mechanism, was developed. It revealed that quiescent centre cell divisions produce two identical cells, that may acquire different fates depending on the feedback between SHR's availability and the state of the regulatory network. Novel experimental data presented here validates our model, which in turn, constitutes the first proposed systemic mechanism for uncoupled SCN cell division and differentiation.
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Alvarez-Buylla ER, García-Ponce B, Sánchez MDLP, Espinosa-Soto C, García-Gómez ML, Piñeyro-Nelson A, Garay-Arroyo A. MADS-box genes underground becoming mainstream: plant root developmental mechanisms. THE NEW PHYTOLOGIST 2019; 223:1143-1158. [PMID: 30883818 DOI: 10.1111/nph.15793] [Citation(s) in RCA: 44] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/29/2018] [Accepted: 02/26/2019] [Indexed: 05/19/2023]
Abstract
Plant growth is largely post-embryonic and depends on meristems that are active throughout the lifespan of an individual. Developmental patterns rely on the coordinated spatio-temporal expression of different genes, and the activity of transcription factors is particularly important during most morphogenetic processes. MADS-box genes constitute a transcription factor family in eukaryotes. In Arabidopsis, their proteins participate in all major aspects of shoot development, but their role in root development is still not well characterized. In this review we synthetize current knowledge pertaining to the function of MADS-box genes highly expressed in roots: XAL1, XAL2, ANR1 and AGL21, as well as available data for other MADS-box genes expressed in this organ. The role of Trithorax group and Polycomb group complexes on MADS-box genes' epigenetic regulation is also discussed. We argue that understanding the role of MADS-box genes in root development of species with contrasting architectures is still a challenge. Finally, we propose that MADS-box genes are key components of the gene regulatory networks that underlie various gene expression patterns, each one associated with the distinct developmental fates observed in the root. In the case of XAL1 and XAL2, their role within these networks could be mediated by regulatory feedbacks with auxin.
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Affiliation(s)
- Elena R Alvarez-Buylla
- Departamento de Ecología Funcional, Instituto de Ecología, Universidad Nacional Autónoma de México, 3er Circuito Exterior, Ciudad Universitaria, Coyoacán, D.F. 04510, Mexico
- Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, 3er Circuito Exterior, Ciudad Universitaria, Coyoacán, D.F. 04510, Mexico
| | - Berenice García-Ponce
- Departamento de Ecología Funcional, Instituto de Ecología, Universidad Nacional Autónoma de México, 3er Circuito Exterior, Ciudad Universitaria, Coyoacán, D.F. 04510, Mexico
- Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, 3er Circuito Exterior, Ciudad Universitaria, Coyoacán, D.F. 04510, Mexico
| | - María de la Paz Sánchez
- Departamento de Ecología Funcional, Instituto de Ecología, Universidad Nacional Autónoma de México, 3er Circuito Exterior, Ciudad Universitaria, Coyoacán, D.F. 04510, Mexico
- Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, 3er Circuito Exterior, Ciudad Universitaria, Coyoacán, D.F. 04510, Mexico
| | - Carlos Espinosa-Soto
- Instituto de Física, Universidad Autónoma de San Luis Potosí, Manuel Nava 6, Zona Universitaria, San Luis Potosí, CP 78290, Mexico
| | - Mónica L García-Gómez
- Departamento de Ecología Funcional, Instituto de Ecología, Universidad Nacional Autónoma de México, 3er Circuito Exterior, Ciudad Universitaria, Coyoacán, D.F. 04510, Mexico
- Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, 3er Circuito Exterior, Ciudad Universitaria, Coyoacán, D.F. 04510, Mexico
| | - Alma Piñeyro-Nelson
- Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, 3er Circuito Exterior, Ciudad Universitaria, Coyoacán, D.F. 04510, Mexico
- Departamento de Producción Agrícola y Animal, Universidad Autónoma Metropolitana Xochimilco, Ciudad de México, 04960, Mexico
| | - Adriana Garay-Arroyo
- Departamento de Ecología Funcional, Instituto de Ecología, Universidad Nacional Autónoma de México, 3er Circuito Exterior, Ciudad Universitaria, Coyoacán, D.F. 04510, Mexico
- Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, 3er Circuito Exterior, Ciudad Universitaria, Coyoacán, D.F. 04510, Mexico
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Álvarez-Buylla Roces ME, Martínez-García JC, Dávila-Velderrain J, Domínguez-Hüttinger E, Martínez-Sánchez ME. Medical Systems Biology. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2018; 1069:1-33. [PMID: 30076565 DOI: 10.1007/978-3-319-89354-9_1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
Abstract
The aim of this volume is to encourage the use of systems-level methodologies to contribute to the improvement of human-health . We intend to motivate biomedical researchers to complement their current theoretical and empirical practice with up-to-date systems biology conceptual approaches. Our perspective is based on the deep understanding of the key biomolecular regulatory mechanisms that underlie health, as well as the emergence and progression of human-disease . We strongly believe that the contemporary systems biology perspective opens the door to the effective development of novel methodologies to the improvement of prevention . This requires a deeper and integrative understanding of the involved underlying systems-level mechanisms. In order to explain our proposal in a simple way, in this chapter we privilege the conceptual exposition of our chosen framework over formal considerations. The formal exposition of our proposal will be expanded and discussed later in the next chapters.
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Abstract
Being concerned by the understanding of the mechanism underlying chronic degenerative diseases , we presented in the previous chapter the medical systems biology conceptual framework that we present for that purpose in this volume. More specifically, we argued there the clear advantages offered by a state-space perspective when applied to the systems-level description of the biomolecular machinery that regulates complex degenerative diseases. We also discussed the importance of the dynamical interplay between the risk factors and the network of interdependencies that characterizes the biochemical, cellular, and tissue-level biomolecular reactions that underlie the physiological processes in health and disease. As we pointed out in the previous chapter, the understanding of this interplay (articulated around cellular phenotypic plasticity properties, regulated by specific kinds of gene regulatory networks) is necessary if prevention is chosen as the human-health improvement strategy (potentially involving the modulation of the patient's lifestyle). In this chapter we provide the medical systems biology mathematical and computational modeling tools required for this task.
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Muñoz S, Carrillo M, Azpeitia E, Rosenblueth DA. Griffin: A Tool for Symbolic Inference of Synchronous Boolean Molecular Networks. Front Genet 2018; 9:39. [PMID: 29559993 PMCID: PMC5845696 DOI: 10.3389/fgene.2018.00039] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2017] [Accepted: 01/29/2018] [Indexed: 11/30/2022] Open
Abstract
Boolean networks are important models of biochemical systems, located at the high end of the abstraction spectrum. A number of Boolean gene networks have been inferred following essentially the same method. Such a method first considers experimental data for a typically underdetermined “regulation” graph. Next, Boolean networks are inferred by using biological constraints to narrow the search space, such as a desired set of (fixed-point or cyclic) attractors. We describe Griffin, a computer tool enhancing this method. Griffin incorporates a number of well-established algorithms, such as Dubrova and Teslenko's algorithm for finding attractors in synchronous Boolean networks. In addition, a formal definition of regulation allows Griffin to employ “symbolic” techniques, able to represent both large sets of network states and Boolean constraints. We observe that when the set of attractors is required to be an exact set, prohibiting additional attractors, a naive Boolean coding of this constraint may be unfeasible. Such cases may be intractable even with symbolic methods, as the number of Boolean constraints may be astronomically large. To overcome this problem, we employ an Artificial Intelligence technique known as “clause learning” considerably increasing Griffin's scalability. Without clause learning only toy examples prohibiting additional attractors are solvable: only one out of seven queries reported here is answered. With clause learning, by contrast, all seven queries are answered. We illustrate Griffin with three case studies drawn from the Arabidopsis thaliana literature. Griffin is available at: http://turing.iimas.unam.mx/griffin.
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Affiliation(s)
- Stalin Muñoz
- Instituto de Investigaciones en Matemáticas Aplicadas y en Sistemas, Universidad Nacional Autónoma de México, Mexico City, Mexico.,Facultad de Ingeniería, Universidad Nacional Autónoma de México, Mexico City, Mexico.,Maestría en Ciencias de la Complejidad, Universidad Autónoma de la Ciudad de México, Mexico City, Mexico
| | - Miguel Carrillo
- Instituto de Investigaciones en Matemáticas Aplicadas y en Sistemas, Universidad Nacional Autónoma de México, Mexico City, Mexico
| | - Eugenio Azpeitia
- Institut National de Recherche en Informatique et en Automatique Project-Team Virtual Plants, Inria, CIRAD, INRA, Montpellier, France.,Department of Evolutionary Biology and Environmental Studies, University of Zurich, Zurich, Switzerland
| | - David A Rosenblueth
- Instituto de Investigaciones en Matemáticas Aplicadas y en Sistemas, Universidad Nacional Autónoma de México, Mexico City, Mexico.,Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de Mexico, Mexico City, Mexico
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Case Studies. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2018; 1069:135-209. [DOI: 10.1007/978-3-319-89354-9_3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
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Davila-Velderrain J, Caldu-Primo JL, Martinez-Garcia JC, Alvarez-Buylla ER. Modeling the Epigenetic Landscape in Plant Development. Methods Mol Biol 2018; 1819:357-383. [PMID: 30421413 DOI: 10.1007/978-1-4939-8618-7_17] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
Computational mechanistic models enable a systems-level understanding of plant development by integrating available molecular experimental data and simulating their collective dynamical behavior. Boolean gene regulatory network dynamical models have been extensively used as a qualitative modeling framework for such purpose. More recently, network modeling protocols have been extended to model the epigenetic landscape associated with gene regulatory networks. In addition to understanding the concerted action of interconnected genes, epigenetic landscape models aim to uncover the patterns of cell state transition events that emerge under diverse genetic and environmental background conditions. In this chapter we present simple protocols that naturally extend gene regulatory network modeling and demonstrate their use in modeling plant developmental processes under the epigenetic landscape framework. We focus on conceptual clarity and practical implementation, providing directions to the corresponding technical literature. The protocols presented here can be applied to any well-characterized gene regulatory network in plants, animals, or human disease.
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Affiliation(s)
- Jose Davila-Velderrain
- Centro de Ciencias de la Complejidad (C3), Universidad Nacional Autónoma de México, Ciudad Universitaria, México D.F, Mexico.,Departamento de Control Automático, Cinvestav-IPN, México D.F, Mexico.,MIT Computer Science and Artificial Intelligence Laboratory, Cambridge, MA, USA.,Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Jose Luis Caldu-Primo
- Centro de Ciencias de la Complejidad (C3), Universidad Nacional Autónoma de México, Ciudad Universitaria, México D.F, Mexico
| | | | - Elena R Alvarez-Buylla
- Centro de Ciencias de la Complejidad (C3), Universidad Nacional Autónoma de México, Ciudad Universitaria, México D.F, Mexico. .,Laboratorio de Genética Molecular, Desarrollo y Evolución de Plantas, Instituto de Ecología, México D.F, Mexico. .,University of California, Berkeley, Berkley, CA, USA.
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García-Gómez ML, Azpeitia E, Álvarez-Buylla ER. A dynamic genetic-hormonal regulatory network model explains multiple cellular behaviors of the root apical meristem of Arabidopsis thaliana. PLoS Comput Biol 2017; 13:e1005488. [PMID: 28426669 PMCID: PMC5417714 DOI: 10.1371/journal.pcbi.1005488] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2016] [Revised: 05/04/2017] [Accepted: 03/30/2017] [Indexed: 11/18/2022] Open
Abstract
The study of the concerted action of hormones and transcription factors is fundamental to understand cell differentiation and pattern formation during organ development. The root apical meristem of Arabidopsis thaliana is a useful model to address this. It has a stem cell niche near its tip conformed of a quiescent organizer and stem or initial cells around it, then a proliferation domain followed by a transition domain, where cells diminish division rate before transiting to the elongation zone; here, cells grow anisotropically prior to their final differentiation towards the plant base. A minimal model of the gene regulatory network that underlies cell-fate specification and patterning at the root stem cell niche was proposed before. In this study, we update and couple such network with both the auxin and cytokinin hormone signaling pathways to address how they collectively give rise to attractors that correspond to the genetic and hormonal activity profiles that are characteristic of different cell types along A. thaliana root apical meristem. We used a Boolean model of the genetic-hormonal regulatory network to integrate known and predicted regulatory interactions into alternative models. Our analyses show that, after adding some putative missing interactions, the model includes the necessary and sufficient components and regulatory interactions to recover attractors characteristic of the root cell types, including the auxin and cytokinin activity profiles that correlate with different cellular behaviors along the root apical meristem. Furthermore, the model predicts the existence of activity configurations that could correspond to the transition domain. The model also provides a possible explanation for apparently paradoxical cellular behaviors in the root meristem. For example, how auxin may induce and at the same time inhibit WOX5 expression. According to the model proposed here the hormonal regulation of WOX5 might depend on the cell type. Our results illustrate how non-linear multi-stable qualitative network models can aid at understanding how transcriptional regulators and hormonal signaling pathways are dynamically coupled and may underlie both the acquisition of cell fate and the emergence of hormonal activity profiles that arise during complex organ development.
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Affiliation(s)
- Mónica L. García-Gómez
- Departamento de Ecología Funcional, Instituto de Ecología, Universidad Nacional Autónoma de México, Coyoacán, Ciudad de México, México
- Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, Coyoacán, Ciudad de México, México
| | - Eugenio Azpeitia
- INRIA project-team Virtual Plants, joint with CIRAD and INRA, Montpellier, France
| | - Elena R. Álvarez-Buylla
- Departamento de Ecología Funcional, Instituto de Ecología, Universidad Nacional Autónoma de México, Coyoacán, Ciudad de México, México
- Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, Coyoacán, Ciudad de México, México
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20
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Méndez-López LF, Davila-Velderrain J, Domínguez-Hüttinger E, Enríquez-Olguín C, Martínez-García JC, Alvarez-Buylla ER. Gene regulatory network underlying the immortalization of epithelial cells. BMC SYSTEMS BIOLOGY 2017; 11:24. [PMID: 28209158 PMCID: PMC5314717 DOI: 10.1186/s12918-017-0393-5] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/19/2016] [Accepted: 01/11/2017] [Indexed: 12/25/2022]
Abstract
BACKGROUND Tumorigenic transformation of human epithelial cells in vitro has been described experimentally as the potential result of spontaneous immortalization. This process is characterized by a series of cell-state transitions, in which normal epithelial cells acquire first a senescent state which is later surpassed to attain a mesenchymal stem-like phenotype with a potentially tumorigenic behavior. In this paper we aim to provide a system-level mechanistic explanation to the emergence of these cell types, and to the time-ordered transition patterns that are common to neoplasias of epithelial origin. To this end, we first integrate published functional and well-curated molecular data of the components and interactions that have been found to be involved in such cell states and transitions into a network of 41 molecular components. We then reduce this initial network by removing simple mediators (i.e., linear pathways), and formalize the resulting regulatory core into logical rules that govern the dynamics of each of the network components as a function of the states of its regulators. RESULTS Computational dynamic analysis shows that our proposed Gene Regulatory Network model recovers exactly three attractors, each of them defined by a specific gene expression profile that corresponds to the epithelial, senescent, and mesenchymal stem-like cellular phenotypes, respectively. We show that although a mesenchymal stem-like state can be attained even under unperturbed physiological conditions, the likelihood of converging to this state is increased when pro-inflammatory conditions are simulated, providing a systems-level mechanistic explanation for the carcinogenic role of chronic inflammatory conditions observed in the clinic. We also found that the regulatory core yields an epigenetic landscape that restricts temporal patterns of progression between the steady states, such that recovered patterns resemble the time-ordered transitions observed during the spontaneous immortalization of epithelial cells, both in vivo and in vitro. CONCLUSION Our study strongly suggests that the in vitro tumorigenic transformation of epithelial cells, which strongly correlates with the patterns observed during the pathological progression of epithelial carcinogenesis in vivo, emerges from underlying regulatory networks involved in epithelial trans-differentiation during development.
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Affiliation(s)
- Luis Fernando Méndez-López
- Centro de Investigación y Desarrollo en Ciencias de la Salud (CIDICS), Universidad Autonoma de Nuevo Leon, A. P. 14-740, México, 07300 D.F México
| | | | - Elisa Domínguez-Hüttinger
- Instituto de Ecología, UNAM, Cd. Universitaria, México, 04510 D.F México
- Centro de Ciencias de la Complejidad, UNAM, Cd. Universitaria, México, 04510 D.F México
| | | | | | - Elena R. Alvarez-Buylla
- Instituto de Ecología, UNAM, Cd. Universitaria, México, 04510 D.F México
- Centro de Ciencias de la Complejidad, UNAM, Cd. Universitaria, México, 04510 D.F México
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Velderraín JD, Martínez-García JC, Álvarez-Buylla ER. Boolean Dynamic Modeling Approaches to Study Plant Gene Regulatory Networks: Integration, Validation, and Prediction. Methods Mol Biol 2017. [PMID: 28623593 DOI: 10.1007/978-1-4939-7125-1_19] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Mathematical models based on dynamical systems theory are well-suited tools for the integration of available molecular experimental data into coherent frameworks in order to propose hypotheses about the cooperative regulatory mechanisms driving developmental processes. Computational analysis of the proposed models using well-established methods enables testing the hypotheses by contrasting predictions with observations. Within such framework, Boolean gene regulatory network dynamical models have been extensively used in modeling plant development. Boolean models are simple and intuitively appealing, ideal tools for collaborative efforts between theorists and experimentalists. In this chapter we present protocols used in our group for the study of diverse plant developmental processes. We focus on conceptual clarity and practical implementation, providing directions to the corresponding technical literature.
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Affiliation(s)
- José Dávila Velderraín
- Centro de Ciencias de la Complejidad (C3), Universidad Nacional Autónoma de México (UNAM), Ciudad Universitaria, México, DF, 04510, Mexico
| | | | - Elena R Álvarez-Buylla
- Centro de Ciencias de la Complejidad (C3), Universidad Nacional Autónoma de México (UNAM), Ciudad Universitaria, México, DF, 04510, Mexico. .,Laboratorio de Genética Molecular, Desarrollo y Evolución de Plantas, Instituto de Ecología, Universidad Nacional Autónoma de México (UNAM), Av. Universidad 3000, Ciudad Universitaria, Mexico City, 4510, Mexico.
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Marcellini S, González F, Sarrazin AF, Pabón-Mora N, Benítez M, Piñeyro-Nelson A, Rezende GL, Maldonado E, Schneider PN, Grizante MB, Da Fonseca RN, Vergara-Silva F, Suaza-Gaviria V, Zumajo-Cardona C, Zattara EE, Casasa S, Suárez-Baron H, Brown FD. Evolutionary Developmental Biology (Evo-Devo) Research in Latin America. JOURNAL OF EXPERIMENTAL ZOOLOGY PART B-MOLECULAR AND DEVELOPMENTAL EVOLUTION 2016; 328:5-40. [PMID: 27491339 DOI: 10.1002/jez.b.22687] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/24/2016] [Revised: 06/16/2016] [Accepted: 06/20/2016] [Indexed: 12/29/2022]
Abstract
Famous for its blind cavefish and Darwin's finches, Latin America is home to some of the richest biodiversity hotspots of our planet. The Latin American fauna and flora inspired and captivated naturalists from the nineteenth and twentieth centuries, including such notable pioneers such as Fritz Müller, Florentino Ameghino, and Léon Croizat who made a significant contribution to the study of embryology and evolutionary thinking. But, what are the historical and present contributions of the Latin American scientific community to Evo-Devo? Here, we provide the first comprehensive overview of the Evo-Devo laboratories based in Latin America and describe current lines of research based on endemic species, focusing on body plans and patterning, systematics, physiology, computational modeling approaches, ecology, and domestication. Literature searches reveal that Evo-Devo in Latin America is still in its early days; while showing encouraging indicators of productivity, it has not stabilized yet, because it relies on few and sparsely distributed laboratories. Coping with the rapid changes in national scientific policies and contributing to solve social and health issues specific to each region are among the main challenges faced by Latin American researchers. The 2015 inaugural meeting of the Pan-American Society for Evolutionary Developmental Biology played a pivotal role in bringing together Latin American researchers eager to initiate and consolidate regional and worldwide collaborative networks. Such networks will undoubtedly advance research on the extremely high genetic and phenotypic biodiversity of Latin America, bound to be an almost infinite source of amazement and fascinating findings for the Evo-Devo community.
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Affiliation(s)
- Sylvain Marcellini
- Laboratorio de Desarrollo y Evolución, Departamento de Biología Celular, Facultad de Ciencias Biológicas, Universidad de Concepción, Concepción, Chile
| | - Favio González
- Facultad de Ciencias, Instituto de Ciencias Naturales, Universidad Nacional de Colombia, Bogotá, Colombia
| | - Andres F Sarrazin
- Instituto de Química, Pontificia Universidad Católica de Valparaíso, Valparaíso, Chile
| | | | - Mariana Benítez
- Laboratorio Nacional de Ciencias de la Sostenibilidad, Instituto de Ecología, Universidad Nacional Autónoma de México, Ciudad de México, México
| | - Alma Piñeyro-Nelson
- Departamento de Producción Agrícola y Animal, Universidad Autónoma Metropolitana, Xochimilco, Ciudad de México, México
| | - Gustavo L Rezende
- Universidade Estadual do Norte Fluminense, CBB, LQFPP, Campos dos Goytacazes, RJ, Brazil
| | - Ernesto Maldonado
- EvoDevo Lab, Unidad de Sistemas Arrecifales, Instituto de Ciencias del Mar y Limnología, Universidad Nacional Autónoma de México, Puerto Morelos, Quintana Roo, México
| | | | | | - Rodrigo Nunes Da Fonseca
- Núcleo em Ecologia e Desenvolvimento SócioAmbiental de Macaé (NUPEM), Campus Macaé, Universidade Federal do Rio de Janeiro, Macae, RJ, Brazil
| | | | | | | | | | - Sofia Casasa
- Department of Biology, Indiana University, Bloomington, IN, USA
| | | | - Federico D Brown
- Departamento de Zoologia, Instituto de Biociências, Universidade de São Paulo, São Paulo, SP, Brazil
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Álvarez-Buylla ER, Dávila-Velderrain J, Martínez-García JC. Systems Biology Approaches to Development beyond Bioinformatics: Nonlinear Mechanistic Models Using Plant Systems. Bioscience 2016. [DOI: 10.1093/biosci/biw027] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
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Ortiz-Gutiérrez E, García-Cruz K, Azpeitia E, Castillo A, Sánchez MDLP, Álvarez-Buylla ER. A Dynamic Gene Regulatory Network Model That Recovers the Cyclic Behavior of Arabidopsis thaliana Cell Cycle. PLoS Comput Biol 2015; 11:e1004486. [PMID: 26340681 PMCID: PMC4560428 DOI: 10.1371/journal.pcbi.1004486] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2015] [Accepted: 08/03/2015] [Indexed: 01/02/2023] Open
Abstract
Cell cycle control is fundamental in eukaryotic development. Several modeling efforts have been used to integrate the complex network of interacting molecular components involved in cell cycle dynamics. In this paper, we aimed at recovering the regulatory logic upstream of previously known components of cell cycle control, with the aim of understanding the mechanisms underlying the emergence of the cyclic behavior of such components. We focus on Arabidopsis thaliana, but given that many components of cell cycle regulation are conserved among eukaryotes, when experimental data for this system was not available, we considered experimental results from yeast and animal systems. We are proposing a Boolean gene regulatory network (GRN) that converges into only one robust limit cycle attractor that closely resembles the cyclic behavior of the key cell-cycle molecular components and other regulators considered here. We validate the model by comparing our in silico configurations with data from loss- and gain-of-function mutants, where the endocyclic behavior also was recovered. Additionally, we approximate a continuous model and recovered the temporal periodic expression profiles of the cell-cycle molecular components involved, thus suggesting that the single limit cycle attractor recovered with the Boolean model is not an artifact of its discrete and synchronous nature, but rather an emergent consequence of the inherent characteristics of the regulatory logic proposed here. This dynamical model, hence provides a novel theoretical framework to address cell cycle regulation in plants, and it can also be used to propose novel predictions regarding cell cycle regulation in other eukaryotes. In multicellular organisms, cells undergo a cyclic behavior of DNA duplication and delivery of a copy to daughter cells during cell division. In each of the main cell-cycle (CC) stages different sets of proteins are active and genes are expressed. Understanding how such cycling cellular behavior emerges and is robustly maintained in the face of changing developmental and environmental conditions, remains a fundamental challenge of biology. The molecular components that cycle through DNA duplication and citokinesis are interconnected in a complex regulatory network. Several models of such network have been proposed, although the regulatory network that robustly recovers a limit-cycle steady state that resembles the behavior of CC molecular components has been recovered only in a few cases, and no comprehensive model exists for plants. In this paper we used the plant Arabidopsis thaliana, as a study system to propose a core regulatory network to recover a cyclic attractor that mimics the oscillatory behavior of the key CC components. Our analyses show that the proposed GRN model is robust to transient alterations, and is validated with the loss- and gain-of-function mutants of the CC components. The interactions proposed for Arabidopsis thaliana CC can inspire predictions for further uncovering regulatory motifs in the CC of other organisms including human.
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Affiliation(s)
- Elizabeth Ortiz-Gutiérrez
- Instituto de Ecología, Universidad Nacional Autónoma de México, 3er Circuito Exterior, Junto a Jardín Botánico Exterior, México, D.F. CP 04510, México; Centro de Ciencias de la Complejidad-C3, Universidad Nacional Autónoma de México, Ciudad Universitaria, Apartado Postal 70-275, México, D.F. 04510, México
| | - Karla García-Cruz
- Instituto de Ecología, Universidad Nacional Autónoma de México, 3er Circuito Exterior, Junto a Jardín Botánico Exterior, México, D.F. CP 04510, México
| | - Eugenio Azpeitia
- Instituto de Ecología, Universidad Nacional Autónoma de México, 3er Circuito Exterior, Junto a Jardín Botánico Exterior, México, D.F. CP 04510, México; Centro de Ciencias de la Complejidad-C3, Universidad Nacional Autónoma de México, Ciudad Universitaria, Apartado Postal 70-275, México, D.F. 04510, México
| | - Aaron Castillo
- Instituto de Ecología, Universidad Nacional Autónoma de México, 3er Circuito Exterior, Junto a Jardín Botánico Exterior, México, D.F. CP 04510, México; Centro de Ciencias de la Complejidad-C3, Universidad Nacional Autónoma de México, Ciudad Universitaria, Apartado Postal 70-275, México, D.F. 04510, México
| | - María de la Paz Sánchez
- Instituto de Ecología, Universidad Nacional Autónoma de México, 3er Circuito Exterior, Junto a Jardín Botánico Exterior, México, D.F. CP 04510, México
| | - Elena R Álvarez-Buylla
- Instituto de Ecología, Universidad Nacional Autónoma de México, 3er Circuito Exterior, Junto a Jardín Botánico Exterior, México, D.F. CP 04510, México; Centro de Ciencias de la Complejidad-C3, Universidad Nacional Autónoma de México, Ciudad Universitaria, Apartado Postal 70-275, México, D.F. 04510, México
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Mora Van Cauwelaert E, Arias Del Angel JA, Benítez M, Azpeitia EM. Development of cell differentiation in the transition to multicellularity: a dynamical modeling approach. Front Microbiol 2015; 6:603. [PMID: 26157427 PMCID: PMC4477168 DOI: 10.3389/fmicb.2015.00603] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2014] [Accepted: 06/01/2015] [Indexed: 12/16/2022] Open
Abstract
Multicellularity has emerged and continues to emerge in a variety of lineages and under diverse environmental conditions. In order to attain individuality and integration, multicellular organisms must exhibit spatial cell differentiation, which in turn allows cell aggregates to robustly generate traits and behaviors at the multicellular level. Nevertheless, the mechanisms that may lead to the development of cellular differentiation and patterning in emerging multicellular organisms remain unclear. We briefly review two conceptual frameworks that have addressed this issue: the cooperation-defection framework and the dynamical patterning modules (DPMs) framework. Then, situating ourselves in the DPM formalism first put forward by S. A. Newman and collaborators, we state a hypothesis for cell differentiation and arrangement in cellular masses of emerging multicellular organisms. Our hypothesis is based on the role of the generic cell-to-cell communication and adhesion patterning mechanisms, which are two fundamental mechanisms for the evolution of multicellularity, and whose molecules seem to be well-conserved in extant multicellular organisms and their unicellular relatives. We review some fundamental ideas underlying this hypothesis and contrast them with empirical and theoretical evidence currently available. Next, we use a mathematical model to illustrate how the mechanisms and assumptions considered in the hypothesis we postulate may render stereotypical arrangements of differentiated cells in an emerging cellular aggregate and may contribute to the variation and recreation of multicellular phenotypes. Finally, we discuss the potential implications of our approach and compare them to those entailed by the cooperation-defection framework in the study of cell differentiation in the transition to multicellularity.
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Affiliation(s)
- Emilio Mora Van Cauwelaert
- Laboratorio Nacional de Ciencias de la Sostenibilidad, Instituto de Ecología, Universidad Nacional Autónoma de MéxicoMexico, Mexico
- Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de MéxicoMexico, Mexico
| | - Juan A. Arias Del Angel
- Laboratorio Nacional de Ciencias de la Sostenibilidad, Instituto de Ecología, Universidad Nacional Autónoma de MéxicoMexico, Mexico
- Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de MéxicoMexico, Mexico
- Programa de Doctorado en Ciencias Biomédicas, Universidad Nacional Autónoma de MéxicoMexico, Mexico
| | - Mariana Benítez
- Laboratorio Nacional de Ciencias de la Sostenibilidad, Instituto de Ecología, Universidad Nacional Autónoma de MéxicoMexico, Mexico
- Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de MéxicoMexico, Mexico
| | - Eugenio M. Azpeitia
- Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de MéxicoMexico, Mexico
- Institut National de Recherche en Informatique et en Automatique Project-Team Virtual Plants joint with CIRAD and INRAMontpellier, France
- Departamento de Ecología Funcional, Instituto de Ecología, Universidad Nacional Autónoma de MéxicoMexico, Mexico
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26
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Davila-Velderrain J, Martinez-Garcia JC, Alvarez-Buylla ER. Descriptive vs. mechanistic network models in plant development in the post-genomic era. Methods Mol Biol 2015; 1284:455-79. [PMID: 25757787 DOI: 10.1007/978-1-4939-2444-8_23] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/26/2023]
Abstract
Network modeling is now a widespread practice in systems biology, as well as in integrative genomics, and it constitutes a rich and diverse scientific research field. A conceptually clear understanding of the reasoning behind the main existing modeling approaches, and their associated technical terminologies, is required to avoid confusions and accelerate the transition towards an undeniable necessary more quantitative, multidisciplinary approach to biology. Herein, we focus on two main network-based modeling approaches that are commonly used depending on the information available and the intended goals: inference-based methods and system dynamics approaches. As far as data-based network inference methods are concerned, they enable the discovery of potential functional influences among molecular components. On the other hand, experimentally grounded network dynamical models have been shown to be perfectly suited for the mechanistic study of developmental processes. How do these two perspectives relate to each other? In this chapter, we describe and compare both approaches and then apply them to a given specific developmental module. Along with the step-by-step practical implementation of each approach, we also focus on discussing their respective goals, utility, assumptions, and associated limitations. We use the gene regulatory network (GRN) involved in Arabidopsis thaliana Root Stem Cell Niche patterning as our illustrative example. We show that descriptive models based on functional genomics data can provide important background information consistent with experimentally supported functional relationships integrated in mechanistic GRN models. The rationale of analysis and modeling can be applied to any other well-characterized functional developmental module in multicellular organisms, like plants and animals.
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Affiliation(s)
- J Davila-Velderrain
- Laboratorio de Genética Molecular, Desarrollo y Evolución de Plantas, Instituto de Ecología, Universidad Nacional Autónoma de México, Ciudad Universitaria, Av. Universidad 3000, México D.F., 04510, Mexico
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27
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Chávez Montes RA, Coello G, González-Aguilera KL, Marsch-Martínez N, de Folter S, Alvarez-Buylla ER. ARACNe-based inference, using curated microarray data, of Arabidopsis thaliana root transcriptional regulatory networks. BMC PLANT BIOLOGY 2014; 14:97. [PMID: 24739361 PMCID: PMC4021103 DOI: 10.1186/1471-2229-14-97] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/03/2013] [Accepted: 03/27/2014] [Indexed: 05/08/2023]
Abstract
BACKGROUND Uncovering the complex transcriptional regulatory networks (TRNs) that underlie plant and animal development remains a challenge. However, a vast amount of data from public microarray experiments is available, which can be subject to inference algorithms in order to recover reliable TRN architectures. RESULTS In this study we present a simple bioinformatics methodology that uses public, carefully curated microarray data and the mutual information algorithm ARACNe in order to obtain a database of transcriptional interactions. We used data from Arabidopsis thaliana root samples to show that the transcriptional regulatory networks derived from this database successfully recover previously identified root transcriptional modules and to propose new transcription factors for the SHORT ROOT/SCARECROW and PLETHORA pathways. We further show that these networks are a powerful tool to integrate and analyze high-throughput expression data, as exemplified by our analysis of a SHORT ROOT induction time-course microarray dataset, and are a reliable source for the prediction of novel root gene functions. In particular, we used our database to predict novel genes involved in root secondary cell-wall synthesis and identified the MADS-box TF XAL1/AGL12 as an unexpected participant in this process. CONCLUSIONS This study demonstrates that network inference using carefully curated microarray data yields reliable TRN architectures. In contrast to previous efforts to obtain root TRNs, that have focused on particular functional modules or tissues, our root transcriptional interactions provide an overview of the transcriptional pathways present in Arabidopsis thaliana roots and will likely yield a plethora of novel hypotheses to be tested experimentally.
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Affiliation(s)
- Ricardo A Chávez Montes
- Laboratorio de Genética Molecular, Desarrollo y Evolución de Plantas, Instituto de Ecología and Centro de Ciencias de la Complejidad (C3), Universidad Nacional Autónoma de México, Ciudad Universitaria, México D.F. 04510, Mexico
- Present address: Laboratorio Nacional de Genómica para la Biodiversidad (Langebio), Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional, Km 9.6 Libramiento Norte, Carretera Irapuato-León, AP 629, CP 36821 Irapuato, Guanajuato, Mexico
| | - Gerardo Coello
- Unidad de Cómputo, Instituto de Fisiología Celular, Universidad Nacional Autónoma de México, Ciudad Universitaria, México D.F. 04510, Mexico
| | - Karla L González-Aguilera
- Laboratorio Nacional de Genómica para la Biodiversidad (Langebio), Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional, Km 9.6 Libramiento Norte, Carretera Irapuato-León, AP 629, CP 36821 Irapuato, Guanajuato, Mexico
| | - Nayelli Marsch-Martínez
- Departamento de Biotecnologıa y Bioquımica, Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional, Km 9.6 Libramiento Norte, Carretera Irapuato-León, AP 629, CP 36821 Irapuato, Guanajuato, Mexico
| | - Stefan de Folter
- Laboratorio Nacional de Genómica para la Biodiversidad (Langebio), Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional, Km 9.6 Libramiento Norte, Carretera Irapuato-León, AP 629, CP 36821 Irapuato, Guanajuato, Mexico
| | - Elena R Alvarez-Buylla
- Laboratorio de Genética Molecular, Desarrollo y Evolución de Plantas, Instituto de Ecología and Centro de Ciencias de la Complejidad (C3), Universidad Nacional Autónoma de México, Ciudad Universitaria, México D.F. 04510, Mexico
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Azpeitia E, Davila-Velderrain J, Villarreal C, Alvarez-Buylla ER. Gene regulatory network models for floral organ determination. Methods Mol Biol 2014; 1110:441-69. [PMID: 24395275 DOI: 10.1007/978-1-4614-9408-9_26] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/05/2023]
Abstract
Understanding how genotypes map unto phenotypes implies an integrative understanding of the processes regulating cell differentiation and morphogenesis, which comprise development. Such a task requires the use of theoretical and computational approaches to integrate and follow the concerted action of multiple genetic and nongenetic components that hold highly nonlinear interactions. Gene regulatory network (GRN) models have been proposed to approach such task. GRN models have become very useful to understand how such types of interactions restrict the multi-gene expression patterns that characterize different cell-fates. More recently, such temporal single-cell models have been extended to recover the temporal and spatial components of morphogenesis. Since the complete genomic GRN is still unknown and intractable for any organism, and some clear developmental modules have been identified, we focus here on the analysis of well-curated and experimentally grounded small GRN modules. One of the first experimentally grounded GRN that was proposed and validated corresponds to the regulatory module involved in floral organ determination. In this chapter we use this GRN as an example of the methodologies involved in: (1) formalizing and integrating molecular genetic data into the logical functions (Boolean functions) that rule gene interactions and dynamics in a Boolean GRN; (2) the algorithms and computational approaches used to recover the steady-states that correspond to each cell type, as well as the set of initial GRN configurations that lead to each one of such states (i.e., basins of attraction); (3) the approaches used to validate a GRN model using wild type and mutant or overexpression data, or to test the robustness of the GRN being proposed; (4) some of the methods that have been used to incorporate random fluctuations in the GRN Boolean functions and enable stochastic GRN models to address the temporal sequence with which gene configurations and cell fates are attained; (5) the methodologies used to approximate discrete Boolean GRN to continuous systems and their use in further dynamic analyses. The methodologies explained for the GRN of floral organ determination developed here in detail can be applied to any other functional developmental module.
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Affiliation(s)
- Eugenio Azpeitia
- Laboratorio de Genética Molecular, Desarrollo y Evolución de Plantas, Instituto de Ecología, Universidad Nacional Autónoma de México, Ciudad Universitaria, México D.F., Mexico
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Hernández-Hernández V, Rueda D, Caballero L, Alvarez-Buylla ER, Benítez M. Mechanical forces as information: an integrated approach to plant and animal development. FRONTIERS IN PLANT SCIENCE 2014; 5:265. [PMID: 24959170 PMCID: PMC4051191 DOI: 10.3389/fpls.2014.00265] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/22/2014] [Accepted: 05/21/2014] [Indexed: 05/04/2023]
Abstract
Mechanical forces such as tension and compression act throughout growth and development of multicellular organisms. These forces not only affect the size and shape of the cells and tissues but are capable of modifying the expression of genes and the localization of molecular components within the cell, in the plasma membrane, and in the plant cell wall. The magnitude and direction of these physical forces change with cellular and tissue properties such as elasticity. Thus, mechanical forces and the mesoscopic fields that emerge from their local action constitute important sources of positional information. Moreover, physical and biochemical processes interact in non-linear ways during tissue and organ growth in plants and animals. In this review we discuss how such mechanical forces are generated, transmitted, and sensed in these two lineages of multicellular organisms to yield long-range positional information. In order to do so we first outline a potentially common basis for studying patterning and mechanosensing that relies on the structural principle of tensegrity, and discuss how tensegral structures might arise in plants and animals. We then provide some examples of morphogenesis in which mechanical forces appear to act as positional information during development, offering a possible explanation for ubiquitous processes, such as the formation of periodic structures. Such examples, we argue, can be interpreted in terms of tensegral phenomena. Finally, we discuss the hypothesis of mechanically isotropic points as a potentially generic mechanism for the localization and maintenance of stem-cell niches in multicellular organisms. This comparative approach aims to help uncovering generic mechanisms of morphogenesis and thus reach a better understanding of the evolution and development of multicellular phenotypes, focusing on the role of physical forces in these processes.
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Affiliation(s)
- Valeria Hernández-Hernández
- Instituto de Ecología, Universidad Nacional Autónoma de MéxicoMexico City, Mexico
- Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de MéxicoMexico City, Mexico
- Posgrado en Ciencias Biológicas, Universidad Nacional Autónoma de MéxicoMexico City, Mexico
| | - Denisse Rueda
- Posgrado en Ciencias Biomédicas, Universidad Nacional Autónoma de MéxicoMexico City, Mexico
- Departamento de Nanotecnología, Centro de Física Aplicada y Tecnología Avanzada, Universidad Nacional Autónoma de MéxicoMexico City, Mexico
| | - Lorena Caballero
- Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de MéxicoMexico City, Mexico
- Posgrado en Ciencias Biológicas, Universidad Nacional Autónoma de MéxicoMexico City, Mexico
- Departamento de Sistemas Complejos, Instituto de Física, Universidad Nacional Autónoma de MéxicoMexico City, Mexico
| | - Elena R. Alvarez-Buylla
- Instituto de Ecología, Universidad Nacional Autónoma de MéxicoMexico City, Mexico
- Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de MéxicoMexico City, Mexico
| | - Mariana Benítez
- Instituto de Ecología, Universidad Nacional Autónoma de MéxicoMexico City, Mexico
- Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de MéxicoMexico City, Mexico
- *Correspondence: Mariana Benítez, Laboratorio Nacional de Ciencias de la Sostenibilidad, Departamento de Ecología de la Biodiversidad, Instituto de Ecología, Universidad Nacional Autónoma de México, 3er Circuito Exterior, México City 04350, Mexico e-mail:
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30
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Garay-Arroyo A, Ortiz-Moreno E, de la Paz Sánchez M, Murphy AS, García-Ponce B, Marsch-Martínez N, de Folter S, Corvera-Poiré A, Jaimes-Miranda F, Pacheco-Escobedo MA, Dubrovsky JG, Pelaz S, Álvarez-Buylla ER. The MADS transcription factor XAL2/AGL14 modulates auxin transport during Arabidopsis root development by regulating PIN expression. EMBO J 2013; 32:2884-95. [PMID: 24121311 DOI: 10.1038/emboj.2013.216] [Citation(s) in RCA: 66] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2012] [Accepted: 08/28/2013] [Indexed: 12/29/2022] Open
Abstract
Elucidating molecular links between cell-fate regulatory networks and dynamic patterning modules is a key for understanding development. Auxin is important for plant patterning, particularly in roots, where it establishes positional information for cell-fate decisions. PIN genes encode plasma membrane proteins that serve as auxin efflux transporters; mutations in members of this gene family exhibit smaller roots with altered root meristems and stem-cell patterning. Direct regulators of PIN transcription have remained elusive. Here, we establish that a MADS-box gene (XAANTAL2, XAL2/AGL14) controls auxin transport via PIN transcriptional regulation during Arabidopsis root development; mutations in this gene exhibit altered stem-cell patterning, root meristem size, and root growth. XAL2 is necessary for normal shootward and rootward auxin transport, as well as for maintaining normal auxin distribution within the root. Furthermore, this MADS-domain transcription factor upregulates PIN1 and PIN4 by direct binding to regulatory regions and it is required for PIN4-dependent auxin response. In turn, XAL2 expression is regulated by auxin levels thus establishing a positive feedback loop between auxin levels and PIN regulation that is likely to be important for robust root patterning.
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Affiliation(s)
- Adriana Garay-Arroyo
- Depto. de Ecología Funcional. Laboratorio de Genética Molecular, Desarrollo y Evolución de Plantas, Instituto de Ecología, Universidad Nacional Autónoma de México, 3er Circuito Ext. Junto a J. Botánico, Ciudad Universitaria, UNAM, México DF, México
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Benítez M, Hejátko J. Dynamics of cell-fate determination and patterning in the vascular bundles of Arabidopsis thaliana. PLoS One 2013; 8:e63108. [PMID: 23723973 PMCID: PMC3664626 DOI: 10.1371/journal.pone.0063108] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2012] [Accepted: 03/28/2013] [Indexed: 12/22/2022] Open
Abstract
Plant vascular meristems are sets of pluripotent cells that enable radial growth by giving rise to vascular tissues and are therefore crucial to plant development. However, the overall dynamics of cellular determination and patterning in and around vascular meristems is still unexplored. We study this process in the shoot vascular tissue of Arabidopsis thaliana, which is organized in vascular bundles that contain three basic cell types (procambium, xylem and phloem). A set of molecules involved in this process has now been identified and partially characterized, but it is not yet clear how the regulatory interactions among them, in conjunction with cellular communication processes, give rise to the steady patterns that accompany cell-fate determination and arrangement within vascular bundles. We put forward a dynamic model factoring in the interactions between molecules (genes, peptides, mRNA and hormones) that have been reported to be central in this process, as well as the relevant communication mechanisms. When a few proposed interactions (unverified, but based on related data) are postulated, the model reproduces the hormonal and molecular patterns expected for the three regions within vascular bundles. In order to test the model, we simulated mutant and hormone-depleted systems and compared the results with experimentally reported phenotypes. The proposed model provides a formal framework integrating a set of growing experimental data and renders a dynamic account of how the collective action of hormones, genes, and other molecules may result in the specification of the three main cell types within shoot vascular bundles. It also offers a tool to test the necessity and sufficiency of particular interactions and conditions for vascular patterning and yields novel predictions that may be experimentally tested. Finally, this model provides a reference for further studies comparing the overall dynamics of tissue organization and formation by meristems in other plant organs and species.
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Affiliation(s)
- Mariana Benítez
- Functional Genomics and Proteomics of Plants, Central European Institute of Technology, Masaryk University, Brno, Czech Republic
- Departamento de Ecología de la Biodiversidad, Instituto de Ecología, Universidad Nacional Autónoma de México, México DF, Mexico
- Centro de Ciencias de la Complejidad C3, Universidad Nacional Autónoma de México, México DF, Mexico
| | - Jan Hejátko
- Functional Genomics and Proteomics of Plants, Central European Institute of Technology, Masaryk University, Brno, Czech Republic
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Barrio RA, Romero-Arias JR, Noguez MA, Azpeitia E, Ortiz-Gutiérrez E, Hernández-Hernández V, Cortes-Poza Y, Álvarez-Buylla ER. Cell patterns emerge from coupled chemical and physical fields with cell proliferation dynamics: the Arabidopsis thaliana root as a study system. PLoS Comput Biol 2013; 9:e1003026. [PMID: 23658505 PMCID: PMC3642054 DOI: 10.1371/journal.pcbi.1003026] [Citation(s) in RCA: 36] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2012] [Accepted: 02/25/2013] [Indexed: 11/18/2022] Open
Abstract
A central issue in developmental biology is to uncover the mechanisms by which stem cells maintain their capacity to regenerate, yet at the same time produce daughter cells that differentiate and attain their ultimate fate as a functional part of a tissue or an organ. In this paper we propose that, during development, cells within growing organs obtain positional information from a macroscopic physical field that is produced in space while cells are proliferating. This dynamical interaction triggers and responds to chemical and genetic processes that are specific to each biological system. We chose the root apical meristem of Arabidopsis thaliana to develop our dynamical model because this system is well studied at the molecular, genetic and cellular levels and has the key traits of multicellular stem-cell niches. We built a dynamical model that couples fundamental molecular mechanisms of the cell cycle to a tension physical field and to auxin dynamics, both of which are known to play a role in root development. We perform extensive numerical calculations that allow for quantitative comparison with experimental measurements that consider the cellular patterns at the root tip. Our model recovers, as an emergent pattern, the transition from proliferative to transition and elongation domains, characteristic of stem-cell niches in multicellular organisms. In addition, we successfully predict altered cellular patterns that are expected under various applied auxin treatments or modified physical growth conditions. Our modeling platform may be extended to explicitly consider gene regulatory networks or to treat other developmental systems. The emergence of tumors results from altered cell differentiation and proliferation during organ and tissue development. Understanding how such altered or normal patterns are established is still a challenge. Molecular genetic approaches to understanding pattern formation have searched for key central genetic controllers. However, biological patterns emerge as a consequence of coupled complex genetic and non-genetic sub-systems operating at various spatial and temporal scales and levels of organization. We present a two-dimensional model and simulation benchmark that considers the integrated dynamics of physical and chemical fields that result from cell proliferation. We aim at understanding how the cellular patterns of stem-cell niches emerge. In these, organizer cells with very low rates of proliferation are surrounded by stem cells with slightly higher proliferation rates that transit to a domain of active proliferation and then of elongation and differentiation. We quantified such cellular patterns in the Arabidopsis thaliana root to test our theoretical propositions. The results of our simulations closely mimic observed root cellular patterns, thus providing a proof of principle that coupled physical fields and chemical processes under active cell proliferation give rise to stem-cell patterns. Our framework may be extended to other developmental systems and to consider gene regulatory networks.
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Affiliation(s)
- Rafael A. Barrio
- Instituto de Física, Universidad Nacional Autónoma de México (UNAM), México, Distrito Federal, México
- * E-mail: (RAB); (ERAB)
| | - José Roberto Romero-Arias
- Instituto de Física, Universidad Nacional Autónoma de México (UNAM), México, Distrito Federal, México
| | - Marco A. Noguez
- Universidad Autónoma de la Ciudad de México, Mexico, Distrito Federal, México
| | - Eugenio Azpeitia
- Instituto de Ecología, Universidad Nacional Autónoma de México, México, Distrito Federal, México
- Centro de Ciencias de la Complejidad-C3, Universidad Nacional Autónoma de México, Distrito Federal, México
| | - Elizabeth Ortiz-Gutiérrez
- Instituto de Ecología, Universidad Nacional Autónoma de México, México, Distrito Federal, México
- Centro de Ciencias de la Complejidad-C3, Universidad Nacional Autónoma de México, Distrito Federal, México
| | - Valeria Hernández-Hernández
- Instituto de Ecología, Universidad Nacional Autónoma de México, México, Distrito Federal, México
- Centro de Ciencias de la Complejidad-C3, Universidad Nacional Autónoma de México, Distrito Federal, México
| | - Yuriria Cortes-Poza
- Centro de Ciencias de la Complejidad-C3, Universidad Nacional Autónoma de México, Distrito Federal, México
| | - Elena R. Álvarez-Buylla
- Instituto de Ecología, Universidad Nacional Autónoma de México, México, Distrito Federal, México
- Centro de Ciencias de la Complejidad-C3, Universidad Nacional Autónoma de México, Distrito Federal, México
- * E-mail: (RAB); (ERAB)
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Mendes ND, Lang F, Le Cornec YS, Mateescu R, Batt G, Chaouiya C. Composition and abstraction of logical regulatory modules: application to multicellular systems. ACTA ACUST UNITED AC 2013; 29:749-57. [PMID: 23341501 DOI: 10.1093/bioinformatics/btt033] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
MOTIVATION Logical (Boolean or multi-valued) modelling is widely used to study regulatory or signalling networks. Even though these discrete models constitute a coarse, yet useful, abstraction of reality, the analysis of large networks faces a classical combinatorial problem. Here, we propose to take advantage of the intrinsic modularity of inter-cellular networks to set up a compositional procedure that enables a significant reduction of the dynamics, yet preserving the reachability of stable states. To that end, we rely on process algebras, a well-established computational technique for the specification and verification of interacting systems. RESULTS We develop a novel compositional approach to support the logical modelling of interconnected cellular networks. First, we formalize the concept of logical regulatory modules and their composition. Then, we make this framework operational by transposing the composition of logical modules into a process algebra framework. Importantly, the combination of incremental composition, abstraction and minimization using an appropriate equivalence relation (here the safety equivalence) yields huge reductions of the dynamics. We illustrate the potential of this approach with two case-studies: the Segment-Polarity and the Delta-Notch modules.
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Affiliation(s)
- Nuno D Mendes
- IGC, Instituto Gulbenkian de Ciência, Rua da Quinta Grande 6, P-2780-156 Oeiras, Portugal
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Azpeitia E, Weinstein N, Benítez M, Mendoza L, Alvarez-Buylla ER. Finding Missing Interactions of the Arabidopsis thaliana Root Stem Cell Niche Gene Regulatory Network. FRONTIERS IN PLANT SCIENCE 2013; 4:110. [PMID: 23658556 PMCID: PMC3639504 DOI: 10.3389/fpls.2013.00110] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/23/2013] [Accepted: 04/10/2013] [Indexed: 05/09/2023]
Abstract
Over the last few decades, the Arabidopsis thaliana root stem cell niche (RSCN) has become a model system for the study of plant development and stem cell niche dynamics. Currently, many of the molecular mechanisms involved in RSCN maintenance and development have been described. A few years ago, we published a gene regulatory network (GRN) model integrating this information. This model suggested that there were missing components or interactions. Upon updating the model, the observed stable gene configurations of the RSCN could not be recovered, indicating that there are additional missing components or interactions in the model. In fact, due to the lack of experimental data, GRNs inferred from published data are usually incomplete. However, predicting the location and nature of the missing data is a not trivial task. Here, we propose a set of procedures for detecting and predicting missing interactions in Boolean networks. We used these procedures to predict putative missing interactions in the A. thaliana RSCN network model. Using our approach, we identified three necessary interactions to recover the reported gene activation configurations that have been experimentally uncovered for the different cell types within the RSCN: (1) a regulation of PHABULOSA to restrict its expression domain to the vascular cells, (2) a self-regulation of WOX5, possibly by an indirect mechanism through the auxin signaling pathway, and (3) a positive regulation of JACKDAW by MAGPIE. The procedures proposed here greatly reduce the number of possible Boolean functions that are biologically meaningful and experimentally testable and that do not contradict previous data. We believe that these procedures can be used on any Boolean network. However, because the procedures were designed for the specific case of the RSCN, formal demonstrations of the procedures should be shown in future efforts.
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Affiliation(s)
- Eugenio Azpeitia
- Laboratorio de Genética Molecular, Desarrollo y Evolución de Plantas, Instituto de Ecología, Universidad Nacional Autónoma de MéxicoCiudad Universitaria, México DF, México
- C3, Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de MéxicoMéxico DF, México
| | - Nathan Weinstein
- Departamento de Ecología de la Biodiversidad, Instituto de Ecología, Universidad Nacional Autónoma de MéxicoCiudad Universitaria, México DF, México
| | - Mariana Benítez
- C3, Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de MéxicoMéxico DF, México
- Instituto de Investigaciones Biomédicas, Universidad Nacional Autónoma de MéxicoCd. Universitaria, México DF, México
| | - Luis Mendoza
- Departamento de Ecología de la Biodiversidad, Instituto de Ecología, Universidad Nacional Autónoma de MéxicoCiudad Universitaria, México DF, México
- *Correspondence: Luis Mendoza, Instituto de Investigaciones Biomédicas, Universidad Nacional Autónoma de México, Apartado Postal 70228, Ciudad Universitaria, México DF 04510, México. e-mail: ; Elena R. Alvarez-Buylla, Laboratorio Genética Molecular, Desarrollo y Evolución de Plantas, Instituto de Ecología, Universidad Nacional Autónoma de México, Circ. Exterior anexo al Jardín Botánico, Ciudad Universitaria, Del. Coyoacán, 04510 México DF, México. e-mail:
| | - Elena R. Alvarez-Buylla
- Laboratorio de Genética Molecular, Desarrollo y Evolución de Plantas, Instituto de Ecología, Universidad Nacional Autónoma de MéxicoCiudad Universitaria, México DF, México
- C3, Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de MéxicoMéxico DF, México
- *Correspondence: Luis Mendoza, Instituto de Investigaciones Biomédicas, Universidad Nacional Autónoma de México, Apartado Postal 70228, Ciudad Universitaria, México DF 04510, México. e-mail: ; Elena R. Alvarez-Buylla, Laboratorio Genética Molecular, Desarrollo y Evolución de Plantas, Instituto de Ecología, Universidad Nacional Autónoma de México, Circ. Exterior anexo al Jardín Botánico, Ciudad Universitaria, Del. Coyoacán, 04510 México DF, México. e-mail:
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Benítez M. An interdisciplinary view on dynamic models for plant genetics and morphogenesis: scope, examples and emerging research avenues. FRONTIERS IN PLANT SCIENCE 2013; 4:7. [PMID: 23386856 PMCID: PMC3560346 DOI: 10.3389/fpls.2013.00007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/14/2012] [Accepted: 01/10/2013] [Indexed: 05/08/2023]
Affiliation(s)
- Mariana Benítez
- Departamento de Ecología de la Biodiversidad, Instituto de Ecología, Universidad Nacional Autónoma de MéxicoMexico City, Mexico
- Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de MéxicoMexico City, Mexico
- *Correspondence:
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Azpeitia E, Alvarez-Buylla ER. A complex systems approach to Arabidopsis root stem-cell niche developmental mechanisms: from molecules, to networks, to morphogenesis. PLANT MOLECULAR BIOLOGY 2012; 80:351-63. [PMID: 22945341 DOI: 10.1007/s11103-012-9954-6] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/05/2012] [Accepted: 08/15/2012] [Indexed: 05/11/2023]
Abstract
Recent reports have shown that the molecular mechanisms involved in root stem-cell niche development in Arabidopsis thaliana are complex and contain several feedback loops and non-additive interactions that need to be analyzed using computational and formal approaches. Complex systems cannot be understood in terms of the behavior of their isolated components, but they emerge as a consequence of largely non-linear interactions among their components. The study of complex systems has provided a useful approach for the exploration of system-level characteristics and behaviors of the molecular networks involved in cell differentiation and morphogenesis during development. We analyzed the complex molecular networks underlying stem-cell niche patterning in the A. thaliana root in terms of some of the key dynamic traits of complex systems: self-organization, modularity and structural properties. We use these analyses to integrate the available root stem-cell niche molecular mechanisms data and postulate novel hypotheses, missing components and interactions and explain apparent contradictions in the literature.
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Affiliation(s)
- Eugenio Azpeitia
- Laboratorio de Genética Molecular, Desarrollo y Evolución de Plantas, Centro de Ciencias de la Complejidad (C3), Universidad Nacional Autónoma de México, Coyoacán, Mexico, DF, Mexico
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Garay-Arroyo A, De La Paz Sánchez M, García-Ponce B, Azpeitia E, Álvarez-Buylla ER. Hormone symphony during root growth and development. Dev Dyn 2012; 241:1867-85. [DOI: 10.1002/dvdy.23878] [Citation(s) in RCA: 57] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/17/2012] [Indexed: 01/29/2023] Open
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Band LR, Fozard JA, Godin C, Jensen OE, Pridmore T, Bennett MJ, King JR. Multiscale systems analysis of root growth and development: modeling beyond the network and cellular scales. THE PLANT CELL 2012; 24:3892-906. [PMID: 23110897 PMCID: PMC3517226 DOI: 10.1105/tpc.112.101550] [Citation(s) in RCA: 38] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/19/2012] [Revised: 08/31/2012] [Accepted: 10/14/2012] [Indexed: 05/21/2023]
Abstract
Over recent decades, we have gained detailed knowledge of many processes involved in root growth and development. However, with this knowledge come increasing complexity and an increasing need for mechanistic modeling to understand how those individual processes interact. One major challenge is in relating genotypes to phenotypes, requiring us to move beyond the network and cellular scales, to use multiscale modeling to predict emergent dynamics at the tissue and organ levels. In this review, we highlight recent developments in multiscale modeling, illustrating how these are generating new mechanistic insights into the regulation of root growth and development. We consider how these models are motivating new biological data analysis and explore directions for future research. This modeling progress will be crucial as we move from a qualitative to an increasingly quantitative understanding of root biology, generating predictive tools that accelerate the development of improved crop varieties.
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Affiliation(s)
- Leah R. Band
- Centre for Plant Integrative Biology, University of Nottingham, Nottingham LE12 5RD, United Kingdom
| | - John A. Fozard
- Centre for Plant Integrative Biology, University of Nottingham, Nottingham LE12 5RD, United Kingdom
| | - Christophe Godin
- Virtual Plants Institut National de Recherche en Informatique et en Automatique Project-Team, joint with Institut National de la Recherche Agronomique and Centre de Coopération Internationale en Recherche Agronomique pour le Développement, Unité Mixte de Recherche Amélioration Génétique et Adaptation des Plantes, Montpellier cedex 5, France
| | - Oliver E. Jensen
- Centre for Plant Integrative Biology, University of Nottingham, Nottingham LE12 5RD, United Kingdom
- School of Mathematics, University of Manchester, Manchester M13 9PL, United Kingdom
| | - Tony Pridmore
- Centre for Plant Integrative Biology, University of Nottingham, Nottingham LE12 5RD, United Kingdom
| | - Malcolm J. Bennett
- Centre for Plant Integrative Biology, University of Nottingham, Nottingham LE12 5RD, United Kingdom
| | - John R. King
- Centre for Plant Integrative Biology, University of Nottingham, Nottingham LE12 5RD, United Kingdom
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Villarreal C, Padilla-Longoria P, Alvarez-Buylla ER. General theory of genotype to phenotype mapping: derivation of epigenetic landscapes from N-node complex gene regulatory networks. PHYSICAL REVIEW LETTERS 2012; 109:118102. [PMID: 23005679 DOI: 10.1103/physrevlett.109.118102] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/29/2011] [Indexed: 05/23/2023]
Abstract
We propose a systematic methodology to construct a probabilistic epigenetic landscape of cell-fate attainment associated with N-node Boolean genetic regulatory networks. The general derivation proposed here is exemplified with an Arabidopsis thaliana network underlying floral organ determination grounded on qualitative experimental data.
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Affiliation(s)
- Carlos Villarreal
- Instituto de Física, Universidad Nacional Autónoma de México, D.F. México, Mexico
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Abstract
We investigate the sensitivity of Boolean Networks (BNs) to mutations. We are interested in Boolean Networks as a model of Gene Regulatory Networks (GRNs). We adopt Ribeiro and Kauffman’s Ergodic Set and use it to study the long term dynamics of a BN. We define the sensitivity of a BN to be the mean change in its Ergodic Set structure under all possible loss of interaction mutations. Insilico experiments were used to selectively evolve BNs for sensitivity to losing interactions. We find that maximum sensitivity was often achievable and resulted in the BNs becoming topologically balanced, i.e. they evolve towards network structures in which they have a similar number of inhibitory and excitatory interactions. In terms of the dynamics, the dominant sensitivity strategy that evolved was to build BNs with Ergodic Sets dominated by a single long limit cycle which is easily destabilised by mutations. We discuss the relevance of our findings in the context of Stem Cell Differentiation and propose a relationship between pluripotent stem cells and our evolved sensitive networks.
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Affiliation(s)
- Jamie X. Luo
- Centre for Complexity Science, University of Warwick, Coventry, West Midlands, United Kingdom
- Department of Physics, University of Warwick, Coventry, West Midlands, United Kingdom
| | - Matthew S. Turner
- Centre for Complexity Science, University of Warwick, Coventry, West Midlands, United Kingdom
- Department of Physics, University of Warwick, Coventry, West Midlands, United Kingdom
- * E-mail:
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Arellano G, Argil J, Azpeitia E, Benítez M, Carrillo M, Góngora P, Rosenblueth DA, Alvarez-Buylla ER. "Antelope": a hybrid-logic model checker for branching-time Boolean GRN analysis. BMC Bioinformatics 2011; 12:490. [PMID: 22192526 PMCID: PMC3316443 DOI: 10.1186/1471-2105-12-490] [Citation(s) in RCA: 30] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2011] [Accepted: 12/22/2011] [Indexed: 01/30/2023] Open
Abstract
Background In Thomas' formalism for modeling gene regulatory networks (GRNs), branching time, where a state can have more than one possible future, plays a prominent role. By representing a certain degree of unpredictability, branching time can model several important phenomena, such as (a) asynchrony, (b) incompletely specified behavior, and (c) interaction with the environment. Introducing more than one possible future for a state, however, creates a difficulty for ordinary simulators, because infinitely many paths may appear, limiting ordinary simulators to statistical conclusions. Model checkers for branching time, by contrast, are able to prove properties in the presence of infinitely many paths. Results We have developed Antelope ("Analysis of Networks through TEmporal-LOgic sPEcifications", http://turing.iimas.unam.mx:8080/AntelopeWEB/), a model checker for analyzing and constructing Boolean GRNs. Currently, software systems for Boolean GRNs use branching time almost exclusively for asynchrony. Antelope, by contrast, also uses branching time for incompletely specified behavior and environment interaction. We show the usefulness of modeling these two phenomena in the development of a Boolean GRN of the Arabidopsis thaliana root stem cell niche. There are two obstacles to a direct approach when applying model checking to Boolean GRN analysis. First, ordinary model checkers normally only verify whether or not a given set of model states has a given property. In comparison, a model checker for Boolean GRNs is preferable if it reports the set of states having a desired property. Second, for efficiency, the expressiveness of many model checkers is limited, resulting in the inability to express some interesting properties of Boolean GRNs. Antelope tries to overcome these two drawbacks: Apart from reporting the set of all states having a given property, our model checker can express, at the expense of efficiency, some properties that ordinary model checkers (e.g., NuSMV) cannot. This additional expressiveness is achieved by employing a logic extending the standard Computation-Tree Logic (CTL) with hybrid-logic operators. Conclusions We illustrate the advantages of Antelope when (a) modeling incomplete networks and environment interaction, (b) exhibiting the set of all states having a given property, and (c) representing Boolean GRN properties with hybrid CTL.
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Affiliation(s)
- Gustavo Arellano
- Instituto de Investigaciones en Matemáticas Aplicadas y en Sistemas, Universidad Nacional Autónoma de México, 01000 México D.F., México
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Azpeitia E, Benítez M, Padilla-Longoria P, Espinosa-Soto C, Alvarez-Buylla ER. Dynamic network-based epistasis analysis: boolean examples. FRONTIERS IN PLANT SCIENCE 2011; 2:92. [PMID: 22645556 PMCID: PMC3355816 DOI: 10.3389/fpls.2011.00092] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/03/2011] [Accepted: 11/17/2011] [Indexed: 05/21/2023]
Abstract
In this article we focus on how the hierarchical and single-path assumptions of epistasis analysis can bias the inference of gene regulatory networks. Here we emphasize the critical importance of dynamic analyses, and specifically illustrate the use of Boolean network models. Epistasis in a broad sense refers to gene interactions, however, as originally proposed by Bateson, epistasis is defined as the blocking of a particular allelic effect due to the effect of another allele at a different locus (herein, classical epistasis). Classical epistasis analysis has proven powerful and useful, allowing researchers to infer and assign directionality to gene interactions. As larger data sets are becoming available, the analysis of classical epistasis is being complemented with computer science tools and system biology approaches. We show that when the hierarchical and single-path assumptions are not met in classical epistasis analysis, the access to relevant information and the correct inference of gene interaction topologies is hindered, and it becomes necessary to consider the temporal dynamics of gene interactions. The use of dynamical networks can overcome these limitations. We particularly focus on the use of Boolean networks that, like classical epistasis analysis, relies on logical formalisms, and hence can complement classical epistasis analysis and relax its assumptions. We develop a couple of theoretical examples and analyze them from a dynamic Boolean network model perspective. Boolean networks could help to guide additional experiments and discern among alternative regulatory schemes that would be impossible or difficult to infer without the elimination of these assumption from the classical epistasis analysis. We also use examples from the literature to show how a Boolean network-based approach has resolved ambiguities and guided epistasis analysis. Our article complements previous accounts, not only by focusing on the implications of the hierarchical and single-path assumption, but also by demonstrating the importance of considering temporal dynamics, and specifically introducing the usefulness of Boolean network models and also reviewing some key properties of network approaches.
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Affiliation(s)
- Eugenio Azpeitia
- Instituto de Ecología, Universidad Nacional Autónoma de MexicoMexico D.F., Mexico
- Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de MexicoMexico D.F., Mexico
| | - Mariana Benítez
- Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de MexicoMexico D.F., Mexico
- Department of Functional Genomics and Proteomics, Masaryk UniversityBrno, Czech Republic
- Central European Institute of Technology, Masaryk UniversityBrno, Czech Republic
| | - Pablo Padilla-Longoria
- Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de MexicoMexico D.F., Mexico
- Instituto de Investigaciones en Matemáticas Aplicadas y en SistemasMexico D.F., Mexico
| | - Carlos Espinosa-Soto
- Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de MexicoMexico D.F., Mexico
- Cinvestav-IPNIrapuato, Mexico
| | - Elena R. Alvarez-Buylla
- Instituto de Ecología, Universidad Nacional Autónoma de MexicoMexico D.F., Mexico
- Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de MexicoMexico D.F., Mexico
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Hernández-Barrera A, Ugartechea-Chirino Y, Shishkova S, Napsucialy-Mendivil S, Soukup A, Reyes-Hernández BJ, Lira-Ruan V, Dong G, Dubrovsky JG. Apical meristem exhaustion during determinate primary root growth in the moots koom 1 mutant of Arabidopsis thaliana. PLANTA 2011; 234:1163-1177. [PMID: 21744091 DOI: 10.1007/s00425-011-1470-4] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/10/2011] [Accepted: 06/22/2011] [Indexed: 05/31/2023]
Abstract
An indeterminate developmental program allows plant organs to grow continuously by maintaining functional meristems over time. The molecular mechanisms involved in the maintenance of the root apical meristem are not completely understood. We have identified a new Arabidopsis thaliana mutant named moots koom 1 (mko1) that showed complete root apical meristem exhaustion of the primary root by 9 days post-germination. MKO1 is essential for maintenance of root cell proliferation. In the mutant, cell division is uncoupled from cell growth in the region corresponding to the root apical meristem. We established the sequence of cellular events that lead to meristem exhaustion in this mutant. Interestingly, the SCR and WOX5 promoters were active in the mko1 quiescent center at all developmental stages. However, during meristem exhaustion, the mutant root tip showed defects in starch accumulation in the columella and changes in auxin response pattern. Therefore, contrary to many described mutants, the determinate growth in mko1 seedlings does not appear to be a consequence of incorrect establishment or affected maintenance of the quiescent center but rather of cell proliferation defects both in stem cell niche and in the rest of the apical meristem. Our results support a model whereby the MKO1 gene plays an important role in the maintenance of the root apical meristem proliferative capacity and indeterminate root growth, which apparently acts independently of the SCR/SHR and WOX5 regulatory pathways.
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Affiliation(s)
- Alejandra Hernández-Barrera
- Departamento de Biología Molecular de Plantas, Instituto de Biotecnología, Universidad Nacional Autónoma de México, Apartado Postal 510-3, 62250, Cuernavaca, Morelos, Mexico
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ten Tusscher K, Scheres B. Joining forces: feedback and integration in plant development. Curr Opin Genet Dev 2011; 21:799-805. [DOI: 10.1016/j.gde.2011.09.008] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2011] [Revised: 09/09/2011] [Accepted: 09/12/2011] [Indexed: 01/30/2023]
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