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Liguori-Bills N, Blinov ML. bnglViz: online visualization of rule-based models. Bioinformatics 2024; 40:btae351. [PMID: 38814806 PMCID: PMC11176710 DOI: 10.1093/bioinformatics/btae351] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2024] [Revised: 05/01/2024] [Accepted: 05/29/2024] [Indexed: 06/01/2024] Open
Abstract
MOTIVATION Rule-based modeling is a powerful method to describe and simulate interactions among multi-site molecules and multi-molecular species, accounting for the internal connectivity of molecules in chemical species. This modeling technique is implemented in BioNetGen software that is used by various tools and software frameworks, such as BioNetGen stand-alone software, NFSim simulation engine, Virtual Cell simulation and modeling framework, SmolDyn and PySB software tools. These tools exchange models using BioNetGen scripting language (BNGL). Until now, there was no online visualization of such rule-based models. Modelers and researchers reading the manuscripts describing rule-based models had to learn BNGL scripting or master one of these tools to understand the models. RESULTS Here, we introduce bnglViz, an online platform for visualizing BNGL files as graphical cartoons, empowering researchers to grasp the nuances of rule-based models swiftly and efficiently, and making the exploration of complex biological systems more accessible than ever before. The produced visualizations can be used as supplemental figures in publications or as a way to annotate BNGL models on web repositories. AVAILABILITY AND IMPLEMENTATION Available at https://bnglviz.github.io/.
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Affiliation(s)
- Noah Liguori-Bills
- Marine Earth and Atmospheric Sciences Department, North Carolina State University, Raleigh, NC 27695, United States
| | - Michael L Blinov
- R. D. Berlin Center for Cell Analysis and Modeling, University of Connecticut School of Medicine, Farmington, CT 06030, United States
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Ma M, Zheng Y, Lu S, Pan X, Worley KC, Burrage LC, Blieden LS, Allworth A, Chen WL, Merla G, Mandriani B, Rosenfeld JA, Li-Kroeger D, Dutta D, Yamamoto S, Wangler MF, Glass IA, Strohbehn S, Blue E, Prontera P, Lalani SR, Bellen HJ. De novo variants in PLCG1 are associated with hearing impairment, ocular pathology, and cardiac defects. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.01.08.23300523. [PMID: 38260438 PMCID: PMC10802640 DOI: 10.1101/2024.01.08.23300523] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
Phospholipase C isozymes (PLCs) hydrolyze phosphatidylinositol 4,5-bisphosphate into inositol 1,4,5-trisphosphate and diacylglycerol, important signaling molecules involved in many cellular processes. PLCG1 encodes the PLCγ1 isozyme that is broadly expressed. Hyperactive somatic mutations of PLCG1 are observed in multiple cancers, but only one germline variant has been reported. Here we describe three unrelated individuals with de novo heterozygous missense variants in PLCG1 (p.Asp1019Gly, p.His380Arg, and p.Asp1165Gly) who exhibit variable phenotypes including hearing loss, ocular pathology and cardiac septal defects. To model these variants in vivo, we generated the analogous variants in the Drosophila ortholog, small wing (sl). We created a null allele slT2A and assessed the expression pattern. sl is broadly expressed, including in wing discs, eye discs, and a subset of neurons and glia. Loss of sl causes wing size reductions, ectopic wing veins and supernumerary photoreceptors. We document that mutant flies exhibit a reduced lifespan and age-dependent locomotor defects. Expressing wild-type sl in slT2A mutant rescues the loss-of-function phenotypes whereas expressing the variants causes lethality. Ubiquitous overexpression of the variants also reduces viability, suggesting that the variants are toxic. Ectopic expression of an established hyperactive PLCG1 variant (p.Asp1165His) in the wing pouch causes severe wing phenotypes, resembling those observed with overexpression of the p.Asp1019Gly or p.Asp1165Gly variants, further arguing that these two are gain-of-function variants. However, the wing phenotypes associated with p.His380Arg overexpression are mild. Our data suggest that the PLCG1 de novo heterozygous missense variants are pathogenic and contribute to the features observed in the probands.
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Affiliation(s)
- Mengqi Ma
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
- Jan and Dan Duncan Neurological Research Institute at Texas Children’s Hospital, Houston, TX 77030, USA
| | - Yiming Zheng
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
- Jan and Dan Duncan Neurological Research Institute at Texas Children’s Hospital, Houston, TX 77030, USA
- Current affiliation: State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Faculty of Medicine and Life Sciences, Xiamen University, Xiamen 361102, China
| | - Shenzhao Lu
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
- Jan and Dan Duncan Neurological Research Institute at Texas Children’s Hospital, Houston, TX 77030, USA
| | - Xueyang Pan
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
- Jan and Dan Duncan Neurological Research Institute at Texas Children’s Hospital, Houston, TX 77030, USA
| | - Kim C. Worley
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Lindsay C. Burrage
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Lauren S. Blieden
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Aimee Allworth
- Division of Medical Genetics, Department of Medicine, University of Washington School of Medicine, Seattle, WA 98195, USA
| | - Wei-Liang Chen
- Division of Medical Genetics, Department of Medicine, University of Washington School of Medicine, Seattle, WA 98195, USA
- Current affiliation: Children’s National Medical Center and George Washington University, Washington DC 20010, USA
| | - Giuseppe Merla
- Laboratory of Regulatory & Functional Genomics, Fondazione IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo, Foggia 71013, Italy
- Department of Molecular Medicine & Medical Biotechnology, University of Naples Federico II, Naples 80131, Italy
| | - Barbara Mandriani
- Department of Interdisciplinary Medicine, University of Bari “Aldo Moro”, Bari 70121, Italy
| | - Jill A. Rosenfeld
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | - David Li-Kroeger
- Department of Neurology, Baylor College of Medicine, Houston, TX 77030, USA
| | - Debdeep Dutta
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
- Jan and Dan Duncan Neurological Research Institute at Texas Children’s Hospital, Houston, TX 77030, USA
| | - Shinya Yamamoto
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
- Jan and Dan Duncan Neurological Research Institute at Texas Children’s Hospital, Houston, TX 77030, USA
| | - Michael F. Wangler
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
- Jan and Dan Duncan Neurological Research Institute at Texas Children’s Hospital, Houston, TX 77030, USA
| | | | - Ian A. Glass
- Division of Medical Genetics, Department of Medicine, University of Washington School of Medicine, Seattle, WA 98195, USA
- Division of Genetic Medicine, Department of Pediatrics, University of Washington School of Medicine, Seattle, WA 98195, USA
- Brotman Baty Institute, Seattle, WA 98195, USA
| | - Sam Strohbehn
- Division of Medical Genetics, Department of Medicine, University of Washington School of Medicine, Seattle, WA 98195, USA
| | - Elizabeth Blue
- Division of Medical Genetics, Department of Medicine, University of Washington School of Medicine, Seattle, WA 98195, USA
- Brotman Baty Institute, Seattle, WA 98195, USA
- Institute for Public Health Genetics, University of Washington, Seattle, WA 98195, USA
| | - Paolo Prontera
- Medical Genetics Unit, Hospital of Perugia, Perugia 06129, Italy
| | - Seema R. Lalani
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Hugo J. Bellen
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
- Jan and Dan Duncan Neurological Research Institute at Texas Children’s Hospital, Houston, TX 77030, USA
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Wysocka EM, Page M, Snowden J, Simpson TI. Comparison of rule- and ordinary differential equation-based dynamic model of DARPP-32 signalling network. PeerJ 2022; 10:e14516. [PMID: 36540795 PMCID: PMC9760030 DOI: 10.7717/peerj.14516] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Accepted: 11/14/2022] [Indexed: 12/23/2022] Open
Abstract
Dynamic modelling has considerably improved our understanding of complex molecular mechanisms. Ordinary differential equations (ODEs) are the most detailed and popular approach to modelling the dynamics of molecular systems. However, their application in signalling networks, characterised by multi-state molecular complexes, can be prohibitive. Contemporary modelling methods, such as rule- based (RB) modelling, have addressed these issues. The advantages of RB modelling over ODEs have been presented and discussed in numerous reviews. In this study, we conduct a direct comparison of the time courses of a molecular system founded on the same reaction network but encoded in the two frameworks. To make such a comparison, a set of reactions that underlie an ODE model was manually encoded in the Kappa language, one of the RB implementations. A comparison of the models was performed at the level of model specification and dynamics, acquired through model simulations. In line with previous reports, we confirm that the Kappa model recapitulates the general dynamics of its ODE counterpart with minor differences. These occur when molecules have multiple sites binding the same interactor. Furthermore, activation of these molecules in the RB model is slower than in the ODE one. As reported for other molecular systems, we find that, also for the DARPP-32 reaction network, the RB representation offers a more expressive and flexible syntax that facilitates access to fine details of the model, easing model reuse. In parallel with these analyses, we report a refactored model of the DARPP-32 interaction network that can serve as a canvas for the development of more complex dynamic models to study this important molecular system.
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Affiliation(s)
- Emilia M. Wysocka
- School of Informatics, University of Edinburgh, Edinburgh, United Kingdom
| | | | | | - T. Ian Simpson
- School of Informatics, University of Edinburgh, Edinburgh, United Kingdom
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