Computational modeling and analysis of the morphogenetic domain signaling networks regulating C. elegans embryogenesis
Caenorhabditis elegans, often referred to as the ‘roundworm’, provides a powerful model for studying cell autonomous and cell–cell interactions through the direct observation of embryonic development in vivo. By leveraging the precisely mapped cell lineage at single cell resolution, we are able to s...
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| Format: | Article |
| Language: | English |
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Elsevier
2022-01-01
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| Series: | Computational and Structural Biotechnology Journal |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2001037022002148 |
| _version_ | 1797978199473258496 |
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| author | Ben Niu Thao Nguyen Bach Xingyu Chen Khyati Raghunath Chandratre John Isaac Murray Zhongying Zhao Michael Zhang |
| author_facet | Ben Niu Thao Nguyen Bach Xingyu Chen Khyati Raghunath Chandratre John Isaac Murray Zhongying Zhao Michael Zhang |
| author_sort | Ben Niu |
| collection | DOAJ |
| description | Caenorhabditis elegans, often referred to as the ‘roundworm’, provides a powerful model for studying cell autonomous and cell–cell interactions through the direct observation of embryonic development in vivo. By leveraging the precisely mapped cell lineage at single cell resolution, we are able to study at a systems level how early embryonic cells communicate across morphogenetic domains for the coordinated processes of gene expressions and collective cellular behaviors that regulate tissue morphogenesis. In this study, we developed a computational framework for the exploration of the morphogenetic domain cell signaling networks that may regulate C. elegans gastrulation and embryonic organogenesis. We demonstrated its utility by producing the following results, i) established a virtual reference model of developing C. elegans embryos through the spatiotemporal alignment of individual embryo cell nuclear imaging samples; ii) integrated the single cell spatiotemporal gene expression profile with the established virtual embryo model by data pooling; iii) trained a Machine Learning model (Random Forest Regression), which predicts accurately the spatial positions of the cells given their gene expression profiles for a given developmental time (e.g. total cell number of the embryo); iv) enabled virtual 4-dimensional tomographic graphical modeling of single cell data; v) inferred the biology signaling pathways that act in each of morphogenetic domains by meta-data analysis. It is intriguing that the morphogenetic domain cell signaling network seems to involve some crosstalk of multiple biology signaling pathways during the formation of tissue boundary pattern. Lastly, we developed the Software tool ‘Embryo aligner version 1.0’ and provided it as an Open Source program to the research community for virtual embryo modeling, and phenotype perturbation analyses (https://github.com/csniuben/embryo_aligner/wiki and https://bioinfo89.github.io/C.elegansEmbryonicOrganogenesisweb/). |
| first_indexed | 2024-04-11T05:19:09Z |
| format | Article |
| id | doaj.art-157553a99d7047b5badd4bdf4a9f0446 |
| institution | Directory Open Access Journal |
| issn | 2001-0370 |
| language | English |
| last_indexed | 2024-04-11T05:19:09Z |
| publishDate | 2022-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Computational and Structural Biotechnology Journal |
| spelling | doaj.art-157553a99d7047b5badd4bdf4a9f04462022-12-24T04:52:49ZengElsevierComputational and Structural Biotechnology Journal2001-03702022-01-012036533666Computational modeling and analysis of the morphogenetic domain signaling networks regulating C. elegans embryogenesisBen Niu0Thao Nguyen Bach1Xingyu Chen2Khyati Raghunath Chandratre3John Isaac Murray4Zhongying Zhao5Michael Zhang6Center for Systems Biology, The University of Texas at Dallas, 75080, USACenter for Systems Biology, The University of Texas at Dallas, 75080, USACenter for Systems Biology, The University of Texas at Dallas, 75080, USACenter for Systems Biology, The University of Texas at Dallas, 75080, USADepartment of Genetics, The University of Pennsylvania, USADepartment of Biology, Hong Kong Baptist University, Hong KongCenter for Systems Biology, The University of Texas at Dallas, 75080, USA; Corresponding author.Caenorhabditis elegans, often referred to as the ‘roundworm’, provides a powerful model for studying cell autonomous and cell–cell interactions through the direct observation of embryonic development in vivo. By leveraging the precisely mapped cell lineage at single cell resolution, we are able to study at a systems level how early embryonic cells communicate across morphogenetic domains for the coordinated processes of gene expressions and collective cellular behaviors that regulate tissue morphogenesis. In this study, we developed a computational framework for the exploration of the morphogenetic domain cell signaling networks that may regulate C. elegans gastrulation and embryonic organogenesis. We demonstrated its utility by producing the following results, i) established a virtual reference model of developing C. elegans embryos through the spatiotemporal alignment of individual embryo cell nuclear imaging samples; ii) integrated the single cell spatiotemporal gene expression profile with the established virtual embryo model by data pooling; iii) trained a Machine Learning model (Random Forest Regression), which predicts accurately the spatial positions of the cells given their gene expression profiles for a given developmental time (e.g. total cell number of the embryo); iv) enabled virtual 4-dimensional tomographic graphical modeling of single cell data; v) inferred the biology signaling pathways that act in each of morphogenetic domains by meta-data analysis. It is intriguing that the morphogenetic domain cell signaling network seems to involve some crosstalk of multiple biology signaling pathways during the formation of tissue boundary pattern. Lastly, we developed the Software tool ‘Embryo aligner version 1.0’ and provided it as an Open Source program to the research community for virtual embryo modeling, and phenotype perturbation analyses (https://github.com/csniuben/embryo_aligner/wiki and https://bioinfo89.github.io/C.elegansEmbryonicOrganogenesisweb/).http://www.sciencedirect.com/science/article/pii/S2001037022002148Computational image analysisMorphogenetic domain cell signaling networkSingle cell gene expression modelingCollective cell behaviorMachine learning |
| spellingShingle | Ben Niu Thao Nguyen Bach Xingyu Chen Khyati Raghunath Chandratre John Isaac Murray Zhongying Zhao Michael Zhang Computational modeling and analysis of the morphogenetic domain signaling networks regulating C. elegans embryogenesis Computational and Structural Biotechnology Journal Computational image analysis Morphogenetic domain cell signaling network Single cell gene expression modeling Collective cell behavior Machine learning |
| title | Computational modeling and analysis of the morphogenetic domain signaling networks regulating C. elegans embryogenesis |
| title_full | Computational modeling and analysis of the morphogenetic domain signaling networks regulating C. elegans embryogenesis |
| title_fullStr | Computational modeling and analysis of the morphogenetic domain signaling networks regulating C. elegans embryogenesis |
| title_full_unstemmed | Computational modeling and analysis of the morphogenetic domain signaling networks regulating C. elegans embryogenesis |
| title_short | Computational modeling and analysis of the morphogenetic domain signaling networks regulating C. elegans embryogenesis |
| title_sort | computational modeling and analysis of the morphogenetic domain signaling networks regulating c elegans embryogenesis |
| topic | Computational image analysis Morphogenetic domain cell signaling network Single cell gene expression modeling Collective cell behavior Machine learning |
| url | http://www.sciencedirect.com/science/article/pii/S2001037022002148 |
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