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1.
Circulation ; 149(25): 1960-1979, 2024 Jun 18.
Article in English | MEDLINE | ID: mdl-38752370

ABSTRACT

BACKGROUND: Cardiomyocyte differentiation involves a stepwise clearance of repressors and fate-restricting regulators through the modulation of BMP (bone morphogenic protein)/Wnt-signaling pathways. However, the mechanisms and how regulatory roadblocks are removed with specific developmental signaling pathways remain unclear. METHODS: We conducted a genome-wide CRISPR screen to uncover essential regulators of cardiomyocyte specification in human embryonic stem cells using a myosin heavy chain 6 (MYH6)-GFP (green fluorescence protein) reporter system. After an independent secondary single guide ribonucleic acid validation of 25 candidates, we identified NF2 (neurofibromin 2), a moesin-ezrin-radixin like (MERLIN) tumor suppressor, as an upstream driver of early cardiomyocyte lineage specification. Independent monoclonal NF2 knockouts were generated using CRISPR-Cas9, and cell states were inferred through bulk RNA sequencing and protein expression analysis across differentiation time points. Terminal lineage differentiation was assessed by using an in vitro 2-dimensional-micropatterned gastruloid model, trilineage differentiation, and cardiomyocyte differentiation. Protein interaction and post-translation modification of NF2 with its interacting partners were assessed using site-directed mutagenesis, coimmunoprecipitation, and proximity ligation assays. RESULTS: Transcriptional regulation and trajectory inference from NF2-null cells reveal the loss of cardiomyocyte identity and the acquisition of nonmesodermal identity. Sustained elevation of early mesoderm lineage repressor SOX2 and upregulation of late anticardiac regulators CDX2 and MSX1 in NF2 knockout cells reflect a necessary role for NF2 in removing regulatory roadblocks. Furthermore, we found that NF2 and AMOT (angiomotin) cooperatively bind to YAP (yes-associated protein) during mesendoderm formation, thereby preventing YAP activation, independent of canonical MST (mammalian sterile 20-like serine-threonine protein kinase)-LATS (large tumor suppressor serine-threonine protein kinase) signaling. Mechanistically, cardiomyocyte lineage identity was rescued by wild-type and NF2 serine-518 phosphomutants, but not NF2 FERM (ezrin-radixin-meosin homology protein) domain blue-box mutants, demonstrating that the critical FERM domain-dependent formation of the AMOT-NF2-YAP scaffold complex at the adherens junction is required for early cardiomyocyte lineage differentiation. CONCLUSIONS: These results provide mechanistic insight into the essential role of NF2 during early epithelial-mesenchymal transition by sequestering the repressive effect of YAP and relieving regulatory roadblocks en route to cardiomyocytes.


Subject(s)
Cell Differentiation , Cell Lineage , Myocytes, Cardiac , Neurofibromin 2 , Humans , Myocytes, Cardiac/metabolism , Neurofibromin 2/genetics , Neurofibromin 2/metabolism , CRISPR-Cas Systems , Human Embryonic Stem Cells/metabolism , Human Embryonic Stem Cells/cytology
2.
Nat Genet ; 56(3): 431-441, 2024 Mar.
Article in English | MEDLINE | ID: mdl-38413725

ABSTRACT

Spatial omics data are clustered to define both cell types and tissue domains. We present Building Aggregates with a Neighborhood Kernel and Spatial Yardstick (BANKSY), an algorithm that unifies these two spatial clustering problems by embedding cells in a product space of their own and the local neighborhood transcriptome, representing cell state and microenvironment, respectively. BANKSY's spatial feature augmentation strategy improved performance on both tasks when tested on diverse RNA (imaging, sequencing) and protein (imaging) datasets. BANKSY revealed unexpected niche-dependent cell states in the mouse brain and outperformed competing methods on domain segmentation and cell typing benchmarks. BANKSY can also be used for quality control of spatial transcriptomics data and for spatially aware batch effect correction. Importantly, it is substantially faster and more scalable than existing methods, enabling the processing of millions of cell datasets. In summary, BANKSY provides an accurate, biologically motivated, scalable and versatile framework for analyzing spatially resolved omics data.


Subject(s)
Algorithms , Benchmarking , Animals , Mice , Gene Expression Profiling , RNA , Transcriptome , Data Analysis
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