Atf3 links loss of epithelial polarity to defects in cell differentiation and cytoarchitecture

Donohoe, Colin D.; Csordás, Gábor; Correia, Andreia; Jindra, Marek; Klein, Corinna; Habermann, Bianca; Uhlířová, Mirka

doi:10.1101/212969

Cited by 5 publications

(4 citation statements)

References 86 publications

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“…There are hundreds of cell types in the fly brain, impeding the use of bulk datasets for accurately deciphering diversity. Even more, compared to the embryo 58,[83][84][85][86][87] or imaginal discs 59,[88][89][90][91][92][93][94] , the number of ChIP-seq or other epigenomic datasets is very limited in the brain 24,[95][96][97] . In contrast, in this study we constructed 40 eGRNs at once, covering 88 transcription factors with 7833 enhancers that are linked to 3776 target genes.…”

Section: Discussionmentioning

confidence: 99%

Decoding gene regulation in the fly brain

Janssens

Aibar

Taskiran

et al. 2022

Nature

124

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The Drosophila brain is a work horse in neuroscience. Single-cell transcriptome analysis 1-5 , 3D morphological classification 6 , and detailed EM mapping of the connectome 7-10 have revealed an immense diversity of neuronal and glial cell types that underlie the wide array of functional and behavioral traits in the fruit fly. The identities of these cell types are controlled by -still unknowngene regulatory networks (GRNs), involving combinations of transcription factors that bind to genomic enhancers to regulate their target genes. To characterize the GRN for each cell type in the Drosophila brain, we profiled chromatin accessibility of 240,919 single cells spanning nine developmental timepoints, and integrated this data with single-cell transcriptomes. We identify more than 95,000 regulatory regions that are used in different neuronal cell types, of which around 70,000 are linked to specific developmental trajectories, involving neurogenesis, reprogramming and maturation. For 40 cell types, their uniquely accessible regions could be associated with their expressed transcription factors and downstream target genes, through a combination of motif discovery, network inference techniques, and deep learning. We illustrate how these "enhancer-GRNs" can be used to reveal enhancer architectures leading to a better understanding of neuronal regulatory diversity. Finally, our atlas of regulatory elements can be used to design genetic driver lines for specific cell types at specific timepoints, facilitating the characterization of brain cell types and the manipulation of brain function. MainThe brain consists of a myriad of different neuronal and glial types, each unique in their morphology and function. The Drosophila brain, which contains around 100,000 cells, is uniquely positioned as a model in which the diversity of brain cell types can be investigated. Recent advances in electron microscopy have allowed the creation of connectome maps of the different regions in the Drosophila brain 7-10 , while the availability of genetic driver lines 11 provides genetic access to many cell types for understanding neuronal function 12 . Furthermore, this diversity of cell types has been bolstered by single-cell transcriptomics on the adult brain 1-5 , the larval brain [13][14][15] , and the ventral nerve cord 16 . The recent development of single-cell assay for transposase accessible chromatin by sequencing (scATAC-seq), makes it possible to measure chromatin accessibility of single cells in high throughput 17,18 , providing an additional crucial layer of information underlying neuronal identity: which genomic regions encode the regulatory information to create and maintain each cell type. The integrated analysis of transcriptomics and chromatin accessibility makes it then possible to jointly study enhancers and gene expression to discover precise regulatory programs across cell types [19][20][21] .Cell type identity is defined by the activity of GRNs in which combinations of transcription factors activate or repress target genes....

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Section: Discussionmentioning

confidence: 99%

Decoding gene regulation in the fly brain

Janssens

Aibar

Taskiran

et al. 2022

Nature

124

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“…Dissected EADs were prepared as previously described [50]. For each sample ( n ≥ 4 per genotype), 30 000 events were counted on LSR Fortessa Flow Cytometer (BD Biosciences, Heidelberg, Germany).…”

Section: Methodsmentioning

confidence: 99%

The mechanosensor Filamin A/Cheerio promotes tumourigenesis via specific interactions with components of the cell cortex

et al. 2022

Self Cite

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Cancer development has been linked to aberrant sensing and interpretation of mechanical cues and force‐generating properties. Here, we show that upregulation of the actin crosslinking protein Cheerio (Cher), the fly ortholog of Filamin A (FLNA), and the conformation of its mechanosensitive region (MSR) are instrumental to the malignancy of polarity‐deficient, Ras‐driven tumours in Drosophila epithelia. We demonstrate that impaired growth and cytoskeletal contractility of tumours devoid of cher can be rescued by stimulating myosin activity. Profiling the Cher interactome in tumour‐bearing imaginal discs identified several components of the cell cortex, including the β‐heavy Spectrin Karst (Kst), the scaffolding protein Big bang (Bbg), and 14‐3‐3ε. We show that Cher binds Bbg through the MSR while the interaction with 14‐3‐3ε and Kst is MSR‐independent. Importantly, our genetic studies define Bbg, Kst, and 14‐3‐3ε as tumour suppressors. The tumour‐promoting function of Cher thus relies on its capacity to control the contractile state of the cytoskeleton through interactions with myosin and specific components of the cell cortex.

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“…However, our collective experiences with monoclonal anti-GFP antibodies have been unsatisfactory. Since single-domain anti-GFP nanobodies offer consistent performance in IP-related experiments [e.g., Cicconi et al 2017; Donohoe et al 2018], and can be readily purified from bacteria, we were prompted to develop a method generally applicable to profiling GFP-tagged chromatin proteins. In our modified scheme called “nanoCUT&RUN”, the nuclease recruitment is accomplished by the binding of a GFP-specific nanobody [Saerens et al 2005], similarly expressed as a fusion protein, to a GFP-tagged target protein produced in vivo .…”

Section: Introductionmentioning

confidence: 99%

The nanoCUT&RUN technique visualizes telomeric chromatin in Drosophila

Chen

Wei

Courret

et al. 2022

Preprint

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Advances in genomic technology led to a more focused pattern for the distribution of chromosomal proteins and a better understanding of their functions. The recent development of the CUT&RUN technique marks one of the important such advances. Here we develop a modified CUT&RUN technique that we termed nanoCUT&RUN, in which a high affinity nanobody to GFP is used to bring micrococcal nuclease to the binding sites of GFP-tagged chromatin proteins. Subsequent activation of the nuclease cleaves the chromatin, and sequencing of released DNA identifies binding sites. We show that nanoCUT&RUN efficiently produces high quality data for the TRL transcription factor in Drosophila embryos, and distinguishes binding sites specific between two TRL isoforms. We further show that nanoCUT&RUN dissects the distributions of the HipHop and HOAP telomere capping proteins, and uncovers unexpected binding of telomeric proteins at centromeres. nanoCUT&RUN can be readily applied to any system in which a chromatin protein of interest, or its isoforms, carries the GFP tag.

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Atf3 links loss of epithelial polarity to defects in cell differentiation and cytoarchitecture

Cited by 5 publications

References 86 publications

Decoding gene regulation in the fly brain

Decoding gene regulation in the fly brain

The mechanosensor Filamin A/Cheerio promotes tumourigenesis via specific interactions with components of the cell cortex

The nanoCUT&RUN technique visualizes telomeric chromatin in Drosophila

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