@article {66002,
	title = {Image-based pooled whole-genome CRISPRi screening for subcellular phenotypes.},
	journal = {Journal of Cell Biology},
	volume = {220},
	year = {2021},
	month = {2021 Feb 01},
	abstract = {<p>Genome-wide CRISPR screens have transformed our ability to systematically interrogate human gene function, but are currently limited to a subset of cellular phenotypes. We report a novel pooled screening approach for a wider range of cellular and subtle subcellular phenotypes. Machine learning and convolutional neural network models are trained on the subcellular phenotype to be queried. Genome-wide screening then utilizes cells stably expressing dCas9-KRAB (CRISPRi), photoactivatable fluorescent protein (PA-mCherry), and a lentiviral guide RNA (gRNA) pool. Cells are screened by using microscopy and classified by artificial intelligence (AI) algorithms, which precisely identify the genetically altered phenotype. Cells with the phenotype of interest are photoactivated and isolated via flow cytometry, and the gRNAs are identified by sequencing. A proof-of-concept screen accurately identified PINK1 as essential for Parkin recruitment to mitochondria. A genome-wide screen identified factors mediating TFEB relocation from the nucleus to the cytosol upon prolonged starvation. Twenty-one of the 64 hits called by the neural network model were independently validated, revealing new effectors of TFEB subcellular localization. This approach, AI-photoswitchable screening (AI-PS), offers a novel screening platform capable of classifying a broad range of mammalian subcellular morphologies, an approach largely unattainable with current methodologies at genome-wide scale.</p>
},
	issn = {1540-8140},
	doi = {10.1083/jcb.202006180},
	author = {Kanfer, Gil and Sarraf, Shireen A and Maman, Yaakov and Baldwin, Heather and Dominguez-Martin, Eunice and Johnson, Kory R and Ward, Michael E and Kampmann, Martin and Lippincott-Schwartz, Jennifer and Youle, Richard J}
}
@article {65896,
	title = {In situ differentiation of iridophore crystallotypes underlies zebrafish stripe patterning.},
	journal = {Nature Communications},
	volume = {11},
	year = {2020},
	month = {2020 Dec 15},
	pages = {6391},
	abstract = {<p>Skin color patterns are ubiquitous in nature, impact social behavior, predator avoidance, and protection from ultraviolet irradiation. A leading model system for vertebrate skin patterning is the zebrafish; its alternating blue stripes and yellow interstripes depend on light-reflecting cells called iridophores. It was suggested that the zebrafish{\textquoteright}s color pattern arises from a single type of iridophore migrating differentially to stripes and interstripes. However, here we find that iridophores do not migrate between stripes and interstripes but instead differentiate and proliferate in-place, based on their micro-environment. RNA-sequencing analysis further reveals that stripe and interstripe iridophores have different transcriptomic states, while cryogenic-scanning-electron-microscopy and micro-X-ray diffraction identify different crystal-arrays architectures, indicating that stripe and interstripe iridophores are different cell types. Based on these results, we present an alternative model of skin patterning in zebrafish in which distinct iridophore crystallotypes containing specialized, physiologically responsive, organelles arise in stripe and interstripe by in-situ differentiation.</p>
},
	keywords = {Animals, Cell Differentiation, Cell Proliferation, Chromatophores, Microphthalmia-Associated Transcription Factor, Mutagenesis, Skin, Skin Pigmentation, Transcriptome, X-Ray Diffraction, Zebrafish, Zebrafish Proteins},
	issn = {2041-1723},
	doi = {10.1038/s41467-020-20088-1},
	author = {Gur, Dvir and Bain, Emily J and Johnson, Kory R and Aman, Andy J and Pasoili, H Amalia and Flynn, Jessica D and Allen, Michael C and Deheyn, Dimitri D and Lee, Jennifer C and Lippincott-Schwartz, Jennifer and Parichy, David M}
}
