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CRISPR modified cell lines

CRISPR modified cell lines

We are using CRISPR gene editing technologies to generate new cell lines as part of the funded project NIH ORIP R24 OD019847 "Next-generation Drosophila cell lines to elucidate the cellular basis of human diseases" (N. Perrimon, PI; A. Simcox, Co-PI).

GFP-tagged knock-in cell lines

As part of the ORIP-funded project, we are making GFP-tagged cell lines, with an emphasis on visualization of various organelles and sub-cellular compartments. The following GFP knock-in cell lines made at the DRSC in collaboration with the Bellne lab are available for distribution by the DGRC in Bloomington, IN. 

Note that the parental cell line is positive for an mCherry fusion and Cas9, as the parental cell line is S2R+-MT::Cas9 (DGRC cell catalog #268), which is described in Viswanatha et al. 2018 (PubMed ID 30051818). This parental cell line was itself derived from DRSC cell line S2R+ NPT005 (DGRC cell catalog #229), which is described in Neumuller et al. 2012 (PubMed ID 22174071).

S2R+ with GFP::Cnx99a. Ordering information: DGRC cell catalog ID #273
S2R+ with GFP::Rab11. Ordering information: DGRC cell catalog ID #274
S2R+ with GFP::Polo. Ordering information: DGRC cell catalog ID #275
S2R+ with GFP::Gmap (clone #4). Ordering information: DGRC cell catalog ID #276
S2R+ with GFP::Gmap (clone $7). Ordering information: DGRC cell catalog ID #277
S2R+ with GFP::Fib (clone #11). Ordering information: DGRC cell catalog ID #278
S2R+ with GFP::Fib (clone #12). Ordering information: DGRC cell catalog ID #279
S2R+ with GFP::Golgin. Ordering information: DGRC cell catalog ID #280
S2R+ with GFP::Arl8. Ordering information: DGRC cell catalog ID #291
S2R+ with GFP::Lam. Ordering information: DGRC cell catalog ID #292
S2R+ with GFP::Spin. Ordering information: DGRC cell catalog ID #293
S2R+ with GFP::Sec23. Ordering information: DGRC cell catalog ID #294

These cell lines were made using constructs designed and provided by Kanca and Bellen (Baylor College of Medicine). The cell lines were engineered, isolated, and validated at the DRSC. Validation testing included live-cell imaging, fixed-cell imaging (co-stained with an antibody, when possible), and molecular characterization of the insertion endpoints.

In addition, C-terminal GFP knock-in cell lines were generated as described in a BioRxiv preprint from Bosch et al. (2019) using an 'armless' donor approach. Act5c::GFP, Tub84B::GFP, His2Av::GFP, and Lamin::GFP fusion cell lines were made using this approach and are being shared with the DGRC for distribution to the community.

Knockout cell lines

S2R+-ZnT63C-KO, NHEJ-mediated knockout of ZnT63C. As described in PMID: 29223976. Ordering information: DGRC cell catalog #265.
S2R+-IA2-KO, NHEJ-mediated knockout of ia2. As described in PMID: 29223976. Ordering information: DGRC cell catalog #266.

These cell lines have been sequence verified as containing only knockout alleles by PCR amplification of the target region followed by next-generation sequencing of the PCR amplicon, contig assembly, and comparison with the wild-type reference sequence. We wanted to make sure that the distribution copies of the cell lines are correct. To do this, the DGRC prepared genomic DNA from their distribution copies of the cell lines and shipped that gDNA to the DRSC/TRiP, which we then used as the template for PCR and NGS analysis.

Did you request these cells from the DGRC and use them in a study? If so, please acknowledge both the cell line developers and distribtors by citing NIH Grant 5R24OD019847, which supported production of the resource at DRSC/TRiP, and the Drosophila Genome Resource Center, NIH grant 2P40OD010949, as well as the relevant pulication (manuscript in preparation).

Publications

Ben Ewen-Campen, Stephanie E Mohr, Yanhui Hu, and Norbert Perrimon. 10/9/2017. “Accessing the Phenotype Gap: Enabling Systematic Investigation of Paralog Functional Complexity with CRISPR.” Dev Cell, 43, 1, Pp. 6-9.Abstract
Single-gene knockout experiments can fail to reveal function in the context of redundancy, which is frequently observed among duplicated genes (paralogs) with overlapping functions. We discuss the complexity associated with studying paralogs and outline how recent advances in CRISPR will help address the "phenotype gap" and impact biomedical research.
Huajin Wang, Michel Becuwe, Benjamin E Housden, Chandramohan Chitraju, Ashley J Porras, Morven M Graham, Xinran N Liu, Abdou Rachid Thiam, David B Savage, Anil K Agarwal, Abhimanyu Garg, Maria-Jesus Olarte, Qingqing Lin, Florian Fröhlich, Hans Kristian Hannibal-Bach, Srigokul Upadhyayula, Norbert Perrimon, Tomas Kirchhausen, Christer S Ejsing, Tobias C Walther, and Robert V Farese. 2016. “Seipin is required for converting nascent to mature lipid droplets.” Elife, 5.Abstract

How proteins control the biogenesis of cellular lipid droplets (LDs) is poorly understood. Using Drosophila and human cells, we show here that seipin, an ER protein implicated in LD biology, mediates a discrete step in LD formation-the conversion of small, nascent LDs to larger, mature LDs. Seipin forms discrete and dynamic foci in the ER that interact with nascent LDs to enable their growth. In the absence of seipin, numerous small, nascent LDs accumulate near the ER and most often fail to grow. Those that do grow prematurely acquire lipid synthesis enzymes and undergo expansion, eventually leading to the giant LDs characteristic of seipin deficiency. Our studies identify a discrete step of LD formation, namely the conversion of nascent LDs to mature LDs, and define a molecular role for seipin in this process, most likely by acting at ER-LD contact sites to enable lipid transfer to nascent LDs.

Benjamin E Housden, Matthias Muhar, Matthew Gemberling, Charles A Gersbach, Didier YR Stainier, Geraldine Seydoux, Stephanie E Mohr, Johannes Zuber, and Norbert Perrimon. 10/31/2016. “Loss-of-function genetic tools for animal models: cross-species and cross-platform differences.” Nat Rev Genet. Publisher's VersionAbstract
2016_Nat Rev Gene_Housden.pdf

Our understanding of the genetic mechanisms that underlie biological processes has relied extensively on loss-of-function (LOF) analyses. LOF methods target DNA, RNA or protein to reduce or to ablate gene function. By analysing the phenotypes that are caused by these perturbations the wild-type function of genes can be elucidated. Although all LOF methods reduce gene activity, the choice of approach (for example, mutagenesis, CRISPR-based gene editing, RNA interference, morpholinos or pharmacological inhibition) can have a major effect on phenotypic outcomes. Interpretation of the LOF phenotype must take into account the biological process that is targeted by each method. The practicality and efficiency of LOF methods also vary considerably between model systems. We describe parameters for choosing the optimal combination of method and system, and for interpreting phenotypes within the constraints of each method.

Stephanie E Mohr, Yanhui Hu, Benjamin Ewen-Campen, Benjamin E Housden, Raghuvir Viswanatha, and Norbert Perrimon. 2016. “CRISPR guide RNA design for research applications.” FEBS J.Abstract
2016_FEBS_Mohr.pdf

The rapid rise of CRISPR as a technology for genome engineering and related research applications has created a need for algorithms and associated online tools that facilitate design of on-target and effective guide RNAs (gRNAs). Here, we review the state-of-the-art in CRISPR gRNA design for research applications of the CRISPR-Cas9 system, including knockout, activation and inhibition. Notably, achieving good gRNA design is not solely dependent on innovations in CRISPR technology. Good design and design tools also rely on availability of high-quality genome sequence and gene annotations, as well as on availability of accumulated data regarding off-targets and effectiveness metrics. This article is protected by copyright. All rights reserved.

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