Continuous muscle, glial, epithelial, neuronal, and hemocyte cell lines for Drosophila research

  1. Nikki Coleman-Gosser
  2. Yanhui Hu
  3. Shiva Raghuvanshi
  4. Shane Stitzinger
  5. Weihang Chen
  6. Arthur Luhur
  7. Daniel Mariyappa
  8. Molly Josifov
  9. Andrew Zelhof
  10. Stephanie E Mohr
  11. Norbert Perrimon  Is a corresponding author
  12. Amanda Simcox  Is a corresponding author
  1. Department of Molecular Genetics, Ohio State University, United States
  2. Drosophila RNAi Screening Center and Department of Genetics, Harvard Medical School, United States
  3. Drosophila Genomics Resource Center and Department of Biology, Indiana University, United States
  4. Howard Hughes Medical Institute, United States
  5. National Science Foundation, United States

Abstract

Expression of activated Ras, RasV12, provides Drosophila cultured cells with a proliferation and survival advantage that simplifies the generation of continuous cell lines. Here, we used lineage-restricted RasV12 expression to generate continuous cell lines of muscle, glial, and epithelial cell type. Additionally, cell lines with neuronal and hemocyte characteristics were isolated by cloning from cell cultures established with broad RasV12 expression. Differentiation with the hormone ecdysone caused maturation of cells from mesoderm lines into active muscle tissue and enhanced dendritic features in neuronal-like lines. Transcriptome analysis showed expression of key cell-type-specific genes and the expected alignment with single-cell sequencing and in situ data. Overall, the technique has produced in vitro cell models with characteristics of glia, epithelium, muscle, nerve, and hemocyte. The cells and associated data are available from the Drosophila Genomic Resource Center.

Editor's evaluation

This valuable work describes the establishment and characterization of new cell lines derived from specific tissues of the fruit fly Drosophila. The evidence supporting the claims of the authors is convincing, with rigorous characterization of the cell lines and incorporation of their transcriptomes into Drosophila Gene Expression Tool website for user-friendly access. These lines will be a valuable resource that complements in vivo Drosophila genetics, improving biochemistry and facilitating high-throughput screening.

https://doi.org/10.7554/eLife.85814.sa0

eLife digest

Fruit flies are widely used in the life and biomedical sciences as models of animal biology. They are small in size and easy to care for in a laboratory, making them ideal for studying how the body works. There are, however, some experiments that are difficult to perform on whole flies and it would be advantageous to use populations of fruit fly cells grown in the laboratory – known as cell cultures – instead.

Unlike studies in humans and other mammals, which – for ethical and practical reasons –heavily rely on cell cultures, few studies have used fruit fly cell cultures. Recent work has shown that having an always active version of a gene called Ras in fruit fly cells helps the cells to survive and grow in cultures, making it simpler to generate new fruit fly cell lines compared with traditional methods. However, the methods used to express activated Ras result in cell lines that can be a mixture of many different types of cell, which limits how useful they are for research.

Here, Coleman-Gosser, Hu, Raghuvanshi, Stitzinger et al. aimed to use Ras to generate a collection of cell lines from specific types of fruit fly cells in the muscle, nervous system, blood and other parts of the body. The experiments show that selectively expressing activated Ras in an individual type of cell enables them to outcompete other cells in culture to generate a cell line consisting only of the cell type of interest.

The new cell lines offer models for experiments that more closely reflect their counterparts in flies. For example, the team were able to recapitulate how fly muscles develop by treating one of the cell lines with a hormone called ecdysone, which triggered the cells to mature into active muscle cells that spontaneously contract and relax.

In the future, the new cell lines could be used for various experiments including high throughput genetic screening or testing the effects of new drugs and other compounds. The method used in this work may also be used by other researchers to generate more fruit fly cell lines.

Introduction

The use of cell cultures has been important for studying biological processes that are not easily accessible in whole organisms (Klein et al., 2022). A number of advances in mammalian cell cultures, for instance, development of 3D/organoid cultures (Rossi et al., 2018), improved genome editing tools to manipulate induced pluripotent stem cells (Hockemeyer and Jaenisch, 2016), and better optimized media formulations for recombinant protein expression Ritacco et al., 2018 have further enhanced the utility of mammalian cell culture systems. These advances are accompanied by the availability of several distinct mammalian cell lines derived from different tissue types. Similarly, the use of insect cell lines also complements whole organismal studies and helped to illuminate many aspects of insect cell biology (Luhur et al., 2019) including development (Sato and Siomi, 2020), immunity (Goodman et al., 2021; Chen et al., 2021), host–pathogen relationships (Smagghe et al., 2009), in addition to biotechnological applications (Hong et al., 2022).

Fruit fly (Drosophila melanogaster) cell cultures are among the most widely used invertebrate cell cultures (Luhur et al., 2019). Drosophila cell lines are relatively homogenous, and highly scalable for both biochemical and high-throughput functional genomic analyses (Debec et al., 2016, Baum and Cherbas, 2008; Zirin et al., 2022; Mohr, 2014; Viswanatha et al., 2019). These features underlie their status as an important workhorse for scientific discovery in organismal development and as models for human disease. There are approximately 250 distinct Drosophila cell lines housed by the Drosophila Genomics Resource Center (DGRC) (Luhur et al., 2019). The majority of these cell lines, initially established by independent laboratories worldwide, were donated to the DGRC. A subset of 25 of these lines was subjected to transcriptome analysis, with the results demonstrating that approximately half of the transcripts expressed by each of these lines were unique such that even cell lines derived from the same tissue had distinct transcriptomic profiles (Cherbas et al., 2011). Furthermore, the transcriptional profiles of several imaginal disc lines analyzed were found to match profiles of cells from distinct spatial locations in the respective discs (Cherbas et al., 2011). All lines exhibited transcript profiles indicative of cell growth and cell division, and not cellular differentiation, as expected for proliferating cells (Cherbas et al., 2011). Thus, the transcriptional profiles of several Drosophila cell lines provided a platform for subsequent analyses. For instance, a few examples of the impact of this work include research into better understanding crosstalk between signaling pathways (Ammeux et al., 2016), exploring transcription factor networks (Rhee et al., 2014), establishing small RNA diversity (Wen et al., 2014), characterizing signaling pathways (Neal et al., 2019), nucleosomal organization (Martin et al., 2017) among multiple other utilities reviewed extensively (Cherbas and Gong, 2014; Luhur et al., 2019).

Over two-thirds of the D. melanogaster cell lines listed in the DGRC catalog were derived from whole embryos and the remainder are from various larval imaginal discs, the larval central nervous system, larval hemocytes, or adult ovaries. The potential of cells from these different sources to differentiate into adult cell types is not known. However, temporal transcriptional profiling of the Ecdysone response of 41 cell lines (Stoiber et al., 2016) provided evidence that cell lines exhibited varying levels of ecdysone sensitivity and potential for cellular differentiation, suggesting the possibility of developing cell-type-specific cell lines with the capacity to differentiate.

As well as having unknown cellular origins, most Drosophila cell lines arose spontaneously, and the time needed to develop a continuous cell line was often protracted. In contrast, expression of activated Ras, RasV12, using the Gal4-UAS system, resulted in the rapid and reproducible generation of continuous cell lines from primary embryonic cultures (Simcox et al., 2008b). The Ras method was used to develop an array of mutant cell lines by using appropriate genotypes to establish the primary cultures (Simcox et al., 2008a, Lee et al., 2015; Kahn et al., 2014; Lim et al., 2016; Nakato et al., 2019). To date all lines have been generated using ubiquitous expression of UAS-Ras with Act5C-Gal4 and therefore the cell type in a given line is unknown.

Here, we describe a second-generation version of the Ras method in which RasV12 expression is restricted to a lineage by using tissue-specific Gal4 drivers. This genetic ‘dissection’ provides only the targeted cells with the survival and proliferation advantage conferred by RasV12 expression (Simcox et al., 2008b). As we show, the approach has been successful and resulted in the generation of cell lines with glial, epithelial, and muscle characteristics. Lines generated by broad RasV12 expression should also include those of specific cell types and by using single-cell cloning and cell type characterization (marker gene expression and RNAseq) we identified lines with neuronal and hemocyte characteristics. Collectively, these cell lines provide in vitro models for five different cell types and are expected to be a valuable resource for high-throughput and biochemical approaches, which rely on large numbers of homogeneous cells.

Results

Primary cultures were established from embryos in which UAS-RasV12 expression was restricted to glial, tracheal epithelial, and mesodermal cells using lineage-specific Gal4 drivers (Table 1, Supplementary file 1). A subset of continuous cell lines derived from each type of primary culture was analyzed with regard to cell morphology, the presence of proteins characteristic of specific cell types, and other attributes (Table 1, Supplementary file 1, Supplementary file 2; Figure 1). We also analyzed lines with neuronal- or hemocyte-like characteristics that were cloned from parental lines resulting from ubiquitous expression of UAS-RasV12 (Table 1, Supplementary file 1, Supplementary file 2; Figure 1). We further analyzed the cell lines by RNAseq to determine the transcriptome and signaling pathways (Figure 2 and Figure 2—figure supplements 13). The gene expression values (Fragments Per Kilobase per Million mapped fragments, FKPM) are provided in Supplementary file 3. The dataset (Ras cell lines) has been imported into the Drosophila Gene Expression Tool (DGET) database (https://www.flyrnai.org/tools/dget/web/), which is the bulk RNAseq data portal at Drosophila RNAi Screening Center (DRSC) (Hu et al., 2017). The TM4 package was used for making the plot in Figure 2 (Wang et al., 2017). As expected, the transcriptomes of the new cell lines are distinct from those of existing cell lines (Cherbas et al., 2011; Figure 2—figure supplement 1) and new cell lines derived from the same Gal4 driver cluster with one another (Figure 2—figure supplement 2). Moreover, comparison of differentially expressed (DE) genes with RNAseq data from single-cell RNAseq data (Li et al., 2022; Table 2) or with known cell type-associated transcription factors (Figure 2—figure supplement 3) reveals that these cells express genes characteristic of specific cell types. The results of our detailed characterization are described according to cell type in the sections below.

Morphology of cells.

(A–C) Glial-lineage clones. The cells have an elongated morphology with variable lengths from approximately 20 to >50 µm (red arrowheads). (D–F) Tracheal-lineage cells. Btl3 and Btl7 cells form squamous epithelial sheets. Btl8 are closely associated but do not abut each other to form a sheet. (G–J) Mesodermal-lineage cells. The cells have a bipolar morphology. Multinucleate cells are frequently found in 24BGI-F3 and 24BG1-GI clones (red arrowheads). (K, L) Neuronal-like clones. ActGSB-6 cells are mainly bipolar; however, some have asymmetric processes or thin processes (red arrowheads). ActGSI-2 are bipolar. (M) Hemocyte-like clone ActGSI-3. The cells form floating clusters that increase in cell number as they proliferate. Individual cells have a round morphology. (N) Schneider’s S2 cells. The cells are thought to be of hemocyte type and grow as single round cells in suspension. Scale bar = 10 µm.

Figure 2 with 3 supplements see all
Expression levels of ligands and receptors for major signaling pathways.

The ligand and receptor annotation for major signaling pathways was obtained from FlyPhoneDB (https://www.flyrnai.org/tools/fly_phone/web/). The expression levels of ligands and receptors are represented as a heatmap of FPKM values.

Table 1
Cell lines analyzed.
Tissue-type alignmentGenotypeLines analyzed*DGRC stock name and numberRRID
GlialRepo-Gal4; RasV12; bratdsRNARbr6 (parental)
Rbr6-2
Rbr6-4
Rbr6-F9
repo>Ras bratdsRNA-L6, 282
repo>Ras bratdsRNA-L6-Clone2, 326
repo>Ras bratdsRNA-L6-Clone4, 327
repo>Ras bratdsRNA-L6-CloneF9, 328
RRID:CVCL_XF57
RRID:CVCL_C7G9
RRID:CVCL_C7GA
RRID:CVCL_C7GB
Epithelialbtl-Gal4; UAS-P35; UAS-RasV12Btl3 (parental)btl>Ras attP-L3, 332RRID:CVCL_B3N7
btl-Gal4; UAS-P35; attP, UAS-RasV12Btl7 (parental)
Btl8 (parental)
btl>Ras attP-L7, 285
btl>Ras attP-L8, 286
RRID:CVCL_XF53
RRID:CVCL_XF54
Muscle24B-Gal4; attP, UAS-RasV1224B5 (parental)
24B5-B8
24B5-D8
24B>Ras attP-L5, 284
24B>Ras attP-L5-CloneB8, 323
RRID:CVCL_XF52
RRID:CVCL_C7G6
24B-Gal4; UAS-GFP; attP, UAS-RasV1224BG1 (parental)
24BG1-F3
24BG1-G1
24B>Ras attP GFP-L1, 283
24B>Ras attP-G1-CloneF3, 325
24B>Ras attP-G1-CloneG1, 324
RRID:CVCL_XF51
RRID:CVCL_C7G8
RRID:CVCL_C7G7
NeuronalAct5C-GeneSwitch-Gal4; UAS-GFP; attP, UAS-RasV12ActGSB-6
ActGSI-2
Act5C-GS>Ras attP-LB-Clone6, 329
Act5C-GS>Ras attP-GFP-LI-Clone2, 330
RRID:CVCL_C7GC
RRID:CVCL_C7GD
BloodAct5C-GeneSwitch-Gal4; UAS-GFP; attP, UAS-RasV12ActGSI-3Act5C-GS>Ras attP-GFP-LI-Clone3, 331RRID:CVCL_C7GE
  1. *

    Clones unless indicated.

  2. Do not differentiate into active muscle.

  3. These cells do not express GFP, the reason for this is not known.

Table 2
RNAseq data analysis.
Tissue typeCell lineCell cluster scRNAseqEnrichment p value scRNAseqscRNAseq datasetCell type based on in situ dataEnrichment p value in situ
GlialRbr6-2Adult reticular neuropil-associated glial cell8.13E−05Whole bodyGlia4.84E−05
Rbr6-4Cell body glial cell7.56E−04Whole body
Rbr6-F9Adult glial cell8.13E−05Whole bodyGlia3.42E−02
EpithelialBtl3Adult tracheal cell2.61E−06Whole bodyTracheal1.08E−01
Btl7Adult tracheal cell8.81E−04Oenocyte
Btl8Adult tracheal cell2.72E−02BodyTracheal2.05E−02
Muscle24B5-B8Muscle cell2.93E−6Male reprod glands
24BG1-F3Muscle cell1.66E−04Antenna
24BG1-G1Muscle8.83E−02
NeuronalActGSI-2leg muscle motor neuron system5.79E−03Whole bodyNeuron6.68E−02
ActGSB-6adult ventral nervous7.56E−04Whole bodyNeuron5.71E−02
BloodActGSI-3hemocyte1.00E−25Whole bodyCirculatory system1.29E−01
  1. Analysis using the Drosophila RNAi Screening Center’s single-cell DataBase (DRscDB), all datasets used are from FCA 10x Sequencing (https://flycellatlas.org/). The in situ data were from the BDGP (https://insitu.fruitfly.org/cgi-bin/ex/insitu.pl) and the enrichment p value was calculated by a hypergeometric test.

Glial-lineage cell lines

Repo is expressed exclusively in glial cells (Xiong et al., 1994). A repo-Gal4 driver that recapitulates Repo expression was used to express UAS-RasV12 (Ogienko et al., 2020; Sepp et al., 2001). This led to robust production of primary cultures however these failed to survive beyond early passages (Supplementary file 1). To counter potential cell death or modulate growth signaling, additional genotypes were tested including co-expression of UAS-transgenes encoding the P35 baculovirus cell survival factor, dsRNAs targeting tumor suppressors, or the Gal4 inhibitor Gal80ts (Supplementary file 1). Co-expression of a UAS-bratdsRNA or expression of tub-Gal80ts each produced a single line of cells that could be propagated for extended passages however the latter line was difficult to maintain and eventually lost (Supplementary file 1). The repo-Gal4: UAS-bratdsRNA; UAS-RasV12 (Rbr6) line has been passaged more than 50 times. The parental Rbr6 line and three clonal derivatives (Rbr6-2, Rbr6-4, and Rbr6-F9) have an elongated morphology and stained positive for Repo (Table 1; Figures 1 and 3, and Figure 3—figure supplement 1). A few cells expressed neuronal markers (Figure 3—figure supplement 1; Supplementary file 2). To induce differentiation, we gave cells two 24 hr ecdysone treatments separated by 24 hr to approximate the pulses of ecdysone during the larval to pupal transition. Cells from each of the clones survived treatment with ecdysone suggesting they are of adult type, two clones showed morphological changes and formed a network, and all continued to express Repo (Figure 3 and Figure 3—figure supplement 2).

Figure 3 with 3 supplements see all
Glial clone Rbr6-2 cells express Repo.

Cells were grown in plain medium (A, C) or treated with ecdysone (B, D). (A, B) After ecdysone treatment, cells make a lace-like network. (C, D) Cells express Repo with or without ecdysone treatment. Inset: DAPI (4′,6-diamidino-2-phenylindole), DNA.

The results of RNAseq analysis revealed that the three Rbr6 clones have very similar expression patterns (Figure 2—figure supplement 2). In addition, their DE gene signatures are also a close match to gene signatures of glial cells as identified by single-cell RNAseq (Table 2) and to glial-associated genes reported in the literature. For example, zydeco (zyd), which encodes a potassium-dependent sodium/calcium exchanger, is upregulated in all three clones, consistent with the literature (Zwarts et al., 2015; Featherstone, 2011), and gcm2, a transcription factor, is upregulated in two clones (Figure 2—figure supplement 3). These data suggest the Rbr6 clones will be a useful in vitro source of glial cells.

Tracheal epithelium-lineage cell lines

Breathless is expressed in the tracheal epithelium and a btl-Gal4 driver was used to express UAS-RasV12 (Shiga et al., 1996). Patches of cells with epithelial morphology proliferated in primary cultures and several continuous lines were generated (Table 1, Supplementary file 1). We were unable to derive clones of these using dilution or selection methods, which were successful for other cell types. Correspondingly, three parental lines were examined: Btl3, Btl7, and Btl8 (Table 1). All showed expression of the epithelial marker Shotgun/E-Cadherin (Shg/Ecad) and two grew in a squamous epithelial sheet with Ecad expression at the cell periphery (Figures 1 and 4, and Figure 4—figure supplement 1). In comparison S2 did not show peripheral expression of Ecad (Figure 4). Treatment of the squamous epithelial cells (Btl3 and Btl7) with ecdysone caused aggregation and formation of large multicellular clusters (Figure 4, Figure 4—figure supplement 2).

Figure 4 with 3 supplements see all
Tracheal-lineage cells of line Btl3 express the epithelial cadherin Ecad/Shotgun.

All panels show Btl3 cells except (B) that shows S2 cells. Cells were grown in plain medium (A–C, E) or treated with ecdysone (D, F). (A) Btl3 cells form a squamous epithelial sheet and express Ecad/Shotgun at cell peripheries. (B) S2 cells grow as single cells and Ecad expression is diffuse. (C) Btl3 cells form a sheet with small cell clusters and expressed Ecad at the cell boundaries (E). (D) Ecdysone-treated cells form large multicellular clusters that expressed Ecad (F). Insets in E and F show nuclei with DAPI.

RNAseq data analysis comparing the top upregulated genes in the Btl cell lines with scRNAseq datasets revealed that the lines closely match the signatures of the adult trachea, a network of epithelial tubules (Table 2) and Btl3 expresses trachealess (trh) a master regulator of tracheal identity (Wilk et al., 1996; Figure 2—figure supplement 3). Overall, the morphological and molecular characteristics of the lines are consistent with an epithelial cell type of tracheal origin.

Mesodermal-lineage cell lines

The 24B-Gal4 driver is an insertion in held out wings (how) and is expressed in mesoderm and muscle cells (Brand and Perrimon, 1993; Zaffran et al., 1997). Expression of UAS-RasV12 with 24B-Gal4 readily produced continuous lines (Table 1, Supplementary file 1). Four clones (24B5-B8, 24B5-D8, 24BG1-F3, and 24BG1-G1) derived from two parental lines (24B5 and 25BG1) were analyzed in more detail (Table 1). The cells had a bipolar shape and expressed mesoderm markers including Twist and Mef2 (Figures 1 and 5, and Figure 5—figure supplement 1). When treated with ecdysone, cells from both parental lines and clones 24B5-B8 and 24B5-D8 elongated, fused as indicated by multinucleate cells, formed a network, and expressed Myosin heavy chain (Mhc) (Figure 5 and Figure 5—figure supplement 2). There was also extensive cell lysis. Beginning 2 days after the second ecdysone treatment, the cells began to contract spontaneously. Contraction of cells from the 24B5 parental line and the two derivative clones (24B5-B8 and 24B5-D8) was visible in real time (Videos 1 and 2), whereas contraction of parental line 24BG1 cells was much slower and visualized more clearly in time-lapse (Videos 3 and 4). The clones 24BG1-F3 and 24BG1-G1 underwent morphological change but did not express Mhc or contract (Figure 5—figure supplements 2 and 3). In later passages, the 24BG1 parental line also lost expression of Mhc and the ability to contract (Figure 5—figure supplement 2). This highlights the importance of using early passage cells and avoiding extended passaging that could alter the phenotypic (and genotypic) characteristics of the cells.

Video 1
24B-Gal4B5-B8 cells contract spontaneously after differentiation with ecdysone.
Video 2
24B-Gal4B5-B8 cells contract spontaneously after differentiation with ecdysone.
Figure 5 with 5 supplements see all
Mesodermal-lineage cells of Clone 24B5-B8 express Myosin heavy chain after differentiation.

Cells were grown in plain medium (A, C) or treated with ecdysone (B, D–F). (A) Cells have a bipolar shape. (B) Ecdysone-treated cells elongate and contract. (C) Control cells do not express Mhc. (D) Ecdysone-treated cells express the muscle marker Mhc. Inset: DAPI, DNA. (E, F) Differentiated 24B5-B8 fuse to form muscle fibers that contain multiple nuclei (white arrowheads), some differentiate without fusing with other cells and have single nucleus (blue arrowhead), and some fail to differentiate and remain spherical with a single nucleus (red arrowhead).

Video 3
24B-Gal4GI cells contract spontaneously after differentiation with ecdysone.

Time-lapse video, view looping.

Video 4
24B-Gal4GI cells contract spontaneously after differentiation with ecdysone.

Time-lapse video, view looping.

We also attempted to derive lines from Mef2-Gal4 because Mef2 regulates muscle development and is expressed in muscle progenitors and differentiated muscle suggesting Mef2-Gal4 would be a good candidate for deriving cell lines (Bour et al., 1995; Gossett et al., 1989; Lilly et al., 1995; Ranganayakulu et al., 1995). However, only rare primary cultures had some proliferating cell patches, and none progressed to continuous lines (Supplementary file 1; Figure 5—figure supplement 4). Analysis of larvae from the cross (Mef2-Gal4/+; UAS-GFP/UAS-RasV12) and control larvae (Mef2-Gal4/+; UAS-GFP/+) showed that RasV12 expression disrupted muscle development, suggesting that the prevalent amorphous GFP-positive cells observed in primary cultures were abnormal muscle cells (Figure 5—figure supplement 4).

The RNAseq analysis for 24B-Gal4-derived cell lines, identified the cells as muscle (Table 2). 24B5-B8 cells express high levels of the transcription factors nautilus (nau) and twist (twi) (Figure 2—figure supplement 3; Figure 5—figure supplement 1; Table 2), and high levels of myoblast city (mbo), which encodes an unconventional bipartite GEF with a role in myoblast fusion (Erickson et al., 1997). The capacity of these mesoderm-derived cell lines to differentiate into active muscle shows that the cells are muscle precursors and thus should be a useful reagent to analyze muscle physiology and development.

Neuronal-like cell lines

To target neuronal cells, we expressed UAS-RasV12 with the pan-neural drivers scratch-Gal4 and elav-Gal4, however none of the primary cultures resulted in continuous cell lines (Supplementary file 1; Figure 6—figure supplement 1). In previous work, we made primary cultures from embryos with ubiquitous expression of UAS-RasV12 using the Act5C-Gal4 driver (Simcox et al., 2008b). The cells growing in these cultures included neuronal cells (Simcox et al., 2008b). Here, we used an Act5C-GeneSwitch-Gal4 driver to express UAS-RasV12. GeneSwitch-Gal4 is only active in the presence of the drug, RU486/mifepristone, which provides the advantage of being able to regulate RasV12 expression (Nicholson et al., 2008; Osterwalder et al., 2001). Several continuous lines were generated (Supplementary file 1). Clones derived from two of these (ActGSB-6 and ActGSI-2) (Table 1) were positive for the neuronal marker, HRP (horseradish peroxidase) (Figure 6, Figure 6—figure supplements 2 and 3). After differentiation with ecdysone, expression of Futsch/MAPB1 (Hummel et al., 2000) and Fas2 (Mao and Freeman, 2009) was enhanced and revealed axonal-like outgrowths from the cells (Figure 6 and Figure 6—figure supplement 3). Differentiated cells also showed enhanced expression of Elav, which is commonly used as a marker for postmitotic neurons (Figure 6 and Figure 6—figure supplement 3; Robinow and White, 1991). Elav is also expressed transiently in glial cells and proliferating neuroblasts Berger et al., 2007; however, the cells were negative for the glial marker Repo (Supplementary file 2).

Figure 6 with 4 supplements see all
Neuronal-like clone ActGSI-2 expresses neuronal markers.

ActGSI-2 cells were grown in three conditions: RU486 (A, D, G, J, M); RU486 and ecdysone (B, E, H, K, N), or with no additives (C, F, I, L, O). RU486/mifepristone is required for GeneSwtch-Gal4 activation, transgene expression, and cell proliferation. (A) In the growing condition, cells reach confluence and continue to grow by piling up. (B) After ecdysone treatment cells elongated and developed axonal-like outgrowths. (C) In the quiescent state (no RU), cells do not proliferate and fail to reach confluence. (D–F) Cells in all conditions are positive for HRP. (G–I) Expression of Elav, is elevated after ecdysone treatment (H). (J–L) Expression of Futsch/MAP1B-like protein (recognized by antibody 22C10) is elevated after ecdysone treatment (K). (M–O) Fas2 neural-adhesion protein. Cells show elevated expression after ecdysone treatment (N). Insets: DAPI, DNA.

RNAseq analysis revealed that many neuronal genes are upregulated in these cell lines, including Glutamic acid decarboxylase 1 (Gad1), slowpoke (slo), 5-hydroxytryptamine (serotonin) receptor 1A (5-HT1A), Protein C kinase 53E (Pkc53E), Diuretic hormone 31 Receptor (Dh31-R), and straightjacket (stj). In addition, comparison of the top upregulated genes in these cells to marker genes from scRNAseq data identifies a cell type of neuronal origin as the best match (Table 2). The cells should be a useful source of neuronal cells.

Hemocyte-like cell line

Cells of clone ActGSI-3 derived from the ActGSI parental line (UAS-RasV12 expression with Act5C-GeneSwitch-Gal4; Table 1, Supplementary file 1) show characteristics of hemocytes and express the hemocyte marker Hemese (Figure 7; Kurucz et al., 2003). They are also positive for HRP, but not other neuronal markers (Figure 7—figure supplement 1). ActGSI-3 cells divide in floating clusters, contrasting with S2 cells, which are also thought to be hemocytes, that grow as single cells (Figures 1 and 7).

Figure 7 with 2 supplements see all
Hemocyte-like Clone ActGSI-3 morphology and marker expression.

Cells were grown in three conditions: RU486 (A, D); RU486 and ecdysone (B, E), or with no additives (C, F). (A) In the growing condition, cells formed floating clusters of multiple cells. (B) After ecdysone treatment cells formed large aggregates and there was cell lysis. (C) In the quiescent state (no RU), individual round cells are seen. (D–F) Cells in all conditions express the hemocyte cell marker Hemese, as recognized by the antibody H2. Inset: DAPI, DNA.

RNAseq analysis demonstrated that many hemocyte genes are upregulated in these cells, including serpent (srp), Hemese (He), eater, u-shaped (ush), Cecropin A2 (CecA2), and Cecropin C (CecC). Comparison of top upregulated genes with scRNAseq data showed that the cells have a strong match to the top marker genes of hemocytes (Table 2).

Growth, karyotype, and transfection efficiency of cell lines

We determined the cell density at confluence for the cell lines (Table 3). The cells in each line grow to confluence attached to the tissue-culture surface, except ActGSI-3, which grow as floating cell clusters (Figure 8). The cells are not contact inhibited and cell clusters are formed allowing cells to grow to higher density (Figure 8). We determined the doubling time of 13 cell lines and clones using growth curves (Table 3; Figure 8—figure supplement 1). Most had doubling times within a range of approximately 20–40 hr (Table 3). The hemocyte-like clone ActGSI-3 was an outlier with a longer doubling time of 70 hr (Table 3). In cells from clones ActGSB-6, ActGSI-2, and ActGSI-3, expression of RasV12 is dependent on GeneSwitch Gal4, which is active only in the presence of mifepristone. In the absence of the drug the cells become quiescent (Figure 8—figure supplement 1).

Figure 8 with 1 supplement see all
Morphology of confluent cultures.

(A–C) Glial-lineage clones. The cells grow in dense sheets and ridges with swirl patterns. (D–F) Tracheal-lineage cells. Btl3 and Btl7 cells form squamous epithelial sheets with raised clusters of cells. Btl8 grow densely however individual cells remain separate. (G–J) Mesodermal-lineage cells. The cells grow densely, and form raised clusters. (K, L) Neuronal-like clones. ActGSB-6 cells grow densely and form peaks and valleys. ActGSI-2 cells grow densely with scattered raised clusters. (M) Hemocyte-like clone ActGSI-3. The cells form floating clusters that coalesce into large cell rafts. (N) Schneider’s S2 cells. The cells grow to high density in suspension. Scale bar = 200 µm.

Table 3
Confluent density, growth, karyotype, and transfection efficiency of cell lines.
Tissue typeLineConfluent density (×106)*Doubling time (hr)KaryotypeTransfection efficiency (%)
GlialRbr6-21.8208, XY24
Rbr6-42.4208, XY28
Rbr6-F93.4198, XY22
EpithelialBtl33.7337, XY, –426
Btl72.637Abnormal tetraploid, XX, variable 434
Btl82.722Abnormal tetraploid, XX, –416
Mesodermal24B5-B81.429Abnormal tetraploid, XXY, variable 423
24B5-D85.123Abnormal tetraploid, XX, variable 427
24BG1-G12.8218, XY (some –4)ND
24BG1-F32.7358, XY (some –4)ND
NeuronalActGSB-62.9237, XO29
ActGSI-28.1278, XXND
BloodActGSI-31.970Abnormal tetraploid, XX, variable 4ND
S26.2NDND53
  1. *

    Confluent density in one well of a 12-well plate, 3.5 cm2 surface area (average of three wells).

We determined the gross karyotype of 13 cell lines and clones. In keeping with previous findings for RasV12 expressing cell lines, most (8) were diploid, or near diploid (Simcox et al., 2008b; Table 3; Figure 3—figure supplement 3; Figure 4—figure supplement 3; Figure 5—figure supplement 5; Figure 6—figure supplement 4; Figure 7—figure supplement 2). Related clones had similar karyotypes, which likely indicates that parental lines may also be clonal as a result of selective pressure for cells that grow well in culture. Some lines were polyploid and common aneuploid conditions include loss of an X chromosome and varying numbers of chromosome 4 (Table 3).

Nine parental and clonal lines were transfected with an Act5C-EGFP plasmid and the fraction of GFP-positive cells was determined after 48 hr. Cells from all lines tested could be transfected. The range of efficiency was from 16% to 34% with most lines showing transfection of approximately one quarter of the cells (Table 3). Similarly treated, cells from the S2 line showed an efficiency of 53%.

Discussion

Expressing activated Ras, RasV12, in primary cells provides a growth and survival advantage and leads to the rapid and reliable generation of continuous cell lines—the so-called Ras method (Simcox et al., 2008b). In a second-generation version of the Ras method, we found that restricting RasV12 expression with lineage-specific Gal4 drivers gave the targeted cells a competitive advantage and produced continuous lines with expected cell-type-specific phenotypes. With this approach we produced glial, epithelial, and muscle cell lines using the repo-, btl-, and 24B/how-Gal4 drivers, respectively.

In theory, the approach could be used to produce cell lines corresponding to any cell type for which there is an appropriate Gal4 driver. We tried to derive lines with Mef2-Gal4, a muscle master regulator gene, and the pan-neuronal driver elav-Gal4; however, no continuous lines were produced (Supplementary file 1; Figure 5—figure supplement 4 and Figure 6—figure supplement 1). In both cases, RasV12 expression appeared to disrupt growth of the targeted cell type. In the case of the muscle lineage, 24B/how-Gal4 was efficient at producing cell lines. The success with one and not the other muscle driver shows that in practice, it may be necessary to test multiple Gal4 lines for a given lineage. Drivers with very specific expression patterns may prove useful, including those generated by the Split Gal4 system (Luan et al., 2006). As with any tissue-culture system, the unnatural conditions of growing in vitro may select for ‘generic’ cells that survive well in culture and lose their lineage identities. This means that characterizing cell lines after generation for a battery of features (morphological, physiological, and molecular) is an essential step in assessing whether cells represent the tissue of origin expected for a given Gal4 driver.

repo-Gal4 is a pan-glial driver and many primary cultures expressing RasV12 with this driver reached confluence and could be passaged several times but did not produce continuous lines (Supplementary file 1). We tested different genotypes to determine if the success rate could be improved by modulation of RasV12 expression (co-expression of the Gal4 inhibitor Gal80ts), co-expression of the p35 baculovirus survival factor, or growth stimulation by downregulation of tumor suppressors (dsRNA for warts or brat). One line, also harboring a Gal80ts transgene, reached passage 25; however, the line was unstable and in early passages the cells variably lost Repo expression and changed morphologically. The one continuous glial line generated expresses a transgene that targets the tumor suppressor, brat (repo-Gal4; UAS-RasV12; UAS-bratdsRNA). Given a single success, it is not clear if downregulation of brat contributed to derivation of the line. Moreover, there is no evidence that these genotypic variations enhanced cell line generation with other drivers, as primary cultures expressing RasV12 without modulation or a survival factor produced lines with similar success rates for the btl-Gal4 or 24B/how-Gal4 drivers (Supplementary file 1).

As with all types of tissue culture, best practices involve maintaining frozen aliquots of cell lines at relatively low passage numbers. Aliquots of cells from the lines and clones described here, on which RNAseq was performed, have been archived at similar passage numbers as those used for the RNAseq analysis. This will allow users to start experimentation with the lines in a known state. The importance of this is exemplified by line 24BG1, which lost the ability to contract and express the muscle protein Mhc after multiple passages (Figure 5—figure supplement 2).

The mesodermal, neuronal, and glial cells represent in vitro counterparts of the tissues of origin that can be used for studying development and physiology in an accessible and reproducible system. The mesodermal cells that differentiate into active muscle will allow investigation of muscle fusion, as the cells are multinucleate (Figure 5), as well as muscle physiology and function. For example, the cells contract spontaneously and in apparent waves (Videos 1 and 2); however, the mechanism for stimulation (if any) and regulation have not been investigated and may cast light on in vivo processes. Given a variety of cell types, it will also be interesting to examine cell form and function in co-cultures, for example, of glia and neurons.

The method and the cells will be useful for generating disease models. New lineage-specific lines could be generated in the desired mutant background by establishing primary cultures from embryos in which only the mutant genotype expresses RasV12 giving these cells a growth and survival advantage (Simcox et al., 2008a). Derivative lines should include those of the desired cell type and genotype. Alternatively, the existing cell lines could be edited using CRISPR, or insertion of transgenes using the attP site that most lines and clones contain (Supplementary file 1; Bateman et al., 2006; Manivannan et al., 2015).

The cells with epithelial morphology derived from the tracheal lineage (Btl3 and Btl7) will provide good models for investigating assay conditions that promote polarization and 3D cell interactions that could allow the cells to manifest a more complex tissue architecture. In keeping with this possibility, treating these cells with ecdysone to induce differentiation showed cell clumping suggestive of a multicellular structure (Figure 4—figure supplement 2).

RNAseq analysis of cells from the ActGSI-3 cell clone showed a striking similarity to hemocytes, and the cells may be a good model for studying immunity (Table 2). The cells lyse after ecdysone treatment suggesting they are of embryonic origin (Figure 7). The cells grow as floating cell clumps (Figures 1 and 7) that may recapitulate subepidermal clusters of sessile hemocytes of the larva (Leitão and Sucena, 2015; Márkus et al., 2009).

The most significantly upregulated marker genes in each cell line are significantly enriched for top marker genes from expected cell types based on the single-cell RNAseq data from Fly Cell Atlas in most cases. This indicates the potential value of these cell lines as corresponding in vitro models for studying these cell types. While the cells will prove to be valuable models, it should be noted that even those showing a clear differentiated phenotype exhibit unexpected patterns of gene expression. For example, some cells in the mesodermal clone, 24B5-B8, are positive for HRP (Figure 5—figure supplement 1; Supplementary file 2) and the two neuronal-like lines express a mesodermal marker, Twist (Figure 6—figure supplement 2; Supplementary file 2). This anomalous gene expression is likely to be an effect of Ras activation on downstream pathways and genes. Ras/MAPK has a key role in muscle cell determination (Buff et al., 1998; Carmena et al., 2002; Halfon et al., 2000) and activates downstream muscle determination genes. It will also be important to consider what genes are not expressed by a given cell line, for example, glial cell missing (gcm) is not differentially expressed in the three glial-lineage cell clones and gcm2 is differentially expressed in only two of the three clones. Further, trachealess (trh) is only differentially expressed in one of the three tracheal-lineage cell lines. Similarly, the muscle-specific transcription factors twist (twi), nautilus (nau), snail (sna), and Mef2 show variable expression in the muscle-lineage cell clones. It should also be noted that the expression patterns were determined for undifferentiated cells and expression levels could change after hormone exposure.

The cells will have value for both low- and high-throughput approaches, including genetic or compound screens for which screening in the relevant cell type will result in identifying targets that are more likely to be of physiological relevance. Most of the cells have an attP-flanked cassette (Table 1), which makes them amenable to insertion of transgenes such as reporters by Recombination Mediated Cassette Exchange (RMCE) (Bateman et al., 2006; Manivannan et al., 2015). Moreover, cells competent for RMCE can be modified by stable expression of Cas9 and then used for genome-wide CRISPR pooled screening. With this approach, a library of single guide RNAs (sgRNAs) are integrated at RMCE sites (Viswanatha et al., 2018; Viswanatha et al., 2019). This generates a pool of cells, each with a different sgRNA, that can be subjected to a screen assay. Results are identified by PCR amplification of inserted sgRNAs followed by next-generation sequencing to detect sgRNAs that are enriched or depleted in the experimental cell pool as compared with a control. To date, pooled CRISPR screens in Drosophila have only been performed in S2 cells, which have hemocyte-like features. The availability of new cell lines with muscle, glial, and epithelial characteristics will enable screens designed to interrogate biological processes specific to these cell types.

There are hundreds of Drosophila cell lines; however, the number corresponding to known cell types is low. This is due in part to the lack of a method for generating cell lines from specific tissues. We expect that the method described here, using restricted expression of RasV12, will be a tractable approach for investigators to generate lines of cell types of interest. Single-cell cloning followed by cell characterization (immunohistochemistry and RNAseq) also proved to be a useful method to identify cell-type-specific lines and this approach could identify additional valuable lines in the existing collection at the DGRC. In summary, we show that lineage-restricted Ras expression and cell cloning has produced a set of new cell lines that will be of immediate value for analyses in the five cell types they represent.

Materials and methods

Fly stocks

Request a detailed protocol

The following fly stocks were used to create primary cell lines: Gal4 drivers: 24B/how-Gal4, w[*]; P(w[+mW.hs]=GawB)how[24B] (BL 1767); repo-Gal4, P(GAL4)repo (BL 7415); btl-Gal4, P(GAL4-btl.S)3-2 (BL 78328); Act5C-GeneSwitch-Gal4, P(UAS-GFP.S65T)Myo31DF[T2]; P(Act5C(-FRT)GAL4.Switch.PR)3 (BL 9431). Transgenes: UAS-RasV12 (3), P(w[+mC]=UAS-Ras85D.V12)TL1 (BL 64195); UAS-RasV12 (2), P(w[+mC]=UAS-Ras85D.V12)2 (BL 64196); UAS-RasV12 with RMCE site (3), P(w[+mC]=UAS-Ras85D.V12)TL1, P(w[+mC]=attP.w[+].attP)JB89B (BL 64197); UAS-GFP nuclear, P(UAS-GFP.nls)14 (BL 4775); bratdsRNA, P(y[+t7.7] v[+t1.8]=TRiP.HMS01121)attP2 (BL 34646); UAS-p35 baculovirus death inhibitor, P(w[+mC]=UAS-p35.H)BH1 (BL 5072) and Gal80ts, w[*]; P(w[+mC]=tubP-GAL80[ts])20 (BL 7019).

Setting up primary cultures

Request a detailed protocol

This follows a detailed method, which has additional information (Simcox, 2013), except that no yeast paste is used on the egg collection plates. Yeast paste, even when sterilized, promotes contamination in the cultures. Crosses were made between the Gal-4 driver lines and UAS-RasV12 lines. Some RasV12 stocks had additional alleles as noted in Supplementary file 1. Approximately 200 males and 200 females of a cross were transferred into a laying cage, with a fluted Whatman 3MM paper insert to increase surface area, and eggs were collected using 60-mm Petri dishes containing egg laying medium. Egg collections were made during the day for 8 hr at room temperature or 16 hr overnight at 17°C. After collection, approximately 3 ml of TXN (NaCl [0.7%], Triton X [0.02%] in water) was added to the plate. Any hatched larvae, which rise to the surface, were removed and the unhatched embryos were dislodged using a large soft paint brush to gently release them from the surface. Embryos were tipped off with the liquid into a sieve. Additional rinsing and brushing were used to ensure most embryos were dislodged and collected in the sieve. After thorough rinsing of the embryos with TXN from a squirt bottle, the sieve was upended over a 15-ml Falcon tube and a stream of TXN was used to transfer the embryos into the tube. Once the embryos settled, the TXN was removed and replaced with 3 ml of 50% bleach (Clorox) in water. The tube was capped and inverted three to five times and subsequently the embryos were treated using sterile techniques. The embryos were allowed to settle at the bottom of the tube and the bleach was removed after 3–5 min. The bleach dechorionates and surface sterilizes the embryos. The embryos were rinsed 2× with 4 ml of sterile TXN and transferred to a fresh tube of TXN to minimize bleach contamination. After two additional TXN rinses the embryos were transferred to TXN in a 5-ml glass homogenizer (with Teflon pestle). Embryos were rinsed in 3 ml of water followed by a rinse in 1 ml of Schneider’s S2 medium (supplemented with 10% heat inactivated fetal bovine serum and 1× Pen-strep solution). Embryos tend to clump in the Schneider’s S2 medium and stick to the sides of the homogenizer and pipette and care is needed to remove the medium without disturbing the embryos. 3 ml of fresh Schneider’s S2 medium was added to the homogenizer and the embryos were disrupted by three gentle strokes with the pestle. Care was taken to minimize bubbles by not withdrawing the pestle beyond the surface of the liquid. The homogenate was allowed to settle for 2 min and the supernatant was transferred to a 15-ml Falcon tube leaving the large cell clumps and any whole embryos in the bottom of the homogenizer. 3 ml of fresh Schneider’s S2 medium was added to the homogenizer and three more strokes, with a twist at the bottom, were used to disrupt remaining tissue and embryos. The second homogenate was added to the Falcon tube. The tube was centrifuged in a benchtop centrifuge at 1400 × g. The supernatant was discarded, and the pellet was resuspended in 3-ml Schneider’s S2 medium and centrifugation step and washing with Schneider’s S2 medium was repeated twice more. The final pellet size was estimated and plated in 1 or more 12.5 cm2 T-flasks with 2–3 ml Schneider’s S2 medium. The number of flasks needed for a given pellet size can also be estimated from the volume of packed embryos with approximately 30 µl of packed embryos being sufficient for one flask.

Culture conditions for new cell lines

Request a detailed protocol

Cells were grown in 25 cm2 T-flasks at 25°C in Schneider’s S2 medium and were passaged at between 90% and full confluence (Figure 8) using trypsin to release cells from the tissue-culture surface. Trypsin is needed as cells in all the lines are adherent except ActGSI3 cells that float freely (Figures 1 and 8). Cells were pelleted and approximately 20–25% of the cells were plated in a new flask. Cells were checked using an inverted microscope approximately every 5 days. The medium was changed on cultures showing signs of poor cell health (extended processes, little growth). This was sometimes necessary for cell types that are more metabolically active and acidify the medium, including the mesodermal lines. Cells were passaged every 5–7 days. Cell freezing (Schneider’s S2 medium with 20% heat inactivated fetal bovine serum and 10% DMSO (Dimethyl sulfoxide)) was used to keep a supply of frozen aliquots so that cells with similar passage numbers were used in experiments.

Cell cloning

Request a detailed protocol

For puromycin selection, 2–6 × 105 cells in a 35-mM well were transfected with 0.4 µg of DNA encoding a puro resistance plasmid (pCoPURO, Addgene #17533) using Effectene Transfection Reagent (QIAGEN). After 24 hr, cells were selected with puromycin at 0.5–2.5 µg/ml for 5 days. After 2–4 weeks, colonies were isolated and expanded. For dilution cloning, cells were seeded into a 96-well plate at a concentration of 0.5–1 cell/well in 100 µl conditioned media (Housden et al., 2015).

Hormone treatment

Request a detailed protocol

To simulate the major pulse of ecdysone at the larval to pupal transition, cells were treated with two 24 hr doses of β-ecdysone (Sigma 5289-74-7) at 1 µg/ml separated by 24 hr in non-supplemented medium.

Immunohistochemistry

Request a detailed protocol

Cells were fixed with 4% paraformaldehyde (Electron Microscopy Sciences) for 15 min or 3.5% formaldehyde (Sigma) for 30 min at room temperature, and then rinsed twice with 0.1% Tween-20 in phosphate-buffered saline (PBS-T). Cells were permeabilized (0.2% Triton X-100 in PBS) for 10 min at room temperature. Cells were blocked (5% bovine serum albumin in PBS-T) for 30 min at room temperature and incubated with diluted primary antibodies overnight at 4°C. Cells were washed three times with PBS-T and incubated with diluted secondary antibodies in blocking buffer for 1 hr at room temperature or overnight at 4°C. Cells were washed three times with PBS-T and mounted in VectaShield with DAPI (Vector Laboratories). For the Dcad2 antibody, cells were fixed and processed as described in Oda et al., 1994. The following primary antibodies and dilutions were used: HRP (rabbit polyclonal, Jackson ImmunoResearch 323-005-021, 1:500), 22C10 (mouse monoclonal anti-Futsch, Developmental Studies Hybridoma Bank, DSHB, 1:100), ELAV (rat monoclonal, DSHB 7E8A10, 1:100), Repo (mouse monoclonal, DSHB 8D12, 1:100), FasII (mouse monoclonal, DSHB 1D4, 1:100), Twist (a gift from M. Levine, UC Berkeley, CA, guinea pig 1:500), MHC (mouse monoclonal, DSHB 3E8-3D3, 1:100), Dcad2 (rat monoclonal, DSHB, 1:100), and DMef2 (a gift from J. R. Jacobs [Vanderploeg et al., 2012], rabbit polyclonal, 1:500), H2 (mouse monoclonal, [Kurucz et al., 2003], 1:10). Cells were incubated with the following secondary antibodies at the indicated dilutions: Cy3-conjugated goat anti-mouse (Jackson ImmunoResearch 115-165-003, 1:1000), Cy3-conjugated goat anti-rat (Jackson ImmunoResearch 112-165-003, 1:1000), Cy3-conjugated goat anti-guinea pig (Jackson ImmunoResearch 106-165-003, 1:1000), Cy3-conjugated goat anti-rabbit (Jackson ImmunoResearch 111-165-045, 1:1000), and Alexa Fluor 488-conjugated donkey anti-rabbit (Invitrogen A-21206, 1:1000).

Growth curve analysis

Request a detailed protocol

1–2 × 105 cells were plated in a 12-well plate. Cells were counted from triplicate wells every 3 days over a 9-day period. Doubling time was calculated using log2 cell numbers (Roth, 2006).

Karyotype analysis

Request a detailed protocol

Cells were grown to 50–90% confluence and incubated with 0.05 µg/ml KaryoMAX (Gibco-Thermo Fisher 15212012) for 3–18 hr. Cells were processed for analysis using the method in Lee et al., 2014, which uses 0.5% sodium citrate as a hypotonic solution and a 3:1 ice cold mix of methanol and acetic acid as a fix. After dropping fixed cells, slides were air dried and mounted in VectaShield with DAPI (Vector Laboratories) and viewed with an Olympus BX41 microscope.

Transfection

Request a detailed protocol

Cells in a 6-well plate (approximately 70% confluent) were transfected with 0.4 µg of an Actin5C-EGFP plasmid (pAc5.1B-EGFP, Addgene #21181) using Effectene Transfection Reagent (QIAGEN). The fraction of GFP-positive cells was scored after 48 hr.

RNA extraction and RNAseq

Request a detailed protocol

Cell cultures were grown and expanded in their respective media. All cell lines were cultured in Schneiders Drosophila Medium (Gibco Cat # 21720001), supplemented with 10% fetal bovine serum (Cytiva Hyclone Cat SH30070.03). For Act5C-GS>Ras attP-GFP-LI-Clone 2, Act5C-GS>Ras attP-GFP-LI-Clone 3, and Act5C-GS>Ras attP-GFP-LB-Clone 6 cultures were grown in the same basal media supplemented with 10 nM of Mifepristone (Thermo Fisher Cat# H11001). Cultures were allowed to grow in T-25 flasks to become confluent before treatment with trypsin (Gibco Cat# 12604013) for 4 min to dislodge the cell monolayer from the growth surface. The cells were resuspended in 4 ml of their respective media and 1 ml of the cell suspension was collected for pelleting, followed by washing in 1× PBS, and then flash-freezing in liquid nitrogen. All cell samples were processed in triplicates.

Total RNA was isolated from the pellets using the TRIzol reagent (Life Technologies [Ambion], Cat#:15596018) as per the manufacturer’s instructions. The isolated total RNA was subjected to further purification using the RNeasy Mini Kit (QIAGEN, Cat#74104) and the RNA post-cleanup was eluted in RNase-free water. The eluted total RNA was confirmed to have a A260/A280 ratio >1.8 and RIN >7.

Upon passing the quality control parameters, Illumina TruSeq libraries were constructed using TruSeq stranded mRNA HT kit (Illumina, Cat# RS-122-2103). Paired end sequencing was performed on an Illumina NextSeq 500 with a 150-cycle high output kits (Illumina, Cat# FC-404-2002).

RNAseq data analysis

Request a detailed protocol

Raw data processing was performed using the STAR sequence aligner (https://github.com/alexdobin/STAR; Dobin et al., 2013). Reads were aligned to the Drosophila genome and featureCounts were used to get gene counts from all samples into a count matrix for downstream analysis. A principal component analysis plot was produced using heatmaply. FPKM values were calculated using fpkm(DEseq2) using gene length output by featureCounts. The reference genome used was FB2022_05, dmel_r6.48 (FlyBase) (Jenkins et al., 2022). Both raw sequencing reads and the count matrix were deposited in the NCBI Gene Expression Omnibus (GEO) database under the accession number GSE219105. The processed dataset has also been imported into DGET database for user to mine gene(s) of interest or search for genes with similar expression pattern (https://www.flyrnai.org/tools/dget/web/).

Each sample was compared against all other samples by using DESeq2 ( Love et al., 2014) to determine differentially expressed genes (DE calling). The set of top DE genes for each cell line was compared with the top 100 markers in single-cell RNAseq datasets corresponding to cell types in the Fly Cell Atlas 10× datasets (Li et al., 2022). Enrichment analysis was conducted using the DRscDB tool to identify the Fly Cell Atlas cell type that matched closely to each cell line (Hu et al., 2021). We also compared the DE genes with the genes identify in various tissues in embryo and larval based on in situ data (PMID: 24359758, 17645804, 12537577) and majority of the best matching tissues are consistent with the analysis using scRNAseq datasets (Table 2).

The RNAseq data for the cell lines described in this work were also compared with RNAseq datasets determined previously for 24 other Drosophila cell lines (Cherbas et al., 2011). The comparison was conducted by hierarchical clustering analysis using Pearson correlation coefficient scores. To survey the activities of major signaling pathways in the cell lines, we specifically selected the ligands and receptors annotated at FlyPhoneDB (PMID: 35100387) to plot their expression levels using heatmap.

Materials availability

Request a detailed protocol

All cell lines described here have been deposited to the Drosophila Genomics Resource Center (DGRC) at Indiana University. The lines are available for distribution to the research community.

Appendix 1

Appendix 1—key resources table
Reagent type (species) or resourceDesignationSource or referenceIdentifiersAdditional information
Genetic reagent (D. melanogaster)24B/how-Gal4Bloomington Drosophila Stock CenterStock # 1767;
FLYB:FBti0150063;
RRID:BDSC_1767
FlyBase symbol: P(w[+mW.hs]=GawB)how[24B]
Genetic reagent (D. melanogaster)repo-Gal4Bloomington Drosophila Stock CenterStock # 7415;
FLYB:FBti0018692; RRID:BDSC_7415
FlyBase symbol: P(GAL4)repo
Genetic reagent (D. melanogaster)btl-Gal4Bloomington Drosophila Stock CenterStock # 78328;
FLYB:FBti019793;
RRID:BDSC_78328
FlyBase symbol: P(GAL4-btl.S)3–2
Genetic reagent (D. melanogaster)Act5C-GeneSwitch-Gal4Bloomington Drosophila Stock CenterStock # 9431;
FLYB:FBti0003040,FBti0076553;
RRID:BDSC_9431
FlyBase symbol: P(UAS-GFP.S65T)Myo31DF[T2]; P(Act5C(-FRT)GAL4.Switch.PR)3
Genetic reagent (D. melanogaster)UAS-RasV12 (3)Bloomington Drosophila Stock CenterStock # 64195;
FLYB:FBti0012505; RRID:BDSC_64195
FlyBase symbol: P(w[+mC]=UAS-Ras85D.V12)TL1
Genetic reagent (D. melanogaster)UAS-RasV12 (2)Bloomington Drosophila Stock CenterStock # 64196;
FLYB:FBti0180323; RRID:BDSC_64196
FlyBase symbol: P(w[+mC]=UAS-Ras85D.V12)2
Genetic reagent (D. melanogaster)UAS-RasV12 with RMCE site (3)Bloomington Drosophila Stock CenterStock # 64197;
FLYB: FBti0012505, FBti0102080; RRID:BDSC_64197
FlyBase symbol: P(w[+mC]=UAS-Ras85D.V12)TL1, P(w[+mC]=attP.w[+].attP)JB89B
Genetic reagent (D. melanogaster)UAS-GFP nuclearBloomington Drosophila Stock CenterStock # 4775;
FLYB: FBti0012492;
RRID:BDSC_4775
FlyBase symbol: P(UAS-GFP.nls)14
Genetic reagent (D. melanogaster)bratdsRNABloomington Drosophila Stock CenterStock # 34646;
FLYB:FBti0140815; RRID:BDSC_34646
FlyBase symbol: P(y[+t7.7] v[+t1.8]=TRiP.HMS01121)attP2
Genetic reagent (D. melanogaster)UAS-p35 baculovirus death inhibitorBloomington Drosophila Stock CenterStock # 5072;
FLYB:FBti0012594; RRID:BDSC_5072
FlyBase symbol: P(w[+mC]=UAS-p35.H)BH1
Genetic reagent (D. melanogaster)Gal80tsBloomington Drosophila Stock CenterStock # 7019;
FLYB:FBti0027796; RRID:BDSC_7019
FlyBase symbol: P(w[+mC]=tubP-GAL80[ts])20
Cell line (D. melanogaster)S2Drosophila Genomics Resource CenterStock # 181; FLYB:FBtc0000181; RRID:CVCL_Z992Cell line maintained in N. Perrimon lab; FlyBase symbol: S2-DRSC.
Cell line (D. melanogaster)24B5-B8Drosophila Genomics Resource CenterStock # 323; RRID:CVCL_C7G624B>Ras attP-L5-CloneB8
Cell line (D. melanogaster)24BG1-G1Drosophila Genomics Resource CenterStock # 324; RRID:CVCL_C7G724B>Ras attP-G1-CloneG1
Cell line (D. melanogaster)24BG1-F3Drosophila Genomics Resource CenterStock # 325; RRID:CVCL_C7G824B>Ras attP-G1-CloneF3
Cell line (D. melanogaster)Rbr6-2Drosophila Genomics Resource CenterStock # 326; RRID:CVCL_C7G9repo>Ras bratdsRNA-L6-Clone2
Cell line (D. melanogaster)Rbr6-4Drosophila Genomics Resource CenterStock # 327; RRID:CVCL_C7GArepo>Ras bratdsRNA-L6-Clone4
Cell line (D. melanogaster)Rbr6-F9Drosophila Genomics Resource CenterStock # 328; RRID:CVCL_C7GBrepo>Ras bratdsRNA-L6-CloneF9
Cell line (D. melanogaster)ActGSI-2Drosophila Genomics Resource CenterStock # 329; RRID:CVCL_C7GCAct5C-GS>Ras attP-LB-Clone6
Cell line (D. melanogaster)ActGSI-2Drosophila Genomics Resource CenterStock # 330; RRID:CVCL_C7GDAct5C-GS>Ras attP-GFP-LI-Clone2
Cell line (D. melanogaster)ActGSI-3Drosophila Genomics Resource CenterStock # 331; RRID:CVCL_C7GEAct5C-GS>Ras attP-GFP-LI-Clone3
Cell line (D. melanogaster)Btl3Drosophila Genomics Resource CenterStock # 332; RRID:CVCL_B3N7btl>Ras attP-L3
Cell line (D. melanogaster)OK6-3Drosophila Genomics Resource CenterStock # 281;
RRID:CVCL_XF56
OK6>Ras attP-L3
Cell line (D. melanogaster)Rbr6Drosophila Genomics Resource CenterStock # 282; RRID:CVCL_XF57repo>Ras bratdsRNA-L6
Cell line (D. melanogaster)24BG1Drosophila Genomics Resource CenterStock # 283; RRID:CVCL_XF5124B>Ras attP GFP-L1
Cell line (D. melanogaster)24B5Drosophila Genomics Resource CenterStock # 284; RRID:CVCL_XF5224B>Ras attP-L5
Cell line (D. melanogaster)Btl7Drosophila Genomics Resource CenterStock # 285; RRID:CVCL_XF53btl>Ras attP-L7
Cell line (D. melanogaster)Btl8Drosophila Genomics Resource CenterStock # 286; RRID:CVCL_XF54btl>Ras attP-L8
Cell line (D. melanogaster)OK6-2Drosophila Genomics Resource CenterStock # 287;
RRID:CVCL_XF55
OK6>Ras attP-L2
cell line (E. coli)DH5-alphaThermo FisherCat. # 18265017Subcloning efficiency DH5-alpha competent cells
Transfected construct (D. melanogaster)pAc5.1B-EGFPAddgeneCat. # 21181; http://n2t.net/addgene:21181; RRID:Addgene_21181pAc5.1B-EGFP was a gift from Elisa Izaurralde
Transfected construct (D. melanogaster)pCoPUROAddgeneCat. # 17533; http://n2t.net/addgene:17533; RRID:Addgene_17533pCoPURO was a gift from Francis Castellino
AntibodyAffiniPure Rabbit Anti-Horseradish Peroxidase (Rabbit polyclonal)Jackson ImmunoResearchCat. # 323-005-021; RRID: AB_2314648Rabbit polyclonal; IF (1:500)
Antibody22C10 (mouse monoclonal)Developmental Studies Hybridoma BankCat. # 22C10
RRID: AB_528403. FBgn0259108
22C10 was deposited to the DSHB by Benzer, S./Colley, N.; mouse monoclonal; IF (1:100)
AntibodyRat-Elav-7E8A10 anti-elav (rat monoclonal)Developmental Studies Hybridoma BankCat. # Rat-Elav-7E8A10 anti-elav, RRID:AB_528218Rat-Elav-7E8A10 anti-elav was deposited to the DSHB by Rubin, G.M.; rat monoclonal; IF (1:100)
Antibody8D12 anti-Repo (mouse monoclonal)Developmental Studies Hybridoma BankCat. # 8D12 anti-Repo, RRID:AB_5284488D12 anti-Repo was deposited to the DSHB by Goodman, C.; mouse monoclonal; IF (1:100)
Antibody1D4 anti-Fasciclin II (mouse monoclonal)Developmental Studies Hybridoma BankCat. # 1D4 anti-Fasciclin II, RRID:AB_5282351D4 anti-Fasciclin II was deposited to the DSHB by Goodman, C.; mouse monoclonal; IF (1:100)
AntibodyGuinea pig anti-Twist (guinea pig polyclonal)M.Levine, UC Berkeley, CAA gift from M. Levine, UC Berkeley, CA; guinea pig polyclonal; IF (1:500)
Antibody3E8-3D3 (mouse monoclonal)Developmental Studies Hybridoma BankCat. # 3E8-3D3, RRID:AB_27219443E8-3D3 was deposited to the DSHB by Saide, J.D.; mouse monoclonal; IF (1:100)
AntibodyDCAD2 (rat monoclonal)Developmental Studies Hybridoma BankCat. # DCAD2, RRID:AB_528120DCAD2 was deposited to the DSHB by Uemura, T.; rat, monoclonal; IF (1:100)
AntibodyRabbit anti-DMef2 (rabbit polyclonal)doi:10.1101/gad.9.6.730A gift from J. R. Jacobs; rabbit polyclonal; IF (1:500)
AntibodyMouse anti-H2 (mouse monoclonal)doi:10.1073/pnas.0436940100Kurucz et al., 2003; IF (1:10)
AntibodyCy3 AffiniPure Goat Anti-Mouse IgG (H+L) (Goat polyclonal)Jackson ImmunoResearchCat. # 115-165-003; RRID: AB_2338680Goat polyclonal; IF (1:1000)
AntibodyCy3 AffiniPure Goat Anti-Rat IgG (H+L) (Goat polyclonal)Jackson ImmunoResearchCat. # 112-165-003; RRID: AB_2338240Goat polyclonal; IF (1:1000)
AntibodyCy3 AffiniPure Goat Anti-Guinea Pig IgG (H+L) (Goat polyclonal)Jackson ImmunoResearchCat. # 106-165-003; RRID: AB_2337423Goat polyclonal; IF (1:1000)
AntibodyCy3 AffiniPure Goat Anti-Rabbit IgG (H+L) (Goat polyclonal)Jackson ImmunoResearchCat. # 111-165-045; RRID: AB_2338003Goat polyclonal; IF (1:1000)
AntibodyDonkey anti-Rabbit IgG (H+L) Highly Cross-Adsorbed Secondary Antibody, Alexa Fluor 488 (donkey polyclonal)Thermo FisherCat. # A-21206; RRID: AB_2535792Donkey polyclonal; IF (1:1000)
Commercial assay or kitEffectene Transfection ReagentQIAGENCat. # 301425
Commercial assay or kitNucleoSpin Plasmid Kit (No Lid)Macherey-NagelCat. # 740499.250
Commercial assay or kitDNeasy Blood & Tissue KitQIAGENCat. # 69504
Chemical compound, drugKaryoMAX Colcemid Solution in PBSGibco Thermo FisherCat. # 15212–012
Chemical compound, drugSchneider′s Insect MediumSigma-AldrichCat. # S0146
Chemical compound, drugFBSGibco Thermo FisherCat. # 26140–079
Chemical compound, drug0.05% Trypsin–EDTA (1×)Gibco Thermo FisherCat. # 25300–120
Chemical compound, drugPenicillin–streptomycin (10,000 U/ml)Gibco Thermo FisherCat. # 15140122
Chemical compound, drugMifepristoneInvitrogen Thermo FisherCat. # H11001
Chemical compound, drug20-HydroxyecdysoneSigma-AldrichCat. # H5142
Chemical compound, drugVECTASHIELD Antifade Mounting Medium With DAPIVector LaboratoriesCat. # H1200
Software, algorithmGraphPad Prism version 9.5.1https://www.graphpad.com/RRID:SCR_002798
Software, algorithmFijidoi:10.1038/nmeth.2019RRID:SCR_002285

Data availability

Sequencing data have been deposited in GEO under accession code GSE219105.

The following data sets were generated
    1. Mariyappa D
    2. Luhur A
    3. Zelhof A
    4. Hu Y
    5. Simcox A
    (2022) NCBI Gene Expression Omnibus
    ID GSE219105. Continuous muscle, glial, epithelial, neuronal, and hemocyte cell lines for Drosophila research.

References

    1. Li H
    2. Janssens J
    3. De Waegeneer M
    4. Kolluru SS
    5. Davie K
    6. Gardeux V
    7. Saelens W
    8. David FPA
    9. Brbić M
    10. Spanier K
    11. Leskovec J
    12. McLaughlin CN
    13. Xie Q
    14. Jones RC
    15. Brueckner K
    16. Shim J
    17. Tattikota SG
    18. Schnorrer F
    19. Rust K
    20. Nystul TG
    21. Carvalho-Santos Z
    22. Ribeiro C
    23. Pal S
    24. Mahadevaraju S
    25. Przytycka TM
    26. Allen AM
    27. Goodwin SF
    28. Berry CW
    29. Fuller MT
    30. White-Cooper H
    31. Matunis EL
    32. DiNardo S
    33. Galenza A
    34. O’Brien LE
    35. Dow JAT
    36. FCA Consortium§
    37. Jasper H
    38. Oliver B
    39. Perrimon N
    40. Deplancke B
    41. Quake SR
    42. Luo L
    43. Aerts S
    44. Agarwal D
    45. Ahmed-Braimah Y
    46. Arbeitman M
    47. Ariss MM
    48. Augsburger J
    49. Ayush K
    50. Baker CC
    51. Banisch T
    52. Birker K
    53. Bodmer R
    54. Bolival B
    55. Brantley SE
    56. Brill JA
    57. Brown NC
    58. Buehner NA
    59. Cai XT
    60. Cardoso-Figueiredo R
    61. Casares F
    62. Chang A
    63. Clandinin TR
    64. Crasta S
    65. Desplan C
    66. Detweiler AM
    67. Dhakan DB
    68. Donà E
    69. Engert S
    70. Floc’hlay S
    71. George N
    72. González-Segarra AJ
    73. Groves AK
    74. Gumbin S
    75. Guo Y
    76. Harris DE
    77. Heifetz Y
    78. Holtz SL
    79. Horns F
    80. Hudry B
    81. Hung R-J
    82. Jan YN
    83. Jaszczak JS
    84. Jefferis GSXE
    85. Karkanias J
    86. Karr TL
    87. Katheder NS
    88. Kezos J
    89. Kim AA
    90. Kim SK
    91. Kockel L
    92. Konstantinides N
    93. Kornberg TB
    94. Krause HM
    95. Labott AT
    96. Laturney M
    97. Lehmann R
    98. Leinwand S
    99. Li J
    100. Li JSS
    101. Li K
    102. Li K
    103. Li L
    104. Li T
    105. Litovchenko M
    106. Liu H-H
    107. Liu Y
    108. Lu T-C
    109. Manning J
    110. Mase A
    111. Matera-Vatnick M
    112. Matias NR
    113. McDonough-Goldstein CE
    114. McGeever A
    115. McLachlan AD
    116. Moreno-Roman P
    117. Neff N
    118. Neville M
    119. Ngo S
    120. Nielsen T
    121. O’Brien CE
    122. Osumi-Sutherland D
    123. Özel MN
    124. Papatheodorou I
    125. Petkovic M
    126. Pilgrim C
    127. Pisco AO
    128. Reisenman C
    129. Sanders EN
    130. dos Santos G
    131. Scott K
    132. Sherlekar A
    133. Shiu P
    134. Sims D
    135. Sit RV
    136. Slaidina M
    137. Smith HE
    138. Sterne G
    139. Su Y-H
    140. Sutton D
    141. Tamayo M
    142. Tan M
    143. Tastekin I
    144. Treiber C
    145. Vacek D
    146. Vogler G
    147. Waddell S
    148. Wang W
    149. Wilson RI
    150. Wolfner MF
    151. Wong Y-CE
    152. Xie A
    153. Xu J
    154. Yamamoto S
    155. Yan J
    156. Yao Z
    157. Yoda K
    158. Zhu R
    159. Zinzen RP
    (2022) Fly Cell Atlas: A single-nucleus transcriptomic atlas of the adult fruit fly
    Science 375:eabk2432.
    https://doi.org/10.1126/science.abk2432
    1. Love M
    2. Anders S
    3. Huber W
    (2014) Deseq2
    Deseq2, 3.4, https://bioconductor.statistik.tu-dortmund.de/packages/3.4/bioc/html/DESeq2.html.
  1. Software
    1. Roth V
    (2006) Doubling Time
    Doubling Time Computing.
    1. Sato K
    2. Siomi MC
    (2020) The piRNA pathway in Drosophila ovarian germ and somatic cells
    Proceedings of the Japan Academy. Series B, Physical and Biological Sciences 96:32–42.
    https://doi.org/10.2183/pjab.96.003
    1. Zwarts L
    2. Van Eijs F
    3. Callaerts P
    (2015) Glia in Drosophila behavior
    Journal of Comparative Physiology. A, Neuroethology, Sensory, Neural, and Behavioral Physiology 201:879–893.
    https://doi.org/10.1007/s00359-014-0952-9

Decision letter

  1. Erika A Bach
    Reviewing Editor; New York University School of Medicine, United States
  2. Claude Desplan
    Senior Editor; New York University, United States
  3. Erika A Bach
    Reviewer; New York University School of Medicine, United States
  4. David Bilder
    Reviewer; University of California, Berkeley, United States

Our editorial process produces two outputs: (i) public reviews designed to be posted alongside the preprint for the benefit of readers; (ii) feedback on the manuscript for the authors, including requests for revisions, shown below. We also include an acceptance summary that explains what the editors found interesting or important about the work.

Decision letter after peer review:

Thank you for submitting your article "Continuous muscle, glial, epithelial, neuronal, and hemocyte cell lines for Drosophila research" for consideration by eLife. Your article has been reviewed by 3 peer reviewers, including Erika A Bach as the Reviewing Editor and Reviewer #1, and the evaluation has been overseen by Claude Desplan as the Senior Editor. The following individual involved in the review of your submission has agreed to reveal their identity: David Bilder (Reviewer #2).

The reviewers have discussed their reviews with one another, and the Reviewing Editor has drafted this to help you prepare a revised submission.

Essential revisions:

1. Increase the 'identity' of the cell lines

– Provide information and possibly new data to increase the utility of Table 2

– Provide information on what expected marker genes are NOT expressed in the new cell lines

– Compare the new lines to existing lines, especially the workhorse S2 cells.

– Provide information/commentary on growing in new cells line in large numbers or employing them in high-throughput screening.

2. Improve user access to genomics data. Downloading and accessing GEO files are not user-friendly. Genomic data should be accessible to the potential users of these cell lines.

– Provide tabular genome-wide data for each cell line.

– Consider generating a website with these data

3. Improve the images and figure legends

– Provide higher magnification views to support the conclusions.

– Figure 2: show Ecad staining on a non-epithelial cell line with comparable density.

– Figure 3D: show more clearly the multinucleate cells.

– Provide information on magnification for images.

4. Methods

– Mention how specific the GAL4 drivers are in embryos (possibly by providing real time expression, maybe using G-trace).

– Provide a detailed description of how the new cell lines were generated (rather than cite Simcox, 2013).

– Provide a detailed description of the culture conditions for the new cell lines.

– Provide reagent tables and RRIDs for all reagents

5. Improve karyotyping.

Reviewer #1 (Recommendations for the authors):

1. The authors should review their reference manager because not all of the references are cited in the same way. Most are last name comma first initial but A. Simcox is frequently cited.

2. Under the Methods section, the authors should provide a description of how they generated the cell lines (rather than cite Simcox, 2013).

3. Is it possible to put scale bars on the micrographs? If not, could the authors please state the magnification?

Reviewer #2 (Recommendations for the authors):

1) The critical assignment of the 'identity' of the cell lines would benefit from more detail and explanation. The process is a bit confusing. For instance, in Table 2, why is the dataset Whole body for some and a specific organ for others? In the latter case, why does Btl8 map to the oenocyte sample? On line 182, the authors say that the glial lines did not result in as clear a similarity as other lines, but that is not obvious from the values in Table 2. Is it possible/useful to compare the enrichment scores of Table 2 to those of well-characterized tissue-specific mammalian cell lines and their in vivo equivalents (say MDCK cells and renal tubule cells) for perspective?

2). Related, the paper would benefit from an explicit critical discussion of the cell lines. For instance, what expected marker genes are NOT expressed? E.g. the tracheal-derived cell lines L8 do not express trh, L7 downregulates trh. In what ways are these not simple immortalized cells of in vivo equivalents -that may be important for people thinking about using them? The authors' simple statements e.g. line 212 do a disservice to the nuances of identity.

3) The authors could make clear how these new lines compare to existing lines. For instance, S2 was generally thought to be hemocyte-like, how does it compare to Act GSI-3? What reason would researchers interested in hemocyte biology want to use one over the other? An example of this value is the comparison of transfection efficiency to S2 (line 237).

4) Any experience with growing in large numbers, or in high-throughput screening format? Since these are promoted as uses, it would be very helpful to have a perspective from the authors, who include those most experienced with the variety of existing cell lines and their use in these contexts.

Other points – not absolutely needed for accceptance

In general, the figures are rather sparse, there is room for more data such as those suggested above.

Any speculation as to why so many of the lines correlate with an adult, rather than embryonic, profiles when the tissue source was embryos?

Figure 2: would be nice to show Ecad staining on a non-epithelial cell line with comparable density.

Would be nice to mention how specific the GAL4 drivers are in embryos

The culture conditions for the cell lines, which is critical information, are buried in a section about 'RNA extraction'.

Figure 3D: would be nice to show more clearly the multinucleate cells.

For the lines where there was a failure to derive (e.g. Mef2; elav) -is it possible that the levels of active Ras were too high to be compatible with life and/or immortalization?

The new lines all group more closely with each other in Figure S1 than with any previous line, regardless of the supposed tissue represented. Presumably, this is due to an activated Ras expression signature. Or is their contribution from their more recent time of derivation, or their more similar genetic background? If you 'filter out' the generic Ras expression signature, does that help with the assignment of the cell type?

Discussion about the role of continuous Ras expression would be nice. Inspection of the figure legends 4C and 5C suggests that turning off GAL4 or Ras activity makes the cells quiescent, but explicit information about this, how long they can live in this state, whether there are obvious effects on differentiation, etc. would be useful.

Reviewer #3 (Recommendations for the authors):

The paper is clear and well-written, but I believe that the work needs to be extended to make it useful.

1) The RNAseq characterization is perhaps the most important and global aspect of the utility, because someone interested in a particular gene, could check to see if it was well expressed and in which of the novel (or existing) cell lines. I did not see tabular genome-wide data that would fit this bill. The expression data is basically not presented in the manuscript. The authors are used to presenting data to the community through the DGRC, DRSC, and FlyBase. They need to make these data easy to access. It is hard to judge the GEO submission as it is still listed as private.

2) The phase images are not sufficient to understand the cell biology nature of these cell lines. High magnification views that show higher content information on the cells are needed. It is nice to show the hormonally induced differentiation onset using one or a few markers, but for a resource, I would hope for more granularity. Again it is difficult to make choices of cell lines for experiments with this resolution.

3) Although I do not recall reading it explicitly, I assume that the chromosome spreads were scored based on chromosome size. This is not very satisfying in the era of chromosome paints and especially DNAseq (e.g. PMID: 25262759).

4) The figure legends should indicate what is being detected. "Expressed" is too vague.

5) Reagent tables are much easier to read than in-text methods with names and undescribed identifiers.

https://doi.org/10.7554/eLife.85814.sa1

Author response

Essential revisions:

1. Increase the 'identity' of the cell lines

– Provide information and possibly new data to increase the utility of Table 2

– Provide information on what expected marker genes are NOT expressed in the new cell lines

– Compare the new lines to existing lines, especially the workhorse S2 cells.

– Provide information/commentary on growing in new cells line in large numbers or employing them in high-throughput screening.

In Table 2, we have added the cell-type based on in situ data. This complements the single cell RNAseq and confirms the cell type identity.

We have added a section on transcription factors, not expressed in the new cell lines, which might be expected for that cell type. Also, we note that the RNAseq data is for undifferentiated cells and genes not expressed in the proliferative state may be expressed in differentiated cells. This is one reason why information on what is not expressed may not be definitive.

We have included figures that show the morphology of the cells, including S2 cells (Figures 1 and 8). These show that none of the new lines are similar to S2, including the hemocyte-like cell line ActGSI-3. While both S2 and ActGSI-3 cells are round and grow in suspension, S2 cells grow individually, whereas ActGSI-3 form large cell rafts.

In Table 3, we have added data about the confluent density of the cells. These numbers show that the cells can be grown to densities of 1.4-8.1 x 106 in a single well of a 12 well plate. In this experiment S2 cells grew to a confluent density of 6.2 X 106. As all cells, except ActGSI-3, are adherent, the cells are also potentially well suited for multi-well plate assays.

2. Improve user access to genomics data. Downloading and accessing GEO files are not user-friendly. Genomic data should be accessible to the potential users of these cell lines.

– Provide tabular genome-wide data for each cell line.

– Consider generating a website with these data

We added a supplementary table (Table S3) with genome-wide expression levels for each gene in each cell line (Fragments Per Kilobase per Million mapped fragments, FPKM).

The dataset has been imported into the Drosophila Gene Expression Tool (DGET) database (https://www.flyrnai.org/tools/dget/web/), which is the bulk RNAseq data portal at Drosophila RNAi Screening Center (DRSC). DGET can be used to query the expression levels for the genes of interest as well as search the genes with similar expression pattern for any input gene. The expression dataset is called “Ras cell lines”.

3. Improve the images and figure legends

– Provide higher magnification views to support the conclusions.

– Figure 2: show Ecad staining on a non-epithelial cell line with comparable density.

– Figure 3D: show more clearly the multinucleate cells.

– Provide information on magnification for images.

The new Figure 1 shows the cells at high magnification. This was a very useful suggestion because it allows comparison of cell morphologies within and between lineages. For example, the glial cells have a long spindle-like shape, and the epithelial cells are cuboidal.

Figure 6 shows Btl3 and S2 cells stained for the epithelial marker E-Cadherin/Shotgun. Btl3 cells expressed Ecad at the cell periphery and S2 cells had low level cytoplasmic expression.

New panels in Figure 5 show the multinucleate muscle cells.

Scale bars are included in Figures 1 and 8, which show phase images of the cells.

4. Methods

– Mention how specific the GAL4 drivers are in embryos (possibly by providing real time expression, maybe using G-trace).

– Provide a detailed description of how the new cell lines were generated (rather than cite Simcox, 2013).

– Provide a detailed description of the culture conditions for the new cell lines.

– Provide reagent tables and RRIDs for all reagents

We find that additional factors other than specificity of expression of Gal4 are necessary for successful cell line development. This is illustrated for the muscle lineage where we tested two well characterized drivers—Mef2-Gal4 and 24B/how-Gal4. Only 24B/how-Gal4 produced continuous cell lines. In a new figure we show that RasV12 expression with Mef2-Gal4 in muscle cells disrupted muscle development and that in primary cultures the RasV12-expressing cells (marked with GFP) failed to attach and grow (Figure 5—figure supplement 4). We. Do not the know the basis for this; however, expression level is a possibility. Even after successful cell line generation it is important to use a battery of assays to determine lineage characteristics because cells change as they adapt for survival in vitro. This is exemplified by some of the 24B-Gal4 derived lines that failed to differentiate after extended passages.

A detailed primary culture procedure is provided in the Methods section.

Culture conditions and passaging regimes for the new cell lines are provided in the Methods section. This method also refers to Figure 8, which shows the cells at confluence and will help users determine when cells are ready for sub-culturing (passaging).

All reagents and RRIDs (when available) are provided.

5. Improve karyotyping.

We redid the karyotypes for all the cell lines and include karyograms for each. The quality is greatly improved and equivalent to the standard for the field. The figures showing the karyotypes and the chromosomes ordered in a karyogram appear in supplemental figures for each cell line and the refined karyotypes are summarized in the revised Table 3.

https://doi.org/10.7554/eLife.85814.sa2

Article and author information

Author details

  1. Nikki Coleman-Gosser

    Department of Molecular Genetics, Ohio State University, Columbus, United States
    Contribution
    Formal analysis, Investigation, Writing – review and editing
    Contributed equally with
    Yanhui Hu, Shiva Raghuvanshi and Shane Stitzinger
    Competing interests
    No competing interests declared
  2. Yanhui Hu

    Drosophila RNAi Screening Center and Department of Genetics, Harvard Medical School, Boston, United States
    Contribution
    Formal analysis, Writing – review and editing
    Contributed equally with
    Nikki Coleman-Gosser, Shiva Raghuvanshi and Shane Stitzinger
    Competing interests
    No competing interests declared
  3. Shiva Raghuvanshi

    Department of Molecular Genetics, Ohio State University, Columbus, United States
    Contribution
    Investigation
    Contributed equally with
    Nikki Coleman-Gosser, Yanhui Hu and Shane Stitzinger
    Competing interests
    No competing interests declared
  4. Shane Stitzinger

    Department of Molecular Genetics, Ohio State University, Columbus, United States
    Contribution
    Formal analysis, Investigation, Writing – review and editing
    Contributed equally with
    Nikki Coleman-Gosser, Yanhui Hu and Shiva Raghuvanshi
    Competing interests
    No competing interests declared
  5. Weihang Chen

    Drosophila RNAi Screening Center and Department of Genetics, Harvard Medical School, Boston, United States
    Contribution
    Formal analysis
    Competing interests
    No competing interests declared
  6. Arthur Luhur

    Drosophila Genomics Resource Center and Department of Biology, Indiana University, Bloomington, United States
    Contribution
    Investigation, Writing – review and editing
    Competing interests
    No competing interests declared
  7. Daniel Mariyappa

    Drosophila Genomics Resource Center and Department of Biology, Indiana University, Bloomington, United States
    Contribution
    Investigation, Writing – review and editing
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4775-1656
  8. Molly Josifov

    Department of Molecular Genetics, Ohio State University, Columbus, United States
    Contribution
    Investigation
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-2899-7186
  9. Andrew Zelhof

    Drosophila Genomics Resource Center and Department of Biology, Indiana University, Bloomington, United States
    Contribution
    Funding acquisition, Writing – review and editing
    Competing interests
    No competing interests declared
  10. Stephanie E Mohr

    Drosophila RNAi Screening Center and Department of Genetics, Harvard Medical School, Boston, United States
    Contribution
    Supervision, Funding acquisition, Writing – review and editing
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-9639-7708
  11. Norbert Perrimon

    1. Drosophila RNAi Screening Center and Department of Genetics, Harvard Medical School, Boston, United States
    2. Howard Hughes Medical Institute, Chevy Chase, United States
    Contribution
    Supervision, Funding acquisition, Writing – review and editing
    For correspondence
    perrimon@genetics.med.harvard.edu
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7542-472X
  12. Amanda Simcox

    1. Department of Molecular Genetics, Ohio State University, Columbus, United States
    2. National Science Foundation, Alexandria, United States
    Contribution
    Conceptualization, Formal analysis, Supervision, Funding acquisition, Investigation, Methodology, Writing - original draft, Project administration, Writing – review and editing
    For correspondence
    simcox.1@osu.edu
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-5572-7042

Funding

National Institutes of Health (NIH) Office of the Director (R24 OD019847)

  • Norbert Perrimon
  • Stephanie E Mohr
  • Amanda Simcox

National Institutes of Health (P40OD010949)

  • Andrew Zelhof

National Institutes of Health (P41 GM132087)

  • Norbert Perrimon
  • Stephanie E Mohr

National Science Foundation (IOS 1419535)

  • Amanda Simcox

Howard Hughes Medical Institute

  • Norbert Perrimon

Women & Philanthropy at The Ohio State University (Grant)

  • Amanda Simcox

National Science Foundation (Support while serving at the National Science Foundation)

  • Amanda Simcox

The funders had no role in study design, data collection, and interpretation, or the decision to submit the work for publication. Any opinion, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.

Acknowledgements

We thank M Levine, J R Jacobs, and D Hultmark for antibodies and the Bloomington Stock Center for fly stocks. We thank Mikhail Kouzminov for help with data analysis. Funding This work is supported by the National Institutes of Health (NIH Office of the Director R24 OD019847 to NP, SEM, and AS, P40OD010949 to the DGRC, and NIH NIGMS P41 GM132087 to the DRSC-BTRR), the National Science Foundation (IOS 1419535 to AS, and support while serving at the National Science Foundation to AS), the Howard Hughes Medical Institute (NP), and a grant from Women & Philanthropy at the Ohio State University (to AS).

Senior Editor

  1. Claude Desplan, New York University, United States

Reviewing Editor

  1. Erika A Bach, New York University School of Medicine, United States

Reviewers

  1. Erika A Bach, New York University School of Medicine, United States
  2. David Bilder, University of California, Berkeley, United States

Version history

  1. Received: December 28, 2022
  2. Preprint posted: January 19, 2023 (view preprint)
  3. Accepted: July 12, 2023
  4. Accepted Manuscript published: July 20, 2023 (version 1)
  5. Version of Record published: August 1, 2023 (version 2)

Copyright

This is an open-access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

Metrics

  • 1,310
    Page views
  • 289
    Downloads
  • 0
    Citations

Article citation count generated by polling the highest count across the following sources: Crossref, PubMed Central, Scopus.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Nikki Coleman-Gosser
  2. Yanhui Hu
  3. Shiva Raghuvanshi
  4. Shane Stitzinger
  5. Weihang Chen
  6. Arthur Luhur
  7. Daniel Mariyappa
  8. Molly Josifov
  9. Andrew Zelhof
  10. Stephanie E Mohr
  11. Norbert Perrimon
  12. Amanda Simcox
(2023)
Continuous muscle, glial, epithelial, neuronal, and hemocyte cell lines for Drosophila research
eLife 12:e85814.
https://doi.org/10.7554/eLife.85814

Share this article

https://doi.org/10.7554/eLife.85814

Further reading

    1. Biochemistry and Chemical Biology
    2. Cell Biology
    Chenjie Xia, Huihui Xu ... Hongting Jin
    Research Article

    Glucocorticoid-induced osteonecrosis of the femoral head (GONFH) is a common refractory joint disease characterized by bone damage and the collapse of femoral head structure. However, the exact pathological mechanisms of GONFH remain unknown. Here, we observed abnormal osteogenesis and adipogenesis associated with decreased β-catenin in the necrotic femoral head of GONFH patients. In vivo and in vitro studies further revealed that glucocorticoid exposure disrupted osteogenic/adipogenic differentiation of bone marrow mesenchymal cells (BMSCs) by inhibiting β-catenin signaling in glucocorticoid-induced GONFH rats. Col2+ lineage largely contributes to BMSCs and was found an osteogenic commitment in the femoral head through 9 mo of lineage trace. Specific deletion of β-catenin gene (Ctnnb1) in Col2+ cells shifted their commitment from osteoblasts to adipocytes, leading to a full spectrum of disease phenotype of GONFH in adult mice. Overall, we uncover that β-catenin inhibition disrupting the homeostasis of osteogenic/adipogenic differentiation contributes to the development of GONFH and identify an ideal genetic-modified mouse model of GONFH.

    1. Cell Biology
    Yong Yu, Shihong M Gao ... Meng C Wang
    Research Article Updated

    Lysosomes are active sites to integrate cellular metabolism and signal transduction. A collection of proteins associated with the lysosome mediate these metabolic and signaling functions. Both lysosomal metabolism and lysosomal signaling have been linked to longevity regulation; however, how lysosomes adjust their protein composition to accommodate this regulation remains unclear. Using deep proteomic profiling, we systemically profiled lysosome-associated proteins linked with four different longevity mechanisms. We discovered the lysosomal recruitment of AMP-activated protein kinase and nucleoporin proteins and their requirements for longevity in response to increased lysosomal lipolysis. Through comparative proteomic analyses of lysosomes from different tissues and labeled with different markers, we further elucidated lysosomal heterogeneity across tissues as well as the increased enrichment of the Ragulator complex on Cystinosin-positive lysosomes. Together, this work uncovers lysosomal proteome heterogeneity across multiple scales and provides resources for understanding the contribution of lysosomal protein dynamics to signal transduction, organelle crosstalk, and organism longevity.