Here, we present a protocol to dissociate and sort a specific cell population from the Drosophila male accessory glands (secondary cells) for RNA sequencing and RT-qPCR. Cell isolation is accomplished through FACS purification of GFP-expressing secondary cells after a multistep-dissociation process requiring dissection, proteases digestion and mechanical dispersion.
To understand the function of an organ, it is often useful to understand the role of its constituent cell populations. Unfortunately, the rarity of individual cell populations often makes it difficult to obtain enough material for molecular studies. For example, the accessory gland of the Drosophila male reproductive system contains two distinct secretory cell types. The main cells make up 96% of the secretory cells of the gland, while the secondary cells (SC) make up the remaining 4% of cells (about 80 cells per male). Although both cell types produce important components of the seminal fluid, only a few genes are known to be specific to the SCs. The rarity of SCs has, thus far, hindered transcriptomic analysis study of this important cell type. Here, a method is presented that allows for the purification of SCs for RNA extraction and sequencing. The protocol consists in first dissecting glands from flies expressing a SC-specific GFP reporter and then subjecting these glands to protease digestion and mechanical dissociation to obtain individual cells. Following these steps, individual, living, GFP-marked cells are sorted using a fluorescent activated cell sorter (FACS) for RNA purification. This procedure yields SC-specific RNAs from ~40 males per condition for downstream RT-qPCR and/or RNA sequencing in the course of one day. The rapidity and simplicity of the procedure allows for the transcriptomes of many different flies, from different genotypes or environmental conditions, to be determined in a short period of time.
Organs are made up of multiple cell types, each with discrete functions and sometimes expressing vastly different sets of genes. To get a precise understanding of how an organ functions, it is often critical to study each distinct cell type that makes up this organ. One of the primary methods used to explore possible function is transcriptome analysis. This powerful method provides a snapshot of the gene expression in a cell, to reveal active processes and pathways. However, this type of analysis is often difficult for rare cell populations that must be purified from far more-abundant neighboring cells. For example, the Drosophila male accessory gland is an organ made up primarily of two secretory cell types. As the rarer of the two cell types comprises only 4% of the cells of this gland, the use of a cell-type specific transcriptome analysis had not been used to help determine the function of these cells.
Accessory glands (AGs) are organs of the male reproductive tract in insects. They are responsible for the production of most of the proteins of the seminal fluid (seminal fluid proteins (SFPs) and accessory gland proteins (ACPs)). Some of these SFPs are known to induce the physiological and behavioral responses in mated females, commonly called the post-mating response (PMR). Some of the PMRs include: an increased ovulation and egg-laying rate, the storage and release of sperm, a change in female diet, and a decrease in female receptivity to secondary courting males1,2. As insects impact many major societal issues from human health (as vectors for deadly diseases) to agriculture (insects can be pests, yet are critical for pollination and soil quality), understanding insect reproduction is an important area of research. The study of AGs and ACPs has been advanced significantly with the model organism Drosophila melanogaster. These studies have highlighted the role of AGs and some of the individual proteins that they produce in creating the PMR, impacting the work in other species like the disease vector Aedes aegypti3,4, and other insects1,5. Furthermore, as AGs secrete the constituents of the seminal fluid1,6 they are often thought of as the functional analog of the mammalian prostate gland and seminal vesicle. This function similarity combined with molecular similarities between the two tissue-types, have made the AGs a model for the prostate gland in flies7.
Within the Drosophila male, there are two lobes of accessory glands. Each lobe can be seen as a sac-like structure made up of a monolayer of secretory cells surrounding a central lumen, and wrapped by smooth muscles. As mentioned above, there are two morphologically, developmentally and functionally distinct secretory cell types making up this gland: the polygonal-shaped main cells (making up ~96% of the cells), and the larger, round secondary cells (SC) (making up the remaining 4% of cells, or about 40 cells per lobe). It has been shown that both cell types produce distinct sets of ACPs to induce and maintain the PMR. Most of the data obtained to date highlight the role of a single protein in triggering most of the characteristic behaviors of the PMR. This protein, the sex peptide, is a small, 36 amino acid peptide that is secreted by the main cells8,9,10. Although the sex peptide seems to play a major role in the PMR, other ACPs, produced by both the main and secondary cells, have also been shown to affect various aspects of the PMR11,12,13,14,15,16,17. For example, based on our current knowledge, the SCs, via the proteins they produce, seem to be required for the perpetuation of the SP signaling after the first day18.
Given the rarity of the SCs (only 80 cells per male), all our knowledge about these cells and the proteins they produce comes from genetics and candidate approaches. Thus far, only a relatively small list of genes has been shown to be SC-specific. This list includes the homeodomain protein Defective proventriculus (Dve)19, the lncRNA MSA20, Rab6, 7, 11 and 1921, CG1656 and CG1757511,15,21 and the homeobox transcription factor Abdominal-B (Abd-B)18. Previously, we have shown that a mutant deficient for both the expression of Abd-B and the lncRNA MSA in secondary cells (iab-6cocuD1 mutant) shortens the length of the PMR from ~10 days to only one day12,18,20. This phenotype seems to be caused by the improper storage of SP in the female reproductive tract12,18,20. At the cellular level, the secondary cells of this mutant show abnormal morphology, losing their characteristic vacuole-like structures18,20,21. Using this mutant line, we previously attempted to identify genes involved in SC function by comparing the transcriptional profiles of whole AGs from either wild type or mutant accessory glands12. Also, other labs showed that SC number, morphology and vacuolar content depend on male diet, mating status and age21,25,26.
Although positive progress was made using these approaches, a full SC transcriptome was far from achieved. The rareness of these cells in this organ made it difficult to progress further even from wild type cells. For testing gene expression, changes in these cells after particular environmental stimuli would be even harder. Thus, a method for isolating and purifying SC RNA that was fast and simple enough to perform under different genetic backgrounds and environmental conditions was needed.
Both the Abd-B and MSA genes require a specific 1.1 kb enhancer from the Drosophila Bithorax Complex (called the D1 enhancer) for their expression in SCs18,20. This enhancer has previously been used to create a GAL4 driver that, when associated with a UAS-GFP, is able to drive strong GFP expression specifically in SCs. Thus, we used this line as the basis for a FACS protocol to isolate these cells from both wild type and iab-6cocuD1 AGs). As iab-6cocuD1 mutant SCs display a different cellular morphology, we show that this protocol can be used to isolate cells for the determination of their transcriptome from this rare cell type under vastly different conditions.
1. Drosophila Lines Used and Collection of Males
2. Solutions and Material Preparation
3. Dissection of Accessory Glands
4. Tissue Digestion
5. Mechanical Dissociation of the Cells
6. FACS (Fluorescence-activated Cell Sorting)
7. RNA Extraction
NOTE: We used Epicentre MasterPure RNA Purification Kit for RNA extraction, with the following adaptations. Other kits might be used as long as the yield is high enough to prepare a library for sequencing from ~500 cells (2 ng RNAs was used here).
8. Quality Controls of RNA Quantity, Quality and Specificity
9. Sequencing (cDNA Library Preparation, Sequencing and Data Analysis)
10. Data Analysis
The protocol presented here enables one experimenter to isolate secondary cells from Drosophila male accessory glands and to extract their RNA in the course of one single day (Figure 1).
We use the Abd-B-GAL4 construct18 to label secondary cells (SC) but not main cells (MC) with GFP (Figure 2A). One objective of this procedure is to obtain the wild type transcriptome of SCs (wild type is written with inverted commas since they are obtained from transgenic flies expressing GFP and GAL4). Another objective is to obtain SC RNA through a fast and easy procedure that allows studying their gene expression in different conditions. Thus, we performed this procedure using wild type and "iab-6cocuD1" mutants that carry a 1.1 kb deletion removing the enhancer of Abd-B responsible for SC expression. This deletion also removes the promoter of MSA, an important transcript for secondary cells development, morphology and function18,20 (Figure 2B,C). This protocol was repeated thrice with 2 genotypes each time to obtain biological triplicates (hereafter referred as WT-1,-2,-3 for the wild type and D1-1,-2 and -3 for the iab-6cocuD1).
This protocol allows MC and SC dissociation from Drosophila accessory glands in a few hours (Figure 2D). Both cell populations are then sorted in two different tubes to isolate MCs and SCs. The gating strategy for FACS is show in Figure 2E-2G. Draq7 allows estimating cell viability around 70% for the whole sample (Figure 2F). The singlets represent over 90% of the SC population, and over 80% of the MC population, as estimated by FSC-A vs FSC-H and SSC-H vs SSC-W. (see Figure 2H). This reflects an efficient dissociation. Around 10% of sorting events were aborted because another cell or debris was present in the same FACS droplet. From 40 males, we typically collect 550 SCs and 1,000 MCs and then interrupt sorting. From 1 sample (out of 6), we could not reach 550 secondary cells. The WT-1 sample was thus obtained from only 427 SC but provided RNA of similar quality and quantity as others.
Cells are sorted into lysis buffer (containing proteinase K). As soon as all samples are ready, RNAs are extracted from each cell sample in order to have RNA pellets at the end of the day. Quality and quantity of RNAs are estimated using a Bioanalyzer with an appropriate chip to deal with low concentrations and small volumes. Because estimated concentrations were variable between samples (ranging from over 1,300 pg/µL down to 344 pg/µL, see Figure 3A), we adjusted the starting material for both RT-qPCR and cDNA library synthesis to roughly 2 ng (measured concentrations are not highly accurate). We quantified the expression of specific genes by real time qPCR on wild type MC and SC extracts to control for the identity of the cell populations we sorted. Figure 3B shows gene expression as relative quantifications normalized to alpha-tubulin expression. Housekeeping genes like 18S rRNA and alpha-tubulin are detected in all samples, as expected. Quite the contrary, the SC gene Rab19 is detected only from SC extracts, and the MC gene Sex Peptide is detected only from MC. We note that Rab19 expression in iab-6cocuD1 mutant SC is low relative to wild type SC, suggesting that the expression of this gene is affected by the loss of Abd-B and MSA (consistently, the large Rab19-labeled vacuoles are lost in the iab-6cocuD1 mutant21). The secondary cell-specific transcript MSA is detected only from wild type SC and not from MC, nor from iab-6cocuD1 SCs, which was expected since MSA promoter is deleted in this mutant. Altogether, the QCs shown in Figure 3 demonstrate that RNAs obtained through this protocol are not degraded, and that both cell populations (SC and MC) are successfully sorted from accessory glands, in both wild type and mutant conditions. Only secondary cells' RNAs were sequenced here, but note that this procedure enables concomitant transcriptome profiling of both SCs and MCs.
RNA-sequencing was realized using standard procedures. Here, we will only discuss the quality control analyses that are pertinent for the purpose of this method. When sequences are obtained, the reads are mapped to the reference Drosophila genome, attributed to genes, and normalized. PCA (Principal Component Analysis) was performed on the 6 samples (3 wild type and 3 iab-6cocuD1 replicates). As much of the variability in the data as possible is accounted for in PC1, and as much of the remaining variability is accounted for in PC2.As shown in Figure 4A, the wild type replicates cluster close together, and far from Iab-6cocuD1 samples. This shows that WT samples are more similar to each other than they are from mutant ones. This illustrates the method reproducibility and its ability to detect abnormal genetic program from mutant secondary cells. While D1-2 and D1-3 samples cluster together, we note that the D1-1 sample is quite divergent. Since all QCs for this replicate are good and comparable to all other replicates, we can exclude a sample preparation issue (29 million reads in total, >76% of which align uniquely to the reference genome. Among those, >77% are attributed to a gene, >90% are mRNAs, and <3% are rRNA). This divergence could reflect that gene expression in SC is unstable in iab-6cocuD, although testing this hypothesis would require more replicates.
Visualizing reads aligned to particular genes on the genome allows for a visual estimation of the data quality. Figure 4 shows a selection of genes, with reads from 1 representative replicate for each genotype. Unsurprisingly, housekeeping genes such as Act5C are expressed in both genotypes (Figure 4B), as well as the SC-specific genes Rab19 and Dve (Figure 4C,D). The lack of intronic reads confirms that polydT selectively primed reverse transcription from mature spliced mRNAs for cDNA library preparation. Notably, we can see important and significant variations in the expression of specific genes between wild type and iab-6cocuD1 SC. This is exemplified in Figure 4E by the MSA gene whose strong expression in wild type is lost in iab-6cocuD1. MSA is presented as a proof of principle that this method enables identifying genes that are mis-regulated in mutant conditions. This will help understanding the phenotypes observed in this mutant, and might give new insights into normal secondary cells functions.
Figure 1: Overview of the protocol. Key steps of the protocol are shown, with the timeline on the right side. This procedure allows one starting with live Drosophila in the morning to have dissociated accessory gland cells by noon, sort them based on GFP expression, and get their RNAs extracted by the end of the working day. RNA sequencing and data analysis will typically take a few weeks. This figure has been modified from reference27. Please click here to view a larger version of this figure.
Figure 2: Isolating and sorting GFP-expressing secondary cells. (A) Confocal image of Abd-B:GAL4 UAS-GFP accessory gland expressing GFP in secondary cells (SC), but not in main cells (MC). Nuclei are stained with DAPI (blue). Dotted white line delimits AG lobes. ED is Ejaculatory duct. White bars in the upper left corner are 50 µm scales. (B,C) Enlarged views of accessory gland distal part with SC expressing GFP, in wild type (B) and iab-6cocuD1 (C) background. (D) Dissociated cells at low magnification under the GFP binocular. (E-H) FACS gating strategy to purify SC and MC. Red dots on all panels shown SCs as defined in panel (G). First the debris are excluded (E, step 6.2.1) as well as the Draq-7 positive dead cells (F, step 6.2.2). GFP positive cells are selected (SC) as well as an homogeneous population of GFP negative cells (MC) (G, steps 6.2.4 and 6.2.5). Doublets are excluded from both MC and SC population (step 6.2.3, only the SSC-H vs SSC-W gating for SC is shown on 2H as an example). This figure has been modified from reference27. Please click here to view a larger version of this figure.
Figure 3: QC on RNAs: quality, quantity, and cell type specificity. (A) Control of RNA quality and concentration estimation on PicoChip. The 25 nt peak is the control for quantification. Low baseline indicates low degradation and the 2 major peaks are the ribosomal RNAs. The 3 samples used for RT-qPCR are shown, their quality is representative of all RNA samples used in this study, and their estimated concentrations reflect the variation in total RNA we obtained between samples. (B) RT-qPCR demonstrate the specificity of the sorting of secondary cells (SC) and main cells (MC). Gene expression quantification is done using the q=2(40-Cq) formula. Each triplicate of each gene in each condition is normalized to the mean quantity of alpha-Tubulin RNA to compensate for total RNA variation. Error bars show standard deviation. WT means wild type and D1 refers to the iab-6cocuD1 mutant. This figure has been modified from reference27. Please click here to view a larger version of this figure.
Figure 4: QC on RNA sequencing data. (A) Principal Components Analysis (PCA) on WT-1,-2,-3 (green dots) and D1-1,-2,-3 (blue dots) RNA sequencing datasets. (B-E) Sequencing reads mapped to the Drosophila reference genome using the IGV software. Only one representative sample of each genotype is shown for clarity sake (WT-1 and D1-2), and only a few specific loci are shown. Gene names are written on top of each panel, > and < symbols refer to their orientation. Numbers in brackets represent for each track the scale for the number of reads per DNA base pair. This scale is the same for both conditions for a given gene, but varies between genes for better visualization. Blue bars at the bottom of each panel show genes' introns (thin line), exons (wide line) and ORF (rectangles with >>). Note that Rab19 and Arl5 are overlapping, convergent genes (C). This figure has been modified from reference27. Please click here to view a larger version of this figure.
Primers used for RT-qPCR in this study: | ||
Target gene | Forward primer | Reverse primer |
alpha-Tubulin | TTTTCCTTGTCGCGTGTGAA | CCAGCCTGACCAACATGGAT |
18S rRNA | CTGAGAAACGGCTACCACATC | ACCAGACTTGCCCTCCAAT |
Rab19 | CAGGAGAGGTTTCGCACTATTAC | TTGGAAAAGGAAGACCGCTTG |
Sex Peptide | GGAATGGCCGTGGAATAGGA | TAACATCTTCCACCCCAGGC |
MSA | CTCATCTGCGTCTTCGCGTG | CAGCTCCGTTTGTAATCTCTCGAGC |
Table 1: Primers sequence
Methods for cell dissociation from Drosophila tissue like imaginal discs are already described23. Our attempts to simply use these procedures on accessory glands failed, encouraging us to develop this new protocol. Protease digestion and mechanical trituration were critical steps we troubleshot for the success of the procedure, and we thus placed many notes in sections 2 to 5 to help experimenters to obtain satisfactory results. For dissociation to be successful, peptidases must reach the accessory gland cells, which are protected by the viscous seminal fluid in the lumen and the muscle layer around the gland. Dissecting the glands' distal part was thus critical (step 3.6). Also, digesting for 60 min at least with vigorous shaking (step 4.1) was necessary. Gentle dissociation with trypsin solution (e.g., TrypLE) preserved the gland integrity and cell viability until mechanical dissociation. The addition of either papain or collagenase in association with trypsin solution improved the dissociation (perfect dissociation was obtained with fewer pipetting, resulting in better cell survival). However, none of those enzymes were sufficient to dissociate the cells on their own. Pipetting using rounded narrow tips generated in part 2.2.2 is a key step for this method. Hence, this trituration (steps 5.2-5.3) should be optimized in small scale experiments to choose the best combination of tips (see note in step 5.3).
Using this protocol, one will be able to isolate 500 to 800 live secondary cells from 40 males. This represents ~20% (± 5%) recovery considering 3,200 SC as the starting material (40 males x 80 SC). 20% efficiency was high enough for RNA sequencing since we could process multiple samples in a day. However, this might be improved by several methods including: working in larger batches; doing trituration in the digestion tube and skipping step 5.4 to reduce transfers; triturating very gently (some dissociated GFP+ cells die shortly after step 5.3); shortening the period between dissociation and FACS; decreasing the digestion time by using trypsin solution at higher concentration; using less stringent parameters for singlet selection (step 6.2.3) and aborted sorting. One limitation of this protocol is that it takes several hours to isolate cells; hence it is not suited to study very transient gene expression changes. With this protocol, 4 x 20 males can be processed by a single person (with training) in one morning, allowing RNA extraction from SC of two different conditions in 1 day (Figure 1). Notably, more experimenters can participate in accessory glands collection (steps 3.1-3.3) in order to process multiple samples on the same day. However, steps 3.4 onwards will preferentially be performed by the same person to maximize reproducibility.
Secondary cells carry out essential functions for male fecundity12,20,24, but the complete picture of the genes they express to fulfill this role is still missing. Here, we describe how to obtain the transcriptome of these cells from a relatively small number of flies, enabling the comparison of gene expression in SC in different conditions. Here, one mutant affecting SC function and morphology was used, and important changes in its transcriptome are visible. This method might thus help identifying new SC genes necessary for their function. To our knowledge, the only alternative method to obtain SC transcriptome was performed in our lab by manual picking of SCs. Good quality RNA sequencing data was obtained, but the procedure was too labor intensive to be performed in multiple conditions. We will compare our SC RNAseq datasets and analyze their biological meaning about SC biology in a distinct paper (in preparation).
In the future, this technique will not only shed light on wild type SC transcriptome, but also enable to study the impact of environment or gene alteration on accessory gland cells transcriptome. SC number, morphology and vacuolar content have been shown to depend on male diet, mating status and age21,25,26. We still have a limited understanding of the genetic pathways involved and comparing SC transcriptomes in different conditions would be insightful. This fast and relatively simple protocol will enable such studies. Importantly, this method allows isolating main cells from the same individuals, and could thus be used as it is to determine whether genetic and environmental parameters affect both accessory gland cell types simultaneously.
The authors have nothing to disclose.
We are grateful to the members of the Karch lab, to the iGE3 genomics plateform, to the Flow Cytometry core facility of the University of Geneva, and to Dr. Jean-Pierre Aubry-Lachainaye who set the protocol for FACS. We thank Luca Stickley for his help with visualizing the reads on IGV. We thank ourselves for gentle permission to reuse figures, and the editors for prompting us to be creative with writing.
This research was funded by the State of Geneva (CI, RKM, FK), the Swiss National Fund for Research (www.snf.ch) (FK and RKM) and donations from the Claraz Foundation (FK).
24-wells Tissue Culture plate | VWR | 734-2325 | |
Binocular microscope for dissection | |||
Binocular with light source for GFP | |||
Bunsen | |||
Draq7 0.3 mM | BioStatus | DR71000 | |
Plastic microtubes 1.5 mL | Eppendorf | ||
FACS | Beckman Coulter | MoFlo Astrios | |
Fine dissection forceps | |||
Foetal bovine serum | Gibco | 10270-106 | heat inactivated prior to use |
Glass dishes for dissection | |||
Ice bucket | |||
ImProm-II Reverse Transcription System | Promega | A3800 | |
MasterPure RNA Purification Kit | Epicentre | MCR85102 | |
Nextera XT kit | illumina | https://emea.illumina.com/products/by-type/sequencing-kits/library-prep-kits/nextera-xt-dna.html | |
P1000 | Gilson | ||
P20 | Gilson | ||
P200 | Gilson | ||
Papain | 50U/mL stock | ||
PBS | home made | ||
Penicillin-Streptomycin | Gibco | 15070-063 | |
PolydT primers | |||
Random hexamer primers | |||
RNA 6000 Pico kit | Agilent | ||
Schneider’s Drosophila medium | Gibco | 21720-001 | |
SMARTer cDNA synthesis kit | Takara | https://www.takarabio.com/products/cdna-synthesis/cdna-synthesis-kits/smarter-cdna-synthesis-kits | |
SYBR select Master mix for CFX | applied biosystems | 4472942 | |
Thermo Shaker | Hangzhou Allsheng intruments | MS-100 | |
Tipone 1250 μl graduated tip | Starlab | S1161-1820 | |
Tipone 200 μl bevelled tip | Starlab | S1161-1800 | |
TrypLE Express Enzyme | Gibco | 12604013 | |
Vortex |