This protocol describes a method for isolating single cells from zebrafish embryos, enriching for cells of interest, capturing zebrafish cells in microfluidic based single cell multiplex systems, and assessing gene expression from single cells.
The zebrafish (Danio rerio) is a powerful model organism to study vertebrate development. Though many aspects of zebrafish embryonic development have been described at the morphological level, little is known about the molecular basis of cellular changes that occur as the organism develops. With recent advancements in microfluidics and multiplexing technologies, it is now possible to characterize gene expression in single cells. This allows for investigation of heterogeneity between individual cells of specific cell populations to identify and classify cell subtypes, characterize intermediate states that occur during cell differentiation, and explore differential cellular responses to stimuli. This study describes a protocol to isolate viable, single cells from zebrafish embryos for high throughput multiplexing assays. This method may be rapidly applied to any zebrafish embryonic cell type with fluorescent markers. An extension of this method may also be used in combination with high throughput sequencing technologies to fully characterize the transcriptome of single cells. As proof of principle, the relative abundance of cardiac differentiation markers was assessed in isolated, single cells derived from nkx2.5 positive cardiac progenitors. By evaluation of gene expression at the single cell level and at a single time point, the data support a model in which cardiac progenitors coexist with differentiating progeny. The method and work flow described here is broadly applicable to the zebrafish research community, requiring only a labeled transgenic fish line and access to microfluidics technologies.
Most current studies of cell and molecular biology are based on population averages. However, important biological events may be masked by these traditional population-based analyses since minor populations can play major roles in biological processes and disease outcome. Understanding gene expression in heterogeneous populations at the single cell level can (and has) lead to relevant biological and clinical insights1,2. Of concern to embryonic development studies, in a larger population of cells, progenitor cells are often underrepresented, making it challenging to detect subtle changes in gene expression that ultimately initiate cell fate decisions3. Similarly, a single cell type may have different expression profiles in response to the microenvironment4. For example, resident endothelial cells in the same organ or in different organs (e.g., aorta or kidney) exhibit significant heterogeneity despite sharing common morphological and functional features5. In addition, cancer cells populating the same tumor can also have varying molecular profiles or mutations at the single cell level6.
In model systems, transcriptomics in single cells has successfully identified new cell populations, characterized intermediate states that occur during cell differentiation, and revealed differential cellular responses to stimuli7,8,9. Such insights would have been masked in conventional population-based studies. Zebrafish embryos are a tremendously under-utilized source of stem, progenitor, and differentiating cells for exploring questions of single cell heterogeneity and molecular regulation of cellular identities during development. Their highly stereotyped, ex vivo development and ease of genetic manipulation make them an excellent model system for this approach10,11. Specifically, a major limitation to interpretation of single cell gene expression data is that reliable identification of novel intermediate cell states during development requires very careful timing of tissue collection9. This is necessary to ensure that heterogeneity between captured cells represents heterogeneity within a tissue at a single time point rather than heterogeneity in gene expression presented by age-dependent cell differentiation. Compared to mice, zebrafish embryo development may be precisely synchronized across a large number of embryos12. Additionally, with large clutch sizes, zebrafish embryos can be used as an abundant source of stem and progenitor cells.
This protocol describes a method to isolate cells from zebrafish embryos and capture single cells using a commercially available integrated microfluidics circuit (IFC) chip and autoprep system for qRT-PCR gene expression analysis. This protocol can be rapidly transferrable to any high throughput multiplexing assays including whole transcriptome sequencing that allows more comprehensive analysis of cellular heterogeneity13. It also offers several advantages to traditional gene expression assays. The single cell isolation protocol yields high viability after FACS, which decreases the proportion of compromised cells that are included in downstream applications. By using an IFC, captured cells may be directly observed to evaluate capture rates and assess cell health morphologically. In addition, this protocol is broadly applicable to the zebrafish research community, requiring only a labeled transgenic fish line and access to microfluidic cell capture technologies.
As proof of principle, single cells derived from cardiac progenitors were isolated and captured on an IFC chip, and then the relative abundance of cardiac differentiation markers was measured by qRT-PCR. Gene expression analysis at the single cell level demonstrates that cardiac progenitors coexist with their differentiating progeny. The insight gained from single-cell profiling of cardiac progenitors may shed light on the heterogeneity in gene expression patterns among cardiac progenitor cells during vertebrate development, which may have been masked in traditional population-based analyses.
This protocol requires the use of live, adult zebrafish to produce embryos. The embryos are harvested for tissue collection. It is essential to obtain approval from appropriate ethics review boards to conduct this experiment.
1. Obtain Staged Embryos
2. Set Up for Single Cell Dissociation
3. Single Cell Dissociation
4. FACS Enrichment
5. Load Cells onto Microfluidics Chip
6. cDNA Synthesis
7. Select cDNA from Single Cells for Single Target qRT-PCR
8. Data Analysis
As proof of principle, gene expression was assessed to explore differentiation dynamics during cardiac development. In zebrafish, cardiac progenitors arise from a mesodermal population of cells that migrate to the anterior lateral plate mesoderm where they fuse to form the linear heart tube. Prior to fusion, cardiac progenitors begin to express the transcription factor nkx2.5 (NK2 homeobox 5), which is thought to be the earliest specific marker of cardiac progenitors16,17. Here, a previously described BAC transgenic fish Tg(nkx2.5:ZsYellow)18, abbreviated nkx2.5:ZsY was used to examine cardiac differentiation markers in single cells at the 18 somite stage, 18 hr post fertilization (hpf)12. This was the earliest time point at which ZsYellow signal was visually detectable. As previously described for this transgenic line, ZsYellow labels cardiac progenitors, as well as a few extra-cardiac cells that give rise to the pharyngeal arch endothelial cells at 28 hpf19 (Figure 1A-B, data not shown). At 18 hpf, nkx2.5:ZsY embryos were dissociated into a single cell suspension then stained with Sytox Blue to exclude dead cells. Live, ZsYellow positive, Sytox Blue negative cells were FACS sorted using either a MoFloXDP or Sony SH800Z sorter equipped with 100 µm nozzle (Figure 1C-F). To assess purity of the sorted population and post-sort viability, an aliquot of sorted cells were stained with Sytox Blue and evaluated the percentage of events that fell within the original sorting gate (Figure 1G-J).
After sorting, cells were entered into an integrated microfluidic circuit (IFC) chip work flow (Figure 2A) according to manufacturer's instructions. A hemocytometer, combined with trypan blue exclusion was used to measure cell diameter, concentration, and viability (Figure 2B, and data not shown). Cell buoyancy was optimized (6.5:3.5 cells:buffer) according to manufacturer's instruction, and cells were loaded onto an IFC to capture 5-10 µm diameter cells. To assess capture efficiency, fluorescence and/or bright field signals were imaged at all capture sites, a tiling function in FIJI was used to stitch a single picture of the microfluidics plate. Each capture site contained 0, 1, or >1 individual cells (Figure 2C-F). As expected from FACS enrichment, captured cells expressed ZsYellow (Figure 2G). Capture efficiency exceeded 90% in 5 individual experiments using nkx2.5:ZsY sorted cells, and at least 70% of capture sites were occupied by a single cell (data not shown). Cells were lysed, RNA isolated, cDNA synthesized and specific target genes were amplified, all according to manufacturer's instructions.
A subset of cell capture sites were selected for qRT-PCR analysis as described in the protocol above. Specifically, elongation factor 1a (efl1a)20 and glyceraldehyde-3 phosphate (gapdh)21 were assayed as housekeeping genes expected to be expressed in every cell; GATA binding protein 4 (gata4)22 and NK2 homeobox 5 (nkx2.5) as early cardiac progenitor markers; ISL LIM homeobox 1 box 1 (isl1) as a second heart field marker23,24; and myosin light chain (myl7) and ventricular myosin heavy chain (vmhc) 25 to mark ventricular cardiomyocytes. Gene-specific probes were validated using cDNA from 48 hpf embryos (Figure 3). qRT-PCR was used to assess relative gene expression of these genes in 45 single cells from 18 hpf embryos, a no-template negative control, and a pooled population positive control containing cDNA from all 96 capture sites. Raw CT values for 40 representative cells and controls are shown in Table 1. Notably, from the pool of 46 cells examined, 6 cells were excluded from analysis because all gene expression CT values exceeded CT=35.0, and it is unknown whether these high CT values are attributable to true, very low expression levels or sample degradation. Since the range of CT values for the housekeeping gene, ef1a, was too broad to compare gene expression between samples, and many CT values exceeded 30, CT values were visualized as a heat map (Figure 3). Comparing across samples, substantial heterogeneity in gene expression was observed, and cells were classified cells as Type 1-5 based on expression pattern (Figure 3).
Figure 1. Single cell isolation of zebrafish nkx2.5:ZsY positive cells at 18 hpf. Whole mount images of representative Tg(nkx2.5:ZsYellow) embryo at 18 hpf with (A) ZsYellow fluorescence alone or (B) merged with bright field image. (C-F) Representative FACS gating strategy to enrich for ZsYellow positive cells and (G-J) post-sort analysis with (C,G) FSC/SSC size gating, (D,H) doublet discrimination, (E,I) Live/Dead gating, and (F,J) sorted population. Scale bar is 100 µm. Please click here to view a larger version of this figure.
Figure 2. Single cell capture of zebrafish nkx2.5:ZsY positive cells. (A) Work flow. (B) Cell size distribution for sorted cells from Tg(nkx2.5:ZsYellow) embryos isolated at 18 hpf. (C-F) Representative cell capture events on IFC plate where (C) is an empty well, (D) contains two cells, (E) has a single cell lodged in the fluidics channel as a "channel capture", and (F) is a single captured cell. Purple boxes mark inset for magnified view of capture sites. (G) Single cell capture with brightfield, ZsYellow and merged images. (C-F) White scale bar is 50 µm; yellow scale bar is 10 µm. (G) Scale bar is 10 µm. Please click here to view a larger version of this figure.
Figure 3. Gene expression analysis of capture single zebrafish nkx2.5:ZsY positive cells. Gene expression by qRT-PCR in positive controls (embryos at 2 days-post-fertilization, pooled cDNA from single cells), negative control (no-template) and 40 single cells (Cell 01-40). Raw CT values were color coded based as described in the Key. Ef1a = elongation factor 1a, gata4 = GATA binding protein 4, nkx2.5 = NK2 homeobox 5, myl7 = myosin light chain 7, vmhc = ventricular myosin heavy chain, gapdh = glyceraldehyde-3 phosphate, and isl1 = ISL LIM homeobox 1. Please click here to view a larger version of this figure.
Cycle Threshold (CT) | ||||||||
ef1a | gata4 | nkx25 | myl7 | vmhc | gapdh | isl1 | ||
Embryo | 20.69 | 20.92 | 28.59 | 32.87 | 26.30 | 27.00 | 33.57 | |
Pool | 26.4 | 22.4 | 27.7 | 27.4 | 24.5 | 29.2 | 40.0 | |
NTC | 40.0 | 40.0 | 40.0 | 40.0 | 40.0 | 40.0 | 40.0 | |
Type 1 | Cell-01 | 25.1 | 40.0 | 40.0 | 40.0 | 40.0 | 40.0 | 40.0 |
Cell-02 | 25.4 | 40.0 | 40.0 | 40.0 | 40.0 | 40.0 | 40.0 | |
Cell-03 | 26.3 | 40.0 | 40.0 | 40.0 | 40.0 | 40.0 | 40.0 | |
Cell-04 | 27.4 | 40.0 | 40.0 | 40.0 | 40.0 | 40.0 | 40.0 | |
Cell-05 | 28.0 | 40.0 | 40.0 | 40.0 | 40.0 | 40.0 | 40.0 | |
Cell-06 | 28.2 | 40.0 | 40.0 | 40.0 | 40.0 | 40.0 | 40.0 | |
Cell-07 | 29.3 | 40.0 | 40.0 | 40.0 | 40.0 | 40.0 | 40.0 | |
Cell-08 | 30.7 | 40.0 | 40.0 | 40.0 | 40.0 | 40.0 | 40.0 | |
Cell-09 | 34.3 | 40.0 | 40.0 | 40.0 | 40.0 | 40.0 | 40.0 | |
Type 2 | Cell-10 | 23.5 | 28.0 | 40.0 | 40.0 | 40.0 | 26.3 | 40.0 |
Cell-11 | 23.5 | 27.2 | 40.0 | 40.0 | 40.0 | 40.0 | 40.0 | |
Cell-12 | 23.7 | 17.9 | 40.0 | 40.0 | 40.0 | 40.0 | 40.0 | |
Cell-13 | 24.1 | 32.4 | 40.0 | 40.0 | 40.0 | 40.0 | 40.0 | |
Cell-14 | 24.9 | 27.5 | 40.0 | 40.0 | 40.0 | 40.0 | 40.0 | |
Cell-15 | 25.9 | 28.6 | 40.0 | 40.0 | 40.0 | 40.0 | 40.0 | |
Cell-16 | 26.0 | 28.1 | 40.0 | 40.0 | 40.0 | 40.0 | 40.0 | |
Cell-17 | 27.0 | 27.7 | 40.0 | 40.0 | 40.0 | 38.5 | 40.0 | |
Cell-18 | 27.0 | 27.4 | 40.0 | 40.0 | 40.0 | 40.0 | 40.0 | |
Cell-19 | 27.0 | 30.2 | 40.0 | 40.0 | 40.0 | 38.2 | 40.0 | |
Cell-20 | 27.0 | 28.2 | 40.0 | 40.0 | 40.0 | 39.2 | 40.0 | |
Cell-21 | 27.7 | 30.3 | 40.0 | 40.0 | 40.0 | 38.6 | 40.0 | |
Cell-22 | 30.4 | 26.2 | 40.0 | 40.0 | 40.0 | 38.3 | 40.0 | |
Cell-23 | 31.3 | 22.4 | 40.0 | 40.0 | 40.0 | 39.7 | 40.0 | |
Cell-24 | 31.5 | 28.8 | 40.0 | 40.0 | 40.0 | 39.5 | 40.0 | |
Cell-25 | 33.8 | 27.4 | 40.0 | 40.0 | 40.0 | 37.3 | 40.0 | |
Cell-26 | 40.0 | 27.4 | 40.0 | 40.0 | 40.0 | 36.6 | 40.0 | |
Type 3 | Cell-27 | 24.7 | 19.9 | 28.8 | 40.0 | 40.0 | 40.0 | 40.0 |
Cell-28 | 24.8 | 28.4 | 26.3 | 40.0 | 40.0 | 40.0 | 40.0 | |
Cell-29 | 25.1 | 23.5 | 27.6 | 40.0 | 40.0 | 32.5 | 40.0 | |
Cell-30 | 26.3 | 21.4 | 27.5 | 40.0 | 40.0 | 39.9 | 40.0 | |
Cell-31 | 26.9 | 24.8 | 28.2 | 40.0 | 40.0 | 40.0 | 40.0 | |
Cell-32 | 27.0 | 22.5 | 23.8 | 40.0 | 40.0 | 40.0 | 40.0 | |
Cell-33 | 27.8 | 27.6 | 27.7 | 40.0 | 40.0 | 40.0 | 40.0 | |
Cell-34 | 28.1 | 21.9 | 26.6 | 40.0 | 40.0 | 37.7 | 40.0 | |
Cell-35 | 29.3 | 26.5 | 28.1 | 40.0 | 40.0 | 38.3 | 40.0 | |
Type 4 | Cell-36 | 24.8 | 20.3 | 26.0 | 27.4 | 26.6 | 40.0 | 40.0 |
Cell-37 | 28.7 | 22.3 | 25.9 | 28.9 | 22.9 | 38.5 | 40.0 | |
Type 5 | Cell-38 | 25.5 | 20.0 | 29.3 | 23.0 | 19.9 | 25.9 | 40.0 |
Cell-39 | 25.9 | 21.8 | 28.6 | 25.1 | 21.7 | 25.7 | 40.0 | |
Cell-40 | 28.9 | 22.0 | 27.0 | 23.0 | 21.3 | 27.6 | 40.0 |
Table 1. Raw CT values.
The method described herein uses expression of a fluorescent protein under control of a cell-type specific promoter to enrich a population of cardiac progenitor cells from zebrafish embryos for use in microfluidic assisted single cell capture system to assess expression of a subset of cardiac genes in single cells. Provided that FACS laser excitation and emission capabilities are compatible with the fluorophore(s) of choice, this method can be used for any fluorescent reporter line. Many zebrafish reporter lines are already in existence, and transgenic fish carrying novel reporters can be generated in as little as 3 months. Additionally, this work flow may be adapted to produce cDNA from the whole transcriptome for single cell-RNA sequencing. To do so, steps 5-7 will need to be modified slightly for use with chemistries optimized for preparing cDNA for generating libraries suitable for RNA sequencing. However, it is advisable to validate population heterogeneity by using the method described here prior to pursing high throughput sequencing applications.
It is important to note that there are some limitations to the described method. First, use of integrated microfluidic circuit (IFC) plates requires specialized, costly equipment. However, microfluidic chips offer substantial advantages over traditional 96 well and 384 well plate formats for assaying single cells. By flowing cells and reagents through micrometer scale lanes, single cells are positioned into single capture sites where they can be directly observed to confirm that they are single cells in good health. RNA extraction and cDNA synthesis occur in situ on the IFC chip using very low volumes for each cell. Integrated fluidic chips, at the time of this writing, are commercially available through only one source. Though non-commercial fabrication has been performed by several groups, it is outside of the capacity of most laboratories. Steps 5-7 may need to be modified for platforms produced by other companies or in-house fabrications. Second, though commercially available IFC plates can accommodate up to 96 genes, the genes selected are limited by the availability of fluorogenic-labeled gene probes validated for use in zebrafish. Third, zebrafish cells are typically smaller than mammalian cells, and this small size presents challenges to sample processing. A small change in cell diameter translates into a large change in cell volume, reducing available material and decreasing the likelihood of detecting low expressing genes.
There are several additional considerations for this protocol. In step 1, it is important to only use embryos fertilized within a short time window. Keeping temperature constant and without limiting oxygen conditions, zebrafish embryos develop synchronously. The ultimate readout of this protocol (relative gene expression from single cells) cannot discriminate the source of heterogeneity between individual cells. For this reason, interpretation of intercellular heterogeneity relies on carefully staged embryos and synchronous development. In steps 2-3, there is a tradeoff between dissociation and viability. Though step 4 selects for viable cells, and step 3 contains several filtering steps that help exclude multimers, over-digestion will reduce the viable material available for FACS and potentially reduce sorted cell yield. Steps to troubleshoot low viability include reducing digestion time, reducing trituration intensity, and optimizing the number of embryos in the starting material. FACS enrichment of the cell population of interest (step 4) is arguably the most critical step in this protocol. Stringent sorting criteria are essential to generate a single cell preparation containing only live cells expressing the fluorescent protein of interest. Contaminating cells from other populations could lead to false representation of intercellular heterogeneity. Notably, FACS enrichment of a population of interest is not restricted to the two color strategy shown in this protocol. More complex strategies can produce more refined cell populations and are a rapid way to extend the methodology reported in the proof of principle study. In step 5, cells may be directly observed to confirm the number of cells captured, cell health, and expression of fluorescence protein. But, depending on cell size and brightness, the fluorophore of interest may not be visually detectable and is not a reliable readout. Successful completion of steps 6-8 requires careful adherence to manufacturer's protocols.
As proof of principle, expression levels of a subset of known cardiac markers were assessed in single derived from a previously described BAC transgenic zebrafish line nkx2.5:ZsY to examine cardiac differentiation markers in individual nkx2.5:ZsY positive cells at 18 hr post fertilization (hpf). To explore the heterogeneity of differentiation markers expressed in captured nkx2.5:ZsYexpressing cells, a suite of genes were assayed including housekeeping genes (ef1a, gapdh), transcription factors known to be turned on early in cardiac specification (gata4, nkx2.5), a second heart field progenitor marker (isl1), and genes known to be turned on later during cardiac differentiation (myl7, vmhc). The relative abundance of each gene was measured by qRT-PCR by calculating cycle threshold (CT). The lowest CT value calculated was 17.9 and the highest was 40, representing no amplification (Table 1). CT values of >35.0 were considered below detection.
Of the 46 cells in the data set, 6 were excluded due to failed amplification of any genes. The remaining cells were sub-categorized cells into 5 types based on expression of gata4, nkx2.5, myl7, and vmhc, and were sorted by ef1a value within groups. Though gapdh was originally included as a possible housekeeping gene, expression was highly variable across cells, making it unsuitable as a housekeeping gene. Gapdh expression likely better represents changes to energy metabolism associated with cardiac differentiation in this cell type. Interestingly, there was one cell in which ef1a was un-detectable but another gene was detectable (gata1 in cells 26). This suggests that while ef1a is generally an adequate housekeeping gene to differentiate between successful and unsuccessful single cell reverse transcription reactions, it may not be ideal for all applications. The lack of ef1a expression in cell 26 could be due to single cell transcriptional dynamics. Recent single-cells studies demonstrate that gene transcription is fundamentally stochastic, alternating between phases of rapid and negligible transcriptional activity26. This transcriptional bursting model suggests that use of a housekeeping gene for quantitative comparisons between single cells may be altogether inappropriate.
In the Type 1 group, ef1a is the only gene detectable. These cell may comprise either nkx2.5:ZsY negative cells or cells with very low expression of the other genes of interest. Type 2 cells, with the exception of Cell-26, expressed both ef1a and gata4 with no correlation in the relative expression levels of these genes. Notably, nkx2.5 expression in Type 1 and Type 2 cells may be due to sub-optimal FACS stringency, transcriptional bursting, transgene leakiness, or sub-threshold expression levels. Type 3 cells expressed detectable levels of ef1a, gata4, and nkx-2.5. These cells are likely cardiac progenitor cells and may include differentiating atrial cardiomyocytes. Type 4 cells expressed detectable levels of ef1a, gata4, nkx2.5, myl7 and vmhc and are likely cells differentiating into ventricular cardiomyocytes. Type 5 cells expressed ef1a, gata4, nkx2.5, myl7, vmhc, and gapdh. The addition of detectable levels of gapdh suggests that these cells have the capacity for enhanced glycolytic metabolism found in differentiated cardiomyocytes. It was intriguing that, despite sorting for ZsYellow positive cells from Tg(nkx2.5:ZsYellow), embryos, 21/40 cells had sub-threshold levels of nkx2.5 in our qRT-PCR analysis. This could be due to transcriptional bursting or could reflect differences in transcript processing between endogenous nkx2.5 and ZsYellow. Importantly, the second heart field marker isl1 was undetectable in any cells or cDNA pooled from all of our capture sites. In sum, comparing across samples, substantial heterogeneity was evident at the single cell level, suggesting that at 18 hpf, nkx2.5:ZsY+ cells comprise cardiac progenitors as well as progeny at different stages of differentiation.
The authors have nothing to disclose.
We thank Dr. C. Geoffrey Burns for fish stock. The authors are grateful to UNC Flow Cytometry Core Facility, UNC-CGIBD AAC core for resources enabling this project, and the ZAC facility for animal care. L.S. is supported by NIH T32 grant HL069768-13 (PI, Nobuyo Maeda). N.F. is supported by NSF Graduate Research Fellowship NSF-DGE-1144081. This study was supported by NIH P30DK034987 grant (to UNC Advanced Analytics Core), American Heart Association Scientist Development Grant 13SDG17060010 and Ellison Medical Foundation New Scholar Grant AG-NS-1064-13 (to Dr. Qian), and NIH R00 HL109079 grant (to Dr. Liu).
Supplies | |||
Dumont #5 forceps | Fine Science Tools | 11254-20 | For removing the chorion from embryos |
Microcentrifuge tube 2 mL | GeneMate | C-3261-1 | |
40 um cell strainer | Biobasic | SP104151 | |
35 mm culture dish | Falcon | 351008 | |
FACS tubes topped with 35 um cell strainer | Falcon | 352235 | |
P1000 and tips | Rainin | 17005089 | |
P20 and tips | Rainin | 17005091 | |
IFC chip manufacturer's protocol | Fluidigm | 100-6117 | Version 100-6117 E1 was used in representative experiment |
Wide bore pastuer glass pippette | VWR | 14673-010 | For transferring embryos |
Adult wild type zebrafish | N/A | We used AB line | |
Adult transgenic zebrafish | N/A | We used Tg(nkx2.5:ZsYellow) | |
Name | Company | Catalog Number | Comments |
Reagents for cell dissociation | |||
Double distilled water | N/A | ||
Instant Ocean Sea Salt | Instant Ocean | SS15-10 | |
NaCl | FisherScientific | S271-3 | make stock in water and use for de-yolking buffer |
KCl | Sigma Aldrich | P5405 | make stock in water and use for de-yolking buffer |
NaHCO3 | Sigma Aldrich | S6014 | make stock in water and use for de-yolking buffer |
Leibovitz's L-15 | Gibco | 21083-027 | |
FBS | FisherScientific | 03-600-511 | Heat inactivate; any brand of FBS should be fine |
Cell Dissociation Reagent 1 -TrypLE | Life Technologies | 12605-010 | Store at room temperature. |
Cell Dissociation Reagent 2 – FACSmax | Genlantis | T200100 | Store -20; thaw on ice; bring to room temp before use |
pronase (optional) | Sigma | P5147 | |
L/D Dye – Sytox Blue | Life Technologies | S34857 | Any live/dead stain suitable for flow cytometry will work |
Trypan Blue | Gibco | 15250-061 | |
Name | Company | Catalog Number | Comments |
Reagents for IFC plate use and qRT-PCR | |||
Gene-specific probes | Probes will vary by experiment | ||
TaqMan Probe ef1a | Life Technologies | Dr03432748_m1 | |
TaqMan Probe gata4 | Life Technologies | Dr03443262_g1 | |
TaqMan Probe nk2-5 | Life Technologies | Dr03074126_m1 | |
TaqMan Probe myl7 | Life Technologies | Dr03105700_m1 | |
TaqMan Probe vmhc | Life Technologies | Dr03431136_m1 | |
TaqMan Probe isl1 | Life Technologies | Dr03425734_m1 | |
TaqMan Gene Expression Master Mix | Life Technologies | 4369016 | |
Reagents listed in IFC manufacturer's protocol | |||
C1 Reagent Kit | Fluidigm | 100-5319 | Reagents for loading cells onto IFC plate |
Ambion Single Cell-to-CTTM | Life Technologies | 4458237 | Reagents for reverse transcription and pre-amplification steps |
Molecular Biology Quality Water | Corning | 46-000CM | |
C1 IFC for PreAmp (5-10 um) | Fluidigm | 100-5757 | IFC plate for small cells |
Name | Company | Catalog Number | Comments |
Equipment | |||
C1 AutoPrep machine | Fluidigm | 100-5477 | For IFC plate use |
Hemocytometer | Sigma Aldrich | Z359629 | For counting cells and assessing cell size |
Dissecting microscope | For removing embryos from chorion | ||
Tissue culture microscope | For assessing single cell digestion | ||
FACS machine | For isolating cells of interest |