The protocol presented in this study describes methods for the real-time monitoring of reprogramming progression via the kinetic measurement of positive and negative pluripotent stem cell markers using flow cytometry analysis. The protocol also includes the imaging-based assessment of morphology, and marker or reporter expression during iPSC generation.
Somatic reprogramming has enabled the conversion of adult cells to induced pluripotent stem cells (iPSC) from diverse genetic backgrounds and disease phenotypes. Recent advances have identified more efficient and safe methods for introduction of reprogramming factors. However, there are few tools to monitor and track the progression of reprogramming. Current methods for monitoring reprogramming rely on the qualitative inspection of morphology or staining with stem cell-specific dyes and antibodies. Tools to dissect the progression of iPSC generation can help better understand the process under different conditions from diverse cell sources.
This study presents key approaches for kinetic measurement of reprogramming progression using flow cytometry as well as real-time monitoring via imaging. To measure the kinetics of reprogramming, flow analysis was performed at discrete time points using antibodies against positive and negative pluripotent stem cell markers. The combination of real-time visualization and flow analysis enables the quantitative study of reprogramming at different stages and provides a more accurate comparison of different systems and methods. Real-time, image-based analysis was used for the continuous monitoring of fibroblasts as they are reprogrammed in a feeder-free medium system. The kinetics of colony formation was measured based on confluence in the phase contrast or fluorescence channels after staining with live alkaline phosphatase dye or antibodies against SSEA4 or TRA-1-60. The results indicated that measurement of confluence provides semi-quantitative metrics to monitor the progression of reprogramming.
Patient-derived induced pluripotent stem cells (iPSCs) are promising tools for cell therapy and drug screening. They provide an autologous source of cells for therapy. In addition, they encompass a very broad set of genetic backgrounds, enabling a detailed in vitro analysis of genetic diseases beyond what current embryonic stem cell (ESC) lines would allow. Recent advances have led to the development of several methods for generating iPSCs, including reprogramming with Sendai virus, episomal plasmids or mRNAs 1,2. Notably, different reprogramming methods are associated with varying levels of efficiency and safety, and are likely to differ in other ways that influence their appropriateness for various applications. With the availability of a variety of reprogramming technologies, it has become important to develop methods for assessing the reprogramming process. Most existing methods rely on the qualitative inspection of morphology or staining with stem cell-specific dyes and antibodies. One recently developed method makes use of lentiviral fluorescence reporters that are sensitive to PSC-specific miRNAs or differentiated cell-specific mRNAs 3. Such monitoring methods facilitate the selection and optimization of reprogramming techniques for different situations. For example, CDy1 has been used as a fluorescent probe for early iPSCs in order to screen for reprogramming modulators 4. The ability to observe and compare different reprogramming experiments is also critical for gaining a better understanding of the process itself. For instance, it is now known that some somatic cell types are easier to reprogram than others 5, and that cells go through intermediate states during reprogramming 6-8. Unfortunately, the mechanisms underlying the reprogramming process are still not completely understood and consequently, the exact differences between reprogramming methods also remain to be defined. Thus, methods for monitoring, assessing, and comparing reprogramming events continue to be critical for the stem cell field.
The methods described in this protocol permit the monitoring and assessing of the reprogramming process and illustrate how these techniques can be used to compare different sets of reprogramming reagents. The first approach involves flow cytometry analyses using combinations of antibodies against positive and negative pluripotent stem cell (PSC) markers. The second approach couples real-time imaging and the measurement of total confluence (the percent surface area covered by the cells) and confluence of marker signals (the percent surface area covered by the fluorescent signals).
1.Solution and Medium Preparation
2. Sendai Mediated Reprogramming of Human Fibroblasts
3. Sendai Reprogramming of BGO1v hOct4-GFP Reporter Human Embryonic Stem Cells (hESC) Derived Secondary Fibroblasts
4. Live Cell Imaging of Fibroblast Reprogramming
5. Measurement of Reprogramming Kinetics Using Flow Cytometry
6. Endpoint Analysis
Monitoring Reprogramming Kinetics Using Flow Cytometry
CD44 is a fibroblast marker while SSEA4 is a PSC marker 6,10. As expected from this expression pattern, flow cytometry of BJ fibroblasts shows an SSEA4– CD44+ population that facilitates the creation of quadrant gates in combination with the unstained sample. During reprogramming of DF1 fibroblasts with the Sendai viruses, CD44 is gradually lost while SSEA4 is slowly expressed. At Day 3 after transduction with the Sendai Viruses, there is a large population of SSEA4– CD44+ cells and a small population of SSEA4+ CD44+ cells that becomes more distinct at Day 7 (Figure 1). At Day 13, the double-positive population transitions towards the SSEA4+ CD44– state. By Day 17, a large percentage of the cells in culture are already SSEA4+ CD44–. This time course shows that flow cytometry with CD44 and SSEA4 can be used to monitor the progression and rate of reprogramming.
A quantitative comparison confirms that reprogramming BJ fibroblasts with Sendai reprogramming viruses generates SSEA4+ CD44– cells at a different rate than reprogramming of BJ Fibroblasts (Figure 2A). The data demonstrates that an early comparison of the percentage of PSC-like SSEA4+ CD44– cells tracks the progression of reprogramming. Interestingly, at Day 8 of DF1 fibroblast reprogramming, sorting and separately culturing the population of cells that are in the process of upregulating SSEA4 and downregulating CD44 generates AP+ colonies 11 (Figure 2B). In contrast, the original SSEA4– CD44+ population generates a much smaller number of AP+ colonies at Day 21 of reprogramming, which is the typical day of final colony analysis. This suggests that it is possible to quantify and compare the transitioning population in order to predict differences in reprogramming kinetics even before the SSEA4+ CD44– population is formed. An important point to note here is that reprogramming is a variable process dependent on several factors such as starting somatic cell population, transduction efficiency, medium, etc. However the general pattern and progression of the above described surface markers is consistent between different reprogramming experiments and starting fibroblasts. The analysis of reprogramming kinetics can also be done with different markers, such as the newly identified negative PSC markers CD73 and B2M 6, as well as the established PSC markers CD24 12,13 and EPCAM 14,15. Similar to CD44, CD73 and B2M are expressed in parental BJ fibroblasts, but are downregulated during the course of reprogramming, becoming undetectable in fully reprogrammed iPSCs (Figure 3A). A flow cytometry time course using CD44 and CD73 or CD44 and B2M shows that CD44 and CD73 are downregulated at a similar rate, whereas B2M is downregulated faster than CD44 (Figure 3B). In both cases, the rate of reprogramming can be observed by measuring the accumulation of the double negative population. In contrast to these negative PSC markers, CD24 and EPCAM are absent in fibroblasts and are expressed in iPSCs (Figure 3A). In a flow cytometry time course, CD24– CD44+ and EPCAM– CD44+ fibroblasts eventually form double-negative populations that later transition into CD24+ CD44– and EPCAM+ CD44– PSC-like cells, respectively (Figure 3B). Thus, during reprogramming, both positive PSC markers are expressed after CD44 is downregulated. Similar to what was observed with SSEA4 and CD44, the formation and accumulation of the different cell populations indicate the progression of reprogramming.
Tracking Reprogramming Using Real-time Imaging Analysis
Real-time imaging of reprogramming cultures after reseeding shows the gradual formation of colonies (Figure 4A), which corresponds to a logarithmic increase in confluence under phase contrast (Figure 4B). Confluence under phase contrast thus provides another metric for monitoring reprogramming quantitatively, but it encompasses both, the colonies that are positive for PSC markers and the continued proliferation of unreprogrammed or partially reprogrammed cells (Figure 4A, last panel). Quantifying the areas that have been stained for pluripotency markers TRA-1-60, SSEA4 and AP 6,10 at Day 21 indicates that iPSCs only account for less than half of the total confluence (Figure 4B). To measure the progress of reprogramming more stringently, it is possible to use a reporter line for reprogramming. Here, secondary fibroblasts were generated from the BG01v/hOG ESC line, which has been engineered with an OCT4-GFP reporter 16. GFP is expressed as the cells are reprogrammed and as colonies are formed (Figure 5A). Measuring confluence under phase contrast and the green channels demonstrates that the GFP confluence increases more slowly than the total confluence, and the GFP confluence at Day 19 is less than half of the total confluence (Figure 5B), reminiscent of TRA-1-60, SSEA4 and AP staining at Day 21.
Figure 1. Monitoring the Progress of Reprogramming Using Flow Cytometry. Flow Cytometry Dot Plots for DF1 Fibroblasts Reprogrammed with Sendai Viruses under Feeder-free Conditions. Cells were harvested and stained with SSEA4 and CD44 antibodies at different intervals from Day 3 (D3) to Day 19 (D19) of the reprogramming process. Cultures at Day 9 (D9) onwards were analyzed after the cells were reseeded at Day 7 (D7). Dot plots show 8,000 singlets. Please click here to view a larger version of this figure.
Figure 2. Evaluating Reprogramming Kinetics and Efficiency under Feeder-free Conditions. (A) Graph showing changes in the percentage of SSEA4+ CD44– reprogrammed cells after transducing DF1 fibroblasts and BJ fibroblasts with the Sendai viruses. Cells were analyzed by flow cytometry at Day 3 to 19 post-transduction, with cultures at Day 9 onwards undergoing reseeding at Day 7. (B) Pseudo-color flow cytometry plots for DF1 cells transduced Sendai viruses and stained with SSEA4 and CD44 antibodies. SSEA4– CD44+ cells (black circle) and SSEA4+ cells (red circle) were sorted at Day 8 and allowed to grow until Day 19 before staining for alkaline phosphatase (red). Please click here to view a larger version of this figure.
Figure 3. Observing Reprogramming Kinetics of Feeder-free Cultures Using Different Positive and Negative PSC Markers. (A-D) Live staining of Day-18 DF1-derived reprogramming cultures using antibodies for the positive PSC markers CD24 and EPCAM and negative PSC markers CD44, CD73, and B2M. The top panels merge the green and red fluorescence channels while the bottom panels also include the phase contrast image. The scale bar represents 200 µm. (E) Flow cytometry dot plots for DF1-derived reprogramming cultures harvested and stained using the same markers from Day 9 to 17 (D9 to D17) post-transduction. Prior to analysis, cultures were reseeded at Day 7. Dot plots show 8,000 singlets. Please click here to view a larger version of this figure.
Figure 4. Tracking Reprogramming Kinetics by Measuring Total Confluence. (A) Real-time imaging of BJ fibroblasts reprogrammed with Sendai viruses under feeder-free conditions. Phase contrast images of the same colonies were taken at Day 7 to 19, then at Day 21 with additional staining for CD44 and SSEA4, TRA-1-60 or AP. Scale bar corresponds to 400 µm. (B) Quantification of total confluence (phase contrast) as reprogramming progresses from reseeding at Day 7 to Day 21. Total confluence at Day 21 is compared to SSEA4, TRA-1-60 and AP signal confluence (green channel). Please click here to view a larger version of this figure.
Figure 5. Assessing Reprogramming Kinetics by Measuring OCT4-GFP Confluence. (A) Real-time imaging of BG01v/hOG hESC-derived fibroblasts reprogrammed with Sendai viruses under feeder-free conditions. Phase contrast, green fluorescence and merged images of the same colonies were generated at Day 7 to 19. Scale bar corresponds to 400 µm. (B) Quantification of total confluence (phase contrast) and OCT4-GFP confluence (green channel) as reprogramming progresses from re-seeding at Day 7 to Day 21. Please click here to view a larger version of this figure.<!–
This study provides strategies for monitoring and tracking of the reprogramming process using flow cytometry and real-time imaging-based analysis. The critical steps in the protocol are initiating reprogramming, measuring reprogramming progression based on marker expression and real-time monitoring of reprogramming. Any reprogramming method of choice can be used but here we focus on Sendai based reprogramming of human fibroblasts. The advantage of this method is the ease of use and consistent high efficiency of reprogramming.
To assess reprogramming progression, cells are harvested at discrete stages of reprogramming and subjected to an end-point flow cytometry analysis. Double staining of reprogramming cultures with the negative PSC marker CD44 and the positive PSC marker SSEA4 allows the assessment of reprogramming progression6. More specifically, the distribution of cells expressing either, neither or both markers at discrete stages of reprogramming enables the quantitative comparison of reprogramming kinetics under different conditions. This approach can demonstrate the differences in the kinetics and efficiency between different reprogramming methods and the media and matrices used during the reprogramming processes. The results obtained using different starting somatic cell samples confirms the importance of these factors in reprogramming efficiency and progression. They also demonstrate how this approach can be used to optimize reprogramming methods. The feasibility of monitoring reprogramming through flow cytometry using other combinations of pluripotent and non-pluripotent markers such as EPCAM, CD24, CD73, and B2M can be used in conjunction with the fore mentioned method14. Interestingly, these marker combinations show the formation of multiple cell populations through the course of reprogramming. Further studies will be required to fully characterize those populations and to determine their relevance in the reprogramming process. Regardless, the applicability of the flow cytometry approach with this diverse set of markers indicates that it can be applied more broadly, making use of different markers-of-interest and uncovering many other reprogramming intermediates. The limitation with this approach is that cells will need to be harvested for end point analysis. This limitation can be overcome with the use of live monitoring methods.
Monitoring of cells undergoing reprogramming in real time is done using the Live Cell Imaging system. Confluence, as measured under phase contrast, increased rapidly as colonies began to form. As such, measuring total confluence under phase contrast allows us to track the progression of reprogramming easily in real time, but because this measurement encompasses unreprogrammed and partially reprogrammed cells that are negative for AP, SSEA4 and TRA-1-60, this approach is only semi-quantitative. Linking the real-time phase contrast images to end-point positive marker staining with either dyes such as Live Alkaline Phosphatase or pluripotent markers such as SSEA4 or TRA-1-60 provides better insight into the kinetics of the reprogramming process11. However, this study shows that a more accurate and quantitative imaging-based method for tracking reprogramming would involve measuring fluorescence signal confluence while using an OCT4 reporter line16. Each of the methods presented here have their own advantages and disadvantages that make them appropriate for different situations. The flow cytometry approach is laborious and requires a lot of cells, but it provides the most accurate quantitative data. Measuring fluorescence confluence while using an OCT4 reporter line is easier and still quantitative, but it is not always feasible to obtain and use OCT4 reporter-containing parental cells. Finally, measuring total confluence under phase contrast is easy and applicable to any parental cell, but this approach is only semi-quantitative. Ultimately, the choice of method should depend on the available resources and the requirements of the actual experiments involved.
The methods outlined here provide a platform for comparing new reprogramming technologies, optimizing current work flows and extending the use of reprogramming to novel primary cell types.
The authors have nothing to disclose.
The authors thank Chad MacArthur for helpful discussions.
DMEM, high glucose, GlutaMAXSupplement, pyruvate | Thermo Fisher Scientific | 10569-010 | |
Fetal Bovine Serum, embryonic stem cell-qualified, US origin | Thermo Fisher Scientific | 16141-061 | |
MEM Non-Essential Amino Acids Solution (100X) | Thermo Fisher Scientific | 11140-050 | |
Trypsin-EDTA (0.05%), phenol red | Thermo Fisher Scientific | 25300-054 | |
Mouse (ICR) Inactivated Embryonic Fibroblasts | Thermo Fisher Scientific | A24903 | |
Attachment Factor Protein (1X) | Thermo Fisher Scientific | S-006-100 | |
DMEM/F-12, GlutaMAX supplement | Thermo Fisher Scientific | 10565-018 | |
KnockOut Serum Replacement | Thermo Fisher Scientific | 10828010 | |
2-Mercaptoethanol (55 mM) | Thermo Fisher Scientific | 21985-023 | |
Collagenase, Type IV, powder | Thermo Fisher Scientific | 17104-019 | |
TrypLE Select Enzyme (1X), no phenol red | Thermo Fisher Scientific | 12563-011 | |
DPBS, no calcium, no magnesium | Thermo Fisher Scientific | 14190-144 | |
Geltrex LDEV-Free, hESC-Qualified, Reduced Growth Factor Basement Membrane Matrix | Thermo Fisher Scientific | A1413302 | |
Essential 8 Medium | Thermo Fisher Scientific | A1517001 | |
FGF-Basic (AA 1-155) Recombinant Human Protein | Thermo Fisher Scientific | PHG0264 | |
UltraPure 0.5M EDTA, pH 8.0 | Thermo Fisher Scientific | 15575-020 | |
Bovine Albumin Fraction V (7.5% solution) | Thermo Fisher Scientific | 15260-037 | |
HEPES (1 M) | Thermo Fisher Scientific | 15630-080 | |
Penicillin-Streptomycin (10,000 U/mL) | Thermo Fisher Scientific | 15140-122 | |
InSolution Y-27632 | EMD Millipore | 688001 | |
CytoTune-iPS Sendai Reprogramming Kit | Thermo Fisher Scientific | A1378001 | |
CytoTune-iPS 2.0 Sendai Reprogramming Kit | Thermo Fisher Scientific | A16517 | |
Countess II Automated Cell Counter | Thermo Fisher Scientific | AMQAX1000 | |
Countess Cell Counting Chamber Slides | Thermo Fisher Scientific | C10228 | |
BJ ATCC Human Foreskin Fibroblasts, Neonatal | ATCC | CRL-2522 | |
DF1 Adult Human Dermal Fibroblast | Thermo Fisher Scientific | N/A | |
BG01V/hOG Cells Variant hESC hOct4-GFP Reporter Cells | Thermo Fisher Scientific | R7799-105 | |
IncuCyte ZOOM | Essen BioScience | ||
SSEA-4 Antibody, Alexa Fluor 647 conjugate (MC813-70) | Thermo Fisher Scientific | SSEA421 | |
SSEA-4 Antibody, Alexa Fluor 488 conjugate (eBioMC-813-70 (MC-813-70)) | Thermo Fisher Scientific | A14810 | |
SSEA-4 Antibody (MC813-70) | Thermo Fisher Scientific | 41-4000 | |
TRA-1-60 Antibody (cl.A) | Thermo Fisher Scientific | 41-1000 | |
CD44 Rat Anti-Human/Mouse mAb (clone IM7), PE-Cy5 conjugate | Thermo Fisher Scientific | A27094 | |
CD44 Alexa Fluor 488 Conjugate Kit for Live Cell Imaging | Thermo Fisher Scientific | A25528 | |
CD44 Rat Anti-Human/Mouse mAb (Clone IM7) | Thermo Fisher Scientific | RM-5700 (no longer available) | |
Goat anti-Mouse IgG (H+L) Secondary Antibody, Alexa Fluor 488 conjugate | Thermo Fisher Scientific | A-11029 | |
Goat anti-Rat IgG (H+L) Secondary Antibody, Alexa Fluor 594 conjugate | Thermo Fisher Scientific | A-11007 | |
Alkaline Phosphatase Live Stain | Thermo Fisher Scientific | A14353 | |
TRA-1-60 Alexa Fluor 488 Conjugate Kit for Live Cell Imaging | Thermo Fisher Scientific | A25618 | |
CD24 Mouse Anti-Human mAb (clone SN3), FITC conjugate | Thermo Fisher Scientific | MHCD2401 | |
beta-2 Microglobulin Antibody, FITC conjugate (B2M-01) | Thermo Fisher Scientific | A15737 | |
EpCAM / CD326 Antibody, FITC conjugate (VU-1D9) | Thermo Fisher Scientific | A15755 | |
CD73 / NT5E Antibody (7G2) | Thermo Fisher Scientific | 41-0200 | |
VECTOR Red Alkaline Phosphatase (AP) Substrate Kit | Vector Laboratories | SK-5100 | |
Zeiss Axio Observer.Z1 microscope | Carl Zeiss | 491912-0003-000 | |
FlowJo Data Analysis Software | FLOJO, LLC | N/A | |
Attune Accoustic Focusing Cytometer, Blue/Red Laser | Thermo Fisher Scientific | Use Attune NXT | |
S3e Cell Sorter (488/561 nm) | BIO-RAD | 1451006 | |
Falcon 12 x 75 mm Tube with Cell Strainer Cap | Corning | 352235 | |
Falcon 15 mL, high-clarity, dome-seal screw cap | Corning | 352097 | |
Falcon T-75 Flask | Corning | 353136 | |
Falcon T-175 Flask | Corning | 353112 | |
Falcon 6-well dish | Corning | 353046 | |
HERAEUS HERACELL CO2 ROLLING INCUBATOR | Thermo Fisher Scientific | 51013669 | |
Nonstick, RNase-free Microfuge Tubes, 1.5 mL | AM12450 | ||
HulaMixer Sample Mixer | 15920D |