Generation of a growth curve for iPS cells in a feeder ...€¦ · images while maintaining the...
Generation of a growth curve for iPS cells in a feeder-free culture by noninvasive image analysis. Takayuki Uozumi 1 , Hiroaki Kii 1 , Momotaro Ishikawa 1 , Chieko Nakada 1 , Hirotada Watanabe 1 , Yasuyuki Asai 2 , Yasujiro Kiyota 1 1 Instruments Company, NIKON CORPORATION, Yokohama, Japan, 2 ReproCELL, Inc, Yokohama, Japan Introduction Methods Algorithm development Confirmation of algorithm Results Conclusion Reference Maintaining the undifferentiated state of iPS cells is an essential, but difficult process to control. The process requires improvement in the following three areas: 1. Feeder-free culturing: To eliminate culture variability and to reduce culturing costs. 2. Automation: To reduce culturing costs, and to achieve consistency in the supply of iPS cells. 3. Establishment of a quantitative index: To quantify culturing status and provide a clear index for evaluation. As a means for implementing these improvements, a system has been developed for time-lapse observation of feeder-free cultures within which iPS colonies can be automatically detected and measured. The Nikon BioStation CT cell culture observation system was used to capture time-lapse images of the entire surface of a 6-well plate (100 images with a 2x objective (4x4mm)) over a 1 week period of feeder-free culturing (using ReproCELL ReproFF2), from seeding to passage. Once a culture dish is inserted and an observation schedule is set, the system automatically captures images while maintaining the observation position even with daily medium replacements, allowing the growth of each colony to be tracked with ease. CL-Quant image analysis software was taught to detect iPS colonies, thus allowing iPS colonies to be identified within phase-contrast images. Changes within each colony were measured and plotted as a colony growth curve which could then be summarized per well, each representing a distinct culturing condition. The system was used to generate growth curves for iPS cells cultured over a 1 week period (from seeding to passaging) while their undifferentiated state was maintained. Quantifying the rate of growth and comparing it to the undifferentiated state established a benchmark for this process. iPS cell culture and growth Colony detection & calculation flow Algorithm development Nikon has developed an algorithm that enables temporal quantitative analysis of colony proliferation, from immediately after cell seeding to cell confluence. Comparison of results from detection using algorithm and manual detection Manual versus auto-detection with CL-Quant calculations were made. The results were similar from center to edge of dish. Experiment 1) Using the CL-Quant algorithm for standard cell culture CL-Quant enables image analysis of standard 1 week iPS cell-culture sequence. Experiment 2) Comparison of cell seeding density The results indicate that growth of colonies depends on seeding density (for 1 week cell cultivation). Experiment 3) Drug addition CL-Quant quantifies the influence of Tzv-addition, which affects a cell’s survival rate. 201B7 etc Step 1) Colony detection Step 2) Merging detection Step 3) Calculation Image acquisition Image analysis iPS cell culture and growth iPS cells were generated from adult human dermal fibroblast (HDF) by retoroviral transduction of four factors: Oct3/4, Sox2, Klf4, and c-Myc [1]. Six days after transduction, the cells were harvested by trypsinization and plated onto feeder free cells using a 6-well plate. Repro FF2 medium ReproCELL was used. Image acquisition Phase contrast images of a 6-well plate were acquired using BioStation CT (NIKON CORPORATION) at 37℃ , 5% CO 2 . High-precision repeatability: Accurate tracing of same cells, as well as X-Y positions (±5µm) for each vessel. Full Scan mode (2x) was set for acquiring full-well tiling images. Image analysis Full-well tiling images were loaded into CL-Quant software (NIKON CORPORATION) and stitched to create 10,000-by-10,000 pixel composite images for analysis. All image analyses (colony segmentation, measurement etc.) were performed using functions built into CL-Quant software [2]. Basic condition (1 week) Culture conditions Cell: hiPSs:201B7, Coating: Matrigel, Culture vessel: 6-well plate, Culture medium: ReproFF2, Medium change: Mon, Wed, Fri/1 week Capture conditions Magnification: x2 (Full scan), Culture day: 1 week, Imaging interval: 3 or 12 hours Experiment procedures Culture conditions Cell: hiPSs:201B7, Coating: Matrigel, Culture vessel: 6 well plate, Culture medium: ReproFF2 Medium change: Mon, Wed, Fri/ 1 week Capture conditions Magnification: x2 (Full scan), Culture day: 2 weeks, Imaging interval: 12hours Experiment procedures Culture conditions Cell: hiPSs:201B7, Coating: Matrigel, Culture vessel: 6 well plate, Culture medium: ReproFF2 Medium change: Mon, Wed, Fri/ 1 week Capture conditions Magnification: x2 (Full scan), Culture day: 1 week, Imaging interval: 12hours Experiment procedures Culture conditions Cell: hiPSs:201B7, Coating: Matrigel, Culture vessel: 6 well plate, Culture medium: ReproFF2 Medium change: Mon, Wed, Fri/ 1 week Capture conditions Magnification: x2 (Full scan), Culture day: 2 weeks, Imaging interval: 3 hours Experiment procedures Culture condition Cell: hiPSs:201B7, Coating: Matrigel, Culture vessel: 6 well plate, Culture medium: ReproFF2 Medium change: Mon, Wed, Fri/ 1 week Capture conditions Magnification: x2 (Full scan), Culture day: 5 days, imaging interval: 3 hours Thiazovivin Mechanism Overview Description Tzv is a novel ROCK inhibitor and Rho-ROCK axis regulates cell-ECM and cell-cell adhesion. Thiazovivin protects human embryonic stem cells (hESCs) in the absence of ECM by regulating E-cadherin mediated cell-cell interaction [3]. This observation suggests that Thiazovivin promotes cell survival. Thiazovivin, in combination with inhibitors of the TGF-ß receptor and MEK pathway, has shown to improve reprogramming efficiency by more than 200-fold [4]. 1. Takahashi, K,. Yamanaka. S. Induction of pluripotent stem cells from adult human fibroblasts by defined factors. Cell. (2007) Nov 30;131(5):861-72. 2. Alworth, SV., Watanabe, H. & Lee, JSJ. Teachable, High-Content Analytics for Live-Cell, Phase Contrast Movies. J Biomol Screening. (2010) 8, 968-977. 3. Xu, Y., Ding, S. Revealing a core signaling regulatory mechanism for pluripotent stem cell survival and self-renewal by small molecules. Proc Natl Acad Sci USA. (2010) 107: 8129-8134. 4. Lin, T., Ding, S. A chemical platform for improved induction of human iPSCs. Nature Methods (2009) 6: 805-808. (URL:https://www.stemgent.com/products/show/72) 1. Nikon has developed an algorithm that enables quantitative analysis of colony proliferation, from immediately after cell seeding to confluency. Comparing manmade and algorithm-detection, the correlation factors in full image areas have similar results: 0.98 at the center of the dish, and 0.99 at edge. 2. CL-Quant enables analysis of effects under various conditions. • Colony area proliferation depends on cell seeding density. • CL-Quant quantifies the effects of thiazovivin density. CL-Quant has achieved non-invasive quantification of change of culture conditions of iPS cells in a feeder-free culture, based on the ratio of colony/bottom of dish area. Experimental procedure Culture condition Cell: hiPSs:201B7, Coating: Matrigel, Culture vessel: 6 well plate, Culture medium: ReproFF2 Medium change: Mon, Wed, Fri/ 1 week Capture condition Magnification: x2 (Full scan), Culture day: 1 week, Imaging interval: 3hours Colony detection1 (whole area) Colony detection 2 (area of well edge) Colony Detection 3 (black regions) Merged Orange = non-well region Purple = center region Green = colony detected in this step Colony region (=Sc) is changed with timelapse. Well region (=Sw) is same with timelapse. R is ratio of colony to well Calculating area of colony region Calculating area of well region Calculating a ratio of colony to well 0h 120h 180h 240h 336h Area ratio Colony / to well Manual Manual CL-Q Mask Original Mask Original CL-Q Time (hours) Time Center Edge Center Edge Downsizing (50%) Original Image Area classification by intensity Well & non-well Center of well Manual CL-Q Manual CL-Q 0 144 60 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 Sample 1 (control) Sample 2 (1.0÷m) Sample 5 (10÷m) 0 0 60 144 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 60 120 144 0 0.04 0.02 0.06 0.08 0.1 Sample 1 (control) Sample 2 (1.0÷M) Sample 5 (10÷M) 0h 0h 0h 60h 60h 60h (x0.5) 10μM (x1) 1.0μM (x2) Control 144h 144h 144h Area Ratio Area Ratio Area Ratio Time (hours) Time (hours) After Before Medium change Time (hours) + + 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0 12 24 36 48 60 72 84 96 10 8 12 0 13 2 14 4 15 6 16 8 18 0 19 2 20 4 21 6 22 8 24 0 Sc Sw R= Sc Sw At the center of the dish, the correlation factor of CL-Quant-made and manual area calculations are 0.98. At the edge of the dish, the correlation factor of CL-Quant-made and manual area calculations are 0.99. This shows that CL-Quant enables high accuracy area calculation from center to edge of dish. 0 0.2 0.4 0.6 0.8 1 Sample 1 Sample 2 Sample 3 60 120 180 240 300 1 week culture schedule FRI SAT SUN MON FRI TUE WED THU 0 20000 40000 60000 80000 100000 120000 140000 160000 180000 0 50000 100000 150000 200000 0 10000 20000 30000 40000 50000 60000 70000 80000 90000 0 20000 40000 60000 80000 100000
Transcript of Generation of a growth curve for iPS cells in a feeder ...€¦ · images while maintaining the...
Generation of a growth curve for iPS cells in a feeder-free culture by noninvasive image analysis. Takayuki Uozumi1, Hiroaki Kii1, Momotaro Ishikawa1, Chieko Nakada1, Hirotada Watanabe1, Yasuyuki Asai2, Yasujiro Kiyota1
1 Instruments Company, NIKON CORPORATION, Yokohama, Japan, 2 ReproCELL, Inc, Yokohama, Japan
Introduction
Methods
Algorithm development
Confirmation of algorithm
Results
Conclusion
Reference
Maintaining the undifferentiated state of iPS cells is an essential, but difficult process to control. The process requires improvement in the following three areas: 1. Feeder-free culturing: To eliminate culture variability and to reduce culturing costs. 2. Automation: To reduce culturing costs, and to achieve consistency in the supply of iPS cells.3. Establishment of a quantitative index: To quantify culturing status and provide a clear index for evaluation.As a means for implementing these improvements, a system has been developed for time-lapse observation of feeder-free cultures within which iPS colonies can be automatically detected and measured. The Nikon BioStation CT cell culture observation system was used to capture time-lapse images of the entire surface of a 6-well plate (100 images with a 2x objective (4x4mm)) over a 1 week period of feeder-free culturing (using ReproCELL ReproFF2), from seeding to passage. Once a culture dish is inserted and an observation schedule is set, the system automatically captures images while maintaining the observation position even with daily medium replacements, allowing the growth of each colony to be tracked with ease.CL-Quant image analysis software was taught to detect iPS colonies, thus allowing iPS colonies to be identified within phase-contrast images. Changes within each colony were measured and plotted as a colony growth curve which could then be summarized per well, each representing a distinct culturing condition.The system was used to generate growth curves for iPS cells cultured over a 1 week period (from seeding to passaging) while their undifferentiated state was maintained. Quantifying the rate of growth and comparing it to the undifferentiated state established a benchmark for this process.
iPS cell culture and growth
Colony detection & calculation flow
Algorithm developmentNikon has developed an algorithm that enables temporal quantitative analysis of colony proliferation, from immediately after cell seeding to cell confluence.
Comparison of results from detection using algorithm and manual detectionManual versus auto-detection with CL-Quant calculations were made. The results were similar from center to edge of dish.
Experiment 1) Using the CL-Quant algorithm for standard cell cultureCL-Quant enables image analysis of standard 1 week iPS cell-culture sequence.
Experiment 2) Comparison of cell seeding densityThe results indicate that growth of colonies depends on seeding density (for 1 week cell cultivation).
Experiment 3) Drug additionCL-Quant quantifies the influence of Tzv-addition, which affects a cell’s survival rate.
201B7 etc
Step 1) Colony detection Step 2) Merging detection
Step 3) CalculationImage acquisition Image analysis
iPS cell culture and growth�iPS cells were generated from adult human dermal fibroblast (HDF) by retoroviral transduction of four factors: Oct3/4, Sox2, Klf4, and c-Myc [1]. �Six days after transduction, the cells were harvested by trypsinization and plated onto feeder free cells using a 6-well plate. Repro FF2 medium ReproCELL was used.
Image acquisition�Phase contrast images of a 6-well plate were acquired using BioStation CT (NIKON CORPORATION) at 37℃ , 5% CO2.�High-precision repeatability: Accurate tracing of same cells, as well as X-Y positions (±5µm) for each vessel.�Full Scan mode (2x) was set for acquiring full-well tiling images.
Image analysis�Full-well tiling images were loaded into CL-Quant software (NIKON CORPORATION) and stitched to create 10,000-by-10,000 pixel composite images for analysis.�All image analyses (colony segmentation, measurement etc.) were performed using functions built into CL-Quant software [2].
Basic condition (1 week)�Culture conditions Cell: hiPSs:201B7, Coating: Matrigel, Culture vessel: 6-well plate, Culture medium: ReproFF2, Medium change: Mon, Wed, Fri/1 week�Capture conditions Magnification: x2 (Full scan), Culture day: 1 week, Imaging interval: 3 or 12 hours
Experiment procedures� Culture conditions Cell: hiPSs:201B7, Coating: Matrigel, Culture vessel: 6 well plate, Culture medium: ReproFF2 Medium change: Mon, Wed, Fri/ 1 week�Capture conditions Magnification: x2 (Full scan), Culture day: 2 weeks, Imaging interval: 12hours
Experiment procedures�Culture conditions Cell: hiPSs:201B7, Coating: Matrigel, Culture vessel: 6 well plate, Culture medium: ReproFF2 Medium change: Mon, Wed, Fri/ 1 week�Capture conditions Magnification: x2 (Full scan), Culture day: 1 week, Imaging interval: 12hours
Experiment procedures�Culture conditions Cell: hiPSs:201B7, Coating: Matrigel, Culture vessel: 6 well plate, Culture medium: ReproFF2 Medium change: Mon, Wed, Fri/ 1 week�Capture conditions Magnification: x2 (Full scan), Culture day: 2 weeks, Imaging interval: 3 hours
Experiment procedures�Culture condition Cell: hiPSs:201B7, Coating: Matrigel, Culture vessel: 6 well plate, Culture medium: ReproFF2 Medium change: Mon, Wed, Fri/ 1 week�Capture conditions Magnification: x2 (Full scan), Culture day: 5 days, imaging interval: 3 hours
Thiazovivin Mechanism OverviewDescription Tzv is a novel ROCK inhibitor and Rho-ROCK axis regulates cell-ECM and cell-cell adhesion.Thiazovivin protects human embryonic stem cells (hESCs) in the absence of ECM by regulating E-cadherin mediated cell-cell interaction [3]. This observation suggests that Thiazovivin promotes cell survival. Thiazovivin, in combination with inhibitors of the TGF-ß receptor and MEK pathway, has shown to improve reprogramming efficiency by more than 200-fold [4].
1. Takahashi, K,. Yamanaka. S. Induction of pluripotent stem cells from adult human fibroblasts by defined factors. Cell. (2007) Nov 30;131(5):861-72. 2. Alworth, SV., Watanabe, H. & Lee, JSJ. Teachable, High-Content Analytics for Live-Cell, Phase Contrast Movies. J Biomol Screening. (2010) 8, 968-977.3. Xu, Y., Ding, S. Revealing a core signaling regulatory mechanism for pluripotent stem cell survival and self-renewal by small molecules. Proc Natl Acad Sci USA. (2010) 107: 8129-8134. 4. Lin, T., Ding, S. A chemical platform for improved induction of human iPSCs. Nature Methods (2009) 6: 805-808. (URL:https://www.stemgent.com/products/show/72)
1. Nikon has developed an algorithm that enables quantitative analysis of colony proliferation, from immediately after cell seeding to confluency. Comparing manmade and algorithm-detection, the correlation factors in full image areas have similar results: 0.98 at the center of the dish, and 0.99 at edge.2. CL-Quant enables analysis of effects under various conditions.• Colony area proliferation depends on cell seeding density.• CL-Quant quantifies the effects of thiazovivin density.CL-Quant has achieved non-invasive quantification of change of culture conditions of iPS cells in a feeder-free culture, based on the ratio of colony/bottom of dish area.
Experimental procedure�Culture condition Cell: hiPSs:201B7, Coating: Matrigel, Culture vessel: 6 well plate, Culture medium: ReproFF2 Medium change: Mon, Wed, Fri/ 1 week�Capture condition Magnification: x2 (Full scan), Culture day: 1 week, Imaging interval: 3hours
Colony detection1 (whole area)
Colony detection 2 (area of well edge)
Colony Detection 3 (black regions)
Merged
Orange = non-well regionPurple = center regionGreen = colony detected in this step
Colony region (=Sc) is changed with timelapse.Well region (=Sw) is same with timelapse. R is ratio of colony to well
Calculating area of colony region
Calculating area of well region
Calculating a ratio of colony to well
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At the center of the dish, the correlation factor of CL-Quant-made and manual area calculations are 0.98.At the edge of the dish, the correlation factor of CL-Quant-made and manual area calculations are 0.99.This shows that CL-Quant enables high accuracy area calculation from center to edge of dish.
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