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Velocity of increase in confluence decreases with time, and doubling rates get slower with time as confluence and contact inhibition increases. A shows the fold change whereas B shows the doubling rate of confluence from the stated time to 2 h. Five independent biological experiments from h feeding frequency and six independent biological experiments for h feeding frequency with paired replicate wells in each experiment for each dose and stimulus were used for statistical analysis.
Confluence at T68 was used instead of T74 for datasets without T After LIF removal, ESCs slowly lose stemness and pluripotency-maintaining transcription factors, but the culture conditions here support similar time-dependent increases in confluence Figure 4A. Similarly, instantaneous entry into the S-G2-M-phase showed a sharp increase from the unfed to fed states, though ND culture has a shallower increase than NS Figure 4B.
A Cells were measured in time-lapse every 2 hours for confluence in the live imager. Three highest PFOA doses suppress entry into the cell cycle, but only the two highest doses suppress the lagging phase accumulated growth measured by confluence.
A Cells were measured in time-lapse every two hours for confluence in the live imager. As the cells grow for a longer period, the effect of the doses increases, causing the LOEL to be a lower dose. B Green cell cycle entry into the S-G2-M-phase was measured simultaneously with confluence measurements in A and after feeding at day 1 and 2.
In general, the green peak decreases as the dose of PFOA increases. NS 0 dose : N is described in Figure 1. PFOA: four biological experiments. Analyses of the stimulation indices from the line graphs, now graphed as histograms, also show that PFOA suppresses accumulated growth as a lagging indicator measured by confluence Figure 6A and suppresses entry into the S-G2-M phase after medium change as a leading indicator Figure 6B predicted during ESC culture with LIF.
In Figure 6A , Tfinal confluence means decrease with dose, but a second measure, the direness index, measures the first hour of departure of significantly decreased confluence compared with NS, 0 mM PFOA dose. In general, the green fold change decreases as the dose of PFOA increases.
The day 1 peak, occurring after the T24 feeding, shows a clearer trend and is less noisy than the day 2 peak which occurs after the T48 feeding. In Figure 6C , a benchmark analysis of the point of departure was used to assess the dose of significant decrease compared with 0 mM sorbitol and normal stemness and such as Tfinal in Figure 6A , is accompanied by the direness significant point of departure for diminished confluence.
As data of the confluences of the wells before the first feeding of the toxicant are not known, T0 was used 2 h after the first feeding for NS. The direness points of departure from Figure 5A are shown in the day 3 bars. B The amount of green fluorescence at the peak after feeding and the nadir before feeding is rationated.
Direness points of departure are shown in Figure 5A. All the models were deemed questionable. DEP suppresses accumulated growth as a lagging indicator measured by confluence and suppresses entry into the S-G2-M phase after medium change as a leading indicator predicted during ESC culture with LIF.
Red asterisks show when confluence starts to significantly differ from NS. For higher doses, the divergence points are realized earlier T58for 10 uM and T52 for uM. The rest of the doses are not significantly different than NS at T B Simultaneously, confluence green fluorescence was measured in time-lapse every two h in the live imager. Green intensity increases cells enter the S-G2-M phase after cells are fed at approximately T24 and T Offsets in the timing of the zero dose and the rest of the curves are due to feeding differences between experiments.
NS 0 dose : N described in Figure 1. As data of the confluences of the wells before the first feeding of the toxicant are not known, T0 used was the first time-lapse recorded T2 for NS. B The amount of green intensity at the peak after feeding and the nadir before feeding are rationated. In general, the green fold change decreases as the dose of DEP increases. DEP: N is described in Figure 7. A FUCCI, Pdgfra, and Oct4 ESC were cultured and assayed as shown in Figure 4 , except confluence increase and doubling rate were both measured in the first 24 h when rate of increase was highest and not as affected by contact inhibition.
Confluence fold change from timepoints T2 to end of day 1 is shown. B During the culture of the same three ESC lines from T2—T26, change in confluence was used to compute the doubling rate. First, the suppression of accumulated cells at Tfinal looks backward at stress effects through culture, and both PFOA and DEP suppress ESC accumulation albeit at different doses and levels of suppression.
Second, the prediction of future cell growth can be done early in culture before contact inhibition obscures the growth of fastest growing stress-free controls.
This predictive assay is based on the suppression of the progression into the green S-G2-M phase of the cell cycle after medium change relieves G1 delay. Third, live imaging provides a time lapse report of when the first significant adverse suppression of ESC accumulation occurs compared to lesser stress doses. Thus, DEP suppression of future growth on day 1 is reversible by day 2. Toxicity can be thought of as a product of the lowest dose that a LOAEL is detected at and the magnitude of the toxic effects.
Thus, for PFOA the time-lapse point of departure is much earlier. Is it reasonable to see early time point effects? Diminished cell growth is not the cause of lower accumulation at the highest dose— uM PFOA; since fewer cells are present than at Tzero, death must account for this first point of departure.
This is consistent with the effects of stress enzymes that diminish Oct4, Sox2, Nanog, and Rex1 protein levels by 4 h and are activated highly by 1 h of hyperosmotic stress which slows growth rapidly Slater et al.
Although Oct4, Sox2, and Nanog protein levels return to normal by 24 h of hyperosmotic stress, Rex1 is maintained at lower levels by Mek1 at 1—4 h and SAPK at 24 h, respectively Slater et al.
Yet, the effects of Rex1 suggest that some stemness features have decreased within 2—4 h, and these decreases persist. Rex1 and Oct4 control the metabolic programs of stemness that control growth rates Frum et al. Time-lapse direness assayed here is also likely to be based on the large programmatic effects of these rate-limiting stemness factors.
So, it can be concluded that hyperosmotic stress at mM sorbitol or similar effects of 10— uM PFOA have early higher effects both on growth and stemness at higher doses and lesser effects at longer durations, as indicated by data here and in previous reports where the metabolism and stemness change over time. It will be important to determine using transcriptomic analysis if PFOA also induces changes in metabolism and stemness that are induced by hyperosmotic stress Abdulhasan et al. This delay in G1 by h feeding was not anticipated, and the analysis of re-entry and its suppression by stress produced interesting outcomes.
Unlike the assay of accumulation, re-entry after feeding into the S-G2-M-phase predicts future growth and its suppression by environmental toxicants. Thus, early suppression of re-entry by DEP is exceedingly small at the highest dose and is very sensitive, occurring at the lowest dose, but is reversible. It will be interesting to test for long-term changes in anabolic and epigenetic transcriptomes in reversible DEP vs irreversible PFOA exposures to find whether brief reversible stress episodes have long-term effects.
This may be because the green suppression is only on day 1 and it reverses so that overall, the cell growth is not suppressed by a large amount. In one report, PFOA exposure alone in the first trimester did not affect later pregnancy, but PFOA and cigarette smoke co-exposure negatively affected fetal growth at a later stage Mamsen et al.
A study of human embryonic and fetal tissues obtained in Denmark from —15 found that by the end of the first trimester, PFOA was the second highest PFAS family member in maternal blood, placenta, and many fetal organs with PFOS being the highest Mamsen et al.
Thus, PFOA crosses the placenta early and accumulates in the fetal organs. Taken together, the data suggest that first trimester PFOA exposures cross the placenta and enter fetal organs and are associated with increased pregnancy loss or decreased fetal growth.
In the environment, point exposures such as ground water in Little Hocking OH were 1 uM Vestergren and Cousins, , and worldwide average blood exposures were 5—20 nM Vestergren and Cousins, The highest level was found in cord blood, and thus the fetus or embryo was also 20 nM Negri et al. Thus, the BMDL doses reported to affect ESC accumulation of cell cycle progression are within the limit of maternal blood and cord blood exposures.
DEP harms animal and human reproduction Radke et al. DEP increases the body weight of F1 after in utero exposure in rodents, decreased the growth rate of cord blood—derived hematopoietic stem cells, and decreased BMI in humans.
Phthalates affect the first trimester placenta by changing its transcriptome and methylome Grindler et al. Although DEP was not studied, many phthalates elevated in first trimester maternal blood are also associated with DNA methylation changes in the offspring LaRocca et al.
Thus, phthalates, in general, and DEP, specifically, cross the placenta, are detected in cord blood, and have first trimester effects that should be predicted by screening cultured ESCs that emulate first trimester embryogenesis.
We report the slowing of the cell cycle here with environmental toxic stressors, consistent with the slowing of the cell cycle using positive control hyperosmotic stress reported previously Slater et al. Interestingly, as the cell cycle is slowed down experimentally with hyperosmotic stress, it has been reported that G1 delay is associated with increased endoderm differentiation and less neuronal differentiation Coronado et al.
Thus, it will be important to test whether experimental stressors also override stemness and proliferation signals from LIF and imbalance forced differentiation similarly to hyperosmotic stress. Unlike previous growth measurements of stressed ESCs, time-lapse measurements given here were done by the analysis of confluence. The discrepancy is likely due to the live imager use of confluence of an ESC epithelium that is squamous near Tzero and columnar near Tfinal and that the higher density of the columnar is missed by the confluence-based cell number and doubling rate estimates.
These discrepancies can be remedied by use of a technique that counts the number of cells instead of measuring confluence. For this initial report, the conclusions reached should be valid but would be more accurate with object-based, rather than confluence-based, estimates of growth rates. Interestingly, the use of a live imager to monitor cell cycle progression of FUCCI ESCs has not been reported, and cell cycle timing is usually evaluated by synchronizing the cells by serum starvation, Zielke and Edgar, and not partially synchronized by medium change as performed here.
This exit or abnormal delay in non-green G1 does occur with serum starvation prior to cell cycle synchronization, which occurs when G1 phases as short as one h in FUCCI-ESCs have been reported, but serum starvation is delayed for 24 h Sakaue-Sawano et al.
The delay in the non-green G1 phase could be due to increased lactate acidosis, due to aerobic glycolytic anabolic metabolism enabling rapid ESC cycles, or to depleted nutrition. Lactate acidosis is a problem as a report suggests that pluripotent stem cells which grow at high densities are hindered by increasing acidosis, and growth is enabled by buffering acid with sodium bicarbonate Liu et al.
Many countries have VAM committees. Taken together, the data here suggest that several measurements of normal and toxicant-modulated growth of ESCs are enabled by live imager time-lapse data for 1 confluence-based accumulated growth assay, 2 predictive cell cycle progression assay of the suppression of cell cycle progression which diminishes future accumulation, and 3 direness index Yang et al. The use of these assays should be applied to more toxicants to inform which toxicants endanger ESCs at lowest levels and fastest endpoints.
Additional endpoints of transcriptomic, epigenomic, and metabolomic nature should be used to complement growth analysis and inform teratogenic and transgenerational effects. We thank Chris Kassotis for comments on the manuscript. All authors listed have made a substantial, direct, and intellectual contribution to the study and approved it for publication.
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors, and the reviewers.
Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher. Front Toxicol. Published online Nov Harris , 4 Douglas M. Ruden , 1 , 4 Awoniyi O. Awonuga , 1 Ayesha Alvero , 1 , 3 Elizabeth E. Puscheck , 1 , 2 , 5 and Daniel A.
Sean M. Douglas M. Awoniyi O. Elizabeth E. Daniel A. Author information Article notes Copyright and License information Disclaimer. Corresponding author.
Rappolee, ude. This article was submitted to Regulatory Toxicology, a section of the journal Frontiers in Toxicology. Received May 14; Accepted Sep The use, distribution or reproduction in other forums is permitted, provided the original author s and the copyright owner s are credited and that the original publication in this journal is cited, in accordance with accepted academic practice.
No use, distribution or reproduction is permitted which does not comply with these terms. This article has been cited by other articles in PMC. Keywords: HTS, high through put screening, perfluorinated alkylated substances, phthalates, developmental toxicity, embryonic stem cell, stress, viable cell count studies.
Introduction Comprehensive in vitro developmental toxicity DevTox assays are controversial, and the current standard is in vivo rodent gestational testing for the Extended One-Generation Reproductive Toxicity Study Beekhuijzen et al. Statistical and Graphical Analyses Initial data analysis was conducted using acquisition software and was provided by IncuCyte Zoom Sartorius, version B This software analyzed the pictures to calculate the confluence and total green object integrated intensity of each well at each timepoint.
Open in a separate window. Author Contributions All authors listed have made a substantial, direct, and intellectual contribution to the study and approved it for publication. Featured Software Modules. Explore more. Additional Software Modules. System Software Updates. Resources and Support. How can we assist you? What are you mainly interested in? What other areas are you interested in? Lab Water Purification.
Pipetting and Dispensing. Cell Analysis - Live Cell Analysis. Cell Analysis - Advanced Flow Cytometry. Lab Filtration and Purification. Microbiological Testing.
Incucyte zoom 2016b download
Gain insights into biological processes of cells in real time via non-perturbing quantitative analysis. Ideal if you use your Incucyte intensively as it keeps data on-line and at your fingertips for longer.
The content of our website is always available in English and partly in other languages. Choose your preferred language and we will show you the content in that language, if available. Stress-free Image Acquisition Guided interface enables even first-time users to set up long-term, live-cell experiments Flexible scheduling tool allows multiple users to run multiple applications in parallel.
Powerful, Purpose-built AI-driven Analysis Guided interface makes processing thousands of wells of data easier, driven by AI or Classic segmentation Graphing tools designed by biologists enable publication-ready graphs without the need for third-party software. Ordering Information. Software Module Description Cat. Add-on Software Modules. Classifier is trained using control wells.
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What other areas are you interested in? Lab Water Purification. Pipetting and Dispensing. Cell Analysis - Live Cell Analysis. Cell Analysis - Advanced Flow Cytometry. Lab Filtration and Purification. Microbiological Testing. Moisture Analysis. The content of our website is always available in English and partly in other languages.
Choose your preferred language and we will show you the content in that language, if available. Simply click on all sites that you wish to export. Graph-on-Graph — Drag and drop to combine two graphs onto either one or two y axes.
Right-click on a graph and drag it to the second graph to combine. New Proprietary DF Brightfield for 3D Cell Cultures — Generate high quality, high contrast brightfield images with an extended depth of focus to enable robust image segmentation. Upgrade Now. Related Products. View Product. Related Applications. Multi-Spheroid Assays View Application. How can we assist you? What are you mainly interested in? What other areas are you interested in?
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Incucyte zoom 2016b download
A guided interface and purpose-built tools make the process of acquiring, viewing, analyzing and sharing images of living cells easier than ever before using the Classic or new AI-driven Analysis. AI-driven Confluence Analysis provides a simple workflow for highly accurate segmentation of cells in phase contrast images, adapting to a wide range of cell types and morphologies with minimal user input.
By viewing images of all locations in your experiment at once, you can quickly assess treatment effects or identify outliers. You can also overlay metrics for rapid assessment and verification of image processing parameters. Then, generate presentation-ready images and movies with just a few clicks. Easily view images of all locations in an experiment at once to scan for trends and outliers, then zoom in on wells of interest.
By providing purpose-built tools to answer your scientific questions, image processing and analysis is uncomplicated yet extremely powerful. Create analysis definitions once, then reapply to subsequent experiments to generate real-time metrics that enable decision-making. Guided analysis interface enables even first-time users to convert images into insights using powerful AI-driven or classic segmentation for confluence measurements. Graphing tools enable review of trends and rapid generation of publication- and presentation-ready graphs.
Perform label-free cell counts and subsequent cell-by-cell classification based on shape, size or fluorescence intensity to quantify dynamics changes in cell subsets within heterogenous living cell cultures. Characterize the differentiation and maturation of organoid cultures in or well plates and assess treatment effects on organoid growth in well microplates.
Analyze growth, viability or invasion of single spheroids in round- bottom multi-well format or measure multiple spheroid in flat bottom plates to detect changes of growth or viability. Enables label-free or fluorescence analysis of neurite outgrowth, maturation or disruption in each well in or well plates. Track and quantify label-free and fluorescence labeled chemotaxis cell migration and invasion in microplate format. Assess complex network development and disruption qualitatively to study therapeutic interventions of vascular formation.
Gain insights into biological processes of cells in real time via non-perturbing quantitative analysis. Ideal if you use your Incucyte intensively as it keeps data on-line and at your fingertips for longer. The content of our website is always available in English and partly in other languages.
Choose your preferred language and we will show you the content in that language, if available. Stress-free Image Acquisition Guided interface enables even first-time users to set up long-term, live-cell experiments Flexible scheduling tool allows multiple users to run multiple applications in parallel.
Powerful, Purpose-built AI-driven Analysis Guided interface makes processing thousands of wells of data easier, driven by AI or Classic segmentation Graphing tools designed by biologists enable publication-ready graphs without the need for third-party software.
Ordering Information. Software Module Description Cat. Add-on Software Modules. Classifier is trained using control wells.
Literature and Documentation. Related Products. Explore More. How can we assist you? What are you mainly interested in?
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