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Results: 5

1.
Figure 1

Figure 1. Models of progressing to a pluripotent state during direct reprogramming. From: Direct cell reprogramming is a stochastic process amenable to acceleration.

Four different models (i–iv) to account for the latency of donor somatic cells in progressing towards the induced pluripotent stem cell (iPSC) state following the expression of OSKM reprogramming factors. Latency can be measured in units of absolute time or cell divisions until the first iPSC is generated from a monoclonal population. Graphs display the general shape of the reprogramming kinetics in the different scenarios. Note that elite models do not necessarily reprogram more slowly as shown in the bottom plots.

Jacob Hanna, et al. Nature. ;462(7273):595-601.
2.
Figure 5

Figure 5. Distinct modes for accelerating reprogramming to pluripotency. From: Direct cell reprogramming is a stochastic process amenable to acceleration.

a, Nearly all donor cells can give rise to iPSCs via a stochastic process. Two parameters characterize the kinetics of the process: the average number of cell divisions required, Cd, and the cell-intrinsic reprogramming rate per cell division, k. b, Accelerating reprogramming in a cell division rate-dependent manner still requires as many divisions as the unaccelerated reference scenario (i.e., still Cd on average) but occurs earlier in time because cells divide faster, whereas in the cell division rate-independent mode, the cell-intrinsic rate reflecting the occurrence of unknown stochastic event(s) is enhanced and reprogramming is achieved within a lower average number of divisions (<<Cd). c, In comparison, somatic cell nuclear transfer can reprogram within 1–2 cell divisions.

Jacob Hanna, et al. Nature. ;462(7273):595-601.
3.
Figure 2

Figure 2. Long-term analysis of reprogramming monoclonal populations. From: Direct cell reprogramming is a stochastic process amenable to acceleration.

a, Schematic of experiments. b, Reprogramming of Pre-B cell monoclonal populations measured as the cumulative number of wells that became Nanog-GFP+. n indicates number of populations monitored. Asterisk indicates flow cytometry for GFP detection was performed every 4 weeks. c, Chimeric mice with agouti coat color from iPSCs derived after 12–13 weeks of DOX. d, Heavy chain rearrangements in iPSCs. e, Relative transgene induction levels of monoclonal populations on DOX. Error bars indicate standard deviation (n=3). f, The population averaged doubling time, td, for each clonal population. Boxes delineate cases where the same clonal population was measured at different times during DOX induction. Lower two lines (green) represent subcloned iPSC lines. Clone labeling: clone #, weeks on DOX (w#), Nanog-GFP >0.5% status (+/−).

Jacob Hanna, et al. Nature. ;462(7273):595-601.
4.
Figure 3

Figure 3. Cell division rate dependent and independent acceleration of reprogramming. From: Direct cell reprogramming is a stochastic process amenable to acceleration.

a, Average induction levels for transgenes in different NGFP1 cell populations. n indicates number of populations sampled per group, presented as mean ± s.d. b, Growth curves for cells on DOX. Exponential growth (dashed line) described the data well (R2=0.97–1.0), and the population-averaged doubling times (td) were calculated from these fits (Supplementary Fig. 9). c, As in Fig. 2b, latencies for reprogramming various clonal B cell derived populations. NGFP1-p53KD, NGFP1-p21KD, and NGFP1-Lin28OE wells were statistically distinct from the NGFP1 and NGFP1-control hairpin wells (p<0.0001, logrank test for dissimilarity). d, Rescaling time by td provides an estimate for the number of cell divisions occurring during latency. No statistical difference between groups was observed after rescaling time by td (p>0.1). e–f, As in c–d, but for NGFP1-NanogOE wells. n indicates number of populations monitored.

Jacob Hanna, et al. Nature. ;462(7273):595-601.
5.
Figure 4

Figure 4. Quantitative analysis of cell reprogramming. From: Direct cell reprogramming is a stochastic process amenable to acceleration.

a, Stochastic model summary. Sequential replating of individual wells during each experiment establishes that, after a time t0 representative of the time at which the replatings started, each experiment can be described in terms of a population of an effective size, Neff. b, Estimate of the population rescaled time, τ, throughout each experiment. After t0, population dynamics are effectively described by a fixed population of size, Neff. NGFP1-p53KD and NGFP1-p21KD have similar dynamics. c, Neff and the population-rescaled average proliferation times, τp, estimated as the population-rescaled time necessary for one iPSC to reach the detection threshold [τp=td,iNefflog2Neff), where ρ is the detection threshold and td,i is the doubling time of iPSCs]. d, Cumulative percentage of Nanog-GFP+ wells as a function of τ, and best fits according to the proposed model. Modeling results are in thick lines, and experiments are in dots. Right graph indicates best fit estimates of the cell-intrinsic rate k expressed in terms of weeks. e, As in d, but per population-rescaled cell divisions, τ/td, instead of per τ units. td is the doubling time of the populations. Error bars indicate 95% confidence intervals.

Jacob Hanna, et al. Nature. ;462(7273):595-601.

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