Early Acquisition of Neural Crest Competence During hESCs Neuralization

Background: Neural crest stem cells (NCSCs) are a transient multipotent embryonic cell population that represents a defining characteristic of vertebrates. The neural crest (NC) gives rise to many derivatives including the neurons and glia of the sensory and autonomic ganglia of the peripheral nervous system, enteric neurons and glia, melanocytes, and the cartilaginous, bony and connective tissue of the craniofacial skeleton, cephalic neuroendocrine organs, and some heart vessels. Methodology/Principal Findings: We present evidence that neural crest (NC) competence can be acquired very early when human embryonic stem cells (hESCs) are selectively neuralized towards dorsal neuroepithelium in the absence of feeder cells in fully defined conditions. When hESC-derived neurospheres are plated on fibronectin, some cells emigrate onto the substrate. These early migratory Neural Crest Stem Cells (emNCSCs) uniformly upregulate Sox10 and vimentin, downregulate N-cadherin, and remodel F-actin, consistent with a transition from neuroepithelium to a mesenchymal NC cell. Over 13% of emNCSCs upregulate CD73, a marker of mesenchymal lineage characteristic of cephalic NC and connexin 43, found on early migratory NC cells. We demonstrated that emNCSCs give rise in vitro to all NC lineages, are multipotent on clonal level, and appropriately respond to developmental factors. We suggest that human emNCSC resemble cephalic NC described in model organisms. Ex vivo emNCSCs can differentiate into neurons in Ret.k- mouse embryonic gut tissue cultures and transplanted emNCSCs incorporate into NC-derived structures but not CNS tissues in chick embryos. Conclusions/Significance: These findings will provide a framework for further studying early human NC development including the epithelial to mesenchymal transition during NC delamination

Human ESC-Derived Neural Crest Model Reveals a Key Role for SOX2 in Sensory Neurogenesis

The transcription factor SOX2 is widely known to play a critical role in the central nervous system; however, its role in peripheral neurogenesis remains poorly understood. We recently developed an hESC-based model in which migratory cells undergo epithelial to mesenchymal transition (EMT) to acquire properties of neural crest (NC) cells. In this model, we found that migratory NC progenitors downregulate SOX2, but then start re-expressing SOX2 as they differentiate to form neurogenic dorsal root ganglion (DRG)-like clusters. SOX2 downregulation was sufficient to induce EMT and resulted in massive apoptosis when neuronal differentiation was induced. In vivo, downregulation of SOX2 in chick and mouse NC cells significantly reduced the numbers of neurons within DRG. We found that SOX2 binds directly to NGN1 and MASH1 promoters and is required for their expression. Our data suggest that SOX2 plays a key role for NGN1-dependent acquisition of neuronal fates in sensory ganglia

Lifespan Differences in Hematopoietic Stem Cells are Due to Imperfect Repair and Unstable Mean-Reversion

<div><p>The life-long supply of blood cells depends on the long-term function of hematopoietic stem cells (HSCs). HSCs are functionally defined by their multi-potency and self-renewal capacity. Because of their self-renewal capacity, HSCs were thought to have indefinite lifespans. However, there is increasing evidence that genetically identical HSCs differ in lifespan and that the lifespan of a HSC is predetermined and HSC-intrinsic. Lifespan is here defined as the time a HSC gives rise to all mature blood cells. This raises the intriguing question: what controls the lifespan of HSCs within the same animal, exposed to the same environment? We present here a new model based on reliability theory to account for the diversity of lifespans of HSCs. Using clonal repopulation experiments and computational-mathematical modeling, we tested how small-scale, molecular level, failures are dissipated at the HSC population level. We found that the best fit of the experimental data is provided by a model, where the repopulation failure kinetics of each HSC are largely anti-persistent, or mean-reverting, processes. Thus, failure rates repeatedly increase during population-wide division events and are counteracted and decreased by repair processes. In the long-run, a crossover from anti-persistent to persistent behavior occurs. The cross-over is due to a slow increase in the mean failure rate of self-renewal and leads to rapid clonal extinction. This suggests that the repair capacity of HSCs is self-limiting. Furthermore, we show that the lifespan of each HSC depends on the amplitudes and frequencies of fluctuations in the failure rate kinetics. Shorter and longer lived HSCs differ significantly in their pre-programmed ability to dissipate perturbations. A likely interpretation of these findings is that the lifespan of HSCs is determined by preprogrammed differences in repair capacity.</p></div

Failures are Dissipated More Slowly in Shorter-lived HSCs than in Longer-lived HSCs.

<p>A: We determined the dissipation rates (yellow dots; vertical axis) relative to the lifespan (horizontal axis) using for -truncated failure rates. The lower bound of the integrand was derived in Theorem 2. To highlight the general tendency in the data, not implying any dependencies of consecutive data points, we fitted the data to a non-linear model (blue line; goodness-of-fit Akaike Information Criterion: ); parameter p-values and ). Calculation of by regressing to normal noise produced a slightly lower exponent (fitted curve indicated by green line). B: Half-lives of dissipation rates (yellow dots; vertical axis) relative to individual lifespans (horizontal axis). To highlight the general tendency in the data, we fitted the data to a non-linear model (blue line; goodness-of-fit Akaike Information Criterion: ; parameter p-values and , respectively). The model of half-lives obtained from experimental data (green line) is shown for comparison. In both graphics A and B, we used contour plots of the respective data sets and , respectively, as background.</p

The Life of A Hematopoietic Stem Cell.

<p>A: Limited lifespan: When a monoclonal hematopoietic system is initiated by transplanting a single HSC (dark blue sphere), it expands to a pool of clonal HSCs through self-renewal (cluster of blue spheres). This pool distributes through the organism. HSCs differentiate to generate mature cells of all lineages (shown as magenta, orange, green, light-blue spheres). This process depends on the intrinsic properties of the founder HSC <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003006#pcbi.1003006-Sieburg4" target="_blank">[63]</a>, <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003006#pcbi.1003006-MullerSieburg5" target="_blank">[65]</a>. The overall output of mature cells in blood (measured in %-donor type cells; vertical axis (not shown in the figure)) over time (horizontal axis labelled “Lifespan”) is indicated by the black curve. For all normal HSCs, this kinetic has a ballistic shape, thus indicating that a clone's ability to produce mature cells of all major lineages (the lifespan) is limited. The lifespan is mathematically predictable with high accuracy from few initial points of the repopulation kinetic <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003006#pcbi.1003006-Sieburg1" target="_blank">[8]</a>. B: Programmed Lifespan: When daughter HSCs derived from a single ancestral HSC are transplanted into separate hosts, the repopulation kinetics are very similar (modified from <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003006#pcbi.1003006-MullerSieburg1" target="_blank">[2]</a>). In particular, all daughter HSCs become extinct at the same time <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003006#pcbi.1003006-Sieburg1" target="_blank">[8]</a>. This suggested that the lifespan is epigenetically fixed (programmed) and heritable in self-renewal. C: Lifespan Diversity: The relialogram illustrates that when HSCs are sampled from bone marrow, lifespans of different durations are found <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003006#pcbi.1003006-MullerSieburg1" target="_blank">[2]</a>, <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003006#pcbi.1003006-MullerSieburg6" target="_blank">[66]</a>, <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003006#pcbi.1003006-MullerSieburg7" target="_blank">[67]</a>. Therefore, the length of time for which HSCs can repopulate an ablated host varies according to the epigenetic programs of individual HSCs.</p

Hurst Exponents of the Failure Rate Kinetics of Long-term Repopulating HSCs.

<p>Plotted are the Hurst exponents (plot symbol: blue triangles; values vertical axis) of the failure rate kinetics of HSCs with lifespans and months (horizontal axis). Calculations were performed using Algorithm 0 (compare Table S1 in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003006#pcbi.1003006.s001" target="_blank">Text S1</a>). All exponents are , thus falling into the region of anti-persistent behavior (defined by Hurst values (light-yellow region)) and not into the region of persistent behavior (defined by (light-pink region (only displayed up to 0.7 to enhance visibility of the data))). Our previous results <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003006#pcbi.1003006-Sieburg1" target="_blank">[8]</a> that past values of an HSC's repopulation kinetic predict future values, had suggested the hypothesis that Hurst exponents of the failure rates would either be greater, or less, than . The value is traditionally interpreted as “no memory” of past behavior in future behavior (horizontal line marked “no memory”). The data shown then suggest that, mechanistically, anti-persistence plays a role in controlling clonal growth. The values obtained from our experimental data were fitted to the line as a function of lifespan (gray solid line through the data). Goodness-of-Fit was determined using the Akaike Information Criterion (). The parameter estimates were highly significant (intercept estimate, standard error, p-value; slope estimate, standard error, p-value). The extension of the fitted line to include lifespans only serves visualization purposes, since we only considered HSCs with lifespans months. The negative slope of the linear fit predicts that anti-persistent behavior in the failure rate kinetics is more pronounced for longer-lived long-term repopulating HSCs than for shorter-lived long-term repopulating HSCs.</p

Reliability and Failure Kinetics of a Long-lived Long-term Repopulating HSC.

<p>A–D: Four types of kinetics were calculated (compare <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003006#pcbi-1003006-box001" target="_blank">Algorithm 1</a>) from experimental kinetics for all clonal cell populations together (black), and the myeloid (green), T lymphocyte (red), and B lymphocyte (gray) cell populations, separately. In the representative example shown, notation is as in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003006#pcbi-1003006-box001" target="_blank">Algorithm 1</a> (applied to a single kinetic, i.e. batch size ). Also shown are the respective kinetics for the population of clonal hematopoietic stem cells (HSCs; blue). Since population data are difficult to obtain for stem cells directly, the HSC-related kinetics were inferred from the other data. This was accomplished by first predicting the reliability (Part B, blue curve) using the structure balance <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003006#pcbi.1003006.e054" target="_blank">eq 1</a> and, then, deriving the other kinetics (blue curves for C, D, then A) with the methods of <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003006#pcbi-1003006-box001" target="_blank">Algorithm 1</a>.</p

Failure Rate Phase Space Regimes of Long-term Repopulating HSCs.

<p>Phase space plot of the failure rate kinetic of a long-term repopulating HSC with long lifespan of months. Points in the plot (red) represent successive failure rates calculated every 2 months. To facilitate visualization, regions were separated by dotted lines. After initial expansion (region E, circled point), the kinetic transitions (blue arrow) into a regime (region OU), where it remains for most of clonal life. The behavior in region is governed by an Ornstein-Uhlenbeck iterative process (compare <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003006#pcbi.1003006.e120" target="_blank">eq 4</a>). The end of clonal life is indicated by the transition (black arrow) from region to the “terminal” absorbing point in region (circled point). Region B is not visited by the dynamic trajectory and, therefore, empty.</p

Breakdown of Mean-Reverting Behavior in the Failure Rate Kinetics of Long-term Repopulating HSCs.

<p>A: An experimental failure rate kinetic (blue scatter-line plot; values vertical axis) compared to the kinetics of 100 realizations (thin red lines) of an Ornstein-Uhlenbeck process over the lifespan period (horizontal axis) of a clone with lifespan months. The realizations of the process were obtained using the iteration schema in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003006#pcbi.1003006.e120" target="_blank">eq 4</a>. The same values of , and as in the experimental data were used. For simplicity, the initial condition was set at for (equivalent to assuming a load-free transplant). The important observation is that without additional conditions on the Ornstein-Uhlenbeck process, the expected behavior of the kinetic generated from data (blue curve) will not occur. B: The moving average (vertical axis; window size = 6) of the same failure rate kinetic as in Part A (blue line-scatter curve) reveals that the parameter increases slowly during the mean-reverting regime (raw moving average data (denoted “Moving Avg ”) are in black). The slow increase changes to rapidly increasing failure rates at around 82% of the lifespan. Both behaviors combine into the model of <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003006#pcbi.1003006.e233" target="_blank">equation 9</a> with parameters , and (p-values = , , , respectively; ).</p

Derivation of hair-inducing cell from human pluripotent stem cells.

Dermal Papillae (DP) is a unique population of mesenchymal cells that was shown to regulate hair follicle formation and growth cycle. During development most DP cells are derived from mesoderm, however, functionally equivalent DP cells of cephalic hairs originate from Neural Crest (NC). Here we directed human embryonic stem cells (hESCs) to generate first NC cells and then hair-inducing DP-like cells in culture. We showed that hESC-derived DP-like cells (hESC-DPs) express markers typically found in adult human DP cells (e.g., p-75, nestin, versican, SMA, alkaline phosphatase) and are able to induce hair follicle formation when transplanted under the skin of immunodeficient NUDE mice. Engineered to express GFP, hESC-derived DP-like cells incorporate into DP of newly formed hair follicles and express appropriate markers. We demonstrated that BMP signaling is critical for hESC-DP derivation since BMP inhibitor dorsomorphin completely eliminated hair-inducing activity from hESC-DP cultures. DP cells were proposed as the cell-based treatment for hair loss diseases. Unfortunately human DP cells are not suitable for this purpose because they cannot be obtained in necessary amounts and rapidly loose their ability to induce hair follicle formation when cultured. In this context derivation of functional hESC-DP cells capable of inducing a robust hair growth for the first time shown here can become an important finding for the biomedical science