The goal of this work was to produce a kinetic analysis of NT-3 signaling in ESNPCs that provides insight into the intracellular processes that promote neuronal differentiation. Many different growth factors and their respective signaling pathways have been implicated in neuronal differentiation, such as the Wnt, bone morphogenic protein, and Shh.34–36
However, this study chose to focus on NT-3 because of its ability to promote neuronal differentiation of stem cells seeded inside of 3D scaffolds for tissue engineering applications and to take advantage of previous work characterizing the MAP kinase cascade.14,24–27,30,32
To achieve this goal of producing a kinetic analysis, it was hypothesized that the mechanism of NT-3–induced differentiation in ESNPCs was due to activation of the MAP kinase cascade, which would promote the production of the transcription factor Mash1. Upregulation of Mash1 has been shown to promote differentiation of mouse ES cells into neurons.19,20
The experimental data in support this hypothesis, showing the activation of MAP kinase cascade in ESNPCs in response to NT-3 stimulation as indicated by levels of phosphoErk present. Based on this experiment, a kinetic analysis of MAP kinase signaling for ESNPCs was implemented using rate constants taken from the literature and select protein concentrations estimated experimentally from mRNA levels. To determine which protein concentrations should be estimated, the differences in concentrations for the signaling pathway components were compared between two cell lines that had already been characterized: HeLa and PC12 cells. If the concentrations were within the same order of magnitude, then the values for the PC12 cells were used in the analysis. Otherwise, real-time RT-PCR was used to estimate the concentration of protein present in the ESNPCs based on mRNA levels.
To estimate the protein concentrations, real-time RT-PCR was used to determine the relative expression of Trk receptor, Shc, Mek, and Erk in PC12 cells and 4−/4+ EBs containing ESNPCs, and theses data were combined with previous data from the literature to approximate the protein concentrations in the ESNPCs. These results were confirmed qualitatively using Western blots. The expression of the TrkA receptor in PC12 was approximately 2.4 times greater than the expression of the TrkC receptor in the ESNPCs. This result is expected because PC12 cells express high levels of the TrkA receptor, which allows them to be responsive to NGF. Conversely, the ESNPCs expressed higher levels of mRNA encoding Shc, Mek, and Erk compared to the PC12 cells. This result followed the same trend like the HeLa cells, which also express more Mek and Erk compared to the PC12 cells. Sensitivity analysis revealed that the concentrations of the upstream components (TrkC receptor and Shc) had a greater effect on the outcome of the kinetic analysis compared to the downstream components (Mek and Erk).
The results of the kinetic analysis can be seen in . The system appears to demonstrate a switch-like behavior where at low concentrations, only small amounts of Erk become activated, and at higher concentrations, a large peak of activated Erk is observed. This shift in activation occurs in between the 4 and 8 ng/mL doses of NT-3. To confirm this kinetic analysis experimentally, two values were chosen on each side of this switch point to test this prediction. A dose of 2 ng/mL of NT-3 was predicted to not activate large amount of Erk, while 10 ng/mL of NT-3 was predicted to produce a peak of Erk activation after stimulation. Sensitivity analysis suggested that this behavior would be observed even if the estimated protein concentrations for the ESNPCs were perturbed as shown in . These results were confirmed experimentally by comparing them to the predicted values from the analysis ().
The kinetic analysis accurately predicted what doses of NT-3 would generate an activation peak, and it also predicted that 25 ng/mL NT-3 would activate the MAP kinase cascade more rapidly than 10 ng/mL of NT-3. The analysis predicted that 25 ng/mL of NT-3 would produce a sharp peak in phosphoErk around 45 min after stimulation with ~60% of the total Erk being phosphorylated. The experimental data showed that this peak did occur at the 45 min time point when ~40% of the total Erk was phosphorylated. Similarly, for the 10 ng/mL of NT-3 dose, the analysis predicted that activation would occur more slowly around 90 min after NT-3 stimulation with ~40% of the total Erk activated. The experimental data showed peak activation occurring at 90 min with ~50% of the total Erk activated. This peak was flatter compared to the sharp peak that was observed for the 25 ng/mL of NT-3. The predicted peak for the 10 ng/mL of NT-3 dose decreased more rapidly than the curve obtained from the experimental data. This result could be due to the error present during quantification of the activated phosphoErk or from the experimental error during the RT-PCR experiments used to estimate the protein concentrations. For the 2 ng/mL dose, the prediction was that the level of Erk activation would rise slowly to ~10%, while the experimental data showed Erk activation ranging between 10% and 20%. These experimental values showed slightly faster activation initially than the predicted values, but were consistent with the predicted values at later time points.
Previous work has demonstrated that NT-3–mediated activation of the MAP kinase cascade and Mash1 transcription factor resulted in neuronal differentiation of neural stem cells derived from mouse embryos.16,17
The results showed that when a large Erk activation peak was observed, an increase in Mash1 production as indicated by mRNA levels was also observed, suggesting a correlation. These data are consistent with experimental results observed by other groups.17
One possible mechanism to explain this observation is that the phosphoErk can activate Mash1, allowing it to translocate to the nucleus where it promotes further Mash1 transcription, along with transcription of genes that promote neuronal differentiation. Additionally, quantitative analysis using FACS confirmed the influence of the different NT-3 doses on the differentiation of ESNPCs into neurons, further supporting this hypothesis. When higher levels of Mash1 mRNA were observed, the fraction of cells that differentiated into neurons also increased with 25 ng/mL of NT-3 being the most effective dose for generating neurons from the ESNPCs.
It is important to note that our characterization of these cells using FACS is limited to determining which cells express a certain phenotypic marker. Additional characterization of the differentiation state of these cells could be performed by evaluating cell morphology or through the use of functional assays for neuronal activity. Additionally, our hypothesis could be further confirmed by using a TrkC inhibitor to abolish the effect of NT-3–induced activation of the MAP kinase cascade. If such an inhibitor was used, it would be expected that no MAP kinase activation would be observed and that the differentiation of the ESNPCs into neurons would be prevented, confirming our hypothesis. The use of such inhibitors provides another potential method of validating our kinetic analysis. These limitations are important to consider when designing future studies involving kinetic analysis for predicting stem cell differentiation.
This work demonstrates how a kinetic analysis can be developed using experimental data and rate constants obtained from the literature. Such an analysis was implemented and used to predict the minimum concentration of NT-3 needed to induce neuronal differentiation from ESNPCs. Such information is useful for designing engineered tissues. For example, the minimum NT-3 concentration necessary provides an initial starting point when designing scaffold materials containing NT-3 for promoting neuronal differentiation of stem cells. Such analysis can reduce the number of experiments necessary for optimizing such scaffolds and reduce the use of excessive amounts of growth factor.
While this present study was limited to looking at the effects of a single growth factor, this kinetic analysis could be expanded for a variety of applications. The present analysis showed how changing the initial protein concentrations present in a cell line can alter the kinetics of a signaling cascade. Thus, to expand this analysis to other cell lines, such as neural stem cells or mesenchymal stem cells, would require obtaining such experimental data. To generate such an analysis for a different growth factor and signaling cascade would require more effort and would require obtaining receptor/ligand kinetics and rate constants for the individual steps of the cascade. This specific kinetic analysis could be extended to include the presence of additional growth factors, such as platelet-derived growth factor (PDGF). PDGF has been shown to have synergistic effects when used in combination with NT-3 treatment for promoting differentiation of ESNPCs into both neurons and oligodendrocytes.30
More recently, PDGF has also been shown to activate the Erk signaling pathway, promoting oligodendrocyte differentiation.37
Thus, the current kinetic analysis could be extended to include the presence of PDGF and its receptor along with the transcription factors associated with the specific lineages, such as Mash1 and Olig2, for predicting the fraction of cells differentiating into neurons and oligodendrocytes, respectively. One of the limitations of the current analysis is that it does not take into account the presence of other growth factors and signaling cascades that could influence ESNPC differentiation.
In conclusion, this study has developed a kinetic analysis that replicates the activation of the MAP kinase cascade in ESNPCs derived from ES cells. The analysis was successfully used to predict the concentration of NT-3 that would be required to promote neuronal differentiation of these cells as confirmed by both expression of the transcription factor Mash1 and expression of a neuronal marker (β-tubulin III). Such models help give understanding into how intracellular signaling can be used to predict stem cell behavior. This specific analysis can be applied to promoting ESNPC differentiation for tissue engineering applications for the treatment of SCI. Additionally, this approach provides one way of looking at the effects of specific growth factors on stem cell differentiation.