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Discipline
Biological, Medical
Keywords
Hypoxia
Physoxia
Stem Cells
Differentiation
Spheroid
Observation Type
Standalone
Nature
Standard Data
Submitted
Apr 30th, 2019
Published
Jan 18th, 2021
  • Abstract

    Three-dimensional (3D) cell culture, particularly spheroid (cluster) biology, is increasingly being recognized to play a central role in regenerative medicine, cancer research, and diagnostics. Focusing on stem cells, 3D cell spheroids have been shown to be not only a valuable tool for the study of stem cell principles but also a prerequisite in differentiation protocols for therapeutic stem cell applications.

    For these, usually, a high number of cell spheroids is needed for therapeutic relevance, ranging from hundreds of thousands to several million. Many available platforms for the generation of such a number of spheroids cannot control their size, leading to diameter variations of sometimes more than a hundred micrometers. However, spheroid size has a direct impact on diffusion distance, inherently building up a concentration gradient for oxygen and also all substances applied to 3D cultures like nutrients, morphogens, and other signaling molecules. Hence, the spheroid size directly influences stem cell differentiation. This imposes a challenge for safe therapeutic applications where correct stem cell differentiation is of utmost importance to avoid uncontrolled tumourigenic growth.

    In this context, oxygen tension and its major transcription factor HIF-1α are more and more shown to play a pivotal role in controlling stem cell differentiation. Cell culture conditions directly impact this process. In classical 2D culture, practically all cells are exposed to the same ambient oxygen tension because they are growing as a monolayer or if cells form clusters in 2D they consist of only a few cell layers growing on top of each other. In contrast in 3D cell culture, only the most outer cell layers of a spheroid are exposed to the same oxygen tension in the ambient medium. With increasing spheroid size, the oxygen concentration is decreasing towards the spheroid center down to anoxia due to the laws of diffusion. When additionally, ambient oxygen is low like in a cell transplant situation, this further impacts cell spheroid oxygenation. It is unclear how these variables are influencing each other. To study these interactions, we have compared HIF-1α+/+ wild type and HIF-1α-/- knockout mouse embryonic stem cells in 2D and 3D culture with varying spheroid sizes and different ambient oxygen tensions. As a readout, we have analyzed the gene expression of the differentiation markers Bmp4, Nes, and Map2 after four days of spontaneous differentiation.

    We found that cell culture conditions, oxygen tension, and HIF-1α are interdependent and have a substantial impact on early spontaneous stem cell differentiation. Counterintuitively, some of the markers were not regulated in a similar way when hypoxia was created by ambient conditions as compared to hypoxia generated by oxygen diffusion limitation caused by large spheroid size.

    This implies that spheroid size and ambient oxygen tension should be controlled independently in order to allow correct mass differentiation of stem cell spheroids. This is instrumental, as safety is the single most important prerequisite for the human application of future stem cell therapies.

  • Figure
  • Introduction

    The growing understanding of the principles of stem cell biology increasingly fuels the vision of regenerative medicine. There, nowadays irreparable tissues or organs can be replaced by tissues or organs created in the laboratory. One example of this approach is “Holoclar”, the first approved stem cell product in the European Union. There, a severely damaged cornea of the eye can reach full regeneration with its own adult stem cells. Literally, a blind eye can reach full vision again. This breakthrough treatment is one of many more to come. As such, regenerative medicine is considered the successor of today’s organ transplantation. The realization and implementation of regenerative medicine hold a lot of promise to become the largest evolution of medicine in history.

    But there is a double-edged sword. The enormous power of stem cells to differentiate into and potentially regenerate any tissue in the human body is at the same time their greatest danger. Indefinite growth ability is a hallmark of stem cells, but indefinite growth is also a hallmark of tumor formation. Therefore, to use stem cells therapeutically in a safe way, final stages of somatic cell differentiation should be achieved up to the point where uncontrolled growth can be safely excluded.

    To understand these processes in all their details, cell culture models reflecting real-life processes are needed. Life is three-dimensional (3D) and therefore the respective cell culture methods should be 3D as well. The exponential growth of the scientific body of evidence about the necessity of 3D cell culture in the last decade is mirroring this understanding. Recent insights of stem cell biology revealed a wealth of information on how cells communicate to coordinate tissue formation and differentiation processes. The spatial cell organization and the creation of diffusion gradients is one of the means of cell communication, well known in developmental biology with principles like "morphogen gradients", where the orchestrated concentration of cytokines and growth factors decide cell fate. Therefore, these principles can be used for the directed differentiation of stem cells towards a specific fate for use in regenerative medicine.

    However, this knowledge lets us rethink how to culture cells in order to gain reliable data and develop effective and sustainable therapies. Given the classical cell culture method, where cells are typically grown flat on plastic culture dishes, the very nature and reactivity of stem cells impose a totally different challenge. In this respect, it is understandable that one of the biggest problems within the stem cell community is data reproducibility.

    One promising approach to address this problem is to start with the first multicellular architecture of life, namely cell spheroids. Cell spheroids are groups of cells in spheroidal form ranging from a few cells only to several thousand cells per spheroid. Three-dimensional cell spheroids are an ideal scientific model that offers additional therapeutic options. Used in developmental biology since the beginning of the 20th century, the "hanging drop" method allows cell spheroids to form simply by the influence of gravity and the self-organization capabilities inherent to many cell types. These 3D cell spheroids reflect real-life processes much better than flat two-dimensional (2D) cell culture. As this is a valid biological principle for many fields, 3D cell spheroids are not only used in stem cell research, but also in drug efficacy and toxicity screening, cancer research, personalized medicine, and cell therapy. This makes it the most widely used 3D cell culture model.

    Although cell spheroids offer advantages such as improved environmental control and reproducibility, precision, and versatility, they also pose several challenges. When cell spheroids are used, spheroid size determines the diffusion distance of oxygen, nutrients, and signaling molecules, leading to concentration gradients within the tissue depending on the physicochemical properties of the individual solutes. Consequently, spheroid size needs to be controlled to obtain reliable and reproducible data.

    One of the most significant single parameters to study is the impact of spheroid size on partial oxygen tension and how differences in the availability of free oxygen affect stem cell differentiation. Low oxygen tension is one of the major stem cell differentiation regulators and appears to be required for stem cell maintenance. Additionally, oxygen tension has been shown to be a key regulator in tumor biology. The activation of HIF-1α (hypoxia-inducible factor 1α), the major molecular regulator of mammalian cell response to hypoxia, has been shown to promote tumor growth and resistance to therapies. On the other hand, HIF-1α has also been shown to be involved in the maintenance of cancer stem cells and the expression of stem cell defining genes in cancer cell lines. HIF-1α acts as a major biological switch regulating more than 2% of all human genes. Consequently, HIF-1α is deeply involved in the fate decisions of stem cells to differentiate correctly or incorrectly and develop tumors. This behavior is directly linked to spheroid size control.

    In this respect, we have studied the influence of spheroid size and hypoxia on gene expression in early stem cell differentiation using standardized spheroid sizes in the hanging drop method compared to classical 2D culturing. We used HM-1 mouse embryonic stem (ES) cells, which do not require feeder cells. Stem cells are known to require a hypoxic environment of around 1–5% oxygen tension for their maintenance (also called “physiologic oxygen tension”, “physoxia”, “physioxia”). As the stem cell “niche” itself is always hypoxic, it is very important to distinguish between ambient hypoxia and hypoxia created by spheroid size diffusion gradients. HIF-1α is activated by hypoxia independent of whether it is created by large spheroid size or low ambient oxygen tension. Therefore, to distinguish the effects driven by a hypoxic environment from those exerted by hypoxia-independent mechanisms, we used HIF-1α+/+ and HIF-1α-/- HM-1 ES cells and compared 2D vs 3D cultures in normoxia and hypoxia of 3.5% oxygen tension.

    The first spontaneous differentiation step from an ES cell is towards primitive ectoderm followed by differentiation steps into all three germ layers with major involvement of Bmp4. In order to assess these very early steps, we have analyzed the differentiation markers Map2 and Nes for the ectodermal/neuronal development and Bmp4 as major early differentiation “switch”. We found that also cell culture conditions themselves regulate gene expression of early differentiation markers interdependent with hypoxia and that HIF-1α is also involved in this regulation.

  • Objective

    Three-dimensional cell culture in the form of spheroids is becoming increasingly important in many areas of biomedical research. Spheroids are also the most used culture format for the development of therapeutic applications with stem cells in regenerative medicine. The spheroid size determines the diffusion distance of oxygen and signaling molecules, leading to concentration gradients within the tissue. These concentration gradients can influence stem cell differentiation by acting as morphogens. To achieve a directed differentiation of stem cells towards a specific somatic fate for use in regenerative medicine, the influencing factors have to be understood also on the level of culture condition. In this study, we have therefore studied the mRNA expression of early transcription factors in spontaneous differentiation of mouse embryonic stem cells. The objective was to gain insight into whether spheroid size alone or the respective hypoxia built up by diffusion is decisive for influencing early differentiation and how this process is influenced by ambient oxygen tension. For this, we have compared 2D cell culture with spheroids of various sizes within varied ambient oxygen tension and performed the experiments with HIF-1α wild type and HIF-1α deficient mouse embryonic stem cells.

  • Results & Discussion

    To study these questions, we have chosen to perform a spontaneous differentiation of HM-1 mouse ES cells in different experimental conditions for 4 days. We compared classical 2D cell culture vs 3D culture in hanging drops with 2 standardized spheroid sizes. To cover a large experimental range, we compared small spheroids from hanging drops with 15 cells starting population (3D small) vs large spheroids from hanging drops with 2000 cells starting population (3D large). These populations were exposed to normoxia and hypoxia (physoxia) of 3.5% oxygen tension. The average diameters of the spheroids after 4 days of spontaneous differentiation were as follows: The small spheroids with 15 cells starting population reached a diameter of 92 μm ± 23 μm (mean ± SD) in normoxia and 73 μm ± 26 μm in hypoxia, respectively. The large spheroids with 2000 cells starting population reached a diameter of 406 μm ± 15 μm in normoxia but were much smaller with 174 μm ± 52 μm in hypoxia, respectively.

    Afterward, the genes Bmp4, a marker for mesenchymal differentiation, Nes, and Map2, markers for ectodermal/neural differentiation, were analyzed. Bmp4, a member of the transforming growth factor β (TGF-β) superfamily, was termed bone morphogenic protein due to its discovery from bone extracts. But the contribution of BMPs to vertebrate development has been shown to be so extensive that several researchers have suggested that the name “body morphogenic proteins” would better describe their significance.

    Furthermore, Bmp4 is involved in cancer stem cell biology. Looking at the Bmp4 gene expression in this setup, there is a very strong differential gene regulation already in 2D culture when comparing normoxia vs hypoxia. Upon spontaneous differentiation, there is an upregulation of a 2-fold change in normoxia, but a strong downregulation to 0.06-fold in hypoxia (Fig. 1A). In 2D culture, due to the flat cell arrangement, there will be no significant oxygen gradient in the stem cell mass. It thus can be assumed that all cells in hypoxic 2D experience the same oxygen concentration of about 3.5%. Thus, it is tempting to assume that hypoxia generally downregulates Bmp4 gene expression. However, looking at small 3D spheroids cultured in hypoxia, there is no downregulation like in 2D. The gene expression stays almost the same as in the maintenance culture with a relative expression change of 0.8-fold (Fig. 1A). If the gradual lowering of oxygen tension was the trigger to downregulate Bmp4 expression like in 2D, the gene expression of Bmp4 would be expected to be the same or even lower in hypoxic 3D with small spheroids.

    In non-vascularized and therefore non-perfused spheroids, an oxygen gradient is built up within the spheroid due to the limited diffusion of O2 into the tissue. Limitation of diffusion distance of oxygen is one of the fundamental reasons why humans and most animals possess a cardiovascular system.

    A 3.5% ambient oxygen tension will be experienced by the outermost cell layer and oxygen concentration towards the spheroid center will decrease gradually. By definition, a spheroid always has a lower oxygen tension in the spheroid core than the ambient oxygen tension. It can thus be suggested that biochemical cues provoked by small spheroid formation have an opposing effect on hypoxia-driven downregulation of Bmp4. In the normoxic 3D situation with small spheroids, there is no significant gene expression difference compared to 2D, as in both culture conditions the Bmp4 expression is about double as much compared to the maintenance culture (Fig. 1A). However, if hypoxia would be the driver for downregulation of Bmp4 expression, spheroids with an inherent oxygen gradient should express less Bmp4 than 2D cultures. But this is not the case.

    Here, further points have to be discussed. Some evidence suggests that the oxygen decrease in relation to spheroid size is not linear and that in spheroids with a diameter lower than 100 μm oxygen diffusion would not be limited substantially. If this was the case, then in the hypoxic situation with small spheroids, no difference in gene expression should occur. Only in the normoxic situation with small spheroids, this data could explain the lack of difference compared to the 2D situation, because the lowering of the oxygen concentration does not suffice to reach hypoxia in small spheroids up to 100 μm. However, this topic still needs further investigation as a measurement of oxygen tension in spheroids is inherently difficult.

    In this respect, it is important to note that normal cell culture conditions are unphysiological in terms of oxygen concentration, as most cells in a mammalian organism never face 21% O2. When oxygen concentration becomes such a crucial parameter for the fidelity of in vitro data with stem cells, consequently ambient oxygen concentration would need to be controlled much better in the experimental setup. Furthermore, it is also important to note that in vitro cells are supplied with oxygen defined by the ambient oxygen tension and limiting diffusion into the tissue, whereas in vivo, oxygen is provided through the vascular system bound to hemoglobin to bring oxygen in close proximity to the cells, depending on the degree of tissue vascularization.

    This is important for medical applications like islet cell transplantation to cure Diabetes, where islet spheroids are being transplanted into the comparably hypoxic environment of the liver. In the first 2 weeks, islets are being supplied with oxygen by diffusion only until revascularization has been completed. Hence, spheroid size is also crucially important in applied clinical reality as the sheer cell survival and thus the success of the transplantation depends on the oxygenation that can be provided by diffusion only. As the global scientific community is working relentlessly to develop islet cells from stem cells for the cure of Diabetes, correct spheroid size is now of double importance: correct cellular differentiation and clinical cellular survival.

    The strong downregulation of Bmp4 to 0.01-fold of the large 3D cell spheroids in normoxia (Fig. 1A) can be likely explained by severe hypoxia caused by the large spheroid size. But as the small 3D spheroids behave opposite with no Bmp4 downregulation even under hypoxia, there has to be another mechanism of Bmp4 gene regulation counteracting the effects mediated by ambient hypoxia in 2D. The strong downregulation of the large spheroids in hypoxia would fit again into the concept of Bmp4 downregulation caused by hypoxia alone, but here it also could be a metabolic breakdown effect with a drastic reduction of cellular activity due to putative anoxia in the spheroid center. Skiles has similarly analyzed the effect of ambient oxygen tension, spheroid size, and HIF-1α expression. He found that the rise of hypoxia, independent of whether it was caused by spheroid size or ambient hypoxia or the cumulation of both, led to a linear upregulation of HIF-1α expression and corresponding rise in vascular endothelial growth factor (VEGF) secretion. When hypoxia reached a critical point, he found VEGF secretion to drop again, arguing that the entire metabolism would collapse and the adaptive function of HIF-1α would not be functional anymore. Based on this data, he proposed to independently control both spheroid size and ambient oxygen tension, a statement that we strongly agree with. But in contrast to his data, our observations demonstrate a partial disconnection of Bmp4 regulation influenced by the spheroid size and ambient oxygen tension, which would suggest that spheroid size also affects gene expression by alternative pathways than by oxygen-dependent ones. Such alternative regulatory mechanisms could be responsible for Bmp4’s role in fate decisions in a dependence of geometrically defined culture conditions, which is shown in a remarkable paper of the Brivanlou group. They detected mechanisms of pattern formation and self-organization which were clearly related to the size of stem cell colonies. The colonies were cultured in 2D colony culture and even there, a size effect of the stem cell colony could be shown. More deliberately tuned than classical morphogen gradients, they describe a mechanism of solute-dependent inhibitory mechanisms that sheds light on the underlying mechanisms of how diffusion distance influences cell fate.

    Our experimental setup does not allow a deeper understanding of the regulatory interdependencies on a mechanistic level. For this, follow-up studies would be needed targeting a deeper understanding of the separate influence of spheroid size vs hypoxia. There, viability and functionality of cells in relation to spheroid sizes as well as individual gene expression on a single cellular level in relation to the spatial position within a spheroid should be analyzed.

    Putting these observations into a larger context, it gets clear that if spheroid size and oxygen tension lead to such deliberate fate decisions, we would need to incorporate such knowledge into stem cell differentiation protocols. Fate decision checkpoints would need to be activated not only by soluble agents but additionally by spatiotemporal control. How this relates to our observed behavior of Bmp4 regulation will need further research.

    Looking at Map2, a spontaneous upregulation upon differentiation in 2D culture happens both in normoxia and hypoxia. In normoxia, Map2 is upregulated 3.7-fold whereas in hypoxia it is upregulated significantly lower with a 2.3-fold change, respectively (Fig. 1B). Also, here, 2D culture in hypoxia leads to an oxygen tension of 3.5% of virtually every cell. When cultured as a 3D spheroid, however, oxygen tension is supposedly lower than in 2D culture. If hypoxia alone was the trigger for the stem cells to express less Map2 than in normoxia like in 2D, small hypoxic 3D spheroids should therefore express less Map2 than in 2D hypoxia. However, taking into account that diffusion distance might not be linear as discussed above, within small hypoxic spheroids hypoxia could theoretically be not significantly higher than in hypoxic 2D. In this case, the regulatory behavior of Map2 in small 3D spheroids should be the same as in 2D. Unexpectedly, small hypoxic spheroids express significantly more Map2 than in hypoxia 2D (3.7 vs 2.3-fold upregulation, respectively; Fig. 1B). Also, here, the same discussion as in Bmp4 applies, and further research is needed on how much the lowering of oxygen tension in relation to spheroid size applies and which conclusions can be drawn. When cultured as large spheroids, the upregulation of Map2 in the normoxic cultivation is highest with a 7-fold increase compared to baseline (Fig. 1B). However, in these large spheroids, there is by definition significant hypoxia present. It is very difficult to directly measure oxygen concentration within a spheroid without destroying the spheroid architecture. It is however recognized that any multicellular spheroid larger than 200 μm experiences relevant hypoxia. In our study, the normoxic spheroids have reached 406 μm on average, therefore chronic hypoxia, possibly even core anoxia must be present. Thus, although experiencing much more hypoxia than in small spheroids, why is Map2 significantly upregulated (7 vs 4.7-fold, respectively)? The opposing, hypoxia-independent regulatory mechanisms activated by spheroid size must therefore be much stronger than the effects of hypoxia alone. The significantly lower upregulation of large spheroids cultivated in hypoxia of 2.2-fold change (Fig. 1B) could be a similar effect as observed in the work of Skiles, wherefrom a certain low oxygen concentration on the entire regulatory mechanism breaks down as homeostasis cannot be maintained anymore.

    For the observed differences of Map2 expression in relation to hypoxia with spheroid size, the literature gives only very scarce data. Mostly studied in hypoxic brain damage models, some reaction on the hypoxic insult yields in colocalization of Map2 expression with HIF-1α, but the mechanism of this relationship remains blurry. To address this question more thoroughly, detailed studies on cell survival in relation to spheroid size and oxygen tension would be needed.

    Looking at the Nes expression, in 2D the upregulation is a 4.4-fold change at normoxic conditions and a 3.2-fold change under hypoxia, respectively (Fig. 1C). In small 3D spheroids, there is an upregulation of 4.4-fold in normoxia and 6.7-fold in hypoxia, respectively (Fig. 1C). This upregulation of small spheroids in hypoxia is significant compared to hypoxic 2D, again indicating other, hypoxia-independent mechanisms for Nes gene regulation as hypoxic conditions in 2D and small spheroid are likely to be similar. In large spheroids cultivated in normoxia, the upregulation is 8.3-fold vs. large spheroids in hypoxia with blunted upregulation of 3.7-fold (Fig. 1C). Regarding the lower Nes expression in the large hypoxic spheroids, like described above in the other examples, most probably physiological regulatory mechanisms were broken down due to significant hypoxia up to anoxia, and regulation for this experimental condition has to be interpreted with caution.

    The influence of HIF-1α and hypoxia on Nes expression was already described on mesenchymal stem cells, wherein 2D cultures, hypoxia was leading to a HIF-1α dependent Nes overexpression on the RNA and protein level. However, the mechanisms of this regulation are not clear. The authors here suggest indirect regulation by VEGF activation. To the best of our knowledge, Nes does not have functional hypoxia response elements (HRE’s) in the promoter region, which would be needed for direct activation by HIF-1α.

    In our study, the mechanisms of the Nes regulation is not solely attributable to spheroid size or oxygen tension, but most likely driven by opposing effects of either stimuli. The many other putative regulatory influences like the diffusion control mechanism of Bmp4 described by Brivanlou (above) are possible explanations. However, as before, this data shows the importance of controlling both spheroid size and oxygen tension in order to be able to understand the individual effects.

    The whole experimental approach was additionally performed with HIF-1α deficient (HIF-1α-/-) stem cells. In comparison to the wild type cells, in HIF-1α deficient cells there is almost no significant regulation observed, and if so, there is a very high standard deviation compared to wild type cells. This happened in any condition tested. The lack of robustly detectable regulation in the absence of HIF-1α in contrast to wild type cells points to a central role of HIF-1α in culture-dependent early differentiation gene expression. This can be best seen in the example of Bmp4, where the strong differential regulation in HIF-1α+/+ cell spheroids is not observed in HIF-1α-/- cells (Fig. 1A, D). This is in line with the literature where Bmp4 is found to act downstream of HIF-1α. But how exactly HIF-1α is mechanistically involved leading to such a strong differential regulation needs further studies.

    Interestingly, BMP-4 is induced in hepatocellular carcinoma by hypoxia and promotes tumor progression. This effect could be abolished by transfection of a dominant-negative form of HIF-1α. Striking similarities exist between molecular mechanisms driving embryonic liver development and the progression of hepatocellular carcinoma, making this an example of how stem cell and cancer research share a lot of commonalities.

    In summary, the described observations demonstrate that gene regulation of Bmp4, Map2, and Nes in stem cell cultures is dependent not only on ambient oxygen tension but also on the spheroid size.

    Relating to cancer research, the knowledge of spheroid biology is especially helpful and has been applied broadly as diffusion gradients play a central role in cancer metabolism as well. Only cell spheroids have allowed us to understand tumor biology better and also their resistance to chemo- and radiotherapy. But the impact of cell spheroids in stem cells and cancer research is much larger than originally thought. With the discovery of cancer stem cells and their identification in various types of solid tumors, there is now a common ground of research in both areas. Cancer stem cells have been detected in the brain, breast, lung, colon, melanoma, and ovarian cancer and the list is expanding rapidly. Based on this data, one of the keys for therapeutic advancement for cancer treatment lies within the understanding of stem cell biology. At the same time, it is well known that the biggest danger in stem cell therapy is tumor formation. Therefore, understanding the mechanisms of fate decisions in stem cells is not only imperative for correct differentiation of stem cells for therapeutic applications, but it also allows to survey this correct differentiation with the knowledge gained from cancer stem cell research, where "triggering events" of stem cells getting out of cell-cycle control, are being studied.

    The importance of these principles can be seen in clinics. The cancer patient is usually not killed by the primary tumor. The patient is killed by the metastases. These, in turn, develop because the invasive and metastasizing property of tumor cells is unleashed by hypoxia, and hypoxia is controlled by diffusion distance, and diffusion distance is controlled by the spheroid size, i.e. the size of the avascular portion of a growing tumor. In short: the more hypoxic a tumor, the more aggressive its behavior.

    Here, science has a direct legal and regulatory impact. Modern risk management methods, which are a prerequisite for any approval of new therapies, are based on such considerations. If derivations for the future are possible on the basis of reproducible observations, i.e. how often could a possible dangerous event occur, and how serious would this event be, then the integration of these observations is legally obligatory.

    The data shown here is only a little hint about the importance of rigid control of cell culture conditions like spheroid size and ambient oxygen tension for cellular differentiation protocols. The interdependent and sometimes opposing regulatory effects are not well understood. Because of the clinical significance, these effects should be investigated in detail.

    More and more elements needed for physiological cell differentiation are being uncovered. Recent literature now shows that the understanding of spheroid size control on fate decisions is growing as architectural support of every single spheroid within a micropatterned surface allowed more directed differentiation towards specific cell types for clinical applications. It is getting clear that only a stringent control of all involved biological parameters enforced by suitable and appropriate 3D cell culture platforms will allow the safe differentiation of stem cells for clinical applications.

  • Conclusions

    Our data shows that cell culture conditions, especially spheroid size, are influencing gene expression in early stem cell differentiation. Spheroid size control not only allows assurance of equal oxygen tension throughout a population of cell spheroids, it also impacts gene expression by mechanisms that cannot be explained by oxygen tension alone. To what extent HIF-1α is responsible for these early regulatory steps needs to be further elaborated.

    The relevance of this data lies within the current developments of regenerative medicine, drug screening, and cancer research where 3D cell spheroids are increasingly being used. Understanding the inherent biological properties of stem cells and the underlying mechanisms allowing fate decisions are on one hand essential for successful cell differentiation towards clinical applications and on the other hand essential for the prevention of uncontrolled growth leading to tumor formation. Therefore, current and future therapeutic research pipelines must adhere, besides other factors, to these principles of spheroid size control before attempting steps towards clinical applications.

  • Limitations

    There are several limitations in our study: First, the only genetic analysis does not lead to conclusions about protein expression. The investigation at the protein level would allow identifying a correlation between genotype and protein synthesis. Second, the formation of cells as 3D spheroids was analyzed in this study with respect to overall genetics. No statement can be made as to which gene expression is different in respect to single-cell gene expression. Our study shows the average gene expression of the entire spheroid. Third, various parameters such as spheroid size and oxygen tension have an influence on the outcome. The effects of the individual factors in this system are still poorly understood and a mechanistic description of the process is not yet feasible. Furthermore, only 4 markers were used in order to get an orientation about the effect of culture conditions on early spontaneous differentiation in a principal manner. For a deeper understanding, our results must be further validated and substantiated with mechanistic studies about the spheroid size and oxygen tension as individual components.

  • Conjectures

    Further investigations of stem cell fate within spheroids and in relation to oxygen tension are necessary. According to the studies by Deglincerti and Huizar, which analyzed embryological fate decision mechanisms in relation to cell conglomerate size offers important insights for the understanding of the mechanisms of self-organization and patterning. Based on our data, fate cascade should be investigated in relation to HIF-1α, spheroid size, and ambient oxygen control from this perspective. Information on the stimulation of both single cells and spheroids with BMP and as a function of oxygen tension will provide further insights into how such an environment affects cells. As differentiation of stem cells for future therapies is based on these principles, we suggest intense research activities which finally may bridge the gap between developmental biology and clinical applications.

  • Methods

    Abbreviations

    2D: Two-dimensional

    3D: Three-dimensional

    ES cells: Embryonic stem cells

    FFC: Free-floating clusters

    LIF: Leukemia inhibitory factor

    TGF-β: Transforming growth factor-beta

    VEGF: Vascular endothelial growth factor

    Map2: Microtubule-associated protein 2

    Bmp4: Bone morphogenic protein 4

    Nes: Nestin

    vs: Versus

    HIF-1α: Hypoxia-inducible factor 1α

    HM-1 embryonic stem cell culture

    HM-1 mES cells, an inbred mouse ES cell line, were knocked out for HIF-1α to produce HIF-1α double deficient (HIF-1α-/-) clones. HM-1 cultivation of wild type (HIF-1α+/+) and HIF-1α-/- was initially done on gelatine-coated Petri dishes as described previously. However, this culturing method was found to promote attachment-induced differentiation of the cells residing on the border of the typical stem cell spheroid growth pattern. As this differentiation behavior was already visible by the eye (Suppl. Fig. 1), we have decided to culture the HM-1 mES cells as free-floating spheroids (FFS).

    Formation of free-floating ES cell spheroids to avoid attachment-induced differentiation took place spontaneously by cultivation in bacterial Petri dishes (Greiner Bio-One, Nr. 639102) with HM-1 ES cells seeded at a density of 4000 (3 days between splitting) or 10’000 to 20’000 (2 days between splitting) cells per ml of medium (10 ml medium per 10 cm Petri dish). FFS were split before reaching a size of 150–200 μm in order to avoid uncontrolled central differentiation and necrosis due to LIF diffusion limitation and hypoxia. Cell splitting was performed by aspirating FFS, spinning cell spheroids for 2–4 min at 260–300 x g, and washing with prewarmed standard phosphate-buffered saline without calcium and magnesium (PBS). Dissociation was done by adding prewarmed non-enzymatic cell dissociation buffer (Sigma-Aldrich C1419) followed by incubation for 10–15 min with occasional shaking, then dissociating the FFS with pipetting up and down using a 5 ml serological pipet (no strong mechanical disruption with narrow pipettes like glass Pasteur pipettes or tips needed). Upon complete dissociation, the reaction was stopped by adding ES medium, washed once with ES medium, counted, and seeded.

    ES cell culture medium

    For the ES cell medium, a stock and a working solution were prepared. The stock solution consisted of Dulbecco’s modified eagle medium (DMEM) with 4.5 g/l glucose and UltraGlutamineTM (Lonza BE04-687F/U1), 1% sodium pyruvate (Invitrogen/Gibco 11360-039), 1% MEM non-essential amino acids (Invitrogen/Gibco 11140-035) and 0.05 mM β-mercaptoethanol (Sigma-Aldrich, M6250). The working medium consisted of a stock solution, 20% stem cell tested fetal bovine serum (FBS, USA origin pre-tested ES cells, Chemie Brunschwig AG, Cat-Nr. 16000-044, Lot. 1057263) and 1000 U/ml leukemia inhibiting factor LIF (ESGRO LIF ESG1107). The differentiation medium consists of the ES cell culture medium, but without LIF.

    ES cell differentiation

    The ES cell cultivation was done in classical cell culture incubators (Forma Scientific) at 37°C humidified atmosphere with ambient oxygen tension (20% O2) supplemented with 5% CO2. Stem cell differentiation was done either in normoxia or in a hypoxia chamber (3.5% O2; Coy Laboratory Products Inc.). Neither a standard physiological oxygen concentration nor the name "physoxia or physioxia" is consistently defined in the literature which is why we use the classical term hypoxia.

    Hanging drop cultivation of small and large stem cell clusters

    HM-1 ES cells were kept in maintenance culture with LIF as FFS. From this maintenance culture, hanging drops were produced by pipetting dissociated ES cells in a differentiation medium. To maintain equally distributed cell numbers, a multichannel repeater (Matrix Technologies Corp.) was used taking care of pipetting the carefully stirred cell solution and pipetting at elaborate speed. Drops were pipetted with a volume of 30 µl on the lid of 145×20 mm Petri dishes (Greiner Bio-One, Nr. 639102). To cover a large experimental range, small spheroids with 15 cells per drop and large spheroids with 2000 cells per drop were pipetted. The bottom of the dish was filled with PBS to prevent the hanging drops from drying out. HM-1 cell spheroids were spontaneously differentiated for 4 days.

    Cell spheroids were evaluated by an inverted light microscope (Zeiss Axiovert) with a camera shot directly through the ocular lens (Sony Ericsson K800i) on day 4. The diameter of each spheroid was determined using ImageJ (version 2.0.0-rc-43/1.50e) software. Thereafter, data were exported to Microsoft Excel, and the mean and standard deviation was calculated.

    RNA extraction and co-application reverse transcription

    RNA extraction was performed using the Macherey-Nagel NucleoSpin RNA II Kit (Macherey-Nagel, 740955.50). All steps were performed according to the manufacturer's instructions. RNA concentration was measured using a nanodrop device (Thermo Scientific).

    Modified cDNA production method with co-application reverse transcription (RT) and SuperScript III reverse transcriptase (Thermo Fisher 18080093) were adapted from Zhu, who developed this technique to combine the advantage and selectivity of oligo-dT priming with the stability and ubiquity of 18S internal standard. The reliability of this method in terms of reproducibility and precision of gene expression detection is described in detail in the supplementary material (Suppl. Fig. 2 and Suppl. Fig. 3).

    For the co-RT reaction, 100 ng RNA was mixed with 1 μl of oligo (dT)20 primer (50 μM), 1 μl of 18S-RNA specific primer (50 μM; 5’-GAGCTGGAATTACCGCGGCT-3’), 1 μl of dNTPs (10 mM) and RNAse-free water. The mixture with a final volume of 14 μl was incubated at 65°C for 5 min. Afterward, 4 μl 5× first-strand buffer, 1 μl DTT (0.1 M), 0.25 μl SuperScript III reverse transcriptase (Invitrogen), and 0.75 μl water were added to the reaction mixture and incubated for 60 min at 50°C, followed by an inactivation step at 70°C for 15 min.

    Real-time PCR

    Cells used for the experiments were sequentially prepared as independent biological triplicates. Real-time PCR was performed using the TaqMan system (Applied Biosystems). According to manufacturer's guidelines, 20 μl reaction volume per sample containing 10 μl universal PCR master mix (TaqMan System, part Nr. 4331182, Thermo Fisher), 4 μl 5× TaqMan assay (reference sequence NM_007554 for Bmp4, NM_008632 for Map2 and NM_016701 for Nes), 2 μl cDNA and 4 μl water were mixed. PCR was loaded in duplicates and all experiments contained no template controls. Cycling parameters corresponded to a standard program with 40 cycles for 15-sec denaturation at 95°C and 1 min annealing/extension at 60°C. Data analysis was performed with the ABI Prism Software (Applied Biosystems) and Microsoft Excel. The delta-delta ct (ddct) method for data analysis was used with relative gene expression value change vs a starting (reference) point. This point consisted of the HM-1 cells kept as FFS in maintenance culture of which the differentiation experiment started. In the figure, this starting point equals 1 on the y axis.

    Statistical analysis

    Statistical analysis has been done with GraphPad Prism 7 software (GraphPad Software, Inc.) using Bonferroni’s multiple comparison test. CI represents confidence interval, and SD represents the standard deviation (see SD values in Suppl. Material Table 1). Results are representative of 3 biological replicates. The replicates consisted of different ES cell passages and each experiment was performed on a different day. Of each biological replicate, technical duplicates were used for the real-time PCR to minimize pipetting error.

    All original data including lab journals and raw data are available upon request.

  • Funding statement

    Julius Müller foundation, Theodor and Ida Herzog-Egli foundation and private anonymous sponsor from the UBS.

  • Ethics statement

    Not Applicable.

  • References
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    Matters14.5/20

    Cell Culture Conditions (2D/3D), Spheroid Size and Hypoxia Interdependently Regulate Spontaneous Early Stem Cell Differentiation

    Affiliation listing not available.
    Abstractlink

    Three-dimensional (3D) cell culture, particularly spheroid (cluster) biology, is increasingly being recognized to play a central role in regenerative medicine, cancer research, and diagnostics. Focusing on stem cells, 3D cell spheroids have been shown to be not only a valuable tool for the study of stem cell principles but also a prerequisite in differentiation protocols for therapeutic stem cell applications.

    For these, usually, a high number of cell spheroids is needed for therapeutic relevance, ranging from hundreds of thousands to several million. Many available platforms for the generation of such a number of spheroids cannot control their size, leading to diameter variations of sometimes more than a hundred micrometers. However, spheroid size has a direct impact on diffusion distance, inherently building up a concentration gradient for oxygen and also all substances applied to 3D cultures like nutrients, morphogens, and other signaling molecules. Hence, the spheroid size directly influences stem cell differentiation. This imposes a challenge for safe therapeutic applications where correct stem cell differentiation is of utmost importance to avoid uncontrolled tumourigenic growth.

    In this context, oxygen tension and its major transcription factor HIF-1α are more and more shown to play a pivotal role in controlling stem cell differentiation. Cell culture conditions directly impact this process. In classical 2D culture, practically all cells are exposed to the same ambient oxygen tension because they are growing as a monolayer or if cells form clusters in 2D they consist of only a few cell layers growing on top of each other. In contrast in 3D cell culture, only the most outer cell layers of a spheroid are exposed to the same oxygen tension in the ambient medium. With increasing spheroid size, the oxygen concentration is decreasing towards the spheroid center down to anoxia due to the laws of diffusion. When additionally, ambient oxygen is low like in a cell transplant situation, this further impacts cell spheroid oxygenation. It is unclear how these variables are influencing each other. To study these interactions, we have compared HIF-1α+/+ wild type and HIF-1α-/- knockout mouse embryonic stem cells in 2D and 3D culture with varying spheroid sizes and different ambient oxygen tensions. As a readout, we have analyzed the gene expression of the differentiation markers Bmp4, Nes, and Map2 after four days of spontaneous differentiation.

    We found that cell culture conditions, oxygen tension, and HIF-1α are interdependent and have a substantial impact on early spontaneous stem cell differentiation. Counterintuitively, some of the markers were not regulated in a similar way when hypoxia was created by ambient conditions as compared to hypoxia generated by oxygen diffusion limitation caused by large spheroid size.

    This implies that spheroid size and ambient oxygen tension should be controlled independently in order to allow correct mass differentiation of stem cell spheroids. This is instrumental, as safety is the single most important prerequisite for the human application of future stem cell therapies.

    Figurelink

    Figure A. Spheroid size regulates early gene expression in HM-1 embryonic stem cells interdependent with hypoxia.

    Real-time PCR of spontaneous undirected differentiation of mouse HM-1 embryonic stem (ES) cells, either as HIF-1α+/+ wild type (A-C) or as HIF-1α-/- knockout (D-F). Gene expression differences are caused solely by different cultural conditions. 2D cell culture is compared to 3D cell culture in hanging drops with either small (15 cells starting population per drop) or large (2000 cells starting population per drop) cell spheroids exposed to either normoxia or hypoxia of 3.5% oxygen tension (physoxia). The duration of spontaneous differentiation for all experiments was four days and followed by an analysis of the differentiation markers Bmp4 (A, D), Map2 (B, E), and Nes (C, F). Gene expression differences are expressed as bars showing fold expression vs. undifferentiated ES cells starts population, which is set to a value of 1.

    Data is given in means with error bars showing standard deviations. Significances are labeled with asterisks showing the significance of fold expression vs. start. No asterisks: not significant vs. start values. Significances in between different groups are shown with brackets. The level of significance is given by a number of asterisks. *: P ≤0.05. **: P ≤0.01. ***: P ≤0.001. ****: P ≤0.0001. The statistical method used: Bonferroni's Multiple Comparison Test.

    Figure B. Gene expression of HIF-1α-/- knockout compared to HIF-1α+/+ wild type.

    Comparative graph highlighting the key differences of the gene expression of HIF-1α-/- knockout compared to HIF-1α+/+ wild type ES cells of figure A.

    Introductionlink

    The growing understanding of the principles of stem cell biology increasingly fuels the vision of regenerative medicine. There, nowadays irreparable tissues or organs can be replaced by tissues or organs created in the laboratory. One example of this approach is “Holoclar”, the first approved stem cell product in the European Union. There, a severely damaged cornea of the eye can reach full regeneration with its own adult stem cells[1]. Literally, a blind eye can reach full vision again. This breakthrough treatment is one of many more to come. As such, regenerative medicine is considered the successor of today’s organ transplantation. The realization and implementation of regenerative medicine hold a lot of promise to become the largest evolution of medicine in history[2][3][4][5][6][7].

    But there is a double-edged sword. The enormous power of stem cells to differentiate into and potentially regenerate any tissue in the human body is at the same time their greatest danger. Indefinite growth ability is a hallmark of stem cells, but indefinite growth is also a hallmark of tumor formation. Therefore, to use stem cells therapeutically in a safe way, final stages of somatic cell differentiation should be achieved up to the point where uncontrolled growth can be safely excluded[8][9][10][11][12].

    To understand these processes in all their details, cell culture models reflecting real-life processes are needed. Life is three-dimensional (3D) and therefore the respective cell culture methods should be 3D as well. The exponential growth of the scientific body of evidence about the necessity of 3D cell culture in the last decade is mirroring this understanding[13][14][15]. Recent insights of stem cell biology revealed a wealth of information on how cells communicate to coordinate tissue formation and differentiation processes. The spatial cell organization and the creation of diffusion gradients is one of the means of cell communication, well known in developmental biology with principles like "morphogen gradients", where the orchestrated concentration of cytokines and growth factors decide cell fate[16]. Therefore, these principles can be used for the directed differentiation of stem cells towards a specific fate for use in regenerative medicine[17][18].

    However, this knowledge lets us rethink how to culture cells in order to gain reliable data and develop effective and sustainable therapies. Given the classical cell culture method, where cells are typically grown flat on plastic culture dishes, the very nature and reactivity of stem cells impose a totally different challenge. In this respect, it is understandable that one of the biggest problems within the stem cell community is data reproducibility[19].

    One promising approach to address this problem is to start with the first multicellular architecture of life, namely cell spheroids. Cell spheroids are groups of cells in spheroidal form ranging from a few cells only to several thousand cells per spheroid. Three-dimensional cell spheroids are an ideal scientific model that offers additional therapeutic options. Used in developmental biology since the beginning of the 20th century, the "hanging drop" method allows cell spheroids to form simply by the influence of gravity and the self-organization capabilities inherent to many cell types. These 3D cell spheroids reflect real-life processes much better than flat two-dimensional (2D) cell culture. As this is a valid biological principle for many fields, 3D cell spheroids are not only used in stem cell research, but also in drug efficacy and toxicity screening, cancer research, personalized medicine, and cell therapy. This makes it the most widely used 3D cell culture model[20][21][22][23][24][25].

    Although cell spheroids offer advantages such as improved environmental control and reproducibility, precision, and versatility, they also pose several challenges. When cell spheroids are used, spheroid size determines the diffusion distance of oxygen, nutrients, and signaling molecules, leading to concentration gradients within the tissue depending on the physicochemical properties of the individual solutes. Consequently, spheroid size needs to be controlled to obtain reliable and reproducible data[26][27].

    One of the most significant single parameters to study is the impact of spheroid size on partial oxygen tension and how differences in the availability of free oxygen affect stem cell differentiation. Low oxygen tension is one of the major stem cell differentiation regulators and appears to be required for stem cell maintenance[28][29][30][31]. Additionally, oxygen tension has been shown to be a key regulator in tumor biology. The activation of HIF-1α (hypoxia-inducible factor 1α), the major molecular regulator of mammalian cell response to hypoxia, has been shown to promote tumor growth and resistance to therapies[31]. On the other hand, HIF-1α has also been shown to be involved in the maintenance of cancer stem cells and the expression of stem cell defining genes in cancer cell lines[32]. HIF-1α acts as a major biological switch regulating more than 2% of all human genes[31]. Consequently, HIF-1α is deeply involved in the fate decisions of stem cells to differentiate correctly or incorrectly and develop tumors. This behavior is directly linked to spheroid size control.

    In this respect, we have studied the influence of spheroid size and hypoxia on gene expression in early stem cell differentiation using standardized spheroid sizes in the hanging drop method compared to classical 2D culturing. We used HM-1 mouse embryonic stem (ES) cells, which do not require feeder cells[33]. Stem cells are known to require a hypoxic environment of around 1–5% oxygen tension for their maintenance (also called “physiologic oxygen tension”, “physoxia”, “physioxia”). As the stem cell “niche” itself is always hypoxic, it is very important to distinguish between ambient hypoxia and hypoxia created by spheroid size diffusion gradients. HIF-1α is activated by hypoxia independent of whether it is created by large spheroid size or low ambient oxygen tension. Therefore, to distinguish the effects driven by a hypoxic environment from those exerted by hypoxia-independent mechanisms, we used HIF-1α+/+ and HIF-1α-/- HM-1 ES cells and compared 2D vs 3D cultures in normoxia and hypoxia of 3.5% oxygen tension[34][31].

    The first spontaneous differentiation step from an ES cell is towards primitive ectoderm followed by differentiation steps into all three germ layers with major involvement of Bmp4[35]. In order to assess these very early steps, we have analyzed the differentiation markers Map2 and Nes for the ectodermal/neuronal development and Bmp4 as major early differentiation “switch”. We found that also cell culture conditions themselves regulate gene expression of early differentiation markers interdependent with hypoxia and that HIF-1α is also involved in this regulation.

    Objectivelink

    Three-dimensional cell culture in the form of spheroids is becoming increasingly important in many areas of biomedical research. Spheroids are also the most used culture format for the development of therapeutic applications with stem cells in regenerative medicine[25]. The spheroid size determines the diffusion distance of oxygen and signaling molecules, leading to concentration gradients within the tissue. These concentration gradients can influence stem cell differentiation by acting as morphogens. To achieve a directed differentiation of stem cells towards a specific somatic fate for use in regenerative medicine, the influencing factors have to be understood also on the level of culture condition[36]. In this study, we have therefore studied the mRNA expression of early transcription factors in spontaneous differentiation of mouse embryonic stem cells. The objective was to gain insight into whether spheroid size alone or the respective hypoxia built up by diffusion is decisive for influencing early differentiation and how this process is influenced by ambient oxygen tension. For this, we have compared 2D cell culture with spheroids of various sizes within varied ambient oxygen tension and performed the experiments with HIF-1α wild type and HIF-1α deficient mouse embryonic stem cells.

    Results & Discussionlink

    To study these questions, we have chosen to perform a spontaneous differentiation of HM-1 mouse ES cells in different experimental conditions for 4 days. We compared classical 2D cell culture vs 3D culture in hanging drops with 2 standardized spheroid sizes. To cover a large experimental range, we compared small spheroids from hanging drops with 15 cells starting population (3D small) vs large spheroids from hanging drops with 2000 cells starting population (3D large). These populations were exposed to normoxia and hypoxia (physoxia) of 3.5% oxygen tension. The average diameters of the spheroids after 4 days of spontaneous differentiation were as follows: The small spheroids with 15 cells starting population reached a diameter of 92 μm ± 23 μm (mean ± SD) in normoxia and 73 μm ± 26 μm in hypoxia, respectively. The large spheroids with 2000 cells starting population reached a diameter of 406 μm ± 15 μm in normoxia but were much smaller with 174 μm ± 52 μm in hypoxia, respectively.

    Afterward, the genes Bmp4, a marker for mesenchymal differentiation, Nes, and Map2, markers for ectodermal/neural differentiation, were analyzed. Bmp4, a member of the transforming growth factor β (TGF-β) superfamily, was termed bone morphogenic protein due to its discovery from bone extracts. But the contribution of BMPs to vertebrate development has been shown to be so extensive that several researchers have suggested that the name “body morphogenic proteins” would better describe their significance[37].

    Furthermore, Bmp4 is involved in cancer stem cell biology[38]. Looking at the Bmp4 gene expression in this setup, there is a very strong differential gene regulation already in 2D culture when comparing normoxia vs hypoxia. Upon spontaneous differentiation, there is an upregulation of a 2-fold change in normoxia, but a strong downregulation to 0.06-fold in hypoxia (Fig. 1A). In 2D culture, due to the flat cell arrangement, there will be no significant oxygen gradient in the stem cell mass. It thus can be assumed that all cells in hypoxic 2D experience the same oxygen concentration of about 3.5%. Thus, it is tempting to assume that hypoxia generally downregulates Bmp4 gene expression. However, looking at small 3D spheroids cultured in hypoxia, there is no downregulation like in 2D. The gene expression stays almost the same as in the maintenance culture with a relative expression change of 0.8-fold (Fig. 1A). If the gradual lowering of oxygen tension was the trigger to downregulate Bmp4 expression like in 2D, the gene expression of Bmp4 would be expected to be the same or even lower in hypoxic 3D with small spheroids.

    In non-vascularized and therefore non-perfused spheroids, an oxygen gradient is built up within the spheroid due to the limited diffusion of O2 into the tissue[39][40][41][42][43]. Limitation of diffusion distance of oxygen is one of the fundamental reasons why humans and most animals possess a cardiovascular system[44].

    A 3.5% ambient oxygen tension will be experienced by the outermost cell layer and oxygen concentration towards the spheroid center will decrease gradually. By definition, a spheroid always has a lower oxygen tension in the spheroid core than the ambient oxygen tension. It can thus be suggested that biochemical cues provoked by small spheroid formation have an opposing effect on hypoxia-driven downregulation of Bmp4. In the normoxic 3D situation with small spheroids, there is no significant gene expression difference compared to 2D, as in both culture conditions the Bmp4 expression is about double as much compared to the maintenance culture (Fig. 1A). However, if hypoxia would be the driver for downregulation of Bmp4 expression, spheroids with an inherent oxygen gradient should express less Bmp4 than 2D cultures. But this is not the case.

    Here, further points have to be discussed. Some evidence suggests that the oxygen decrease in relation to spheroid size is not linear and that in spheroids with a diameter lower than 100 μm oxygen diffusion would not be limited substantially[45][46]. If this was the case, then in the hypoxic situation with small spheroids, no difference in gene expression should occur. Only in the normoxic situation with small spheroids, this data could explain the lack of difference compared to the 2D situation, because the lowering of the oxygen concentration does not suffice to reach hypoxia in small spheroids up to 100 μm. However, this topic still needs further investigation as a measurement of oxygen tension in spheroids is inherently difficult[46].

    In this respect, it is important to note that normal cell culture conditions are unphysiological in terms of oxygen concentration, as most cells in a mammalian organism never face 21% O2. When oxygen concentration becomes such a crucial parameter for the fidelity of in vitro data with stem cells, consequently ambient oxygen concentration would need to be controlled much better in the experimental setup. Furthermore, it is also important to note that in vitro cells are supplied with oxygen defined by the ambient oxygen tension and limiting diffusion into the tissue, whereas in vivo, oxygen is provided through the vascular system bound to hemoglobin to bring oxygen in close proximity to the cells, depending on the degree of tissue vascularization.

    This is important for medical applications like islet cell transplantation to cure Diabetes, where islet spheroids are being transplanted into the comparably hypoxic environment of the liver. In the first 2 weeks, islets are being supplied with oxygen by diffusion only until revascularization has been completed. Hence, spheroid size is also crucially important in applied clinical reality as the sheer cell survival and thus the success of the transplantation depends on the oxygenation that can be provided by diffusion only[47]. As the global scientific community is working relentlessly to develop islet cells from stem cells for the cure of Diabetes, correct spheroid size is now of double importance: correct cellular differentiation and clinical cellular survival.

    The strong downregulation of Bmp4 to 0.01-fold of the large 3D cell spheroids in normoxia (Fig. 1A) can be likely explained by severe hypoxia caused by the large spheroid size. But as the small 3D spheroids behave opposite with no Bmp4 downregulation even under hypoxia, there has to be another mechanism of Bmp4 gene regulation counteracting the effects mediated by ambient hypoxia in 2D. The strong downregulation of the large spheroids in hypoxia would fit again into the concept of Bmp4 downregulation caused by hypoxia alone, but here it also could be a metabolic breakdown effect with a drastic reduction of cellular activity due to putative anoxia in the spheroid center. Skiles[48] has similarly analyzed the effect of ambient oxygen tension, spheroid size, and HIF-1α expression. He found that the rise of hypoxia, independent of whether it was caused by spheroid size or ambient hypoxia or the cumulation of both, led to a linear upregulation of HIF-1α expression and corresponding rise in vascular endothelial growth factor (VEGF) secretion. When hypoxia reached a critical point, he found VEGF secretion to drop again, arguing that the entire metabolism would collapse and the adaptive function of HIF-1α would not be functional anymore. Based on this data, he proposed to independently control both spheroid size and ambient oxygen tension, a statement that we strongly agree with. But in contrast to his data, our observations demonstrate a partial disconnection of Bmp4 regulation influenced by the spheroid size and ambient oxygen tension, which would suggest that spheroid size also affects gene expression by alternative pathways than by oxygen-dependent ones. Such alternative regulatory mechanisms could be responsible for Bmp4’s role in fate decisions in a dependence of geometrically defined culture conditions, which is shown in a remarkable paper of the Brivanlou group[49]. They detected mechanisms of pattern formation and self-organization which were clearly related to the size of stem cell colonies. The colonies were cultured in 2D colony culture and even there, a size effect of the stem cell colony could be shown. More deliberately tuned than classical morphogen gradients, they describe a mechanism of solute-dependent inhibitory mechanisms that sheds light on the underlying mechanisms of how diffusion distance influences cell fate.

    Our experimental setup does not allow a deeper understanding of the regulatory interdependencies on a mechanistic level. For this, follow-up studies would be needed targeting a deeper understanding of the separate influence of spheroid size vs hypoxia. There, viability and functionality of cells in relation to spheroid sizes as well as individual gene expression on a single cellular level in relation to the spatial position within a spheroid should be analyzed.

    Putting these observations into a larger context, it gets clear that if spheroid size and oxygen tension lead to such deliberate fate decisions, we would need to incorporate such knowledge into stem cell differentiation protocols. Fate decision checkpoints would need to be activated not only by soluble agents but additionally by spatiotemporal control. How this relates to our observed behavior of Bmp4 regulation will need further research.

    Looking at Map2, a spontaneous upregulation upon differentiation in 2D culture happens both in normoxia and hypoxia. In normoxia, Map2 is upregulated 3.7-fold whereas in hypoxia it is upregulated significantly lower with a 2.3-fold change, respectively (Fig. 1B). Also, here, 2D culture in hypoxia leads to an oxygen tension of 3.5% of virtually every cell. When cultured as a 3D spheroid, however, oxygen tension is supposedly lower than in 2D culture. If hypoxia alone was the trigger for the stem cells to express less Map2 than in normoxia like in 2D, small hypoxic 3D spheroids should therefore express less Map2 than in 2D hypoxia. However, taking into account that diffusion distance might not be linear as discussed above, within small hypoxic spheroids hypoxia could theoretically be not significantly higher than in hypoxic 2D. In this case, the regulatory behavior of Map2 in small 3D spheroids should be the same as in 2D. Unexpectedly, small hypoxic spheroids express significantly more Map2 than in hypoxia 2D (3.7 vs 2.3-fold upregulation, respectively; Fig. 1B). Also, here, the same discussion as in Bmp4 applies, and further research is needed on how much the lowering of oxygen tension in relation to spheroid size applies and which conclusions can be drawn. When cultured as large spheroids, the upregulation of Map2 in the normoxic cultivation is highest with a 7-fold increase compared to baseline (Fig. 1B). However, in these large spheroids, there is by definition significant hypoxia present. It is very difficult to directly measure oxygen concentration within a spheroid without destroying the spheroid architecture[46]. It is however recognized that any multicellular spheroid larger than 200 μm experiences relevant hypoxia[45]. In our study, the normoxic spheroids have reached 406 μm on average, therefore chronic hypoxia, possibly even core anoxia must be present[50]. Thus, although experiencing much more hypoxia than in small spheroids, why is Map2 significantly upregulated (7 vs 4.7-fold, respectively)? The opposing, hypoxia-independent regulatory mechanisms activated by spheroid size must therefore be much stronger than the effects of hypoxia alone. The significantly lower upregulation of large spheroids cultivated in hypoxia of 2.2-fold change (Fig. 1B) could be a similar effect as observed in the work of Skiles[48], wherefrom a certain low oxygen concentration on the entire regulatory mechanism breaks down as homeostasis cannot be maintained anymore.

    For the observed differences of Map2 expression in relation to hypoxia with spheroid size, the literature gives only very scarce data. Mostly studied in hypoxic brain damage models, some reaction on the hypoxic insult yields in colocalization of Map2 expression with HIF-1α, but the mechanism of this relationship remains blurry[51][52]. To address this question more thoroughly, detailed studies on cell survival in relation to spheroid size and oxygen tension would be needed.

    Looking at the Nes expression, in 2D the upregulation is a 4.4-fold change at normoxic conditions and a 3.2-fold change under hypoxia, respectively (Fig. 1C). In small 3D spheroids, there is an upregulation of 4.4-fold in normoxia and 6.7-fold in hypoxia, respectively (Fig. 1C). This upregulation of small spheroids in hypoxia is significant compared to hypoxic 2D, again indicating other, hypoxia-independent mechanisms for Nes gene regulation as hypoxic conditions in 2D and small spheroid are likely to be similar. In large spheroids cultivated in normoxia, the upregulation is 8.3-fold vs. large spheroids in hypoxia with blunted upregulation of 3.7-fold (Fig. 1C). Regarding the lower Nes expression in the large hypoxic spheroids, like described above in the other examples, most probably physiological regulatory mechanisms were broken down due to significant hypoxia up to anoxia, and regulation for this experimental condition has to be interpreted with caution.

    The influence of HIF-1α and hypoxia on Nes expression was already described on mesenchymal stem cells, wherein 2D cultures, hypoxia was leading to a HIF-1α dependent Nes overexpression on the RNA and protein level[53]. However, the mechanisms of this regulation are not clear. The authors here suggest indirect regulation by VEGF activation. To the best of our knowledge, Nes does not have functional hypoxia response elements (HRE’s) in the promoter region, which would be needed for direct activation by HIF-1α[54].

    In our study, the mechanisms of the Nes regulation is not solely attributable to spheroid size or oxygen tension, but most likely driven by opposing effects of either stimuli. The many other putative regulatory influences like the diffusion control mechanism of Bmp4 described by Brivanlou (above)[49] are possible explanations. However, as before, this data shows the importance of controlling both spheroid size and oxygen tension in order to be able to understand the individual effects.

    The whole experimental approach was additionally performed with HIF-1α deficient (HIF-1α-/-) stem cells. In comparison to the wild type cells, in HIF-1α deficient cells there is almost no significant regulation observed, and if so, there is a very high standard deviation compared to wild type cells. This happened in any condition tested. The lack of robustly detectable regulation in the absence of HIF-1α in contrast to wild type cells points to a central role of HIF-1α in culture-dependent early differentiation gene expression. This can be best seen in the example of Bmp4, where the strong differential regulation in HIF-1α+/+ cell spheroids is not observed in HIF-1α-/- cells (Fig. 1A, D). This is in line with the literature where Bmp4 is found to act downstream of HIF-1α[55]. But how exactly HIF-1α is mechanistically involved leading to such a strong differential regulation needs further studies.

    Interestingly, BMP-4 is induced in hepatocellular carcinoma by hypoxia and promotes tumor progression. This effect could be abolished by transfection of a dominant-negative form of HIF-1α[56]. Striking similarities exist between molecular mechanisms driving embryonic liver development and the progression of hepatocellular carcinoma, making this an example of how stem cell and cancer research share a lot of commonalities.

    In summary, the described observations demonstrate that gene regulation of Bmp4, Map2, and Nes in stem cell cultures is dependent not only on ambient oxygen tension but also on the spheroid size.

    Relating to cancer research, the knowledge of spheroid biology is especially helpful and has been applied broadly as diffusion gradients play a central role in cancer metabolism as well. Only cell spheroids have allowed us to understand tumor biology better and also their resistance to chemo- and radiotherapy[20][56][57]. But the impact of cell spheroids in stem cells and cancer research is much larger than originally thought. With the discovery of cancer stem cells and their identification in various types of solid tumors, there is now a common ground of research in both areas. Cancer stem cells have been detected in the brain, breast, lung, colon, melanoma, and ovarian cancer[58] and the list is expanding rapidly. Based on this data, one of the keys for therapeutic advancement for cancer treatment lies within the understanding of stem cell biology. At the same time, it is well known that the biggest danger in stem cell therapy is tumor formation. Therefore, understanding the mechanisms of fate decisions in stem cells is not only imperative for correct differentiation of stem cells for therapeutic applications, but it also allows to survey this correct differentiation with the knowledge gained from cancer stem cell research, where "triggering events" of stem cells getting out of cell-cycle control, are being studied[59].

    The importance of these principles can be seen in clinics. The cancer patient is usually not killed by the primary tumor. The patient is killed by the metastases. These, in turn, develop because the invasive and metastasizing property of tumor cells is unleashed by hypoxia, and hypoxia is controlled by diffusion distance, and diffusion distance is controlled by the spheroid size, i.e. the size of the avascular portion of a growing tumor. In short: the more hypoxic a tumor, the more aggressive its behavior[60][31].

    Here, science has a direct legal and regulatory impact. Modern risk management methods, which are a prerequisite for any approval of new therapies, are based on such considerations. If derivations for the future are possible on the basis of reproducible observations, i.e. how often could a possible dangerous event occur, and how serious would this event be, then the integration of these observations is legally obligatory[61][62].

    The data shown here is only a little hint about the importance of rigid control of cell culture conditions like spheroid size and ambient oxygen tension for cellular differentiation protocols. The interdependent and sometimes opposing regulatory effects are not well understood. Because of the clinical significance, these effects should be investigated in detail[49][63][64].

    More and more elements needed for physiological cell differentiation are being uncovered. Recent literature now shows that the understanding of spheroid size control on fate decisions is growing as architectural support of every single spheroid within a micropatterned surface allowed more directed differentiation towards specific cell types for clinical applications[64][65][66][67][68]. It is getting clear that only a stringent control of all involved biological parameters enforced by suitable and appropriate 3D cell culture platforms will allow the safe differentiation of stem cells for clinical applications.

    Conclusionslink

    Our data shows that cell culture conditions, especially spheroid size, are influencing gene expression in early stem cell differentiation. Spheroid size control not only allows assurance of equal oxygen tension throughout a population of cell spheroids, it also impacts gene expression by mechanisms that cannot be explained by oxygen tension alone. To what extent HIF-1α is responsible for these early regulatory steps needs to be further elaborated.

    The relevance of this data lies within the current developments of regenerative medicine, drug screening, and cancer research where 3D cell spheroids are increasingly being used. Understanding the inherent biological properties of stem cells and the underlying mechanisms allowing fate decisions are on one hand essential for successful cell differentiation towards clinical applications and on the other hand essential for the prevention of uncontrolled growth leading to tumor formation. Therefore, current and future therapeutic research pipelines must adhere, besides other factors, to these principles of spheroid size control before attempting steps towards clinical applications.

    Limitationslink

    There are several limitations in our study: First, the only genetic analysis does not lead to conclusions about protein expression. The investigation at the protein level would allow identifying a correlation between genotype and protein synthesis. Second, the formation of cells as 3D spheroids was analyzed in this study with respect to overall genetics. No statement can be made as to which gene expression is different in respect to single-cell gene expression. Our study shows the average gene expression of the entire spheroid. Third, various parameters such as spheroid size and oxygen tension have an influence on the outcome. The effects of the individual factors in this system are still poorly understood and a mechanistic description of the process is not yet feasible. Furthermore, only 4 markers were used in order to get an orientation about the effect of culture conditions on early spontaneous differentiation in a principal manner. For a deeper understanding, our results must be further validated and substantiated with mechanistic studies about the spheroid size and oxygen tension as individual components.

    Conjectureslink

    Further investigations of stem cell fate within spheroids and in relation to oxygen tension are necessary. According to the studies by Deglincerti and Huizar[69][36], which analyzed embryological fate decision mechanisms in relation to cell conglomerate size offers important insights for the understanding of the mechanisms of self-organization and patterning. Based on our data, fate cascade should be investigated in relation to HIF-1α, spheroid size, and ambient oxygen control from this perspective. Information on the stimulation of both single cells and spheroids with BMP and as a function of oxygen tension will provide further insights into how such an environment affects cells. As differentiation of stem cells for future therapies is based on these principles, we suggest intense research activities which finally may bridge the gap between developmental biology and clinical applications.

    Methodslink

    Abbreviations

    2D: Two-dimensional

    3D: Three-dimensional

    ES cells: Embryonic stem cells

    FFC: Free-floating clusters

    LIF: Leukemia inhibitory factor

    TGF-β: Transforming growth factor-beta

    VEGF: Vascular endothelial growth factor

    Map2: Microtubule-associated protein 2

    Bmp4: Bone morphogenic protein 4

    Nes: Nestin

    vs: Versus

    HIF-1α: Hypoxia-inducible factor 1α

    HM-1 embryonic stem cell culture

    HM-1 mES cells, an inbred mouse ES cell line, were knocked out for HIF-1α to produce HIF-1α double deficient (HIF-1α-/-) clones[70]. HM-1 cultivation of wild type (HIF-1α+/+) and HIF-1α-/- was initially done on gelatine-coated Petri dishes as described previously[71]. However, this culturing method was found to promote attachment-induced differentiation of the cells residing on the border of the typical stem cell spheroid growth pattern. As this differentiation behavior was already visible by the eye (Suppl. Fig. 1), we have decided to culture the HM-1 mES cells as free-floating spheroids (FFS).

    Formation of free-floating ES cell spheroids to avoid attachment-induced differentiation took place spontaneously by cultivation in bacterial Petri dishes (Greiner Bio-One, Nr. 639102) with HM-1 ES cells seeded at a density of 4000 (3 days between splitting) or 10’000 to 20’000 (2 days between splitting) cells per ml of medium (10 ml medium per 10 cm Petri dish). FFS were split before reaching a size of 150–200 μm in order to avoid uncontrolled central differentiation and necrosis due to LIF diffusion limitation and hypoxia. Cell splitting was performed by aspirating FFS, spinning cell spheroids for 2–4 min at 260–300 x g, and washing with prewarmed standard phosphate-buffered saline without calcium and magnesium (PBS). Dissociation was done by adding prewarmed non-enzymatic cell dissociation buffer (Sigma-Aldrich C1419) followed by incubation for 10–15 min with occasional shaking, then dissociating the FFS with pipetting up and down using a 5 ml serological pipet (no strong mechanical disruption with narrow pipettes like glass Pasteur pipettes or tips needed). Upon complete dissociation, the reaction was stopped by adding ES medium, washed once with ES medium, counted, and seeded.

    ES cell culture medium

    For the ES cell medium, a stock and a working solution were prepared. The stock solution consisted of Dulbecco’s modified eagle medium (DMEM) with 4.5 g/l glucose and UltraGlutamineTM (Lonza BE04-687F/U1), 1% sodium pyruvate (Invitrogen/Gibco 11360-039), 1% MEM non-essential amino acids (Invitrogen/Gibco 11140-035) and 0.05 mM β-mercaptoethanol (Sigma-Aldrich, M6250). The working medium consisted of a stock solution, 20% stem cell tested fetal bovine serum (FBS, USA origin pre-tested ES cells, Chemie Brunschwig AG, Cat-Nr. 16000-044, Lot. 1057263) and 1000 U/ml leukemia inhibiting factor LIF (ESGRO LIF ESG1107). The differentiation medium consists of the ES cell culture medium, but without LIF.

    ES cell differentiation

    The ES cell cultivation was done in classical cell culture incubators (Forma Scientific) at 37°C humidified atmosphere with ambient oxygen tension (20% O2) supplemented with 5% CO2. Stem cell differentiation was done either in normoxia or in a hypoxia chamber (3.5% O2; Coy Laboratory Products Inc.). Neither a standard physiological oxygen concentration nor the name "physoxia or physioxia" is consistently defined in the literature[34][72] which is why we use the classical term hypoxia.

    Hanging drop cultivation of small and large stem cell clusters

    HM-1 ES cells were kept in maintenance culture with LIF as FFS. From this maintenance culture, hanging drops were produced by pipetting dissociated ES cells in a differentiation medium. To maintain equally distributed cell numbers, a multichannel repeater (Matrix Technologies Corp.) was used taking care of pipetting the carefully stirred cell solution and pipetting at elaborate speed. Drops were pipetted with a volume of 30 µl on the lid of 145×20 mm Petri dishes (Greiner Bio-One, Nr. 639102). To cover a large experimental range, small spheroids with 15 cells per drop and large spheroids with 2000 cells per drop were pipetted. The bottom of the dish was filled with PBS to prevent the hanging drops from drying out. HM-1 cell spheroids were spontaneously differentiated for 4 days.

    Cell spheroids were evaluated by an inverted light microscope (Zeiss Axiovert) with a camera shot directly through the ocular lens (Sony Ericsson K800i) on day 4. The diameter of each spheroid was determined using ImageJ (version 2.0.0-rc-43/1.50e) software. Thereafter, data were exported to Microsoft Excel, and the mean and standard deviation was calculated.

    RNA extraction and co-application reverse transcription

    RNA extraction was performed using the Macherey-Nagel NucleoSpin RNA II Kit (Macherey-Nagel, 740955.50). All steps were performed according to the manufacturer's instructions. RNA concentration was measured using a nanodrop device (Thermo Scientific).

    Modified cDNA production method with co-application reverse transcription (RT) and SuperScript III reverse transcriptase (Thermo Fisher 18080093) were adapted from Zhu[73], who developed this technique to combine the advantage and selectivity of oligo-dT priming with the stability and ubiquity of 18S internal standard. The reliability of this method in terms of reproducibility and precision of gene expression detection is described in detail in the supplementary material (Suppl. Fig. 2 and Suppl. Fig. 3).

    For the co-RT reaction, 100 ng RNA was mixed with 1 μl of oligo (dT)20 primer (50 μM), 1 μl of 18S-RNA specific primer (50 μM; 5’-GAGCTGGAATTACCGCGGCT-3’[73]), 1 μl of dNTPs (10 mM) and RNAse-free water. The mixture with a final volume of 14 μl was incubated at 65°C for 5 min. Afterward, 4 μl 5× first-strand buffer, 1 μl DTT (0.1 M), 0.25 μl SuperScript III reverse transcriptase (Invitrogen), and 0.75 μl water were added to the reaction mixture and incubated for 60 min at 50°C, followed by an inactivation step at 70°C for 15 min.

    Real-time PCR

    Cells used for the experiments were sequentially prepared as independent biological triplicates. Real-time PCR was performed using the TaqMan system (Applied Biosystems). According to manufacturer's guidelines, 20 μl reaction volume per sample containing 10 μl universal PCR master mix (TaqMan System, part Nr. 4331182, Thermo Fisher), 4 μl 5× TaqMan assay (reference sequence NM_007554 for Bmp4, NM_008632 for Map2 and NM_016701 for Nes), 2 μl cDNA and 4 μl water were mixed. PCR was loaded in duplicates and all experiments contained no template controls. Cycling parameters corresponded to a standard program with 40 cycles for 15-sec denaturation at 95°C and 1 min annealing/extension at 60°C. Data analysis was performed with the ABI Prism Software (Applied Biosystems) and Microsoft Excel. The delta-delta ct (ddct) method for data analysis was used with relative gene expression value change vs a starting (reference) point. This point consisted of the HM-1 cells kept as FFS in maintenance culture of which the differentiation experiment started. In the figure, this starting point equals 1 on the y axis.

    Statistical analysis

    Statistical analysis has been done with GraphPad Prism 7 software (GraphPad Software, Inc.) using Bonferroni’s multiple comparison test. CI represents confidence interval, and SD represents the standard deviation (see SD values in Suppl. Material Table 1). Results are representative of 3 biological replicates. The replicates consisted of different ES cell passages and each experiment was performed on a different day. Of each biological replicate, technical duplicates were used for the real-time PCR to minimize pipetting error.

    All original data including lab journals and raw data are available upon request.

    Funding Statementlink

    Julius Müller foundation, Theodor and Ida Herzog-Egli foundation and private anonymous sponsor from the UBS.

    Conflict of interestlink

    The authors do declare conflicts of interest:

    P. K. and P. W. are employees of Kugelmeiers AG. W. M. is an employee of InSphero AG.
    Ethics Statementlink

    Not Applicable.

    No fraudulence is committed in performing these experiments or during processing of the data. We understand that in the case of fraudulence, the study can be retracted by ScienceMatters.

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