Stem cell systems and regeneration in planaria

Controlling stem cell division rates constitutes a further critical aspect of organismal stem cell homeostasis. Many systems display a basal rate of stem cell activity during normal tissue turnover, which can dramatically increase in response to injury, for example (reviewed by Arwert et al. 2012). Similarly, the planarian Neoblast system clearly switches between regulatory states. At steady state, Neoblasts divide at a basal rate much like stem cells in high turnover tissues like the gut or the epidermis. Interestingly, neoblast divisions continue during prolonged periods of starvation, even though starving planarians shrink continuously due to decreasing cell numbers (Baguñà and Romero 1981; Oviedo et al. 2003; Takeda et al. 2009; González-Estévez et al. 2012a). The catabolism of dying cells likely fuels divisions during starvation, thus maintaining tissue turnover at the cost of progressive cell loss (Baguñà and Romero 1981; Baguñà et al. 1990). Feeding has the opposite effect: Ingested food elicits a rapid and pronounced increase in the fraction of Neoblasts in M-phase, peaking already 8 h post feeding and taking several days to return to baseline (Baguñà 1974; Kang and Sánchez Alvarado 2009). This transient increase in Neoblast divisions temporarily tips the steady state towards a net increase in cell numbers, leading to a burst of growth at the whole animal level. Wounding has a similar effect on Neoblast mitotic activity, causing a sharp peak of M-phase Neoblasts within 6–8 h post injury and a second, more sustained mitotic peak in the wound vicinity at 3 days post wounding (Wenemoser and Reddien 2010; Baguñà 1976b). Progenitors generated during wounding are thought to migrate to the injury site and to give rise to the regeneration blastema (Aboobaker 2011; Forsthoefel and Newmark 2009; Baguñà 2012).

Interestingly, injuries as small as a needle prick can elicit the rapid injury response component (Wenemoser and Reddien 2010).

What constitutes the Neoblast reserve capacity — a non-cycling Neoblast subpopulation set aside specifically for activation during growth or repair? Or acceleration of cell cycle dynamics within a continuously cycling population? The mitotic peak occurring already at 6–8 h post wounding/feeding has been interpreted in favor of a G2-arrested subpopulation (Baguñà 1974; Saló and Baguñà 1984). The introduction of BrdU pulse labeling by Newmark and Sánchez Alvarado challenged this idea (Newmark and Sánchez Alvarado 2000). The authors calculated a mean G2 duration of 5 h based on fractional labeling of mitoses, suggesting that a G2-arrested population might not be required to explain the rapid feeding-induced rise of mitoses. Further, the finding that 12 h after feeding a BrdU/food mixture or after 3 days of continuous BrdU injections all dividing cells were BrdU-positive, led the authors to the conclusion that all Neoblasts divide continuously. A caveat to this interpretation was the intermittently discovered activation of Neoblasts even by injection injuries, which has so far precluded BrdU measurements of neoblast dynamics in the unstimulated state (Wagner et al. 2011; Wenemoser and Reddien 2010). This leaves open the very real possibility that under unstimulated conditions some Neoblasts might take considerably longer than 3 days to divide or maybe even not divide at all. Hence the cellular mechanisms by which the planarian stem cell system adjusts progeny output to changing physiological needs remain unclear. The importance of the question also in terms of Neoblast population heterogeneity and the availability of more versatile Neoblast markers now warrant an experimental return to these questions. The recently developed soaking method for BrdU delivery (Cowles et al.

2012) might offer a first opportunity to examine Neoblast cycling dynamics under unstimulated conditions.

The fact that the Neoblast system can dramatically change its progeny output emphasizes the importance of proliferation controlling signals. From the above, the Neoblast division control network can be expected to encompass local self-renewal signals, global activating signals released in response to wounding or changes in metabolic status, as well as negative feedback loops mediating the return to basal division rates. So far, only incidental observations provide glimpses of the molecular underpinning. Early studies suggested an effect of neuropeptides on Neoblast division rates (Baguñà et al. 1989; Saló and Baguñà 1986), which have been interpreted in support of a general role of the nervous system in controlling Neoblast proliferation (Rossi et al. 2012; Baguñà et al. 1989). Hh signaling exerts a global influence on mitotic cell densities and Hh is also expressed in the nervous system (Rink et al. 2009; Yazawa et al. 2009). However, neither in this case nor in others has an explicit role of the nervous system in Neoblast proliferation control been established. Jun-kinase activation appears to be generally required for the initiation of mitosis (Tasaki et al. 2011b), but its upstream regulators remain to be identified. Smed-inx11, a gap junction gene required for Neoblast maintenance, has been suggested as part of local niche signals (Oviedo and Levin 2007). The two FGF receptors specifically expressed in Neoblasts are further interesting candidates in this respect (Wagner et al. 2012). The Wnt signaling pathway, which provides important niche signals in multiple systems (Nusse 2008; Klaus and Birchmeier 2008), has so far not been implicated in planarian stem cell maintenance. Instead, planarian Wnt signaling has prominent effects on body plan patterning (Gurley et al. 2008; Petersen and Reddien 2008; Iglesias et al. 2008).

Feedback loops dampening the Neoblast response may include SMED-EGFR-1, an EGF receptor expressed in the planarian intestine (Fraguas et al. 2011) and Dj-P2X, a likely ATP-gated plasma membrane channel expressed in a subset of Neoblasts (Sakurai et al. 2012). The TOR pathway, which has diverse functions in cell growth and metabolism (Zoncu et al. 2011), recently emerged as an important component in orchestrating the Neoblast response to wounding and regeneration (Peiris et al. 2012; Tu et al. 2012; González-Estévez et al. 2012b). Neither wound nor food response signals have been identified, but a recent report implicates planarian Insulin signaling in the maintenance of Neoblast divisions during starvation (Miller and Newmark 2012).

Clearly, key elements of the neoblast control network await identification and much remains to be learned about the mechanistic and dynamic interconnections between pathways and cell types. Further, planarians not only regulate Neoblast proliferation, but also the rates of differentiated cell removal, likely even in a tissue-specific manner (González-Estévez et al. 2012a; Pellettieri et al. 2010). The signals and signaling pathways controlling this important part of the steady state equation remain largely unknown, but the recent studies of planarian TOR signaling tentatively implicate this pathway (Peiris et al. 2012; Tu et al. 2012).

A further critical factor in maintaining the steady state between stem cells and differentiated cells is the appropriate orchestration of stem cell progeny differentiation. Clearly, the complexity of this task increases with the number of available choices. Vertebrate adult stem cells are tissue specific and possible progeny fates are therefore limited, e.g., Goblet-, Paneth-, Enteroendocrine cell and absorptive enterocytes in the vertebrate intestine (van der Flier and Clevers 2009). Pluripotent cNeoblasts giving rise to all planarian cell types represent a worst case scenario in terms of fate choice complexity, raising a number of important questions: Are Neoblast progenitor fate choices intrinsically programmed or influenced by the momentary needs of the tissue? At which point of the lineage downstream of cNeoblasts are cell fates determined? How are fate choices coordinated with the global organization of the planarian body plan?

The so-called category markers discovered by Eisenhoffer and colleagues provided first insights into the spatiotemporal orchestration of Neoblast progeny differentiation (Eisenhoffer et al. 2008). Based on the differential downregulation kinetics of irradiation sensitive genes and on BrdU pulse labeling, this study defined two gene categories likely expressed sequentially in differentiating postmitotic Neoblast progeny (Cat. 2: Early progeny; Cat. 3: Late progeny; Cat. 1: dividing Neoblasts). The distinct expression domains of the category markers suggested that Neoblast progeny are “born” deep within the mesenchyme and undergo outward migration during the course of differentiation (Eisenhoffer et al. 2008), consistent with previous BrdU-pulse labeling studies (Newmark and Sánchez Alvarado 2000). The Category markers also provided an important assay for identifying molecular regulators of progeny differentiation. Pearson and colleagues found that Smed-p53, the homologue of the vertebrate tumor suppressor p53, is required for the transition between Cat. 1 and 2 expression, as Smed-p53(RNAi) causes the accumulation of mitotic Neoblasts at the expense of progenitors (Pearson and Sánchez Alvarado 2010). Erk kinase activation appears to be similarly required for exiting the proliferative state (Tasaki et al. 2011a). The formation of Cat. 3 expressing cells, on the other hand, requires the polycomb chromatin remodeling complex Smed-CHD-4 (Scimone et al. 2010; Wagner et al. 2012). A further chromatin remodeling complex member, Dj-RbAp48, has also been implicated in Neoblast differentiation, emphasizing the likely importance of chromatin rearrangements during the transition from pluripotency to terminal differentiation (Bonuccelli et al. 2010). Recently, Wagner and colleagues found that the relative ratios between Cat.

1, -2, and -3 expressing cells remain constant during the clonal expansion of cNeoblast colonies in sublethally irradiated animals (Wagner et al. 2012). Besides the interesting conclusion that self-amplifying Neoblast divisions occur at a fixed proportion to progeny-generating divisions (at least during clonal expansion), this finding allowed a quantitative distinction between Neoblast self-renewal and differentiation defects. This new tool confirmed the role of previously reported differentiation factors and further implicated the likely chromatoid body component Smed-Vasa-1 and an as yet uncharacterized zinc finger transcription factor into regulating the transition between proliferating Neoblasts and postmitotic progeny. What remains unclear is the identity of the cells expressing the category markers, in particular the extent by which they represent generic differentiation stages or early stages of a specific lineage with unknown end point (Eisenhoffer et al. 2008; Scimone et al. 2010).

One recent publication in particular provides a fascinating bird’s eye view of the differentiation process from Neoblasts all the way to the terminally differentiated cells types of the planarian eye (Lapan and Reddien 2011). The authors defined a set of transcription factors expressed in- and required for the differentiation of planarian optic cup cells and photoreceptive neurons. Using these tools to ask where and when eye precursors arise during head regeneration, the authors reached two important conclusions: First, eye precursors differentiate far from the forming eye, giving rise to a ~200 μm long “trail” of eye progenitor cells migrating distally from the base of the blastema. Second, at its proximal boundary (i.e., close to the old tissue), the optic cup precursor cells were found to co-express the Neoblast marker genes Smed-H2b and smedwi-1. Similarly, transcription factors required for protonephridial cell fate specification (Scimone et al. 2011), general neuronal differentiation (Wenemoser et al. 2012), tyrosine hydroxylase as marker of dopaminergic neurons (Nishimura et al. 2011) and a muscle-specific myosin heavy chain (Hayashi et al. 2010) have been shown to co-express with Neoblast markers, generalizing the onset of differentiation towards specific cell fates already within smedwi-1 expressing cells.

The mechanisms and conceptual principles orchestrating progenitor differentiation in planarians are currently mainly a matter of speculation. Are progenitor fate choices under the control of external signals, such that particular cell types could differentiate “on demand” (Fig. 3a)? Or are fate choices the outcome of stochastic cell intrinsic decision making processes, as for example the differentiation of retinal precursor cells (Gomes et al. 2011)? “On demand” models entail flexibility in matching progenitor differentiation to local needs, for example the replacement of a dying cell by means of a concomitantly released differentiation cue. However, such models necessitate a multitude of specific “replace me” signals for the multitude of cell types in the organism and, more significantly, would render regeneration impossible as soon as all cells of a particular type were lost (e.g., loss of photoreceptors and their differentiation signal in a head amputation). The fact that planarians can regenerate all tissues and organs de novo therefore challenges any model requiring the presence of a differentiated cell for progenitor differentiation into this cell type. By contrast, progenitor fate choice via cell intrinsic mechanisms could accomplish the de novo specification of lost cell types, yet again at conceptual costs. During regeneration, the provision of the exact numbers and types of progenitors long before and far away from their assembly into tissues and organs (Lapan and Reddien 2011) is difficult to envisage on basis of stochastic mechanisms. During steady state, purely cell intrinsic fate choice would result in the exact same progenitor production throughout the animal, entailing the differentiation of cell types in places where they are of little use (e.g., photoreceptors in the tail).

Apoptosis or long-range migration could conceivably deal with supernumerary or out-of-place progenitors, but further phenomena difficult to envisage on basis of purely cell-intrinsic fate choice mechanisms include the size-threshold-dependent differentiation of reproductive organs (Newmark et al. 2008) or the changing need for epithelial cells during growth and degrowth due to changing surface to volume ratios.Fig. 3Concepts in stem cell lineage organization. a “Differentiation on demand”: signals from differentiated cells instruct the fate choice of a pluripotent progenitor. b Stochastic differentiation. Purely cell-intrinsic mechanisms determine the fate choice of a pluripotent progenitor. Tissue loss due to injury (red line symbolizing amputation plane) could affect fate choices in a, but not in b. c Hypothetical differentiation hierarchy utilizing a combination of mechanisms. Initial lineage segregation occurs via cell intrinsic mechanisms (top). Terminal cell fates arise from additional choice points within lineages, involving a combination of (1) local “differentiation on demand” signals in the tissue environment (bottom left); (2) global patterning signals (centre) and (3) self-assembly of complex structures by means of spatiotemporal interactions amongst progenitors. Note that the scheme does not distinguish neoblasts and postmitotic progeny: initial lineage segregation (top) amongst postmitotic progeny would imply uniform neoblast pluripotency; lineage segregation already within dividing cells would imply neoblast heterogeneity in form of transit amplifying cells

Both the above scenarios run into conceptual difficulties because they assume terminal cell fate specification at a single control point. However, a single control point is unlikely already in face of the sheer multitude of planarian cell types existing. Furthermore, cell fate choices during embryonic development result from the gradual restriction of differentiation potential via multiple differentiation cues. A hierarchical organization of Neoblast differentiation therefore appears likely (Baguñà et al. 1990), in particular one incorporating relatively general lineage restrictions at the top of the lineage tree (e.g., “neuronal”, “intestine” and “muscle”, or possibly “ectoderm”, “endoderm”, “mesoderm”) and the gradual specification of terminal cell fate (e.g., precise neuronal subtype) at later differentiation stages (Fig. 3c). The observed expression of the pigment cup marker Smed-tyrosinase in the immediate vicinity of the regenerating eye, yet the expression of “early” eye markers in much wider domains is broadly consistent with such a model (Lapan and Reddien 2011). Significantly, cell fate decisions in differentiation hierarchies are not taken at once, but represent the cumulative outcome of multiple intermediate control points. Differentiation hierarchies can therefore incorporate both cell-intrinsic and signal-mediated fate choice mechanisms at different control points, thus combining stability with flexibility in the fate choice problem. Execution of the initial lineage choice by cell intrinsic mechanisms, as for example the stochastic cell fate choice of retinal progenitors (Gomes et al. 2011), provides an appealing mechanism for guaranteeing long-term stability of the lineage tree. The aforementioned caveat of generating out of place progenitors becomes less important the more general the initial lineage choices are.

Except for the brain and pharynx, all major planarian organs including the CNS are rather uniformly distributed, suggesting similar requirements for generic “neuron”, “muscle” or “intestine” progenitors throughout the planarian body plan. Intrinsic choice mechanisms could remain in place during regeneration, as the de novo formation of any tissue would again require the same generic progenitor classes.

On the other hand, signal-mediated “on demand” progenitor fate choice mechanisms are appealing towards later stages of the differentiation hierarchy, especially because they leave room for self-organization. The de novo regeneration of the planarian eye via the coalescence of individually migrating progenitors arising far from their target site provides a striking example of self-organization (Lapan and Reddien 2011). Assembling a structure as complex as the eye necessitates both multiple cell fate choices and precise spatial arrangements of cells. Pattern formation, the analysis of collective properties arising from dynamic interactions (Bois et al. 2011; Gierer and Meinhardt 1972; Howard et al. 2011), provides an appealing conceptual framework for rationalizing de novo organ regeneration. Accordingly, a general commitment to a particular lineage could initiate specific signaling interactions amongst similar progenitors and the tissue environment, leading to progenitor coalescence concomitant with terminal progenitor fate choices (Fig. 3c). Pattern formation not only as consequence, but also as cause of progenitor fate choice could alleviate the aforementioned need for precise “counting” of progenitors long before the distant assembly of the organ. Nevertheless, it is important to stress the conceptual nature of the above discussion. The possibility remains that final fate choices occur already high up in the lineage and that Neoblasts in the postblastema region are therefore able to precisely gauge future progenitor requirements after all. In fact, the co-expression of the dopaminergic neuron marker Dj-tyrosine hydroxylase with Dj-piwi-1 (Nishimura et al. 2011), and the apparent specification of pigment cup cells at a similar state (Lapan and Reddien 2011) provide some evidence to this effect.

Important questions include the possibility of hierarchical differentiation stages already within the piwi + Neoblast population, the extent by which individual cell types and lineages compete for progenitors and whether regeneration and steady state turnover rely on the same or different lineage choice mechanisms. The observation that Smed-runt1(RNAi) leads to eye defects in regenerating, but not in uninjured animals (Wenemoser et al. 2012), could point towards regeneration specific fate choice mechanisms.

Which leaves the crucial question of how the regionalization of the planarian body plan is achieved, that is, why eyes and their associated cell types form only in the head and not in the tail of the animals? Or how regeneration rebuilds exactly what is missing. Clearly, these phenomena necessitate an influence of global body plan patterning signals over local cell fate choices (Lobo et al. 2012; Reddien 2011; Forsthoefel and Newmark 2009; Baguñà 2012). Mechanistic detail is once again lacking, but the profound effects of altered Smed-β-catenin-1 activity are conceptually important. β-Catenin is the intracellular effector of canonical Wnt signals (Clevers and Nusse 2012). In planarians, decreased activity of β-catenin-1 forces head regeneration irrespective of the wound context (Gurley et al. 2008; Iglesias et al. 2008; Petersen and Reddien 2008), increased activity has the opposite effect by dominantly forcing tail regeneration (Gurley et al. 2008). These phenotypes are remarkable, since the identity switch of regenerating tissues resulted from global manipulations of a single gene. β-Catenin-1 therefore cannot act as simple cell intrinsic fate determinant, which would have turned RNAi-treated animals into uniform masses of either anterior or posterior marker expressing cells. Instead, the result of perfectly patterned heads and tails indicates that β-catenin-1 activity exerts a binary choice high up in a tissue fate program. Embryonic organizers provide an interesting paradigm for how this might occur. Organizers are self-organizing and self-maintaining signaling centers (incidentally often specified via β-catenin), that orchestrate embryonic axis establishment (De Robertis 2009). Two aspects of the organizer concept are particularly appealing in planarian regeneration.

First, they self-assemble on basis of dynamic interactions between cells, which can account for pervasive head or tail regeneration competence without the need for pre-localized determinants (Meinhardt 2008, 2009). Second, organizers determine and spatially organize the lineage choices of surrounding cells (Niehrs 2004). The role of Smed-β-catenin-1 could consequently signify the choice between establishing one of two self-maintaining signaling systems at the injury site — either a Wnt/β-catenin-1-dependent positive feedback system mediating tail regeneration, or a mutually exclusive Wnt inhibitory system at sites of head regeneration. The signaling environments established by such “blastema organizers” could subsequently orchestrate lineage choices and spatial arrangement of differentiating progeny towards the reconstruction of a head or tail, respectively.

An influence of patterning signals over lineage choices necessitates region-specific cell fate determinants or factors mediating regional differentiation competence. An example for the former could be the LIM-homeodomain transcription factor Dj-ISLET. This protein is specifically required for proper tail regeneration, expressed in a narrow stripe of differentiating progeny and, interestingly, required for the maintained expression of tail fate determining Wnt ligands (Hayashi et al. 2011). The TALE-homeobox gene Smed-prep on the other hand is broadly required for head induction downstream of beta-catenin-1(RNAi) (Felix and Aboobaker 2010). TALE-homeobox genes can function as Hox co-factors, which would fit with a role of Smed-prep as head region selector gene. Importantly, the mechanisms specifying blastema fate also participate in the maintenance of the planarian body plan at steady state. Smed-betaCatenin1(RNAi) in non-regenerating animals causes the conversion of the tail into a head and the emergence of ectopic heads all along the body edge (Gurley et al. 2008; Iglesias et al. 2008; Petersen and Reddien 2008). Gene expression patterns suggest permanently high canonical Wnt signaling in the tail and low levels in the head, as in the respective regeneration blastemas (Gurley et al. 2010; Petersen and Reddien 2009; Adell et al. 2009). β-Catenin and canonical Wnt signaling therefore exert the same high-level lineage choices at steady state as during regeneration and the head-territory specific expression of Smed-prep in non-regenerating animals indicates the participation of similar factors. The challenge over the coming years will be the cell biological dissection of the signaling cascades and their influence on gene regulatory networks.

Both the regionalization of the planarian body plan and its astonishing regenerative abilities are therefore likely two different sides of the same coin: a pluripotent differentiation hierarchy under the influence of a regulative patterning system. The uniquely dynamic body architecture of planarians arises from the intimate entwinement between the stem cell lineage and the patterning systems. Progenitors differentiate according to patterning signals into cells that produce patterning signals. The end of cell fate choices therefore once again becomes a beginning and the pattern continuously replaces itself. How such pattern of signals manifests itself in the physical shape and proportions of the planarian body plan is possibly the most fascinating challenge posed by the model system. Meeting it will require a multidisciplinary systems biology approach, combining cell biology, biophysics and mathematical modeling. The prize are fundamental insights into a universal design principle of biological systems, the dynamic steady state.

Finally, how unusual are planarians and their pluripotent adult stem cell system in the context of evolution? Interestingly, Neoblast-like somatic stem cells are being discovered in a growing list of animals. piwi +, bruno + and PDX10 + positive stem cells occur within the posterior growth zone of several annelid species, which adds new segments during growth (Giani et al. 2011; Yoshida-Noro and Tochinai 2009; Rebscher et al. 2007). Acoels, either basal bilateria or basal deuterostomes (Ruiz-Trillo 1999; Philippe et al. 2011; Bourlat et al. 2006), harbor a Neoblast system that closely resembles the one of planarians (De Mulder et al. 2009). Ctenophores (Alié et al. 2011) and cnidarians maintain dynamic stem cell systems that express piwi, vasa and nanos and, at least in the case of the cnidarians, are able to regenerate the germ cells as well (Mochizuki et al. 2001; Rebscher et al. 2008; Denker et al. 2008; Mochizuki et al. 2000). Sponges as the evolutionarily oldest extant metazoans harbor pluripotent piwi+ stem cells that also give rise to the germ line (Funayama et al. 2010; Funayama 2010). The tunicates, a subphylum at the base of the vertebrates, provide fascinating examples of whole body regeneration from pluripotent and piwi+ stem cells (reviewed by Kürn et al. 2011).

Flatworms are therefore neither unique in possessing pluripotent somatic stem cells, nor are they the only animals that undergo continuous turnover. Rather, stem cell systems across the animal kingdom come as a continuum of potencies and activities, in which Planarians mark a dynamic extreme. Hydra is situated nearby, displaying continuous body turnover, yet driven by independent multi- and unipotent cell lineages. Vertebrates with extremely tissue-specific turnover rates and tissue-specific stem cells reside somewhere in the middle, while C. elegans completely lacking adult somatic stem cells and somatic cell turnover occupies the “static” extreme of the spectrum. Similarly, the mechanisms segregating the pluripotent germ line from somatic lineages range from differentiation from pluripotent somatic stem cells in hydra, planarians or sponges via embryonic epigenesis in mouse to the segregation of maternally inherited “immortal” germ plasm in fly and C. elegans (Extavour 2007). Based on these observations, pluripotent somatic stem cells have been suggested as the ancestral state of animal stem cell systems (Agata et al. 2006; Extavour 2007; Blackstone and Jasker 2003). Tissue specific somatic stem cells might represent a secondary adaptation to the increasing size and functional specialization of body parts. This view would predict that the molecular components of pluripotency were initially shared between the pluripotent somatic stem cells and the germ line, before becoming increasingly restricted to the germ line. The expression of piwi and other germ line genes in the pluri- and multipotent stem cell systems of invertebrates, but generally not in the lineage restricted vertebrate stem cells, would indeed fit this picture.

Or are cNeoblasts and other pluripotent invertebrate stem cells pre-meiotic germ cells instead that have maintained the ability to contribute to the somatic lineages? Clearly, studying the embryonic origins of Neoblasts and similar cells in other emerging invertebrate model systems now provide experimental opportunities to approach the evolution of pluripotency and animal stem cell systems in general.

Planarians as model system contribute unique perspectives to current problems in stem cell research.

Their first asset is an abundance of adult stem cells, so called cNeoblasts. The recent demonstration of cNeoblast pluripotency in single cell transplants has been an important achievement (Wagner et al. 2011). The phylogenetic distances between cNeoblasts and mammalian ES and IPS cells provide unique opportunities for investigating whether pluripotency emerges from an evolutionarily conserved core mechanism or instead from general interactions between cellular processes as a systems property. The unknown degree of population heterogeneity amongst Neoblasts remains both a conceptual and experimental bottleneck. New tools are required for the definition of Neoblast subpopulations based on molecular and functional criteria (e.g., stem cell potency, self-renewing capacity). Establishing the fraction of pluripotent cNeoblasts amongst smedwi-1 expressing cells, the isolation of pure cNeoblast preparations, the establishment of in vitro culture conditions and the localization of cNeoblasts within their tissue microenvironment represent important future milestones.

Second, Neoblasts are the sole source of new cells in planarians and they divide continuously to replace all differentiated cell types. Planarians therefore exist in a dynamic steady state between a single proliferating stem cell type and multiple short-lived differentiated cells. Maintenance of the steady state constitutes a universal problem in any stem cell containing tissue, yet the phenomenon remains poorly understood. Their complete turnover within a matter of weeks makes planarians uniquely suitable for studying the underlying mechanisms and conceptual principles. Key challenges include the identification of signaling systems controlling Neoblast proliferation and differentiated cell turnover, the orchestration of progenitor differentiation downstream of the pluripotent cNeoblasts and a systematic analysis of cell movements at steady state and during regeneration. The development of planarian transgenesis tools are especially important in addressing these questions.

Third, the ability of planarians to maintain their body plan in face of constant turnover is simply fascinating. Planarians grow and de-grow by changing overall cell numbers depending on food availability, leading to a 40-fold variation in body size between 0.5 mm and 20 mm in the case of S. mediterranea. Moreover, even random injury remnants can restore the body plan by regeneration. Understanding the mechanisms that maintain and re-establish the dynamic steady state between Neoblasts and differentiated cells within the exact shape, size and proportions of the planarian body plan constitutes possibly the greatest frontier in planarian stem cell research. A crucial missing link between morphogenesis and the stem cell system is the currently unknown intersection point of patterning signals with progenitor fate choices. The origin and mechanisms of the mechanical forces required to convert signaling patterns into physical shape represents a further frontier. As for any steady state, understanding the planarian body plan in mechanistic detail will ultimately require mathematical modeling. Quantitative measurements are a crucial prerequisite to move into this direction and data relating to such parameters as progenitor production rates, cell flows and cell turnover rates will represent important contributions.

What planarians can uniquely contribute to our understanding of stem cells is the systems perspective: an integrated view of the stem cell and its descendants as a dynamic steady state.