Gap Junctional Blockade Stochastically Induces Different Species-Specific Head Anatomies in Genetically Wild-Type Girardia dorotocephala Flatworms

The shape of an animal body plan is constructed from protein components encoded by the genome. However, bioelectric networks composed of many cell types have their own intrinsic dynamics, and can drive distinct morphological outcomes during embryogenesis and regeneration. Planarian flatworms are a popular system for exploring body plan patterning due to their regenerative capacity, but despite considerable molecular information regarding stem cell differentiation and basic axial patterning, very little is known about how distinct head shapes are produced. Here, we show that after decapitation in G. dorotocephala, a transient perturbation of physiological connectivity among cells (using the gap junction blocker octanol) can result in regenerated heads with quite different shapes, stochastically matching other known species of planaria (S. mediterranea, D. japonica, and P. felina). We use morphometric analysis to quantify the ability of physiological network perturbations to induce different species-specific head shapes from the same genome. Moreover, we present a computational agent-based model of cell and physical dynamics during regeneration that quantitatively reproduces the observed shape changes. Morphological alterations induced in a genomically wild-type G. dorotocephala during regeneration include not only the shape of the head but also the morphology of the brain, the characteristic distribution of adult stem cells (neoblasts), and the bioelectric gradients of resting potential within the anterior tissues. Interestingly, the shape change is not permanent; after regeneration is complete, intact animals remodel back to G. dorotocephala-appropriate head shape within several weeks in a secondary phase of remodeling following initial complete regeneration.

We present a conceptual model to guide future work to delineate the molecular mechanisms by which bioelectric networks stochastically select among a small set of discrete head morphologies. Taken together, these data and analyses shed light on important physiological modifiers of morphological information in dictating species-specific shape, and reveal them to be a novel instructive input into head patterning in regenerating planaria.

Development, cancer suppression, large-scale remodeling, and regeneration all hinge on an organism’s ability to store and process information about its correct anatomical structure, and correct any deviations from that structure that may occur during injury or other environmental impacts [1,2]. It is commonly assumed that species-specific anatomical shapes are encoded in the genome, although data from environmental epigenetics have long suggested that morphological outcomes are a function of not only inheritance but also of environment and life history inputs [3].

Whether via nucleotide sequences or chromatin modifications, the genome does not specify organismal 3-dimensional shape directly. Instead, large-scale morphology is an emergent feature of the dynamics of complex networks of activity carried out by cells. Thus, pattern formation is the outcome of a rich layer of chemical and physical processes occurring between DNA and anatomy. Indeed, distinct morphologies can arise from a single genotype [4,5]. Understanding how cells communicate and coordinate their functions in vivo to reliably form complex body plans and organs is of fundamental importance not only for evolutionary developmental biology, but also for biomedicine [6]. Transformative advances in regenerative medicine and synthetic bioengineering require us to know which inputs can be provided to a cellular system to induce specific morphological outcomes—rational control of growth and form. This is a truly difficult problem because of the complex nonlinearity of biological regulation [7]. Hence, step 1 is uncovering processes that provide instructive control over the determination of large-scale shape.

Most of the field today is focused on gene-regulatory networks [8,9] and physical forces [10,11] in an effort to understand how final patterning outcomes arise and are maintained during development and regeneration. However, another fascinating layer of biological regulation has recently been implicated in the control of morphogenesis: endogenous bioelectrical signaling [12,13,14]. Spatio-temporal gradients of resting potential among all cell types (not just excitable nerve and muscle) can regulate cell proliferation, migration, shape, and apoptosis [15,16]. Even more importantly, they can function as instructive cues for large-scale morphogenesis, regulating positional information, organ identity, size, and axial polarity [1,17,18]. Recent work has implicated these voltage gradients in the regulation of anterior-posterior polarity [19,20], appendage regeneration [21,22,23,24], craniofacial patterning [25], left-right asymmetry [26,27,28,29], eye development [30,31], and brain patterning [32]. Numerous studies have now identified transduction mechanisms linking bioelectric properties with downstream transcriptional and epigenetic targets [13,18,33,34], thus revealing how these physical properties integrate with genetic information during patterning.

Three aspects of bioelectric signaling make them particularly relevant to the origin of large-scale shape and the role of the genome. First, bioelectric patterns specify shape in a distributed (non-local) manner: several studies have shown that the size, shape, and identity of specific structures integrates bioelectrical information from remote regions [32,35,36,37,38,39], making bioelectric signaling an ideal modality for coordinating individual cell behaviors towards a specific anatomical outcome. Second, bioelectric patterns can override default genetic/biochemical information: specific Vmem changes can prevent mesenchymal stem cell differentiation despite the presence of chemical inducers [40,41], can induce an eye to form in a tissue (e.g., mesoderm or endoderm) that is otherwise not competent to become eye when misexpressing a “master” eye inducer like Pax6 [31], can induce metastatic melanoma in the absence of genetic damage [36,37], can prevent the formation of tumors in the presence of otherwise-sufficient oncogenes [42,43], and can rescue brain defects caused by mutations in powerful regulators of neurogenesis such as Notch [32]. Thus, bioelectric signaling is a good explanatory candidate in instances of epi-genetic influences over pattern formation. Finally, bioelectric properties seem to directly encode outcomes at the level of organs, inducing whole appendages [17,23,24] or complex eyes [31]. This ability to trigger downstream developmental modules, without having to specify individual cell positions (micromanage the process), makes bioelectric signals not only attractive control knobs for biomedical intervention, but also reveals how bioelectric network states can be seen as attractors instructing complex patterning outcomes.

Global bioelectric network dynamics are regulated in part by gap junctions—electrical synapses between cells that facilitate direct ion exchange, thereby allowing cells to compare their Vmem with those of their neighbors, and establish isopotential cell fields or boundaries between compartments [44,45]. Because gap junctions can be themselves voltage-sensitive [46,47], they in effect can function as transistors—enabling complex information processing and feedback loops. Gap junctions also provide rich opportunities for selective gating of small molecule signals in addition to ion current [48]. Unsurprisingly, because of these features, this versatile signaling element is crucial for development [49,50,51] and also for the plasticity of cognitive memory in the brain [52,53,54]. Thus, we investigated here the role of gap junction-mediated physiological networks in regulating pattern formation.

Planaria are free-living flatworms with impressive regenerative abilities [55,56,57]. After traumatic injury such as amputation, planarians regenerate all missing tissues, reproducing their target morphology perfectly in a relatively short time span of about two weeks. This morphological remodeling is not restricted to trauma; after periods of starvation, planarians shrink themselves allometrically, and grow in the same, scaled manner after food has been reintroduced [58]. This remarkable example of spatial and temporal cellular organization requires the storage and sharing of morphological and physiological information across a diverse and widely dispersed population of cells. Such morphological robustness provides a unique system in which to study complex traits such as the plasticity of morphology. While recent work has made remarkable progress on the molecular details of pathways regulating adult stem cell behavior in planaria [59,60,61], very little information is available on how specific head shape is controlled. The vast majority of the functional literature reports phenotypes of either failure to regenerate or switching of head/tail identity; the field currently has no mechanistic understanding of how a species-specific head shape is established or regulated [62], although voltage-based signaling has been shown to be involved in head shape/size in at least one species [25].

Importantly, different species of planaria have characteristic head shapes that are readily distinguished by anatomical inspection. Thus, we examined the consequences of disrupting the body-wide gap junction communication network for head shape in planaria. Remarkably, we observed a stochastic phenotype in which the regenerating heads of a genomically-normal G. dorotocephala flatworm acquired a head morphology appropriate to other extant planarian species. The effect was observed in the head, as well as in the brain morphology. Unlike our recent demonstration of a permanent (stable) change of target morphology in D. japonica [20], this effect was temporary, and the worms remodeled back to their native state within 30 days. The ability to stochastically select one of several discrete head shapes appropriate to a different species, simply by altering a physiological network, suggests that quantitative models of bioelectric network modes will be an important part of understanding evolutionary change and the role of genomic vs. physiological circuits in establishing anatomical structure.

Planarian flatworm species display a broad range of head shapes, from the very rounded to the almost triangular, with varied shapes of auricles (Figure 1A–D). To interrogate the mechanisms responsible for regeneration and maintenance of head shape, G. dorotocephala planarians were amputated along a plane positioned posterior to the pharynx but anterior to the tail, to produce a pre-tail (PT) fragment. PT fragments were then treated with the gap junction (GJ) communication blocker octanol (8-OH). 8-OH is a commonly-used pan-GJ blocker [20,63,64,65,66,67,68,69,70,71], altering the physiological connectivity between populations of cells, and thereby perturbing the rate and pattern of transmission of bioelectrical and other small molecule signals. Dosage was titrated to a level low enough to enable interference with regenerative signaling without organismic toxicity. 8-OH exposure has been validated to be transient by GC-MS: drug levels are undetectable after a few hours of worm wash-out in water, and octanol does not alter genetic sequences in the worm [20,72].

After 3 days of octanol exposure, worms were allowed to complete regeneration (10 days total). Remarkably, this process resulted in worms that exhibited head shapes highly similar to the heads appropriate to other species of planarians (Figure 1E–H). 8-OH treated fragments regenerated both head and tail correctly, but in many cases, head shape was drastically altered. Wild-type G. dorotocephala (GD) possess a very pointed head shape, with two elongated auricles at the plane of the eyes (Figure 1A). Fragments subjected to the same 8-OH treatment scheme regenerated one of: entirely rounded heads like the planarian S. mediterranea (SM) (Figure 1H), heads with thick necks and “cat-like” auricles like those of the planarian P. felina (PF) (Figure 1G), heads that are triangular like the planarian D. japonica (DJ) (Figure 1F), or heads that resemble wild-type G. dorotocephala (Figure 1E). We will refer to the head shapes of regenerates as “pseudo” of the morphologically most similar species. Variant, other species-specific head morphologies were never observed after amputation or during regeneration in water (the control condition)—the normal process of head regeneration has 100% fidelity to the species-specific shape (Figure S1A). The same schedule of exposure to hexanol (6-OH), a closely-related compound to octanol which does not effectively block GJs and thus can be used as a control [69], had no effect (Figure S1B). Likewise, intact worms soaked in 8-OH for >3 days did not exhibit any unusual morphological outcomes. Based on these results, we conclude that discrete, species-specific head shapes can be achieved by manipulating the connectivity of physiological networks in the planarian flatworm during head regeneration.

Geometric morphometrics [73] was used to quantify similarities and differences between head shapes of true species, as well as the experimentally derived pseudo morphologies. In brief, geometric morphometric analysis involves placement of a series of landmarks, which are both biologically significant and reproducible across all samples, removal of non-shape variation (size, rotation, etc.), and performance of a set of statistical analysis [74]. Landmarks were chosen based on the common biological landmarks that existed across samples, and semi-landmarks were placed with prescribed relations to these landmarks (Figure 2B). Landmark data was recorded for n > 60 worms, including GD worms whose head shape had been experimentally perturbed by 8-OH, control GD worms who had regenerated in water for 10 days, and adult wild-type worms from each of the three species. Principal components analyses (data not shown) and canonical variate analyses were run on the data set. This enabled visualization of mean shape changes between wild-type species morphologies, and between experimentally derived head shapes. Both analyses resulted in the separation of pseudo morphologies from the wild-type G. dorotocephala morphology. Procrustes distances between each of the groups were calculated, in order to produce a quantified metric for comparison of shape differences.

The quantification was used to determine whether the shapes that looked like other species objectively resembled those species, and to suggest a continuous morphospace within which octanol-induced shape change can be visualized along a continuum (from normal to that of a different species). Canonical variate analysis supported the statistical significance of the given pre-defined morphological groupings (in this case, groupings were based on experimental treatment and morphology) (Figure 2A). Comparisons of the Procrustes distances between shape groups (Figure 2A, Table 1) showed that the experimentally derived morphologies were closer in shape to the wild-type morphologies they resembled than the wild-type Girardia dorotocephala head morphology. Analysis of variance (ANOVA) of both centroid size and shape between wild-type morphology and pseudo morphology groups also confirmed significant differences between groupings (F = 7.94, p < 0.0001, and F = 7.40, p < 0.0001, respectively). We conclude that amputation and treatment in 8-OH can produce regenerated worms whose morphology has changed to become significantly more like that of another species of planarian.

Obtaining distinct regenerated morphologies, at different frequencies, despite the same treatment conditions, led us to explore the evolutionary relationship between the four species represented. We mapped out an evolutionary tree based on rRNA homology [75,76], and compared this tree (Figure 3A) to frequencies of the different species’ heads arising from 8-OH treatment (Figure 3B). Interestingly, morphologies corresponding to species that are most closely related to G. dorotocephala (SM and DJ, which are removed from GDs by at least 100 million years of evolutionary distance) occur with a much higher frequency than morphologies corresponding to less-related species (PF). We conclude that not only are phenotypic outcomes from physiological network perturbation stochastic (as the same treatment leads to one of several discrete shapes among individuals), but the frequencies are not equal and correlate roughly with evolutionary distance between the worm species these heads resemble.

We next asked whether internal structures were likewise converted to a different shape, as was external morphology. Few aspects of the planarian internal anatomy differ appreciably between species; however, brain size and shape offer an interesting exception to this rule. The brains of wild-type G. dorotocephala are elongated and narrow, while D. japonica and S. mediterranea have appreciably shorter and wider brain morphologies (Figure 4A–C). No living wild-type P. felina could be obtained for this work, and the low frequency of pseudo PF occurrence limited the number available for analysis. Thus, we focused on G. dorotocephala, D. japonica, and S. mediterranea. We performed immunostaining using an anti-synapsin antibody, in order to visualize both the brain, and ventral nerve cords of pseudo and wild-type worms. As recapitulation of wild-type head shape after ten days of regeneration in water had been confirmed by geometric morphometrics, we chose to compare pseudo morphologies to adult worms of other species, in order to minimize confounding data due to variability of regeneration time between species. Overall shape differences were captured by measurement of the brain length/width ratio. These calculations were used to quantify shape differences between species, and to quantify brain remodeling in “pseudo” worms (Figure 4G). Strikingly, we found that pseudo worms possessed brain morphologies that look like the brain morphologies of wild-type worms whose head shapes they resembled (Figure 4D–F) (ANOVA, p < 0.001). We conclude that the patterning processes that are disrupted after gap junction communication perturbation are also responsible for producing the morphology of the brain, and that the altered shapes are not limited to the overall head geometry but include the patterning of the central nervous system within.

Planarians derive much of their remarkable regenerative power from a population of heterogeneous adult stem cells, called neoblasts, which comprise the only mitotically active cell population in the body of the flatworm [56,70,77]. We next investigated whether or not the spatial distribution of neoblasts was appreciably different between species of planarians, and whether GJ-inhibited worms acquired the neoblast distribution characteristic of the species whose morphology they had taken on. As neoblasts are the only mitotically active cells within the planarian body, we performed immunostaining of phosphorylated histone H3, a standard neoblast marker in planaria [78], in order to visualize neoblast populations.

In wild-type G. dorotocephala, very few neoblasts reach into the most anterior 1/6th of the worm (Figure 5A). In wild-type D. japonica, the number of neoblasts in the anterior portion of the body is increased in comparison to G. dorotocephala, however it is still relatively low (Figure 5B). Wild-type S. mediterranea planarians have an abundant neoblast population in the anterior-most region (Figure 5C). All neoblasts in the anterior 1/6th of the worm’s anatomy were counted by hand (Figure 5G). Remarkably, the distribution of neoblasts in pseudo worms mirrored precisely the distribution of neoblasts in the wild-type species that they resembled (Figure 5D‒F) (ANOVA p < 0.05). We conclude that the transformation of G. dorotocephala worms to resemble other species also extends to the species-specific, characteristic internal distribution of their stem cells, and that the patterning processes that are disrupted after GJC perturbation are also responsible for organizing the distribution of mitotically active cells.

One of the physiological signals propagated within GJ-mediated cell networks is electric current: patterns of GJ-dependent connectivity can determine isopotential cell fields [19,25,79], and we observed that octanol indeed increased the number of regions with distinct Vmem patterns (Figure 6). Because analytical pipelines to read out encoded pattern states from bioelectrical measurements (as has been done for the human brain [80]) do not yet exist, we sought to begin to establish physiological metrics that could reveal permanent changes of the somatic bioelectric network induced by GJ blockade and could distinguish pseudo worms from those with the original (wild-type) morphology. Thus, we next examined the distribution of isopotential cell groups among the different worm shape outcomes, as such groups are established by the function of gap junctions and are a readout of the topology (connectivity) of developmental bioelectrical networks [20,35,39,51,81,82]. Patterns of endogenous relative membrane depolarization and hyperpolarization were visualized using a DiBAC (bis-(1,3-dibarbituric acid)-trimethine oxonol) dye [79,83]. DiBAC is anionic, so dye enters cell membranes based on relative degrees of depolarization [84]. Therefore, increased fluorescence indicates regions of depolarization, and decreased fluorescence indicates relative hyperpolarization. Wild-type worms of the species G. dorotocephala, D. japonica, S. mediterranea, and P. felina, and GJ-perturbed pseudo worms were imaged with DiBAC dye in order to assess potential differences in relative membrane potential. Images were analyzed with a custom image analysis program (as described in Methods) to determine the number of distinct isopotential regions present in the entire worm.

Analysis of worms 10 days after 8-OH treatment (after regeneration was complete, Figure 6A–H) revealed that transient perturbation of gap junction communication alters body-wide patterns of voltage distribution for many days after the end of 8-OH treatment. We detected an increased number of isopotential regions in the pseudo worms compared to the states of control worms; interestingly, the numbers of isopotential regions return to those of a wild-type state after 30 days of morphological remodeling (Figure 6I). Although we cannot be certain that every single cell had been penetrated by the dye, the pattern of isopotential regions and variability among animals suggests that octanol action is stochastic and not 100% effective, only partially disrupting electrical coupling (revealed as regions that differ in Vmem) throughout animals treated in drug. We conclude that octanol exposure alters the normal pattern of G. dorotocephala resting potential toward a pattern that persists even after 8-OH is withdrawn and regenerative repair occurs, producing an increased concentration of isopotential regions throughout the worm.

In D. japonica, physiological perturbations can stably change the basic architecture of the planarian body-plan, producing two-headed worms that continue to regenerate as two-headed in perpetuity across future rounds of regeneration in plain water [20]. Thus, we next asked whether our observed head shape changes in G. dorotocephala were permanent. Photographs of worms after treatment with 8-OH were taken daily, from day 10 (when the morphologies of the worms were scored), through day 30 (the time necessary for complete cellular turnover in the planarian flatworm). We found that the induced morphologies were remodeled, long after regenerative processes had ended, to produce morphologies that bore closer resemblance to wild-type G. dorotocephala. Interestingly, the time course and result of this non-regenerative remodeling differed depending on the starting head shapes. Regenerates that had rounded heads, which resemble S. mediterranea, began to develop a more triangular head shape by day 17, and by day 30, bore more of a resemblance to D. japonica than S. mediterranea. Over the same time course, regenerates that had triangular heads, resembling D. japonica, developed pronounced auricles, and by day 30 were indistinguishable from wild-type G. dorotocephala (Figure 7A,B). These findings are fascinating in two respects. First, the change in morphology in absence of a trauma highlights dynamic and robust mechanisms underlying morphological homeostasis—the anatomical state is remodeled over the long-term from an abnormal configuration existing after regenerative repair was complete. Secondly, the remodeling occurs via “paths” through the shape space illustrated by canonical variate analysis (Figure 7C). DJ morphology lies between GD and SM morphologies in this space, and we observe remodeling that moves from SM morphology to DJ morphology to GD morphology.

From these data, we conclude that morphology is both plastic and robust, restoration of the “target” morphology can occur without trauma to the organism, and that the CV shape space is informative in illustrating parameters and boundaries to morphological variation.

One of the key challenges facing developmental biology and regenerative medicine is linking large-scale patterning outcomes to the individual activity of cells guided by genetic networks and signaling pathways [2,85,86,87,88,89]. Most of the work in the planarian field deals with anterior-posterior fragment polarity [60,62,90] or stem cell differentiation [57,59,91], and does not address the actual morphology of the head or the rest of the body. Recent quantitative, genetically-grounded models of regeneration [92,93,94] likewise use anterior-posterior identity as a binary readout, which does not address or explain changes to the shape of these anatomical regions. Our study of the bioelectrical control of regeneration reported alterations of head remodeling [25], but was limited to scaling and did not model the detailed shape of the head. To begin to mechanistically link individual cell behaviors (such as those regulated by GJ-mediated signals) to large-scale anatomical outcomes, we next constructed an agent-based model of cell signaling and morphogenesis. Our model focused on cell migration and cell-cell signaling, as these are clearly important for implementing different morphogenetic outcomes [95,96,97], and also known to be regulated by GJ connectivity [98] and bioelectric properties of neighboring cells [99].

We considered two cell types, A and B. Cells of type A have fixed positions—they cannot move. They produce a substance whose concentration C spreads in space. Its distribution can be described by a reaction-diffusion equation or by some other models. Cells of the type B can move. They do not produce any substance but they receive the substance C produced by cells A and their motion is determined by its concentration distribution. We modeled the planarian head with the following elements: cells of type A, deactivated cells of type A, cells of type B, and a surface boundary. Deactivated A cells are fixed but they do not produce substance C. If there is more than one cell B, then they repulse each other in the same way as they are repulsed by cells A. We choose deactivated cells A symmetrically with respect to the anterior-posterior axis, in order to preserve symmetry of outcome (which implies that B cells move in a similar way on the left and right sides). The outer boundary is composed of points and elastic “springs” connecting them. When a cell B approaches the boundary, a repulsive force acts on it from the boundary. This force is proportional to the distance from the particles and from the intervals of the boundary. Full details of the modeling are given in Figure S2. In this model, we hypothesize that instructive (GJ-dependent) signaling occurs from the somatic tissues to the neoblasts or their progeny, to guide the new tissue generation and shaping during regeneration. Thus, the red cells are migrating neoblasts (or their progeny) while the black cells are somatic cells interconnected by GJs (Figure 8). In the model, octanol disruption of cell:cell communication is thus modeled by the deactivation of signaling from a specific cell type.

When simulated in silico, this model produced planarian head shapes observed in the experiments. These different shapes were achieved from the same initial cell configuration but different deactivation pattern of cells A and different elastic properties of the boundary. These deactivation patterns correspond to octanol treatments that reduces cell-cell communication among a subset of cells. We hypothesize that this results in deactivation of some of the cells’ signaling. The initial cells location configuration and its resulting equilibrium configuration are shown in Figure S2H,I. Cells of type B remain surrounded by A cells. This configuration is chosen in such a way that after deactivation of some of cells A, cells B either remain inside or they migrate outside and produce one of the required four configurations (Figure S2A–D). Specific head shape emerges because cells B are pushed away by cells A and by other cells B. They escape through the lower concentration levels of substance C left by deactivated cells A, arriving at the outer membrane and changing its shape.

Note that the shape of the auricles in Figure 8D is more pronounced than in cases Figure 8B,C. This corresponds to the experimentally observed shapes. In modeling, this difference is achieved with different properties of the outer boundary, being softer in the lower part (red in the figure) and resulting in sharper auricles. This is consistent with prior work showing that integument integrity (and thus stiffness) is dependent on the correct expression and function of gap junction channels [100]. Figure 8 shows the final positions of cells B and their trajectories after simulating four different deactivation patterns. In order to compare real worm morphological data to the results of our modeling, we carried out morphometric measurements as shown in Figure 8E–H on the outcomes of our in silico simulations. We measured the length of the horizontal interval L1 and of the vertical interval L2 (in the case 1b and 2b these intervals necessarily had to not be straight). The results are seen in Table 2, and provide a good concordance with the observed outcomes in real worms (Figure 1). Let us note that the final morphologies of planarian’s head in computer simulations are determined by the initial cell configuration. They differ by locations of deactivated cells (white cells in Figure 8). If these cells are close, then the final head forms are also close. If we compare DJ (Figure 8C) and GD (Figure 8D), then the initial cell configuration and the final morphologies are more close to each other than these two compared with SM (Figure 8A). Moreover, DJ seems to be in between the SM and GD models. It is interesting to note that this ordering corresponds to their genetic distance (Figure 3).

We conclude that a small set of cell-level behaviors, such as migration and cell-cell signaling that are known to be regulated by GJC and thus are perturbed by octanol exposure [35,39,49,98,101,102], can quantitatively explain the morphologies we observed in planaria.

Our data show that in the planarian flatworm G. dorotocephala, outcomes of morphogenesis can be modified by the perturbation of physiological networks. Brief exposure to a well-characterized disruptor of electrical synapses (gap junction blocker) resulted in regenerated head shapes that quantitatively resembled those of another planarian species. We observed head shapes (and internal structures) resembling D. japonica, S. mediterranea, and P. felina. Note that other species exist with head shapes similar to each (for example, 2 other species are known that exhibit P. felina-like flattened heads); because these three types are good representatives of each shape class and are available as living specimens for analysis (unlike other members of the same morphological head types), we refer to our phenotypes as pseudo japonica, pseudo mediterranea, and pseudo felina respectively. Future analysis of other planarian species will reveal if these phenotypes are in fact more closely resembling one of the other members in each shape class.

The head morphology alteration effect was instructive, and not merely one of toxicity or a house-keeping defect, because the outcome was not merely disruption of regenerative ability or a generalized mis-patterning (e.g., tumor or other disorganized growth), but rather resulted in one of several coherent (and ecologically-valid) morphologies. No intermediate morphologies were observed, highlighting the discrete nature of the complex patterning outcomes following GJ blocker exposure. The same 3-day treatment with the closely related alcohol, hexanol (6-OH), which does not efficiently block gap junction channels, and subsequent regeneration in water for 7 days, did not produce altered morphologies, consistent with the importance of the GJ-blocking activity of octanol, and not some other generalized effect of long-chain alcohols.

Dramatically-different morphologies can be derived from the same genome [103,104,105]. Mules and hinnies, which differ only in the sex of the respective donkey and horse parents, are quite morphologically distinct, despite almost identical DNA sequences. Toadflax (Linaria vulgaris) has a morphological variant produced solely by variations in DNA methylation patterns, and numerous reptilian species will develop morphologically distinct sexual organs in a temperature-dependent manner [106]. Moreover, recent data revealed how alterations in biochemical signaling can select among different species-specific morphologies [103,107]. Here, we identify a novel physiological input into the process by which distinct morphologies can be derived from the same genome: physiological bioelectric networks. The compatibility of multiple morphological outcomes with a single genomic sequence underlies the importance of learning to understand and control the instructive patterning information that is generated by chemical, physical, and bioelectrical processes beyond hardwired gene-regulatory networks.

Geometric morphometrics is a technique commonly used to quantify and compare biological shapes. We employed landmark-based analysis, which involves the recording of landmark data, the transformation of resulting shapes to remove scaling and rotational noise, and the performance of statistical analyses. Canonical variate analysis (CVA) was employed to compare wild-type morphologies of four species of worm with the corresponding pseudo morphologies, as well as compare wild-type G. dorotocephala morphology to all pseudo morphologies. CVA determines the statistical significance of variation between given groupings of samples [74,108]. In this case the groupings corresponded to observed phenotype and experimental treatment. We chose to employ Procrustes distances to quantify “distance” between shapes, as it is a measure of the square root of the summed squared distances between the corresponding landmarks in two shapes, and is commonly used in morphometric studies comparing differing morphologies. The Procrustes distances between pseudo morphologies and the species that they resembled are smaller than the Procrustes distances between the pseudo morphologies and wild-type G. dorotocephala. The observation was supplemented with both Procrustes ANOVA of centroid size and shape (p < 0.001, and p < 0.001, respectively). This demonstrates a significant alteration of morphology, and quantitatively confirms the apparent similarity between the pseudo phenotypes and their wild-type counterpart species.