Daniel Lobo , Wendy S. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. This article has been cited by other articles in PMC. Associated Data Text S1: Previously proposed models of patterning in planarian regeneration. Molecular biologists are working to identify the pathways underlying the remarkable regenerative abilities of model species that perfectly regenerate limbs, brains, and other complex body parts.

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Daniel Lobo , Wendy S. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. This article has been cited by other articles in PMC. Associated Data Text S1: Previously proposed models of patterning in planarian regeneration.

Molecular biologists are working to identify the pathways underlying the remarkable regenerative abilities of model species that perfectly regenerate limbs, brains, and other complex body parts. However, a profound disconnect remains between the deluge of high-resolution genetic and protein data on pathways required for regeneration, and the desired spatial, algorithmic models that show how self-monitoring and growth control arise from the synthesis of cellular activities.

This barrier to progress in the understanding of morphogenetic controls may be breached by powerful techniques from the computational sciences—using non-traditional modeling approaches to reverse-engineer systems such as planaria: flatworms with a complex bodyplan and nervous system that are able to regenerate any body part after traumatic injury. Currently, the involvement of experts from outside of molecular genetics is hampered by the specialist literature of molecular developmental biology: impactful collaborations across such different fields require that review literature be available that presents the key functional capabilities of important biological model systems while abstracting away from the often irrelevant and confusing details of specific genes and proteins.

To facilitate modeling efforts by computer scientists, physicists, engineers, and mathematicians, we present a different kind of review of planarian regeneration. Focusing on the main patterning properties of this system, we review what is known about the signal exchanges that occur during regenerative repair in planaria and the cellular mechanisms that are thought to underlie them.

By establishing an engineering-like style for reviews of the molecular developmental biology of biomedically important model systems, significant fresh insights and quantitative computational models will be developed by new collaborations between biology and the information sciences.

Possibly the people who are trying to discover how to set up a computer to learn to play good chess, or bridge, are among those most likely to make a major contribution to the fundamental theory of evolution. Waddington [1] Introduction The ability to control the pattern formation of organs and appendages is a key aim of regenerative medicine. Transformative impact in areas such as birth defects, traumatic injury, cancer, and degenerative disease requires that we understand the molecular mechanisms that allow living beings to detect and repair damage to complex biological structures.

A similar goal is pursued by engineers seeking to build resilient machines and fault-tolerant, robust systems. However, there does exist a natural system capable of performing these amazing feats: the planaria. Planarians are nonparasitic flatworms that have bilateral symmetry, a true brain driving a complex behavioral repertoire [2] , and an extraordinary capacity to regenerate due to the presence of a large adult stem cell population [3].

Individual planarians are practically immortal—able to regenerate aging, as well as severely damaged or lost, tissues [4]. A trunk fragment cut from the middle of an adult planarian will regenerate into a whole worm, always growing a new head and new tail in the same orientation as the original worm. Planaria are a popular model for molecular-genetic and biophysical dissection of pathways that underlie regenerative patterning [4] , [7] , [8] , having more genes in common with humans than with the fruit fly Drosophila.

A mechanistic understanding of the communication and control networks that maintain complex shape against radical perturbations will revolutionize our ability to regulate stem cell behavior in the context of the host organism. Thus, reverse-engineering the remarkable system that is planarian regeneration would have profound impacts on regenerative medicine, bioengineering, synthetic biology, and robotics.

Regeneration in planarians involves a truly complex interaction of several systems at the organismal level. After an injury, the stem cells in the worm proliferate and migrate to form a protective mass of new cells blastema at the wound site. This cell proliferation is tightly coordinated with the selective destruction of some old cells apoptosis , effectively remodeling both the new and old tissues to recreate exactly those regions and organs the worm is missing, adjust the proportions of the remaining regions and organs to the new smaller worm size, and maintain the original patterning orientation of the worm with the new tissues.

These complex interactions are controlled by a diverse set of signals, including molecular pathways, gap junctional communication, ion fluxes, and nervous system signals. Although essential for regeneration, the mechanisms by which these signals integrate to maintain and restore the correct geometry of the animal are still not well understood.

After more than years of research, no single model has been proposed that explains comprehensively the mechanisms of all the known components of planarian regeneration; the majority of current models are descriptive in nature and limited to only one or two observed properties [9] — [12].

Current research efforts capitalize on molecular and cell biology techniques to produce an ever-increasing set of detailed data on genetic components that are necessary for normal regeneration [13].

However, making use of such information for biomedical or engineering purposes requires the integration of protein or gene networks into constructive models that are sufficient to predict and explain geometry of tissues and organ systems, and reveal what changes must be made in specific signals to drive necessary alterations of tissue topology.

If we hope to understand and tame powerful regenerative mechanisms, we will need to develop algorithmic models that are consistent with the existing experimental datasets but also bridge the gap between functional genetic data and self-assembly of three-dimensional shape and dynamic morphostasis.

Algorithmic also called mechanistic or computational models, in contrast to descriptive ones, explain precisely at every step what information a system needs and what logical steps should be performed, i. Unlike bare gene or protein networks, such models are constructive in the sense that they make explicit the events that need to occur to create a specific shape. There is a gap between the success of high-resolution genetic analysis and the needed level of insight into systems-level mechanisms that enable adaptive control of pattern formation.

A fresh set of ideas may be helpful, from areas of science that have developed techniques for reverse-engineering complex systems, utilizing analytical methods and types of models that are distinct from those familiar to most cell biologists today.

To facilitate the application of engineering and information sciences to this fascinating problem [24] — [26] , experts outside of molecular and developmental biology need to become aware of the basic capabilities of the planarian model system and the current state of knowledge about the control mechanisms involved.

The first reviews to highlight the remarkable regenerative capacity of planaria were mainly descriptive collections reporting on various cutting experiments [27] , [28]. Later, functional experiments were also described, including starvation, transplantations, irradiation, and pharmacological exposures [29] , [30].

Given the revolution in available molecular methods, the most recent reviews have superbly summarized the genetics of regeneration [4] , [10] , [31] — [34] , detailing the growing number of gene products whose experimental inhibition results in various kinds of regenerative failures.

Unfortunately, these reviews are largely unusable by computer scientists or engineers, as the molecular details of pathways and protein—protein interactions obscure the main features and control functions to be modeled. In this review, we hope to close the gap between regenerative biology and the fields of mathematics, computer science, and engineering and lower the barrier for experts from the information and systems engineering sciences to apply their knowledge to unraveling the mechanisms of large-scale regeneration.

Here we provide an overview of the planarian regeneration system, explain what is known about the signaling mechanisms, summarize the proposed partial models in the literature, and frame the specific issues that must be addressed to bring the power of interdisciplinary investigation to fruition. Our goal is to present the basic features of this system from an engineering perspective to facilitate modeling approaches [35] — [38]. If the modeling and engineering communities can be engaged to produce algorithmic models that can accurately explain the regeneration process, the application of biologically inspired computational ideas will feed back into biology and aid our understanding of complex biological systems [39].

Conversely, the insights gained from the construction and application of these regenerative models will equally benefit computer science, artificial life, robotics, and many areas of engineering. Moreover, we hope this review will have the broader impact of establishing a precedent for much-needed different kinds of reviews that lower the barrier for true interdisciplinary cross-fertilization. Planaria constitute an excellent test case with which to explore this type of approach.

The Building Blocks for Modeling Planaria Basic Anatomy and Physiology Several species are used for research; Figure 1 summarizes the basic anatomy of Schmidtea mediterranea planaria and outlines their major anatomical axes.

Planaria possess an intestine gastrovascular tract , a body-wall musculature, a well-differentiated nervous system including brain with most of the same neurotransmitters as humans, three tissue layers endoderm, ectoderm, and mesoderm , and bilateral symmetry [3]. The gastrovascular tract consists of a highly branched gut spread throughout the entire body, with a single ventral opening from which a long muscular tube the pharynx both takes in food and expels wastes [40].

The central nervous system is comprised of a bi-lobed cephalic ganglia the brain connected to two ventral nerve cords that run longitudinally throughout the animal and fuse in the tail [41].


Modeling Planarian Regeneration: A Primer for Reverse-Engineering the Worm

Learn how and when to remove this template message Planarian reproductive system There are sexual and asexual planaria. Sexual planaria are hermaphrodites , possessing both testicles and ovaries. Thus, one of their gametes will combine with the gamete of another planarian. Each planarian transports its secretion to the other planarian, giving and receiving sperm. Eggs develop inside the body and are shed in capsules. Weeks later, the eggs hatch and grow into adults.


Fundamentals of planarian regeneration.




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