Future medicine: from molecular pathways to the collective intelligence of the body

Abstract

The remarkable anatomical homeostasis exhibited by complex living organisms suggests that they are inherently reprogrammable information-processing systems that offer numerous interfaces to their physiological and anatomical problem-solving capacities. We briefly review data suggesting that the multiscale competency of living forms affords a new path for biomedicine that exploits the innate collective intelligence of tissues and organs. The concept of tissue-level allostatic goal-directedness is already bearing fruit in clinical practice. We sketch a roadmap towards 'somatic psychiatry' by using advances in bioelectricity and behavioral neuroscience to design methods that induce self-repair of structure and function. Relaxing the assumption that cellular control mechanisms are static, exploiting powerful concepts from cybernetics, behavioral science, and developmental biology may spark definitive solutions to current biomedical challenges.

Keywords: bioelectricity; cognition; regenerative medicine; top-down control.

Figure 1:. Anatomical compiler and multiscale competency:

(A) The remarkable complexity of the human body (shown here in cross-section through an adult torso) is not specified directly in the genome (which codes for subcellular hardware: proteins) but arises from the activity of a collection of embryonic blastomeres. It is the physiological software implemented by this cellular collective that makes anatomical decisions about growth and form, and it is these decisions that we must target and modify when attempting to repair or regenerate missing or damaged organs. (B) Bodies are constructed via a multiscale competency architecture, where each layer processes information to solve problems in physiological, transcriptional, anatomical, and behavioral spaces. Taking advantage of their competencies is a powerful roadmap for biomedicine. (C) The ultimate goal of this emerging field is to construct an “anatomical compiler” – a system which enables the user to specify any anatomical shape, and converts that to a set of stimuli that must be given to cells to get them to grow it (such as the 3-headed flatworm shown here). Crucially, the anatomical compiler will not be a 3D printer or a device to micromanage gene expression or stem cell fate: it will be in effect a communications device, converting the anatomical goals of the user into a re-specification of the target morphology information in cellular collectives. Images in A,B courtesy of Jeremy Guay of Peregrine Creative. Image in A used with permission from [173]. Image in B used with permission from [14]. Images in C courtesy of Daniel Lobo and Junji Morokuma.

Figure 2:. Morphostasis and the control loop of anatomical control

(A) A homeostatic loop schematic depicting the conventional emergence of a set anatomy, and recursive surveillance and adjustment circuits that maintain that precise anatomy over time, despite environmental perturbation. Complex structure and function is the feed-forward result of cells mechanically following local rules, and feedback loops detect error relative to a specified setpoint (a pattern memory of large-scale form, encoded in bioelectric properties – see Figure 5), and induce cells to act to reduce error relative to that setpoint. (B) Anatomical homeostasis implements regulative development, such as for example when an early embryo is cut in half and gives rise to two complete monozygotic twins, not half-bodies. This error minimization strategy also enables regeneration in adults, such as limb regeneration in salamanders (C) and antler regeneration in deer (D). Image in A used with permission from [173]. Photo in B by Oudeschool via Wikimedia commons. Image in C courtesy of Jeremy Guay of Peregrine Creative, used with permission from [174]. Images in D used with permission from [15].

Figure 3:. Problem-solving by cells and tissues

(A) Tadpoles must rearrange their face to become frogs. But, even experimentally-scrambled tadpole faces become normal frog faces as the organs move in novel paths appropriate to their aberrant locations. This illustrates the problem-solving capacity of cellular collectives: they do not merely execute the same hardwired motions each time, but move as needed to reach the frog face target morphology, despite novel circumstances. (B) This ability to navigate a problem space despite novel interventions and scenarios extends to physiological and transcriptional spaces. Planaria soaked in the potassium channel blocker barium experience rapid head degeneration, but soon regenerate new heads that are barium-adapted. This occurs by identifying which genes to turn on and off (only a handful) to enable cells to function despite barium. Since planaria have not evolved under environmental pressure to resist barium, this navigation of gene expression space is a solution to a novel problem. (C) Kidney tubules in newts (seen here in cross-section) develop to a specified diameter regardless of the size of the component cells. When the cells are experimentally forced to be much larger, fewer of them gather to make a tubule of the same size. When they are gigantic, a single cell will bend around itself to generate the lumen. In this case, the solution to a novel problem occurs via different molecular mechanisms depending on cell size (cell:cell communication vs. cytoskeletal bending). (D,D’) Trophic memory is evidenced in seasonal regeneration of deer antlers. Damage in one year (D) alters the stable, stereotypical memory of the antler structure and causes new tines to appear in the same location when the entire rack is re-grown in the subsequent year (D’). Images in A courtesy of Douglas Blackiston and Erin Switzer, used with permission from [71]. Panel B used with permission from [22]. Image in C courtesy of Jeremy Guay of Peregrine Creative, used with permission from [14] and adapted from [164] with permission. Images in D,D’ used with permission from [2].

Figure 4:. A hepatocyte-centric view for liver regeneration and the need of function.

After partial hepatectomy from surgical removal or accidental loss of hepatic tissue, hepatocytes respond to the need of function by proliferation, guided by phenotypic fidelity and hypertrophy to restore liver mass. After hepatocyte transplantation directed to the liver with diseased hepatocytes, healthy hepatocytes replace ailing hepatocytes, driven by the need to restore liver function. In hepatocyte transplantation into lymph node, heathy hepatocytes regenerate new liver tissue by proliferating and recruiting other cells to precisely restore lost liver mass and function, a process of complete liver regeneration driven by the need of function. This figure and images were created by Eric Lagasse using Adobe Photoshop and Powerpoint.

Figure 5:. Bioelectricity as an ancient somatic control mechanism

(A) The remarkable problem-solving capacities of brains arise as a function of physiological dynamics of computations mediated by voltage states propagating through networks of neurons. (B) Somatic cells also set resting potentials via ion channels and most cells can communicate voltage to their neighbors. (C,D) There is a deep isomorphism between the actions of the nervous system to control goal-directed movement by controlling muscles (C), and the action of non-neural bioelectric networks to achieve anatomical setpoints by controlling downstream cell behavior and navigating anatomical morphospace (D). (E) Techniques borrowed from neuroscience can be used to control network topology (target gap junctional electrical synapses) and node state (resting potential of each cell) via optogenetic, genetic, and pharmacological techniques. (F) The “electric face” in a frog embryo [71], is required for normal development and encodes the target morphologies to which cells will build (regulating gene expression, cell migration, differentiation, etc.). (G) Pathological bioelectric patterns, such as the depolarizations induced by oncogenes, can be targeted with optogenetic or mRNA-based ion channel misexpression strategies (H) to control the voltage state and force cells to participate in the electrical network’s project of normal tissue maintenance instead of tumorigenesis. In this example of a tadpole injected with a human oncogene, there is no tumor (H’) despite the very strong presence of a red fluorescence protein-labeled oncoprotein (H”). Images in A-E courtesy of Jeremy Guay of Peregrine Creative. Images in A, B used with permission from [69]. Images in C,D used with permission from [175]. Image in E used with permission from [176]. Image in F used with permission from [71]. Images in G,H,H’,H” used with permission from [87].

Figure 6:. Bioelectric repair strategies

(A) Misexpressing potassium channels in specific cells to induce the bioelectric prepattern corresponding to a native eye (Fig. 5F) can produce an ectopic eye (red arrowhead) in locations where the “master eye gene” Pax6 cannot do so (posterior to the head); thus, novel differentiation and morphogenesis competencies of cells are revealed by using higher-level (bioelectric) prompts instead of biochemical transcription factor machinery. (A’) Immunohistochemistry confirms all the correct tissue contents of an eye are present despite the very simple nature of the trigger. We did not specify what genes to turn on or how to make an eye; rather, we specified a bioelectric signal that said “make an eye here” and relied on the competency of the cells to do the rest. (A”) When too few cells (labeled in cyan) are injected, the resulting lens includes unmanipulated neighboring cells recruited to help complete the job. (B) Regeneration of the tadpole tail can be induced in non-regenerative conditions by a brief, 1-hour soak in monensin – a sodium ionophore which drives a depolarized wound state (green signal), inducing a tail regrowth program that lasts almost 2 weeks. (C) The same monensin signal induces MSX-1-positive blastema cells and eventually leg regeneration in froglets at a normally non-regenerative stage, showing not only that bioelectric states can induce complex appendage repair in vertebrates, but also that the initial signal does not have to contain much information about the organ to be restored – the host body contains that information, which can be triggered via this interface. Images in A,A’ used with permission from [177]. Image in A”” used with permission from [14]. Images in B used with permission from [90]. Images in C used with permission from [78].

Figure 7:. The landscape of emerging biomedical interventions

(A) Biomedical interventions can be classified into two main approaches. Bottom-up: conventional approaches such as genomic editing, molecular medicine, and stem cell biology seek to control outcomes by focusing on the micro-level hardware. Aside from successes in targeting low-agency invaders (antibiotics, surgery, and chemotherapy), permanent repair is very hard to accomplish: symptoms tend to recur when the intervention is stopped, and emergent system complexity makes it very hard to know which genes or proteins to target for a desired large-scale outcome. Top-down: these novel strategies leverage the host body’s native competencies, treating it as a computational, goal-directed navigational system and targeting its memories, assessment of current state, and effector subroutines. These include shaping cell and tissue behavior via experiences or via signals provided by morphoceuticals (interventions that target the decision-points of anatomical homeostasis) and a subclass – electroceuticals. (B) Tools, concepts, and computational frameworks from several different fields can be used to develop new ways to reprogram biological behaviors at different levels to advance regenerative medicine, neuroscience, synthetic bioengineering, and basic evolutionary developmental biology. (C) A basic workflow in top-down control for biomedicine consists of a simulation platform being fed physiological data, which can predict novel interventions (time-dependent stimuli) to shift system goals to states that effect long-term repair. These must be coupled with protocols for applying such interventions, and a delivery technology (e.g., a wearable bioreactor or smart implant). Images from Jeremy Guay of Peregrine Creative, used with permission.