MBI Summit on the Rules of Life

Breschine Cummins:
DSGRN: Dynamic Software for Network Discovery

The mathematical field of dynamical systems plays a crucial role in describing the behavior of a cellular or genetic regulatory network over time. Traditional dynamical systems studies concentrate on trajectories and invariant sets as the primary approaches to network analysis. We present a new angle on dynamical systems that instead focuses on a robust, scalable and computable description of dynamics in terms of graphs and partially ordered sets (posets). A poset represents a “dynamic signature” of the network that is constant over a large region of parameter space. The number of such parameter regions is finite, leading to a global description of the dynamics across high dimensional parameter space. Our software tool Dynamic Signatures Generated by Regulatory Networks (DSGRN) ingests a regulatory network and produces the posets representing network dynamics over all of parameter space. The dynamic signatures generated by DSGRN can be used to answer questions about regulatory network performance in the context of network discovery, as well as other goals such as network design in synthetic biology and diagnosis of misbehavior. I will briefly overview the graphical approach of DSGRN and then discuss the role of DSGRN in a pipeline for network discovery using a case study of time series data measured in vitro from the malaria parasite P. falciparum.

Keith Farnsworth:
Autonomy: Living by One’s Own Rules

I present a thesis for scrutiny. It is that 1) the most fundamental difference between living and not, could be the strange phenomenon of self-causation. It is strange because it seems to violate the universal law of cause and effect and unique to life because only living things a) can have an identity with which to define ‘self’ and b) can respond to a change in exogenous force that is not the inevitable consequence of that change. 2) The elementary essence of life is a dynamic system of interactions configured to form closed causal loops so that ‘effect’ is generated from within. The configuration is itself a store of information (embodied by the network of connections) which incorporates at least one ‘set point’ that forms the core of a goal-oriented system that can at least perform homeostasis. 3) A nested hierarchy of such systems gives rise to increasing degrees of self-determination as the number of (Russian doll) layers increases, from simple homeostasis all the way to apparent free-will. 4) This phenomenon can be quantified via (more or less elaborate) information theoretic metrics that take account of the direction of causality. The presentation is intended to stimulate thought about how the thesis can be quantitatively tested using such metrics.

Marcella Gomez:
In Search of General Design Principles for Collective Behavior

The first wave of systems and synthetic biology has provided general network design principles that lead to robust dynamic behavior seen in nature such as adaptation, oscillations, and bi-stability.  The next frontier in this respect is finding general design principles for collective behavior of systems such as single-strain colonies with cell-to-cell communication or even multi-cellular systems. Mapping single-cell dynamics to collective behavior is not a trivial task. Some of the most well-known work includes theory developed by A. Turing for architectures leading to pattern formation. Here, I discuss a different mechanism, unique from Turing, that leads to similar patterning based on the well-known toggle switch architecture and associated properties.

Jeremy Gunawardena:
Following the Energy: the Hopfield Barrier as an Organising Principle

Hopfield's classic paper on kinetic proofreading conceals an important observation. If a biochemical system implementing a given information processing task is operating at thermodynamic equilibrium, there is an upper limit to how well it can perform that task; the only way to exceed this limit is to maintain the system away from equilibrium by expending energy. We call the limit the Hopfield barrier for the task in question. We will discuss some examples and suggest that identifying Hopfield barriers for the various tasks which biological cells undertake offers a systematic way to rise above molecular complexity and discern the underlying Rules of Life.

Christopher Kuzawa:
The Energetic Constraints of Building a Costly Brain: Implications for the Evolution of Human Childhood and the Developmental Origins of Obesity

Many adults who are overweight were already overweight as children.  What accounts for who gains excess weight early in life and who, as a result, is at increased risk for becoming an overweight or obese adult?  In my talk I will present our recent work that shows that the brain accounts for a lifetime peak of 66% of the body’s resting metabolic expenditure at 4-5 years of age, and that there is a strong inverse relationship between developmental changes in brain energetics and the rate of body weight gain between infancy and puberty. The peak in brain developmental energetics traces to synaptic and other energetically costly processes related to neuronal plasticity and learning, and requires compensatory reductions in other expenditures like body growth.  In the second half of my talk, I will review evidence linking brain energetics with overweight and obesity during childhood, and argue that variation in the timing and intensity of the brain energetics peak could help explain the well-documented finding of an inverse relationship between the BMI and cognitive function.  This framework could also help explain emerging evidence for genetically-mediated trade-offs (pleiotropy) between cognitive development and body fat gain.  In closing, I argue that educational interventions that harness plasticity in these traits, and increase the peak or duration of brain developmental energetics, could lower obesity risk by increasing the brain’s energy needs and the strength of energetic trade-offs with fat deposition.

Bruce Levin:
CRISPR-Cas: Better as a Tool for Molecular Biologists than for Protecting Bacteria from the Ravages of infections with Virulent Viruses

To some arguably, but surely to those who study it or use it as a tool for genome editing and manipulation, CRISPR-Cas has been the single most significant advance in molecular biology and biotechnology this millennium. It is commonly assumed that this “adaptive immune system” evolved and is maintained as a mechanism to protect bacteria against infections with virulent bacteriophage and other deleterious DNAs. In support of this hypothesis (conventional wisdom?) are retrospective DNA sequence data; nestled between the palindromic repeats of the CRISPRCas regions of bacteria and archaea are the 30 or so base pair sequences of DNA, spacers, homologous to the DNA of phage and plasmids. Also consistent with this hypothesis, are the results of in vitro experiments demonstrating that when bacteria with functional CRISPR-Cas systems acquire (or are provided with) spacers, they can prevent the cells from being killed by infections with lytic phage or the establishment of plasmids bearing DNA homologous to those spacers. Included among the observations which are inconsistent with the hypothesis that CRISPR-Cas commonly plays this protective role in natural populations of bacteria and virulent phage are the (i) abundance of species and strains of bacteria that do not have functional CRISPR-Cas systems, (ii) existence of phage with anti-CRISPR systems, (iii) ease with which these systems are lost when not selected for, and (iv) dearth of truly lytic (rather than modified temperate) phage that can provide spacers to bacteria with functional CRISPR-Cas systems. Also inconsistent with this hypothesis are results of (i) a mathematical – computer simulation modeling study of the population and evolutionary dynamics of bacteria with envelope resistance as well a CRISPR-Cas immunity, and (ii) the short term that phage that can provide spacers are maintained in experimental populations of spacer-providing phage and bacteria with functional CRISPR-Cas systems. --- Based on these observations, model-based predictions and experimental results, we postulate that in natural populations of bacteria and phage, the utility of CRISPR-Cas immunity for protection against lytic phage is transient and restricted to relatively avirulent lytic phages. When confronted with these phages, CRISPR-Cas will be selected for and evolve to protect the bacterial population until the phage are eliminated (or are maintained but no longer provide new spacers), at which time because of auto-immunity and/or other costs, this adaptive immune system will be selected against and/or become non-functional or lost. When these now CRISPRCas negative populations of bacteria are again confronted with lytic phage that can provide spacers, by repairing their existing CRISPR-Cas system or acquiring new systems by horizontal transfer, CRISPR-Cas will once again do it’s short-term protection thing. In this interpretation, the spacers with phage-homologous DNA that are considered evidence for CRISPR-Cas serving as an adaptive immune system are more likely to reflect past encounters with phage than this system protecting extant populations of these bacteria from phage infection. In this talk I will suggest, and hopefully stimulate discussion, about how the conditions for the operation of this transient protection hypothesis can be addressed with mathematical and computer simulation models and tested experimentally.

Armin Moczek:
On the Origins of Novelty and Diversity in Development and Evolution: Case Studies on Horned Beetles

The origin of novel traits is among the most intriguing and enduring problems in evolutionary biology. It is intriguing because it lies at the heart of what motivates much of evolutionary biology: to understand the origins of exquisite adaptations and the evolutionary transitions and ecological radiations that they enabled. It is enduring because it embodies a fundamental paradox. On the one hand, Darwin's theory of evolution is based on descent with modification wherein everything new, ultimately, must come from the old. On the other hand, biologists are captivated by complex novel traits precisely because they lack obvious homology to pre­existing traits. How, then, does novelty arise from within the confines of ancestral variation?

Combining approaches from evolutionary developmental genetics, behavioral ecology, and microbiology my research explores the genetic, developmental, and behavioral mechanisms, and the interactions among them, that promote innovation and diversification in the natural world. Most of the work in my research group focuses on the inordinately diverse and bizarre horns of scarab beetles, while side projects have explored the origins of light-­producing organs in fireflies as well as the exuberant helmets of treehoppers. In my talk I will first present recent results on the role of developmental repurposing in the evolution of novel morphological traits and developmental functions. In the second half I will discuss the significance of host microbiome interactions and environment­-engineering in the origins of novelty, when collectives innovate, adapt and problem-­solve in ways single species cannot. Throughout my talk I use our findings to highlight where I believe they expand and revise our current understanding of the genesis of novelty in evolution.

David Murrugarra:
Frequent Regulatory Rules in Molecular Interaction Networks

Understanding the regulatory mechanisms in molecular interaction networks is an important goal in systems biology. This talk will focus on processes at the molecular level that determine the state of an individual cell, involving signaling or cell regulation. The mathematical framework to be used is that of Boolean networks and their multi-state generalization. These models represent the interactions of different molecular species as logical rules that describe how these species combine to regulate others. Regulatory rules that appear in published models tend to have special features such as the property of being nested canalizing, a concept inspired by the concept of canalization in evolutionary biology. This talk will survey a set of results about nested canalizing rules and how these constrain network dynamics. It has been shown that networks comprised of nested canalizing functions have dynamic properties that make them suitable for modeling gene regulatory networks, namely small number of attractors and short limit cycles. In this talk, I will discuss a normal form as polynomial function that applies to any Boolean or multi-state function. This description provides a partition of the inputs of any Boolean function or multi-state function into canalizing and non-canalizing variables and, within the canalizing ones, we can categorize the input variables into layers of canalization. I will also describe the structure of the non-canalizing variables. Applications for how to use this normal form and some other properties of these functions will be given at the end of the talk.

Randolph Nesse:
Intrinsically Vulnerable Organic Systems

Natural selection shapes living systems to such remarkable efficacy and robustness that disease vulnerability is usually and correctly attributed to the limits of natural selection. Mutation, migration, genetic drift, path dependence and the slow pace of evolution are important explanations for disease vulnerability. Some systems are, however, intrinsically vulnerable to failure for other reasons. The role of tradeoffs is well-recognized, but it may have wider applications than is often appreciated. For instance, antagonistic pleiotropy provides benefits early in life that maximize reproduction at the cost of a shorter life span. Systems that regulate defenses such as immune responses and anxiety are expected to generate false alarms because the costs of not responding are far higher than the costs of a false alarm. Some such systems become more responsive after repeated arousal, making them inherently vulnerable to runaway positive feedback, as may be illustrated by panic disorder and cytokine storm. Traits with cliff-edged fitness functions are especially vulnerable to failure. Strong selection on a trait vulnerable to catastrophic failure, such as racehorse bones, is an example. Even in the absence of strong recent selection, such traits are likely to be vulnerable because natural selection shapes them to a mean value that maximizes multigenerational gene transmission despite the associated increase in the proportion of population with low fitness. Pathogen pressure is likely to also shape fitness functions with steep slopes. Higher telomerase activity and numbers of stem cells provide advantageous tissue repair but increases the risk of cancer. Uric acid concentrations give increasing antioxidant benefits until crystals form and cause gout. The high heritability of many diseases is turning out to arise from the tiny effects of many alleles spread across the entire genome. Some are deleterious mutations subject to mutation selection balance, but some may be maintained because they influence the level of a trait with a cliff-edged fitness function. Disorders that can be considered in this light include epilepsy, atrial fibrillation, migraine headaches, and schizophrenia.

Karl Niklas:
Polarity, Planes of Cell Division, and the Evolution of Multicellularity 

Organisms as diverse as bacteria, fungi, plants, and animals manifest a property called “polarity.” The literature shows that polarity emerges as a consequence of different mechanisms in different lineages. However, across all unicellular and multicellular organisms, polarity is evident when cells, organs, or organisms manifest one or more of the following: orientation, axiation, and asymmetry. I will review the relationships among these three features in the context of cell division and the evolution of multicellular polarity primarily in plants (defined here to include the algae). Data from unicellular and unbranched filamentous organisms (e.g., Chlamydomonas and Ulothrix) show that cell orientation and axiation are marked by cytoplasmic asymmetries. Branched filamentous organisms (e.g., Cladophora and moss protonema) require an orthogonal reorientation of axiation, or a localized cell asymmetry (e.g., “tip” growth in pollen tubes and fungal hyphae). The evolution of complex multicellular meristematic polarity required a third reorientation of axiation. These transitions show that polarity and the orientation of the future plane(s) of cell division are dyadic dynamical patterning modules that were critical for multicellular eukaryotic organisms.

Fred Nijhout:
Causes and Consequences of Robustness and Plasticity in Biological Systems: Two Sides of the Same Coin

Two universal Rules of Life are that all organisms are subject to variable environments, and all are also subject to continuous mutations in genes that are important for normal function and survival. Organisms have evolved a variety of mechanisms that buffer form and function against deleterious environmental and genetic variables. These are collectively called homeostatic and robustness mechanisms, which stabilize the phenotype, so that the same phenotype is produced in spite of genetic and environmental variation. Insofar as natural selection acts only on phenotypes, but heritable change comes from genotypes, it has been thought that robustness mechanisms produce a constraint on evolution by decoupling phenotype form genotype. An apparently contradictory fact is that many organisms have a variable phenotype that depends on environmental conditions. This is called plasticity, and produces different phenotypes from the same genotype. Plasticity, therefore, also seems to uncouple phenotype and genotype. Plasticity, like robustness, can be an adaptation to a variable environment. Using conceptual and mathematical models, I will discuss a diversity of mechanisms that produce robustness and plasticity and show they are closely related. I will also discuss why such mechanisms, rather than constraining evolution, actually enable rapid evolution.

John Tyson:
Information Processing in Living Organisms: What Does Bifurcation Theory Teach Us?

One of the basic characteristics of living organisms is their ability to process information about their external environment and internal state and to implement adaptive responses to the challenges they face. At the cellular level, these information processing tasks are carried out by complex networks of interacting genes and proteins; quite differently than the information processing done by digital computers or (analog) central nervous systems. Despite the triumphs of molecular biologists over the past 40 years in identifying and characterizing the components of these networks, their information-processing capabilities are still largely mysterious. Is there a basic theory of information-processing by molecular reaction networks that is biochemically realistic, reasonably accurate and comprehensive, and of predictive value? I will make the case that bifurcation theory of dynamical systems provides a framework for thinking about this problem. Briefly put, a one-parameter bifurcation diagram (dynamical variable as a function of control parameter) is the mathematical analog of the physiologist’s “signal-response” curve; and a two-parameter bifurcation diagram (e.g., physiological control parameter versus level of gene expression) can provide insight into the translation from genotype to phenotype. I will illustrate these principles with a number of classic examples from the field of network dynamics and cell physiology, and I will relate this particular problem to broader considerations of the “Rules of Life”.

Alexandria Volkening:
Modeling Pattern Formation on the Skin of Zebrafish

Abstract not available.

Yangyang Wang:
Analysis for Neuromechanical Motor Control System with Hard Boundary

Many neuromechanical motor control systems exhibit periodic motions that make and break contact with constraint surfaces, and adjust the shape and timing of the motion in response to external perturbations to enhance robustness for motor control. The existing methods of variational and phase response curve analysis are well established for quantifying changes in timing and shape for smooth systems and have recently been extended to nonsmooth dynamics with transversal crossing boundaries. In this work, we further extend both methods to nonsmooth systems with hard boundaries, for both instantaneous and sustained perturbations. These analyses are applied to a control system of feeding movements in the sea slug Aplysia to uncover the mechanism of the robust sensory feedback control.