Is metabolism goal-directed? Investigating the validity of modeling biological systems with cybernetic control via omic data

Cybernetic models are uniquely juxtaposed to other metabolic modeling frameworks in that they describe the time-dependent regulation of cellular reactions in terms of dynamic metabolic goals. This approach contrasts starkly with purely mechanistic descriptions of metabolic regulation which seek to explain metabolic processes in high resolution — a clearly daunting undertaking. Over a span of three decades, cybernetic models have been used to predict metabolic phenomena ranging from resource consumption in mixed-substrate environments to intracellular reaction fluxes of intricate metabolic networks. While the cybernetic approach has been validated in its utility for the prediction of metabolic phenomena, its central feature, the goal-directed control strategy, has yet to be scrutinized through comparison with omic data. Ultimately, the aim of this work is to address the question Is metabolism-goal directed? through the analysis of biological data. To do so, this work investigates the idea that metabolism is goal-directed from three distinct angles. The first is to make a comparison of cybernetic models to other metabolic modeling frameworks. These mathematical formulations for intracellular chemical reaction networks range from purely mechanistic, kinetic models to linear programming approximations. Instead of comparing these frameworks directly on the basis of accuracy alone, a novel approach to systems biological model selection is developed. This approach compares models using information theoretic arguments. From this point of view, the model that compresses biological data best captures the most regularity in the data generated by a process. This framework is used to compare the flux predictions of cybernetic, constraint-based and kinetic models in several case studies. Cybernetic models, in the test cases examined, provide the most compact description of metabolic fluxes. This method of analysis can be extended to any systems biological model selection problem for the purposes of optimization and control. To further examine cybernetic control mechanisms, the second portion of this dissertation focuses on confronting cybernetic variable predictions with data that is representative of enzyme regulation. More specifically, the dynamic behavior of cybernetic variables, ui, which are representative of enzyme synthesis control are matched with gene expression data that represents the control of enzyme synthesis in cells. This comparison is made for the model system of cybernetic modeling, diauxic growth, and for prostaglandin (PG) metabolism in mammalian cells. Via analysis of these systems, a correlation between the dynamic behavior of cybernetic control variables and the true mechanisms that guide cellular regulation is discovered. Additionally, this result demonstrates potential use of cybernetic variables for the prediction of relative changes in gene expression levels. The last approach taken to test the veracity of cybernetic control is to develop a technique to mine objective functions from biological data. In this approach, returns on investment (ROIs) for various pathways are first established through simultaneous analysis of metabolite and gene expression data for a given metabolic system. Following this, the ROIs are used to determine a metabolic systems observed goal signal. Gene expression data is then mined to select genes that show expression changes that are similar to the goal signal\u27s behavior. This gene list is then analyzed to determine enriched biological pathways. In the final step, these pathways are then surveyed in the literature to establish feasible metabolic goals for the system of interest. This method is applied to analyze diauxic growth and prostaglandin systems and generates objective functions that are relevant to known properties of these metabolic networks from the literature. An enhanced understanding of metabolic goals in mammalian systems generated by this work reveals the potential utility of cybernetic modeling in new directions related to translational research. Overall, this investigation yields support of the notion of dynamic metabolic goals in cells through comparison of metabolic modeling approaches and through the analysis of omic data. From these results, a lucid argument is made for the use of goal-directed modeling approaches and a deeper understanding of the optimal nature of metabolic regulation is gained

The role of stimulus-driven versus goal-directed processes in fight and flight tendencies measured with motor evoked potentials induced by Transcranial Magnetic Stimulation

This study examines two contrasting explanations for early tendencies to fight and flee. According to a stimulus-driven explanation, goal-incompatible stimuli that are easy/difficult to control lead to the tendency to fight/flee. According to a goal-directed explanation, on the other hand, the tendency to fight/flee occurs when the expected utility of fighting/fleeing is the highest. Participants did a computer task in which they were confronted with goal-incompatible stimuli that were (a) easy to control and fighting had the highest expected utility, (b) easy to control and fleeing had the highest expected utility, and (c) difficult to control and fleeing and fighting had zero expected utility. After participants were trained to use one hand to fight and another hand to flee, they either had to choose a response or merely observe the stimuli. During the observation trials, single-pulse Transcranial Magnetic Stimulation (TMS) was applied to the primary motor cortex 450 ms post-stimulus onset and motor evoked potentials (MEPs) were measured from the hand muscles. Results showed that participants chose to fight/flee when the expected utility of fighting/fleeing was the highest, and that they responded late when the expected utility of both responses was low. They also showed larger MEPs for the right/left hand when the expected utility of fighting/fleeing was the highest. This result can be interpreted as support for the goal-directed account, but only if it is assumed that we were unable to override the presumed natural mapping between hand (right/left) and response (fight/flight)

A trans-diagnostic perspective on obsessive-compulsive disorder

© Cambridge University Press 2017. This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.Progress in understanding the underlying neurobiology of obsessive-compulsive disorder (OCD) has stalled in part because of the considerable problem of heterogeneity within this diagnostic category, and homogeneity across other putatively discrete, diagnostic categories. As psychiatry begins to recognize the shortcomings of a purely symptom-based psychiatric nosology, new data-driven approaches have begun to be utilized with the goal of solving these problems: specifically, identifying trans-diagnostic aspects of clinical phenomenology based on their association with neurobiological processes. In this review, we describe key methodological approaches to understanding OCD from this perspective and highlight the candidate traits that have already been identified as a result of these early endeavours. We discuss how important inferences can be made from pre-existing case-control studies as well as showcasing newer methods that rely on large general population datasets to refine and validate psychiatric phenotypes. As exemplars, we take 'compulsivity' and 'anxiety', putatively trans-diagnostic symptom dimensions that are linked to well-defined neurobiological mechanisms, goal-directed learning and error-related negativity, respectively. We argue that the identification of biologically valid, more homogeneous, dimensions such as these provides renewed optimism for identifying reliable genetic contributions to OCD and other disorders, improving animal models and critically, provides a path towards a future of more targeted psychiatric treatments.Peer reviewedFinal Published versio

Structure and Complexity in Planning with Unary Operators

Unary operator domains -- i.e., domains in which operators have a single effect -- arise naturally in many control problems. In its most general form, the problem of STRIPS planning in unary operator domains is known to be as hard as the general STRIPS planning problem -- both are PSPACE-complete. However, unary operator domains induce a natural structure, called the domain's causal graph. This graph relates between the preconditions and effect of each domain operator. Causal graphs were exploited by Williams and Nayak in order to analyze plan generation for one of the controllers in NASA's Deep-Space One spacecraft. There, they utilized the fact that when this graph is acyclic, a serialization ordering over any subgoal can be obtained quickly. In this paper we conduct a comprehensive study of the relationship between the structure of a domain's causal graph and the complexity of planning in this domain. On the positive side, we show that a non-trivial polynomial time plan generation algorithm exists for domains whose causal graph induces a polytree with a constant bound on its node indegree. On the negative side, we show that even plan existence is hard when the graph is a directed-path singly connected DAG. More generally, we show that the number of paths in the causal graph is closely related to the complexity of planning in the associated domain. Finally we relate our results to the question of complexity of planning with serializable subgoals

Teleonomy

The distinction between teleology and teleonomy that biologists sometimes refer to seems to be helpful in certain contexts, but it is used in several different ways and has rarely been clearly drawn. This paper discusses three prominent uses of the term “teleonomy” and traces its history back to what seems to be its first use. This use is examined in detail and then justified and refined on the basis of elements found in the philosophy of Aristotle, Kant, Anscombe and others. In the course of this explication, it will also be shown how the description of end-directed processes relates to their explanation

Gaze, goals and growing up: Effects on imitative grasping

Developmental differences in the use of social-attention cues to imitation were examined among children aged 3- and 6-years old (n = 58) and adults (n = 29). In each of 20 trials, participants watched a model grasp two objects simultaneously and move them together. On every trial, the model directed her gaze towards only one of the objects. Some object pairs were related and had a clear functional goal outcome (e.g., flower, vase), while others were functionally unrelated (e.g., cardboard square, ladybug). Owing to attentional effects of eye gaze, it was expected that all participants would more faithfully imitate the grasp on the gazed-at object than the object not gazed at. Children were expected to imitate less accurately on trials with functionally-related objects than those without, due to goal-hierarchy effects. Results support effects of eye gaze on motor contagion. Children’s grasping accuracy on functionally-related and functionally-unrelated trials was similar but they were more likely to only use one hand on trials where the object pairs were functionally related. Implications for theories of imitation are discussed