Physiol. Genomics 30: 205-208, 2007.
First published May 1, 2007; doi:10.1152/physiolgenomics.00043.2007
1094-8341/07 $8.00
Received 23 February 2007;
accepted in final form 26 April 2007.
Physiological Genomics 30:205-208 (2007)
1094-8341/06 $8.00 © 2007 American Physiological Society
Perspectives
Evolution, atmospheric oxygen, and complex disease
Lauren Gerard Koch and
Steven L. Britton
Functional Genomics Laboratory, Department of Physical Medicine and Rehabilitation, University of Michigan, Ann Arbor, Michigan
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ABSTRACT
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If evolution is an accurate statement of our biology, then disease must be tightly associated with its patterns. We considered selection for more optimal capacity for energy transfer as the most general pattern of evolution. From this, we propose that the etiology of complex disease is linked tightly to the evolutionary transition to cellular complexity that was afforded by the steep thermodynamic gradient of an oxygen atmosphere. In accord with this thesis, clinical studies reveal a strong statistical link between low aerobic capacity and all-cause mortality. In addition, large-scale unbiased network analyses demonstrate the pivotal role of oxygen metabolism in cellular function. The demonstration that multiple disease risks segregated during two-way artificial selection for low and high aerobic capacity in rats provides a remote test of these possible connections between evolution, oxygen metabolism, and complex disease. Even more broadly, an atmosphere with oxygen may be uniquely essential for development of complex life anywhere because oxygen is stable as a diatomic gas, is easily transported, and has a high electronegativity for participation in energy transfer via redox reactions.
thermodynamics; metabolism; health; biocomplexity
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INTRODUCTION
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ABOUT TWENTY YEARS AGO we started an assessment of how to create an animal model that emulates the polygenic nature of a complex disease such as Type 2 diabetes or hypertension. We did not think that the commonly utilized animal models were appropriate, and an updated version of this view can be summarized in four statements: 1) Chemical and physical maneuvers, such as administration of streptozotocin to mimic diabetes mellitus or ligation of coronary arteries to emulate arterial disease, more accurately reflect response to injury and not the progression of disease. 2) Single- or multiple-gene knockout approaches are problematic because complex diseases generally result from expression of combinations of allelic variants sensitive to a given environment (18). That is, gene knockout only reveals essentiality of a gene and biological reorganization subsequent to its loss. 3) Mutagenic approaches, such as that produced by administration of the gametic mutagen ethylnitrosourea (ENU), are random and provide no direct information as to what allelic variants or gene combinations are involved (20). 4) Superficially, it seems that disease models derived from selection would be highly useful. Yet selection for a particular disease is problematic if it is based on measurable traits or symptoms and not the full complement of underlying mechanisms. This problem is amplified because chronic diseases emerge not as discrete events, but as complexes, such as the cascade represented by the metabolic syndrome. These kinds of problems led us to consider a more fundamental and speculative approach to the development of animal models of complex diseases.
The initial idea was that disease must be associated closely with the strongest pattern of evolution. We defined this pattern operationally as selection for a more optimal capacity for energy transfer (2). From this, we propose that complex disease is linked tightly to the evolutionary transition to cellular complexity that was afforded by the steep thermodynamic gradient of an oxygen atmosphere. As a test of these possible connections, we hypothesized that artificial selection of rats based on low and high intrinsic aerobic treadmill running exercise capacity would yield models that contrast for disease risks. Here we first describe the models that emerged and then explain the underlying logic.
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Artificial Selection for Complex Disease
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In 1996 we (14) started large-scale selective breeding to develop strains of rats that contrast for intrinsic (i.e., untrained) aerobic treadmill running capacity. After 11 generations of selection, the low-capacity runners (LCR) and high-capacity runners (HCR) differed by over 300% in aerobic running capacity (Fig. 1). The LCR scored higher on cardiovascular risks and features of the metabolic syndrome, including higher blood pressure, insulin, random glucose, fasting glucose, free fatty acids, visceral adiposity, and triglycerides when young adults. The HCR were higher for health factors (29) such as maximal oxygen consumption, heart function, endothelial nitric oxide formation, economy of oxygen use, and levels of transcription factors and oxidative enzymes required for mitochondrial function in skeletal muscle (Fig. 2).
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Fig. 1. Response to selection for aerobic treadmill running capacity across 11 generations (n = 2,912 rats). On average the low-capacity runner (LCR) rats decreased 16 m per generation and the high-capacity runner (HCR) rats gained 40 m per generation in distance run to exhaustion. Values are means ± SD. Modified from Ref. 29.
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The general divide in aerobic capacity and health status between LCR and HCR was confirmed in studies using rats from generations 15–19 of selection (10, 27). LCR rats from generations 15 and 17 were found to be more susceptible to ischemia-mediated cardiac ventricular tachycardia relative to HCR (16); although predictable from our general hypothesis, this is an important find because acute coronary artery occlusion that leads to ventricular arrhythmias is the leading cause of death in humans in developed countries (1).
Because of the interaction of environments with genetic predisposition to disease, it was of large interest to know whether LCR and HCR respond differentially to clinically relevant changes in environment. In the first trial of this possibility (22), the effects of a high-fat diet (HFD) on weight gain patterns, insulin sensitivity, and fatty acid oxidative capacity were evaluated in sedentary male rats. LCR rats fed normal chow were heavier, hypertriglyceridemic, and less insulin sensitive and had lower skeletal muscle oxidative capacity compared with HCR rats. LCR rats on a HFD gained more weight and fat mass, and their insulin-resistant condition was exacerbated, despite consuming similar amounts of metabolizable energy as chow-fed controls. Remarkably, these metabolic variables remained unaltered in HCR when shifted from normal chow to HFD.
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Clinical Studies Provide Circumstantial Evidence
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Clinical investigations demonstrate dysfunctional oxygen and energy metabolism in essentially all disease conditions such as Type 2 diabetes (18), cardiac arrhythmias (1), inflammation (5), neurodegenerative dysfunction (15), and cancer (17). In a study with over 6,000 subjects, Myers and colleagues (19) concluded that aerobic exercise capacity is a more powerful predictor of mortality than other established risk factors. They reported a 12% increase in survival for each 1-metabolic equivalent (MET) increase in aerobic capacity. At a closer functional level it has been shown that the hydrolysis potential at which oxidative phosphorylation can deliver ATP in the heart is a better predictor of cardiovascular mortality than usual clinical indexes such as ejection fraction (21).
As a direct test of the hypothesis that inefficient energy metabolism in blood vessels can promote vascular disease, Bernal-Mizrachi et al. (4) generated mice with doxycycline-inducible expression of the mitochondrial uncoupling protein-1 (UCP-1) in the walls of arteries. They found that UCP-1 expression in aortic smooth muscle cells causes hypertension and increases dietary atherosclerosis without affecting cholesterol levels. UCP-1 expression also increased superoxide production and decreased the availability of nitric oxide, suggestive of oxidative stress.
Longevity and capacity at a given age can perhaps be considered the most relevant clinical phenotypes. Zahn et al. (30) compared transcriptional profiles across aging in humans, mice, and Drosophila. Although expression changes were species specific (private) for several pathways, only the electron transport pathway was decreased in association with aging in all three species (public). These results suggest that changes in electron transport pathways may be the common signature that underlies aging.
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The Speculation
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Our goal was to define the broadest possible feature mechanistically underlying the polygenic condition of complex disease and then artificially select for low and high forms of this feature. This led us to consider that disease is tightly associated with the patterns of evolution. For this we "borrowed" heavily from a paper by Baldwin and Krebs entitled "The evolution of metabolic cycles" (2). This paper initiated our view that evolution is a thermodynamic event related to the more optimal use of resources. That is, selection weighs the benefit of a change for its worth in energy transfer.
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Atmospheric Oxygen and the Evolution of Complexity
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There is general agreement that cellular life originated 
3.7 billion years ago (Ga) in an anoxic environment. For anaerobic energy transfer early organisms developed glycolytic pathways that are extant for all known cells (26). The relatively modest energy transfer afforded by glycolysis was sufficient for life at the single-cell level, but there are no known examples of multicellular complex organisms that are exclusively anaerobic (6). Further complexity apparently required and awaited, pari passu, the development of pathways for larger energy transfer.
Geochemical studies have assembled a reasonably well known history of Earth's oxygenation (6, 9, 12) (Fig. 3). Cells capable of anoxygenic photosynthesis were present about 3.3 Ga. By 2.4 Ga oxygenic photosynthesis became established and initiated the Great Oxidation Event (GOE) with atmospheric oxygen increasing to a partial pressure of 15 mmHg by 2.0 Ga. During the next 1 billion years aerobic respiration and small noncomplex organisms became widespread in an atmosphere of oxygen that remained at 15 mmHg. From 1.0 to 0.5 Ga atmospheric oxygen rose to its current value of 150 mmHg. This increase was associated with an escalating development of complexity that included the Cambrian explosion during which all the major animal phyla appeared. Protein sequence data and molecular clock methods have been used to estimate the timing of the rise in the number of different cell types (11). Organisms with 2–3 cell types appeared shortly after the GOE (2.3 Ga) and increased up to 120 cell types by 0.5 Ga (Fig. 1). The concurrent increases in atmospheric oxygen and cell type, as a marker of complexity, provide circumstantial evidence of mechanistic association.
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Fig. 3. Oxygen and complexity.  , Atmospheric oxygen (in mmHg) as estimated from geochemical studies (6, 9, 12); •, number of cell types present as estimated with protein sequence data and molecular clock methods (11). The coincident increases in atmospheric oxygen and complexity are suggestive of mechanistic association.
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At a fundamental level, organisms can be viewed as systems in thermodynamic disequilibrium (24) that exist by exchanging low-entropy inputs for high-entropy outputs to yield a continuous stream of transferred free energy (i.e., energy that can be converted to do work). From this, we presume it axiomatic that a transfer of free energy was necessary and antecedent for the transition from inanimate to animate (biogenesis) and for all subsequent steps of escalating biocomplexity. This view implies that the initial and continued driving force behind evolution is related directly to capacity of selectable replicating units to transfer free energy that is obligatory for change. Atmospheric oxygen was apparently permissive for evolution of complex pathways within single cells that could transfer energy by utilizing the widened redox potential afforded by oxygen. The emergence of multicellular organisms with multiple cell types was presumably a continuation of this pattern.
Several thermodynamically advantageous properties may make oxygen a requirement for development of complex life in any biosphere (6). First, reduction of oxygen provides for close to the largest possible energy transfer per electron exchange. That is, among the 85 stable elements only 9 are more electronegative on the Pauling scale than carbon and thus able to serve as an acceptor of electrons from carbon-based fuel substrates. Of these nine, oxygen ranks second only to fluorine in electronegativity. Second, diatomic ground-state triplet oxygen is sufficiently stable to allow it to accumulate and distribute freely as an atmospheric gas. Third, a terminal oxidant in the form of a gas seems more likely, relative to a liquid or solid, because the lower viscosity and higher diffusibility of gases make transport less costly.
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Network Analysis Reveals Centrality of Energy Transfer Pathways
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The centrality of energy transfer pathways is revealed in three large-scale unbiased interrogations of biological connectivity. First, Jeong et al. (13) examined the core metabolic networks of 43 organisms in the WIT database (now merged into PUMA 2). The goal was to quantify the topological properties of metabolic networks with graph theory and statistical mechanics. Analysis yielded two conclusions: 1) biochemical reactions connect through nodes as scale-free networks, and 2) the most highly associated nodes were for pathways associated with energy transfer [top 15 nodes: H2O, ADP, phosphate, ATP, L-glutamate, NADP+, pyrophosphate, NAD+, NADPH, NADH, CO2, NH4, coenzyme A (CoA), AMP, and pyruvate].
Second, Barrett et al. (3) used a genome-scale in silico reconstruction of the integrated transcriptional regulatory and metabolic network for Escherichia coli (iMC1010v1) to computationally assess growth phenotypes. The visualized structure showed that the regulatory network governing metabolism in E. coli responds primarily to the available electron acceptor and to the presence of glucose as the carbon source.
Third, Raymond and Segrè (25) evaluated the effect of the presence or absence of common biomolecules such as oxygen on the complexity of metabolic networks. They used a heuristic in which sets of compounds were allowed to react according to the rules of the Kyoto Encyclopedia of Genes and Genomes (KEGG) to create reaction networks. The first network was generated from a randomly chosen set of seed compounds. The second network was generated from that same seed set amended with the addition of one of these nine metabolites: NAD+, S-adenosyl methionine, CoA, ATP, O2, CO2, NH3, pyruvate, or 2-oxoglutarate. Their analysis revealed the existence of four discrete groups of networks of increasing complexity. Groups I, II, and III were associated with a maximum of 2,800 reactions. The most complex group IV reactions were associated almost exclusively with the presence of oxygen and had about 1,000 more reactions than networks achieved in the absence of oxygen. This striking connection of oxygen with network complexity strengthens the argument that increases in atmospheric oxygen were permissive for evolution of advanced biocomplexity. In accordance with this, new evidence suggests that differences in atmospheric oxygen are explanatory for the large-scale biological events of insect gigantism (8), polar gigantism (7), and Romer's Gap in vertebrate and arthropod terrestrialization (28).
In summary, our initial idea that major features of complex diseases are mechanistically underwritten by flaws in oxygen metabolism is consistent with current information assembled from a broad range. Simultaneous emergence of contrasting health profiles during two-way artificial selection for low and high aerobic capacity corroborates this notion. Nevertheless, evidence for the general idea that complex diseases are mechanistically associated with flaws in oxygen metabolism is circumstantial and direct tests remain a challenge. Recently, Pladevall and colleagues (23) used confirmatory factor analysis to conclude that the components of the metabolic syndrome are manifestations of a single common mechanistic factor. We suggest that alteration in oxidative capacity is that underlying factor.
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GRANTS
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This work was supported by National Heart, Lung, and Blood Institute grant HL-6427 and National Center for Research Resources Grant RR-17718.
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ACKNOWLEDGMENTS
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We gratefully acknowledge Lori Gilligan and Nathan Kanner for expert care of the LCR/HCR rat colony, Julie Stotler for preparation of the manuscript, and J. W. Britton for helpful discussions.
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FOOTNOTES
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Address for reprint requests and other correspondence: S. L. Britton, Functional Genomics Laboratory, 2220 Basic Science Research Bldg., Dept. of Physical Medicine and Rehabilitation, Univ. of Michigan, Ann Arbor, Michigan 48109-2200 (e-mail: brittons{at}umich.edu).
Article published online before print. See web site for date of publication (http://physiolgenomics.physiology.org).
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Copyright © 2007 by the American Physiological Society.
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ABSTRACT
INTRODUCTION
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