Artificial selection for low and high endurance exercise capacity in rats Steven L. Britton Lauren Gerard Koch University of Michigan Artificial Selection for Low and High Endurance Exercise Capacity in Rats

John P. Rapp Studied the genetics of Dahl salt sensitive rats. Starting in 1982 I was influenced by the quantitative geneticist John Rapp. The Pioneer of Mammalian Genomics. He stimulated me to think about animal models of complex diseases. I studied models but could not grasp the logic. They seemed too simplistic. Streptozotocin = diabetes? Coronary occlusion = heart failure? Knock in/knock out? Mutagenetics? None captured the polygenic condition of complex diseases or followed from a hypothesis

Initial idea: use artificial selection to create a low and high form for disease risks. Make contrasting models. But what trait would tell us the most about disease? I went searching……….and made guides (~1986). The model must: 1) emulate an important clinical phenotype(s) 2) be polygenic 3) respond to positive and negative health environments 4) be explained by fundamental scientific principles. Wanted the approach to be explanatory and predictive.

Energy Metabolism Evolution + Disease An idea emerged in ~1988 I envisioned a connection between disease and evolution that might have mechanistic value Clinical Association Theoretical base

Clinical Association: In the 1980s A literature emerged demonstrating a strong statistical linkage between a wide range of disease risks and low capacity for energy transfer. On this basis I formulated the: Energy transfer hypothesis “Variation in capacity for energy transfer is a central mechanistic determinant of the divide between disease and health.” [the wide ranging influence of exercise was perplexing: diabetes→heart failure→cancer→depression]

1992: I formulated that 2-way artificial selection for low and high exercise capacity would test the energy transfer hypothesis. That is, would disease risks segregate with artificial selection for low capacity for energy transfer? If true, it would also yield mechanism-based contrasting models for study. This was the predictive type of approach I sought. LOWHIGH High Disease Risk Low Disease Risk Founder Population 1996 capacity n low high capacity low high capacitylowhigh capacity low high capacity lowhigh Generation

Energy Metabolism Evolution + Disease An idea emerged in ~1988 I envisioned a connection between disease and evolution that might have mechanistic value Clinical Association Theoretical base We thought it weak to move forward based only upon clinical association

We sought a principle-based explanation for the Energy Transfer Hypothesis. In a very non-linear path we connected ideas from: Evolution Energy Metabolism Earth’s oxygen history

Two messages in this paper: 1. Life evolves along the transfer of energy. 2. More complexity equates with more energy transfer. -You don’t get something for nothing -This paper made the obvious perfectly clear Hans Krebs Jack Baldwin Directed us towards using evolution and thermodynamics. The evolution of metabolic cycles Jack E. Baldwin & Hans Krebs Nature 1981

Biochemical Pathways Krebs Cycle Energy transfer capacity evolved simultaneously with all other features.

From Alberts, et al, Molecular Biology of the Cell Pyruvate Acetyl CoA Glucose Cholesterol

THE RELATIVE ELECTRONEGATIVITY OF ATOMS LINUS PAULING Journal of the American Chemical Society Volume 54, p , 1932 Pauling scale: 0.7 lowest 3.98 = highest Start with the obvious Oxygen is special in the universe for energy transfer Operates at the high end of the energy spectrum Ranks #2 in electronegativity amongst all elements

photosynthesis: electrons to carbon respiration: electrons to oxygen Energy transfer is basically an electron shuttle between oxygen and carbon. Pauling Electronegativity Scale (0.9 to 4.1)

As a heuristic, we synthesized bio-complexity and earth’s oxygen history to a one page picture. 1. The rise of oxygen over the past 205 million years and the evolution of large placental mammals. Paul Falkowski, Science (2005). 2. The oxygenation of the atmosphere and oceans. Heinrich Holland, Philos Trans R Soc Lond B Biol Sci (2006). 3. Why O2 is required by complex life on habitable planets and the concept of planetary "oxygenation time?" David Catling et al, Astrobiology (2005). 4. A molecular time scale of eukaryote evolution and the rise of complex multicellular life. Blair Hedges, et al, BMC Evolutionary Biology (2004) Koch & Britton, J. Physiology, 2008

4.6 Earth formation 3.7 First living cells 3.3 Anoxygenic photosynthesis 2.5 Oxygenic photosynthesis Great oxidation event Aerobic respiration widespread Multicellular organisms Placental animals Single cell organisms onlySingle & multicellular organisms There are no complex multicellular organisms that are purely glycolytic Anaerobic only: (glycolysis) single cells Anaerobic + aerobic: multicellular complexity Koch & Britton, J. Physiology, 2008

Founder Population Generation 1 Generation 2 Generation 3 Generation 4 LOWHIGH In 1996 we started artificial divergent selection for energy transfer capacity. Low capacity runner = LCR High capacity runner = HCR

Current = Intrinsic + Adaptational Phenotype Sedentary Acquired by training Exercise Capacity Can Be Operationally Divided Into Two Components.

Energy transfer capacity was estimated from a speed-ramped treadmill run to exhaustion Assessed for Intrinsic capacity Not trained capacity N:NIH as founder population Rat equivalent of the Bruce Protocol

Yu-yu Ren, Katherine Overmyer, Nathan Qi, Mary Treutelaar, Lori Heckenkamp, Molly Kalahar, Lauren Koch, Steven Britton, Charles Burant, Jun Li, PLOS ONE, ~ 14,000 rats HCR LCR

The proportion of total running performance that is due to the additive effects of genes is about 40% in each line. [h 2 or narrow sense heritability] Heritability estimates for maximal running distance (G1-G28) LineSOLAR*WOMBAT* HCR0.44 ± ± 0.08 LCR0.39 ± ± 0.06 Yu-yu Ren University of Michigan Jun Li Human Genetics *Modern variants of: Average information algorithm and Spatial matrix Residual Maximum Likelihood (ASreml) software Heritability

 Longevity & Aging (Karvinen & Kainulainen)  Phosphorylating respiration (Kainulainen, Hawley)  Fatty liver disease (Thyfault) Post-surgery cognitive decline (Mervyn Maze)  Metabolic syndrome (Wisloff)  Activity (NEAT) (Levine & Novak)  Cardiac stress signaling (Burniston) Alzheimer’s-like neurodegeneration (Russell)  Intra-cerebral hemorrhage (Keep & Hua)  Metabolic flexibility (Evans & Burant)  Susceptibility to cancer (Thompson)  Hippocampal Neurogenesis (Tognoni & Williams) LCR relative to HCR display

High runners live longer Survival Curves (n= 23 LCR n= 23 HCR) 24 months 34.7 months (From Lauren Koch……Ulrik Wisloff et. al, Circulation Research, 2011)

VO 2max predicted time of death both between strains and for each rat within strain.

Exercise Capacity = Innate + Adaptive Rat Model #2 Low Response Trainers - LRT High Response Trainers - HRT Exercise Capacity Can Be Divided Into Two Components.

-In the large sense- We do not have explanation for how (apparently) disparate clinical conditions associate with low aerobic exercise capacity. For interpretation we synthesize ideas from Hans Krebs, Peter Mitchell, and Ilya Prigogine about non-equilibrium thermodynamics and entropy (order from disorder). -Succinctly-

Summary of Prigogine’s conclusions: 1.Systems tend to organize to a higher complexity when the resulting system can dissipate energy faster than the independent parts. 2.Entropy can temporarily decrease and ordered systems can form (order from disorder). Interpreting through Ilya Prigogine is our new challenge. (a non-equilibrium thermodynamic lens) Nobel Prize: Chemistry 1977 "for his contributions to understanding energy dispersal and complexity”

Condensed statement: 1)evolution was underwritten by obligatory energy dissipation mechanisms (entropy). 2)emergence of complexity was coupled to the high energetic nature of oxygen metabolism. These statements form the basis for the Energy Transfer Hypothesis: “Variation in capacity for energy transfer is a central mechanistic determinant of the divide between disease and health.” -Selection for low and high exercise capacity was an unbiased test of this hypothesis- EvolutionEnergy metabolismEnergy dissipation ┼ ┼ Krebs Mitchell Prigogine

These contrasting rat model systems are maintained as an international resource by: Department of Anesthesiology University of Michigan and National Institutes of Health United States Department of Health and Human Services Low Capacity Runner (LCR) High Capacity Runner (HCR) Low Response Trainer (LRT) High Response Trainer (HRT) Contact Steven Britton or Lauren Koch at the University of Michigan for availability of these rats for study

Exercise Capacity = Innate + Adaptive Rat Model #2 Low Response Trainers - LRT High Response Trainers - HRT Exercise Capacity Can Be Divided Into Two Components.

In 1999 the HERITAGE Family Study provides initial information about the large inter-individual variation in response to exercise training. Bouchard et al., J. Appl. Physiol. 87(3), 1999 V)VO 2 max Low responders High responders Twin and familial studies show a significant genetic component. Δ VO 2 max (ml/min)

Wide variation for response to training in N:NIH genetically diverse rats Population mean = +140 m Koch et al., Physiol Gen. 2013

Mean for HRT = +223 m -65 m = Mean for LRT Selection produced populations of Low Response Trainers (LRT ) and High Response Trainers (HRT). Koch et al., Physiol Gen min longer 2.5 min less

Blunted Cardiomyocyte Remodeling Response in Exercise-Resistant Rats Ulrik Wisloff......>>......Lauren Koch, 2015 Wisloff et al., 2015

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 Metabolic flexibility (Evans & Burant) Art created by Maggie Burant

Miami Nature Winter Symposia, Celebration of 50 th year of the“Double Helix.” Jim Watson to Lauren Koch: “If you go after something big, everyone will try to make you feel bad.”

Miami Nature Winter Symposia, Celebration of 50 th year of the“Double Helix.” Koch, Watson, Britton, Irene Wolf

Ju Li, Yu-Yu Ren, Steve Britton, Jonathon Flint Cold Spring Harbor Laboratory, December, 2013