energy and metabolism - usp€¦ · of enzymes (e.g. in relation to temperature, hydrostatic...

Energy and MetabolismRaul K. Suarez*1

ABSTRACTAlthough firmly grounded in metabolic biochemistry, the study of energy metabolism has gonewell beyond this discipline and become integrative and comparative as well as ecological andevolutionary in scope. At the cellular level, ATP is hydrolyzed by energy-expending processes andresynthesized by pathways in bioenergetics. A significant development in the study of bioenergeticsis the realization that fluxes through pathways as well as metabolic rates in cells, tissues, organs,and whole organisms are “system properties.” Therefore, studies of energy metabolism havebecome, increasingly, experiments in systems biology. A significant challenge continues to bethe integration of phenomena over multiple levels of organization. Body mass and temperatureare said to account for most of the variation in metabolic rates found in nature. A mechanisticfoundation for the understanding of these patterns is outlined. It is emphasized that evolution,leading to adaptation to diverse lifestyles and environments, has resulted in a tremendous amountof deviation from popularly accepted scaling “rules.” This is especially so in the deep sea whichconstitutes most of the biosphere. C© 2012 American Physiological Society. Compr Physiol 2:2527-2540, 2012.

Introduction

The most noble aim of the biochemist,often discussed when inebriate, seldom when sober,is to relate the in vitro to the in vivoChantler (20).

Energy metabolism has been the subject of much researchfor over a century. The intricate details of the reactions in-volved as well as the structures and properties of the enzymesthat catalyze them now fill multiple chapters in undergradu-ate textbooks. So much is known about the subject that it isoften regarded by nonspecialists as a static collection of facts.However, new discoveries and advances in the understand-ing of biochemical processes underlying energy metabolismcontinue to be made. While many biochemists continue tofocus primarily on questions concerning mechanisms, oth-ers have joined with physiologists, expanding the scope ofinvestigations to address functional significance. Thus, thestudy of energy metabolism in animals has evolved to be-come much broader, more integrative and, therefore, physio-logical. Studies of energy metabolism address a wide rangeof questions concerning how the enzymes and pathways ofbioenergetics operate in vivo, how metabolism is integratedover multiple levels of biological organization and regulatedover time courses ranging from seconds to years. Evolution-ary processes have made animals structurally and function-ally diverse as well as adapted to a wide range of environ-mental conditions. Therefore, in addition to asking whethermetabolic rates adapt physiologically within the lifetimes ofindividual animals, researchers ask whether adaptation occursacross generations, whether evolution gives rise to qualitativeor quantitative variation in pathways, enzymes, and fluxes.

The study of the biology of energy expenditure has becomepart of the research agenda of comparative physiology (112).

Cells expend energy mainly in the synthesis of largemolecules, active transport across membranes, and the per-formance of mechanical work. These are made possible bygroup transfer and hydrolysis reactions involving ATP. Understeady-state conditions, ATP concentrations remain relativelystable because rates of synthesis are matched to rates of hy-drolysis. As cells change the rates at which they engage inbiosynthesis, active transport, or mechanical work, regulatorymechanisms ensure that rates of ATP synthesis are dynami-cally matched to rates of ATP hydrolysis. ATP turnover is thecentral process of cellular energy metabolism (2).

Given the complex, multicellular nature of animals, purelybiochemical, reductionist approaches to the study of bioener-getics provide a very incomplete picture of the process. Themetabolism of an organ consisting of multiple cell and tissuetypes, supplied with metabolic fuels and O2 by a circulatorysystem and displaying a rate of physiological function that isregulated according to the needs of the whole animal cannotbe explained solely on the basis of biochemical phenomenaoccurring within individual cells. It is the animal, consistingof multiple (metabolizing) organs, that displays a whole-bodymetabolic rate that changes with the animal’s behavior and re-sponds to changes in its environment (Fig. 1). Thus, to addressa wide range of questions, metabolic rates are measured atrest, or as time-averaged values in the field, as values elevated

*Correspondence to [email protected] of Ecology, Evolution and Marine Biology, University ofCalifornia, Santa Barbara, California

Published online, October 2012 (comprehensivephysiology.com)

DOI: 10.1002/cphy.c110009

Copyright C© American Physiological Society

Volume 2, October 2012 2527

Energy and Metabolism Comprehensive Physiology

Figure 1 The transport of fuels and O2 to cells at various rates ofenergy expenditure [from Weibel (134), with permission]. The illustra-tion emphasizes how, at basal metabolic rate (BMR), ATP hydrolysisby processes such as biosynthesis and ion transport mainly determinethe rate of whole-body energy metabolism. Physical activity results inincreasing contribution to ATP hydrolysis by muscle work such that, atmaximum metabolic rate (MMR or V̇O2max), 90% or more of whole-body metabolic rate is due to the respiration of muscle mitochondria.It is proposed that, at BMR, energy expenditure dominates the controlof whole-body V̇O2 while, at MMR, processes involved in the deliveryof fuels and/or O2 to cells contribute to the control of V̇O2max (34).

during exercise, digestion, lactation, thermogenesis, osmoreg-ulation or depressed during hibernation, anoxia, dessication,or estivation. The importance of a fundamental understandingof the mechanisms underlying temporal, mass-dependent, on-togenetic, intrapopulation, or interspecific variation in rates ofenergy metabolism has become recognized across biologicaldisciplines. However, the scope of the subject is so enor-mous that an introduction to it is necessarily incomplete andidiosyncratic. This one is intended for readers with a basicbackground in physiology and biochemistry. It serves as agateway to some key concepts that have emerged, as well asthe literature pertinent to them.

Biochemical UnderpinningsAnything that is true of E. coli must be true for elephants,except more so

Jacques Monod (in a discussion in 1954).

The complete combustion of carbon compounds to CO2 +H2O leads to the production of heat. However, in biolog-ical systems, the operation of pathways for the oxidationof carbohydrates, fats, and amino acids leads to both heatproduction—Kleiber’s “Fire of Life” (73), as well as the step-wise, regulated capture of some of the energy contained inthese compounds through the synthesis of ATP (2). Glycol-ysis, the Krebs cycle, and fatty acid oxidation are pathways

found in most, if not all, animal species. Biochemists havebeen profoundly impressed by what they consider to be thehighly conserved nature of organisms at the molecular level,that is, the unity of life. Upon further investigation, compara-tive physiologists and biochemists came to realize that thereis considerable diversity within this apparent unity (67). Celltypes within an organism as well as homologous cells acrossspecies vary in terms of the kinds or amounts of enzymes thatthey express; such variation commonly leads to variation inthe extent to which fuels and pathways are used for energymetabolism. In-depth coverage of adaptive variation in kindsof enzymes (e.g. in relation to temperature, hydrostatic pres-sure, and solute microenvironment) is beyond the scope of thisarticle; excellent introductory accounts have been publishedand updated over the past decades (65 and 66). With respectto enzyme concentrations, there is a well-developed concep-tual framework (83, 84, 110) for the use of maximal enzymeactivities, i.e., Vmax values, measured in vitro, as measuresof the maximum capacities for flux through these pathwaysin vivo. In this context

Vmax = [E] × kcat,

where [E] is enzyme concentration and kcat is catalytic effi-ciency or turnover number. In general, the kcat values of or-thologous enzymes purified from animals with similar bodytemperatures are remarkably similar (66, 67). Thus, interspe-cific or inter-tissue variation in Vmax is due to variation in[E]. It is possible to compare maximum capacities for flux,estimated using this approach, with physiological rates of fluxin vivo. This approach has been used, for example, to deter-mine the main substrates and pathways used by the locomo-tory muscles of many species of vertebrates and invertebrates(27-29, 123, 149).

Understanding metabolic regulationCritical to the study of energy metabolism is a basic un-derstanding of metabolic biochemistry. The qualitative andquantitative variation observed in bioenergetic pathways canbe understood in light of these basic principles, but gain bio-logical meaning in the context of ecology and evolution.

Enzyme-catalyzed reactions in multistep pathways dif-fer in their thermodynamic and kinetic properties. In theglycolytic pathway, for example, certain reactions (glyco-gen phosphorylase, hexokinase, and phosphofructokinase) areheld far from equilibrium in vivo; that is, the ratios of [prod-uct]/[substrate] of these reactions in vivo are much less thantheir respective equilibrium constants, measured in vitro. Asa result, their Gibbs free energy changes, �G, are large andnegative, given

�G = �Go − RT ln[product]/[substrate],

where, �Go is the standard Gibbs free energy change (es-timated in vitro), R is the gas constant, and T is absolute

2528 Volume 2, October 2012

Comprehensive Physiology Energy and Metabolism

temperature. These reactions are considered to be thermo-dynamically irreversible in the cell. The Vmax values of en-zymes catalyzing such reactions are commonly measured toestimate upper limits to flux at nonequilibrium steps in path-ways (83,84). In contrast, other reactions are maintained closeto equilibrium in vivo; that is, [product]/[substrate] ratios ofthese reactions in the cell are close to their respective equilib-rium constants. These reactions are reversible in vivo and therate of net flux is the difference between forward and reversefluxes. Both the rate and direction of net flux can change inresponse to changes in [product]/[substrate] in the cell. Thenature of such steps in pathways is such that their Vmax valuesare typically much greater than the rate of pathway flux. Inglycolysis, for example, enzyme Vmax values 2 to 3 ordersof magnitude greater than flux are not unusual. It is a rathercommon notion that pathways have “excess enzyme” in thesense that there is more enzyme than is needed to sustainpathway flux. However, this is an oversimplification of thesituation in vivo. For example, the Vmax of phosphoglucoseisomerase (PGI) in honeybee flight muscles is about 30-foldgreater than the rate of glycolytic flux during flight. Model-ing the reaction according to the Haldane relationship (58)reveals that this is the Vmax required for net flux to occur atthe rate required during flight while the enzyme maintainsnear-equilibrium (109). Thus, in this example, the Vmax forPGI is, in Diamond’s words, “enough but not too much” (38).

While the rules of “solution biochemistry” might be sup-ported by much empirical data (e.g. references 25, 71, and129), it is necessary to consider alternative possibilities. It ispossible, perhaps likely, that metabolism does not happen ina homogeneous “soup” (137, 143). For example, it has beensuggested that the Krebs cycle enzymes operate in the mito-chondrial matrix under conditions so crowded that the rulesof solution biochemistry may not apply (107, 108). Instead,the Krebs cycle enzymes may operate as part of a multien-zyme complex, the “metabolon” (93), wherein Krebs cycleintermediates are handed directly from one enzyme to thenext in a process called “metabolic channeling” (124). Whenglycolytic enzymes are genetically modified such that they nolonger localize at specific parts of myofibrils in Drosophilaflight muscles, the flies can no longer fly (148). The hexok-inase isoform that binds to porin on the outer mitochondrialmembrane preferentially uses ATP obtained from the adeninenucleotide translocase to phosphorylate glucose over ATP inbulk solution (146). There is evidence of metabolic channel-ing in other processes and pathways, but whether “structuredmetabolism” and channeling occur in all cell types is notclear. It is also unclear whether some, most, or all of theflux in metabolism occurs via channeling or whether the de-gree of channeling might change under various circumstances(111, 137).

Flux is a system propertyWith the development of metabolic control theory and itsapplication as metabolic control analysis, the concept of the

single rate-limiting step has fallen into disfavor (49). Flux isconsidered a system property and its control tends to be sharedby multiple steps, including enzyme-catalyzed reactions andmembrane transport. The degree to which the control of fluxis shared by multiple steps can be empirically determined byestimation of flux control coefficients, Ci, which represent thedegree to which various steps, i, contribute to the regulation offlux, J. Ci is expressed, for any step, as the fractional changein flux (δJ/J) that occurs in response to a fractional change inenzyme activity (δei/ei):

Ci = (δ J/J )/(δei/ei ).

It is possible to experimentally determine Ci values forvarious enzyme-catalyzed steps or transport processes in path-ways such as glycolysis (71), fatty acid oxidation (42) andmitochondrial respiration (10) using a variety of approachesincluding genetic manipulation, inhibitor titration, bottom-up,or top-down control analysis. It is also possible to quantifythe extent to which ATP-utilizing processes contribute to therate of cellular energy metabolism relative to the contributionmade by ATP-synthesizing pathways (16). Ci values of dif-ferent steps in a pathway or of different processes in a cellcan dramatically change, depending on physiological circum-stances (Fig. 2). Fell (49) provides an excellent and accessibleintroduction to the theory and practice of metabolic controlanalysis as applied to the analysis of the control of flux at thebiochemical level.

An issue that often arises in comparative physiologicalstudies of metabolic design, fuel use, and flux concerns the“rate-limiting step.” It was previously thought that if the rate-limiting step of a pathway could be identified, then measure-ment of the Vmax of the enzyme catalyzing this step wouldmake possible the prediction of the maximum physiologicalflux rate in vivo (83,84). Metabolic control analysis, of course,has made this a nonissue. In addition, it is now realized that

1.0

0.8

0.6

0.4

Flu

x-co

ntro

l coe

ffici

ent o

ver

resp

iratio

n

0.2

0 20 40

Respiration rate (% of state 3)

60 80 100

Figure 2 Flux control coefficients of ATP turnover (solid line), sub-strate oxidation (thick dashed line), and proton leak (thin dashed line).Results from top-down control analysis show how contributions to con-trol change as the system approaches 100% of state 3 respiration rate.Adapted, with permission, from Suarez and Darveau (114); redrawn,with permission, from Brand et al. (10).



whether the maximum rate of flux of a pathway in vivo evermatches the Vmax values of any of the enzymes catalyzingnonequilibrium reactions is an empirical question. Becauseof the need to regulate flux through pathways, it has beenargued that metabolic enzymes should not operate at Vmax invivo (2). Even in the case of glycolysis, which displays someof the highest metabolic flux rates known, enzymes typicallydo not operate at Vmax (122). Nevertheless, it is important toadd that enzyme Vmax values can be used to address varioustypes of questions (110), including those asked in metaboliccontrol analysis (e.g. references 71 and 75).

With such heavy emphasis on biochemistry must come areminder that many species of animals transport O2 from theexternal environment to mitochondria in various cell types,tissues, and organs via diffusive and convective steps throughrespiratory and cardiovascular systems. It seems clear thatbasal metabolic rate (BMR) values in mammals, for example,are determined by rates of energy expenditure by internal or-gans (34,115,116,132), rather than by delivery rates througha distribution system. At the maximum aerobic metabolicrates achieved during exercise (V̇o2max), when 90% or moreof whole-body metabolic rate is accounted for by musclemitochondria, control is shared by multiple steps in the O2-transport pathway (36,37,70,131) (Fig. 1). Clearly, elephantsmust differ from Escherichia coli in terms of the control ofmetabolic rate and approaches that transcend the study ofcellular biochemistry must be adopted to gain a more com-plete understanding of energy metabolism and its regulationin animals.

Variations on Common ThemesEnzyme Vmax data (27-29, 83) as well as other lines ofevidence, for example, from studies of mitochondrialsubstrate preferences in vitro (80, 113, 117), make possiblethe construction of metabolic maps showing the majorroutes of carbon flow through catabolic pathways in energymetabolism. Such studies have revealed that pathwaysof energy metabolism are most highly conserved amongvertebrate animals. However, despite such conservatism,levels of expression of elements of the metabolic machineryfor ATP synthesis can vary tremendously, reflecting lifestylesand environments. Mitochondria occupy less than 5% ofmuscle cell volume in some species but as high as 35% inhummingbirds (119) and 51% in some Antarctic fish (69).The Vmax values of orthologous glycolytic and Krebs cycleenzymes can vary by as much as a 1000-fold when comparingthe muscles of sluggish, deep-sea species (21, 41) with thoseof high-speed predators such as tunas (56, 57).

Given their long evolutionary histories and degrees ofevolutionary divergence, it is not surprising that greater vari-ation on the common themes of energy metabolism would befound among invertebrate taxa. Parasitic helminth worms areobligately anaerobic and make lactate, acetate, and propionateas end products (78). Marine intertidal invertebrates are facul-

tative anaerobes that use O2 for mitochondrial ATP synthesiswhen it is available, but switch to pathways similar to thosein helminths when anaerobic. Under anoxic or hypoxic con-ditions and, in some cases, during exercise, many species ofmarine mollusks also produce a variety of anaerobic end prod-ucts including octopine (51), alanopine, or strombine (52).The production of these compounds is catalyzed by opinedehydrogenases in reactions considered to be functionallyequivalent to that catalyzed by lactate dehydrogenase (LDH).Whereas vertebrates use only creatine phosphate as theirmuscle phosphagen compound, across invertebrate species,there is great variation in phosphagens as well as in the phos-phagen kinases that catalyze their synthesis and breakdown(43, 44).

Figure 3 is a simplified diagram of the main pathwaysused in carbohydrate and fatty acid oxidation in cardiac, fastand slow oxidative muscles of vertebrate animals. Figure 4shows carbohydrate oxidation in insect flight muscles. Theseare used for comparison to illustrate the paradox of unity anddiversity in cellular bioenergetics. The examples have in com-mon glycolysis, the Krebs cycle and, although not shown, themitochondrial pathways and mechanisms for electron trans-port, proton pumping, and ATP synthesis. Despite these simi-larities, carbohydrate oxidation in vertebrate and insect flightmuscles differ with respect to the mechanisms used to main-tain the high cytoplasmic [NAD+]/[NADH] ratios requiredfor high glycolytic flux. Two shuttles that transfer reducingequivalents from the cytoplasmic to mitochondrial compart-ment are known. These operate through the enzyme-catalyzedreduction of a metabolite in the cytoplasm; this leads to oxida-tion of cytoplasmic NADH to NAD+. The reduced compoundis then transported into the matrix, where it is oxidized. Theoxidation reaction is accompanied by the reduction of NAD+

to NADH or FAD to FADH2 in the mitochondrial matrix.The net effect is the transfer of reducing equivalents fromthe cytoplasm to the mitochondrial matrix. Operation of bothmalate-aspartate (Fig. 3) and glycerol 3-phosphate shuttlescan be demonstrated in mitochondria isolated from vertebratemuscles (7). In contrast, insect flight muscles that rely heav-ily or exclusively on carbohydrate oxidation (e.g. bees) usethe glycerol 3-phosphate shuttle (Fig. 4) and are completelyincapable of using fatty acids to fuel metabolism during flight(98). Vertebrate muscles typically express high activities ofLDH and, under certain circumstances (e.g. when glycolysisserves as the main source of ATP during burst exercise), accu-mulate lactate as an anaerobic end product. In contrast, energymetabolism during flight in insects functions as an obligatelyaerobic, O2-dependent, process (65).

Such examples of variation on the common themes ofenergy metabolism are seen in enzymatic capacities for fueluse. For example, among vertebrates as well as in insects,muscles that rely more on exogenous (blood or haemolymph)glucose to fuel energy metabolism display higher hexokinaseVmax values (28, 117, 123, 149) than muscles that rely moreon endogenous stores of glycogen. Those that rely more onglycogen and less on exogenous glucose as the carbon source



GLYCOGEN G6P

GAP

Glu

1,3DPG

HK

NAD

Pyruvate Pyruvate

Oxaloacetate Citrate

Fatty acylCoA

AcetyCoA

GLUCOSE

CYTOPLASM MITOCHONDRION CYTOPLASM

Glu

Asp

2-KGA

KREBSCYCLE

Oxa

Mal Mal

Asp

Oxa

2 KGA- NADH

NAD

NADH

NADH

NAD

Fatty acylcarnitine

carnitine carnitine

CPT

CPT

Fatty acylcarnitine

Fatty acylCoA

FATTY ACID

CT

Figure 3 Pathways of glucose (left) and fatty acid oxidation (right) in vertebrate muscles, highly simplified, and redrawn, withpermission, from Suarez et al. (120). Readers are encouraged to consult a biochemistry textbook for details. Diagram showsthe role played by the malate-aspartate shuttle in maintaining high cytoplasmic [NAD+]/[NADH] during the oxidation of glucose.Abbreviations: HK, hexokinase; G6P, glucose 6-phosphate; GAP, glyceraldehyde 3-phosphate; 1,3 DPG, 1,3-diphosphoglycerate;NAD+, nicotinamide adenine dinucleotide (oxidized); NADH, nicotinamide adenine dinucleotide (reduced); Oxa, oxaloacetate;Mal, malate; 2-KGA, 2-ketoglutarate; Glu, glutamate; Asp, aspartate; CPT, carnitine palmitoyltransferase; CT, carnitine acyl-translocase.

for pyruvate production display higher glycogen phospho-rylase Vmax values (28, 57, 117, 123, 149). Oxidative verte-brate muscles typically possess the capacity to fuel exercisemetabolism using both carbohydrate or fatty acids and switchback and forth between these, depending upon factors such asprandial state (139, 140) or exercise intensity (11, 133). Beeflight muscles do not express fatty acid oxidizing enzymes andare incapable of using fatty acids to fuel flight (29, 117). Incontrast with bees, other insect species, for example, locusts(6,18), and moths (85,86), also switch between carbohydrateand fatty acid oxidation when fueling flight.

ATP yieldThe physiological purpose of pathways of energy metabolismis the production of ATP; therefore, it is relevant to considerhow much ATP can be obtained from them. In the absenceof O2, obligate as well as facultative invertebrate anaerobesuse pathways that couple the use glycogen and amino acids

to increase to ATP yield beyond what can be derived fromglycolysis alone (64,66). This, along with the storage of largequantities of glycogen and the depression of metabolic (ATPturnover) rates, eliminates the need for O2 in the case ofparasitic helmith worms and enables many marine intertidalspecies to survive anoxia for prolonged periods. Higher ATPyields are obtained in aerobic energy metabolism and Brand(9) provides the most recent estimates of the maximum pos-sible ATP yields of carbohydrate and long-chain fatty acidoxidation (Table 1). The calculations on which these arebased are not as straightforward as might be imagined be-cause, in addition to substrate-level phosphorylations in thecatabolic pathways, the stoichiometry of H+ pumping by el-ements of the electron transport chain and diffusion back inthrough ATP synthase must be considered. Thus, while gly-colysis alone results in a net yield of 2 moles of ATP per moleof glucose metabolized, glucose oxidation, when the malate-aspartate shuttle is used for redox balance results in 28.9 molesATP per mole of glucose with a maximum P/O ratio (ADPphosphorylated to ATP per O atom consumed) of 2.41. The



GLYCOGEN

G6PATP

F6P

FDP

TREHALOSE

FLIGHT MUSCLE HEMOLYMPH FAT BODY

glucose

TREHALOSE

glucose

PROL PROLINEPROL

PROL

CITOXA

glut

TREHALOSE

ACETYL-CoA

DHAPH

GAP

PYR

PYRH

ATPADP

Pi

HCO3

CYTOMITO

G3P

DHAPG3P

-KG

Figure 4 Carbohydrate oxidation in bee flight muscles, also highly simplified, from Suarez et al. (117).Readers are encouraged to consult a biochemistry textbook for details. Diagram highlights the rolesplayed by fat body, hemolymph, cytoplasmic, and mitochondrial reactions and shows the main routesof carbon flow, the role played by the glycerol 3-phosphate (G3P) shuttle in maintaining high cytoplas-mic [NAD+]/[NADH] during the oxidation of glucose, and anaplerotic (pyruvate carboxylase and prolineoxidation) reactions. Abbreviations: Pi, inorganic phosphate; G6P, glucose 6-phosphate; F6P, fructose6-phosphate; FDP, fructose 1,6-diphosphate; DHAP, dihydroxyacetone phosphate; GAP, glyceraldehyde3-phosphate; pyr, pyruvate; G3P, glycerol 3-phosphate; H, reducing equivalent; OXA, oxaloacetate; CIT,citrate; αKG, alpha-ketoglutarate; glut, glutamate; PROL, proline; CYTO, cytoplasmic compartment; MITO,mitochondrial matrix.

oxidation of a mole of palmitate yields 96.46 moles of ATP ata maximum P/O ratio of 2.097. While the stoichiometries ofglucose and palmitate oxidation to CO2 + H2O are fixed, theATP yields and P/O ratios are not predetermined and resultfrom evolved properties of bioenergetic pathways (2, 9).

The balanced equations are useful for the determination ofsubstrate oxidation rates under steady-state conditions by in-

Table 1 Stoichiometries, Respiratory Quotients (RQ), ATP Yields, andMaximum P/O Ratios from Carbohydrate and Long-Chain Fatty AcidOxidation, Taken from Brand (9)

Pathway RQTotal ATPyield

MaximumP/O

Glucose + 12[O] → 6CO2 + 6H2OMalate-aspartate shuttle 1.0 28.9 2.41Glycerol 3-phosphate shuttle 1.0 27.5 2.29Palmitate + 46[O] → 16CO2 + 16H2O 0.7 96.5 2.10

Total ATP yields, when glycogen substitutes for glucose, increase by1.0.

direct calorimetry or respirometry, that is, measurement of O2

consumption (V̇o2) and CO2 (V̇CO2) production rates (50).ATP yields and P/O ratios allow realistic calculation of cel-lular ATP turnover rates. Under certain circumstances, suchcalculations can be performed using respirometric data ob-tained from whole animals. For example, in animals engagedin aerobic, steady-state hovering, the flight muscles accountfor more than 90% of whole-body metabolic rate. In bees andhummingbirds, these muscles consist of a single fiber type.Thus, it is possible to use data obtained with respirometryto determine which fuel(s) are oxidized, to estimate the fluxthrough the relevant pathways, and to estimate the rate ofATP turnover (118). For example, the rate of ATP hydrolysisrequired to hold a hummingbird aloft during hovering shouldbe independent of the nature of the fuel(s) oxidized. There-fore, given the 15% higher P/O ratio when carbohydrate isoxidized compared with the oxidation of fatty acid (9), theV̇o2 would be expected, and is observed, to decline by aboutthis much when fasted hummingbirds that oxidize fatty acidsswitch to carbohydrate oxidation as they feed on sugar (138).The lower requirement for O2 when oxidizing carbohydratemay facilitate hover feeding at high altitude.



Mechanisms Underlying Variation inMetabolic RateVariation in rates of energy metabolism in the same organ oranimal over time, among individuals in a population, or acrossspecies can result from two general types of mechanisms.The first, called metabolic regulation, can be the outcome ofallosteric mechanisms, covalent modification, or mass-actioneffects on flux. For example, within seconds, glycolytic fluxcan be activated by several-hundred-fold when muscles gofrom rest to intense exercise (31); this change in flux doesnot require the synthesis of new protein, that is, it does notrequire the activation of transcription and translation. Thesecond category of mechanism that causes variation in flux,called hierarchical regulation (127), involves changes in [E]and are detectable by measurement of Vmax values. The term“hierarchical” comes from the idea that the change in flux,in this case, is the consequence of changes in [E] that resultfrom changes somewhere in the hierarchy from genome totranscriptome to proteome.

Techniques with which to examine changes in mRNAlevels (e.g. northern blots, real-time quantitative polymerasechain reaction, and microarrays) are now widely used incomparative physiology. Some investigators use these tech-niques to specifically address questions concerning energymetabolism. In other cases, the screening of the expressionof large numbers of genes in response to some kind of envi-ronmental or physiological perturbation yields results indicat-ing changes in mRNA levels of enzymes involved in energymetabolism. It is not uncommon to hear at scientific confer-ences, or to read in scientific papers, statements to the effectthat because mRNA levels of metabolic enzymes change, thenmetabolism must have changed in response to the perturba-tion. This is not necessarily so. For example, Feder and Walser(48) examined the results reported in 21 papers concerningstress responses and found that changes in protein levels canbe predicted by changes in mRNA levels less than 50% ofthe time. However, belief that mRNA and protein levels (ormetabolic rates) are closely related is strong among some re-searchers (55). This is inspired by positive results obtained,for example, in model organisms such as yeast (82) as well asthe finding that more than 80% of the variation in metabolicrates of isolated cardiac ventricles is explained by variationin mRNA coding for metabolic enzymes in Fundulus (30).These issues are addressed and a brief summary of mech-anisms that often lead to lack of correspondence betweenmRNA and protein levels is provided in reference 121.

Two-dimensional polyacrylamide gel electrophoresis hasbeen used in combination with MALDI-TOF mass spectrom-etry as the favored approach in proteomics, taking moleculardata a step closer to physiological function. However, as pre-viously discussed, flux is a system property, and typically notthe consequence of the activity of a single, rate-limiting stepwithin the pathway. If the control of flux is shared by multiplesteps, changes in [E], for example, at the phosphofructoki-nase or citrate synthase or cytochrome c oxidase steps, do not

necessarily lead to changes in flux in glycolysis, the Krebs cy-cle or in mitochondrial respiration. It is possible that changein [E] results in no change in flux, as in a classic experimentinvolving yeast (100). It is possible that an observed change influx is the result of metabolic regulation and not hierarchicalregulation. Or, it could be the result of both.

Hans Westerhoff’s group developed hierarchical regula-tion analysis (15, 95, 127, 128) to address the problem of dis-tinguishing between metabolic and hierarchical regulation.The hierarchical regulation coefficient, ρh, which measuresthe contribution of [E], and the metabolic regulation coeffi-cient, ρm, which measures the contribution of mechanismsregulating a constant concentration of enzyme, to variation influx, are related as

1 = ρh + ρm .

At any enzyme-catalyzed step i, ρh is a function of therelative change in rate, ∂vi , divided by the relative change inenzyme concentration, ∂ei , times the ratio of change in ei tothe change in flux J. Since ∂ ln vi/∂ ln ei equals 1 (127), then

ρh = ∂ ln vi

∂ ln ei· d ln ei

d ln J= d ln ei

d ln J.

Similarly, at any step i, metabolic regulation results from achange in an enzyme-catalyzed rate divided by the change inconcentration of its substrate, product, or allosteric modulator,X, times the ratio of change in X to change in J, resulting in

ρm =∑

X

∂ ln vi

∂ ln Xi· ∂ ln X

∂ ln J.

One approach to obtaining ρh is to estimate the slope ofln Vmax versus ln J. The other value is obtained by subtrac-tion as ρm = 1 – ρh. This particular approach is illustratedin pioneering work by ter Kuile and Westerhoff using proto-zoa (127). Change in flux can be entirely due at certain stepsto hierarchical regulation (when ρh = 1) and, at other steps,due entirely to metabolic regulation (when ρh = 0). In cer-tain cases, both mechanisms contribute to the change in flux(when ρh > 0 but < 1). Hierarchical regulation analysis hasbeen applied to yeast metabolism and has been extended toconsider time-dependent changes in the relative contributionsof hierarchical and metabolic regulation (15, 128).

Approaches such as hierarchical regulation analysis havethe potential to allow comparative physiology to take the nextmajor step in studies of the mechanisms underlying tempo-ral variation in flux within animals as well as variation influx across species. In Panamanian orchid bees, for example,there is allometric variation in flux rates through pathwaysof carbohydrate oxidation in muscle during hovering (32).Plots of enzyme Vmax values against ln J allowed estimationof regulation coefficients. It was found that the interspecificvariation in J at all steps examined are likely due to metabolicregulation, except for the hexokinase reaction where ρh = 1.



The interspecific variation in flux at the hexokinase step inorchid bees is accounted for by interspecific variation in [E],even after taking phylogenetic relationships among speciesinto account (116).

Size and Temperature EffectsThat body size (measured as mass) and temperature haveprofound effects on rates of energy metabolism has beenwell known to biochemists and physiologists for decades(17, 65, 72, 73, 101). Among mammalian species, for exam-ple, body mass varies by several orders of magnitude; thisdrives the allometry in basal (144, 145), field (81) and maxi-mal metabolic rates (135, 136). On the other hand, the mech-anistic underpinnings of temperature effects on the rates ofchemical reactions date back to the work of Boltzmann andArrhenius in the 1800s. Consideration of both mass and tem-perature effects on metabolism has led to new approaches andinsights into theoretical modeling and empirical investiga-tions of ecological phenomena at the population, community,and ecosystem levels (13).

Body mass and energy metabolismWhy a kg of mouse displays a BMR about 10-fold greater thana kg of cow has captured the interest of physiologists for morethan half a century. Various theories to explain the allometricrelationship between metabolic rate and body mass have beenproposed since the pattern was first described (reviewed inreferences 1, 14, 17, and 101). This section is not intendedto discuss all these theories or the many controversies sur-rounding them (see, for example, references 1,115, and 141).Instead, the focus shall be on aspects of energy metabolismand its regulation that are relevant to the mechanistic under-standing of the size dependence of metabolic rates.

When metabolic rate, y, plotted against body mass, M, onlogarithmic axes, yields a slope, b < 1, the relationship is saidto be allometric. In contrast, isometric scaling yields b = 1.The equation describing this relationship can be expressed asa power function in the form

y = aMb,

where a is a normalization constant. Whether b, the allomet-ric exponent, is 3

4 (99) when all organisms, or all animals,all mammals, or only select taxa are considered is a matterof dispute. On the surface, such debate may appear trivial.However, quantitative, mechanistic theories have been pro-posed that predict a 3

4 exponent. In contrast, empirical datafrom various taxa yield exponents that deviate significantlyfrom 3

4 (114,115). Thus, the mechanistic assumptions under-lying proposed theories should be considered in relation tothe empirical data collected by comparative physiologists.

It has been proposed that the metabolic scaling exponentsclose to 0.75 result from physical limits to the rates of delivery

of materials to cells by branching or fractal-like distributionsystems (3-5,142). According to this view, as animals becomelarger, their delivery systems become less able to provide fuelsand/or O2 to cells and, therefore, energy metabolism in cows,elephants, and whales is more supply limited than in miceand shrews. There seems little doubt that capacities for de-livery should scale allometrically, but whether physiologicalrates of delivery actually limit metabolic rates and mecha-nistically explain the allometric scaling of metabolism underbasal, field, or maximal conditions, and whether b = 0.75 areempirical questions.

Animals consist of multiple cell types arranged as tissuesand organs. Hans Krebs (74) was perhaps the first to showthat metabolic rates of tissues from animals of differing masscould be measured in vitro and summed to explain whole-body metabolic rates and how they scale. A similar approachproved successful when applied to fish (87). Recently, organmetabolic rates in vivo, combined with information concern-ing the scaling of organ masses, allowed the estimation of b =0.76 in mammals (132). So, at least in the case of vertebrates,larger animals have proportionately less of certain internalorgans than smaller animals. In addition, the mass-specificmetabolic rates of these organs decline with increasing mass(Table 2).

This leads to the question, what determines the mass-specific metabolic rates of internal organs? Top-downmetabolic control analysis (8) of the respiration of mitochon-dria in vitro reveals that the Ci values for ATP turnover, sub-strate oxidation and proton leak change as the rate approachesstate 3, the maximum rate of ADP-stimulated respiration.When the mitochondria are actively engaged in ATP synthe-sis (as they would be in vivo), respiration is controlled mainlyby ATP turnover and secondarily by substrate oxidation andproton leak (10) (Fig. 2). Control analysis of respiration inisolated liver cells, for example, yields Ci = 0.29 for the pro-cesses that generate the proton electrochemical gradient, 0.49for the processes involved in ATP turnover, and 0.22 for protonleak (12). In the case of the heart, 85% of cardiac metabolicrate is due to the combined energetic costs of mechanicalwork and ion pumping (94) and control analysis of cardiacrespiration yields a Ci value of 0.9 for ATP hydrolysis (39,40). Although Ci values for the control of kidney respirationdo not appear to be available, the value for ATP hydrolysiswould be expected to be high as rates O2 consumption aredirectly related, in linear fashion, to rates of Na+ pumping(76). Clearly, the rates of energy expenditure (ATP hydrol-ysis) of internal organs play large roles in determining theirO2 consumption rates. In vivo, rates of energy expenditureof internal organs are regulated, according to physiologicalconditions, to suit the needs of the whole animal. Allometricscaling of BMR is observed in euthermic rodents; however,the allometry is lost and BMR scales isometrically (Fig. 5)(103) when rates of energy expenditure are actively down-regulated (61, 62) during hibernation. The role of a supplysystem that physiologically constrains BMR and, in doing so,determines how it scales is not apparent in mammals.



Table 2 Scaling of Organ Masses and Metabolic Rates in Mammals, Taken from Wang et al. (132)

OrganOrganmass =

Specific metabolicrate =

Organ mass × specificmetabolic rate =

Liver 0.033M0.87 2861M−0.27 94.4M0.60

Brain 0.011M0.76 1868M−0.14 20.5M0.62

Kidneys 0.007M0.85 2887M−0.08 20.2M0.77

Heart 0.006M0.98 3725M−0.12 22.4M0.86

Remainder 0.939M1.01 125M−0.17 117.4M0.84

M is body mass in kg; specific metabolic rates are in kJ kg−1 day−1. Organ masses and specific metabolicrates decline with increasing body mass.

Given the observed decline in organ mass-specificmetabolic rates with increasing body mass, it is relevant toconsider allometric scaling in the structures and functionalcapacities of the machinery involved in cellular bioenerget-ics. Vmax values for citrate synthase, the Krebs cycle enzymeoften used as an indicator of mitochondrial content (79), de-cline with increasing body mass in the locomotory musclesof mammals (47, 63) and pelagic fishes (23, 106). In var-ious mammalian organs, Vmax values for Na+-K+-ATPase(26) and Ca2+-ATPase (59), as well as mitochondrial con-tent (45, 46, 68, 77) decline with increasing mass. Thus, bio-chemical capacities for ATP hydrolysis as well as for theaerobic synthesis of ATP decline with increasing body mass,along with physiological rates of energy metabolism. In con-trast with the absence of data indicating that basal or restingmetabolic rates in animals are physiologically limited by thesupply of materials by a branching or fractal-like distribution

50

40

30

MR

(m

L O

2 ×

kg–1

× m

in–1

)

20

10

0

0.01 0.1

Body mass (kg)

1 10

Figure 5 Metabolic rate (V̇O2) as a function of body mass in ro-dents, denoted by various symbols (left to right: hazel mouse, edibledormouse, ground squirrel, European hamster, European hedgehog,and alpine marmot). Solid line shows that basal metabolic rate (BMR)scales allometrically during euthermia while dashed line shows how,during hibernation, metabolic rate scales isometrically. Euthermic andhibernating metabolic rates differ due to changes in the rates of energyexpenditure in internal organs. Adapted, with permission, from Suarezand Darveau (114); redrawn, with permission, from Singer et al. (103).

system, there is abundant evidence to support the idea that al-lometric scaling patterns in animals at rest are driven mainlyby rates of energy expenditure (34, 114, 115).

Animals are capable of increasing metabolic rates to var-ious degrees. Among mammals, maximal aerobic metabolicrates (V̇o2max values) are, on average, about 10-fold higherthan BMR (126) while in insects, the difference betweenmetabolic rates at rest and in flight can be as high as 100-fold(98). During the transition from rest to high-intensity aerobicexercise, animals undergo a dramatic physiological transfor-mation. Whereas resting values are determined mainly by themetabolic rates of internal organs (132), V̇o2max and valuesclose to it are determined mainly by mitochondrial respira-tion rates in exercising muscles (125) (Fig. 1). At the levelof muscle fibers, actomyosin ATPase is responsible for abouthalf of the control of mitochondrial respiration; the rest ofthe Ci values are shared by the adenine nucleotide translocaseand the electron transport chain (147). It is when whole-bodymetabolic rates approach or reach V̇o2max that supply lim-itations imposed by a branching or fractal-like distributionsystem might be expected. Control analyses of mammalianV̇o2max during exercise reveal that control is distributed amongthe multiple convective and diffusive steps in the pathway forO2 from the external environment to muscle mitochondria(36,70,130,131). Under these conditions, b = 0.87 (136) andsignificantly higher than 0.75, as would be predicted by mod-els based on supply limitation. In addition, the mitochondrialrespiration rate in muscles during exercise at V̇o2max is massindependent and lies within the narrow range of 3 to 5 mLO2/cm3 of mitochondria per minute (126). These results donot indicate that muscle mitochondria in larger mammals aremore limited by the supply of O2 or substrates than in smallermammals during exercise at V̇o2max. In honeybees, the tra-cheal system appears to possess substantial excess capacityfor O2 flux (60). A detailed interspecific study of orchid beesrevealed that the biomechanics of flight provides a sufficientexplanation for the allometry of V̇o2 during hovering. In theseinsects, the interspecific variation in wing-loading (mass perunit area) accounts for the interspecific variation in wing-beatfrequency, such that higher wing loading results in higher fre-quency. Wing-beat frequency, a major determinant of mus-cle power output during steady-state flight (90), determines



hovering V̇o2, so interspecific variation in frequency accountsfor the interspecific variation in V̇o2values (33). The biochem-ical machinery for aerobic ATP synthesis is mainly subject tometabolic regulation; hierarchical regulation (ρm = 1) is ob-served only at the hexokinase reaction when phylogeny istaken into account (116).

Temperature and energy metabolismThe thermal biology of animals, thermal adaptation, mech-anisms of thermogenesis and thermoregulation constitute alarge and well-developed area of scientific inquiry (66, 67).Awareness of the importance of a fundamental, mechanisticunderstanding of temperature effects on energy metabolismhas grown at least partly as a result of climate change effectson species distribution and abundance (91, 92). Gilooly et al.(54) express the combined effects of mass and temperature onthe mass-corrected rate of energy metabolism, I, in a singleequation as

I = io M3/4e−E/kT ,

where io is a normalization constant, M is mass, e−E/kT isthe Boltzmann factor wherein k is the Boltzmann constant,E is the activation energy, and T is the absolute temperature.This equation serves as the basis for the “metabolic theoryof ecology” (13). Using empirical data from the literatureand plotting ln I against 1/kT yields straight lines for vari-ous taxa, with negative slopes corresponding to organismalactivation energies, E, between 0.41 and 0.74 eV (mean =0.62 eV). Upon mass-correcting and temperature-correctingorganismal metabolic rates, it is observed that unicells, plantsand animals differ in their specific metabolic rates by only 20-fold, at most; the rest of the variation in nature is explainablein terms of the Boltzmann factor and mass-dependent 3

4 powerscaling. A point of controversy is whether the metabolic the-ory of ecology is mechanistic. For example, it is proposedthat because the lower metabolic rates of hibernators can beexplained in terms of their lower body temperatures, there isno need to invoke other mechanisms to explain the reductionin metabolic rate (54). Having previously dealt with the mech-anistic determinants of and mass effects on metabolic rates,brief consideration of temperature effects is appropriate.

Based on the foundations laid by Arrhenius and Boltz-mann, it is understood that at a given temperature, only asmall fraction of molecules in a large population possessessufficient energy (“activation energy”) to undergo an uncat-alyzed chemical reaction. Increased temperature causes anincrease in the fraction of molecules with sufficient activa-tion energy; this causes the increase in the reaction rate. Theutility of direct application of the Arrhenius/Boltzmann ap-proach to rates of energy metabolism in organisms is limitedby at least two factors. The first is that biochemical reactionsare enzyme-catalyzed; metabolic enzymes typically operate atlow, subsaturating substrate concentrations, so in vivo rates ofenzyme catalysis are substrate limited. The enzymes that cat-

alyze metabolic reactions undergo conformational changes,bind substrates, and release products by reversible formationand breakage of weak bonds. Weak bonds and, therefore,higher order protein structure as well as ligand-binding affini-ties are perturbed by changes in temperature. The Michaelisconstant, km, is temperature dependent and, among metabolicenzymes, typically increases with temperature (65 and 66).An important mechanism in thermal adaptation involves theevolution of differential sensitivities to temperature; that is, km

values of orthologous enzymes for their substrates are foundto be similar when measured at their respective biologicallyrelevant body temperatures (65 and 66). The second is that“energy metabolism” concerns ATP turnover: the hydrolysisof ATP by energy-utilizing processes in cells and its con-comitant resynthesis by pathways in bioenergetics. Thus, amechanistic explanation for temperature effects on rates ofenergy metabolism must provide a mechanistic explanationfor its effects on rates of enzyme-catalyzed processes involv-ing ATP hydrolysis as well as its effects on enzyme-catalyzedrates of ATP synthesis (24). Because ATP hydrolysis and syn-thesis are kinetically and stoichiometrically coupled (2), thequestion of temperature effects on metabolism concerns itseffects on metabolic regulation and goes well beyond the ide-alized behavior of molecules in a population, as described bythe statistical mechanics of the 1800s. The mechanisms un-derlying temperature effects on energy metabolism continueto be the subject of research in comparative and ecologicalphysiology. Because flux is a system property, temperatureeffects on flux must be studied in terms of its effects onsystem properties. Therefore, a promising approach involvesthe application of metabolic control analysis to this problem(16, 19).

Energy metabolism in the deep oceanMost of the Earth’s surface is covered by ocean and mostof it is deep (35). Given the great diversity and ancient lin-eages of marine animal species, it is not surprising that manypossess mechanisms and pathways for ATP production thatdiffer markedly from those well studied in vertebrate animals.For example, certain species of sea slugs that feed on algaeincorporate chloroplasts into their own cells and photosyn-thesize (96,97). Deep-dwelling species such as hydrothermalvent tubeworms engage in chemoautotrophy with the aid ofsymbiotic bacteria, taking up hydrogen sulfide from the en-vironment and oxidizing it as a source of energy for CO2

fixation (53). Since many marine invertebrate species harborbacterial symbionts and engage in chemoautotrophy (22), it isonly from a nonbiological, excessively anthropocentric per-spective that such processes would be considered unusual,given that most of the biosphere consists of deep ocean.

In the deep sea, high hydrostatic pressures perturb bio-chemical processes such as ligand binding, protein folding,conformational changes, polymerization and depolymeriza-tion, affecting enzyme-catalyzed rates, and biochemical equi-libria in bioenergetic (and other) pathways. The perturbation



is thought to result from effects of pressure on the volumechanges accompanying these processes (66). The thermody-namics of these processes is usually considered in terms ofthe Gibbs free energy change, �G,

�G = �H − T �S,

where �H is the enthalpy change, T is temperature, and �Sis the change in entropy. This expression ignores a third termthat, at high pressure, becomes significant. The more completeequation that applies to deep-sea environments that comprisemost of the biosphere is

�G = �H − T �S + P�V,

where P is pressure and �V is the change in volume associ-ated with the biochemical process (104). Pressure effects onbiochemical processes are thought to have led to the evolutionof reduced volume changes associated with ligand binding,conformational changes, polymerization, and depolymeriza-tion in deep-sea organisms. Reduction of volume changeswould result in minimization of the perturbing effects of highhydrostatic pressure on protein structure, enzyme catalysis,and regulation (66, 104).

The diversity of life is the outcome of evolutionary pro-cesses. Animal species have evolved to exploit innumerableniches, evolving body masses spanning several orders of mag-nitude as well as extremely diverse lifestyles and environ-ments. Although biological systems certainly obey physicallaws, evolutionary processes have produced emergent out-comes, that is, patterns and processes that could not havebeen predicted simply on the basis of physical laws. It isbecause of evolution and adaptation that many taxa displaymetabolic scaling exponents that deviate significantly (115)from the b value of 0.75 predicted by supply-limitation models(3, 141). Energy expenditure plays a significant role in deter-mining whole-body metabolic rates and the manner in whichthese scale under basal, field, and maximal exercise conditions(114,115). As deep ocean comprises most of the biosphere, aninteresting and important issue concerns the factors that deter-mine the metabolic rates of deep-sea animals (21). Althoughmetabolism scales with respect to body mass in allometricfashion and changes in response to temperature as expected,considerable research on pelagic species reveals that mass-specific metabolic rates decline with increasing depth of dis-tribution in the water column. Associated with these lowermetabolic rates are reduced locomotory activity and lowerenzyme Vmax values (21). Pelagic, deep-sea animals live in aperpetually dark environment. Therefore, it has been hypoth-esized that relaxation of the selective forces associated withvisual predation (e.g. pursuit of prey and predator avoidance)explains the decline in enzyme activities and metabolic rateswith increasing habitat depth. For example, among cephalo-pod mollusks, habitat depth accounts for more of the inter-

specific variation in metabolic rates than body mass (102).Thus,

“a deep-living vampire squid. . .weighing just 1·g has thesame mass-specific metabolic rate as an elephant. . .while anepipelagic squid weighing 10·kg has the same mass-specificmetabolic rate as a mouse” (102).

Decreases in metabolic rates with increasing depth arealso seen in pelagic crustaceans and fishes (21). These dataraise the intriguing possibility that the “metabolic theory ofecology” (13) does not apply to most of the biosphere.

Concluding RemarksEnergy metabolism is a many-splendored thing. Much mech-anistic, experimental biology as well as analyses of patternsand processes have yielded insights into the nature of andmechanisms underlying metabolic variation among animals.The unity and diversity observed in energy metabolism amonganimals exemplifies the tension between yin and yang famil-iar to practitioners of comparative biochemistry and physiol-ogy (67, 105). It can be reasonably argued that knowledge ofthe metabolic similarities and differences among animals andtheir underlying causes may contribute to the understandingof metabolic diseases afflicting humans (88, 89) as well asresponses and adaptation to climate change (91, 92).

AcknowledgementsThe author is grateful to C. D. Moyes and to an anonymousreviewer for critical comments. His research has been fundedby the US National Science Foundation (IOB 0517694).

References1. Agutter PS, Wheatley DN. Metabolic scaling: Consensus or contro-

versy? Theor Biol Med Model 2004: 1-13, 2004.2. Atkinson DE. Cellular Energy Metabolism and Its Regulation. New

York: Academic Press, 1977.3. Banavar JR, Damuth J, Maritan A, Rinaldo A. Supply-demand balance

and metabolic scaling. Proc Natl Acad Sci U S A 99: 10506-10509,2002.

4. Banavar JR, Maritan A, Rinaldo A. Size and form in efficient trans-portation networks. Nature 399: 130-131, 1999.

5. Banavar JR, Moses ME, Brown JH, Damuth J, Rinaldo A, Sibly RM,Maritan A. A general basis for quarter-power scaling in animals. ProcNatl Acad Sci U S A 107: 15816-15820, 2010.

6. Beenakkers AMT, Van Der Horst DJ, Van Marrewijk WJA. Metabolismduring locust flight. Comp Biochem Physiol 69B: 315-321, 1981.

7. Bookelman H, Trubels JMF, Sengers RCA, Janssen AJM, VeerkampJH, Stadhouders AM. Reconstitution of malate-aspartate and alpha-glycerophosphate shuttle activity in rat skeletal muscle mitochondria.Int J Biochem 10: 411-414, 1979.

8. Brand MD. Top down metabolic control analysis. J Theor Biol 182:351-360, 1996.

9. Brand MD. The efficiency and plasticity of mitochondrial energy trans-duction. Biochem Soc Trans 33: 897-904, 2005.

10. Brand MD, Chien L-F, Rolfe DFS. Regulation of oxidative phospho-rylation. Biochem Soc Trans 21: 757-762, 1993.

11. Brooks GA. Mammalian fuel utilization during sustained exercise.Comp Biochem Physiol 120B: 89-107, 1998.



12. Brown GC, Lakin-Thomas PL, Brand MD. Control of respiration andoxidative phosphorylation in isolated liver cells. Eur J Biochem 192:355-362, 1990.

13. Brown JH. Toward a metabolic theory of ecology. Ecology 85: 1771-1789, 2004.

14. Brown JH, West GB, Enquist BJ. Scaling in biology: Patterns, pro-cesses, causes and consequences. In: Brown JH, West GB, editors.Scaling in Biology. New York: Oxford University Press, 2000, pp. 1-21.

15. Bruggeman FJ, de Haan J, Hardin H, Bouwman J, Rossell S, van EunenK, Bakker BM, Westerhoff HV. Time-dependent hierarchical regulationanalysis: Deciphering cellular adaptation. IEE Proc Syst Biol 153: 318-322, 2006.

16. Buttgereit F, Brand MD. A hierarchy of ATP-consuming processes inmammalian cells. Biochem J 312: 163-167, 1995.

17. Calder WA. Size, Function and Life History. Cambridge, Mas-sachusetts: Harvard University Press, 1984.

18. Candy D, Becker A, Wegener G. Coordination and integration ofmetabolism in insect flight. Comp Biochem Physiol 117B: 497-512,1997.

19. Chamberlin ME. Top-down control analysis of the effect of temperatureon ectotherm oxidative phosphorylation. Am J Physiol 287: R794-R800,2004.

20. Chantler PD. Caged ATP set free in muscle. Nature 300: 682-683, 1982.21. Childress J. Are there physiological and biochemical adaptations of

metabolism in deep-sea animals? TREE 10: 30-36, 1995.22. Childress JJ, Girguis PR. The metabolic demands of endosymbiotic

chemoautotrophic metabolism on host physiological capacities. J ExpBiol 214, 2011.

23. Childress JJ, Somero GN. Metabolic scaling: A new perspective basedon scaling of glycolytic enzyme activities. Am Zool 30: 161-173, 1990.

24. Clarke A, Fraser KPP. Why does metabolism scale with temperature?Func Ecol 18: 243-241, 2004.

25. Connett R. In vivo glycolytic equilibria in dog gracilis muscle. J BiolChem 260: 3314-3320, 1985.

26. Couture P, Hulbert AJ. Relationship between body mass, tissuemetabolic rate, and sodium pump activity in mammalian liver and kid-ney. Am J Physiol 268: R641-R650, 1995.

27. Crabtree B, Newsholme EA. The activities of lipases and carnitinepalmitoyltransferase in muscles from vertebrates and invertebrates.Biochem J 130: 697-705, 1972a.

28. Crabtree B, Newsholme EA. The activities of phosphorylase, hexok-inase, phosphofructokinase, lactate dehydrogenase and the glycerol3-phosphate dehydrogenases in muscles from vertebrates and inverte-brates. Biochem J 126: 49-58, 1972b.

29. Crabtree B, Newsholme EA. Comparative aspects of fuel utilizationand metabolism by muscle. In: Usherwood PNR, editor. Insect Muscle.New York: Academic Press, 1975, pp. 405-491.

30. Crawford DL, Oleksiak MF. The biological importance of measuringindividual variation. J Exp Biol 210: 1613-1621, 2007.

31. Danforth W, Lyon Jr. J. Glycogenolysis during tetanic contraction ofisolated mouse muscles in the presence and absence of phosphorylaseA. J Biol Chem 239: 4047-4050, 1964.

32. Darveau C-A, Hochachka PW, Roubik DW, Suarez RK. Allometricscaling of flight energetics in orchid bees: Evolution of flux capacitiesand flux rates. J Exp Biol 208: 3593-3602, 2005.

33. Darveau C-A, Hochachka PW, Welch Jr. KC, Roubik DW, Suarez RK.Allometric scaling of flight energetics in Panamanian orchid bees: Acomparative phylogenetic approach. J Exp Biol 208: 3581-3591, 2005.

34. Darveau C-A, Suarez RK, Andrews RD, Hochachka PW. Allometriccascade as a unifying principle of body mass effects on metabolism.Nature 417: 166-170, 2002.

35. Denny M. How the Ocean Works. An Introduction to Oceanography.New Jersey: Princeton University Press, 2008.

36. di Prampero PE. Metabolic and circulatory limitations to VO2max atthe whole animal level. J Exp Biol 115: 319-331, 1985.

37. di Prampero PE. Factors limiting maximal performance in humans. EurJ Appl Physiol 90: 420-429, 2003.

38. Diamond J. Evolutionary design of intestinal nutrient absorption:Enough but not too much. NIPS 6: 92-96, 1991.

39. Diolez P, Raffard G, Simon C, Leducq N, Dos Santos P, Canioni P.Mitochondria do not control heart bioenergetics. Mol Biol Rep 29:193-196, 2002.

40. Diolez P, Simon C, Leducq N, Canioni P, Dos Santos P. Top downanalysis of heart bioenergetics. In: Hofmeyr JHS, Rohwer M, SnoepJL, editors. BTK2000: Animating the Cellular Map. Stellenbosch: Stel-lenbosch University Press, 2000, pp. 101-106.

41. Drazen JC, Seibel BA. Depth-related trends in metabolism of benthicand benthopelagic deep-sea fishes. Limnol Oceanog 52: 2306-2316,2007.

42. Eaton S, Fukumoto K, Duran NP, Pierro A, Spitz L, Quant PA, BartlettK. Carnitine palmitoyl transferase 1 and the control of myocardial beta-oxidation flux. Biochem Soc Trans 29: 245-249, 2001.

43. Ellington WR. Phosphocreatine represents a thermodynamic and func-tional improvement over other muscle phosphagens. J Exp Biol 143:177-194, 1989.

44. Ellington WR. Evolution and physiological roles of phosphagen sys-tems. Ann Rev Physiol 63: 289-325, 2001.

45. Else PL, Hulbert AJ. An allometric comparison of the mitochondria ofmammalian and reptilian tissues: The implications for the evolution ofendothermy. J Comp Physiol B 156: 3-11, 1985a.

46. Else PL, Hulbert AJ. Mammals: An allometric study of metabolism attissue and mitochondrial level. Am J Physiol 248: R415-R421, 1985b.

47. Emmett B, Hochachka PW. Scaling of oxidative and glycolytic en-zymes in mammals. Respir Physiol 45: 261-272, 1981.

48. Feder ME, Walser JC. The biological limitations of transcriptomics inelucidating stress and stress responses. J Evol Biol 18: 901-910, 2005.

49. Fell D. Understanding the Control of Metabolism. London & Miami:Portland Press, 1997.

50. Ferrannini E. The theoretical bases of indirect calorimetry: A review.Metabolism 37: 287-301, 1988.

51. Fields J, Baldwin J, Hochachka P. On the role of octopine dehydroge-nase in cephalopod mantle muscle metabolism. Can J Zool 54: 871-878,1976.

52. Fields JHA, Eng AK, Ramsden WD, Hochachka PW, Weinstein B.Alanopine and strombine are novel imino acids produced by a dehy-drogenase found in the adductor muscle of the oyster, Crassostrea gigas.Arch Biochem Biophys 201: 110-114, 1980.

53. Freytag JK, Girguis PR, Bergquist DC, Andras JP, Childress JJ, FisherCR. A paradox resolved: Sulfide acquisition by roots of seep tubewormssustains net chemoautotrophy. Proc Natl Acad Sci U S A 98: 13408-13413, 2001.

54. Gillooly JF, Brown JH, West GB, Savage VM, Charnov EL. Effectsof size and temperature on metabolic rate. Science 293: 2248-2251,2001.

55. Gracey AY. Interpreting physiological responses to environmentalchange through gene expression profiling. J Exp Biol 209: 1584-1592,2007.

56. Guppy M, Hochachka PW. Controlling the highest lactate dehydroge-nase activity known in nature. Am J Physiol 234: R136-R140, 1978.

57. Guppy M, Hulbert WC, Hochachka PW. Metabolic sources of heat andpower in tuna muscles. II. Enzyme and metabolite profiles. J Exp Biol82: 303-320, 1979.

58. Haldane JBS. Enzymes. London: Longmans, Green and Co., 1930.59. Hamilton N, Ianuzzo CD. Constractile and calcium regulating capaci-

ties of myocardia of different sized mammals scale with resting heartrate. Mol Cell Biochem 106: 133-141, 1991.

60. Harrison JF, Camazine S, Marden JH, Kirkton SD, Rozo A, YangX. Mite not make it home: Tracheal mites reduce the safety marginfor oxygen delivery of flying honeybees. J Exp Biol 204: 805-814,2001.

61. Heldmaier G, Elvert R. How to enter torpor: Thermodynamic and phys-iological mechanisms of metabolic depression. In: Barnes BM, CareyHV, editors. Life in the Cold: Evolution, Mechanisms, Adaptation andApplication. 12th International Hibernation Symposium. Fairbanks:University of Alaska, 2004, pp. 185-198.

62. Heldmaier G, Ruf T. Body temperature and metabolic rate during natu-ral hypothermia in endotherms. J Comp Physiol 162B: 696-706, 1992.

63. Hochachka PW, Emmett B, Suarez RK. Limits and constraints in thescaling of oxidative and glycolytic enzymes in homeotherms. Can JZool 66: 1128-1138, 1988.

64. Hochachka PW, Mommsen TP. Protons and anaerobiosis. Science 219:1391-1397, 1983.

65. Hochachka PW, Somero GN. Strategies of Biochemical Adaptation.Philadelphia, London, Toronto: W.B. Saunders Co., 1973.

66. Hochachka PW, Somero GN. Biochemical Adaptation. Princeton, NewJersey: Princeton, 1984.

67. Hochachka PW, Somero GN. Biochemical Adaptation. Mechanism andProcess in Phyisological Evolution. Oxford: Oxford University Press,2002.

68. Hoppeler H, Lindstedt SL, Claassen H, Taylor CR, Mathieu O, WeibelER. Scaling mitochondrial volume in heart to body mass. Respir Physiol55: 131-137, 1984.

69. Johnston IA, Calvo J, Guderley H, Fernandez D, Palmer L. Latitu-dinal variation in the abundance and oxidative capacities of musclemitochondria in perciform fishes. J Exp Biol 201: 1-12, 1998.

70. Jones JH. Optimization of the mammalian respiratory system: Sym-morphosis versus single species adaptation. Comp Biochem Physiol120B: 125-138, 1998.

71. Kashiwaya Y, Sato K, Tsuchiya N, Thomas S, Fell DA, Veech RL,Passonneau JV. Control of glucose utilization in working perfused ratheart. J Biol Chem 269: 25502-25514, 1994.

72. Kleiber M. Body size and metabolism. Hilgardia 6: 315-353, 1932.73. Kleiber M. The Fire of Life. New York: John Wiley & Sons, 1961.74. Krebs HA. Body size and tissue respiration. Biochim Biophys Acta 4:

249-269, 1950.



75. Lambeth MJ, Kushmerick MJ, Marcinek DJ, Conley KE. Basalglycogenolysis in mouse skeletal muscle: In vitro model predicts invivo fluxes. Mol Biol Rep 29: 135-139, 2002.

76. Mandel LJ, Balaban RS. Stoichiometry and coupling of active transportto oxidative metabolism in epitherlial tissues. Am J Physiol 240: F357-F371, 1981.

77. Mathieu O, Krauer R, Hoppeler H, Gehr P, Lindstedt SL, Alexander R,Taylor CR, Weibel ER. Design of the mammalian respiratory system.VII. Scaling mitochondrial volume in skeletal muscle to body mass.Respir Physiol 44: 113-128, 1981.

78. Matthews PM, Foxall D, Shen L, Mansour TE. Nuclear magnetic res-onance studies of carbohydrate metabolism and substrate cycling inFasciola hepatica. Mol Pharmacol 29: 65-73, 1986.

79. Moyes CD. Controlling muscle mitochondrial content. J Exp Biol 206:4385-4391, 2003.

80. Moyes CD, Suarez RK, Hochachka PW, Ballantyne JS. A comparisonof fuel preferences of mitochondria from vertebrates and invertebrates.Can J Zool 68: 1337-1349, 1990.

81. Nagy KA. Field metabolic rate and body size. J Exp Biol 208: 1621-1625, 2005.

82. Newman JR, Ghaemmaghami S, Ihmels J, Breslow DK, Noble M,DeRisi JL, Weissman JS. Single cell proteomic analysis of S. cere-visiae reveals the architecture of biological noise. Nature 441: 840-846,2006.

83. Newsholme EA, Crabtree B. Maximum catalytic activity of somekey enzymes in provision of physiologically useful information aboutmetabolic fluxes. J Exp Zool 239: 159-167, 1986.

84. Newsholme EA, Crabtree B, Zammit VA. Use of enzyme activities asindices of maximum rates of fuel utilization. Ciba Found Symp 73:245-258, 1980.

85. O’Brien DM. Fuel use in flight and its dependence on nectar feeding inthe hawkmoth Amphion floridensis. J Exp Biol 202: 441-451, 1999.

86. O’Brien DM, Suarez RK. Fuel use in hawkmoth (Amphion floridensis)flight muscle: Enzyme activities and flux rates. J Exp Zool 290: 108-114, 2001.

87. Oikawa S, Itazawa Y. Relationship between summated tissue respira-tion and body size in a marine teleost, the porgy Pagrus major. FisheriesSci 69: 687-694, 2003.

88. Pedersen BK. Muscles and their myokines. J Exp Biol 214: 337-346,2011.

89. Pedersen BK, Fischer CP. Beneficial health effects of exercise - the roleof IL-6 as a myokine. Trends Pharmacol Sci 28: 152-156, 2007.

90. Pennycuick CJ, Rezende MA. The specific power output of aerobicmuscle, related to the power density of mitochondria. J Exp Biol 108:377-392, 1984.

91. Portner HO, Farrell AP. Physiology and climate change. Science 322:690-692, 2008.

92. Portner HO, Knust R. Climate change affects marine fishes through theoxygen limitation of thermal tolerance. Science 315: 95-97, 2007.

93. Robinson J, Inman L, Sumegi B, Srere P. Further characterization of theKrebs tricarboxylic acid cycle metabolon. J Biol Chem 262: 1786-1790,1987.

94. Rolfe DFS, Brown GC. Cellular energy utilization and molecular originof standard metabolic rate in mammals. Physiol Revs 77: 731-758,1997.

95. Rossell S, van der Weijden CC, Lindenbergh A, van Tuijl A, FranckeC, Bakker BM, Westerhoff HV. Unraveling the complexity of fluxregulation: A new method demonstrated for nutrient starvation in Sac-charomyces cerevisiae. Proc Natl Acad Sci U S A 103: 2166-2171,2006.

96. Rumpho ME, Summer EJ, Manhart JR. Solar-powered sea slugs. Mol-lusc/algal chloroplast symbiosis. Plant Physiol 123: 29-38, 2000.

97. Rumpho ME, Worful JM, Lee J, Kannan K, Tyler MS, Bhattacharya D,Moustafa A, Manhart JR. Horizontal gene transfer of the algal nucleargene psbO to the photosynthetic sea slug Elysia chlorotica. Proc NatlAcad Sci U S A 105: 17867-17871, 2008.

98. Sacktor B. Biochemical adaptations for flight in the insect. BiochemSoc Symp 41: 111-131, 1976.

99. Savage VM, Gillooly JF, Woodruff WH, West GB, Allen AP, EnquistBJ, Brown JH. The predominance of quarter-power scaling in biology.Func Ecol 18: 257-282, 2004.

100. Schaaff I, Heinisch J, Zimmermann FK. Overproduction of glycolyticenzymes in yeast. Yeast 5: 285-290, 1989.

101. Schmidt-Nielsen K. Scaling. Why is Animal Size So Important? Cam-bridge: Cambridge University Press, 1984.

102. Seibel BA. On the depth and scale of metabolic rate variation: Scal-ing of oxygen consumption rates and enzymatic activity in the ClassCephalopoda (Mollusca). J Exp Biol 210: 1-11, 2007.

103. Singer D, Schunck O, Bach F, Kuhn H-J. Size effects on metabolicrate in cell, tissue, and body calorimetry. Thermochimica Acta 251:227-240, 1995.

104. Somero GN. Life at low volume change: Hydrostatic pressure as aselective factor in the aquatic environment. Am Zool 30: 123-135, 1990.

105. Somero GN. Unity in diversity: A perspective on the methods, con-tributions, and future of comparative physiology. Ann Rev Physiol 62:927-937, 2000.

106. Somero GN, Childress JJ. Scaling of ATP-supplying enzymes, myofib-rillar proteins and buffering capacity in fish muscle: Relationship tolocomotory habit. J Exp Biol 149: 319-333, 1990.

107. Srere PA. The infrastructure of the mitochondrial matrix. TIBS 5: 120-121, 1980.

108. Srere PA. Organization of proteins within the mitochondrion. In: WelchGR, editor. Organized Multienzyme Systems. Catalytic Properties. NewYork, London: Academic Press, 1985, pp. 1-61.

109. Staples JF, Suarez RK. Honeybee flight muscle phosphoglucose iso-merase: Matching enzyme capacities to flux requirements at a near-equilibrium reaction. J Exp Biol 200: 1247-1254, 1997.

110. Suarez RK. Upper limits to mass-specific metabolic rates. Ann RevPhysiol 58: 583-605, 1996.

111. Suarez RK. Shaken and stirred: Muscle structure and metabolism. JExp Biol 206: 2021-2029, 2003.

112. Suarez RK. The biology of energy expenditure. J Exp Biol 214: 163-346, 2011.

113. Suarez RK, Brown GS, Hochachka PW. Metabolic sources of energyfor hummingbird flight. Am J Physiol 251: R537-R542, 1986.

114. Suarez RK, Darveau C-A. Multi-level regulation and metabolic scaling.J Exp Biol 208: 1627-1634, 2005.

115. Suarez RK, Darveau C-A, Childress JJ. Metabolic scaling: Amany-splendoured thing. Comp Biochem Physiol 139B: 531-541,2004.

116. Suarez RK, Darveau C-A, Hochachka PW. Roles of hierarchical andmetabolic regulation in the allometric scaling of metabolism in Pana-manian orchid bees. J Exp Biol 208: 3603-3607, 2005.

117. Suarez RK, Darveau C-A, Welch Jr. KC, O’Brien DM, Roubik DW,Hochachka PW. Energy metabolism in orchid bee flight muscles: Car-bohydrate fuels all. J Exp Biol 208: 3573-3579, 2005.

118. Suarez RK, Herrera M. LG, Welch KC. The sugar oxidation cascade:Aerial refueling in hummingbirds and nectar bats. J Exp Biol 214:172-178, 2011.

119. Suarez RK, Lighton JRB, Brown GS, Mathieu-Costello O. Mitochon-drial respiration in hummingbird flight muscles. Proc Natl Acad SciU S A 88: 4870-4873, 1991.

120. Suarez RK, Lighton JRB, Moyes CD, Brown GS, Gass CL, HochachkaPW. Fuel selection in rufous hummingbirds: Ecological implicationsof metabolic biochemistry. Proc Natl Acad Sci U S A 87: 9207-9210,1990.

121. Suarez RK Moyes CD. Metabolism in the age of ‘omes’. J Exp Biol (InPress), 2012.

122. Suarez RK, Staples JF, Lighton JRB, West TG. Relatioships betweenenzymatic flux capacities and metabolic flux rates in muscles: Nonequi-librium reactions in muscle glycolysis. Proc Natl Acad Sci U S A 94:7065-7069, 1997.

123. Suarez RK, Welch Jr. KC, Hanna SK, Herrera LG. Flight muscle en-zymes and metabolic flux rates during hovering flight of the nectarbat, Glossophaga soricina: Further evidence of convergence with hum-mingbirds. Comp Biochem Physiol 153A: 136-140, 2009.

124. Sumegi B, Sherry A, Malloy C. Channeling of TCA cycle intermediatesin cultured Saccharomyces cerevisiae. Biochemistry 29: 9106-9110,1990.

125. Taylor CR. Structural and functional limits to oxidative metabolism:Insights from scaling. Ann Rev Physiol 49: 135-146, 1987.

126. Taylor CR, Weibel ER, Karas RH, Hoppeler H. Matching structuresand functions in the respiratory system. Allometric and adaptive varia-tions in energy demand. In: Wood SC, editor. Comparative PulmonaryPhysiology. Current Concepts. New York, Basel: Marcel Dekker, 1989,pp. 27-65.

127. ter Kuile BH, Westerhoff HV. Transcriptome meets metabolome: Hi-erarchical and metabolic regulation of the glycolytic pathway. FEBSLetts 500: 169-171, 2001.

128. van Eunen K, Bouwman J, Lindenbergh A, Westerhoff HV, Bakker BM.Time-dependent regulation analysis dissects shifts between metabolicand gene-expression regulation during nitrogen starvation in baker’syeast. FEBS J 276: 5521-5536, 2009.

129. Veech RL, Raijman L, Dalziel K, Krebs HA. Disequilibrium in thetriosephosphate isomerase system in rat liver. Biochem J 115: 837-842,1969.

130. Wagner PD. Algebraic analysis of the determinants of VO2max. RespirPhysiol 93: 221-237, 1993.

131. Wagner PD. A theoretical analysis of factors determining VO2max atsea level and altitude. Respir Physiol 106: 329-343, 1996.

132. Wang Z, O’Connor TP, Heshka S, Heymsfield SB. The reconstruc-tion of Kleiber’s law at the organ-tissue level. J Nutr 131: 2967-2970,2001.

133. Weber J-M, Haman F. Oxidative fuel selection: Adjusting mix and fluxto stay alive. Int Congr Ser 1275: 22-31, 2004.

134. Weibel ER. The pitfalls of power laws. Nature 417: 131-132, 2002.



135. Weibel ER, Bacigalupe LD, Schmitt B, Hoppeler H. Allometric scalingof maximal metabolic rate in mammals: Muscle aerobic capacity asdeterminant factor. Respir Physiol Neurobiol 140: 115-132, 2004.

136. Weibel ER, Hoppeler H. Exercise-induced maximal metabolic ratescales with muscle aerobic capacity. J Exp Biol 208: 1635-1644, 2005.

137. Welch GR, Clegg JS. The organization of cell metabolism. In: NATOAdvanced Science Institutes Series. New York, London: Plenum Press,1986, p. 389.

138. Welch KC, Altschuler DL, Suarez RK. Oxygen consumption rates inhovering hummingbirds reflect substrate-dependent differences in P/Oratios: Carbohydrate as a ‘premium fuel’. J Exp Biol 210: 2146-2153,2007.

139. Welch KC, Bakken BH, Martinez del Rio C, Suarez RK. Hummingbirdsfuel hovering flight with newly-ingested sugar. Physiol Biochem Zool79: 1082-1087, 2006.

140. Welch KC, Herrera LG, Suarez RK. Dietary sugar as a direct fuel forflight in the nectarivorous bat, Glossophaga soricina. J Exp Biol 211:310-316, 2008.

141. West GB, Brown JH. The origin of allometric scaling laws in biologyfrom genomes to ecosystems: Towards a quantitative unifying theory ofbiological structure and organization J Exp Biol 208: 1575-1592, 2005.

142. West GB, Brown JH, Enquist BJ. A general model for the origin ofallometric scaling laws in biology. Science 276: 122-126, 1997.

143. Westerhoff H. Organization in the cell soup. Nature 318: 106, 1985.144. White CR, Seymour RS. Mammalian basal metabolic rate is propor-

tional to body mass 2/3. Proc Natl Acad Sci U S A 100: 4046-4049,2003.

145. White CR, Seymour RS. Allometric scaling of mammalian metabolism.J Exp Biol 208: 1611-1619, 2005.

146. Wilson JE. Isozymes of mammalian hexokinase: Structure, subcellu-lar localization and metabolic function. J Exp Biol 206: 2049-2057,2003.

147. Wisniewski E, Gellerich FN, Kunz WS. Distribution of flux controlamong the enzymes of mitochondrial oxidative phosphorylation incalcium-activated saponin-skinned rat musculus soleus fibers. Eur JBiochem 230: 549-554, 1995.

148. Wojtas K, Slepecky N, von Kalm L, Sullivan D. Flight muscle functionin Drosophila requires colocalization of glycolytic enzymes. Mol BiolCell 8: 1665-1675, 1997.

149. Yacoe ME, Cummings JW, Myers P, Creighton GK. Muscle enzymeprofile, diet and flight in South American bats. Am J Physiol 242:R189-R194, 1982.


energy and metabolism - usp€¦ · of enzymes (e.g. in relation to temperature, hydrostatic...

Documents