How do we retain emphasis on function?

Systems Biology Systems biology studies biological systems by systematically perturbing them (biologically, genetically, or chemically); monitoring the gene, protein, and informational pathway responses; integrating these data; and ultimately, formulating mathematical models that describe the structure of the system and its response to individual perturbations. Ideker, T., T. Galitski, and L. Hood. 2001. A new approach to decoding life: systems biology. Annu. Rev. Genomics Hum. Genet. 2: 343-372. How do we retain emphasis on function? Joanne K. Kelleher, jkk@mit.edu

The Transcriptome DNA -> RNA Homeostasis not possible. Not satisfactory to Physiologist. RNA -> Protein The Proteome Glucose Pyruvate Cholesterol Fatty acids Pyruvate Physiology or Metabolism Succinate Glutamine Acetyl CoA Malate Citrate α-ketoglutarate Glutamate Glutamate Glutamine Citrate Acetyl CoA Dark days for the metabolites

Glucose Pyruvate Pyruvate Cholesterol Fatty acids Acetyl CoA Acetyl CoA or Physiology Succinate Malate Citrate α-ketoglutarate Glutamate Glutamate Citrate Metabolism Glutamine Glutamine RNA -> Protein The Proteome The Transcriptome DNA -> RNA

Metabolites and metabolism have not held a prominent place in Biomedical research in the past two decades. Two factors may drive rebirth of Metabolism in Human Physiology 1. Role of metabolites in homeostasis at gene level of control 2. Complexities of mammalian physiology revealed by knockout models

Orphan Nuclear Receptors: Shifting Endocrinology into Reverse Kliewer, et al., 1999. Science 284: 757. New Old Nuclear receptor

Metabolites directly affect gene expression in mammalian cells =

Glucose Pyruvate Pyruvate Cholesterol Fatty acids Acetyl CoA Acetyl CoA or Physiology Succinate Malate Citrate α-ketoglutarate Glutamate Glutamate Citrate Metabolism Glutamine Glutamine RNA -> Protein The Proteome The Transcriptome DNA -> RNA

Food Brain Endogenous glucose production Plasma Glucose Other tissues Liver cell Plasma Glucose meal sleep Time

Food Brain Endogenous glucose production Plasma Glucose Other tissues PEP OAA +ATP -- -- Glucose (G) PEPCK - signaling GG) NucleusG) I Glucose Insulin PEPCK high high low low low high G I C C C C C Lactate C Lactate Liver cell I G

Food Brain Endogenous glucose production Plasma Glucose Other tissues She, P., M. Shiota, K. D. Shelton, R. Chalkley, C. Postic, and M. A. Magnuson. 2000. Phosphoenolpyruvate carboxykinase is necessary for the integration of hepatic energy metabolism. Mol. Cell Biol. 20: 6508-6517. Abstract: We used an allelogenic Cre/loxP gene targeting strategy in mice to determine the role of cytosolic phosphoenolpyruvate carboxykinase (PEPCK) in hepatic energy metabolism. Mice that lack this enzyme die within 3 days of birth, while mice with at least a 90% global reduction of PEPCK, or a liver-specific knockout of PEPCK, are viable. Surprisingly, in both cases these animals remain euglycemic after a 24-h fast. However, mice without hepatic PEPCK develop hepatic steatosis after fasting despite up-regulation of a variety of genes encoding free fatty acid-oxidizing enzymes. Also, marked alterations in the expression of hepatic genes involved in energy metabolism occur in the absence of any changes in plasma hormone concentrations. Given that a ninefold elevation of the hepatic malate concentration occurs in the liver-specific PEPCK knockout mice, we suggest that one or more intermediary metabolites may directly regulate expression of the affected genes. Thus, hepatic PEPCK may function more as an integrator of hepatic energy metabolism than as a determinant of gluconeogenesis

Macroscopic Physiology, evaluating the roles of metabolites What happens when we move form cells to tissues to mammalian organisms Tissues have more than one type of cell. Input ant output to tissues may not be easy to measure. Mammalian organisms consume a variety of energy sources. Mammals have many interacting cells and tissues that control affect physiology Opportunities for bioinformatics

Metabolic Physiologist would like to determine flux amounts (size of pool is relatively easy to determine) fluxes are more difficult Inter-organ fluxes : flux of glutamine from muscle to liver Intracellular fluxes: lactate to glucose in the liver Intra-molecular fluxes: sources of acetyl moiety of citrate G A 3 A 3 1 1 E 1 1 C 1 B H 2 A 3 1 4 Measuring the amounts of metabolites does not provide information about fluxes D

Analysis of Metabolite levels may reveal site of disease lesion or drug action Cross over theorem. 100% Normal A B C D E A B C D E Diseased 100% A B C D E A B C D E

Medium Chain Acyl Dehydrogenase (MCAD) Deficiency. A disease of muscle weakness detected by changes in urine metabolites. 100 % C 2 carnitine C 3 carnitine Normal C 16 carnitine 0 100 C 8 carnitine MCAD deficiency % C 6 carnitine C 10:1 C 10:1 carnitine 0 225 250 275 300 325 350 375 400 425 450 475 500 m/z

Glucose Labeling of D physiologist engineer A* time 3 A G 3 1 1 C E 1 1 B 1 1 Fa Fz 2 1 D 1 Sample problems: Whole body protein synthesis. Rate of proliferation of specific cells (DNA synthesis). Rate of glucose synthesis by the liver. Rates of lipogenesis.

Liquid scintillation counting of 14 C labeled compounds yields only one equation for total amount of labeled atoms. No information about unlabeled ------- ------- ------- ------- dpm = f (x) Organic Mass spectrometry of 13 C labeled compounds and metabolic model yields one equation for the amount of each mass including unlabelled (mass+0) 0 1 2 3 4 Mass + ------- mass+0 = f (x)0 ------- mass+1 = f (x)1 ------- mass+2 = f (x)2 ------- mass+3 = f (x)3 ------- mass+4 = f (x)4 Although both 14 C and 13 C labeled compounds may be useful in metabolic studies. There are fundamental differences in the type of information available when these isotopes are detected by standard methods.

Radioisotopes are detected by Decay. 1 uci = 2.2 * 10 6 dpm Isotope half life decay constant maximum SA 14 C 5730 years 1.209 x 10-4 /year 62.5 Ci/mole 11 C 20.4 min 3.40 x 10-2 /min 9.20 x 10 9 Ci/mole 3 H 12.4 years 5.59 x 10-4 /year 2.88 x 10 4 Ci/mole 35 S 87.4 days 7.93 x 10-3 /day 1.49 x 10 6 Ci/mole 32 P 14.3 days 4.85 x 10-2 /day 9.13 x 10 6 Ci/mole

Determination of Testosterone production rates by Stable Isotope Dilution Organic Mass Spectrometry Infuse tracer [1,2-2 H]Testosterone = *T at constant rate 20 µg/hour for 12 hr to reach steady state Sample Blood (5ml) At t = 12 hr Begin sampling A Steady State method rapid changes in T production will be damped useful only for T production Ra T T* T T T T* T T T T Testes T T Recirculating T T* T T T T Rd T T* T* T T Intensity MS of T* + T 0 1 2 3 mass +, or m+ Estimated T production rates in men of 64 to 101 µg/hour in women of 3.6 to 6.0 µg/hour Issue of lowering infusion rate

Doubly labeled water method for CO 2 production and for total energy expenditure 2 Isotopic enrichment 1.5 1 0.5 18 O water 2 H water CO 2 carbonic anhydrase + H 2 O H + HCO 3 0 0 10 20 30 40 50 Days CO 2 carbonic anhydrase 2 H 18 + 2 O H + HCO 3 18 O lost, respiration C 18 O 2 and as water H 2 18 O 2 H lost as water H 2 18 O Rate of CO 2 production is computed from rate of 18 O loss in respiration

Isotopes are the key to determining metabolic fluxes. A common ground for Metabolic Physiologists and Metabolic Engineers Many kinds of tracers may be used Isotopes of various atoms 14 C, 13 C, 11 C, 2 H, 3 H, 15 N, 17 O, 18 O, 32 P, etc. Isotopes detected by numerous methods A G 3 A 3 1 4 E B 1 1 1 C 1 2 3 1 Labeling of D D physiologist time engineer Consider C = acetyl CoA

Measuring the rate of the TCA cycle in the heart with 13C and NMR Aspartate Oxaloacetate Acetyl CoA Citrate 5 C Acetyl CoA 4 C 3 C C 6 2 C Oxaloacetate 1 C α- Ketoglutarate CO 2 Glutamate CO 2

Measuring the rate of the TCA cycle in the heart with 13C and NMR Glucose fatty acids Acetyl CoA Oxaloacetate Ketone bodies Citrate 5 C Acetyl CoA 4 C 3 C C 6 2 C Oxaloacetate 1 C α- Ketoglutarate CO 2 Glutamate CO 2 The heart is an omnivore and we cannot take a sample of heart But we do have 13C tracers and NMR

Labeling of glutamate, visible in the NMR, in vivo provides estimate for fraction acetyl CoA derived from labeled precursor C C C C C C C C 1 C C 2 Acetyl CoA Citrate C C C C C C Citrate C C C C C C C C 1 C C 2 C C 3 C C 4 Oxaloacetate C C C C C Glutamate C3,4 doublet C 5 C 4 C 3 C 2 C 1 Glutamate C3 singlet

Many interesting biomolecules are products of condensation of identical subunits. Condensation Polymerization n A 1 B 2 lactate 1 glucose 16 acetate 1 palmitate 18 acetate 1 cholesterol + 9 C 6 mevalonate 1 cholesterol + 3 C 2 acetate 1 acetoacetate? H from water 1 cholesterol or fatty acids n hydroxyproline 1 collagen n adenylic acid 1 poly A tail on Messenger RNA n glucose glycogen or glycosylated protein n aa (X) peptide.xxx.

Media with [U-13C]Glucose -- Isotopomer Spectral Analysis (ISA) of Fatty acid Biosynthesis Acetyl CoA (precursor dilution) D =? 1-D? Natural sources of Acetyl CoA, 12C 8 Acetyl CoA -> 1 Palmitate Intracellular lipogenic precursor Acetyl CoA Newly (product dilution) Synthesized fatty acid g(t) =? 1-g(t) Sampled fatty acid Natural fatty acid due to 1.1% natural 13C abundance and derivative 0 1 2 3 4 Mass + 0 1 2 3 4 Mass + 0 1 2 3 4 Mass +

Tracer 13 C Acetate T 0 = 0.01, T 1 = 0.02, T 2 = 0.97, Fractional abundance Natural Acetate N 0 = 0.9799, N 1 = 0.0200, N 2 = 0.0001, Composition of precursor (acetate) for biosynthesis is known Fractional abundance pre- New synthesis existing Mass+0 = g(t) * (D T 0 + (1-D) N 0 ) 8 + (1-g(t)) N 8 0 1 2 3 0 4 New synthesis preexisting Mass + Mass+1 = g(t) * 8 * (D T 0 + (1-D) N 0 ) 7 * (D T 1 + (1-D) N 1 ) + (1-g(t)) 8* N 07 * N + 1 derivative effect ISA vs MIDA ISA uses nonlinear regression to fit data to model. No correction for deriv prior to analysis. Derivative is included in the model.

Isotopomer Spectral Analysis of Gluconeogenesis -C [U-13C] lactate infused (precursor dilution) -C D =? 1-D? 2 triose -> 1 glucose Newly Synthesized glucose g(t) =? -C -C Natural sources of gluconeogenic precursors Intrahepatic triose P Natural glucose G Mass + Sampled 0 1 2 3 4 5 6 product g(t) = G [1 - e Mass + plasma glucose - t F/n ] 0 1 2 3 4 5 6 -C g(t) -C diet glycogen

Hepatoma CellPalmitateSynthesis [1,2-13 C] Acetate D 1-D Natural Acetyl CoA Media [1,2, -13C]Acetate Acetyl CoA Best fit, lowest error is: 8 AC Palmitate 0.80 D = 0.63 + 0.004 g(t) = 0.52 + 0.003 denovo synthesized Palmitate G1 1-G1 Natural Palmitate (Pre-existing) 0.60 Experiment FRACTIONAL ABUNDANCE 0.40 0.20 0.08 0.06 0.04 0.02 0.00 MODEL g(t) New Synthesis. 1-g(t) Pre-existing 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 1617 Sampled Triglycerid epalmitate MASS +

(Media) Labeled Acetate, 13C Natural sources of Acetyl CoA, 12C D =? 1-D? Squalene 30C 18 acetate ->1 squalene Lanosterol Dihydrolanosterol new squalene 8,24 -dimethylsterol 8,24 -monomethylsterol 8 -dimethylsterol 8 -monomethylsterol 8,24 -cholestenol 8 -cholestenol Lathosterol Desmosterol Cholesterol 27C

Isotopomer Spectral Analysis : g(12 hrs) values for Cholesterol and Its Precursors new steroid g(t) =? Diet g(t) G g(t) = G [1 - e - t F/n ] Sampled product 1.0 Lanosterol -8-Cholestenol Dihydrolanosterol g(12 hrs) 0.75 0.50 Cholesterol Lathosterol 0.25 0.00

Fractional Abundance 0.15 0.10 0.05 0.00 0.35 Data, Dog Liver Lathosterol Fit of model to data Pre-existing (1-g(t) = 0.28 New synthesis g(t) = 0.72 D = 0.46 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 mass+ (Media) Labeled Acetate, 13C D =? Natural sources of Acetyl CoA, 12C 1-D? Fractional Abundance 0.30 0.25 0.20 0.15 0.10 0.05 Data, HepG2 Hepatoma Cell Line Fit of model to data Lathosterol Pre-existing (1-g(t) = 0.53 New synthesis g(t) = 0.47 D = 0.32 The standard form of the model assumes that D is constant. But this does not always appear to be true. 0.00 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Data, Dog Liver Lathosterol Fractional Abundance 0.15 0.10 0.05 0.00 Fit of model to data Pre-existing (1-g(t) = 0.28 New synthesis g(t) = 0.72 D = 0.46 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 mass+ (Media) Labeled Acetate, 13C D =? Natural sources of Acetyl CoA, 12C 1-D? Fractional Abundance 0.15 0.10 0.05 Data, Dog Liver Lathosterol Fit of model to data Pre-existing (1-g(t) = 0.28 New synthesis g(t) = 0.72 D = 0.138-0.699 D = 0.138 D = 0.699 0.00 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 mass+

Subject agrees to consume 2 H 2 O to yield 0.35% total body water. Because water equilibrates across cell membranes the dilution problem is simplified. The enrichment of plasma water equals the enrichment of all body water pools Gut 2 H 2 O Plasma 2 H 2 O ECF 2 H 2 O Cytosol 2 H 2 O Mito 2 H 2 O Also discuss breath tests H. pylori infection diagnosis, fat malabsorption