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SPECIAL SECTION ON MITOCHONDRIAL MODELING AND FUNCTION
1Laboratory of Cardiac Energetics, National Heart Lung and Blood Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland; and 2Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, Indiana
Submitted 11 March 2006 ; accepted in final form 5 September 2006
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ABSTRACT |
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 TOP ABSTRACT MATERIALS AND METHODSRESULTS AND DISCUSSIONGRANTSREFERENCES |
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oxidative phosphorylation; liquid chromatography; mass spectrometry; electrophoresis; histone; liver; heart; kidney; brain
The purpose of this study was to evaluate the functional consequences of the mitochondrial protein heterogeneity of the heart, liver, kidney, and brain of the rat, as described in the companion paper (26) for 382 proteins. This screen provided excellent coverage of most of the major mitochondrial metabolic pathways. This effort had several goals: to further evaluate the distribution of mitochondrial functional emphasis between different tissues based on the protein distribution, establish the overall protein requirements for generating the mitochondrial functional emphasis in different tissues, and develop graphical viewing tools of the differential expression of mitochondrial reaction pathways. Finally, this study sought to begin characterizing the potential activity of proteins with unknown functions localized to the mitochondrial matrix space.
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MATERIALS AND METHODS |
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TOPABSTRACTMATERIALS AND METHODSRESULTS AND DISCUSSIONGRANTSREFERENCES |
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Canonical pathway approaches. The canonical metabolic and signaling pathways were constructed utilizing the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway database (http://www.genome.jp/kegg/pathway.html) to provide a generally available pathway framework. The number of proteins demonstrated vs. the number resident to a pathway was derived from the total number of proteins in this screen vs. the total number of proteins that have been assigned to the nodes (E.C. numbers) resident in that pathway according to the KEGG classification system and the Uniprot databases (http://www.expasy.uniprot.org/). There were disadvantages to using these pathways for this type of analysis. There is, as yet, no resource that catalogs the mitochondrial canonical pathways specifically and many of the canonicals that pass through mitochondria also involve enzymes in other subcellular compartments. KEGG pathways often include side reactions that do not directly participate in the pathway in an effort to include all possible reactions in the canonical pathway. There are often several proteins which occupy the same node, many of these being tissue specific or localized to organelles other than the mitochondria, and so these tissue or compartment specific proteins were not expected to be detected in this study. Taken together, these facts tend to reduce the apparent coverage of a study such as this. For the sake of completeness with respect to the literature all of the proteins included in a KEGG pathway for rat were included in the estimate of protein coverage of the canonical pathways evaluated. This may not give an accurate representation because many were in tissues not covered by this study, and furthermore, many were from compartments other than the mitochondria. The KEGG pathways have the advantage of being linked to several other major databases. While they are sometimes overly inclusive, often including proteins that physiologically do not perform the function listed, KEGG pathways rarely exclude proteins that are in any particular pathway.
To better evaluate the major mitochondrial metabolic pathways, oxidative phosphorylation, citric acid cycle, GABA metabolism, urea cycle, ROS metabolism, and inner membrane transport mechanisms, a graphical presentation scheme was developed. The pathways were determined from a primary review of the mammalian mitochondria enzyme literature but only the mitochondrial-based reactions were included, in contrast to KEGG. Proteins were all listed by expression relative to brain expression of the same protein. Proteins were then highlighted when they differed in expression value 
30% relative to the brain. As discussed previously (26), we used the arbitrary difference threshold of 30% as a physiological significant difference well above the 
5–10% statistical significance difference threshold for this methodology. The 30% value was selected since the actual control strength relative to different enzymes in a pathway is not known for most proteins, and several examples of modifications on this order of magnitude have been ascribed to clinically relevant conditions. The relative expression of these proteins was established across six sets of samples of each tissue mitochondria. All protein level differences were determined with a Q value <0.05. Q value is a more stringent criterion than P value because it encompasses both rejections of the null hypothesis (P value) as well as incorporating the false discovery rate (36). Since the database is relational, i.e., the amount of a given protein can only be compared relative to the amounts of that same protein in the other tissues, all of the protein levels are expressed relative to the brain. Brain was selected as the reference since it had the most protein levels in common with the other tissues under study. In the diagrams, a thin line represents a protein concentration within ±30% of the brain. A thick line represents a protein content >30%, whereas a dotted line represents 30% downregulated compared with the brain levels. An asterisk next to a thick line represents an increase in protein over twofold (i.e., >100% increase) relative to the brain. Protein identifications are given in the figure legends. Quantitative data is reported in supplemental Table 1 listed by canonical pathway (KEGG) (The online version of this article contains two supplemental tables).
Total coverage of the canonical pathways found in the mitochondrial proteome analysis is listed in Fig. 1.
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BLAST analysis. Proteins that have not previously been identified as mitochondrial, which had probability of translocase of outer membrane (TOM) complex translocation (PTcT) of >0.5 and purification in the mitochondrial fraction across four tissues and six samples of each tissue (total of 24) that had not been previously localized to the mitochondria were subjected to NCBI-conserved domain protein BLAST search. Domains of known function determined to have P values <0.005 via NCBI calculation are reported in supplemental Table 2.
In circumstances where multiple related domains were found, the domains that corresponded most closely to the sequences in our study were reported. Any protein without a conserved domain found by this method was reported as unknown.
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RESULTS AND DISCUSSION |
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TOPABSTRACTMATERIALS AND METHODSRESULTS AND DISCUSSIONGRANTSREFERENCES |
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To better understand the functional differences between the different mitochondria and the role of protein concentration in the overall regulation of these functions two types of analysis were performed. The first analysis centered on specific metabolic pathways based on the KEGG metabolic pathway while the second analysis focused on the overall mitochondrial function within a given tissue.
With the use of the KEGG pathways, a very consistent view of the relative emphasis of different functional aspects of mitochondria in the different tissues could be accessed. Clearly this relational protein content data placed in the functional context of a metabolic pathway only gives the relative amount of protein associated with a given pathway, and it does not provide direct information on relative flux. In many ways, this relational database is much like looking down on a roadmap of a city without monitoring the passage of cars, or flux, controlled by stoplights or other forms of traffic control. Looking at such a roadmap yields a good idea of where the traffic (metabolic flux) is because the cell likely does not waste energy building roads where they are not needed. With regard to many of the major mitochondrial functional pathways, the net protein content in a pathway correlates very well with the known functional heterogeneity mitochondria in different tissues. A cursory review of these pathways reveals, in general, that for a given functional pathway the entire pathway of enzymes were upregulated with a few exceptions, consistent with the roadmap analogy. By increasing most of the proteins in a given pathway that enhances a particular metabolic outcome, the flux through the pathway can be increased without changing the concentration of the substrates for the process contributing to the overall metabolic homeostasis of the system. This is useful since many of the metabolites are also involved in other reactions that also need to be maintained. It also implies that the alteration of a single or alternately a few "rate-limiting" enzymes is not adequate to support a required function. This observation is consistent with the notion that any metabolic pathway is already balanced (44) and any increase in flux capacity would require an upregulation of the entire pathway, not just one rate-limiting step. This notion has been supported from several different theoretical points of view (35). Peterson suggested that a single rate-limiting step would waste "biosynthetic energy" by having unused enzymatic capacity in the non-rate-limiting steps of the pathway (35). These data support the general notion that pathway proteins are regulated as a group, with all or most of the proteins associated with an upregulated pathway being augmented. These data do not provide support for the idea of alteration of individual rate limiting proteins being differentially regulated while the rest of a pathway is held nearly constant as a means of differential regulation (15). It must be stated, however, that flux data was not collected in these experiments and as such specific flux data is outside the scope of this study.
As discussed earlier, one of the limitations of the KEGG model is that it is not specific for the mitochondrial compartments and many of the proteins listed in a given pathway are nonmitochondrial. Thus, we have constructed more specific models for several of the major pathways, including oxidative phosphorylation, citric acid cycle, fatty acid oxidation, urea cycle, GABA metabolism, and ROS metabolism. The goal of detailed analysis of metabolic pathways was to map the distribution of proteins within a pathway to gain insight into which proteins are regulated together, as well as to provide predictions for enzymes that are required for alterations in overall pathway capacity. As discussed above, in general, the entire pathway was upregulated in a given tissue with enhanced capacity. However, if only one or two enzymes were not increased in an upregulated pathway, it is reasonable to assume that these enzymes concentrations were not rate limiting for the overall reaction. This approach can only be approximate, since posttranslational modifications such as phosphorylation (19), concentrations of reactants, and allosteric effectors were not evaluated and could play a major role in the enzymatic turnover rate per mol of enzyme. In addition, other unidentified or undetected enzymes or pathways may be bypassing steps in different tissues.
Oxidative phosphorylation. As previously discussed (26), the proteins encoded by mitochondrial DNA were not adequately sampled in this study to make our statistical thresholds, likely due to the inability to solubilize these highly hydrophobic proteins and ionize the peptides derived by tryptic digestion. There are also likely lower levels of these proteins. Membrane proteins were probably underrepresented as membrane-spanning domains are often highly repetitive and conserved among integral membrane proteins, and hence not useful for determining the identity of the proteins from which they were derived. Thus the mitochondrial-encoded proteins have been excluded from this report. By using the confidently identified proteins, a graphic presentation of proteins of oxidative phosphorylation across tissues is presented in Fig. 2.
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10% in kidney and a decrease of 10% in liver with respect to brain. Despite the good quantitative correlation between the electron transport chain elements and ATP synthase (F0F1) across tissues, the transporters that support this reaction (the adenylate translocase and phosphate transporter) do not correlate with the level of these related proteins. This was true even taking into account the different forms of the adenylate translocase (ANT-1, ANT-2). Only a modest increase in the levels of renal ANT-2 relative to brain was found while ANT-1 was homogeneously distributed across the tissues. The enzymes of oxidative phosphorylation are quite complex with numerous subunits and a mix of mitochondrial and nuclear DNA-encoded proteins. We detected primarily nuclear-encoded proteins with only three mitochondrial-encoded proteins reaching the 1* criterion. The 1* group were proteins identified with high confidence, these identifications comply with the highest minimum standards recommended in the literature as described by Carr et al. (4). Any comparison of nuclear- vs. mitochondrial-encoded protein content across tissues would be difficult. The reason for detecting only a few of the mitochondrial-encoded proteins even in our lower statistical groups in this analysis is unknown. Potentially highly hydrophobic nature of the mitochondrial-encoded proteins prevented adequate solubilization or prevented the generation of suitable peptide ions for analysis in this type of study. Thus, only the nuclear-encoded proteins were analyzed in this study.
All of the electron transport complexes were expressed at much higher levels in the heart than in any other tissue. On average the proteins associated with complexes 1–4 were upregulated 56% in heart relative to the other tissues. Complex 4 was higher than the other proteins with a mean increase of 75% in heart, while the other complexes were essentially identical except for an increase in Complex 2 in the kidney. The electron transport flavoprotein (ETF) was upregulated in heart, kidney, and liver compared with the brain. ETF upregulation is a key modification for the adaptation to fatty acid oxidation in mitochondria. ETF is the entry point of FADH2 derived from fatty acid oxidation into the electron transport chain. Fatty acids do not cross the blood brain barrier and cannot be substrate for the brain aside from brain lipid breakdown products (34).
At the level of ATP generation, the ATP synthase (F0F1) proteins were upregulated in the heart in proportion to the increase in electron transport complexes. This implies a co-ordination in the capacity of generating the proton motive force with ATP synthetic capacity. This was not matched by the transport proteins that support the ATP synthase (F0F1) activity, ANT and the phosphate transporter in the inner membrane. The concentration of these transport proteins was essentially constant across tissues with the exception of a slight increase in renal ANT content. These data suggest that the concentration of these transporters is in excess capacity, at least in kidney, liver and brain tissue. The ANT could also be in excess capacity in the heart based on these data as well as functional studies (16) and warrants further study to elucidate the functionality and capacity of this transporter. Naturally, this speculation is based on protein concentrations and not on activity which could be altered by posttranslational modifications, allosteric factors, or substrate concentrations. Nevertheless, these data are consistent with the notion that an increase in expression of all the cytochrome chain proteins, including the ATP synthase (F0F1), are required to increase the maximum capacity for ATP generation while the upregulation of the associated phosphate and adenylate transporters are not required. A complex of ANT, phosphate transport, and the ATP synthase (F0F1) has been recently proposed (6). However, since the ratio of these proteins are not constant across tissues, it is may be that the stoichiometry of these complexes is not fixed or that these transporters exist outside of complexes in addition to participating in these complexes.
Citric acid cycle. The citric acid cycle generates the majority of the NADH and FADH2, which provides the potential energy for oxidative phosphorylation with both fatty acid oxidation and glycolysis, which feed into the citric acid cycle via acetyl-CoA. The relative protein amounts for the cycle are graphically presented in Fig. 3.
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At first consideration, it was surprising that the protein concentrations of the citric acid cycle enzymes did not closely follow the distribution of electron transport chain protein level, however, when one considers that the brain relies primarily on glucose oxidation where other tissues use fatty acids sometimes in preference to glucose. During 
-oxidation, nearly 33% of the reducing equivalents can be generated from reactions outside of the citric acid cycle as well as generating more FADH2. This leads to less efficient generation of ATP from oxygen. This results in these tissues requiring a higher ratio of electron transport proteins than citric acid cycle enzymes. Thus, it follows that the ratio of citric acid cycle proteins to electron transport chain complexes would be higher in brain than in other tissues, which consume fatty acids as illustrated in Figs. 2 and 3.
We were also able to characterize the levels of hydroxyacid-oxoacid transhydrogenase (HOT), an enzyme also known as alcohol dehydrogenase, iron containing 1, in the literature. The activity of this enzyme was determined before the sequence of the enzyme was characterized with the sequence being matched to the activity by Kardon et al. (23). 4-Hydroxybutyrate (4-HB) has important but not fully characterized signaling functions. It is a drug of abuse as well as a therapeutic treatment for narcolepsy and alcoholism (41). HOT converts 4-HB to succinate semialdehyde coupled to conversion of 2-oxoglutarate to D-2-hydroxyglutarate (24, 42). This is the rate limiting step in overall catabolism of 4-HB with the rate of HOT three orders of magnitude slower than succinate semialdehyde dehydrogenase (SSDH) (24). Succinate semialdehyde is then able to feed into the citric acid cycle upon conversion to succinate through SSDH. This in turn affects levels of 4-HB in tissues. The levels of HOT change 100-fold during the course of development (31). The levels of this enzyme were higher in the kidney and liver, and lower in the heart and brain. The importance of 4-HB signaling as well as the strong control strength of this enzyme makes this an important target for further characterization. The differences demonstrated here are likely biologically significant secondary to the high control strength of this enzyme, which warrants further investigation. The relative levels of this enzyme in isolated mitochondria have not been previously demonstrated.
These results again suggest that the absolute capacity of the citric acid cycle exceeds the demands imposed by oxidative phosphorylation in most tissues. Alternately, other pathways, such as fatty acid oxidation (FOx), are upregulated to match the increased demand of ATP through oxidative phosphorylation. This excludes enzymes known to have almost no control strength on the pathway (i.e., malate dehydrogenase) and those that participate in secondary pathway intersections such as succinate dehydrogenase.
FOx. A physiologically important pathway for generation of reducing equivalents to the electron transport chain is FOx. The relative enzyme levels for this reaction sequence are presented in Fig. 4.
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Urea cycle. A major function of the mitochondria is the processing and elimination of fixed nitrogen derived from ammonia and protein metabolism. The urea cycle is an important mitochondrial metabolic pathway for the elimination of fixed nitrogen derived from these sources. The enzymes of the urea cycle also play an important role in generation of ornithine, arginine, and proline. These experiments do not examine the cytoplasmic enzymes of the urea cycle, thus we are unable to draw conclusions about the completeness of the urea cycle in tissues other than the liver, which has a complete urea cycle (46). The mitochondrial components of the urea cycle are shown in Fig. 5.
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The levels of urea cycle enzymes in kidney, which suggests a major role for the kidney in amino acid metabolic regulation. It is appreciated that kidney is the major source of arginine (29, 42) as well as a major source of proline in postnatal mammals. Proline is a nonessential amino acid in the full-term infants and adults (18), but is conditionally essential in preterm infants (30–32). Pyrroline-5-carboxylate synthetase (PCS) and ornithine aminotransferase were found upregulated in kidney mitochondria in this study. This is consistent with the work of Hu et al. (21). PCS is an enzyme that generates L-glutamate semialdehyde from glutamate in a NADPH and ATP dependant irreversible reaction. In the presence of high levels of ornithine aminotransferase, this would tend to favor conversion of glutamate to ornithine, which could then be processed in several directions including proline synthesis, arginine synthesis, and the generation of putrescine. PCS has previously been demonstrated primarily in enterocytes of the gut (48) and in the placenta, as well as in the pancreas and kidneys of full-term infant and adult mammals (21). The importance of PCS in the generation of arginine and proline is illustrated by the inability of neonates to make adequate levels of these amino acids (30, 47). This may demonstrate the expression of PCS late in development, only allowing proline and arginine independence once the kidney begins expressing PCS. This is further supported by the elevated expression of PCS in placenta in the work of Hu et al. (21). The directionality of this pathway generating ornithine opens the possibility that the kidney may be a major producer of ornithine. This would couple the overall mitochondrial function with the levels of arginine, which has defined and important role in many signaling functions (3). While there is literature to support high levels of PCS in the kidney, the standard dogma is that ornithine is produced in enterocytes of the gut since the gut is thought to be uniquely elevated in PCS. It is notable that all of the data gathered by Wu et al. (46–49, 51) in establishing this was collected in neonatal pig, which may not accurately reflect the mature animal. The data gathered here suggests that the role of the kidney in ornithine metabolism may be under appreciated.
The utility of urea cycle enzymes in the brain and heart, which are not thought to generate urea is not well understood. We can only speculate that these enzymes are necessary in as yet unappreciated metabolic or catabolic processes. CPS was identified with high confidence across all tissues in all samples. In the liver and possibly in the kidney CPS would be important in the disposal of fixed nitrogen as urea. In the brain and heart, where urea synthesis has never been demonstrated, this is an unlikely function.
We also found an enzyme with strong homology to the trifunctional (carbamoyl phosphate synthase-aspartate transcarbamoylase) dihydroorotase domain-containing protein (generally referred to as CAD). Although CAD is known to exist in the cytosol and nucleus (38), the enzyme identified in this study has a strong NH2-terminal mitochondrial localization sequence with functional domains capable of catalyzing the first three steps of de novo pyrimidine synthesis. De novo nucleotide synthesis is not an appreciated function of the mitochondria but the findings of this study open this question for further investigation.
GABA metabolism.
The key enzymes in the known pathways of GABA metabolism are SSDH and 
-aminobutyrate transaminase that link GABA to the mitochondrial citric acid cycle. These enzymes are upregulated in the brain, but are surprisingly upregulated only 33% over other tissues. These data suggest a rather active mitochondrial GABA metabolism capacity in all of these tissues. The matching distribution of the diazepam binding inhibitor protein with the GABA metabolism capacity across tissues may indicate that GABA and related signaling molecules are more prevalent in nonneuronal tissues than generally realized or maybe that unknown substrates of these enzymes bear similarities to GABA. Clearly, the functional significance of the ubiquitous distribution of the GABA metabolizing enzymes merits further investigation.
This connection of GABA metabolism to the citric acid cycle though succinate dehydrogenase (SDH) allows GABA degradation to be coupled to both the citric acid cycle and the redox state of the matrix (SDH is a FAD-dependent enzyme). The lower levels of SDH in the brain could act as a bottleneck for GABA degradation, especially if the higher levels of SSDH and -aminobutyrate transaminase enhance this effect. This mechanism allows for the possibility that the energetic state of the mitochondria of brain, and other tissues, may interact in signaling through GABA levels. In highly reduced state (i.e., hypoxia, ischemia, carbon substrates in excess, or functional arrest) there would be an excess of succinate preventing SSDH from generating additional succinate from succinate semialdehyde, hence preventing the breakdown of GABA. This would present a novel method for control of GABA levels based on metabolic capacity, which warrants further investigation.
Solute and protein transport. The communication between the cytosol and matrix space is critical for the function and construction of the mitochondria. Many of the cells' most important pathways terminate or have elements in the mitochondria. Substrate switching, ATP synthesis, ROS signaling, and pathways of apoptosis are directly performed by the mitochondria. The transporters isolated with high confidence and not previously covered in the represented pathways are consolidated in Fig. 6.
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ROS metabolism. The role of ROS (8) in every aspect of the mitochondrial function from apoptosis control to various signaling pathways is of great interest. The proteins associated with the scavenging of ROS are outlined in Fig. 7.
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NADPH is used for the reversible reduction of oxidized glutathione or thioredoxin which are major elements in the ROS scavenging pathway. The four major reactions for generation of NADPH are glutamate dehydrogenase I, 
p-driven NAD(P)H transhydrogenase [NAD(P)-THG] (23), malic enzyme 3 (24), and isocitrate dehydrogenase (25). Again, the MnSOD content did not correlate with matrix NADPH generation capacity. For example, the relatively unique high Mn-SOD-Prx content of the brain was not matched by the NADPH regenerating system, whereas the NAD(P)-THG content was actually somewhat lower in the brain. The lack of correlation of MnSOD levels with peroxide scavenging systems and NADPH generating enzymes suggest that other sources of ROS and other metabolic needs of NADPH may be dominating the distribution of these enzymes, or that perhaps posttranslational modification of the enzymes is much more important that overall protein content in balancing ROS production and elimination.
Protein sequence analysis. Several of the proteins determined to be mitochondrial via PTcT and isolation in the mitochondrial fraction across all 24 samples are novel and of special interest. These included many proteins associated with DNA structure. This included the histone family proteins isolated along with histone regulatory proteins as discussed earlier (26). Equally important was a DNA methyltransferase (NP_445806), identified with high confidence and a PTcT >0.5. This makes mitochondrial localization likely. Multiple proteins were identified with DNA binding domains (XP_227373, NP_569095, XP_221129, XP_235304, XP_225373, XP_344596, XP_344600, XP_221423, XP_217615, XP_233603, XP_237221.1, and NP_445806). This implies that the structure of mitochondrial DNA and its regulation are considerably more complicated than has been assumed in the literature to this point. Further study on these proteins as they relate to mitochondrial DNA structure is plainly warranted by these findings.
From a BLAST domain analysis, a protein consistent with a family III CoA transferase was found in all tissues. Most CoA transferases belong to two well-characterized enzyme families, but recent work on unusual biochemical pathways of bacteria (primarily anaerobes) has revealed the existence of a third family of CoA transferases (family III) (17). Type III CoA transferases differ in sequence and reaction mechanism from CoA transferases of type I and type II. Characterized enzymes of this class include 1) formyl-CoA, oxalate CoA transferase, 2) succinyl-CoA, (R)-benzylsuccinate CoA transferase, 3) (E)-cinnamoyl-CoA: (R)-phenyllactate CoA transferase, and 4) butyrobetainyl-CoA: (R)-carnitine CoA transferase (1, 14, 17, 27, 28, 37). The formyl-CoA transferase is particularly interesting since it could provide a pathway to metabolize formyl-CoA, which could be generated from the metabolism of glyoxylate by pyruvate dehydrogenase (43). In both Archaea and Eukarya, there remain many enzymes of this family with uncharacterized function.
In addition, there were several enzymes identified with homology to glyceraldehyde-3-phosphate dehydrogenase. This is surprising in that glyceraldehyde-3-phosphate is not produced in mitochondria according to the existing literature. However, these sequences were distinct from the cytoplasmic isoforms in that they have mitochondrial localization signals, and the sequences were different enough to be distinct in databases. The high degree of homology between members of the dehydrogenase families makes it difficult to speculate on potential functions of mitochondrial glyceraldehyde-3-phosphate dehydrogenase-like proteins without further investigation.
In conclusion, utilizing the extensive protein coverage now available for proteomic screens, the functional pathways of the major metabolic pathways of the mitochondria were evaluated in a relational database. The known functional emphasis of the mitochondria in each tissue was generally confirmed by an increase in the entire metabolic pathway associated with a given function. Notable exceptions included the adenylate translocase and phosphate transporter of the inner membrane with the enhancement of oxidative phosphorylation capacity in the heart suggesting that these enzymes have excess capacity in liver, brain, and kidney mitochondria. The graphical representation of these data provided a simple method of grasping the overall pathway preferences of the tissue by generating a relative roadmap of the metabolic fluxes. To finally map out the relative flux occurring through each of the metabolic pathways clearly, more information on the posttranslational modifications, concentration of substrate, products, and modulators (along with the protein complex formations) will be required to generate a truly quantitative model. There were also several proteins identified that expand the functionality of the mitochondria, and with further research, these proteins may adjust the existing dogma of tissue specific mitochondrial function.
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GRANTS |
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TOPABSTRACTMATERIALS AND METHODSRESULTS AND DISCUSSIONGRANTSREFERENCES |
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FOOTNOTES |
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The costs of publication of this article were defrayed in part by the payment of page charges. The article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
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REFERENCES |
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TOPABSTRACTMATERIALS AND METHODSRESULTS AND DISCUSSIONGRANTSREFERENCES |
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