Comparative Biochemistry and Physiology Part A: Molecular & Integrative Physiology
Stable isotope analysis of CO2 in breath indicates metabolic fuel shifts in torpid arctic ground squirrels
Introduction
Animals use three primary metabolic fuels to meet energy demands: protein, carbohydrate, and lipid. Protein is typically reserved for structural and functional roles and does not contribute significantly to energy metabolism during periods of energy balance (Robbins, 2001). Carbohydrates are often directly metabolized for immediate energy and are not stored in large quantities in mammals (Vock et al., 1996). Lipid is the most energy-dense fuel, providing 8 to 10-times more energy on a wet mass basis than carbohydrate or protein (McWilliams et al., 2004). Thus, lipid, which is stored as white adipose tissue, is used over relatively long time frames after carbohydrate stores are depleted. Several factors influence which fuels are selected for metabolism, including exercise intensity, training status, and diet (reviewed in Holloszy et al., 1998). Animals enduring fasting or starvation exhibit a well-defined pattern of metabolic fuel selection, with timing of shifts between fuels based on the amount of lipid available and catabolism of protein as a last resort (Robbins, 2001).
Mammalian hibernation is a strategy used by a variety of species to conserve energy in anticipation of and during periods of insufficient food resources. During hibernation, animals often do not eat for months and rely entirely on endogenous stores of metabolic fuel. Some animals can conserve as much as 90% of the energy they would otherwise use by spending most of the hibernation season in torpor, the low-metabolism, energy-saving phase of hibernation (Karpovich et al., 2009, Wang and Wolowyk, 1988). Most hibernators support their metabolic demand from large lipid stores which are accumulated during the pre-hibernation fattening period (Dark, 2005), but this appears insufficient for animals hibernating in extreme environmental conditions, such as the Arctic (Buck and Barnes, 2000).
Arctic ground squirrels (Urocitellus parryii) are the most northern small hibernator in North America and experience hibernacula temperatures averaging − 8.9 °C and as low as − 23 °C over the 6–8 month hibernation season (Buck and Barnes, 1999b). Arctic ground squirrels defend a minimum body temperature as low as − 2.9 °C for weeks at a time during torpor (Barnes, 1989), which requires them to be continuously thermogenic due to the still lower burrow temperatures (Buck et al., 2008). During the short active season, arctic ground squirrels increase lipid (Buck and Barnes, 1999a) and lean mass (Boonstra et al., 2011, Sheriff et al., 2013), and significant proportions of both tissues are used over winter, as indicated by body composition estimates before and after hibernation (Buck and Barnes, 1999b). Use of lean mass during hibernation is also indicated by a shift toward increased reliance on mixed fuel metabolism during torpor at decreasing ambient temperatures (Ta), as indicated by respirometry (Buck and Barnes, 2000). Carbohydrate (glucose) is needed to facilitate lipid oxidation associated with brown adipose tissue thermogenesis (Cannon and Nedergaard, 1979, Vallerand et al., 1990), to support anaplerosis (Owen et al., 2002), and to fuel certain organs such as the kidneys (Berg et al., 2002). The primary precursor to glucose in most hibernators is glycerol, a byproduct of triglyceride catabolism (Galster and Morrison, 1975, Staples and Hochachka, 1998). However, it has been suggested that the increasing demand for carbohydrates by thermogenesis surpasses the supply of glucose formed from glycerol and requires the additional breakdown of protein for gluconeogenesis (Buck and Barnes, 2000, Galster and Morrison, 1975, Krilowicz, 1985). This hypothesis is supported by dramatic upregulation during hibernation of the gene PCK1, which codes for a crucial enzyme in gluconeogenesis from pyruvate, lactate, or amino acid precursors (Williams et al., 2011). Whether amino acids are catabolized directly for fuel use during torpor has not yet been determined.
Respirometry is the traditional method used to differentiate metabolic fuel use, but it cannot differentiate between protein and mixed fuel catabolism. The respiratory quotient (RQ), the ratio of carbon dioxide (CO2) produced to oxygen (O2) consumed (Kleiber, 1961), is approximately 0.7 during lipid oxidation while carbohydrate oxidation results in an RQ of 1.0. Oxidation of proteins yields an intermediate RQ of 0.83 (Kleiber, 1961), similar to that expected from mixed lipid and carbohydrate metabolism. Respiratory exchange ratios (RER), collected from whole-animal respirometry, are used in this study to approximate RQ values, and we will discuss RQ and RER as a singular concept for the purposes of this study. Alternative measures of fuel use in addition to RQ may help to better distinguish the proportions of metabolic contribution among carbohydrate, protein, and lipid.
Stable carbon isotope measurements are becoming more common in studies of substrate use, as respired CO2 is a direct product of the animal's metabolism (Hatch et al., 2002, Voigt et al., 2008a; reviewed in: McCue and Welch, 2016, Welch et al., 2016). Lipid has a lower carbon isotope ratio (δ13C) than other metabolites (DeNiro and Epstein, 1977; reviewed in McCue and Welch, 2016). Animals that are fasting shift toward lower δ13C values in respired CO2 (Perkins and Speakman, 2001, Schoeller et al., 1984, Voigt et al., 2008a, Voigt et al., 2008b), which is consistent with an increase in the proportion of lipid utilization during food deprivation (McCue and Pollock, 2013, Robbins, 2001). Investigations of metabolism in plants have shown a strong correlation between RQ and δ13C values in respired CO2 (Pataki, 2005, Tcherkez et al., 2003), but few studies in animals have combined measurements of RER and breath δ13C values from naturally distinct, endogenous substrates (Gautier et al., 1996, Schoeller et al., 1984).
Metabolic processes have the potential to preferentially use one form of isotope over others. This discrimination can lead to differences in the δ13C values between fuel source and exhaled CO2. Several experimental studies have found differences between δ13C values in breath and diet (discrimination factors; surveyed in Table 2 in Voigt et al., 2008a), but the number of metabolic steps that exogenous and endogenous substrates go through before utilization are different and thus differ in their potential for discrimination. In addition, discrimination in the breakdown of endogenous protein and lipid stores likely varies due to the differences in metabolic pathways, but most metabolic processes have not been thoroughly investigated for evidence of discrimination.
Our first objective was to determine whether RER and δ13C values covary in an animal system utilizing endogenous substrates with naturally distinct δ13C signatures. To address this objective, we concurrently measured RER and breath δ13C values in fasting and hibernating arctic ground squirrels, using changes in Ta to induce shifts in fuel use. Previous work on torpid arctic ground squirrels showed a robust, linear increase in RER as Ta decreased below 0 °C (Buck and Barnes, 2000) and a clear difference in δ13C values between tissue lipids and lean mass (Lee et al., 2012). Our second objective was to determine whether using two 2-endpoint measurements, RER and breath δ13C values, could help resolve fuel use in torpid arctic ground squirrels. Specifically, if RER values are intermediate and δ13C values are intermediate, we would conclude that squirrels are using a mix of lipid and other fuels. However, if RER values are intermediate and δ13C values are high, we would conclude that the animals are using a fuel based on proteins and/or carbohydrates but utilizing little, if any, lipid. Our final objective was to determine whether there was evidence of discrimination between endogenous fuels and breath δ13C values.
Section snippets
Animals
Arctic ground squirrels (Urocitellus parryii) were captured near Toolik Field Station (68° 38′ N, 149° 36′ W) in the Alaskan Arctic in fall 2008 and summer 2009 and maintained on Mazuri Rodent Chow in captivity at the University of Alaska Anchorage. Each animal had a temperature-sensitive radiotransmitter surgically implanted in its abdomen (~ 7 g; Data Sciences International, St. Paul, MN, USA, see Richter et al., 2015 for methods). Ground squirrels were initially held at room temperature on an
Results
Metabolic rate of arctic ground squirrels during steady-state torpor increased linearly as Ta decreased from − 2 to − 26 °C (Fig. 1a; reported in Richter et al., 2015). RER of these animals also varied significantly with decreasing Ta in each environmental chamber (Chamber 1: F9,68 = 11.81, p < 0.0001; Chamber 2: F4,34 = 9.07, p < 0.0001; Fig. 1a), but it did not follow a linear pattern. Instead, RER ranged from a maximum mean of 0.76 at − 2 °C to a minimum mean of 0.73 at − 10 °C during steady-state torpor.
Discussion
Carbon isotope ratios of breath CO2 during torpor varied widely between the endpoints of lipid and lipid-free tissue from hibernating arctic ground squirrels. RER and breath δ13C values were correlated during steady-state torpor over Ta from − 2 to − 26 °C and a corresponding range of torpid metabolic rates from 0.02 to 0.37 ml O2/(g ∗ hr) (Richter et al., 2015). This suggests that breath δ13C values may be a useful tool to investigate endogenous fuel use due to the distinct δ13C values between lipid
Conclusion
This study answers a call to expand the use of 13C-breath testing into new research areas (McCue and Welch, 2016, Welch et al., 2016) and demonstrates that breath δ13C values can be used to identify metabolic shifts between endogenous substrates with naturally distinct δ13C signatures in animals. The correlation between δ13C values in breath and RER provides a foundation for using breath δ13C values as an index of endogenous fuel use. The breath δ13C value extrapolated from our data to coincide
Acknowledgments
We thank Tim Stevenson, Brady Salli, and Jermey Becker for help with captive animal care and Franziska Kohl for animal and logistics support. We also thank Tim Howe and Norma Haubenstock of the Alaska Stable Isotope Facility for support in sample preparation and timely analysis. We thank two anonymous reviewers for thoughtful comments that improved this manuscript. This work was supported by a collaborative National Science Foundation International Polar Year Grant [grant numbers EF-0732755 to
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- 1
Present Address: Biology Department, 1906 College Heights Blvd., #11080, Western Kentucky University, Bowling Green, KY 42101, USA.
- 2
Present Address: Department of Biological Sciences and Center for Bioengineering Innovation; 617 S. Beaver St., Northern Arizona University, Flagstaff, AZ 86011-5640, USA.