Metabolic rates of cultured skeletal muscle of Coturnix quail selected for
different rates of growth
THESIS
Presented in Partial Fulfillment of the Requirements for the Degree Master of
Science in the Graduate School of The Ohio State University
By
Clara Cooper-Mullin, B.S.
Graduate Program in Evolution, Ecology and Organismal Biology
The Ohio State University
2013
Master's Examination Committee:
Dr. Joseph B. Williams, Advisor
Dr. David Denlinger
Dr. Peter Reiser
Copyright by
Clara Cooper-Mullin
2013
Abstract:
The connection between whole-organism life history and cellular physiology is a
nascent field in Physiological Ecology. Life histories of animals tend to fall on a “slowfast” continuum where species on the “slow” end are characterized by low metabolic
rates, slow growth rates, greater longevity, and lower investment in reproduction,
whereas species on the “fast” end are characterized by higher metabolic rates, faster
growth rates, and greater investment in reproduction. Growth rate is a fundamental
parameter of an organism’s life history and varies 30-fold across bird species. Passerine
nestlings from temperate sites, on the “fast” end, had growth rates that were 23% higher
than species from the tropics on the “slow” end. To explore how growth rate and rate of
metabolism of cells were connected to these whole-organism attributes, I used myoblast
cells from Japanese quail (Coturnix coturnix japonica) that had been selected for fast or
slow growth for over 60 generations. Cells from the fast-growth line had significantly
higher rates of oxygen consumption and glycolysis than cells from the slow line, and
significantly higher mitochondrial density. This finding led me to hypothesize that
attributes of the mitochondria differ between the cell lines. Because mitochondrial DNA
is inherited solely from the female and genes within the mitochondria code for 13
polypeptide proteins that are involved in oxidative phosphorylation, I tested the idea that
the genes involved in complexes in the mitochondria influence the rate of metabolism of
cells. I reared chicks from two hybrid lines, a fast male crossed with a slow female and a
ii
fast female line crossed with a slow male line. These reciprocal parental configurations
allowed me to trace the effect of mitochondrial DNA on growth rate in the whole chick,
and metabolic rates of cultured myoblasts. The growth rate of the chicks from each
hybrid lines was significantly different from the fast and the slow lines, and had
intermediate growth rates and adult weights. On the cellular level, myoblasts in the
hybrid lines had intermediate rates of basal oxygen consumption, glycolysis, and density
of the mitochondria, indicating that metabolic rates on the cellular level are intrinsic to
growth rate on a whole organism level, but that the mitochondrial DNA is not the driving
force behind these differences.
iii
Dedication:
This work is dedicated to my parents, John and Alison Cooper-Mullin.
iv
Acknowledgements:
I would first like to thank my advisor, Dr. Joseph B. Williams for his help in all aspects
of collecting data, writing and overwhelming support during this process. I would also
like to thank the members of my committee: Dr. David Denlinger and Dr. Peter Reiser.
Special thanks to Dr. Ana G. Jimenez for her friendship and long hours of help. Big
thanks to Dr. Harry Itagaki for suggesting that I cross the fast and the slow lines. Thanks
to Dr. Sandra G. Velleman, Cynthia Coy and Dr. Jim Van Brocklyn for their help with
the cell culture, and Dr. Matt Workman for his help on the Seahorse XF96. I would like
to thank Andrew Sudimack for his help with processing the Japanese quail, and all of my
lab mates for their helpful comments on this paper. Thanks to the Department of
Evolution, Ecology and Organismal Biology for sponsoring me with teaching
assistantships. Last, but not least, I would like to thank my family and close friends for
their love, and support and willingness to hear about my work.
v
Vita:
May 2005 ………………………………………………………. Irvington High School
May 2009 ………………………………………………………. B.S., Kenyon College
September 2009 – August 2010 …………………… U.S. Student Fulbright, Botswana
September 2011- Present ………………………………. Graduate Teaching Associate,
Department of Evolution, Ecology
and Organismal Biology, The Ohio
State University
Publications:
Ana G. Jimenez, Clara Cooper-Mullin, Elisabeth A. Calhoon, and Joseph B Williams.
Physiological underpinnings for differences in the pace of life and metabolic rate
in birds. Invited review Journal of Comparative Physiology.
Fields of Study:
Major Field: Evolution, Ecology and Organismal Biology
vi
Table of Contents:
Abstract………………………………………………………………………………….. ii
Dedication……………………………………………………………………………...…iv
Acknowledgements……………………………………………………………………….v
Vita…………………………………………………………………………………….... vi
List of Figures…………………………………………………………………………… ix
Introduction……………………………………………………………………………… 1
Methods…………………………………………………………………………………... 7
Quail lines…………………………………………………………………………7
Growth rate calculations…………………………………………………………..7
Cell culture………………………………………………………………………...7
Metabolic rate analysis and cell size………………………………………………9
Mitochondrial density……………………………………………………………10
Statistics………………………………………………………………………….11
Results………………………………………………………………………………….. 12
Growth rates of quail lines………………………………………………………12
Pax7 and MyoD………………………………………………………………….12
Metabolic rate analysis…………………………………………………………..12
vii
Mitochondrial density……………………………………………………………13
Discussion………………………………………………………………………………. 14
References………………………………………………………………………………. 17
Appendix A: Figures…………………………………………………………………….22
viii
List of Figures:
Figure 1: Growth rate constant (K) and asymptote (A) of chicks from the F, S, FFSM,
SFFM lines from Day zero to Day 56……………………………………………..22
Figure 2: Pax7 (A) and MyoD (B) expression in myoblasts from Coturnix coturnix
japonica. Nuclei stained with DAPI in yellow. Images taken with Fluoview
confocal microscope at 40x. …………………………………………………………….23
Figure 3: Basal oxygen consumption rate, proton leak, max oxygen consumption and
non-mitochondrial oxygen consumption in myoblasts from the F (N = 12), hybrid
(FFSM, N = 6; SFFM, N = 7), and S (N = 13) lines of Coturnix (ANOVA, Error bars are
SE).……………………………………….………………………………………………24
Figure 4: Basal extracellular acidification rate, glucose response and glycolysis in
myoblasts from the F (N = 12), hybrid (FFSM, N = 6; SFFM, N = 7), and S (N = 13)
lines of Coturnix (ANOVA, Error bars are SE).…………………………………………25
Figure 5: MitoTracker florescence per cell area in myoblastas from the F, hybrid (FFSM,
SFFM), and S lines of Coturnix (ANOVA, Error bars are SE).…………………..26
ix
Introduction:
Life-history theory posits that the schedule and duration of key events, such as
juvenile development, age of first reproduction, number of offspring produced, and rate
of senescence are molded by natural selection to produce the largest possible number of
surviving offspring. Life histories of animals tend to fall on a “slow-fast” continuum,
with some species having large numbers of offspring per reproductive event, and low
survivorship, whereas others have few offspring per reproductive event and live long
(Roff, 1992; Wiersma et al., 2012). Species on the “slow” end of this continuum are
characterized by low metabolic rates, slow growth rates, greater longevity, and lower
investment in reproduction, whereas species on the “fast” end are characterized by higher
whole-organism metabolic rates, faster growth rates, and greater investment in
reproduction (Robinson et al., 2010; Wiersma et al., 2012). Growth rate is a fundamental
parameter of an organism’s life history and varies 30-fold across bird species (Ricklefs,
1984; Williams et al., 2007; Dmitriew, 2011). Passerine nestlings from temperate sites
had growth rates that were 23% higher (Ricklefs, 1976; Oniki and Ricklefs, 1981; Stearns,
1992; Martin et al., 2011) and metabolic rates that averaged 25% higher (Ricklefs, 1973)
than nestlings of tropical species, consistent with the idea that species of birds that live in
temperate environments fall on the fast end of the “slow-fast” continuum.
Differences in growth rates among animals on opposing ends of the life history
continuum may be associated with the ability of muscle fibers to produce heat, or
1
associated with the metabolic costs attendant to faster rates of growth (Ricklefs and Stark,
1998; West et al., 2003). Two hypotheses have been proffered to explain variation in
rates of growth of nestling birds. The “growth rate-maturity” hypothesis states that
growth rate is inversely related to the development of the ability of muscle tissue to
produce heat, or as it is sometimes referred to, “the functional maturity of muscle cells”
(Ricklefs and Peters 1979; Ricklefs and Webb 1985; Dietz and Ricklefs 1997; Arendt,
1997; Ricklefs et al. 1998). In opposition the “growth rate-high metabolism” hypothesis
posits that rapid growth is possible only with a concomitant increase in resting and peak
metabolic rates of chicks (Klaassen and Drent, 1991; Williams et al., 2007).
Results from experiments to test these two hypotheses are mixed, making general
conclusions difficult. The “growth rate-maturity” hypothesis has garnered considerable
support (Stark and Ricklefs, 1998); many studies involve comparisons between precocial
birds that mature early, grow slowly, and have the ability to thermoregulate early in life,
and altricial birds that mature late and grow fast (Choi et al., 1993; Ricklefs et al., 1994;
Stark and Ricklefs, 1998). When cold-stressed, the thermoregulatory capacity of muscle
tissue from nestlings of two precocial species, Japanese quail (C. coturnix japonica) and
the northern bobwhite quail (Colinus virginianus), and one altricial species, the European
starling (Sturnus vulgaris), was inversely related to growth rate, consistent with the
“growth rate – maturity” hypothesis (Choi et al., 1993). Additionally, during the growing
period, muscle maturity, as measured by dry weight, water content, and pyruvate kinase
activity in the muscle tissue, was higher in quail than in starlings, supporting “growth
rate-maturity” hypothesis (Ricklefs, 1967; Ricklefs and Web, 1985; Ricklefs et al., 1994).
In contrast, a study on Arctic shorebirds measured resting and peak metabolic rates
2
during development in seven species of shorebird chicks that ranged in size from the least
sandpiper (Calidris minutilla; adult mass 20–22 g) to the whimbrel (Numenius phaeopus;
380 g) and found no evidence that chicks of shorebirds with fast growth rates had lower
resting or peak metabolic rates, as would be predicted by the “growth rate–maturity”
hypothesis. Instead, their data suggested that pectoral muscles from faster growing
species resulted in increased thermogenic capacity, consistent with the “fast growth–high
metabolism” hypothesis (Williams et al., 2007). Additional insights into understanding
the relationship between growth rate and metabolic rate can be achieved through studies
that integrate molecular and cellular information with whole-organism growth rates.
Although it is thought that basic cell physiology may underlie many life history
traits, the connection between life history and physiology of organisms remain elusive
(Stearns 1992; Ricklefs and Wikelski 2002; Speakman, 2008). In vertebrates, cells
produce ATP through substrate phosphorylation during glycolysis and Kreb’s cycle, or
by oxidative phosphorylation in the mitochondria. In the cytosol glucose is broken down
into pyruvate producing protons, and thus pH of the surrounding media of the cell can be
monitored as a proxy for the rate of glycolysis (Sansbury et al. 2011; Hill et al., 2012). In
alignment with the “growth rate-maturity” hypothesis, slower growth rate would allow
for muscle cells with greater functional maturity, resulting in greater demand for
chemical potential energy in the form of ATP, and, presumably, increased heat
production and oxygen consumption. Alternatively, the “growth rate–high metabolism”
hypothesis posits that high growth rates require high levels of ATP that would result in
increased heat production and oxygen consumption (Millward et al., 1976; Peterson et
al., 1999).
3
Although metabolic rate, skeletal muscle development and growth rate have been
studied in whole-organisms, the link between an organism’s growth rate and metabolic
rate on a cellular level remains obscure. Cell lines held in a common environment, but
established from chicks that grow at different rates, would allow for examination of the
intrinsic differences in the cellular metabolic profile as a result of differences in growth
rates. The link between life history and physiology on the cellular level in birds has been
examined using fibroblasts as a model cell system. Fibroblasts from tropical Panamanian
birds had lower metabolic rates than did phylogenetically paired counterparts from
temperate Ohio (Williams, 2010; Jimenez et al., in review). Fibroblasts, however, are
viewed as cells that contribute relatively little to whole-organism metabolic rate, in
contrast to cells of muscle and liver (Brown et al., 2007). Among endotherms, striated
muscle constitutes the largest fraction of body mass, and despite a low tissue-specific
metabolic rate, muscle contributes more to whole-organism basal metabolism than any
other tissue (Krebs, 1950, Martin and Furhman 1955). Therefore, the relationship
between growth rate and metabolic function may be profitably explored by studying
skeletal muscle cells of individuals of the same species, but with markedly different rates
of growth (Martin and Fuhrman 1955; Taylor et al., 1982; Rolfe and Brown 1996). To
integrate information on cellular metabolic rate and growth rate of muscle, I established
primary muscle cell cultures from two strains of quail with markedly different rates of
growth.
Japanese quail (Coturnix coturnix japonica) have been artificially selected for
over 60 generations for either fast or slow growth (Ricklefs and Marks, 1985; Khaldari et
al, 2010). In previous studies the fast (F) line reached a body mass of 271.7 grams at the
4
age of four-weeks, more than double the slow (S) line at 127.5 grams for the same growth
period, and had a higher growth rate constant (K) of 0.096, compared with a K of 0.075
for the slow line (Ricklefs and Marks 1985). K is a measure of how rapidly a chick grows
to asymptotic mass (Ricklefs, 1967; Austin et al., 2011). The difference of 22% in growth
rate between the F and S strains of quail is similar to the 23% difference in growth rate
between tropical and temperate species (Ricklefs, 1976; Ricklefs and Marks, 1985; Oniki
and Ricklefs, 1981; Stearns, 1992; Martin et al., 2011). To test the idea that the metabolic
capacity of muscle cells may be compromised by fast growth rates, in accordance with
the “growth rate-maturity” hypothesis, or whether it is elevated as in agreement the
“growth rate-high metabolism” hypothesis, I measured the metabolic profile of cultured
myoblasts from the two strains of quail. In addition, I searched for an association between
high rates of cell metabolism and mitochondrial density. As cell size may also influence
metabolic rate, I measured the diameter of cells in culture (West et al., 1997; Savage et
al., 2007).
The genetic mechanisms underlying life history traits, such as growth rate, and
their relationship to metabolism are not well understood. Mitochondrial DNA (mtDNA)
is inherited solely from the female and genes within the mitochondria code for 13
polypeptide proteins that are involved in oxidative phosphorylation (Schefler, 1999).
Studies have emphasized the importance of these genes in the efficiency of energy
production by oxidative phosphorylation, suggesting a link between the genes coding for
proteins in the mitochondria and life history traits (McBride et al., 2006; Ballard et al,
2007; Tieleman et al., 2009; Towes et al., 2013). At least 70 nuclear-encoded peptides
are imported into the mitochondria and assembled with the subunits encoded by mtDNA
5
to produce functional complexes in the electron transport chain (Blier et al., 2001;
Ballard and Rand, 2005; Das, 2006). Additionally, the fission and fusion of mitochondria
in cells are regulated by a nuclear-encoded mitochondrial transcription factor (Scheffler,
1999; Ekstrand et al., 2004). It is not clear whether the mitochondrial encoded subunits,
the nuclear-encoded subunits or a match between the mtDNA and nuclear DNA are most
important for regulating metabolic rates (Ballard and Whitlock, 2004; Tieleman et al.,
2009).
To test whether a mismatch in mtDNA and nuclear DNA affects cell metabolism,
I crossed females from the slow line with males from the fast line (SFFM), and females
from the fast line with males from the slow line (FFSM), and cultured the myoblasts of
their chicks. I then explored whether mtDNA inherited from the female had an influence
on the rate of metabolism of the cell (Tieleman et al., 2007; Schefler, 1999; Towes et al.,
2013).
I found that myoblasts from the fast line had higher metabolic rates, and a greater
density of mitochondria, than did myoblasts from the slow line in accordance with the
“growth rate-high metabolism” hypothesis. Myoblasts from the hybrid lines had
metabolic rates and mitochondrial densities that were statistically indistinguishable, but
significantly different from cells from the fast and slow line. Metabolic rates and
mitochondrial densities from the hybrid lines were intermediate to the fast and slow lines
indicating that oxygen consumption, glycolysis, and mitochondrial density are controlled
by nuclear DNA-encoded processes.
6
Methods:
Quail Lines:
The four lines of Japanese quail (Coturnix coturnix japonica) were acquired from
the Department of Poultry Science at the University of Arkansas. The fast line (F) was
selected for post-hatch growth rate for over 60 generations and the slow, or control, line
(S), was not selected for any trait, but was kept in similar conditions to the fast line,
including being fed an identical diet. A backcross of fast females, slow males (FFSM) or
slow females, fast male (SFFM) was preformed to form the hybrid lines. I incubated eggs
from each line for 16 days at 37.5oC and 60% humidity. Within 24 hours of hatch, chicks
were sacrificed and muscle tissue was dissected for isolation of myoblasts.
Growth Rate Calculations:
I weighed chicks from each line daily for 56 days, starting with day zero, the day
of hatch. Next, I calculated Gompertz growth curves in Sigma Plot 12.2 (Systat Software,
San Jose, CA) based on:
m(t) = Ae-k(t-ti)
where m(t) was the body mass (g) at age t (days), A was the asymptotic body mass (g), ti
was the time at the inflection point of the curve, and K was the growth rate constant
(1/days). I fixed the asymptote at the average adult mass for each line (Ricklefs, 1967;
Austin et al., 2011).
Cell Culture:
7
Because muscle cells are terminally differentiated and non-mitotic, all cultured
muscle cells result from quiescent mononucleated myogenic cells called satellite cells.
These cells lie between the sarcolemma and basement membrane of all muscle fibers and,
when activated in response to muscle growth or regeneration, migrate into the muscle
fiber and divide into satellite-cell derived myoblasts that proliferate until differentiating
into mature myofibers (Mauro, 1961; Hawke and Garry, 2001; Zammit et al., 2006).
I cultured myoblasts using a modified technique developed for turkey satellite cell
culture by Velleman et al. (2000). Cells were liberated from the basal lamina by
immersing muscle tissue in 0.8mg/mL Pronase solution for 40 minutes. Following
enzymatic digestion, I separated cells from muscle debris by differential centrifugation.
Pre-plating techniques were used to reduce contamination by other cell types, specifically
fibroblasts because these cells tend to adhere to a culture plate before myoblasts. Cell
proliferation was optimized in cell cultures grown on gelatin-coated plates in the presence
of a plating media containing Dulbecco's Modified Eagle Medium, 10% Chicken Serum
(CS), 5% Horse Serum (HS), 1% Antibiotic/Antimycotic (AbAm), and 1% Gentamicin.
After 24 hours, I replaced the plating media with a feeding media containing
McCoy’s 5A, 10 % CS, 5 % HS, 1 % AbAm, 0.1 % Gentamicin and 20 ng/mL basic
Fibroblast growth factor. Fibroblast growth factor is a potent stimulator of skeletal
muscle cell proliferation, and prevents the differentiation of these cells (Velleman et al.,
2003). At 60% confluence I passaged the cells using 0.05% trypsin and froze them in
liquid nitrogen. Two days before analysis on the Seahorse XF96, cells were thawed and
plated in feeding media.
8
I verified that the cells I cultured were myoblasts by immunostaining with Pax7
and MyoD (Halevy et al., 2004). Quiescent satellite cells express the Pax7 transcription
factor, and once activated into myoblasts will also express the transcription factor MyoD
(Coutinho et al., 1993; Zammit et al., 2006). Cells were plated at 20,000 cells on Plus
Microscope Slides (Fisher Scientific) for two days in feeding media. Media was removed
and cells were fixed with 4% paraformaldehyde before blocking overnight at 4oC. Cells
were incubated with the primary antibody Pax7 supernatant or D7F2 supernatant for
MyoD (Developmental Studies Hybrodoma Bank) overnight at 4 oC, followed by
secondary antibody incubation Alexa Fluor 488-conjugated AffiniPure Rabbit AntiMouse IgG (H+L). Images were acquired on a Fluoview Olympus 1000 filter confocal
microscope at 40x.
Metabolic Rate and Cell Size:
I measured oxygen consumption rates (OCR) in myoblasts using a Seahorse
XF96. The XF96 sensor cartridge was hydrated with 1 ml calibration buffer per well
overnight at 37oC (Hill et al. 2012). Previous to the assay, the cells were incubated in a
high glucose media to mimic the high glucose concentrations in plasma of wild birds
(Umminger, 1977; Holmes et al., 2001). A metabolic profile was obtained by measuring
basal respiration followed by injections of oligomyosin A, Carbonylcyanide-ptrifluoromethoxyphenylhydrazone (FCCP), and a combination of rotenone and
Antimycin A. Oligomyosin A inhibits ATP synthase and provides an estimate of proton
leak across the inner mitochondrial membrane plus any oxygen consumption attributable
to non-mitochondrial sources (Sansbury et al. 2011). When non-mitochondrial O2
consumption is subtracted from OCR obtained after the addition of oligomycin, a
9
measurement of proton leak can be estimated (Sansbury et al. 2011). Driven by the
magnitude of the proton motive force across the inner mitochondrial membrane (∆p), the
rate of proton leak is determined by the inner membrane conductivity to protons at a
given ∆p (Brown and Brand 1991). Oligomycin induces a respiratory condition similar to
that of state-4 respiration, which increases mitochondrial membrane potential where ∆p is
maximal and thus proton leak rate is at or near its maximum (Brown, 1990; Porter et al.
1999, Sansbury et al. 2011). These measurements are especially useful for examining
mitochondrial responses to a given treatment and comparing treatment groups such as
birds from tropical and temperate environments. FCCP is a proton ionophore that makes
the inner mitochondrial membrane permeable to protons, and thus the electron transport
chain runs at a maximum to restore the gradient. Rotenone inhibits Complex III and
Antimycin A inhibits Complex I in the electron transport chain and provides a measure of
non-mitochondrial oxygen consumption (Hill et al., 2012).
I measured extracellular acidification rates (ECAR) in a Seahorse XF96
glycolysis assay. After incubating cells in a media without glucose and measuring basal
ECAR, I then exposed cells to an injection into the media of 10 mM glucose for a
measure of glycolysis. The assay ended with an injection of 2-deoxyglucose (2-DG), a
molecule that binds competitively to glucose hexokinase, the first enzyme in the
glycolytic pathway. Addition of 2-DG stops glycolysis, allowing measurement of nonglycolytic acidification rates (Hill et al., 2012). Immediately after the assay, images were
taken at 40x on a dissecting microscope and analyzed to determine size of the cells from
each quail line using Image J.
Mitochondrial Density:
10
Cells were stained using 25 ug/mL DAPI and MitoTracker Deep Red 694. DAPI
preferentially stains the A-T rich regions of DNA to illuminate the nucleus in cells, and
MitoTracker DeepRed 694 is a far red-fluorescent dye (abs/em ~644/665 nm) that stains
mitochondria in live cells. Cells were fixed with 4% paraformaldahyde directly after
staining. Cell Area per florescence intensity was used to estimate mitochondrial density
of myoblasts from the four lines of quail. Images were acquired on a Fluoview Olympus
1000 filter confocal microscope at 40x. Image J and FIJI were used for image analysis.
Statistics:
All metabolic parameters, cell size, and MitoTracker Florence from the four lines
(F, S, FFSM, SFFM) were analyzed using an ANOVA in SPSS. Post hoc analysis was
carried out using Ryan-Einot-Gabriel-Welsch F-test for unequal group sizes. As cell size
was not different among groups, I did not include it as a covariate. All results are
presented as mean ± SE.
11
Results:
Growth Rates of Quail Lines:
The F line had a growth rate constant of 0.138 ± 0.002, whereas the S had a
constant of 0.113 ± 0.003, an 18% difference that was significant (ANOVA, p < 0.05).
The hybrid lines, FFSM and SFFM, had intermediate growth rates compared with the fast
and slow line, and identical growth rates of 0.128 ± 0.002 compared with each other
(ANOVA, p < 0.05, Fig. 1).
Pax7 and MyoD:
Pax7 and MyoD were expressed in our cells (Fig. 2), confirming that the cells
used in my experiments were myotubes (Zammit et al., 2006).
Metabolic Rate Analysis:
FAST vs SLOW
Basal OCR, proton leak, maximal uncoupled respiration and non-mitochondrial
OCR were 65-75% higher in myoblasts from the F line than from myoblasts from S line
of quail (ANOVA, p <0.001, Fig. 3). Basal ECAR, glucose response and glycolysis were
55-70% higher in myoblasts from the F line than the S line (ANOVA, p <0.001, Fig. 4).
Hybrid Lines
For all measures of oxygen consumption and glycolysis, there were no differences
between the two hybrid lines (Fig.3, Fig. 4). Basal oxygen consumption and basal ECAR
in myoblasts from the hybrid lines were intermediate to myoblasts between the F and S
lines (ANOVA, p <0.05, Fig. 3, Fig. 4). Proton leak, maximal uncoupled respiration,
12
non-mitochondrial OCR, glucose response and glycolysis in myoblasts from the hybrid
lines were 60-70% higher than the S line, but not significantly different from the F line
(ANOVA, p < 0.05, Fig. 3, Fig. 4).
Mitochondrial Density:
The F line had 17% higher mitochondrial density per cell area than the S line
(ANOVA, p < 0.001, Fig. 5). Mitochondrial density per cell area in the two hybrid lines
were not significantly different from F line, but was 14% higher than the S line (ANOVA,
p < 0.05, Fig. 5).
13
Discussion:
Myoblasts from quail selected for fast growth rate had higher rates of oxygen
consumption than the control cell line (Fig.3). These data indicate that all parameters of
mitochondrial metabolism were higher in myoblasts from quail with faster growth, in line
with the “growth rate-high metabolism” hypothesis (Klaassen and Drent, 1991; Williams
et al., 2007). Cells from the F line also had higher extracellular acidification rates, most
likely a result of increased demand for substrates for the oxidative phosphorylation
pathway (Fig. 4). These data correspond with previous findings in studies of wholeorganism metabolic rate. In a study on gulls and terns (Laridae), petrels
(Procellariiformes), and multiple families of shorebirds (Charadriformes), relative
postnatal growth rate was positively associated with resting metabolic rate (Drent and
Klaassen, 1989, Williams et al. 2007).
Metabolic rates of cells are controlled by many factors including the number
and/or density of mitochondria, permeability of the inner mitochondrial membrane to
protons, rate of enzyme reactions, or composition of lipids in the inner mitochondrial
membrane, especially the number and location of double bonds in the fatty acids of the
lipids (Rubin, 1975; Fell et al., 1992; Steyermark et al., 2005; West et al., 2003; Hulbert
and Else, 1999; Hulbert et al., 2007). Mitochondrial density was higher in myoblasts
from the F line than myoblasts from the S line. Mitochondrial density in the hybrid lines
was higher than the S line, but not significantly different from the F line (Fig.5). The
larger magnitude of change in basal OCR from the S line to the two hybrid lines versus
14
the two hybrid lines to the fast line F line may be, at least in part, explained by
mitochondrial density.
For all metabolic parameters, the two hybrid lines had similar rates of oxygen
consumption and glycolysis (Fig.3, Fig. 4). They also had similar mitochondrial densities
(Fig. 5). Mitochondrial transcription factor is crucial for regulating the replication and
expression of mtDNA, and is encoded by the nuclear genome (Scheffler, 1999; Ekstrand
et al., 2004). When mitochondrial transcription factor A was overexpressed or knocked
out in mice, mtDNA copy number was directly proportional to the total level of
mitochondrial transcription factor A protein expressed in tissues (Ekstrand et al., 2004;
Pohjoismäki et al., 2006). My findings that mitochondrial density was higher in
myoblasts from faster growing quail align with these studies, indicate that nuclear factors
are important for determining mitochondrial density and metabolic rate in myoblasts.
The literature is conflicted about the connection between mtDNA and metabolic
rate. A study on stonechats demonstrated differences in whole-organism basal metabolic
rate among hybrids with contrasting parental configurations, highlighting the importance
of a genetic match between mitochondrial and nuclear genomes (Tieleman et al., 2009).
In contrast, there were no differences in mitochondrial density or oxygen consumption
rate between northern migratory and southern resident yellow-rumped warblers with
different mtDNA sources, consistent with our findings. There was a difference in ratio of
State III to State II respiration, indicating that warblers with mtDNA from more northern
individuals had mitochondria that were more coupled and more efficient (Towes et al.,
2013). In a study between tropical and temperate birds, the rate of amino acid
substitutions varied in Complex I and Complex IV in the oxidative phosphorylation
15
pathway, and in 10 of the 13 mitochondrial genes that code for complexes in the
oxidative phosphorylation pathway (Fries, 2009). Although it is not clear whether these
genes translate into functional differences in the complexes of the electron transport chain,
it is possible that changes in the genes that code for these complexes may underlie
differences in metabolic rate and life history between tropical and temperate birds (Fries,
2009). Black-capped chickadees (Poecile atricapillus) had higher whole-organism
metabolic rates than Carolina chickadees (Poecile carolinensis), and hybrids between
these species have metabolic rates that were higher than Carolina chickadees, but not
different from the black-capped chickadees, similar to our findings in myoblasts from
hybridized fast and slow growing quail (Olson et al., 2010). Although our study focused
only on growth rate as a life history trait, our finding that there were similar cellular
metabolic rates between the hybrid lines, and that these rates were intermediate to
ancestral rates indicated that metabolic rate resulted predominantly from nuclear DNAencoded processes. Additionally, we demonstrated that higher metabolic rates are an
intrinsic property of high growth rates.
In conclusion, I have shown that birds with faster growth rates have higher
cellular metabolic rates in accordance with the “growth rate-high metabolism” hypothesis,
and high metabolic rate is, at least in part, a result of higher mitochondrial density in
myoblasts from fast growing individuals. Additionally, I demonstrated that oxygen
consumption, glycolysis, and mitochondrial density in myoblasts of quail selected for
different rates of growth results predominantly from nuclear DNA-encoded processes.
16
References:
Arendt, J.D. 1997. Adaptive intrinsic growth rates: an integration across taxa. The
Quarterly Review of Biology 72: 149-177.
Austin, S. H., Robinson, T. R., Robinson, W. D., and Ricklefs, R. E. (2011). Potential
biases in estimating the rate parameter of sigmoid growth functions. Methods in
Ecology and Evolution, 2(1), 43-51.
Ballard, J. W. O., and Whitlock, M. C. 2004. The incomplete natural history of
mitochondria. Molecular ecology, 13(4), 729-744.
Ballard, J. W. O., and Rand, D. M. 2005. The population biology of mitochondrial DNA
and its phylogenetic implications. Annual Review of Ecology, Evolution, and
Systematics, 621-642.
Ballard J.W.O., Melvin R.G., Katewa S.D., Maas K. 2007. Mitochondrial DNA variation
is associated with measurable differences in life-history traits and mitochondrial
metabolism in Drosophila simulans. Evolution 61, 1735-1747.
Blier, P. U., Dufresne, F., and Burton, R. S. 2001. Natural selection and the evolution of
mtDNA-encoded peptides: evidence for intergenomic co-adaptation. TRENDS in
Genetics, 17(7), 400-406.
Brown, G. C., and Brand, M. D. 1991. On the nature of the mitochondrial proton leak.
Biochimica et Biophysica Acta (BBA)-Bioenergetics, 1059(1), 55-62.
Brown, G. C. 2001. Regulation of mitochondrial respiration by nitric oxide inhibition of
cytochrome c oxidase. Biochimica et Biophysica Acta (BBA)-Bioenergetics, 1504(1),
46-57.
Brown, M. F., Gratton, T. P., and Stuart, J. A. 2007. Metabolic rate does not scale with
body mass in cultured mammalian cells. American Journal of Physiology-Regulatory,
Integrative and Comparative Physiology, 292(6), R2115-R2121.
Choi, I. H., Ricklefs, R. E., and Shea, R. E. 1993. Skeletal muscle growth, enzyme
activities, and the development of thermogenesis: a comparison between altricial and
precocial birds. Physiological Zoology, 455-473.
Coutinho, L. L., Morris, J., Marks, H. L., Buhr, R. J., and Ivarie, R. 1993. Delayed somite
formation in a quail line exhibiting myofiber hyperplasia is accompanied by delayed
expression of myogenic regulatory factors and myosin heavy chain. Development,
117(2), 563-569.
Das, J. 2006. The role of mitochondrial respiration in physiological and evolutionary
adaptation. Bioessays, 28(9), 890-901.
Dietz, M., and R. E. Ricklefs. 1997. Growth rate and maturation of skeletal muscles over
a size range of galliform birds. Physiological Zoology 70(5): 502-510.
Dmitriew, C. M. 2011. The evolution of growth trajectories: what limits growth rate?.
Biological Reviews, 86(1), 97-116.
Drent R. and M. Klaassen. 1989. Energetics of avian growth: the causal link with BMR
and metabolic scope. Pp. 349-359 in C. Bech and R.E. Reinertsen, eds. Physiology of
Cold Adaptation in Birds. Plenum, New York and London.
17
Ekstrand, M. I., Falkenberg, M., Rantanen, A., Park, C. B., Gaspari, M., Hultenby, K.,
Rustin, P. and Larsson, N. G. 2004. Mitochondrial transcription factor A regulates
mtDNA copy number in mammals. Human molecular genetics, 13(9), 935-944.
Fell, D. A. 1992. Metabolic control analysis: a survey of its theoretical and experimental
development. Biochemical Journal, 286(Pt 2), 313.
Fries, A. C. 2009. The molecular evolution of mitochondrial oxidative phosphorylation
genes in the Order Passeriformes (Doctoral dissertation, The Ohio State University).
Halevy, O., Piestun, Y., Allouh, M. Z., Rosser, B. W., Rinkevich, Y., Reshef, R.,
Rozenboim, I., Wleklinski-Lee, M. and Yablonka-Reuveni, Z. 2004. Pattern of Pax7
expression during myogenesis in the posthatch chicken establishes a model for
satellite cell differentiation and renewal. Developmental Dynamics, 231(3), 489-502.
Hawke, T.J., and D.J. Garry. 2001. Myogenic satellite cells: physiology to molecular
biology. Journal of Applied Physiology 91: 534-551.
Hill, B. G., Benavides, G. A., Lancaster, J. R., Ballinger, S., Dell’Italia, L., Zhang, J., and
Darley-Usmar, V. M. 2012. Integration of cellular bioenergetics with mitochondrial
quality control and autophagy. Biological Chemistry. 393(12), 1485–1512. DOI:
10.1515/hsz-2012-0198
Holmes, D. J., Flückiger, R., and Austad, S. N. 2001. Comparative biology of aging in
birds: an update. Experimental gerontology, 36(4), 869-883. DOI: 10.1016/S05315565(00)00247-3
Hulbert, A. J., and Else, P. L. 1999. Membranes as possible pacemakers of metabolism.
Journal of theoretical biology, 199(3), 257-274.
Hulbert, A. J., Pamplona, R., Buffenstein, R., and Buttemer, W. A. 2007. Life and death:
metabolic rate, membrane composition, and life span of animals. Physiological
Reviews, 87(4), 1175-1213.
Jimenez, A.G., J. Van-Brocklyn, M. Wortman, and J.B. Williams. Cellular metabolic rate
is influenced by life-history traits in tropical and temperate birds. In Review.
Khaldari, M., A. Pakdel, H. Mehrabani Yeganeh, A. Nejati Javaremi, and P. Berg. 2010.
Response to selection and genetic parameters of body and carcass weights in Japanese
quail selected for 4-week body weight. Poultry Science 89: 1834-1841.
Klaassen, M., and R. Drent. 1991. An analysis of hatchling resting metabolism: in search
of ecological correlates that explain deviations from allometric relations. The Condor
93: 612-629.
Krebs, H.A. 1950. Body size and tissue respiration. Biochimica et Biophysica 4: 249-269.
Mauro, A. 1961. Satellite cell of skeletal muscle fibers. Journal of Biophysical and
biochemical cytology 9: 493-495.
Martin, A.W., and F.A. Fuhrman. 1955. The relationship between summated tissue
respiration and metabolic rate in the mouse and dog. Physiological Zoology 28: 18-34.
Martin, T. E., Lloyd, P., Bosque, C., Barton, D. C., Biancucci, A. L., Cheng, Y. R., and
Ton, R. 2011. Growth rate variation among passerine species in tropical and
temperate sites: an antagonistic interaction between parental food provisioning and
nest predation risk. Evolution, 65(6), 1607-1622.
McBride, H. M., Neuspiel, M., and Wasiak, S. 2006. Mitochondria: more than just a
powerhouse. Current Biology, 16(14), R551-R560.
Millward. D.J., and P.J. Garlick. 1976. The energy cost of growth. Proceedings of the
Nutrition Society 35 339–349.
18
Olson, J. R., Cooper, S. J., Swanson, D. L., Braun, M. J., and Williams, J. B. 2010. The
Relationship of Metabolic Performance and Distribution in Black-Capped and
Carolina Chickadees. Physiological and Biochemical Zoology, 83(2), 263-275.
Oniki, Y., and R. E. Ricklefs. 1981. More growth rates of birds in the humid New
World tropics. Ibis 123: 349-354.
Peterson, C.C., B.M. Walton, and A.F. Bennett. 1999. Metabolic costs of growth in freeliving Garter Snakes and the energy budgets of ectotherms. Functional Ecology 13:
500-507.
Pohjoismäki, J. L., Wanrooij, S., Hyvärinen, A. K., Goffart, S., Holt, I. J., Spelbrink, J. N.,
& Jacobs, H. T. 2006. Alterations to the expression level of mitochondrial
transcription factor A, TFAM, modify the mode of mitochondrial DNA replication in
cultured human cells. Nucleic acids research, 34(20), 5815-5828.
Porter, R. K., Joyce, O. J. P., Farmer, M. K., Heneghan, R., Tipton, K. F., Andrews, J. F.,
McBennett, S.M., Lund, M.D., Jensen, C.H., and Melia, H. P. 1999. Indirect
measurement of mitochondrial proton leak and its application. International journal
of obesity. Supplement, 23(6), S12-S18.
Ricklefs, R. E. 1967. A graphical method of fitting equations to growth curves. Ecology,
48(6), 978-983.
Ricklefs, R. E. 1973. Patterns of growth in birds. II. Growth rate and mode of
development. Ibis, 115(2), 177-201.
Ricklefs, R.E. 1976. Growth rates of birds in the humid new world tropics. Ibis 118: 179207.
Ricklefs, R. E., and S. Peters. 1979. Intraspecific variation in the growth rate of nestling
starlings (Sturnus vulgaris). Bird-Banding 50: 338-348.
Ricklefs, R. E. 1984. The optimization of growth rate in altricial birds. Ecology
65:1602-1616.
Ricklefs, R. E., and T. Webb. 1985. Water content, thermogenesis, and growth rate of
skeletal muscles in the European starling. Auk 102: 369-376.
Ricklefs, R. E., R. E. Shea, and I.-H. Choi. 1994. Inverse relationship between
functional maturity and exponential growth rate of avian skeletal muscle: a constraint
on evolutionary response. Evolution 48: 1080-1088.
Ricklefs, R. E. 1998. Evolutionary theories of aging: confirmation of a fundamental
prediction, with implications f or the genetic basis and evolution of life span.
American Naturalist 152: 24-44.
Ricklefs, R. E., and Starck, J. M. 1998. The evolution of the developmental mode in birds.
OXFORD ORNITHOLOGY SERIES, 8, 366-380.
Ricklefs, R. E., and M. Wikelski. 2002. The physiology-life history nexus. Trends in
Ecology and Evolution 17(10): 462-468.
Robinson, W.D., M. Hau, K.C. Klasing, M. Wikelski, J.D. Brawn, S.H. Austin, C.E.
Tarwater, and R.E. Ricklefs. 2010. Diversification of life histories in new world birds.
The Auk 127: 253-262.
Roff, D. A. 1992. The Evolution of Life Histories. Theory and Analysis. New York:
Chapman and Hall.
Rolfe, D. and Brown, G. C. 1997. Cellular energy utilization and molecular origin of
standard metabolic rate in mammals. Physiological Reviews 77: 731–758.
19
Rubin, H. 1975. Central role for magnesium in coordinate control of metabolism and
growth in animal cells. Proceedings of the National Academy of Sciences, 72(9),
3551-3555.
Sansbury, B. E., Jones, S. P., Riggs, D. W., Darley-Usmar, V. M., and Hill, B. G. 2011.
Bioenergetic function in cardiovascular cells: the importance of the reserve capacity
and its biological regulation. Chemico-biological interactions, 191(1), 288-295.
Savage, V. M., Allen, A. P., Brown, J. H., Gillooly, J. F., Herman, A. B., Woodruff, W.
H., and West, G. B. 2007. Scaling of number, size, and metabolic rate of cells with
body size in mammals. Proceedings of the National Academy of Sciences, 104(11),
4718-4723.
Schefler, I.E., 1999. Mitochondria, 1st edn. Wiley, New York.
Speakman, J.R. 2008. The physiological costs of reproduction in small mammals.
Philosophical Transactions of The Royal Society 27: 375-398.
Starck, J. M., and Ricklefs, R. E. (Eds.). (1998). Avian growth and development:
evolution within the altricial-precocial spectrum (No. 8). Oxford university press.
Stearns, S.C. 1992. The Evolution of Life Hisoties. Oxford, Oxford University Press.
Steyermark, A.C., A.G. Miamen, H.S. Feghahati and A.W. Lewno. 2005. Physiological
and morphological correlates of among-individual variation in standard metabolic rate
in the leopard frog Rana pipiens. The Journal of Experiemental Biology 208: 12011208.
Taylor, C.R., N.C. Heglund, G.M.O. Maloiy. 1982. Energetics and mechanics of
terrestrial locomotion. I. Metabolic energy consumption as a function of speed and
body size in birds and mammals. The Journal of Experimental Biology 97: 1-21.
Tieleman, B. I., Versteegh, M. A., Fries, A., Helm, B., Dingemanse, N. J., Gibbs, H. L.,
and Williams, J. B. 2009. Genetic modulation of energy metabolism in birds through
mitochondrial function. Proceedings of the Royal Society B: Biological Sciences,
276(1662), 1685-1693.
Toews, D. P., Mandic, M., Richards, J. G., and Irwin, D. E. 2013. Migration,
mitochondria and the yellow-rumped warbler. Evolution.
Umminger, B. L. 1977. Relation of whole blood sugar concentrations in vertebrates to
standard metabolic rate. Comparative Biochemistry and Physiology Part A:
Physiology, 56(4), 457-460. DOI: http://dx.doi.org/10.1016/0300-9629(77)90267-5
Velleman, S.G., X. Liu, K.E. Nestor, and D.C. McFarland. 2000. Heterogeneity in
growth and differentiation characteristics in male and female satellite cells isolated
from turkey lines with different growth rates. Comparative Biochemistry and
Physiology Part A 125: 502-509.
Velleman, S.G., Coy, C.S., Anderson, J.W., Patterson, R.A., and Nestor, K.E. 2003.
Effect of selection for growth rate and inheritance on post hatch muscle development
in turkeys. Poultry Science 82:1365-1372.
West, G. B., Brown, J. H., and Enquist, B. J. 1997. A general model for the origin of
allometric scaling laws in biology. Science, 276(5309), 122-126.
West, G.B., V.M. Savage, J. Gilloolu. B.J. Enquist, W.H. Woodruff, and J.H. Brown.
2003. Physiology: why does metabolic rate scale with body size? Nature 421: 713713.
Wiersma, P., A. Munoz-Garcia, A. Walker and J.B. Williams. 2012. Tropical birds have
a slow pace of life. Proceedings of the National Academy of Sciences 22: 9340-9345.
20
Williams, J.B., B.I. Tieleman, G.H. Visser, and R.E. Ricklefs. 2007. Does growth rate
determine the rate of metabolism in shorebird chicks living in the Arctic?
Physiological and Biochemical Zoology 80(5): 500-513.
Williams, J. B., Miller, R. A., Harper, J. M., and Wiersma, P. 2010. Functional linkages
for the pace of life, life-history, and environment in birds. Integrative and
comparative biology, 50(5), 855-868.
Zammit, P.S., T.A. Partridge, and Z. Yablonka-Reuveni. 2006. The skeletal muscle
satellite cell: the stem cell that came in from the cold. Journal of Histochemistry and
Cytochemistry 54: 1177-1191.
21
Appendix A: Figures
Fig 1. Growth rate constant (K) and asymptote (A) of chicks from the F, S, FFSM, SFFM
Body Mass (g)
lines from Day zero to Day 56
300
250
200
150
100
50
0
A = 146.1
K = 0.113
SFSM
0
300
250
200
150
100
50
0
20
A = 179.3
K = 0.128
0
20
40
60
300
250
200
150
100
50
0
300
250
200
150
100
SFFM 50
0
40
60
A = 254.8
K = 0.138
FFFM
0
40
60
A = 195.3
K = 0.128
FFSM
0
Days after Hatch
22
20
20
40
60
Fig 2. Pax7 (A) and MyoD (B) expression in myoblasts from Coturnix coturnix japonica.
Nuclei stained with DAPI in yellow. Images taken with Fluoview confocal microscope at
40x.
23
Fig 3. Basal oxygen consumption rate, proton leak, max oxygen consumption and nonmitochondrial oxygen consumption in myoblasts from the F (N = 12), hybrid (FFSM, N =
6; SFFM, N = 7), and S (N = 13) lines of Coturnix (ANOVA, Error bars are
SE
S
SFFM
FFSM
F
60
40
20
24
OC
R
No
n-M
ito
Ma
xO
CR
Pro
ton
Le
ak
0
Ba
sal
OC
R
OCR (Pmole/ Min)
80
Fig 4. Basal extracellular acidification rate, glucose response and glycolysis in myoblasts
from the F (N = 12), hybrid (FFSM, N = 6; SFFM, N = 7), and S (N = 13) lines of Coturnix
(ANOVA, Error bars are
ECAR (mpH/ Min)
200
150
100
Slow
SFFM
FFFM
Fast
50
SE
25
Gl
yc
ol
ys
is
Gl
uc
os
eR
es
po
ns
e
Ba
sa
lE
CA
R
0
Fig 5. Figure 5: MitoTracker florescence per cell area in myoblastas from the F, hybrid
Area/Relative Florescence
(FFSM, SFFM), and S lines of Coturnix (ANOVA, Error bars are SE).
8
6
4
2
0
26