Intracellular convection, homeostasis and metabolic regulation
Department of Zoology, University of British Columbia, Vancouver, BC, Canada V6T 1Z4
Accepted 17 March 2003
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Summary |
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Key words: metabolic regulation, homeostasis, intracellular, diffusion, intracellular perfusion, oxygen delivery, oxygen regulation
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Contrasting demands of homeostasis and tissue work |
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Current popular interpretations of such large scale differences in steady
state energy turnover are regulated assume cybernetic feedback control
circuitry. The standard theory is summarized in
Fig. 1 (see
Balaban, 1990;
Chance et al., 1986
;
Connett, 1988
;
Connett et al., 1985
;
Connet and Honig, 1989
;
From et al., 1990
;
Kushmerick et al., 1992
;
Rumsey et al., 1990
).
Following the arrival of activation signals at the muscle cell, an increase in
ATP demand `turns on' cell ATPases, whose catalytic function leads to
increased product (ADP, Pi, H+) concentrations; the
latter then serve as substrates and as positive feedback signals for
accelerating ATP supply pathways (Fig.
1). Metabolites such as ADP and Pi are thought to be
pivotal in mitochondrial metabolic control, but powerful activation of cell
work also demands a proportional activation of catalytic function at
essentially every enzyme step involved in the ATP supply and demand pathways.
Hence, if substrate, product and modulator concentration changes are to be the
main mediators of large (100-fold or more) changes in ATP turnover rate, one
would anticipate equally large perturbations in pool sizes of the numerous
intermediates. This would be especially true for regulation processes based on
MichaelisMenten kinetics, where the kinetic order cannot exceed 1
[Atkinson, 1977
,
1990
; i.e. percentage change in
catalytic rate (ATP turnover rate) cannot exceed the percentage change in
substrate concentration driving the metabolic rate change
(Hochachka and Matheson, 1992
;
Hochachka, 1994
)]. Whereas
`homeostasis' demands `constancy of the internal milieu', muscle work would
thus appear to require drastic changes in intracellular conditions, the degree
of perturbation being somehow related to the intensity of work. The problem
(and paradox) is how the conflicting demands of homeostasis versus
metabolic regulation are resolved in muscle during different work and
metabolic states; i.e. how muscles sustain both metabolic homeostasis and
metabolic regulation.
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Two views or approaches dominate the metabolic regulation field |
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The Model I approach |
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To explain this precision and integration of linked sequences of enzyme
function, several regulatory models are currently being evaluated by workers
in this field (Hochachka et al.,
1998). These include: (i) simple feedback and mass action controls
(the standard model above), (ii) allosteric controls, (iii) models involving
the regulation of eo (the concentration of functional
catalytic sites) in various ways, such as by alteration in protein
interactions (as in actomyosin ATPase), change in phosphorylation state (as in
pyruvate dehydrogenase), change in redox state (as in V-type ATPases), by
Ca2+ activation, or translocation from inactive to an active
intracellular location (as in glucose transporters), and (iv) various versions
of metabolic control analysis originally introduced over a decade ago (these
make minimal assumptions at the level of enzyme mechanism). The diversity of
mechanisms and models of enzyme regulation arise in part from the differing
requirements at different enzyme loci in metabolism.
Enzyme catalytic and regulatory properties determine control
requirements for specific metabolic reactions
Many, and perhaps most, enzymes in metabolic pathways obey
MichaelisMenten kinetics and operate under near-equilibrium conditions
(at equilibrium, of course, forward and reverse fluxes for such enzyme
reactions are the same and there can be no net forward or reverse flux).
During pathway and enzyme activation
(Staples and Suarez, 1997),
net forward flux for such enzymes is achieved by modest adjustments in
substrate(s)/product(s) concentration ratios. Several requirements arise for
such enzymes in vivo. First of all, since the chemical potential
driving the net forward reaction is usually modest, large amounts of enzyme
are the rule in order to be able to match the flux rates required in
vivo. This is achieved by high enzyme content or by high
kcat (turnover number per active site on the enzyme), or
by both mechanisms at once. Traditionally, for most metabolic biochemists,
this is the explanation for `near-equilibrium' enzymes occurring at relatively
enormous concentrationsthe higher the enzyme concentration, the closer
to equilibrium is in vivo functionand for `near-equilibrium'
enzymes being catalytically especially efficient. Triose phosphate isomerase
(TPI) is one such example. In tissues with a high (aerobic or anaerobic)
glycolytic potential (such as various fast twitch muscles) the enzyme occurs
at almost mmol l-1 concentrations and its high
kcat means that its in vivo activity (in terms of
µmol substrate converted to product g-1 min-1) is
enormous. In fact, studies carried out over two decades ago (see Hochachka,
1980
,
1994
;
Fersht, 1985
) showed that
selection for high efficiency has pushed this enzyme towards a state of
catalytic `perfection': any further improvement in the enzyme's efficiency
would not be expressed in higher reaction rates because it would be limited by
diffusion-based enzymesubstrate encounter.
Most metabolic pathways also contain allosteric enzymes that function under
quite different conditions and are much more subject to regulation. Allosteric
regulation (Fersht, 1985;
Hochachka and Somero, 1984
) is
based on positive or negative modulators binding at sites other than the
active site (hence the term `allosteric' rather than isosteric, which would
apply to modulators competing with substrate at the active site).
Phosphofructokinase (PFK) in glycolysis is a quintessential example of an
allosteric enzyme. PFK in vivo operates far from equilibrium, tending
to work largely in the forward direction, catalyzing the reaction
F6P + ATP ADP + F1,6P.
The enzyme is product-activated by both ADP and fructose-1,6-phosphate
(F1,6P), by fructose-2,6-phosphate (F2,6P), AMP, ammonia and high pH.
Fructose-6-phosphate (F6P) saturation curves are sigmoidal with an interaction
coefficient, n, of 2 or more. This means that when one F6P is bound
the affinity of the next site for F6P rises; in this sense, F6P is both a
substrate and an activator of the enzyme acting upon it. Most modulators
affect PFK by shifts in substrate affinities, rather than in
max, except for the
cosubstrate ATP: at high concentrations ATP becomes a substrate inhibitor of
the reaction. Taken together, these regulators add up to a pattern in which
energy-rich conditions downregulate PFK activity, while energy-depleted
conditions upregulate PFK activity. These properties mean that the chemical
potential driving the forward reaction tends to be very high and high fluxes
can therefore be sustained with lower enzyme activities (i.e. lower enzyme
concentrations are required and the lower kcat values are
quite tolerable).
Still other enzymes are regulated essentially in onoff fashion. Pyruvate dehydrogenase (PDH), for example, is regulated by phosphorylationdephosphorylation mechanisms (by protein kinases and protein phosphatases, respectively). The ATP-dependent PDH kinase-catalyzed reaction converts PDH to the low-activity (off) form, which is favored under energy saturated conditions, while a phosphatase hydrolyzes this bond, releasing Pi and converting PDH back to its high-activity (on) form. This may be viewed as a kind of coarse control system; fine control of PDH catalytic activity is achieved by NADH and acetylCoA product inhibition. As in the case of PFK, PDH functions far from equilibrium and the chemical potential driving the forward reaction is high. This means that the same maximum in vivo flux capacities can be matched by lower enzyme concentrations and lower catalytic efficiencies than in the case of near-equilibrium enzymes such as TPI.
Similar phosphorylation-based onoff control types of enzymes
activity were first discovered for glycogen phosphorylase in the 1960s and
have been shown for numerous other enzymes. Although protein kinase and
phosphatase couplets are the most common, they are not the only means by which
enzymes can be held in either on or off states. Two other mechanisms to
briefly mention are those based on proteinprotein interactions and on
redox change in SH residues. Actomyosin ATPase is an example of the
former (Grabarek et al., 1992)
and V-type ATPAse of the latter (Harvey
and Wieczorek, 1997
). At rest actomyosin ATPase in skeletal muscle
is catalytically inert, held that way by troponin c. Ca2+
activation (during excitationcontraction or EC coupling) relieves
troponin c binding and unleashes this enzyme's huge catalytic activity. Low-
and high-activity forms of V-type ATPases are similarily regulated by hypoxia
or other parameters that change local redox conditions (reducing the SS
bridge to SH). Because the concentration of catalytically active sites
(eo) is effectively low in the off state and high in the
on state, this category of mechanisms is referred to as eo
regulation of enzyme activity (Hochachka
and Matheson, 1992
). The exceptionally huge metabolic flare up
associated with electric organ discharge in electric fishes may supply a
particularly clear example of this kind of regulatory mechanism (Blum et al.,
1990, 1991
).
Homeostasis of pathway intermediates
The largest problem (and paradox) facing metabolic regulation
theory
Given this diversity in the nature of enzymes that in vivo are
linked together to form single metabolic or physiological functions, it is all
the more perplexing to find, and challenging to account for, the empirical
observation that enzymes linked in linear series to form metabolic pathways
are so exquisitely integrated that large changes in pathway flux are sustained
with minimal perturbation of pathway substrates and products. [ATP] is almost
perfectly homeostatic under most conditions (except under very extreme
O2-limited or fatigue conditions) and other intermediates in
pathways of ATP supply or demand are stabilized within less rigorously
controlled concentration ranges (where these changes may reflect change in ATP
turnover rates, but clearly cannot cause them. A cursory count shows that the
percentage changes in concentrations of >60 substrates and intermediates
(in glucose, fat and amino acid catabolic pathways) quantified to date are far
less than the percentage changes in flux rates with which they correlate. This
is observed over and over again, for low-capacity and high-capacity pathways.
Although on first analysis oxygen appeared to be the only metabolite that was
an exception, even this crucial metabolite turns out to be impressively
homeostatic.
Aerobic metabolic rate and oxygen delivery
(O2) are closely related
There is a huge literature on how O2 functions both as a
substrate and as a potential regulator of tissue metabolism over varying times
of exposure and we shall not review this comprehensively at this time. There
are both physiological and biochemical aspects to controlling the relationship
between O2 delivery and consumption. As energy demand changes,
physiological mechanisms must be harnessed for appropriate perfusion changes.
Multiple metabolite signals (adenosine, K+, H+,
endothelins, nitric oxide) are utilized for coordinating perfusion with
cell-level energy demands. Nitric oxide (NO) has received particular attention
over the last decade. NO is formed from arginine in a reaction catalyzed by
nitric oxide synthase (NOS), which in mammals occurs as three different
isoforms (Förstermann and Hartmut,
1999). NOS I or ncNOS was originally discovered in neurons, NOS II
or iNOS in cytokine-induced macrophages, and NOS III or ecNOS in endothelial
cells. This field of research is far too large to explore in detail here.
Suffice to point out that NO released by NOS catalytic activity serves in
perfusion regulation by direct vasodilation, and indirectly through hemoglobin
(Hb) binding. The latter mechanism is only now being worked out in detail, but
it already appears that NO binding to Hb occurs at the lungs while its release
is favored at the tissues; the lower the oxygen tension, the greater the need
for NO-mediated vasodilation, and the greater the NO release from Hb
(Gow et al., 1999
). These
kinds of studies go a long way towards explaining why numerous studies have
found essentially a 1:1 relationship between
O2 and tissue (especially
muscle) work. For example, recent studies using dog gastrocnemius muscle
(Arthur et al., 1992
), found
such a relationship over an 18-fold change in ATP turnover rate. Later, Hogan
et al. (1992
) used the same
preparation to analyze subtle submaximal work changes; these transitions were
sustained with no change at all in concentrations of PCr, ATP and other
metabolites. Yet through these transitions a 1:1 relationship between
O2 and
O2 was maintained, and
these results are similar to many other data from other laboratories on
different tissues and organs. This leads to the conclusion that this is the
only metabolite signal so far identified that varies 1:1 with work over
realistic biological rate changes. That is why we and many others in the field
accept that O2 plays a key role in regulating up- or down-change in
ATP turnover. But how is the O2 signal transduced within the
cell?
Oxygen signal transduction in working muscle does not rely on change
in intracellular [O2]
Interestingly, the answer to the question posed above remains unclear. So
far the only mechanisms proposed from traditional studies in this area assume
simple diffusion paths from capillaries and calculate smooth diffusion
gradients within the cell ending in mitochondrial O2 sinks.
However, this approach has been less than satisfactory for, to unravel the
puzzle of how O2 delivery translates into effects on metabolism
within the cell, we require hard data on intracellular O2
concentration. The difficulty is that for most tissues this key parameter
remains elusive and unknown; only in muscle is the situation more favorable.
In this tissue, myoglobin (Mb) is a direct intracellular detector of
[O2]. Mb is a relatively small, monomeric respiratory pigment
occurring in heart and mitochondria-rich skeletal muscles at concentrations of
less than 0.5 mmol l-1; in muscles of marine mammals such as seals,
Mb concentrations reach into the 45 mmol l-1 range. Gene
knockout experiments (Garry et al., 1999; Goedeke et al., 1999) show that even
if mice can survive without Mb they can do so only by activating compensating
mechanisms such as increasing capillary densities and blood O2
carrying capacity. It is therefore usually assumed that Mb is functionally
important under the usual physiological conditions. At 37°C, O2
solubility in physiological solutions is approximately 1 µmol
l-1 torr-1 (1 torr133.3 Pa). Because the reaction
Mb+O2
MbO2 is always in equilibrium, with a
P50 of 3 torr (Kd of approximately 3 µmol
l-1), whenever [O2] is less than saturating for Mb,
%MbO2 directly estimates intracellular [O2].
Earlier attempts to make such estimates with working muscle preparations
almost exclusively relied upon near infrared spectroscopy. More recently, MRS
is being used to take advantage of a histidine-H being 1H MRS `visible' in
deoxyMb but being MRS `invisible' in oxyMb
(Richardson et al., 1996). For
the first time, this new technology supplies workers in the field with a
noninvasive window on the oxygenation state of muscles in different work and
metabolic states, at least for muscles with a high enough [Mb] to be 1H MRS
`visible'. When first applied to both working human skeletal muscles
(Richardson et al., 1996
) and
to heart (Jelicks and Wittenberg,
1995
) the same instructive results were found: essentially stable
%MbO2 through large changes in work rate. In such studies, as soon
as a work load is imposed (even in very low intensity exercise, such as
unloaded pedaling), %MbO2 quickly establishes a new steady state,
usually between 40% and 70% saturation, both as a function of time and as a
function of tissue work intensity. Along with gold labeling studies showing a
random Mb distribution in rat heart and skeletal muscles (S. Shinn and P. W.
Hochachka, unpublished observations), the MRS data imply that %MbO2
and intracellular [O2] both remain relatively constant up to the
maximum sustainable aerobic metabolic rate of the tissue. Just as CPK serves
to `buffer' ATP concentrations during changes in muscle work so Mb apparently
serves to `buffer' intracellular [O2] in different metabolic
states.
Parenthetically, it should be acknowledged that the volume of interest in
such MRS studies is large and the MRS data necessarily are averages obtained
from large numbers of fibers. Human muscles, like muscles in other mammals,
are formed from mixtures of fiber types and as work intensity rises for a
given muscle mass, there may be changes in recruitment and in the percentage
contribution of different fiber types. This problem does not arise in studies
of heart muscle, which is biochemically rather homogenous. While Richardson et
al. (1996) apparently avoided
this artifact, this does not seem to be the case in the study by Mole et al.
(1999
) on an unknown mix of
fibers in human calf muscle. Evidence of the problem initially arises from
their 31P MRS data, which showed an expected linear decrease in [PCr] as work
increased; at maximum aerobic work, [PCr] changed maximally by approximately
threefold. Since the same [PCr] change occurs when gastrocnemius work rate
reaches only 40% of sustained aerobic maximum, but much smaller changes in
[PCr] occur in (the mainly slow fibers of) soleus during the same work
transition (Allen et al.,
1997
), it is probable that the regions of interest in Mole et
al.'s study (Mole et al.,
1999
) may have overlapped into muscles rich in slow twitch fibers,
where the change in [PCr] is less for a given level of work than in fast
twitch fibers. Otherwise it would be difficult to understand why their
preparation had to be pushed to its maximum work level to achieve the same
%[phosphagen] shifts that Allen et al.
(1997
) observed at only 40% of
aerobic maximum. For these reasons, the %MbO2 values recorded at
different work intensities almost certainly represent different combinations
of fiber types. Nevertheless, these studies found that at about 50% and 80% of
sustained aerobic maximum work rate (representing huge ATP turnover rates,
equivalent to about 5080 µmol ATP g-1 min-1),
%MbO2 did not change significantly (stabilizing at approximately
6570 %MbO2), in agreement with earlier studies; however, at
the maximum work rate, a further modest desaturation to approximately 50
%MbO2 occurred, which is not in full agreement with the data of
Richardson et al. (1997). Because of the mixed fiber and recruitment problems,
readers should not be surprised by these modestly different results; and, at
least tentatively, we consider that the small discrepancies probably arise
from artifacts caused by differing metabolic states in different fiber types.
Thus they do not strongly influence our main conclusion that [O2]
is largely homeostatic.
In fact, even if most workers probably would accept that Mb should function
to buffer intracellular [O2], the significance of this has not been
fully appreciated. As Carl Honig pointed out in a discussion in 1987, this may
be because of a too enthusiastic acceptance of traditional diffusion models
assuming smooth gradients across the capillarymuscle cell threshold all
the way to the mitochondrial sinks. Such models, which assume complete
homogeneity and necessarily ignore the issues of fiber type and recruitment
heterogeneity, are not accepted by the Honig group. According to Honig et al.
(1992), the structure of the
capillarymuscle system develops steep gradients (and localized high
O2 fluxes) only at the capillarymuscle interface but very
shallow gradients within the muscle cell per se, as indeed was found
by the more recent MRS data on %MbO2 in vivo. That is why
Hochachka and McClelland
(1997
) accepted the MRS data
on %MbO2 at face value and emphasized that, under normoxic
conditions, O2 is perfectly homeostatic in the sense that its
concentration is stable even while its flux to cytochrome oxidase can change
by two or more orders of magnitude. In the examples above, the concentration
of O2 ranged between 2 and 4 µmol l-1 during pathway
flux changes from approximately 1 to >80 µmol ATP g-1
min-1 (these high mass-specific metabolic rates are achieved
because most of the cardiac output during these protocols is available for
supporting the work of relatively small muscle masses).
To recapitulate, the situation arising from these new studies of oxygen and
metabolic regulation can be summarized as follows. First, because of the
buffering role of Mb, oxygen concentrations are low (in the P50 or
Kd range) and intracellular [O2] gradients must
be quite shallow. Second, it is emphasized by Honig et al.
(1992) that the
capillarymuscle contact surface area is only a fraction of the surface
area of inner mitochondrial membranes and cristae; by definition this means
that the highest gradients and highest O2 fluxes are at the
capillarymuscle cell threshold and that these gradients are necessarily
much shallower in the cytosol. Thirdly, the low intracellular [oxygen] remains
essentially stable (i.e. remains effectively buffered by the
MbO2
Mb+O2 equilibrium, throughout large changes in
work and metabolic rates. Nevertheless,
O2 and O2
delivery are closely related, suggesting a key role for O2 in
metabolic regulation.
Previously proposed mechanisms accounting for O2 flux from
capillaries to mitochondria
Given that it is O2
not intracellular [O2] that correlates with work
rate, the problem remaining is how the O2 signal is transmitted to
the machinery of cell metabolism. At this time, we admit that there is no
widely accepted resolution of this problem. The traditional answer, of course,
assumes oxygen diffusion down smooth concentration gradients from capillary
plasma to tissue mitochondria. A second mechanism assumes accelerated
intracellular O2 transfer by Mb-facilitated diffusion in
Mb-containing cells (in this case two species are diffusing to the
mitochondrial targets at once: molecular O2 and MbO2). A
third mechanism assumes that lipids (either phospholipid bilayers or
triglyceride droplets) form the preferred path of O2 diffusion
because of the greater O2 solubility in lipids than in aqueous
phase. A final mechanism is that of O2 sensing. When we first
recognized this puzzling problem of O2 transmission and realized
the limitations of the classical diffusion model to explain the observations,
we postulated an O2 sensing system, presumably located in the cell
membrane (or even more distally), and signal transduction pathways or
mechanisms for `telling' the cell metabolic machinery when and how potently to
respond to changing availability of O2
(Hochachka, 1994
). Whereas
each of the above explanations of O2 transfer can claim to be able
to account for observed O2 fluxes under some conditions, none of
the these mechanisms above are able to easily explain why the flux rates vary
with O2 delivery rather than with intracellular O2
concentrations.
All of the above mechanisms represent so-called traditional explanations and, as briefly mentioned above they are formulated within the Model I framework of cell function: this is the view of cells as watery bags in which solution chemistry rules basically dominate the functional behavior of the system. Model II views of the cell are very different and assume that intracellular conditions are so complex that solution behavior is not necessarily the rule. The Model II view (of metabolic regulation in general and of O2 regulation in particular) takes an entirely different tack and postulates that intracellular circulation, not diffusion, is the main means of bringing ligands and their binding sites together during upwards or downwards transitions in metabolic and tissue work rates. Let us review how this picture differs from the more classical or traditional framework discussed above.
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The Model II approach |
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First and most fundamental is the structural argument: ultrastructural,
histochemical and cytochemical studies do not reveal the cell as a static bag
of substrates and enzymes, but rather a three-dimensional, membrane-bound
microcosm housing an internal milieu filled with complex organelles, motors,
membranes, cables, trabeculae and channels. Rather than a static, dead-still
solution (as would be required for formal application of laws of diffusion),
the internal medium is very much `alive' in the sense that movement is the
rule of thumb, movement of organelles, of particles, and of cytosol (so-called
cytoplasmic streaming at rates of up to 23 m s-1). In
contrast to what might be expected of a bag of enzymes and substrates, over a
half-century of research has clearly concluded that many metabolic pathways
and their component enzymes are restricted to specific cell compartments, and
numerous so-called soluble enzymes show intracellular binding to specific
intracellular sites. Order and structure is the name of the game, as far as
the literature on cell ultrastructure is concerned, and it is not a
diffusion-dominated game. Take away the order and the system behaviour falls
apart; sometimes function is lost completely. A good recent example of this
comes from genetic studies of Drosophila flight muscle metabolism.
While earlier studies had shown that aldolase, glyceraldehyde 3-phosphate
dehydrogenase and -glycerophosphate dehydrogenase colocalize mainly at
Z-discs, Wojtas et al.
(1997
) used clever genetic
manipulations (that influenced binding but not overall catalytic activities)
to show that mislocating these enzyme activities in the cytosol rather than
correctly bound to Z-discs would render Drosophila
flightlessa dramatic demonstration that even if all three enzymes are
expressed at high activities, their three-dimensional organization is part and
parcel of in vivo regulated function of the pathway.
Second is the argument on macromolecular functional constraints. As we
might expect from the above (and indeed find), the intracellular mobilities of
enzymes and of carrier proteins such as Mb are not equivalent to those in
simple aqueous solutions. For example, intracellular diffusibility estimates
for Mb in the cytosol range from as low as one tenth of that found in simple
solutions (Juergens et al.,
1994) to values of about half that in simple solution
(Wang et al., 1998
).
Interestingly, the latter MRS study estimated rotational diffusion, while the
former study estimated translational diffusion; as indicated below, these may
change independently. Just as Mb appears to be less mobile within the cytosol
than previously believed, so also are cytosolic enzymes apparently rather
restricted in their intracellular mobilityagain this picture is not
easily compatible with the concept of the cell as a bag of enzymes whose
functions are determined mainly by self-diffusion and substrate diffusion at
appropriate rates. With enzyme and Mb translational mobilities reduced to only
one tenth of that expected in aqueous solution, diffusion of macromolecules
becomes a highly inefficient means of assisting in enzymesubstrate
encounter (or in the case of Mb, for assisting O2 flux through the
cytosol).
Third is the argument on metabolite mobility. Because of the complexity of
the internal milieu, the translational mobility of even simple molecules may
be restricted compared to simple solutions, and this is especially true in the
mitochondrial matrix. For example, studies with 14C-labeled Cr
(Hochachka and Mossey, 1998)
show that CPK is unable to readily equilibrate the entire pool of PCr + Cr in
fish white muscle (fast twitch fibers). At the same time, parallel
1H MRS studies (Trump et al.,
2001
) show that in human muscle in vivo the intracellular
behaviour of Cr is highly constrained. One set of studies, focussing on the
methyl hydrogens, shows that Cr mobility is dependent on metabolic state being
three- to fourfold less mobile in ischemic fatigue than in muscle at rest.
Another set of studies focussing on the methylene protons found that only in
PCr were the methylene protons MRS visible; on PCr conversion to Cr during
muscle work, the methylene protons become MRS invisible (in simple solutions
MRS cannot distinguish these between PCr and Cr). Taken together these data
supply powerful evidence that the behaviour of metabolites in vivo
may be much more precisely regulated (and certainly much more constrained)
than previously expected (for literature in this area, see
Hanstock et al., 1999
;
Trump et al., 2001
). Another
recent study (Kao et al.,
1993
) showed that three factors (viscosity, binding and
interference from cell solids) could account for translational diffusion of a
metabolite-sized analogue in cytosol being decreased to only 27% of the rate
observed in water. As in the MRS studies, these workers also demonstrated
mobilites that were state-dependent: during osmotic stress (a twofold cell
volume increase), when metabolism is known to be increased, there is a
correlated (if unexplained) sixfold increase in the apparent translational
diffusion coefficient, while rotational diffusion remained constant. The
complex and metabolic state-dependent diffusion behaviour of metabolite-sized
molecules would not readily facilitate enzymesubstrate encounters as is
required for simple solution models of regulated cell function.
Given these constraints, several workers
(Wheatley, 2003;
Wheatley and Clegg, 1994
;
Hochachka, 1999b
) consider
diffusion by itself to be an inadequate, inefficient and minimally regulatable
means of delivering carbon substrates and oxygen to appropriate enzyme targets
in the cell under the variable conditions and rates that are required in
vivo. Instead, we favor an hypothesisalmost demanded by the rules
imposed by a structured and ordered internal milieuof an intracellular
convection or perfusion system as an elegantly simply resolution of the
problem of how substrates (including O2) and enzymes are brought
together. From our present point of view
(Hochachka, 1999a
), the key
advantage of this model is that it easily explains how enzymes and substrates
can be brought together and how reaction rates can occur at widely varying
rates with minimal change in substrate concentrations. This is the empirical
starting point of the paradox in this whole field, which in my opinion has
never been satisfactorily explained (for O2 or for any other
intermediate in mainline metabolism). As in the perfusion of organs/tissues
such as muscle mentioned above, rates of intracellular metabolic reactions as
predicted by this model are simple products of intracellular perfusion rates:
the greater the perfusion rates the greater the metabolic rates, with no
concomitant changes in substrate concentrations required. In this view, during
osmotic activation of metabolic rate, the sixfold increase in metabolite
mobility observed (but not explained) could well represent a similarly large
increase in intracellular convection. In the case of the MRS data, a fourfold
change in Cr mobility in hypometabolic ischemic muscle may well represent a
similar change in intracellular convection (this is viewed as a coarse but
dominant control, which need not necessarily rule out other fine-tuning
control mechanisms, such as those that have so far absorbed much of metabolic
research).
For O2 transport, this view places the function of a
half-O2-saturated, randomly distributed Mb into an entirely
different perspective, where the fundamental purpose of an intracellular Mb
may be to equalize [O2] everywhere in the cytosol, thereby ensuring
that intracellular convection would always be delivering similar amounts of
O2 per unit volume of cytosol to cytochrome oxidases (and
simultaneously minimize or even destroy intracellular O2
gradients). While this model is consistent with the minimal intracellular
O2 gradients in muscle cells proposed by the Honig and coworkers
(Gayeski and Honig, 1986;
Honig et al., 1992
), it takes
on a quite different meaning. Finally, the concept of an intracellular
perfusion system supplies purpose and meaning to intracellular movements
(motor-driven or otherwise-induced cytoplasmic streaming) that have been
mainly ignored by traditional metabolic biochemists to this time. If accepted,
the concept of intracellular convection modifies our overall view to include
an intracellular component in the chain of convective and diffusive steps in
the overall path of O2 from air to mitochondria
(Table 1).
|
The anatomy of intracellular circulation
According to the best evidence that is currently available, intracellular
movement and circulation are largely powered by molecular motors:
unconventional myosins running on actin fibers, myosin motor-driven
mitochondrial movements on actin tracks, dynein motors running on tubulin
tracks, and kinesin motors running on tubulin tracks. Experimental protocols
that are used to tease out which systems are operative include monitoring
effects of (i) actin fiber disruption (for example, with cytochalasin D), (ii)
tubulin disruption (for example, with nocodazole), or (iii) disruption of
motors causing cytoplasmic streaming (for example, disruption of such
mitochondrial motors stops mitochondrial movement, coincident with a fivefold
decrease in cell metabolic rate). Given the above situation, intracellular
microfilament distribution may supply us with insight as to possible
circulatory pathways.
Interestingly, in slow and fast fibers, intracellular microfilaments are most abundant near the surface and decrease in concentration towards the center. Despite the smaller diameter of slow fibers compared to fast fibers, and their much higher oxidative capacities, microfilament numbers and distribution patterns are similar in slow and fast fibers, implying similar convection capacities. A key insight is that microfilaments extend right through the actomyosin contractile apparatus, both along horizontal and vertical dimensions. Thus, these microfilament distribution patterns in theory supply possible circulatory pathways within the muscle cell, both at the periphery and in the interior of the muscle fiber.
In conclusion, the polarisation illustrated by Model 1 and Model 2 approaches of living cells extends throughout the metabolic regulation field and has caused the field to progress along two distinctly independent pathways, with minimal communication between them. The time may have come when cross-talk between Model 1 and Model 2 approaches may be useful.
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