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OUTLINE

 1. Highlights
 2. Abstract
 3. Keywords
 4. Pathway-centric views of metabolism and its shortcomings
 5. Testing and establishing the electrical view of metabolism – the road ahead
 6. Conflict of interest statement
 7. Acknowledgments
 8. References

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CITED BY (9)




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CURRENT OPINION IN SYSTEMS BIOLOGY

Volume 13, February 2019, Pages 59-67



INTERROGATING METABOLISM AS AN ELECTRON FLOW SYSTEM

Author links open overlay panelChristianZerfaß12MunehiroAsally123Orkun
S.Soyer123PersonEnvelope
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HIGHLIGHTS



•

Cell metabolism represents an interconnected network rather than isolated
pathways.

•

Capturing the interconnected nature of metabolism makes experimental and
theoretical analysis of metabolism very challenging.

•

We highlight kinetic and thermodynamic constraints arising from a view of
metabolism as an electron flow as a fundamental approach to study and understand
metabolism.

•

We call for the development of experimental tools and models that focus on
capturing redox and ion fluxes connected to electron flows through metabolism.




ABSTRACT

Metabolism is generally considered as a neatly organised system of modular
pathways, shaped by evolution under selection for optimal cellular growth. This
view falls short of explaining and predicting a number of key observations about
the structure and dynamics of metabolism. We highlight these limitations of a
pathway-centric view on metabolism and summarise studies suggesting how these
could be overcome by viewing metabolism as a thermodynamically and kinetically
constrained, dynamical flow system. Such a systems-level, first-principles based
view of metabolism can open up new avenues of metabolic engineering and cures
for metabolic diseases and allow better insights to a myriad of physiological
processes that are ultimately linked to metabolism. Towards further developing
this view, we call for a closer interaction among physical and biological
disciplines and an increased use of electrochemical and biophysical approaches
to interrogate cellular metabolism together with the microenvironment in which
it exists.

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KEYWORDS

Electrobiology
Metabolic organisation
Evolution of metabolism
Redox potential
Thermodynamics
Cellular physiology
Cellular trade-offs

Metabolism refers to the collective set of biochemical reactions that occur
within a cell. Early pioneering studies, crowned by several Nobel prizes, have
mapped the so-called core metabolism that includes glycolytic and pentose
phosphate pathways (PPP), Calvin–Benson cycle, gluconeogenesis and the
tricarboxylic acid (TCA) cycle 1, 2. In parallel, the chemiosmotic theory of
energy generation through the respiratory electron transport chain has been
formulated and proven correct [3] (even though the mechanistic details are still
a matter of debate 4∗∗, 5). These productive lines of research elucidating
individual enzymatic reactions continue to make important contributions to our
understanding of metabolism [6]. In this opinion article, we argue that it is
now time to use this accumulating knowledge to develop an explanatory
theoretical framework based on electron flows for interrogating cellular
metabolic structure and dynamics at systems level.


PATHWAY-CENTRIC VIEWS OF METABOLISM AND ITS SHORTCOMINGS

Following the early pioneering studies on the biochemistry of enzymes, a
pathway-centric framework has dominated the description of metabolism 7∗, 8, 9.
This textbook view organizes cellular metabolism into modular pathways that link
sugars to pyruvate (i.e. the glycolysis pathways of pentose-phosphate (PP),
Entner–Doudoroff (ET), and Embden–Meyerhof–Parnas (EMP)), and those that link
pyruvate to the generation of the key reductive equivalents via the TCA (a.k.a.
Krebs) cycle and associated glyoxylate and glutamate cycles. These pathways and
their interactions with the biosynthesis pathways of lipids and amino acids are
considered to give rise to a higher organisation of metabolism as catabolic
(energy generating) and anabolic (energy consuming) reactions 7∗, 8, 9. Such
organisational view is further enforced by graph-theory analyses that suggest a
hierarchical and modular organisation of metabolism 10, 11 (although it is
important to note that identifying appropriate null models is challenging when
studying metabolism as a graph 12, 13 and different graph representations can
give different results [14]).

This pathway-centric framework, thus, draws a picture of cellular metabolism as
consisting of well-defined flows through modularly organised pathways. The
pathways themselves are suggested to represent historical contingencies in
evolution, where a key set of metabolites and metabolic conversions emerged as
first forms of “life” [15] and subsequently maintained and expanded through an
evolutionary process that is commonly seen as driven by cellular growth under
diverse conditions. While this adaptive view of metabolism gives us one possible
way of rationalising it, it ignores other possible driving forces and
constraints in the evolution of metabolism (e.g. osmotic or toxic effects,
trade-offs, cell stability) 16, 17, and falls short in explaining and predicting
many of the key structural and dynamical features of metabolism. We list below
some of these as open questions, and argue for the development of a new
explanatory framework, which can offer starting points towards addressing them.

Why are metabolic systems diverse across different species? Pathways that offer
alternative routes for glucose consumption are present or absent in different
microbes [18]. Biosynthesis pathways for essential co-factors, such as thiamine
or vitamin B12, are lacking in different algae and fungi species 19, 20, and
even the TCA cycle structure can be varied in different organisms [21]. While
the pathway-centric view tends to explain such structural diversity as
“adaptations to different conditions”, we need a more predictive theory that can
directly link specific environmental factors to specific metabolic structures
(e.g. lack of a given enzyme predicted under a certain environment). For
example, loss of metabolic pathways in some organisms is explained as an
adaptive process under the provision of specific metabolites by other organisms
[22], but it is left unclear why and under what conditions any organism would
excrete any such metabolites. Similarly, functionally equivalent pathways are
suggested to be adaptive under different conditions due to their different
energetic costs 7∗, 18∗, but it is left unclear what those conditions might be.
An ideal theoretical framework for metabolism should provide experimentally
testable predictions about where and when to find which structural variants of
metabolism.

What are the design principles of common metabolic system structures? While
metabolic systems show some diversity, there are common structures that are
conserved across many species, and that can be presented as key metabolic
pathways. It is still not clear why these common pathways are structured in the
way that they are. Several studies have tried to answer this question based on
biophysical and energetic aspects 18∗, 23, 24∗, but did so while treating
individual pathways as isolated units. These approaches should be further
developed, given the fact that no pathway (and its reactions and metabolites)
exists in isolation in a cellular environment, but instead operates under high
interconnectedness through metabolites and common electron shuttles (Figure 1).
Developing a system-level framework that could naturally explain the emergence
of interconnected pathways as a whole remains to be an open challenge.

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Figure 1. Common metabolic pathways, shown in their broader context, and
highlighting their interconnected nature. Reactions are compiled from Ref. [7]
and do not represent the full list of known metabolic reactions in the cell.
Metabolites are shown using their common names, while reactions are indicated
with arrows. Yellow and green arrows indicate oxidation and reduction reactions,
respectively, with arrow type indicating the involved electron shuttle; solid,
dashed, and double dashed lines for NADH, NADPH, and FADH2. Reactions releasing
and consuming ATP are shown in red and blue, respectively. Where multiple
reactions are involved when going from one metabolite to another, this is
indicated by multiple arrows. Involvement of co-factors and release of small
molecules (such as carbon dioxide) are indicated partly (with smaller arrows).
Metabolites involved in multiple reactions, and therefore forming additional
metabolic cycles, are indicated with a grey backdrop.

Why do cells excrete metabolites and enzymes to their environment? Many
metabolites are readily excreted from cells despite still carrying energy value,
and many enzymes are known to operate outside of the cell. A pathway-centric
view focused on optimization of growth does not provide any explanations for
these observations, nor does it allow any predictions about which metabolites or
enzymes might be secreted under which conditions. Adaptive arguments have been
made about some metabolic excretions (i.e. ethanol) providing a mechanism to
inhibit or kill competing species [25]. This particular example also highlights
a broader issue with adaptive arguments in that they can readily be formulated
for many different observations, but lack a clear sequential evolutionary path;
in this case, for example, the killing argument does not explain how small
amounts of metabolic excretions, that would not yet function as a toxic agent,
could have emerged and stabilised. A series of recent studies indicate that
metabolic excretions, in particular those involving organic acids, can arise
from cellular trade-offs linked to biophysical constraints on enzymatic
reactions such as space (i.e. cytosolic vs. membrane–bound reactions) 26∗∗, 27,
28 and protein capacity 29, 30. These studies highlight the importance of
considering the biophysical basis and limits as directing evolutionary processes
when explaining and predicting specific features of metabolic systems.

How does metabolism exhibit non-linear dynamics as a whole? The pathway-centric
view of metabolism does not consider the dynamics of fluxes across pathways.
This dynamic nature is evident from the interconnectedness of key metabolic
pathways through common electron and energy shuttles such as NADH and ATP
(Figure 1), and the fact that many of their constituting reactions are close to
thermodynamic equilibrium under standard conditions [31] (Figure 2). These
reactions could thus be operating reversibly with changing cellular conditions,
such as pH and redox potential, as shown for some pathways 32, 33∗∗, 34∗, and
lead to non-intuitive flux dynamics. In addition, the sharing of (or competition
for) metabolites and enzymes across many reactions can lead to complex temporal
dynamics such as oscillations and multi-stability, as theoretically shown for
even simplified biochemical reaction systems 35∗, 36, 37∗, 38∗∗. Indeed, where
measured, periodic oscillations are found to be present in central metabolism
39, 40, 41∗∗, 42. These oscillations are well studied in continuous yeast
cultures, in which they have been shown for virtually all metabolites and
coincide with a separation of oxidative and reductive phases [43]. Similarly,
combined levels of NADH and NADPH in Escherichia coli, measured
fluorimetrically, were found to oscillate in line with the cell division cycle
[41]. It has been furthermore suggested that these oscillations are crucially
linked to other biological oscillations, such as cell cycle and circadian
rhythms 44, 45. While some models 46, 47, 48 and metabolic mediators 39, 49 have
been proposed to explain these oscillations, a detailed and predictive
understanding of metabolic oscillations still needs to be developed. Besides
oscillations, bistable dynamics have been predicted and experimentally shown for
isolated enzymatic reactions and pathways 36, 50, 51, 52, 53. These dynamics are
still challenging to analyse at the single-cell level, but emerging fluorescence
approaches offer a promising route [54]. Finally, the dynamics arising from
(seemingly) futile enzymatic cycles have been discussed theoretically as a
mechanism for achieving robustness against perturbations [37], but have not been
studied in the context of temporal dynamics. Theoretical models of futile cycles
have shown that these can give rise to bistability and oscillations under
certain parameter regimes [50], but these ideas have not been explored
experimentally. Overall, the dynamics of metabolism either at the whole system
level or at the level of commonly observed dynamical modules (like futile
cycles) is understudied.

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Figure 2. Thermodynamics of common metabolic conversions as collated from
references 31∗, 73∗. The y-axis shows the standard Gibbs free energy at
physiological conditions (ΔG0′), while the x-axis is used for reaction index
(ordering them from lowest to highest ΔG0′). In calculating the ΔG0′, reactions
are considered in their spontaneous direction and the H+/H2 pair is used for
electron balancing (in the case of redox reactions). Each reaction is shown as a
single data point, while lines are for the density distribution (as indicated in
the inset). Reactions that were included in Fig. 1 are shown as green filled
points and their distribution by the green line. This figure suggests that most
metabolic conversions have a ΔG0′ value close to zero (see distributions), but
calls for a further mapping of metabolites and reactions in order to allow more
general conclusions to be drawn (with regards to how these distributions compare
to those of all possible reactions). We note that reactions with the most
negative ΔG0′ (<-250 kJ/mol, left side in plot) are those involving the
reduction of nitrate, oxygen, and sulphite; common terminal electron acceptors.


METABOLISM AS A THERMODYNAMICALLY DRIVEN ELECTRON FLOW SYSTEM

Life depends on free energy gradients [55]. Organisms, or cells, act as
“disequilibrium converters” [56] that exploit these energy gradients and couple
thermodynamically spontaneous and nonspontaneous reactions through a defined
path, the metabolic reaction network. The ratio of the forward and reverse
kinetic constants of a reaction equals to the equilibrium constant Keq, which in
turn determines its standard Gibbs free energy at a dynamical steady state
(ΔG0 = R⋅T⋅ln(Keq), where R is universal gas constant and T is temperature in
Kelvin) 56, 57, 58. The actual reaction free energy (and hence the spontaneous
direction of a reaction) at a given condition is based on ΔG0 (Figure 2), which
relates to the concentrations of substrates and products under that condition.
Thus, changing concentrations through one reaction can make another reaction
feasible, allowing metabolism to couple external gradients to internal ones in a
turnstile-like mechanism [56]. For example, light-energy drives photosynthetic
reactions forward (i.e. water-oxidation with carbon dioxide reduction), and once
a pool of metabolites is generated, the reverse reaction (e.g. glucose oxidation
with oxygen reduction) becomes spontaneous (i.e. energy releasing), allowing
excess energy for other non-spontaneous reactions.

These dynamics of metabolic flows can be formalised through non-equilibrium
thermodynamics, which is well developed for simplified enzymatic reaction
networks 58, 59. The use of this formalism as a general theoretical framework
for studying the entire cellular metabolism, however, has not been fully
explored. This is mainly due to a lack of information about thermodynamic
properties (i.e. standard Gibbs energies) and intracellular concentrations of
many metabolites. The former issue can be approached computationally using
statistical (e.g. group contribution) or quantum chemical methods, however,
these are currently limited and can only cover a fraction of cellular
metabolites 60∗, 61. The intracellular metabolite concentrations can be
increasingly determined using technological developments in high-throughput mass
spectrometry and ion chromatography [33], hence, with knowledge of a reaction's
ΔG0, allowing direct assessment of the thermodynamic state of the reaction.

Development of a dynamical thermodynamic framework for cellular metabolism can
benefit from a special focus on redox reactions. These reactions hold a key
interconnecting role among different pathways and offer electrochemical
interrogation of their dynamics 62, 63. Redox reactions interlink for example
glucose oxidation via PP, ET, and EMP pathways, pyruvate oxidation through the
TCA cycle, and biosynthesis of many of the amino acids (Figure 1), through the
shared use of conserved moieties acting as electron shuttles, such as NAD+/NADH,
NADP+/NADPH, FAD/FADH2, ferredoxins, and quinones. This, crucially, makes the
ratio of the concentration of the oxidised and reduced forms of these molecules
a key factor in determining the thermodynamics of (and flows through) different
metabolic paths.

Considering this interconnected set of redox reactions can crucially allow us to
consider electronic circuits as an analogy to metabolic systems [64] on one
hand, and to attempt their manipulation by electrochemical means on the other
65, 66, 67. Indeed, it has been shown that influencing the ratio of key electron
shuttles (e.g. NAD+/NADH) through enzymatic and electrochemical means can
directly influence metabolic pathway fluxes and the dynamics of metabolic
excretions 63, 68, 69, 70∗.


POTENTIAL EXPLANATORY POWERS OF VIEWING METABOLISM AS ELECTRON FLOWS

We argued so far that considering metabolism as a thermodynamically driven flow
system, rather than isolated pathways, can provide an overarching theoretical
framework and that focusing this framework to redox reactions can further allow
the formulation of new explanatory and predictive theories. We list below some
of the key areas where this electrical view of metabolism can make immediate
impact in our understanding of metabolism.

Energetic barriers in electron flow driving metabolic pathway diversity and
utilization. When strong electron acceptors are not available in the
environment, cells have to use weaker electron acceptors such as organic acids
or inorganic molecules (such as H+) as electron sinks (i.e. to maintain electron
flow). The result is a smaller free energy available from the overall redox
reaction that the cell implements, and an increased risk of the system reaching
equilibrium by product accumulation (i.e. thermodynamic inhibition). Recently,
it has been shown theoretically that this type of thermodynamic inhibition due
to product accumulation can lead to diversity of microbial growth-supporting
metabolic reactions and possibly internal metabolic pathways [71]. This theory
aligns well with the observation that organisms, such as methanogens and sulfate
reducers, adapted to weak or fluctuating electron acceptors show diverse
respiratory and fermentative pathways and enzymes 55∗, 72, 73∗. It would be
interesting to see if theories relating to thermodynamic inhibition could be
developed further to link the diversity of broader organization of metabolic
systems (in particular redox shuttle and respiratory enzyme usage) to
environmental conditions, and in particular availability and ecological dynamics
of common electron acceptors.

Metabolic excretions to maintain electron flows. Thermodynamic inhibition could
also be a driving force beyond observed metabolic excretions. For example,
oxidation of certain metabolites can become thermodynamically inhibited if the
reduced forms of their paired electron shuttle have reached a low concentration.
Such an inhibition would be lifted if another metabolite could be reduced using
the oxidized form of the same shuttle molecule. This coupling can be further
facilitated if one (or some) of the metabolites can be made to act as a sink,
e.g. by excreting them from the cell. The increased rate of formation and
excretion of organic and amino acids through reductive reactions can be
understood within this view, as a mechanism to combat shifts in the NAD+/NADH
ratio. Indeed, experimental manipulation of the NAD+/NADH ratio in E. coli and
yeast were found to directly influence the dynamics of metabolic excretions
through fermentative pathways (i.e. acetate and ethanol excretion) 69, 70∗.
Thus, furthering a theoretical framework based on thermodynamically driven redox
paths might allow us to predict metabolic excretions under different conditions.

Enzymatic excretions combatting toxic effects arising from redox reactions
involving electron sinks (i.e. respiration). Redox reactions with compounds that
act as final electron acceptors (i.e. electron sinks), should ideally involve
strong electron acceptors so to provide a significant energy gradient (see
Figure 2). This, however, creates an additional constraint on metabolic system
structure and dynamics in that strong terminal redox reactions can also result
in the generation of even stronger redox active compounds [74]. The respiration
(i.e. reduction) of O2, for example, is found to lead to a generation of
reactive oxygen species (ROS) at a rate up to 20% [75], while sulfate and
nitrate respiration results in ‘toxic’ sulfide and nitrite, respectively. To
avoid additional, uncontrolled redox reactions by these strong oxidizing agents,
cells must have evolved ways to generate enzymes and redox metabolites that can
act as effective neutralizers against strong redox agents. While catalases and
peroxidases are known enzymes that can combat ROS toxicity [76], the generation
of ROS from respiration could have been a strong driver also for the overall
metabolic structure and dynamics. Indeed, connections between resistance to ROS
and metabolic flux changes have been shown 77, 78, 79, 80, 81, and ROS
mitigation is suggested as an explanation for excretions of metal oxidizing
enzymes in bacteria 82, 83.

Compartmentalization of electron flows in space or time. Spatial
compartmentalization of metabolism can be seen in form of specialized organelles
within an individual cell 84, 85 (e.g. mitochondria and chloroplasts) and in
form of subpopulations within an isogenic cell population 54, 86. Such
compartmentalization could be understood in the context of thermodynamic
inhibition due to product accumulation and the associated issue of maintaining
electron flows: local microenvironments that can maintain a disequilibrium
through separation or flow of products from their reactions can allow overcoming
thermodynamic inhibition. A similar effect could also be achieved by separation
of processes over time, i.e. by implementing oscillatory dynamics that can
balance the impact of opposing processes (e.g. on the NAD+/NADH ratio). Indeed,
theoretical analyses suggest that oscillations, as observed for example in the
NAD+/NADH ratio in yeast and eukaryotic cells 39, 44, 49, may enhance the
thermodynamic efficiency of glycolysis [87] or, more broadly, coupled chemical
reaction systems [88]. This is in line with experimental observations of
periodic NADH/NADPH concentration oscillations correlating with cell cycle
phases 41∗∗, 43, which could be an adaptation to alternately maximize
thermodynamic driving force through pathways of interest with temporal
separation.


TESTING AND ESTABLISHING THE ELECTRICAL VIEW OF METABOLISM – THE ROAD AHEAD

It has been long-recognized that metabolism is a prime example of a system
obeying non-equilibrium thermodynamics [89]. Bringing this view to practical
study and engineering of metabolism, however, remains a challenge. We believe
that the presented framework highlighting a view of metabolism that is based on
maintenance of electron flows, under constraints arising from thermodynamics,
kinetics, and interconnectedness of pathways through common electron and energy
shuttles, can initiate further studies towards overcoming this challenge. This
framework calls for more interaction between experimental and modelling
disciplines and the development of new theoretical and experimental tools.

On the theoretical side, we note that efforts have been made to expand the
stoichiometric, constraint-based optimization models of metabolism (i.e. flux
balance analysis, FBA) with thermodynamics 90, 91, 92, 93 and also with overall
constraints that can mimic some of the biophysical constraints arising from
resource and space limitations 27, 94, 95, 96. It would be important to continue
these developments, and also consider coupling FBA with the modelling of cell
environment dynamics 95, 97 towards incorporating possible thermodynamic
inhibitions and electron acceptor availabilities in these environments.
Inevitably, however, capturing the full dynamics of metabolism as electron flows
will require kinetic and even spatial models that account for physiological
parameters such as pH and membrane potential. To achieve this, current kinetic
models, which usually assume fixed ratios for common electron and energy
shuttles, and tend to consider pathways in isolation, need to be further
developed. Dynamics of electron shuttles and the possibility of reaction
reversibility will need to be incorporated to account for thermodynamics.
Statistical thermodynamics simulations, as used recently to simulate TCA cycle
dynamics [98], can be useful in this context but would need to be expanded and
further developed to account for the larger parts and interconnected nature of
metabolism. Similarly, emerging thermodynamic models for modelling overall
metabolic conversions embedded through metabolism (i.e. thermodynamic microbial
growth models) [99] can be possibly adapted to model cellular metabolism. As
kinetic models incorporate more biochemical realism through reaction
reversibility, electron and energy shuttle dynamics, and pathway
interconnectedness, the major challenge will be to maintain models as tractable
and ‘simple enough’ so that they can still generate experimentally testable
insights and predictions.

On the experimental side, approaches integrating physiological, metabolomic, and
electrochemical techniques will need to be developed to better understand
electron flows in metabolism and constraints on these flows. In particular, we
note that combined application of fluorescent reporters (as being increasingly
used to interrogate cellular redox states and physiology (e.g. 41∗∗, 100, 101,
102, 103, 104)) and emerging nano-scale electrochemical probing methods [105]
can provide powerful insights into the electron flow dynamics at cellular and
population levels. These methods can be particularly suited to link metabolic
dynamics to higher–level complex physiological processes such as cellular
differentiations. Intriguingly, cellular differentiation is often associated
with specialization of metabolism (e.g. bacterial spores 106, 107, T cells
[108], cancer cells [109]). We envision that development of the electron-flow
based view to metabolism may provide a novel insight to these cellular
differentiation processes as arising from thermodynamic limits and imbalances in
metabolism. This, in turn, can open up novel means of controlling these
processes using electrochemistry, and opening up new medical intervention
methods.


CONFLICT OF INTEREST STATEMENT

Nothing declared.


ACKNOWLEDGMENTS

This work is funded by The University of Warwick and by the Biotechnological and
Biological Sciences Research Council (BBSRC), with grant IDs: BB/K003240/2 (to
OSS) and BB/M017982/1 (to the Warwick Integrative Synthetic Biology Centre,
WISB).

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