Discussion
Understanding plant responses to short-term changes in the environment
is of considerable importance if we wish to improve crop yields in the
light of changing climates. The relationship between these environmental
changes and the signal transduction pathways which promote cellular
adjustment is still poorly understood. Because all of metabolism is
affected by temperature, it is difficult to pinpoint an obvious
temperature-sensor or to assess the direct effect that metabolic changes
have on gene expression (Herrmann et al ., 2019a). For this
reason, rather than looking at individual components of a system, it is
important to look at the entire system and consider the role that
individual components play within it (Kitano, 2002). In this sense,
formal frameworks, which conceptualize, rather than merely describe, the
functioning of its components, are required (Lazebnik, 2003).
Robustness can be used to assess how well a system maintains function
across changing environmental conditions. Robustness, however, does not
capture the likelihood that the system will be able to perform its
function independently of the environmental conditions. This is captured
by measures of reliability.
Here, we have adapted the failure mode and effect analysis (FMEA)
framework used in reliability engineering and applied it to plant carbon
metabolism. We used a metabolic graph of carbon metabolism to identify
metabolites which can be considered of high risk to the system, due to
their high probability of failure and severity of impact on the rest of
the system. From an engineering perspective, high-risk components should
be carefully controlled and regulated such that they can maintain their
functionality in the event of failure. A fail-safe, for example, can be
used to ensure that perturbations are mitigated effectively. Such a
fail-safe increases the overall reliability of a system by increasing
its likelihood of correct functioning. A good fail-safe is able to
mitigate many different types of system failure, and fail-safes are of
particular importance under abrupt and unexpected changes.
Diurnal fumarate accumulation increases in response to both cold and
warm treatment (Fig’s 3, S5). This surprising observation is consistent
with flux to fumarate acting as an inherent fail-safe to the metabolic
system. Our FMEA analysis identifies malate and oxaloacetate, the
immediate precursors of fumarate, as high-risk components. Fumarate
itself is of low risk to the metabolic system and changing its
concentration has negligible effect on overall system functionality. An
influx of carbon can be re-directed to fumarate without disturbing the
system. Our results show that, unlike fumarate, the amount of malate
accumulating through the day in both wild type accessions is
surprisingly constant in response to initial warm and cold treatment and
only changes following acclimation. Mathematical modelling confirms that
an increased accumulation of fumarate and a constant accumulation of
malate are metabolically plausible under the Arrhenius law (Arrhenius,
1889), and that no regulatory mechanisms are required for fumarate
accumulation to increase at both high and low temperatures.
Nevertheless, active regulation of fumarate accumulation under these
conditions cannot be excluded.
To date, there is little direct experimental evidence for the presence
of a cytosolic fumarase enzyme in plant species other thanArabidopsis thaliana (Chia et al. 2000). However, a recent
phylogenetic study demonstrated that several close relatives of A.
thaliana possess orthologues of the fum2 gene (Zubimendiet al ., 2018). This study also shows that other plant species
obtained the gene through parallel evolution. Because fumarate has
recently evolved in Arabidopsis species and relatives (Zubimendiet al ., 2018), it is likely that other mechanisms regulate the
concentration of high-risk metabolites (like malate) in other species.
For instance, phosphoenolpyruvate carboxylase (PEPC), which produces
malate from oxaloacetate, is inhibited by malate across many plant
species (O’Leary et al ., 2011). This negative feedback loop could
have the same effect as a fumarate sink, in that it maintains a constant
accumulation of malate, even when the carbon influx is changing. This
regulatory mechanism, however, is intricately dependent on
phosphorylation and cellular pH (O’Leary et al ., 2011), both of
which may also be affected by changing environmental conditions. Thus,
the evolution of a cytosolic fumarase fail-safe provides an alternative
control mechanism regulating the malate concentration, while at the same
time maintaining metabolic fluxes and allowing efficient storage of
fixed carbon.
Photosynthetic acclimation to cold is dependent on the presence of FUM2
activity or protein (Dyson et al ., 2016). Here, we have shown
that C24, which has reduced FUM2 content has an attenuated the
acclimation response. Furthermore, we show that FUM2 is also essential
for acclimation of photosynthetic capacity to high temperatures.
Photosynthetic capacity, measured under control temperature and
CO2 and light-saturating conditions, provides a readily
measurable indicator of the acclimation state of the photosynthetic
apparatus (Herrmann et al ., 2019b). Mutant fum2 plants are
unable to accumulate fumarate and do not show a consistent adjustment ofPmaxin response to temperature. C24 plants accumulate intermediate levels of
fumarate and attenuated temperature acclimation ofPmax , compared with Col-0. ThePmax acclimation responses of Col-0 and C24
highlight that, although the changes in CO2 assimilation
in growth conditions may be modest, there is a significant metabolic
response associated with these changes.
Although malate accumulation is buffered on the first day of temperature
treatment, it does increase in response to sustained temperature
treatment, as part of the acclimation response. Our FMEA analysis
suggests that malate concentration should be tightly regulated to
support a specific system functionality. This functionality may change
in response to cold conditions, at which point a different rate of
malate accumulation may be required. Either way, the required
concentration is likely to be controlled by adjusting the flux to the
low-risk metabolite fumarate.
The functionality of a metabolic system may vary under changing
environmental conditions and the ability to achieve function should be
maximised. Thus, finding reliable rather than robust traits, should be
of equal if not of higher priority in optimizing a metabolic system.
Methods for capturing system reliability currently remain underutilized
in biology.
While we have focused here on malate as a high-risk metabolite, our
analysis has identified other high-risk candidates. Interestingly, some
of them have previously been noted as critical components of acclimation
(Timm et al ., 2012; Dyson et al ., 2015; Weise et
al ., 2019). For example, it was shown that expression of GTP2, a
chloroplast glucose 6-phosphate/phosphate translocator, is required for
acclimation to high light in the Arabidopsis accession Wassilewskija-4
(Dyson et al ., 2015). Our FMEA highlights glucose 6-phosphate in
the chloroplast and in the cytosol as high-risk components, which are
upstream of the starch and sucrose carbon sinks in the metabolic
network. GPT2 allows for appropriate distribution of carbon between
these two sinks. When this control mechanism is broken, the two glucose
6-phosphate metabolite concentrations cannot be regulated and
acclimation to high light is affected (Dyson et al ., 2015). Other
high-risk metabolites identified by our FMEA, such as glyceraldehyde
3-phosphate, pyruvate, phosphoenolpyruvate, and α-ketoglutarate, may
also play important roles in maintaining system reliability under
changing environmental conditions.
In conclusion, we were able to show that cytosolic fumarase, an enzyme
promoting the accumulation of fumarate, a metabolite with few known
metabolic functions, can act as a fail-safe, preventing
over-accumulation of the high-risk metabolite malate. We have used FMEA
to discuss alterations in plant carbon metabolism under different
temperature conditions, and we propose FMEA as a tool to assess the
reliability of biological systems.
Our proposed FMEA framework is computationally inexpensive and can be
applied to all of metabolism in order to identify pathways that are
especially important for maintaining system reliability. As we have
shown FMEA allows for the quantification of high-risk and low-risk
components in existing systems. However, FMEA could also be used to
quantify the risk associated with metabolic alterations that are the
result of gene deletions or insertions. For this we would recommend a
gene-centric rather than a reaction-centric view of the network that
underlies the metabolic system of interest. This approach holds the
potential to be used in metabolic engineering, for the study of
synthetic pathways and the impact of pathways alterations on system
reliability.