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.