We determined embryonic viability in a range of temperatures for Caenorhabditis elegans and Caenorhabditis briggsae and operationally defined the thermal limits as the upper and lower edges of the temperature range within which >90% of embryos hatched. We thus found that the thermal limits of C. elegans were of 12°C and 25°C (Figure 1A), and those of C. briggsae of 14°C and 27°C (Figure 1B), in line with the fact that C. briggsae usually lives in warmer climates than C. elegans (Prasad et al., 2011). The thermal range defined by these upper and lower limits ensures robust propagation of the population and is narrower than merely the reproductive range for C. elegans (9°C–26°C [Anderson et al., 2011]) or C. briggsae (14°C–30°C [Anderson et al., 2007; Prasad et al., 2011]).

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Figure 1—source data 1

Quantified features.

List of features that were quantified and their thermal responses within and beyond the thermal range for C. elegans (N2). Within the thermal range, features were categorized as ‘temperature-dependent’ if the Pearson correlation p-value was below 0.0014 = 0.05/35 (see ‘Materials and methods’ for Bonferroni correction; ‘temperature-independent’ is shown underlined). Beyond the thermal limit, we performed an F-test to determine if the thermal response of the feature was changing compared to within the thermal range (see ‘Materials and methods’; we indicated a change in thermal response when the F-test p-value was below 0.0014, highlighted in bold). Abbreviations: PC: pseudo-cleavage, PM: pronuclear meeting, ME: mitotic entry, T: temperature, C/R: centration-rotation, MT: microtubules. The following features were also quantified but displayed no consistent thermal response both within and beyond the thermal range and hence were not included in the table: anterior-most position at the end of C/R, number of anterior and posterior oscillations, spindle position at the onset of oscillations.

https://doi.org/10.7554/eLife.04810.004

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We reasoned that identifying cellular features that operate differently beyond the thermal limits defined above, as compared to within the thermal range, might reveal critical mechanisms acting at these limits. In order to systematically identify such limit-sensitive features, we first analyzed cellular processes within the thermal range. We conducted this analysis initially in C. elegans embryos, but then also studied embryos of C. briggsae, which has been estimated to have diverged from C. elegans 18–100 million years ago (Stein et al., 2003; Cutter, 2008), thus probing evolutionary conservation of putative limit-sensitive features. Using temperature-controlled time-lapse DIC (Differential Interference Contrast) microscopy and semi-automated quantifications of the resulting movies with in-house scripts (Figure 1C–J, Figure 1—figure supplement 1, ‘Materials and methods’, and Source code 1), we measured 35 cellular features that describe the main events of the first cell cycle of C. elegans embryos (Figure 1C–F). In brief, after fertilization, the female pronucleus migrates towards the male pronucleus (Figure 1C). After their meeting, the pronuclei move to the embryo center whilst undergoing a 90°C rotation (Figure 1D). The nuclear envelopes then break down, followed by assembly of the mitotic spindle, which moves slightly to the posterior during the remainder of mitosis whilst oscillating perpendicular to the anterior–posterior axis (Figure 1E). This results in the asymmetric division of the one-cell stage embryo into a larger anterior cell and a smaller posterior one (Figure 1F). Our analysis established that the vast majority of the monitored features were temperature-dependent within the thermal range (Figure 1—source data 1). Interestingly, some features, including the fraction of time spent in mitosis (Figure 2B) and cell division asymmetry (Figure 2C), exhibited a temperature-independent behavior, suggesting that temperature-compensation mechanisms are also at play.

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We then were in a position to identify cellular features that might operate differently beyond the thermal limits compared to within the thermal range. We found that although some features exhibited the same thermal response as within the thermal range, others responded differently, suggesting that they were sensitive to the thermal limits (Figure 1—source data 1). Thus, the duration of mitosis, which decreased monotonically with increasing temperatures within the thermal range, plateaued beyond both lower and upper thermal limits in C. elegans (Figure 2A). Moreover, although C. briggsae can develop at warmer temperatures than C. elegans (Figure 1A–B) (Prasad et al., 2011), we found that cell cycle duration was not faster in C. briggsae than in C. elegans at any temperature (Figure 3A, compare with Figure 2A). Interestingly, cell cycle duration within the thermal range was well described by Arrhenius kinetics in C. elegans (92% of explained variance; ‘Materials and methods’) (Arrhenius, 1915). In C. briggsae, by contrast, the data beyond 25°C reduced the explained variance from 86% to 39%, suggesting that cell cycle duration plateaued already below the upper thermal limit in this species, underscoring the fact that mitosis duration is a limit-sensitive feature.

Figure 3

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We also observed that the asymmetry of the first cell division in C. elegans, which was constant within the thermal range, decreased below 12°C (F-test p = 0.0005) and increased above 25°C (F-test p < 10⁻⁷) (Figure 2C; see ‘Materials and methods’ for statistics). In C. briggsae, the asymmetry of the first cell division also increased beyond the upper thermal limit, at both 28°C and 29°C (F-test p-value < 10⁻¹⁰) (Figure 3C). However, a reciprocal decrease was not observed at the lower thermal limit in this species, perhaps because spindle pole oscillations are weaker in C. briggsae than in C. elegans (Riche et al., 2013) (compare panel D in Figures 2, 3), potentially limiting the dynamic range over which asymmetry can be tuned.

Our analysis also revealed interesting alterations in embryo geometry at the upper and at the lower thermal limits. Thus, embryo size was larger at the lower end of the thermal range (i.e., 12°C for C. elegans, Figure 2E; 14°C for C. briggsae, Figure 3E), and tended to decrease with increasing temperature within the thermal range. This is in line with the ‘temperature-size rule’ observed in the vast majority of ectotherms (Atkinson, 1994; Forster et al., 2012), and in agreement with previously reported data for C. elegans at 10°C vs 20°C (Van Voorhies, 1996). Strikingly, below the lower thermal limit, embryo size was actually significantly reduced in both C. elegans and C. briggsae (Figures 2E, 3E; F-test p < 10⁻⁷ and p = 0.001, respectively). Such a reversal of the temperature size rule below the lower thermal limit has also been reported in protists and in Drosophila (Karan et al., 1998; Atkinson et al., 2003). These observations are compatible with the MASROS hypothesis, which posits that such a size decrease below the lower thermal limit may reflect cold-inhibited mitochondrial function (Atkinson et al., 2006).

Beyond the upper thermal limit, we observed a plateau in the size of both C. elegans and C. briggsae embryos (Figures 2E–3E). Interestingly, however, we observed that embryos in both species were more elongated beyond the upper thermal limit (Figures 2F–3F; F-test p = 0.0004 and F-test p < 10⁻¹⁰, respectively). Such an elongation results in an increase of the surface area, thus potentially augmenting its availability for oxygen diffusion (Figure 2—figure supplement 1). Overall, these results reveal that changes in cell size and shape are signature hallmarks of the thermal limits.

Do the observed changes in embryo size below the lower thermal limit and of shape above the upper thermal limit reflect an adaptation to reduced aerobic metabolism at those temperatures? We set out to explore this possibility by determining the extent of respiration at different temperatures in wild-type C. elegans embryos. As shown in Figure 4A, we found that respiration increased exponentially within the thermal range, as predicted by Arrhenius-like kinetics (Arrhenius, 1915). Strikingly in addition, this analysis uncovered that respiration departed from Arrhenius-like kinetics both below the lower thermal limit (F-test p-value < 10⁻⁴) and above the upper thermal limit (F-test p-value < 10⁻¹⁰), in support of reduced respiration at those temperatures (Figure 4A). Although we do not know whether the observed relative reduction in aerobic capacity beyond both thermal limits as compared to within the thermal range contributes to increased lethality at those limits, our results show a clear correlation between these features.

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One possibility to interpret these data is that the energetic needs of the embryo are not satisfied beyond the thermal limits due to insufficient aerobic metabolism. Another possibility is that these needs are actually fulfilled to some extent despite reduced respiration, either because other metabolic routes are used to a larger relative extent or because embryos are metabolically depressed at the thermal limits and thus require less energy altogether. We reasoned that if aerobic metabolism became insufficient beyond the thermal limits, then further compromising mitochondrial activity should have more of an impact at the thermal limits than within the thermal range. By contrast, if energetic needs could be fulfilled at the least to some extent despite reduced respiration beyond the thermal limits, then further compromising mitochondrial activity should have less of an impact at the thermal limits than within the thermal range. Therefore, to distinguish between these two possibilities, we depleted three components of the mitochondrial respiratory chain using RNAi: the beta-subunit of ATP synthase ATP-2 (Tsang et al., 2001), a complex V component, the subunit of the mitochondrial complex I NUO-1 (Tsang et al., 2001), and the component of the mitochondrial complex III CYC-1 (Dillin et al., 2002). We ascertained that embryonic respiration was reduced in cyc-1(RNAi) embryos, reaching on average 56% ± 13% of the wild-type levels under the assay conditions (t-test p-value < 10⁻³; see ‘Materials and methods’). Since ATP-2 and NUO-1 are part of complex V and I, respectively, respiration may still occur upon their depletion, even if the mitochondrial respiratory chain is compromised (Braeckman et al., 2009), so that respiration measurements may not have been telling in these cases. Importantly, we found that all three RNAi conditions were embryonic lethal to some extent (Figure 4B–D), probably owing to decreased energy production through respiration, although we cannot exclude that the observed lethality stems from changes in pH or increased reactive oxygen species. Importantly, in addition, this analysis uncovered that embryonic lethality was reduced towards the lower thermal limit as compared to within the thermal range in all three cases, as well as towards the upper thermal limit in both cyc-1(RNAi) and nuo-1(RNAi) (Figure 4B–D). These results offer strong experimental support to the notion that the capacity of the mitochondrial respiratory chain is restricted beyond both thermal limits, and raise the possibility that other metabolic routes are used to a larger relative extent at those temperatures in the face of reduced respiration.

Following up on this result, we set out to test whether the changes in size or shape observed beyond the thermal limits in the wild-type reflect an adaptation response to restricted aerobic capacity. We reasoned that if this were the case, then such changes should occur already within the thermal range of embryos in which components of the mitochondrial respiratory chain are compromised. Interestingly, we found that whereas embryo size was not significantly affected upon RNAi-mediated depletion of atp-2 (Figure 4E), these embryos were more elongated at both 12°C and 16°C (Figure 4F, U-test p(12°C) = 0.0034, p(16°C) = 0.0039). In nuo-1(RNAi), embryo size was significantly reduced at both temperatures (U-test p(12°C) = 0.02, U-test p(16°C) < 10⁻³, Figure 4E), whereas a similar response was observed in cyc-1(RNAi) embryos at 12°C (U-test p(12°C) < 10⁻³, Figure 4E). While it remains to be investigated why the cellular consequences of depleting these three components differ to some extent, remarkably, they share the net result of increasing surface to volume ratio within the thermal range, thus mimicking the situation in the wild-type beyond the thermal limits. Therefore, these results strongly support the notion that the uncovered cellular hallmarks observed at the thermal limits of wild-type embryos reflect restricted aerobic capacity.

In this work, we assessed the thermal response of cellular features during the first cell cycle of C. elegans and C. briggsae embryos. Interestingly, we uncovered that the thermal response of select cellular features changed precisely at the limit temperatures defined by embryonic viability tests (see Figure 1A–B). While we do not know whether these cellular hallmarks are responsible for the observed increased lethality beyond the thermal limits, we note that a mere 10% decrease in embryonic viability is associated with readily observable cellular changes during the first cell cycle. Importantly, experiments in which mitochondrial respiration is compromised revealed that aerobic metabolism plays a smaller relative role towards the thermal limits than within the thermal range, raising the possibility that other metabolic routes are favored to produce energy. Furthermore, these experiments uncover that the changes in size and shape observed beyond the thermal limits in the wild-type can be recapitulated within the thermal range by impairing aerobic metabolism, strongly supporting the view that these changes arise in response to restricted aerobic metabolism. Together, our work provides critical experimental evidence supporting the notion that restricted aerobic metabolism is a general principle characterizing thermal limits in multicellular organisms in water and on land. Other elements contribute to setting boundary conditions within which a thermal range can be envisaged. Thus, cold-induced increase in unsaturated fatty acids in cyanobacteria, Arabidopsis (Hazel, 1995) and C. elegans contributes to setting the lower thermal limit (Svensk et al., 2013), although it only accounts for 16% of the observed difference in cold tolerance at 10°C vs 25°C in C. elegans (Murray et al., 2007). Moreover, warm-induced increase in post-translational glycosylation also contributes to setting the upper thermal limit in Drosophila melanogaster, Danio rerio and C. elegans (Radermacher et al., 2014). In addition, defects in synaptonemal complex assembly (Bilgir et al., 2013) and in sperm (Harvey and Viney, 2007) contribute to setting the upper organismal limit in C. elegans. The restricted aerobic metabolism experimentally uncovered here is another important piece of the puzzle that contributes to defining both thermal limits.

Another study investigating the temperature dependence of cell division processes in C. elegans and C. briggsae was published whilst the present manuscript was under consideration (Begasse et al., 2015).

All the strains were maintained according to standard procedures (Brenner, 1974) in incubators set at the temperature at which embryos would then be imaged. Note, however, that since C. elegans was not fully viable above 25°C (see Figure 1A), worms were kept at the imaging temperature for only 6–24 hr prior to imaging. Embryos were dissected in 1× M9 medium tempered at the culture temperature, mounted on slides, placed under a coverslip and imaged using time-lapse DIC microscopy. Considering the crowded compressive environment of the uterus in the intact animal, and considering furthermore that the same mounting procedure was followed for all specimens at all temperatures, we surmise that the observed alterations in thermal response of embryo size and shape at given temperatures are not due to the mounting procedure. However, we cannot totally exclude that the observed changes in embryo size and shape may result from differential resilience to pressure of the cover slip used for imaging at the various temperatures.

The recording rate was adjusted as follows (we also mention the number n of embryos that were imaged from each condition):

C. elegans (N2): 10°C (9 s, n = 9), 12°C (8 s, n = 12), 14°C (6 s, n = 11), 16°C (6 s, n = 9), 20°C (5 s, n = 20), 24°C (4 s, n = 19), 25°C (4 s, n = 15), 26°C (4 s, n = 16), 27°C (2 s, n = 10).

C. briggsae (AF16): 12°C (8 s, n = 8), 14°C (7 s, n = 9), 16°C (6 s, n = 16), 20°C (4.5 s, n = 21), 25°C (3 s, n = 14), 28°C (2 s, n = 16), 29°C (1.5 s, n = 15).

atp-2(RNAi): 12°C (n = 14), 16°C (n = 16). In this condition, only few embryos were imaged over the whole first cell cycle (n(12°C) = 3, n(16°C) = 6).

cyc-1(RNAi): 12°C (n = 15), 16°C (n = 14). In this condition, only few embryos were imaged over the whole first cell cycle (n(12°C) = 2, n(16°C) = 4).

nuo-1(RNAi): 12°C (n = 8), 16°C (n = 15). In this condition, only few embryos were imaged over the whole first cell cycle (n(12°C) = 1, n(16°C) = 4).

While imaging, the temperature was regulated by an air-blower that cooled/heated both sample and objective, and which was feedback-controlled by a thermocouple (LABFACILITY ZO-PFA-K-1) inserted next to the embryo (Figure 1—figure supplement 1A). We also ensured that the device was well calibrated in the experimental thermal range [8, 32]°C (Figure 1—figure supplement 1B).

Prior to imaging, we made sure that embryos did not touch each other in order to facilitate segmentation. All DIC recordings were analyzed in a semi-automated fashion using Matlab. The analysis pipeline consisted of the following steps:

1. We automatically segmented the eggshell contour using ASSET (Blanchoud et al., 2010). All the measured positions were then automatically corrected at each time frame by the centroid of the egg in the same frame. This was an important step because the air-blow from the temperature controller displaced the embryos during the recordings.

2. We detected by careful visual inspection the onset of pseudo-cleavage (deepest furrow), mitotic entry (nuclear envelope breakdown) and cytokinesis (start of membrane invagination). Cytokinesis onset defined time 0; hence, all the times in our analysis were negative.

3. We automatically detected the migrating pronuclei using a custom segmentation algorithm based on (Hamahashi et al., 2005). The exact timing of pronuclear meeting was then corrected by manual inspection. The speed of the female pronucleus was computed using its movement along the x-axis.

4. After pronuclear meeting, the spindle poles were manually tracked until completion of centration-rotation. The angular and spatial trajectories were then fitted with the following model:

   $x=\frac{A·{\left|t\right|}^n}{K^n+{\left|t\right|}^n}+cte,$

   where x is the mid-position of the spindle poles or the angle they make with respect to the A-P axis. K represents the time at which centration (resp. rotation) is midway to completion. A relates to the initial position (resp. angle). cte is an offset and n relates to the steepness of the profile. The velocity can then be computed using ν = dx/dt.

5. After mitotic entry, the spindle poles were manually tracked until oscillations had dampened out. The position along the x-axis was used to compute spindle pole elongation speed towards the anterior and posterior poles, while positions along the y-axis monitored spindle oscillations. In order to retrieve the oscillation frequency, amplitude and duration, we first identified the dominant angular frequency ω by fast Fourier transform. We then applied a low-pass filter with threshold 3 2π ω, to remove the noise, followed by a high-pass filter to remove any drift of the oscillations (with threshold 0.5 2π ω). Note that these filters did not change the dominant frequency of the signal, but were useful to better detect the peaks and measure the amplitude of the oscillations. Since the oscillations envelope was not always well fit by a sinusoidal function, we determined the duration of the oscillations by manual inspection of the oscillations profile (after filtering).

6. In order to determine embryo size, the embryo was manually contoured just before cytokinesis onset in order to extract its area.

7. The area of each daughter cell was manually contoured at time $t\cong 0.25·t_{PM}$, where t_PM is the duration of the first cell cycle, defined as the time from pronuclear meeting to cytokinesis onset.

In order to perform progeny tests, five to ten young adults were placed on a plate with a 5 µl drop of OP50 and left to lay eggs at the temperature of interest (at least in triplicates). After 2–4 hr, we removed all the adults and counted the number of embryos on the plate (generally between 30 and 100 embryos, except at extreme temperatures beyond the thermal limits where few or no embryos were laid). After a few days at the temperature of interest, we assessed the number of larvae that had hatched.

Unsynchronized embryos were obtained by bleaching adult wild-type C. elegans worms. The number of embryos per μl was then assessed by optical density (OD_{595 nm}). We measured the respiration of wild-type C. elegans embryos from 9°C to 28°C using the Oroboros Oxygraph-2k, following the manufacturer's instructions. Prior to the experiment, a calibration was performed with 1× M9 buffer at 20°C in each chamber. We then dispensed 100,000 embryos in four chambers containing M9 buffer (i.e., 25,000 embryos/chamber): two chambers were used to go down in temperature from 20°C to 9°C, and two chambers were used to go up from 20°C to 28°C. The data from each chamber was normalized to its respiration rate at 20°C. We also repeated the same experiment using 35,000 embryos per chamber (i.e., 140,000 embryos in total).

In order to measure respiration at 20°C upon CYC-1 depletion, we dispensed 2000 wild-type embryos/plate on 16 large Petri dishes with OP50 bacteria as food source. After 28 hr at 20°C, all the resulting larvae were collected by centrifugation and washed three times to remove the OP50. Half of the collected larvae was re-suspended and distributed in 16 large OP50 plates, the other half in 16 large cyc-1(RNAi) IPTG feeding plates (prepared the day before and left at room temperature). After 44 hr at 20°C, embryos were collected in both control and cyc-1(RNAi) conditions by bleaching adult worms. Respiration was measured in two chambers as follows: after calibrating the machine with 1× M9 buffer at 20°C, 35,000 wild-type embryos were dispensed in each chamber and their respiration measured at that temperature. The chamber was then washed, and we dispensed 35,000 embryos from the cyc-1(RNAi) condition and likewise measured their respiration. For each chamber, we compared the respiration of cyc-1(RNAi) embryos over wild-type. The experiment was repeated once using 35,000 embryos in the four chambers. Note that the lethality incurred following cyc-1(RNAi) in these experiments was less pronounced than that reported in Figure 4C, probably owing to the need to scale up to assess respiration in a large number of embryos, such that the reported diminution of respiration is likely an underestimate of the actual impact.

The C. elegans ORFeome RNAi library was a gift from Jean-François Rual and Marc Vidal, Harvard Medical School, Boston, USA (Rual et al., 2004). Bacterial RNAi feeding strains were prepared as described (Kamath et al., 2001). RNAi was performed by feeding early L3 larvae at temperature T with bacteria expressing dsRNA against the target gene for N hours at temperature T. The required feeding durations at each temperature were determined by fitting the duration of embryogenesis at 16°C (29 hr), 20°C (18 hr) and 25°C (14 hr) (Epstein and Shakes, 1995) with the following equation (Gillooly et al., 2002):

where T₀ = 273 K and T_c is the temperature in °C, yielding α = 0.1, in agreement with (Gillooly et al., 2002) (Figure 4—figure supplement 1). We therefore used this value of α to fit the reported feeding durations from the literature (∼72 hr at 15°C [Ahringer, 2006], ∼47 hr at 20°C [Afshar et al., 2005] and ∼38 hr at 22°C [Ahringer, 2006]), yielding the following feeding durations: 12°C (90 hr), 16°C (65 hr), 20°C (44 hr), 24°C (31 hr).

In order to verify that the results we uncovered in Figure 4B–D did not result from a general temperature-dependency in the effectiveness of the RNAi response, we also performed RNAi directed against AIR-1, a serine/threonine kinase required for spindle assembly (Hannak et al., 2001), a process not known to be related to metabolic status (Figure 4—figure supplement 2).

Thermal response within the thermal range was assessed by Pearson correlation. A feature was considered to be temperature-dependent within the thermal range if its Pearson p-value was below 0.0014 (which assumes a Bonferroni correction for multiple-testing 35 features, i.e., 0.05/35 = 0.0014; c.f. Figure 1—source data 1).

Beyond the thermal range (TR), we assessed if there was a significant change in the thermal response of the features by F-test (nested-model analysis). For temperature-independent features, our first model was a simple regression y = mean (feature within TR). This model was nested within our second model y = mean (feature within TR) + β(T − 25) (T ≥ 25°C) which accounted for the potential change in the feature's thermal response beyond 25°C (a similar model was implemented for C. elegans lower thermal limit, as well as for C. briggsae at its respective thermal limits). We then determined if the second model (which has more parameters and therefore always fits the data better) significantly improved the fit of the data using an F-test. The F statistic is given by:

where RSS_i is the residual sum of squares of model i, p_i the number of parameters of model i and n the number of data points. Under the null hypothesis, F follows an F-distribution with (p₂ − p₁; n − p₂) degrees of freedom.

For temperature-dependent features, the first model was an exponential fit of the data within the thermal range: for example, for C. elegans, $y=y_0·\exp \left(\alpha ·T\left(T\in \left[12°,25°\right]\right)\right)$. The nested model included a linear regression for the data above 25°C (or similar for C. elegans lower thermal limit, as well as for C. briggsae at its respective thermal limits):

In some temperature-dependent cases, the data within the thermal range was better fitted by linear regression (the exponential and linear model having the same number of parameters, the model with smallest sum of residuals was considered to be the best). In those cases, we used the following first model: $y=y_0+\alpha ·T\left(T\in \left[12°,25°\right]\right)$.

And the nested model: $y=y_0+\alpha ·T\left(T\in \left[12°,25°\right]\right)+\beta \left(T-25\right)\left(T\ge 25°C\right)$.

In all cases (temperature-dependent or temperature-independent), the thermal response of a feature was considered to change beyond the upper thermal limit if the F-test p-value was below 0.0014 (threshold 0.05 corrected for multiple testing 35 features, i.e., 0.05/35 = 0.0014; c.f. Figure 1—source data 1). If the p-value was above 0.0014, the feature's thermal response above the upper thermal limit was tagged as unchanged in Figure 1—source data 1.

We also performed Mann Whitney U-tests to test if two distributions were different (Figure 4E–F).

Cell cycle durations within the thermal range were fitted to the following Arrhenius-like model (Arrhenius, 1915), to determine if the pace of cell division increased exponentially with temperature, as would be expected by Arrhenius kinetics:

where k_B is the Boltzmann constant, T is the temperature (in [K]), E is the activation energy describing the thermal dependence (in [eV]) and A is a normalization constant.

The funder had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Some strains were provided by the CGC, which is funded by NIH Office of Research Infrastructure Programs (P40 OD010440). We are very grateful to Alessandro De Simone for co-developing the pronuclei detection algorithm, to Johan Auwerx and Norman Moullan in his lab for guidance and technical help with the respiration experiments, as well as to Alexandra Bezler, Simon Blanchoud, Marie Delattre, Virginie Hamel, Andrew Hirst, Laurent Mouchiroud, Laurent Keller and Luc Pellerin for careful reading of the manuscript and useful comments. This work was supported by a SystemsX.ch Transition Postdoc Fellowship to AN (SXFSI0_141995). The authors declare no conflicts of interest.

© 2015, Neves et al.

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